Table of contents

This volume of Journal of Physics: Conference Series contains the selected papers presented at the 2nd International Seminar on Computer Science and Engineering Technology (SCSET 2020).

The 2nd International Seminar on Computer Science and Engineering Technology was successfully held in Shanghai, China during Oct. 30-31, 2020. The SCSET2020 had received great attention and response from various research institutes, university teachers and students, and scholars. There were more than 70 participants, and many author participated in the oral report. Each topic report lasted about 20 minutes, including 5 minutes for mutual answers. Participants and reporters had in-depth exchanges and extensive discussions.

List of Sponsors, Conference Chair, Program Committee Chairs and Technological Committees are available in this pdf.

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

• Type of peer review: Single-blind / Double-blind / Triple-blind / Open / Other (please describe)

SCSET2020 adopts double-blind review. 1) The first step is the preliminary examination. We would reject the submissions whose topics did not meet the publication requirements. Besides, submissions with suitable topics would be further checked for their similarity through the Turnitin system. Accordingly, the manuscript would be rejected also if the repetition rate does not meet the standard. 2) The second step is double-blind review. The manuscripts will be assigned to the eligible reviewers in own review system. Meanwhile, the reviewer cannot see the authors' names and affiliation information during reviewing period, and also, the author cannot see the reviewer's information when viewing the review results. Reviewers will rate the article from the following aspects (1 is the lowest, and 7 is the highest) a) Appropriateness to the Conference b) Originality c) Technical Strength d) Presentation At the same time, the reviewer will give the comments and review results: rejection, modification, or acceptance.

• Conference submission management system: http://www.scset.org/submission

• Number of submissions received: 348

• Number of submissions sent for review: 336

• Number of submissions accepted: 204

• Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 58.6%

• Average number of reviews per paper: 2

• Total number of reviewers involved: 95

• Any additional info on review process:

• Contact person for queries: Mr. Kang Li, scset@foxmail.com

Taking the advantage of fuzzy systems, a class of T-S fuzzy models used to describe nonlinear systems. Firstly, by designing a memory state feedback controller, we draw the conclude of robust stability and the conditions of passive control. Secondly, using Lyapunov stability and linear matrix inequality technology in MATLAB, we can utilize the gain matrix about the controller of the memory state feedback. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

This paper mainly analyzes the characteristics of software defect prediction from the perspective of machine learning, and proposes a semi-supervised software defect prediction method based on sampling and integration for the problem of class imbalance in software defect data and the incomplete classification of data sets. SISDP). SISDP firstly constructs a robust KNN marking model by taking a balanced sample of samples to mark a batch of unmarked data, and then iteratively adds the newly marked data to the original data set for the next marking model. , iterate until the data is marked. For the marked data set, the hybrid sampling algorithm is used to obtain the training set, and the integrated classification model composed of the multi-classification algorithm is classified and trained. SISDP not only reduces the interference of a few classes on the marking process, but also improves the generalization ability of the defect prediction model.

Enrichment of Pesticide Organic pollutants in Surface Water by solid Phase extraction, Analysis and characterization by Gas Chromatography-Mass Spectrometry and Total screening Software, semi-quantitative, At the same time, the semi-quantitative results were verified by SIM mode of gas chromatography-mass spectrometry. The results show that the recovery rate of acids, alcohols and ketones in water meets the requirements of monitoring index. The verification results show that, This screening method is based on the absence of external standard materials and targets. Can be used for early warning monitoring of most potential pesticide organic pollutants in water.

With the IoT technology as the entry point, this paper designs the general plan for the IoT-based forest fire warning & monitoring system of Jizhou District, through the analysis of the application of IoT technology in the forest fire prevention of Tianjin; builds the workflow of the IoT-based forest fire warning system; and put forward the suggestions and countermeasures for the development of forest fire warning system in Jizhou District, thus providing theoretical basis and realistic foundation for improving the efficiency of Tianjin forest disaster prevention and mitigation.

China's Tibetan ghee sculpture art is the first batch of works of art approved by the state council to be included in the national intangible cultural heritage list. This paper mainly studies the origin, digitalization and intelligent protection of the Tibetan butter sculpture art in China, and also explores and attempts to effectively protect the intangible cultural heritage with modern science and technology. We hope that more people will understand, inherit and protect the fine traditional culture of the Chinese nation, and that our cultural confidence will continue to advance to new levels.

Type 2 diabetes is the most common type of diabetes. The cornerstone of type 2 diabetes treatment is healthy lifestyle. This paper proposes a machine learning model for quantifying the effect of lifestyle interventions for patients. In the proposed incremental intervention model, the original physical indicators and the lifestyle interventions were taken as input vectors separately and transformed through different nonlinear functions. We evaluated our method with the dataset of 12,318 patients from a national funding project and compared with MLP and SVR. The experimental results (R²=0.85, RMSE= 0.51, MAE=0.35) indicated that the model outperformed those prediction models. Besides, the machine learning based method is cost-effective and time-saving. The proposed method provides new insights into prevention and treatment of chronic diseases.

The data of Internet of Vehicles (IoV) can be used to evaluate the driving safety risk of auto insurance policyholder and provide technical means for Usage Based Insurance (UBI). There are many types of IoV data, such as continuous or ordinal, categorical, binary etc., which contain highly sparse and dimensional features after One-Hot processing, thus they learning the interaction between critical features and training predictive model difficult. Furthermore, some of the available data have been desensitized, so it is impossible to perform feature engineering based on experience. We propose an end-to-end deep learning framework named Deep Attentional Factorization Machine (DeepAFM), which combines the power of attentional factorization machine with deep learning for feature learning in a new neural network architecture. Compared with existing deep learning models, our approach can learn the weighted interactions between various features effectively by introducing the structure of feature fields without feature engineering. Experimental results showed that our model yields excellent results in real-world data.

The officers of Dekalb Police Department were aware of the high crime rate and they're considering whether set up a new office or relocate the existing department to shorten the distance, also, ensure to reach the crime scene in super speedy. To select a more reasonable location, an essential assumption is that the current office will no longer associated with. Besides the existed office, geo-policing is not a necessary factor neither. Therefore, the police officers will work from the new location that we inferred and answer the incoming calls there. First thing first is to model it as a single facility location problem, and then, calculate by the Minisum model with rectangular distances as well as the Minimax model with tchebychev distances.

Cost-effective development of proved oil resources is the goal of oil and gas field development workers. One of the ways to achieve this is to make the reservoir development in an optimal state based on the existing production conditions, which is also one of the core contents of intelligent oilfield. This paper proposes a new production optimization control method, which aims to maximize the net present value of reservoir development and production. By solving the mathematical model of development and production, the input and output control parameters of the reservoir are optimized in real time to obtain the optimal production plan. The conventional maximum principle method requires two time series solution calculations. In this paper, the coefficient matrix of the full implicit simulator is used to directly obtain the required adjoint equations. The efficient combination of simulation calculation and gradient solution of discrete maximum principle greatly improves the solution efficiency of the model and saves the calculation time. The reservoir examples are analyzed through theoretical research. The results show that the optimal production scheme is in line with the actual situation of the oilfield, which provides theoretical and technical support for the intelligent oilfield system.

With the gradual advancement of electric energy substitution, the power consumption of agricultural electromechanical drainage and irrigation pumping station increases rapidly. It is urgent to update and transform the pumping station. Aiming at the substitution scenario of electric energy for agricultural irrigation and drainage, the technology of internet communications are combined in the application. It focuses on the design of two systems: monitoring and warning of operation conditions, and charging management of pumping stations. An electrical control cabinet integrated with power supply and control is designed by using PLC control system. This control cabinet is installed in the pump house of irrigation and drainage area. Some control terminals can be connected to it, and each terminal can be connected with a load that can work or shut down independently. These two systems store and analyse the operation conditions and electricity charge information. They also establish database and exchange data with external power supply companies and water resources management bureaus through internet communications. They are used to realize intelligent control and management. It is of great significance to establish a perfect integrated power supply control system for agricultural irrigation and drainage.

In order to research the influence of 80-mesh traditional Chinese medicine particle characteristics and particle stack thickness on percolation performance, wire screen was used to carry out filtration by the vibratory action of oscillator, screen No. and screen pore size were recorded and weight of screen residue was measured, so as to calculate average distribution density of particles, distribution function of particle size, form factor and specific surface area of particles. Percolation pressure drop was utilized as the index to evaluate percolation performance. Ethanol solution at 20°C with volumetric concentration of 47% was selected as percolation solution to measure and calculate the percolation pressure drop when ethanol solution flowed through 100mm, 150mm, 180mm, 250mm and 300mm 80-mesh particle layer. The results showed that percolation pressure drop is proportional to particle stack thickness, and it is high relatively due to the small size of 80-mesh particle, which shall result in high energy consumption of percolation system.

To solve the shortcomings of the conventional assessment methods for crowd evacuation stability, such as over-reliance on the experience of the judges, obvious subjectivity and time-space limitations, this paper proposes an assessment model for judgment on the stability situation of crowd evacuation. Furthermore, the scenarios of large-scale crowd evacuation is diverse, and the compositions of crowd, the causes of crowd trampling are different. So it is particularly important to analyze specific problems for different scenarios. However, different data acquisition and poor real-time performance are main practical problems of judgment on the stability situation of large-scale crowd evacuation. With regard to shortcomings and problems above, the assessment model proposed in this paper uses big data technology to figure out a real-time crowd distribution thermodynamic map and obtain the crowd distribution density data. According to the criterion of crowd stability proposed by the Green Guide in Britain, the assessment model is further constructed to judge the stability situation of large-scale crowd evacuation in real-time.

The classification of patients is very important for accurately determining the patient's disease and subsequent drug use. More and more clinical data provide a clue for the classification of various diseases. We use related software to generate simulation data based on ICD10 and propose a specific algorithm to classify patients, and find patients belonging to other categories in the classified patient group, which provides a theoretical basis for the improvement of various classification algorithms for diseases.

Malodorous gas sensor array system for the olfaction robot is developed with four sensors including two semiconductor metal oxide sensors, a electrochemical sensor and a photoionization detector (PID). The system structure and experiments analysis are introduced in this paper. Result of experiments show that the steady system can keep ±0.03V fluctuation limited from 0 to 5 V after it stabilized and the maximum difference of response less than 0.02V. It means that the developed system can be satisfied for the olfaction application of robots in malodorous environment.

With the development of e-commerce, it provides users with many choices. But how to quickly and accurately recommend goods to users is an important topic in this field. Matrix factorization recommendation model based on scoring data is widely used, but data sparsity affects the recommendation quality of the model. In the paper, a product recommendation algorithm based on deep interest network is proposed. First, the user's purchased goods and the user's search are embedded coded, and the sparse features are transformed into low-dimensional dense features.Then, the feature vectors of the purchased goods and the search text vectors are joined together to input the deep interest network as the feature to predict the user's interest.Finally, the effectiveness of the model is validated by using record data. The validity of the model is verified by comparing with other models.

Aiming at the problem that the feature extraction of Chinese title data is insufficient in the process of named entity recognition and the marking data is difficult to obtain, this paper presents a CNN-BiLSTM-CRF model. The model trains large-scale corpus to generate word vectors with semantic information and trains the character vectors in words through CNN to generate character vectors containing character features, the word vector and the character vectors are merged as the input of BiLSTM network. Through the BiLSTM network, the front and back texts features are fully extracted, and CRF is used to restrict the relevance of tags. In addition, this paper proposes an algorithm based on active learning. This algorithm uses the proposed model construction committee to select the samples with large amount of information to mark, which effectively reduces the amount of data annotation.

The problem encountered by military manufacturing enterprises in the preparation of production plans is mainly attributable to the failure to optimize supply and demand resources in the supply chain. The article innovatively employs the advanced planning system based on linear programming model to solve the problem. The problem is first of all described mathematically; then its linear programming model is constructed, and the latter's APS system designed; at last, the model is solved and checked. Upon the verification, the model is proven helpful for enterprises to work out production plans quickly and efficiently, and carry out what-if analysis. While winning the time advantage for military manufacturing enterprises in the market competition, it also enhances their operating management efficiency.

In 2009, IBM put forward the development policy of building "smart city" before building "smart earth". In response to this policy, the National Bureau of Surveying and Mapping issued "The Notification on the Development of Smart City Spatiotemporal Information Cloud Platform", which formally took the construction spatiotemporal information cloud platform of smart city as a pilot project. In this paper, the OSGi (Open Service Gateway Initiative) technology is used as the framework. Developing component on demand is realized by the SOA architecture and OSGi technology, which improves the efficiency of developing software, shortens the cycle of developing software and saves labor costs. Resource access is achieved through RESTful services, and distributed coordination services are implemented through Zookeeper.

Visual target tracking is an important topic in the field of vision research. Its main task is to automatically process and analyze the input video information by computer, so as to obtain the position and key motion information of the target in the input video sequence, and to facilitate the subsequent research and analysis of the track and behavior of the tracking target. At present, researchers in the field of visual target tracking have proposed a series of excellent algorithms and frameworks. However, in view of the problems of deformation, occlusion, illumination change and random motion in the process of target tracking, it is still a great challenge to ensure the real-time, accuracy and robustness of tracking algorithms. In recent years, with the excellent performance of depth neural network in many tasks, the fusion of depth features based on relevant filtering algorithms to achieve target tracking tasks has become a hot research topic. In this paper, an improved target tracking algorithm is proposed based on the framework of classical target tracking methods: (1) Integrating deeper ResNet-101 deep convolution neural network model to detect target features more accurately. (2) Improve the model training method to save the network training cost. Finally, the performance of the proposed tracking algorithm is tested on the OTB target tracking standard dataset, and compared with other mainstream algorithms. The results show that the improved method proposed in this paper can effectively improve the tracking effectiveness and robustness.

In this paper, the defects of the existing models in virtual reality, such as the excessively long pretreatment time, time consuming in update operations and so on, when dealing with the large-scale automatic information association technology are analyzed. And a kind of construction method for the hierarchical detail model of energy environment (hereinafter referred to as CHDM for short) based on the integration of automatic information association technology is put forward. In this method, the information is aggregated in virtual reality to establish the hierarchical detail model of energy environment. Then the geometric parameters and form features are integrated to calculate the hierarchical details of each volume element. The topology connection relationship of the hierarchical detail model of energy environment is used to form a "Hierarchical detail model of energy environment", which is merged and simplified in virtual reality. The experimental results show that for the automatic association of information with a patch complexity of about 10M can improve the average rate of model establishment about 3 times on the premise of guaranteeing certain construction quality on the ordinary PC. And the pretreatment time is controlled within 7min.

In the multi-joint robot water polo competition, it often occurs that the robot fish glances off the ball when pushing it due to the water waves generated by the fish swimming and the influence of the opponent fish's attack behavior on the target ball. In order to improve the success rate of the robot fish hitting the ball, this paper proposes a long-distance posture adjustment strategy and double-fish alternative attack strategy. The long-distance posture adjustment strategy is based on the detailed division of the relative positions of the fish, the ball and the goal. The probability of the fish, the ball and the goal being in a three-point line is improved by setting the distance through which the fish body reaches the preset hitting point and the posture adjustment strategy. Besides, the double-fish alternative attack strategy is proposed on the basis of this ball-pushing strategy. The cooperation between the two fishes is strengthened by developing another fish's returning strategy during the opponent fish hitting the ball, thereby improving the attack efficiency. The experimental results show that the underwater robot fish can avoid the close touch-ball and can attack the ball into the goal more quickly and accurately.

In order to solve the problem that the image information is difficult to handle due to the swing of the snake robot's head during its serpentine locomotion, this paper improves the control function of the general winding gait for the orthogonal joint-connected snake-like robot, and the useful image information is obtained by reducing the swing of the camera-mounted snake's head based on the improved function. Combining the Sigmoid function with the general function to control the rotation of the yaw joints and applying the Gaussian function to the pitch joints to lift the snake head off the ground, this new control function presented in this paper not only enables the joints to rotate smoothly, but also decreases the swing range of the snake head. Additionally, it can also fasten the robot's movement. Experiments based on MATLAB and GAZEBO platform demonstrate the superiority and effectiveness of the improved winding gait.

In this paper, the characteristics of software defect prediction are analyzed from the perspective of machine learning. To solve the problem of some redundant or uncorrelated features in defect data sets, a stable feature selection method based on relevancy and redundancy (RRSFS) is proposed. RRSFS combines the redundancy between features and the correlation between features and classes to select the optimal subset. RRSFS not only reduces the cost of data operation in the prediction model, but also enhances the stability of feature selection algorithm.

The existing Chinese event extraction methods are mostly one-stage methods. Even if there are two-stage methods, the correlation between the stages is not high, the extracted event trigger words and event elements have low matching degree, and there is a class imbalance problem in the training process. This paper proposes a Chinese event extraction method based on HMM and multi-stage method. The first stage of the method recognises the event trigger word positive examples in the text; the second stage classifies the trigger word positive examples recognised in the first stage, determines the event type, and forms the sequence of event trigger words; the third stage matches the event elements, and forms the sequence of event elements, according to the first two stages of event trigger word extraction results. This method effectively alleviates the class imbalance problem in training, improves the matching degree between event trigger words and event elements extraction, and obtains better extraction performance. The accuracy, recall rate and F value of Chinese event extraction are all More than 78%.

Power system equipment have many characteristics, such as many kinds, single color, similar appearance and complex environment of transmission and substation. These characteristics make it difficult for traditional image recognition technology to achieve good recognition results. If there are few training data samples, the performance of in-depth learning recognition declines sharply. To solve these problems, this paper designs an optimization and training recognition method based on the combination of generating confrontation network and deep forest. Firstly, the generated countermeasure network is used to expand the samples of power equipment, and then the active learning method is used to optimize the generated samples. Secondly, the traditional model-enhanced sample expansion method is used to expand the optimized samples twice. Finally, the robust network model is obtained by using the deep forest method to accurately identify the power equipment. Experiments show that this method has high recognition accuracy and is superior to many other algorithms.

Activation functions are very essential in artificial neural networks (ANNs), since they are non-linear functions and they have been proved necessary to implement deep learning. Recently, ReLU is one of the most well-known activation functions; however, several competitors – e.g. LReLU and SWISH – have nowadays been proposed or 'discovered'. In this paper, the authors perform a detailed comparison of five activation functions over two image classification datasets. We found the overall performances of accuracy rates ranked from the best GELU, RELU, SWISH, SELU, down to Sigmoid. Such the observation would result in the improvement of future image classification via designing new state-of-the-art activation functions.

Bitcoin plays an increasingly crucial role currently, whose of prices are challenged to be predicted when compared to the index of any traditional stock markets. With the accent of machine learning and deep learning, it is urgent to find out whether a machine learning model can or cannot see the way that the changes of Bitcoin's price or volume interact over some period of time leads to a price increase or decrease within next few days. Testing results indicated that, the proposed two machine learning models built by LSTM and SVR were capable to capture longer-range dependencies and performed accurately by producing state-of-the-art results.

As an important lifeline industry of the national economy, electric power has great demand for navigation and positioning, short message communication and timing of the BeiDou system. With the BeiDou III put into operation, the BeiDou system will be more widely used and deepened in power. This paper first introduces the main application of BeiDou system in China's power system, and then introduces the construction situation and various performance indicators of BeiDou III in detail. From the three aspects of precise positioning, short message communication and timing function, the performance index of BeiDou III and its specific application in power system are expounded. In addition, the future application and development of BeiDou system in energy industry are prospected.

Aiming at the time synchronization problem of pure pseudolite system in high precision positioning, a technique of time synchronization in pseudolite system based on single-difference method is proposed. The reference receiver with dual-antenna and the carrier phase observation equation are used and phase integer ambiguity is adjust-ed by the least-squares ambiguity decorrelation adjustment (LAMBDA) method. High precision synchronization of the system clock can be realized through the clock error broadcast or centralized processing. Both theoretical derivation and simulation show that the system is able to provide high accuracy time synchronization and the precision of synchronization can reach 0.02 ns.

Indoor positioning technique is the foundation of Internet of Things (IoT) and location big data, which provides IoT function and location data for retail, manufacturing, energy, medical, emergency, logistics, robotics and other industries. Indoor positioning performance is an important performance indicator of IoT intelligent communication terminals. In order to accurately evaluate the indoor positioning performance of IoT intelligent communication terminals, this paper constructs an indoor positioning performance test system for IoT intelligent communication terminals. The test results show that the uncertainty of horizontal positioning accuracy of Wi-Fi positioning and Bluetooth positioning can be limited within 0.32 m (k=2).

This paper introduces a new image acquisition scheme based on the principle of internal reflection for the inner wall of the small hole, and visually inspects small hole workpieces with an inner diameter of 2-10mm. The customized reflector is inserted into the small hole, and the internal wall image is displayed in the CCD industrial camera through the reflection of light, and then the subsequent image processing is performed. The feasibility of the scheme is verified by theoretical calculations, and the obtained inner wall image resolution can reach 10 μm, which has high practical value.

WSN(Wireless Sensor Network) is intended for obtaining sensory data so that the query processing technology of high efficiency is the precondition of widely used WSN. Existing query processing technology assumes that the WSN deployed in two-dimensional or three-dimensional free space are not suitable for those deployed in such limited circumstances as roads, pipelines and indoor environments. This paper explores the problems of existing query processing technology, does research on perception data query processing method and technology, and seeks out the existing problem and its solution by means of using the WSN actually deployed in a building as an experimental platform.

Gas sensors play a key role in gas detection. Gas sensors are prone to failure, so they are of great significance to classify gas sensor fault. Traditional gas sensor fault diagnosis methods do not consider the condition of the imbalance of fault data. In this paper, the generative adversarial networks (GAN) method is used to generate small sample sensor fault data, balance various types of sensor fault data, and then the random forest is used for fault classification. Finally, the sensor fault data is obtained by self-made experimental system to verify the proposed method. The experimental results show that the proposed method could effectively improve the accuracy of gas sensor fault diagnosis.

The rapid development of information science and the transformation of modern teaching concepts have made the teaching work more inclined to the cultivation of students' practical ability. Comprehensive training is a teaching activity for the better application of students' computer theory knowledge. The research and practice of practical teaching system, practical teaching content and practical teaching methods are particularly important in the teaching work of colleges and universities. Based on this, we have built and improved the core layer of the practical teaching system, namely the comprehensive training of software and theory.

East Zhejiang water diversion project is a major water resources allocation project to ensure the sustainable economic and social development of xiaoshaoningzhou area in eastern Zhejiang. The project task is to introduce Qiantang River water to provide domestic, industrial and agricultural irrigation water to xiaoshaoning plain and Zhoushan City, and to improve water environment. Its head project is Xiaoshan hub project. In order to ensure the safety of water quality along the water diversion line, it is very important to strengthen the monitoring and evaluation of water quality at the source of eastern Zhejiang. In this paper, BP network algorithm based on error back propagation is used to evaluate the water quality station of Xiaoshan junction. The evaluation results show that most of the water quality in Xiaoshan water diversion project is class II water and class III water.

The world has witnessed a growth in multimedia data, especially video data over the past few years due to increased internet bandwidth and higher processing power of computers. Having a large number of video data also require techniques to store, summarize, index and information retrieval. More attention has been given in recent years to develop techniques which summarize, index and retrieve sports videos due to its commercial aspects. This paper proposes a framework which classifies a cricket video into one of the four events namely Bowled Out, Caught Behind, Catch Out and LBW Out. The framework uses training videos from each category of event and summarizes the videos into key frames. HOG and LBP features are computed for key frames and fused to form a single feature vector which will be labeled accordingly which represents a single event in video. Feature vector is given to a Multi-Class SVM which classifies the video into one of the four events. The experimental results show that the Precision of our technique is 77.23%, Recall is 77.86%, F-Measure is 77.55% and the Accuracy is 65.62%. The evaluation metrics of our technique are promising, because in the literature there is no other technique present so far for event detection & classification in cricket videos.

In this paper, a complete mathematical model is established for the traffic efficiency of autonomous vehicles under high traffic light. Under the background of the mature automatic driving technology, a model to calculate the traffic efficiency is established to calculate the time consumed by passing a certain vehicle. In the case of setting traffic lights, we first block off intersections that interfere with the operation of fire trucks, and then make dynamic planning for the traffic lights after the fire trucks pass, so as to finally restore traffic order. Based on the tabu search algorithm scheduling strategy under traffic lights, the scheduling mechanism of special vehicles under general conditions is obtained.

Now a day's android is the fastest growing package in hand-held operating system. And it has become the most appealing and practical goal of malicious applications. This principal platform has approved itself not only in the mobile global but also in the Internet of the Things (IOT) devices. The most real risk of Android clients is malware contamination by means of Android application markets. The huge diffusion of malware in cellular platform is plaguing customers. Threat of malicious software has come to be an essential element within the protection of smartphones. The war between protection analyst and malware intellectual is abiding as contraption grows. The proposed methodology demonstrated the common precision 94% a tagged mobile malware datasets visitors with a lot of applications contains benign and twelve very different groups of all malware and adware in particular and complicated nature of malware is converting quickly and therefore emerge as harder to understand. We assessed different blends of oddity location calculations, include determination strategy and the quantity of the top highlights to decide the mix that gives the best activity in distinguishing new malware on Android. This research condenses the malware progression recognition procedures backed machine learning algorithms devoted to the Android OS.

The article introduces an automatic algorithm for cutting contour based on triangular mesh model, which realizes the solid section, automatic filling and material inheritance of the 3D model in the virtual reality environment, which can be accurately visualized in the virtual reality environment. It can not only describe the solid section of the 3D model, but also inherit the material texture relatively accurately, and it has a good real-time. The algorithm is applied to the immersive virtual reality simulation platform of the hydropower plant, which can allow students to perform real-time 360-degree viewing and cutting of the equipment of the power plant, and improve the knowledge level of the employees of the power plant on the internal structure of the equipment.

Along with the rapid development of high-speed railway, high-speed railway express products gradually mature, the electronic commerce industry of high-speed rise in demand for goods, the implementation of the high-speed rail freight trains is imperative, but freight trains operation organization faces new challenges at night. In this paper, we study the freight trains, different types of high-speed rail transportation express product process, the purpose is to effectively reduce skylight influence on train operation organization and freight trains for passenger train interference, and improve transportation efficiency, increase freight trains, operation specification, create a good environment for the emu operation. Based on the characteristics of different types of high-speed rail express products, this paper puts forward suggestions on rationalizing the transport process of freight emu, so as to give full play to the transport capacity advantages of freight emu, which is conducive to the high-quality development of freight emu.

In order to solve the problem that the development of self-built logistics cannot meet the development of fresh e-commerce, a coordinated distribution strategy of self-built logistics and third-party logistics is proposed. The tasks assigned by third-party logistics are used to determine the price discount ratio. Third-party distribution outsourcing cost function, customer satisfaction function, and freshness function of fresh produce. Aiming at the goal of minimum delivery cost, maximum customer satisfaction, and maximum freshness of fresh produce, a collaborative delivery optimization model was established, and a corresponding genetic algorithm was designed with examples. Simulation results show that: collaborative distribution can effectively reduce the cost of distribution, when the proportion of price discount increases, the cost of collaborative distribution decreases. It has a certain reference value for the optimization of fresh e-commerce enterprises' distribution mode.

The interaction of information during the structural design of aircraft is complex. In order to optimize the design process and improve the efficiency in research and development, this paper performs clustering calculation on the structural design matrix of a certain type of trainer and optimizes it through genetic algorithm. In addition, a specific method for calculating the amount of information through information connection weight is given. The simulation results show that the optimized matrix has strengthened the information interaction within the cluster, reduced the information interaction between clusters, and reduced the frequency of information feedback during the design process, which plays a role in improving the efficiency of research and development.

Zoning is widely used in land-use control and the criteria for a 'good' zoning scheme varies dramatically for different purposes of zoning. Studies during the past decades have presented many theoretical frameworks for the design and evaluation of zoning schemes designed for dynamic urban processes especially the housing market, but challenges remain. Therefore, this paper attempts to explore the robust zoning over time help derive boundaries that better fit with changing housing market. It starts with the preliminary introduction of the zoning and a review of spatial big data and existing studies on evaluating the suitability of zoning schemes over time. Three indicators are adopted to evaluate the current zoning framework. A new index called RHD that can evaluate zoning changing dynamics over time is proposed, followed by the discussion of the empirical findings of the impacts of the zoning on land supply and house prices in the territory. The proposed framework for evaluating zoning can benefit future studies of zoning regarding dynamic housing market in the world.

In view of the fact that the existing hyperspectral image anomaly detection algorithms only pay attention to distinguish between target and background by using spectral differences and ignore the correlation between pixels, and that local RX algorithm is easy to detect global non-anomalies as anomalies when the background is relatively complex, a hyperspectral anomaly detection method based on linear background removal is proposed. In this method, the edge information of hyperspectral image is obtained first, then the line part of edge image is extracted by Hough transform, and finally the local anomaly detection is carried out based on the linear background removal. By comparing the ROC curve and AUC value of this algorithm with RX algorithm and local RX algorithm, it shows that the algorithm of this paper can effectively reduce the false alarm rate of detection and has a better detection effect.

Aiming at the problem of insufficient comprehensive feature extraction in the fault diagnosis of rolling bearings, this paper proposes a fault diagnosis model of convolutional neural network (CNN) based on Convolutional Block Attention Module (CBAM). The model uses CBAM instead of pooling layer to join the CNN, and then exports to the full connected layer to realize the fault type identification and complete the fault diagnosis of rolling bearing. Experiments show that the accuracy of this method is 99.94%, and comparison with some other methods proves the effectiveness of this method.

The time source of this paper is based on Shanghai Laboratory of National Time-Frequency Measurement Center. The target of this paper is to build a multipath network timing system within the wide area network which could make sure the accuracy, reliability and safety of network time service. This Multipath Network Time Service System also playing an influential role in providing dedicated network time services for seconds-level time-demanding industries. The pharmacological analysis of the medical industry is used as a service demonstration case to verify and promote the application of the multi-path network timing system.

Based on the Encoder-Decoder framework, an automatic summarization model MNPAS for marine natural products literature is proposed. Instead of directly using the structure of the common encoder in the past, a certain degree of innovation has been made to make Gru model complete the coding work. This advantage is that data information is not so easy to lose. In decoder, attention mechanism is integrated to improve the quality of predicted output word sequence. Compared with the traditional methods, the method proposed in this paper can complete the automatic generation of marine natural product literature abstracts better.

With the remarkable achievements of smart city construction and the evolution of war form to intelligence, the future urban operations will be intelligent operations supported by smart city. This paper analyses the requirements of artificial intelligence on urban operations equipment support, and clarifies the supporting condition provided by smart city construction on equipment support from the equipment status perception, equipment support command and control, equipment supply support and equipment maintenance support four aspects, focusing on winning urban operations under intelligent warfare. On this basis, a new support model of urban operations equipment support is proposed.

This paper is devoted to the research of an intelligent bookshelf system. By introducing the current status of reading and purchasing books by people in various countries around the world, the value of the existence of the intelligent bookshelf is analyzed and proved. By introducing the main related technologies and algorithms used in the intelligent bookshelf system, this paper brings out the introduction to the principle and mode of operation, and an analysis of the system.

In this paper, the drawing robot studied is after the system extracts the edge of the image, convert its pixels to actual physical coordinates, then control the robot to track these coordinate values and realize image drawing. In many cases, the edges extracted by the edge detection algorithm have a lot of unnecessary details and edge lines of many branch points. Here, some techniques are used to remove these redundant and branch points. When the robot is tracking the trajectory, the quality of its control algorithm directly determines its performance. In this paper, the control system is designed using the deep deterministic strategy gradient (DDPG) algorithm in reinforcement learning, focusing on the setting of its reward function. Here we propose a reward function. After simulation testing, the reward function setting meets the system requirements, the controller can achieve high-precision and high-speed trajectory tracking effect, and it can also suppress chattering caused by external interference and model errors.

With the development of IoT technology, the number of attacks against IoT software chain vulnerabilities is greater than ever, and a reasonable vulnerability assessment system needs to be established for research. The Common Vulnerability Scoring System (CVSS) is a free, public risk assessment system used by information security vendors to assess the severity of vulnerability threats. However, CVSS is insufficient because of the strong subjectivity in the selection of measurement standards and the allocation of evaluation index weights. Based on this reason, this paper designs and proposes a more objective risk assessment method for IoT software chain vulnerabilities, and verifies the feasibility and effectiveness of the method through experiments.

The image inpainting algorithms based on GAN have problems such as color inconsistencies of the inpainted region with the surrounding part and the mode collapse during the training. This paper proposes an inpainting algorithm based on double discriminator generative adversarial networks (GANs). This algorithm introduces the loss function of WGAN-GP into a global discriminator and local discriminator independently. It combines the Mean-Square Error (MSE) and feature reconstruction loss function to train the inpainting model and repair the missing area. The algorithm uses more dilated convolutions instead of standard convolutions to obtain a larger receptive field and the skip connection to enhance the structural prediction ability of the generator. The experiment results on the labeled faces in the wild dataset show that our algorithm improves the quality of image inpainting and the stability of the training process.

At present, the commercial operating system VxWorks is the first choice of leading international intelligent equipment manufacturers. They implement their own equipment controller based on VxWorks. However, VxWorks is not specifically designed for the control field, so there are many deficiencies in the control field, such as: using a dynamic model, dynamically calling various resources at runtime, making the system less predictable and real-time. Aiming at the typical application scenarios of the object operating system, this paper gives the overall software architecture of the object bus. The designed object bus provides a transparent mechanism for communication between components. In view of the highly dynamic adjustment of the objects in the object bus, this article has designed a corresponding set of migration mechanisms for the object bus to solve the various negative effects of cache invalidation after dynamic adjustment. In the last part of the article, the functional verification of the implemented object bus is carried out, and the analysis and summary are carried out.

This article distinguishes the difference between dynamic operating system and static operating system from the design goal, and discusses the resulting difference in the technology used in system implementation. With this as the theoretical basis, according to the ISO17356 OS specification, using hardware abstraction layer design ideas, a simple and efficient static real-time operating system is implemented on the ARM platform. This paper adopts the idea of separating mechanism and strategy, and uses internal resources as a mechanism to implement different scheduling strategies; a task scheduling algorithm based on priority grouping is proposed, which achieves good performance in time and space.

The ARINC series of standards are mainly used to define how to use the computing resources of avionics. The ARINC 653 standard applies to the service interface of the spacecraft's integrated electronic operating system to the upper-layer application software. It isolates the application software from the underlying processor architecture and meets the requirements of the on-board real-time system with good scalability. This article will follow the ARINC 653 standard, design and implement a partition operating system, providing basic system static configuration capabilities, space partition capabilities, time sharing capabilities, inter-zone communication capabilities, and security monitoring capabilities

In order to meet the demand of real-time data acquisition and analysis in the process of digital PCR detection, this paper proposes a high-speed data acquisition system and design scheme based on FPGA. The system uses FPGA as the signal acquisition platform, USB interface as the data transmission module, develops a set of real-time acquisition and processing software, and proposes a peak extraction algorithm based on Chebyshev inequality. The algorithm improves the peak detection accuracy, shortens the peak extraction time, and reduces the requirements for software and hardware. The system can monitor and analyze the data signal. It provides a reliable basis for the later data processing, and has strong engineering practice.

This paper proposes a parallel collision detection algorithm based on ray tracing to improve GPU performance. The algorithm uses parallel ray tracing pipeline technology to improve the performance of the graphics processing unit (GPU). When the GPU combines multiple ray tracing, it will cause the work group threads to diverge, resulting in too many idle threads, which will reduce the performance of the system. In order to avoid thread divergence, a new collision detection technology for the detailed detection stage of ray tracing using a pipeline structure is proposed. By optimizing the addition of buffers, the ray tracing is divided into three stages, and the pipeline is designed to integrate multiple rays tracking to avoid unnecessary synchronization issues between the CPU and GPU, thereby improving system performance. The comparison experiment results show that the proposed algorithm improves the system performance by 2.7 times.

How to efficiently and accurately monitor the sparse aircraft Refueling behaviors from a large amount of video streams is of great significant for improving the level of management and refueling efficiency of aviation fuel stations. Due to the COVID-19 virus epidemic, the number of flights has dropped severely, the collection of image samples for refueling behaviors from large airport becomes difficult, which hinders the real-time detection of Refueling behaviors and reduces the efficiency of aviation fuel station. Therefore, automatically detecting the refueling behaviors of each station in time and accurately from a large number of aviation refuel stations still keeps challenging. To address this challenge, we propose a novel aircraft refueling behavior detection model based on deep learning, to quickly and accurately determine the refueling behaviors through analysing the video stream collected from the massive cameras deployed in the airport. Our proposed model adopts Inception v3 architecture of ImageNet to realize the model capability of transfer learning, the data augmentation to address the issue of overfitting, and the mAP (mean Average Precision) to test the performance. Our proposed model is also applied in the detection of refueling behaviors in China National Aviation Fuel Group, LTD (CNAF). The practical application results show better performance than other existing methods. Our work will promote the updating of related industry standard.

With the gradual deepening of the influence of artificial intelligence technology on all walks of life, enterprise IT operation and maintenance management is also undergoing changes in a more intelligent and advanced direction. In order to change the practical problems of enterprise IT operation and maintenance management, such as single method and lack of means, this paper analyzes and studies the overall framework of enterprise it intelligent operation and maintenance management technology, and deeply analyzes the key intelligent methods in operation and maintenance management, such as fault prediction, fault analysis, operation and maintenance scheduling, so as to provide support for effectively improving the level of enterprise it intelligent operation and maintenance and systematic support ability.

Distribution entropy (DistEn) is an effective index to measure the complexity of time series. In this paper, the moving distribution entropy (M-DistEn) method is proposed by combining the distribution entropy method with the moving window technology. The moving cut data-distribution entropy (MC-DistEn) method is proposed by combining the DistEn with the moving removal window. Based on the M-DistEn method, moving weighted distribution entropy (MW-DistEn) is proposed. These three distribution entropy methods are used to identify the chaotic state of mixed Logistic map sequences with different parameters. The results show that the M-DistEn method only recognizes the first three mixed states of the sequence, and it cannot accurately recognize the last two chaotic states of the sequence, so it has certain limitations. The MC-DistEn method can accurately identify the four different chaotic states of the sequence, but the DistEn value greatly fluctuates due to the influence of the size of the moving removal window, and the position judgment of sequence state change is not accurate enough. The MW-DistEn method not only accurately recognizes different chaotic states, but also is more accurate in judging the position of sequence state changes and more stable in DistEn value than the M-DistEn method and MC-DistEn method, thereby it has a good application prospect.

The intersect operation of geometry is a common method of collision detection. To achieve a fast intersect operation, a hierarchical bounding box must be quickly constructed. This paper proposes an effective space division method for constructing high-quality linear hierarchical bounding boxes through ray tracing. This method can generate more regular axial bounding boxes into a complete binary tree. This structure can be completely parallel on the GPU, and effective parallelization can ensure the fastest tree-building time. The algorithm in this paper uses a non-stack ray tracing method to increase the frame rate of the 3D model rendering in the graphics processing unit and reduce the construction time of the bounding box. The experimental analysis of construction time, frame rate, average number of intersections and other performance indicators, the experimental results show that the use of stack-free midpoint splitting method and surface heuristic splitting method to ensure rapid construction time and efficient ray traversal performance, improve the object's light traversal efficiency.

The surface roughness algorithm and its evaluation system is the key factor of surface morphology measurement. This paper studies the UWP (Universal Windows Platform) platform and uses C# language to realize surface roughness evaluation system. The system can accurately calculate 4 commonly used surface roughness parameters based on the established mathematical model. The system includes 3D surface data reading, surface roughness calculation, graphic interaction and other functions. Experiments results show that the system can realize rapid and multi-parameter measurement of the workpiece's surface roughness, and is adequate for surface morphology characterization. The cross-platform evaluation system is user-friendly with visualized 3D data and reliable results.

Aiming at the problem of poor flexibility of traditional industrial robot, the vision system and industrial robot control system are combined to propose a visual servo control method based on Faster RCNN. The image information of the target object is collected through the camera, and the Convolutional Neural Network(CNN) is used to detect the entire picture, then the category and position of the object to be grasped are obtained, which improves the control performance of the robot system. Experiments show that the visual servo robot control system can quickly complete the position recognition of different objects. Mean average precision of this method can reach 0.867. The maximum error between the recognized grasping position and the actual position on the coordinate axis does not exceed 3.4 mm, the detection time of each picture in the GPU environment is 17.1ms, which has certain guiding significance in the visual servo control of industrial robots.

In this paper, we improved the ROAM tracking model as well as replaced the first 12 layers of VGG-16 used in the experiment with the HETCONV convolution layer, where the first layer remains unchanged, as well as the other layers are divided into 4 parts. Each part has only one 3*3 convolution kernel, as well as the other convolution kernels are all 1*1, thus improving the speed of the tracking model while keeping the accuracy unchanged. We have extensively evaluated the improved ROAM as well as the unimproved ROAM on the TrackingNet benchmark, as well as the results prove that this method effectively improves the frame rate.

As an important power source of diesel engine, the fuel supply system has the characteristics of high failure rate and being difficult to be detected, which is critical to detect and diagnose the fault for the reliable and stable operation of diesel engine. In the paper, principal component analysis (PCA) was used to process the initial data, back-propagation (BP) neural network was used to diagnose fault of diesel engine, BP diagnosis efficacy was analyzed, then the BP neural network fault diagnosis system was optimized by being introduced in the genetic algorithm , and the comparison results of training error and diagnostic analysis showed that: the fault diagnosis of BP neural network optimized by genetic algorithm is more accurate than that of traditional BP, which can effectively improve the fault diagnosis accuracy and reduce the training time.

With the development of data science, there are more and more ways to dig for patterns hidden in the data. If we can apply the advanced model of data science to the power data, we can mine the potential value of power data. In this paper, the monitoring and inspection data of 110kV main transformers and related basic environmental data are fused to establish conditional inference tree model and AdaBoost algorithm to evaluate whether the 110kV main transformers have defects and faults. The accuracy of the two algorithms is compared. Finally, we select the AdaBoost algorithm with higher accuracy for building the 110kV main transformer fault evaluating model. This paper provides a reference for the automatic detection of power grid faults, and provides new ideas for the application of power grid big data.

With the rapid development of virtual reality technology and collision detection technology, virtual reality has become a lot of research fields in China. Collision detection is one of the most important technologies, and virtual surgery simulation has gradually become an important application of medicine in virtual reality technology. Virtual surgery can not only provide a skilled training platform for medical staff, but also analyze the feasibility and danger of surgical scheme, so that medical staff can have the same authenticity and strong immersion in virtual environment as in physical surgery. In this paper, a mixed hierarchical bounding box is constructed to detect the collision between the virtual human soft tissue and the rigid tissue of surgical instruments, and a parallel algorithm, fast bounding box coordinate chain calculation, compression storage and so on are introduced. For the deformation model of the software which is difficult to construct, the collision detection can be completed quickly and accurately, which can effectively save the collision detection time and improve the real-time performance of the collision.

Production logging is the main means of dynamic monitoring of oil wells at present. The interpretation method of production logging fluid profiles is the key to the dynamic evaluation of oil wells and is of great significance. A joint optimization technique of a AGA and L-M is proposed to deal with the profile data of oil-water two-phase flow. The method is based on the energy conservation of the fluid in the production unit space. According to the nonlinear weighted least squares principle and the error theory, the objective function of the minimum value is established by the difference between the theoretical fluid temperature and the measured value of the thermometer. According to the fluid volume conversion, the flow rate of each phase in the well and the flow log value at the bottom of the control body are constrained. In order to improve the interpretation accuracy, the global search method (AGA) of genetic algorithm and the direct local search method of L-M algorithm are combined to solve the optimal solution. Firstly, the adaptive genetic algorithm is used for heuristic global search, and then as a result of the initial parameters, the L-M method is applied to approach the optimal solution. The interpretation results from the joint inversion are stable and reliable. This method is not only suitable for vertical wells but also for inclined wells.

Firstly, the mixed key system task model of compatible with periodic tasks and sporadic tasks is studied. Based on the model compatible with these two tasks, a semi-divided real-time task scheduling mechanism is proposed. This process also considers the aggressive handling of Low critical task to improve resource utilization. Finally, the relevant program code is designed and developed, and the performance of the proposed algorithm is evaluated by means of simulation and simulation. The correctness of the model and theory is verified, and the theory and protocol design are further improved.

In order to further improve the efficiency of data mining, it proposes a kind of data mining algorithm based on new association rules and classification rules. Specific research process is as follows. Firstly, MDML-PP algorithm is analyzed and applied to the multi-dimensional multi-level association rules in data mining, and then selects the test data sets for performance evaluation, meanwhile, it also studies the multi-support rate cut and classification rule mining algorithm, which is applied to multi-support rate classification rules in data mining, finally, using the compare experiment to verify the effectiveness of multi-support rate classification rules. The results show that the proposed algorithm in this paper can be better used in data mining with multi-dimensional and multi-layer association rules, which can improve the efficiency and quality of data mining.

In this paper, the sampling rate of traditional signal reconstruction should be more than 2 times the maximum frequency of the original signal in order to ensure the non-distortion reconstruction of the signal. The theoretical knowledge of compressed sensing is deeply analysed, and the image signal is reconstructed by block compression sensing method. Experiments show that the sampling rate is more higher, and the reconstruction error is more smaller, but the processing complexity is more higher; conversely, the lower the sampling rate, the lower the processing complexity, the greater the reconstruction error.

Compared with other optimization algorithms, the particle swarm optimization algorithm (pso) has the advantages of fast convergence, simple calculation, and fewer parameters to be adjusted. Therefore, it has been greatly developed in the past period of time. In order to further accelerate convergence, in recent years, more efficient and convenient particle swarm optimization algorithms such as LDWPSO, NLPSO, and DPSO have been proposed.However, these algorithms have many problems such as large amount of calculation, lack of precision, and easy to fall into local optimum.Therefore, the algorithm still needs to be improved. In order to obtain an efficient global search ability early in the algorithm iteration and better local optimization performance in the later stage of the algorithm iteration, this paper proposes a special expression form of dynamic change speed attenuation factor and inertia weight factor, and in the algorithm some random parameters are added to the iterative formula and applied to the algorithm iteration formula to improve the optimization speed and optimization effect of the algorithm.Finally, the effectiveness and correctness of the algorithm are also demonstrated by computer simulation experiments.

This paper puts forward a chaotic encryption algorithm based on Bernoulli Shift Map. This algorithm adopts dynamic encryption key and uses plaintext image parameters to control generation of chaotic key, and enhance connection between chaotic key and plaintext data; the iterative operation precision of chaotic map during encryption is high, avoiding cycle of chaotic system iteration process. The NPCR and UACI analysis, adjacent pixels correlation analysis and image information entropy analysis on encrypted image show this encryption algorithm has favorable encryption characteristics such as larger space for key, sensitivity to plaintext and random distribution of ciphertext.

Selective clustering ensemble algorithm can eliminate the inferior quality clustering member's influence and can achieve a better clustering solution relative to the clustering ensemble algorithm. For high dimensional data clustering, in this paper, a novel selective ensemble algorithm based on semi-supervised K-means clustering is proposed. In this paper, through a large number of experiments to verify the validity of the proposed algorithm for dealing with high dimensional data clustering. The new algorithm can achieve statistically significant performance improvement over other clustering algorithms.

The proper work of main transformers plays an important role in the stability of the power grid. The development of power data allows us to evaluate the instant status of the main transformer. If we use appropriate data classification algorithm, the laws and values hidden behind the mass power data can be discovered. This paper took basic power data, main transformers' status data and oil chromatography data into consideration, and used Logistic regression and Naive Bayes algorithm to evaluate 110kV main transformers' defects and faults from regression analysis and probability statistics seperately. The results of these two algorithms were obtained and compared. Finally, a more accurate algorithm of evaluating main transformer fault was selected, which provided a new reference for the application of power big data.

In order to realize the multi-objective management objectives in the production cycle of aviation products, this paper combines particle swarm optimization algorithm and critical path optimization algorithm to carry out multi-objective optimization on the research and development process of aviation products. First, calculate the start time of each process by the critical path method and construct the initial population. Then construct the fitness function. Finally, particle swarm optimization is used for optimization, and through continuous iteration, the optimal combination that can achieve multi-objective optimization is obtained. Through the optimization experiment on the research and development process of aviation products, the global optimal research and development process calculated in this paper can shorten the production period by 32.4% and reduce the cost by 41.1%. Therefore, the multi-objective optimization scheme based on hybrid optimization algorithm proposed in this paper has theoretical and practical significance for the model management of the whole life cycle of aviation products.

UWSN (Underwater wireless sensor network) is a significant part of marine environment stereo monitoring system, and the energy problem has always been an important constraint and challenge that limits its wide application. Due to the development of wireless charging technology and intelligent mobile nodes, the energy problem in UWSN has been solved. The underwater sensor network using wireless charging method is called UWRSN (underwater wireless rechargeable sensor network). In wireless rechargeable sensor networks, one of the core issues is the design of the charging planning. In this paper, a charging path planning algorithm based on multi-parameters is proposed for the on-demand charging system of UWRSN. The algorithm plans the charging path for the underwater MC (mobile charger) according to the parameters such as the remaining power, position, and power consumption speed of the underwater sensor node, so as to minimize the number of network dead nodes, improve network energy efficiency, and extend life of the network. Simulation results show that the algorithm has good performance in terms of charging efficiency, extending network life and other performance indicators.

Aiming at the problems that the ViBe algorithm causes error detection when the camera jitter, ghosts appear when processing moving targets, and the detected moving targets are incomplete, an improved ViBe algorithm based on motion compensation is proposed. In the background modeling stage, the motion compensation method based on KLT is used to obtain background model to enhance the robustness of the algorithm to the dynamic background. In the foreground detection stage, combined the background model of the current pixel with 8 neighbor pixel background model, by the double discriminant algorithm to eliminate ghost areas caused by detecting the real background points as foreground points, introduce OTSU algorithm to obtain the optimal threshold for foreground detection. In the post processing stage, filter the connected components for segmentation masks and update models to limit the wrong background points scattered in the foreground.Finally, the connected domain is repaired by morphological opening operation. The results show that the algorithm can effectively eliminate the interference caused by camera jitter, and suppress the ghost phenomenon to obtain more accurate foreground images.

In an embedded environment, applications have a strong demand for real-time scheduling, but it is difficult to ensure the real-time scheduling performance under a partitioned operating system, mainly because in a multi-operating system environment. It is difficult to determine the real-time schedulability within and between partitions. The research of this paper will focus on the real-time scheduling algorithm of partition operating system with simple task model in single-core environment.

In this paper, on the premise of analyzing the theoretical knowledge of collision detection algorithm, the advantages and disadvantages of several commonly used hierarchical bounding box methods are compared and analyzed, and then the traditional collision detection algorithm is studied. This paper presents a new collision detection algorithm. After preprocessing, the first order collision detection based on the separation axis theorem is used to exclude a large number of disjoint spatial model objects through preprocessing. The purpose of adding primary collision detection is to further investigate disjoint object pairs, and prepare for the final detailed detection stage. The pre-determined OBB bounding box is used for fast collision detection, and its storage structure and mode are optimized quickly. After preprocessing, it effectively eliminates the obviously disjoint space object pairs, reduces a large number of operations, and improves the detection efficiency.

Video target tracking is one of hot fields of computer vision, and its application is also very extensive. However, due to the complexity and variability of tracking environment, which brings some challenges to the research of target tracking. ECO(Efficient Convolution Operators) Algorithm is proposed based on convolutional neural network in three aspects. Firstly, residual neural network ResNet50 is adopted instead of convolutional neural network to extract the appearance features of target, and deeper residual neural network is applied to obtain more abundant target semantic information, so as to improve the tracking effect of tracking algorithm.Secondly, sample space classification strategy is improved. Different weights are assigned to shallow feature and deep feature, which make the deep feature play a more important role and improve the effect of target tracking. Finally, the method of scale estimation is improved so that better bounding boxes can be estimated with the scale changing. Experimental results show that the distance accuracy and success rate of the algorithm.

Based on the analysis of power line features in aerial images, this paper proposes a power line detection algorithm for aerial images based on adjustable direction filtering. The thesis first performs directional filtering on the image and calculates its directional energy function and ridge energy function, then combines the image local and global information to fit the line segments in the image, and finally verifies the reliability and real-time performance of the algorithm through experimental methods. The calculation of this algorithm is about half of the ED Lines algorithm. Experimental results show that the algorithm can detect power lines in aerial images better, and the algorithm is not complicated, which is suitable for real-time detection of power lines.

By the huge development of large scale and modular photovoltaic power generation, accurate photovoltaic (PV) output prediction can help PV power station, scheduling department and power system operate safely and economically. In the process of PV output prediction, the data density is large, and the output data is relatively regular. Therefore, this paper considers the use of long-termed and short-termed memory neural network algorithm to optimize the problem of algorithm gradient vanishment in recurrent neural network, and complete the output prediction of PV power in the regional energy Internet on the basis of historical output data. In this paper, LSTM algorithm is used to analyze the historical output data of PV stations in an industrial zone of a certain city. It can be found that LSTM algorithm has good adaptability for short-term PV output prediction, which can meet the needs of application.

The traditional ant colony algorithm based on raster algorithm has slow searching speed and convergence speed in the problem of robot path planning, and it is easy to fall into the problem of local optimal. In order to solve this problem, an improved ant colony algorithm based on Wolf distribution rules and reconnaissance ant strategy is proposed, which can adjust the pheromone coefficient adaptively and obtain a more suitable proportion of pheromone allocation. Experiments show that this algorithm is superior to the traditional ant colony algorithm in terms of optimal path searching speed, quality and convergence speed in simple and complex environments.

In order to more accurate for nonlinear function extreme, this paper used improved particle swarm optimization neural network combining with genetic algorithm method to solve the problem. In view of the particle swarm optimization algorithm is easy to appear "premature" faults, introducing the adaptive threshold, initializing particles if they were under the constraint conditions, making particles jump out to the optimal value of the position in previous search. Through the experiment, contrasts to the genetic neural network algorithm and traditional BP neural network, this method is faster in convergence and has the smallest prediction error. Finally, combining with genetic algorithm, calculating the extreme value of nonlinear function by using the above three kinds of neural network trained forecast as an individual output fitness value. The adaptive particle swarm optimization neural network proves the most close to the theoretical calculation. It shows that the method is effective.

The detection and monitoring methods of power equipment are relatively complex. The analysis of a large amount of data obtained from detection and monitoring and the development of data recording methods make it possible to obtain higher-dimensional power data. If we adopt appropriate data analysis method to the data sets, we can better get the potential laws and value of power data. In this paper, we took various basic monitoring data and faults records of the 110kV main transformers into consideration, and the grid-equipment-environment data was fused. Based on the fused data, we used the decision tree and random forest algorithm to evaluate the main transformers' defects and faults. The evaluation results of the two algorithms were obtained and compared, which proved the effectiveness of the fault evaluation algorithm and selected a more accurate fault evaluation algorithm. This paper provides new ideas for smart fault detection for power grid, and provides a reference for a more in-depth evaluation of power grid equipment.

Some machine learning algorithm tools, such as neural networks and Gaussian process regression, are increasingly being applied to the exploration of materials. Here, we have developed a form to use this nonlinear interpolation tool to describe properties that depend on the degrees of freedom in multi-component solids. A symmetrically adapted clustering function is used to distinguish different atomic order degrees. These features are used as the input of neural networks, Gaussian process regression and other algorithmic models, and some inherent properties of materials, such as formation energy, can be reproduced by the trained machine algorithm model. We use this technique to reproduce the expansion Hamiltonian of a synthetic cluster with multi-body interaction, and calculate the formation energy of ZrO based on first principles. The form proposed in this paper and the results shown that complex multi-body interactions can be approximated by nonlinear models involving smaller clusters. The training models used in this paper to predict energy include neural networks, Gaussian process regression, random forests, and support vectors regression, using MSE and coefficient of determination to evaluate the prediction results, and adding genetic algorithms in the feature selection process can remove some redundant features and improve the prediction efficiency and accuracy. The results show that the neural network is the best algorithm model which selected in this article, the prediction effect of support vector regression is relatively inferior.

In order to accurately evaluate the impact of voltage sag on both utility and customer, a data mining analysis method based on improved FP-growth algorithm and AHP algorithm is proposed. The proposed method selects and classifies voltage sag characteristics and combines voltage sag severity level to construct a data mining analysis framework. The improved FP-growth algorithm is used for data mining on voltage sag events to improve the efficiency of mining. The association rule matching model is constructed by AHP algorithm for evaluating the voltage sag severity level, which improves the accuracy of the evaluation results. Finally, a practical example verifies the practicability of the proposed method.

The inter-annual and inter-decadal variation of temperature in Dabie Mountain of West Anhui Province is analyzed according to actually measured data of daily average temperature, maximum temperature and minimum temperature during 1960-2013 in five meteorological stations in Dabie Mountain. Results show: The quarterly and annual average temperature, average maximum temperature and average minimum temperature (except the average maximum temperature in summer) in Dabie Mountain of West Anhui Province are all in a rising tendency. The annual average temperature increases remarkably at an amplitude of 0.165°C/10 years. The increase amplitude of average minimum temperature is 1-2 times of the average maximum temperature, and the daily range shows obvious reduction. The annual extremely maximum temperature and extremely minimum temperature are both on the rise, and the amplitude of the latter is larger than that of the former. From 1960s, the average temperature, average maximum temperature and average minimum temperature turned rising in Dabie Mountain of West Anhui Province. The abnormally warm years are 1967, 1968, 206, 207, 1998 and 2013, while the abnormally cold years are 1967 and 1981.

Thirty samples of crucian carp and carp are collected in upstream pine forest, midstream Dadingzi mountain and downstream Jiamusi section in the main stream of Songhua river. The ICP method is used to test heavy metals content of the fish. The exposure health risks of exposed way of edible fish in the Songhua River is assessed by exposure to the health risk assessment model. The results show that the noncarcinogenic target risk quotient (THQ) of each heavy metals is less than 1. The biggest heavy metal of the noncarcinogenic risk is As. From high to low in the order, the THQ is As>Cu>Mn>Pb>Cd. Composite exposure non carcinogenic hazard index (HIs_F) is 0.18∼0.23. As of fish exposed can cause the evident in the risk of cancer, TR is 2.89×10⁻⁵∼6.78×10⁻⁵.

The influences of using several dosages of Yuetian soil conditioner on the output, heavy metal concentration of areca taro and soil basic fertility characteristics were studied by field plot experiment. Outcomes indicated that the output of areca taro enhanced by 6.2%∼12.8%, As concentration decreased by 28.9%∼40.0%, Hg concentration decreased by 28.6%∼50.0%, soil pH value enhanced by 4.0%∼34.9%, exchangeable acid decreased by 10.5%∼95.2%, available phosphorus decreased by 36.4%∼54.6%, and the concentration of organic matter, hydrolytic nitrogen and available K was different, but the concentration of Pb, Cd and Cr enhanced, and the concentration of Hg and As was different.

Carp from Jiamusi section of Songhua River were collected to analyze and evaluate the residues of heavy metals, organochlorine pesticides, polycyclic aromatic hydrocarbons and volatile organic compounds in muscle tissue. The results showed that 100% of heavy metals, organochlorine pesticides and polycyclic aromatic hydrocarbons were up to standard, and a small amount of volatile organic compounds were detected. The structure and morphology of fish tissue samples were not abnormal, and the structure of nucleus and cytoplasm was normal. No pathological changes or morphological abnormalities were found. Fish were healthy.

In order to study the Hubei lightning locating system detection efficiency in 2015-2016, this paper adopts the method of mathematical statistics, compared and analyzed the distribution structure, detection efficiency, space-time distribution and lightning current characteristics between two lightning systems. The results show that the more sub-stations and the smaller the baseline distance are, the higher the detection efficiency is. The average number of cloud and ground lightning in 3D lightning locating system is 86.8% more than that in 2D system, and the proportion of positive ground lightning is slightly higher than that in 2D system. The positive and negative flashover of the 3D system are between 0-90kA, Positive current of 10-20kA and negative current of 20-30kA are the most. The positive and negative lightning in 2D system are between 10-100kA, the current has the highest percentage of 20-30kA and the lowest percentage of 10-20kA. The 3D system detection efficiency and lightning density distribution are better than 2D system. two sets are consistent in lightning time characteristics, geographical distribution and intensity distribution rules, which plays an important role in lightning disaster investigation, lightning monitoring and early warning and other business applications.

Based on the problems of poor productivity and natural regeneration of Cyclobalanopsis glauca secondary forest in hilly areas in southeast Hunan Province, experiments of thinning were carried out to analyze the effects on stand growth and regeneration of different thinning intensities and to provide guidance for managing secondary forests. Cyclobalanopsis glauca secondary forest was selected for research object, then experimental design was arranged with a randomized block by thinning intensity such as control(un-thinning), light thinning (10%), moderate thinning (20%) and heavy thinning (30%). Tree measuring factor and number of naturally regenerated seedlings were investigated for researching the responses to thinning treatment. Results showed that there were significant differences of mean DBH and current annual increment of DBH in terms of the four thinning treatments, and the larger the thinning intensity, the higher the DHB increment. The maximum mean height (10.1m) happened in stand of heavy thinning. However, significant differences existed in the current annual increment of height among the four thinning treatments. Stand volume was 93.27, 91.49, and 91.90 m³ hm⁻² respectively in stand of heavy thinning, moderate thinning, light thinning, and were all lower than that of the control, but current annual increment of volume was 5.65, 4.43 and 3.75 m³ hm⁻² yr⁻¹, respectively and higher than that of the control. The Simpson index of shrub layer and herb layer of heavy thinning stand was 0.45 and 0.80, Shannon-Wiener index was 1.03 and 2.03, respectively. There were significant differences of naturally regenerated seedlings according to four thinning treatments only for seedlings of 5∼30 cm level, but there were no significant differences for seedlings of 30∼50 and 50∼150 cm level. The growing space and nutritional condition of retained trees after thinning were effectively improved, stand DBH and height increased with the increasing thinning intensity. However, stand volume was not significantly different among four thinning treatments. Besides, thinning at appropriate intensities could increase the biodiversity in shrub layer and herb layer, quantities of naturally regenerated seedlings also increased with the increasing thinning intensity. Heavy thinning (30%) was the best one among four thinning treatments for silvicultural interventions on Cyclobalanopsis glauca secondary forest.

The natural runoff of the Yellow River has been reduced sharply since 2000. Based on rainfall network of 1966 and 1977 are built on GIS platform, the trend of rainfall variety in 1956∼2013 is analyzed. The turning point of runoff of natural period and human activities impact period in the eighteen tributaries was analyzed with the method of orderly clustering and MWP test and so on. The model was established with the data from 1956 to the turning point year, and the runoff during this period was regarded as benchmark value. The runoff variety and the impacts brought by rainfall in the status series from 2007 to 2013 were analyzed by equation of runoff division. It is showed that natural runoff reduced 5.411 billion cubic meters, among which brought by rainfall not negative value but increased 0.424 billion cubic meter.

Environmental art design is a subject to deal with the relationship between artificial environment and natural environment, and also a subject to create a livable and ecological balanced living environment for human beings. Thus, it is of paramount of importance to study how artificial construction can adapt to the natural environment. To this end, the concept of physics "Resilience" is introduced into the landscape design of urban wetland park, and the strategies of shaping and utilizing resilience landscapes in urban wetland park is discussed in order to provide effective measures to deal with urban flood disaster, realize "sponge function", promote regional ecological environment balance and sustainable development.

The dam site of Tongjiqiao reservoir is located in Puyang River, a tributary of Qiantang River. Tongjiqiao reservoir is the backbone flood control water conservancy project in Puyang River Basin and an important source of ecological and environmental protection tourism. It is also a reserve water source protection area for the future development of Pujiang County. The reservoir not only provides most of the industrial and agricultural production and domestic water for several major towns (streets) and economic development zones of Pujiang County, but also undertakes the ecological water supply task of Puyang river. For a long time, Tongjiqiao reservoir has played an important role in the economic and social development of Pujiang County. In this paper, the model of adaptive neural fuzzy inference system is used to predict the rainfall of Tongjiqiao reservoir. The results show that the rainfall of the reservoir area is in the average level of many years from 2020 to 2025.

Haihe River Basin is an area with frequent droughts and floods in China. There is a serious shortage of water resources in the Haihe River Basin. The average annual water resources in the basin are 37.2 billion cubic meters, with a per capita share of 305 cubic meters, 1/7 of China. which is one of the serious water shortage areas in China. Panjiakou Reservoir is a large reservoir in the Haihe River Basin, with a water storage capacity of 2.93 billion cubic meters. It is responsible for the water supply of Tianjin, Tangshan and other large and medium-sized cities. The reasonable operation of Panjiakou Reservoir plays an important role in Haihe River Basin. In this paper, the support vector machine model is used to predict the runoff of Panjiakou Reservoir. The prediction results can provide reference for the reasonable operation of Panjiakou Reservoir.

The north line of water diversion from Cao'e river is one of the six major water diversion projects in eastern Zhejiang Province. The project passes through three cities of YuYuCi. It mainly supplies water for Industry and agriculture, and takes into account the improvement of water environment. Cixi City is located at the end of the north line of water diversion from Cao'e river, and its water quality is affected by the nodes along the water diversion line. Using the least square method which can extract the main components of the independent variables on the dependent variables, the regression equations of the independent variables: Mushan sluice, Qitang sluice, Sitang sluice, Puqian sluice, xinsanjiang sluice and Luzhongwan pumping station are established, and the contribution values of each node to Luzhongwan pumping station under the indexes of permanganate, ammonia nitrogen, total phosphorus and dissolved oxygen are calculated. The results show that Sitang sluice has the greatest contribution to permanganate and total phosphorus of Luzhongwan pumping station, Puqian sluice has the greatest impact on ammonia nitrogen index of Luzhongwan pumping station, and xinsanjiang sluice has the greatest impact on dissolved oxygen index of Luzhongwan pumping station. Generally speaking, the stations which have the greatest impact on the water quality of Luzhongwan pumping station are Sitang sluice and Qitang sluice.

This paper describes the analysis of nutrients matter in soil sampled from Datong abandoned mining area in Huainan City. Spatial interpolation in GIS is applied to the revelation of spatial distribution of nutrients matter. Results show that: In abandoned land in Datong coal mining, the level of available phosphorus in soil was very short and the following grades, and the level of nitrogen was short grades, and the level of organic matter was medium and the following grades. Distribution of these heavy metals present a stronger spatial relevance because their spatial pattern are mainly influenced by natural factors such as complex micro-geomorphology, vegetation, topography, strongly human disturbance and other structural factors. All of spatial variability was middle and small scale. Characteristic of spatial variation was relation with the complex distribution object. Random factors, such as sampling interval, soil type and so on, play a relatively greater role in spatial variability of nutrients matter.

Based on laboratory analysis of soil samples collected from abandoned coal mine in Datong area, content of heavy metals in the soils was monitored and the soils were evaluated for heavy metal pollution. The spatial distribution of heavy metals was study with means of Kriging method by under ArcGIS environment in the abandoned coal mine in Huainan area. The results show: (1) the content of 5 types of heavy metals( Hg, Cd, Cr, Pb, Cu) were all higher than Huainan area background value of soil elements, among of these heavy metals, the enrichment of Cd was higher and polluted quite seriously; the enrichment of Hg, Cr, Pb and Cu was lower, and polluted lightly comparatively. (2) The coal mine waste rock pile and abandoned chemical plant were the main pollution sources. (3) The heavy metal concentrations and space distribution were mainly affected coal mine waste rock pile, and abandoned chemical plant. (4) Positive correlation between concentrations of most heavy metals was significant, and there is a certain relationship between concentrations of heavy metals and organic matter, nitrogen, available phosphorus. On the basis of the above research, some countermeasures were put forward for ecological restoration in Datong abandoned coal mine.

This paper combs the relevant theories and literature, and analyses the three impact mechanisms of FDI on environmental pollution which includes economic scale, technology and structural effects , This paper selects foreign direct investment panel data of 29 provinces in China in 2009-2017, explores the impact of foreign direct investment on China's environmental pollution, verifies that the "pollution shelter" hypothesis does exist in China, and concludes that the inflow of foreign direct investment aggravates China's environmental pollution, and based on this, the paper puts forward targeted policy recommendations.

In the context of the country's great efforts to build a socialist ecological development, the weaponry and equipment, as an important part of the development of the national defense, are becoming more and more important in the direction of green ecological environment. The article analysed and discussed several key ways of implementing green integrated support of equipment-----green design for equipment, green manufacturing for equipment, and green maintenance for equipment, which promotes coordinated and continuous development of military, environment and economy on the basis of expounding the connotation of green ecological environment and equipment integrated support.

Analyzing PM_2.5 concentrations from remote sensing images and surface measurements using the model of aerosol optical depth (AOD) is a popular method to evaluate the exposure to PM2.5 in some geographic regions. For analyzing the ground-level PM_2.5 density on a daily basis using satellite-derived AOD in Shanghai area, we use Aqua MODIS (Moderate Resolution Imaging Spectroradiometer) to obtain the AOD values at 3-km resolution by dark pixel. However, AOD values are missing in many regions caused by processing method and imaging process. Interpolating the AOD values to extend the coverage area of MODIS and integrating the surface measurements, we filter the AOD values and PM2.5 measurements. The analysis results indicate that the correlation coefficient is 0.54 in Shanghai area. Satellite derived mean PM_2.5 for Shanghai was 42.69 ug/m³ during the study period (Jan 2016 to Dec. 2018), whereas mean PM2.5 is highest in winter period (61.68 ug/m³), and lowest in autumn period (31.4 ug/m³) over study period in study area.

The wavelet analysis method is applied to analysis of multi-level time change characteristics of temperature and precipitation in Dabie Mountain based on the meteorological observation data of five stations in Dabie Mountain from 1960 to 2013. According to results, the temperature shows oscillation periods of 22 years and 10 years in Dabie Mountain, West Anhui. While the precipitation shows an oscillation period of26 years. The change relationships of temperature and precipitation are not the same based on different time scales. From the scale of 3 years, to 10 years and 20 years, the out-of phase becomes weaker. The tendency of consistence appears gradually.

The influences of several doses of Tebei calcium oyster powder on rice output, heavy metal concentration and basic soil fertility characteristics were studied by field plot experiment. Outcomes indicated that the use of several doses of Tebei calcium oyster powder could raise the dry matter output of rice by 5.24%∼20.65%, reduce the Cd and Pb concentration of rice by 7.80%∼53.67% and 12.63%∼60.10%, raise the pH value of soil by 4.1%∼24.5%, decrease the exchangeable acid (potential acid) by 1.0%∼53.8%, and decrease the concentration of Influenceive Cd and Pb by 64.22%∼77.98% and 4.65%∼22.59%, respectively.

This paper investigates the thermal stresses of low-heat cement concrete under different loading ages, and thermal stresses were calculated with different compensation cycles by the Boltzmann superposition principle. An application of the Boltzmann superposition principle on the temperature stress test shows how the formulation may be used to evaluate the mechanical properties of low-heat cement concrete and how the accuracy of calculated stresses applies to measured stresses. The comparison between measured stresses and the simulated results shows good agreement under different compensation cycles, which indicates that the thermal stresses can be well estimated via the line superposition. Furthermore, these experiment results indicate that the maximum compression stresses increase rapidly with the increment of curing ages while the cracking stresses have subtle differences.

In this paper, high-density resistivity of the north bank of Huangming Reservoir in Yuyao City was detected by the Wenner device. Through the detection of multiple sections in the longitudinal and transverse sections, the distribution rules of the rock mass of the slope are summarized, and the weathering grade of the rock is judged. The research results will provide a strong basis for the disaster prevention and mitigation work in the later period.

The mass fraction of kaolin was 3%, 5%, 7%, 9%, 11%, 13% and 15%, respectively. The three indexes of kaolin were tested. The results showed that after kaolin was added, the penetration, softening point, ductility and deformation resistance of matrix asphalt were decreased. In addition, indoor adhesion test was conducted to analyze the adhesion of modified asphalt of granite and limestone with different kaolin contents, and the adhesion of modified asphalt in distilled water and 5%NaCl solution were compared. It is found that adding kaolin can improve the adhesion between asphalt and aggregate. Through a comparison of properties, it is suggested that the content of kaolin should be 5% rather than more than 7%.

With the development of computer technology, computer-aided diagnosis has been greatly improved. Computer-aided diagnosis can help doctors diagnose with medical imaging and other technique. Cardiovascular disease(CVD) lead to death with high probability. The computer-aided toward blood vessel is necessary. In this paper, we propose a novel method for 3D reconstructing of blood vessels. We calculate the volume data of blood vessels using an implicit modeling method based on the scanned blood vessel images, and establish a 3D model for blood vessels. Compared with existing methods, our method can obtain the surface and internal information of blood vessels accurately based on the implicit function method. The experimental results reflect that our method can implement 3D reconstruction of blood vessels with high accuracy and smoothness.

In this experiment, the carp scale as raw material, containing calcium and protein impurities in the scale and so on, respectively by two sodium EDTA (EDTA two sodium, EDTA) and sodium chloride solution (sodium chloride, NaCl) solution and its removal, scale collagen protein extraction and design. By using different single factor test the 4 factors determine the extraction of collagen during the experiment the optimum extraction process, the 4 factors are the enzyme (pepsin) dosage, ultrasonic time, solid-liquid ratio, extraction liquid (acetic acid) concentration of glue. The optimum extraction process for raw protein ultrasonic time 200Min, enzyme dosage 300mg/g, extraction concentration of 0.3 mol/L, the ratio of material to liquid 1:40 (g/mL), in this condition, the extraction rate was 28.7. By UV spectrophotometer identification, the material in the 230nm have obvious absorption peak, so the test the material of collagen.

The task of front obstacle detection in unmanned driving is to allow the model to accurately detect types and corresponding position of each object. Complex true driving environment, multiple types of objects within range of visibility and multiple examples are challenges for detection. Particularly in unmanned driving field, not only the detection precision shall be pursued, but also the detection speed shall be guaranteed. This paper puts forward the front obstacle detection method based on YOLOv3. It establishes a Tensor Flow+Keras framework on GPU server cluster, designs and realizes YOLOv3, and realizes calibration and classification of front obstacles through training and optimization of the model on the data set. This method supports over 10 object types. Experimental results show validation set Loss (VAL Loss) reaches 21.206, mAP reaches 78.64, and detection speed reaches 30 FPS. The study provides theoretical basis for obstacles detection of automated vehicle in complex environment.

In order to better improve economical efficiency, the newly built supercritical units mostly adopt more fuel-saving ignition mode, but in the initial startup stage, the parameters of unit and boiler are not compatible. This paper carries out study and analysis on parameters in the initial startup stage, and optimizes all parameters by adjusting startup feed-water quantity, fuel quantity, air volume and ratio for several times. With favorable effect, this paper may be used as good reference for other similar units.

Because of the increasing incidence of coronary artery disease, the use of cardiovascular stents is gradually increasing. In percutaneous coronary intervention, advantage of bioresorbable stent is that the stent does not remain in the human body after completing the necessary mechanical support to ensure the blood vessel open, and finally degrades into harmless molecules. Compared with bare stents, which require long-term retention in the body, the incidence of restenosis in stent or late stent thrombosis was lower. Current biodegradable stent mainly include polymers, biodegradable stents and metal alloy stent. Magnesium-based stent degradation and its copolymers are used in the application of biological absorbable stents and attract the attention of researchers.

The paper introduces the realization process of a plasma burner in a middle storage-type lean coal-fired boiler from the aspects of cold leveling test, relevant logic optimization, cold pulverizing method, online monitoring of relevant parameters of the pulverized-coal feeding system and combustion adjustment and proposes corresponding measures for some problems in the plasma burner arising during adjustment. In the case of appropriate coal quality, the successful application of plasma in key links like steam blowing, air-cooled island hot flushing, and no-load test has saved a lot of fuel, presenting a good economic efficiency.

In order to improving ultraviolet radiation (UV) aging resistance of polypropylene (PP) and expanding its application range, it is necessary to research the rule and mechanism of PP in UV aging process. On the base of Fourier transform infrared spectroscopy and differential scanning calorimetry characterization, the variations of structure parameter (crystallinity and carbonyl index) of homo-PP corresponding to different UV aging time were calculated and analyzed. Combined with tensile strength testing, the influences of both crystallinity and carbonyl index on tensile strength in UV aging process of PP were researched. Then the relationship formula between tensile strength and structure parameter was constructed based on linear relationship, and the quantitative structure-activity relationship of PP during UV aging was analyzed. The results show that, with the extending of aging time, the influence of crystallinity on tensile strength of PP declines, while that of carbonyl index is on the contrary. During UV aging, the tensile strength of PP rises slightly with the increase of crystallinity first, then acceleratedly declines for the increase of carbonyl index. It should be noted that, although the crystallinity of PP begins to decline after 100 h UV aging, its effect to tensile strength can't be ignored while aging time is less than about 300 h.

In the inspection and identification of engineering structures, it is often necessary to understand the force state of the main ribs of the components. Based on the structural performance test, the relationship between the bending moment of the concrete beam (or slab) in the elastic phase and the plastic phase and the strain of the main rib is analyzed. The initial moment of the main beam of the concrete beam (or slab) is proposed by the bending moment increment method. By adding a small amount of bending moment and measuring the strain increment of the main rib, the initial strain of the main rib of the flexural member is estimated to better understand the structural performance of the member. During the bending moment increment detection process, the increase in bending moment is small and does not adversely affect the concrete structure.

Conventional and nanostructured ZrO₂-7wt.%Y₂O₃ thermal barrier coatings (TBCs) were prepared by plasma spraying technology. Microstructure and hot corrosion resistance of two TBCs in 75%Na₂SO₄+25%NaCl (mass fraction) mixed molten salt under 850 °C were compared. Meanwhile, hot corrosion failure mechanisms of TBCs were investigated. Results demonstrated that both conventional and nanostructured TBCs were typical lamellar stacking characteristic. However, compared with conventional TBC, the nanostructured TBC presented the base phase which is gained from recrystalization of fully melted nano-particles as well as the embedding phase of partially melted nano-particles. The nanostructured TBC has lower porosity and higher density. For both conventional and nanostructured TBCs, hot corrosion failure is caused by partial transformation of tetragonal phase (t-ZrO₂) into monoclinic-phase (m-ZrO₂) martensite as a response to the consumption of the stabilizer Y₂O₃. However, the nanostructured TBC generally has lower degree of hot corrosion and better protection to the metal bonding layer and matrix compared with conventional TBC.

The concept of win-win cooperation emphasized by partnering mode can promote all parties of the project to achieve win-win, and can effectively reduce the conflict and controversy caused by the confusion of work interface, poor communication and coordination and other issues in the project. In this study, first of all, rough set method in conflict analysis theory is used to reflect the conflict degree of each participant on a certain problem and the main conflicts in the problem. Then, combined with the conflict level division and conflict ejection mechanism in partnering mode, a conflict handling mechanism of EPC project based on partnering mode is constructed, which provides a theoretical basis for conflict handling of EPC project According to and practical guidance.

This paper introduces a detection method that uses a white-light interference microscope to scan along the circle of latitude line to detect defects on the entire surface of microsphere with a diameter of 2mm. The surface of the microsphere is exposed under the white light interference microscope from the top to the equator in turn according to the annular belts of different latitudes to make the acquired image cover the entire surface of the ball. The topography data is processed, the defects are identified, and the number of defects of different horizontal and vertical sizes is counted, so as to achieve the quantitative evaluation of the surface defects of the small ball.

In order to explore the feasibility of testing the compressive strength of sleeve grouting material in practical engineering by the Leeb hardness method, we made 12 groups of standard specimens out of grouting material, analyze the correlation between surface hardness and compressive strength of grouting material by experiments. Experimental results show that, The surface hardness test results of the sleeve grouting material are in accordance with the normal distribution. With the guarantee rate of 95%, eliminating the extreme value in the hardness test data can significantly reduce the discreteness of the data and improve the accuracy of the calculation results. There is a significant correlation between surface hardness and compressive strength of grouting material, the best fitting effect is by using exponential function, the average relative error is 7.45%, the relative standard deviation is 8.61% and the correlation coefficient is 0.864. The experimental results provide a reference for testing the compressive strength of sleeve grouting material by the Leeb hardness method.

In this paper, AlN complex ceramic coatings are prepared on the surface of 1060 Al by micro-arc oxidation (MAO), selecting the current density, the AlN additive amount and NaOH concentration as parameters. In order to analyze the influence of three parameters on comprehensive performance of the ceramic coating, nine models are designed via a L₉(3³) orthogonal array. The surface morphology and phase composition of the MAO complex ceramic coatings are examined by scanning electron microscopy (SEM) and X-ray diffraction (XRD) respectively. Roughness, coating thickness and bonding strength of the Al substrate to the MAO complex ceramic coatings are tested and analyzed respectively. We present the results as follow: a the current density has a relatively large influence on the roughness of the coatings, the minimum roughness of the coating is 0.034 μm. b NaOH solution concentration has greater impact on the bonding strength of the coatings. The maximum critical load is 29.375 N. c AlN additive amount has the largest impact on thickness and thermal conductivity of the coatings. The biggest thickness is 15.4 μm, and the maximum thermal conductivity is 3.9436 W/(mK). The corrosion resistance of the MAO samples is obviously improved.

Nano-materials fabricated chemically or biologically are usually kept in liquid or solution. The characterization of these materials, especially about their dimensional scales, is important to the study of the materials as well as their further application. In this research, the dimensional features of a typical biomacromolecule nano-material are characterized by AFM in air mode and the uniformity is analyzed. Some dry samples are prepared for air mode measurement. The height of sample structure, h is (2.252±0.021) nm. The respective deviation of the overall structures' heights and of the section heights in single structure is 0.023 nm, and 0.021 nm, which shows ideal homogeneity of the material and good uniformity of the structure.

In this paper, based on the concept of integration of phosphine ligands and ionic liquids, a new phosphine-functionalized polyether imidazolium ionic liquid [Ph(EO)₁₆MIM]₃[P(m-C₆H₄SO₃)₃] was designed and synthesized. The phosphine-functionalized ionic liquids have the characteristics of both phosphine ligands and ionic liquids. They can be used not only as ligands to complex metal rhodium, but also as catalyst supports. Based on this unique property, we constructed a Rh-[Ph(EO)₁₆MIM]₃[P(m-C₆H₄SO₃)₃] biphasic catalytic system to catalyze the hydroformylation of 1-octene. The results show that the catalyst is not only easy to separate and recover, but also can obtain 2717 h⁻¹ TOF value within 0.5 h. When the catalyst was reused for 15 times, there was no obvious deactivation of the catalyst, and the total conversion number TTON was as high as 43288.

Due to the particularity of the pumping of the compound paste slurry material, the traditional stress analysis method is difficult to apply. Based on the cylindrical hole expansion model of compacted grouting, the theoretical formula of the compacted grouting displacement field of soil is established on the basis of simplified body strain. Based on the displacement field theory, the analytical solution of the soil permeability coefficient after grouting and compaction is established according to the compressed porosity and Konzeny-Carman equation. The field test of compact grouting was carried out, and the water injection test was used to obtain the change of permeability coefficient before and after grouting under different grouting intervals. The obtained results are in good agreement with the theoretical solution and have certain engineering guidance significance.

Monomer 2,2'-bis [4-(5-amino-3-methyl-2-pyridoxy) phenyl] propane was successfully synthesized by 2-chloro-3-methyl-5-nitropyridine and bisphenol A, and the structure of pyridine diamine monomer was confirmed by ¹HNMR. A series of polyimides were prepared by two-step polymerization of the pyridine diamine monomer with five aromatic dianhydride monomers. The results show that the polyimide films had good thermal stability and mechanical properties. Tg was 236-300°C in DSC test and 240-299°C from DMA test, T5% and T10% weight loss at N₂ were 470-492 and 499-515°C, respectively. Moreover, the polyimide films showed outstanding mechanical properties with tensile strength of 72-90MPa, tensile modulus of 1.8-2.4Pa, and breaking elongation of 5-12%. The cut-off wavelength was 338-399nm.

As a major country with coal as its main energy source, China has great pressure on the production and reuse of coal fly ash. In this paper, three kinds of original low calcium fly ash from different regions were divided into five bulk density particle groups, < 1 g/cm³, 1-2 g/cm³, 2-2.5 g/cm³, 2.5-2.89 g/cm³ and > 2.98 g/cm³. The results showed that the bulk density of fly ash particles was mostly concentrated in 1-2.5 g/cm³. There were significant differences in the chemical composition and activity of the particle groups with different bulk density, but no consistent changes were observed. The correlation degree between acid oxide content and activity was significantly higher than that between bulk density and activity, indicating that acid oxide content had a significantly higher influence on activity than bulk density.

Ureteral stent is one of the commonly used instruments in urology, and its clinical efficacy is confirmed. However, there are also a series of complications or deficiencies, including infection after catheterization, formation of stent shell, and secondary endoscopy for tube extraction. The biodegradable ureteral stent can play the same role as the double-J tube, and it will be completely degraded after a certain time. The degradation fragments will be discharged with the urine, and the physiological functions of the ureter will not be affected. At the same time, there is no need to perform a second cystoscope for tube extraction. Therefore, patients do not have to undergo an invasive operation again, so as to alleviate the pain of patients and save time and cost.

In order to realize precise positioning with remote observation and control of the food delivery robot in the room. This paper designs a indoor robot positioning information system based on the DW1000 module and the network module of ESP8266. The improved TWR algorithm is used in the system to avoid the problem of clock out of sync among the base stations and improve the clock offset error of the base stations. The simplify Toa Algorithm makes the system locate quickly and accurately. At the same time, the wireless ethernet module ESP8266 is used to transmit the position data and the status information to the remote server which is easy to view the real-time position state and control the robot movement. The system is an embedded wireless interconnection system, which can satisfy the indoor robot positioning and information transmission, and realize the remote control of the robot.

In order to validate the damping effect of metamaterials, the low frequency damping effect of the spring oscillator metamaterials was used to test the vibration of thin plates. And the damping effect was compared with the viscoelastic damping materials. The results show that, with lighter additional weight, the low frequency damping effect of the spring oscillator metamaterials for plate was better than that of the viscoelastic damping materials.

A field experiment was conducted to test the influences of several doses of Yuetian brand soil conditioner on dry matter output and heavy metal concentration of rice, and the influence of basic physical and chemical properties of soil. The outcomes indicated that the dry matter output of rice was increased by 1.29%∼23.42% by using different dosage of Yuetian brand soil conditioner compared with no soil conditioner treatment (treatment 1). The effect of Treatment 5 (1875kg/ha) was better on enhancing dry matter output of rice. And they could reduce Cd and Pb concentration of rice by 17.32%∼60.17% and 11.47%∼64.68%, respectively. Ttreatment 5 and 6 had a better effect on reducing heavy metal concentration in rice, and could increase the pH of the soil by 4.7%∼37.2% and decrease the exchangeable acid (latent acid) by 3.5%∼55.9% , the concentrations of soil effective Cd and Pb were reduced by 9.28%∼49.48% and 8.34%∼24.40% , respectively.

With the development of economy and science and technology in China, pile group foundation is widely used in various constructions to meet the complex engineering conditions. Pile foundation is often affected by inclined load (i.e. horizontal load and vertical load). The behavior of pile under inclined load is much more complex than that under single load. In engineering, the vertical component and the horizontal component of the pile top are often calculated separately, and then modified. This method is only suitable for small deformation, which is different from the actual situation. In this paper, taking the four pile foundation as an example, through the rotation of the cushion cap (the column does not rotate) and the column eccentricity, the force of the foundation pile can be relatively uniform. At the same time, the design calculation of the group pile foundation under the oblique load can be approximately equivalent to the design calculation of the group pile foundation under the single vertical load. When the force distribution on the pile top is relatively uniform under the same inclined load, the eccentricity of the column has a linear relationship with the depth of the cap. Through ABAQUS numerical simulation analysis, the correctness of the above understanding is verified.

A new laser induced ultrasonic transducer (LIU-T) based on photoacoustic effect was presented. Compared with traditional piezoelectric transducers, Liu-T reduced electromagnetic interference and improved the sound pressure signal. Firstly, Liu-T was made and its sound field characteristics were characterized. The experimental results have shown that the sound pressure of this transducer can reach 3.9MPa and the frequency range was 2.5MHz-7.9MHz. Then an experimental platform for magneto-acoustic-electrical tomography(MAET) based on Liu-T was designed and built. Furthermore, B-scan images of abnormal copper plates were obtained by B-scan, which further indicated that LIU-T would play an important role in the field of NDT and biomedical imaging.

Hydrochloric acid, especially when contains a certain amount of FeCl₃ (or oxidizing salt such as copper chloride), is highly corrosive to chemical equipment, which will lead to problems of malignant destruction and failure. Therefore, the correct and rational selection of material is essential for the production and use of hydrochloric acid. In this paper, from the corrosion characteristics of hydrochloric acid and the factors affecting the selection of hydrochloric acid resistant materials, the metal materials resistant to hydrochloric acid corrosion are reviewed, which provides a scientific basis for material selection of alumina extraction from fly ash by acid method and other similar working conditions.

In view of the complex terrain, low level of mechanization and intelligence in hilly region, a human-computer interaction system was designed for electro-hydraulic hitch control system of tractors in hilly region. According to the actual functional requirements of electro-hydraulic hitch control system of tractors in hilly areas, human-computer interaction interface was designed in flash environment, and CAN communication module in Human-computer interaction system was designed in Flash Develop environment. Finally, a hardware test platform of the human-computer interaction system was built in the room for laboratory tests. The results showed that the human-computer interaction system can meet the working requirements of the electro-hydraulic hitch control system of tractors in hilly areas.

Laser ultrasonic technology has been widely used in the field of NDT due to its advantages of non-contact and high resolution. The sensitivity of laser ultrasonic detection signal is not only related to laser excitation parameters, but also to the thermal absorption of the target. Therefore, once the measured target is determined, the sensitivity of laser ultrasonic detection based on thermoelastic effect is limited by the damage threshold of the measured target. In order to improve the sensitivity of the detection signal under the damage threshold, it is a good choice to add a layer of enhanced medium with high photoacoustic conversion efficiency on the surface of the laser target material. Based on this, a method based on CB(carbon black)-PDMS composite film was proposed to enhance the sensitivity of detection signal.

The research status of photocatalytic and thermal insulation coatings at home and abroad was summarized. The different types of photocatalytic coatings were summarized. The factors influencing the photocatalytic coatings, such as the activity of photocatalytic coatings, the load of photocatalytic coatings, and the dispersion process, were expounded. The type and property of insulation coatings and the effects of fillers on the properties of insulation coatings were summarized. At present, the primary problem of photocatalysis and heat preservation and heat insulation building coatings in China is lack of research and development of dispersants and composite materials. The evaluation system of photocatalysis, heat preservation and heat insulation need to be improved. It is of significance for the multi-functional coatings with the performance of luminescent catalytic insulation.

White light interferometer (WLI) is one of the common machines that are used to characterizing surface structures. The indication errors of WLI are key metrologic characteristics, which may affect evaluation result of WLI. In this paper, a two-dimensional micro/nano pitch (2D pitch) standard is introduced to calibrate the lateral indication error of WLI. The calibrating experiments are carried out in four measurement positions. The results and the uncertainty is anlysized. And the expanded uncertainty of WLI in lateral measurement (x50) is evaluated as tens of nanometer.

Steel cable bridge is a kind of flexible suspension bridge with steel wire rope as the main stress components. It has the advantages of low construction cost, short engineering period, reliable structure, simple construction, etc., and has been widely used in driving and walking passages. In this paper, a 110m steel cable bridge supporting the belt conveyor is as an example, the finite element software Midas/civil is used to establish a spatial calculation model, and the cable force and displacement are calculated and analyzed. The results and calculation process can provide theoretical basis and practical experience for the design of steel cable bridge for belt conveyor.

The brewery fermentation process has inherence characteristics of multivariable, seriously nonlinear, uncertain, time-variant and large delay. The given process parameters aren't traced very well. In this paper, segmented control strategy is used, which is dividing the ferment process into pre-fermentation and post-fermentation period. In each ferment period, strategy of fuzzy neural control based on Multivariate –decoupling is adopted and simulated in MATLAB, the results show the strategy's validity and practicability in controlling beer ferment.

It is hardly to carry out large-scale shaking table test of entire structure for the high cost of model construction and the capability limited of shaking table in the field of civil seismic research. In this paper, a shaking table substructure test method loading by inertial mass was studied, and the inertial mass parameter was designed based on the principle of frequency equivalence. Numerical simulation was performed and the applicability of the test method was analysed. A shaking table test model of 5-stories steel frame model and the substructure test loading by inertial mass have been carried out. Result shows that the phase of the time history curves could in good agreement, but the peak responses of the substructure model were larger than the entire structure tests. So, the shaking table substructure test loading by inertial mass based on the principle of frequency equivalence is not suitable for the structure with uniform distribution of mass and stiffness. Finally, it has been verified that the substructure test based on the principle of frequency equivalence is suitable for the structures with large rigidity and concentrated mass by analysing of another example. The research of this paper could be referred for substructure test of large and complex structure.

Along with the wide spread and deep penetration of STEM theory in China, the imperative task is to develop compatible courses with thorough interdisciplinary integration. The aim of this paper is to present a project-based learning (i.e., PBL) case study for college mechanics courses, in terms of the global structure, target analysis, activity design, comprehensive evaluation and implementation process. The features of this study can be summarized as follows. Firstly, in combination of students' activity experience, the content of this study derived from a real-life problem truly realizes the interdisciplinary integration. Secondly, other than simply mixing the subject knowledge with hands-on skills, the objective of this study attaches specific importance to the stimulation of students' interests and potentials in learning science and technology. Thirdly, the genuine research resources are adopted for implementing the project during the whole course. Fourthly, in order to urge students to form deep self-analysis, the course evaluation is composed of process and result assessments. In all, this study provides a reference for the development of an integrated STEM course. It may contribute to the acceleration of training professionals and construction of building innovation-oriented country.

The Buckling-Restrained Braces is an excellent seismic energy dissipator. In this paper, the effects of the three core width-thickness ratios, gaps, and constraint ratios of the Buckling-Restrained Braces on the seismic performance of the Buckling-Restrained Braces are studied and modeled and analyzed by ABAQUS The simulation results show that the Buckling-Restrained Braces has the best seismic performance when the width-to-thickness ratio is 10-16; when the gap is 1-2mm, the Buckling-Restrained Braces has the best seismic performance; when the constraint ratio is about 5, the Buckling-Restrained Braces The best seismic performance.

Bismuth oxides with a micro porous structure were prepared by a simple combustion reaction between oxidizer (bismuth nitrate) and fuel (citric acid). These porous bismuth oxides were prepared at different values of the stoichiometric coefficient. The as-prepared products were characterized by X-ray diffraction (XRD), and scanning electron microscopy (SEM). The results show that many pores distributed in tetragonal bismuth oxides (β-Bi₂O₃) granules which have varied crystallinity and particle sizes at different oxidizer/fuel ratio. Increasing the fuel concentration improved the crystallinity and purity of β-Bi₂O₃. A further calcination could also increase the particle size, crystallinity and transform the phase structure from β-Bi₂O₃ to pure α-Bi₂O₃.

With the rapid economic and social development, the construction of urban underground rail transit is in full swing, and even many second and third tier cities are starting to build, In order to control the environmental impact of the excavation team and control the deformation, this paper takes a deep foundation pit project of a station in Wuhan Metro as the research object, combining with theoretical analysis, field monitoring and Midas GTS Nx numerical software simulation and other methods are used to discuss the ground settlement around the foundation pit, the impact on the adjacent bridge pile foundation, and the deformation control analysis.

Aims to remove oil and anionic surfactants in domestic wastewater on the ship, the micro-electrolysis treatment with fillers was applied in this paper. The effect of the system on the removal efficiency of oil and surfactants was studied, and the optimal operating conditions were determined. The results show that the removal rate of oil and LAS is 81.2% and 77.5% with safe effluent quality under the optimal working conditions.

This paper investigated the temporal variations of the phytoplankton biomass along 10 years in the Nierji reservoir located in the northeast of China. The factor analysis was applied to identify significant influencing factors of algal growth. The results demonstrated that total nitrogen (TN) was strongly correlated to phytoplankton in the middle of the reservoir and total phosphorus (TP) showed the same pattern in the outflow of the reservoir. In contrast, water transparency was weakly affected by the production of phytoplankton. Besides, there were annual variations observed for the ratios of TN to TP, while 54.02% of the collected data indicated that TP was limiting the phytoplankton.

An extensive range of studies have been conducted on coal-fired power station CCP's in order to investigate their geotechnical properties for construction of structural fills. Many such researches are based on the performance of fresh ash, however very few have studied their behavior after a long term service period. There exists a rarely discussed CCP ash that was identified in this investigation. Understanding of the long term behavior of CCP's is essential for motivation of their use in structural fills. This ash was used as an alternative to natural soils for the construction of transport embankment layerworks in countries such as the USA and South Africa. Several decades later after its use in railway embankment fills, the geotechnical properties are evaluated in this study by method of experimental investigation. A series of tests (particle size distribution analysis, specific gravity, compaction and permeability) were carried out with the objective of characterizing the material and determining the shear strength behavior by direct shear test. Test results revealed that the ash is comparable to a granular soil. The direct shear test results revealed that the ash exhibited a significantly high shear strength by the internal friction angle of 51.86°. Furthermore, a reversal and re-shearing of the sample was completed and presented a slightly lowered residual friction angle of 49.37°.

TC21 alloy is a new two-phase titanium alloy with good comprehensive properties of high strength, toughness and damage tolerance. The isothermal thermal compression deformation test of TC21 titanium alloy is carried out on the Gleeble-3500 thermal simulation test machine. Based on the stress-strain data at different temperatures and strain rates, the constitutive relation model of TC21 alloy was established by using BPNN(Back Propagation Neural Network), which has high prediction and generalization ability, and the predicted flow stress value is very close to the experimental data.

Ureteral stent has become a necessary consumptive device in the urinary system in the routine clinical practice. However, indwelled stent can cause complications such as hematuria, stone formation, and bladder irritation, et al. In recent years, the use of coating has become an important research direction to modify the surface of the stent and to reduce complications. In this paper, polycaprolactide lactide copolymer was used as coating material, uniformly coated the polymer on ureteral stent surface using solution impregnation method, so as to prepare ureteral stent with a certain coating thickness, and study the degradation behavior of coating in urine.

Using nonequilibrium Green's functions in combination with density-functional theory, we investigate the electronic transport properties of carbon chains covalently connected with two bear armchair graphene electrodes. The results show that the transport properties are obviously dependent on the odd and even length chains located between graphene nanoribbons. For graphene nanoribbons connected to the chain with even chains, the negative differential resistance (NDR) is also observed in the I-V curves. The reason is that the even-odd effects are related to the connection structure between electrodes and carbon chains.

Due to machining accuracy, installation error and other factors, the rotor has various eccentricity, which will cause adverse effects on the operation of generator of certain mobile power station and even lead to all systems failure. In order to investigate the generator rotor's vibration characteristics, taking a military mobile power station generator as the research object, a Jeffcott rotor model is established which considering rotor eccentricity with cubic term in this paper. It is consistent with the Duffing equation in any transverse motion equation. It is simplified to Duffing equation for solving. The analytical solution is solved by the Runge-Kutta method. By studying the effects of various types mechanical parameters on the transverse vibration, the rotor system's main resonance is studied: the stiffness has extremely few effect on the amplitude change, however, the stability of the system changes greatly with them. While the amplitude only changes and the mass eccentricity reaches a certain value, the rotor system is prone to rub. Resonance amplitude, the response and phase of the system are all affected by the damping, therefore, damper is one of the most effective ways to suppress vibration of generator.

Buffer analysis is one of the most important functions in GIS spatial analysis, which is used to establish the scope of influence around spatial entities. The conventional buffer radius is fixed. However, in practical situations, the buffer radius should be dynamically adjusted by considering the specific environment of the space entity such as nature and socio-economy condition. Therefore it is able to achieve accurate and scientific spatial analysis, which aims to provide efficient decision-making services and intellectual support for the construction of the social economy and the ecological civilization. In this paper, based on analysis of the shortcomings of conventional buffer, several special buffers are discussed and the uncertain buffer radius is calculated under different conditions. Finally, an example is harnessed to illustrate the existence of uncertain buffer radius.

A dimethyl ether (DME) pre-mixing system was installed on a 2105 diesel engine for realizing pre-mixed charge compression ignition combustion mode. Combustion processes of a PCCI engine fueled with DME/diesel under various DME pre-mixing ratios were investigated in this paper. The results showed that the heat release process showed three stages with port induction of DME. As the DME pre-mixing ratio (PR) increased, the peak value of cylinder temperature and pressure raised and the corresponding crank angles advanced. The start of combustion (SOC) moved forward obviously and the duration of combustion extended; the peak value of the pressure rise rate reduced first and then raised. The results in this paper provided a reference for the combustion process optimization of DME/diesel PCCI engine.

DC Transformer (DCT) is a new type of intelligent power electronic device using power semiconductors and high-frequency transformer to realize power conversion. Multi-ports DCT has broad applications in DC distribution networks. In this paper, the power transmission characteristics of the phase-shift controlled multi-ports DCT are analyzed. The non-linear coupling characteristics of the output power at different ports are also studied. The small-signal dynamic coupling model of the multi-ports DCT is established. On this basis, a feed-forward term is introduced and constructed in the closed-loop voltage control system. The theoretical analysis shows that the feedforward term can decouple the output voltage of different ports of the multi-ports DCT. The correctness of the feed-forward control method is verified by simulations.

PMSM servo system has nonlinear, parameter time-varying, load disturbance and other issues. In the face of these problems, traditional PI control strategies often fail to achieve ideal parameter tracking and load immunity, showing a large degree of limitations. Aiming at this kind of problem, this paper designs a fuzzy PI control method combining PI control and fuzzy control, and uses the vector rotation control method of current speed double closed loop to drive the permanent magnet synchronous motor for control. Finally, the traditional PI control system and fuzzy PI control system simulation model are built in Matlab/Simulink environment. The simulations were carried out in three cases of high speed, medium speed and low speed, and the speed and current waveforms of the two control methods were observed. The simulation results show that the fuzzy PI control system can increase the response rate, reduce the overshoot of the speed and reduce the current fluctuation in the full speed range. The robustness of the system is improved, the adaptability of the system to load changes is enhanced, and the correctness of the theoretical analysis is verified.

The nuclear support, which is used to support pipe or equipment with nuclear safety level, is of great importance for nuclear power plants. In this work, we studied that the door type nuclear support was transformed to disassemble easily by installing bolts. The 3D models of nuclear support before and after transformation were established in ANSYS Workbench software. With the reasonable setting of the contact conditions and boundary, the deformation, stress and natural frequency were calculated in ANSYS Workbench by using the finite element method. The results show that bolted connections will lead to the loss of stiffness of support and natural frequency decrease. The order natural frequency of the support decreases with addition of the thickness of plates and the bolt circle diameter has little effect on global stiffness of the support. The finite element analysis results provide reference for the transformation design and optimization of nuclear support and have practical engineering value.

In order to improve the efficiency of car wash and reduce the labor intensity of car washers. According to the process flow of automatic car washing and its characteristics of simple operation, high efficiency, convenience and stable operation, an automatic car washing control system based on PLC is designed, and WinCC configuration software is selected as the upper computer as the man-machine interface design. The simulation results show that the system has strong stability, improves the automation of car washing and meets the actual needs.

The high-precision identification of the non-intrusive residential electrical load is an essential technology to realize the intelligentization of the power grid. Due to its low input cost and easy maintenance, this technology has received much attention at home and abroad. In order to improve the accuracy of load identification, this paper proposes a non-intrusive residential electric load monitoring equipment based on system on a programmable chip (SOPC), which is focused on hardware system design, characteristic parameters optimizing and BP neural network algorithm optimization. The feasibility of the system was verified by experimental simulation and tests. The results of experiment show that the method used for hardware design can not only improve the speed of system and most closely match the actual running state of electrical appliances in testing circumstances, but it can also realize the function of load identification rapidly and accurately under the condition of the given residential electricity.

Multipath effects usually occur in information dissemination, which leads to inter-symbol interference and affects the quality of communication transmission. This paper uses an adaptive equalizer to achieve channel equalization and eliminate inter symbol interference, and develops and verifies it on the FPGA using the ISE suite. Compared with the equalizer output error signal calculated on the MATLAB software, the calculation results of the two platforms are basically the same, which confirms that the design is feasible. The FPGA-designed equalizer implements hardware acceleration and is more suitable for high-speed real-time signal processing. After the data passes through the adaptive bit equalizer, the signal-to-noise ratio is improved, thereby reducing the bit error rate and verifying the relationship between the bit error rate and the signal-to-noise ratio.

The newly built unit in certain power generation company adopts storage pulverizing system and 16 sets impeller coal feeder. The pulverized coal feeders suffered unstable feeding frequently during infrastructure debugging, leading to large fluctuation of furnace negative pressure, steam temperature and load, and affecting safe and stable operation of the unit. This paper deeply analyzes the causes of congested feeding of pulverized coal feeder, formulates corresponding countermeasures from aspects of cleaning, installation and operation adjustment of pulverizing system, and guarantees stable operation of the unit through optimization logics and operation method. This paper provides references for actual operation and solution of similar problems in power plants.

A new-type of multi-layer percolation equipment was developed and utilized to extract effective component of a certain traditional Chinese medicine. Porosity and penetration rate of 100-mesh medicine powders were measured respectively. Moreover, the superiority of the performance of such equipment over single percolation method and repercolation method was studied where the total solids content in percolated fluid was utilized as the evaluation index. The results show that for 100-mesh medicine powders, porosity and penetration rate of medicine powder layer both decrease with the increase of particle layer height; total solids content in percolated fluid of 100-mesh medicine powders is high, and the new-type multi-layer percolation equipment has the best performance in the extraction of effective component in the medicine.

Through investigating the sinh-Gaussian beam with complex beam parameters, it is the first time to find that such beams can carry vortices and exhibit dark hollow intensity distributions when the complex beam parameters are sufficiently small. A closed-form propagation equation for sinh-Gaussian beams through paraxial ABCD optical systems is derived based on the Collins formula and illustrated with numerical methods. It is shown that the perfect hollow configuration can retain a quite long propagating distance under small complex beam parameters. The analytical discussions affirm the numerical conclusions.

A method of SOPC implementation of digital frequency meter is presented in this paper. In the method, Encapsulated AXI IP core for frequency measurement and duty cycle measurement are configured with the embedded soft core MicroBlaze processor. The parameter measurement of the digital frequency meter is implemented by FPGA logic resources, and the measured data are transmitted to the soft core processor via AXI bus. The computation, control and display is completed by Microblaze soft core. The system is verified and tested on the Basys3 board card launched by digilent company. The results show that the system has the advantages of accurate measurement, good stability, simple scheme and low cost.

In this paper, it is studied the passive control of a class of fuzzy systems with state uncertainty and time-delay. First, a class of nonlinear systems is described by using T-S fuzzy model with uncertain items and time-delay ; Secondly, by using the linear matrix inequality technique(LMI) and designing the state feedback controller, we can obtain the feedback gain matrix , the robust stability of the closed-loop system is achieved by using Lyapunov's stability theory, at the same time, it is realized the sufficient conditions for passive control of the system. Finally, the feasibility and validity of the results are verified by simulation examples.

Under different height-to-diameter ratios (H/D), the gas-solid mixing characteristics in a fluidized bed filled with Geldart B were studied employing the Eulerian-Eulerian two-fluid model. Researches showed that with the H/D increased, the larger bubbles were generated and significantly affected the gas-solid mixing process. And at H/D=1.5, the radial particle velocity distribution had a relatively smaller fluctuation at different axial heights and a higher particle fluidization quality was obtained. Therefore, it can be concluded that under given conditions, a proper H/D is essential for obtaining a good gas-solid mixing in a fluidized bed.

This paper proposes a photovoltaic grid-connected inverter based on a Z-source NPC three-level topology to achieve buck-boost control and improve the transmission efficiency of the system. In view of the instability of the output power of the photovoltaic system, which affects the output of the grid-connected inverter, this paper proposes a dual closed-loop sliding mode control strategy. The DC bus voltage outer loop of this strategy adopts traditional sliding mode control and grid-connected current The inner loop adopts PI control to weaken the system chatter. The anti-interference ability of photovoltaic grid-connected system and harmonic content of grid-connected current were studied through the Matlab/Simulink simulation platform. The results show that the control strategy can effectively improve the robustness of the system and reduce the harmonic content of grid-connected current.

The axial solid concentration distributions were measured by using pressure inspection instrument in a glass bead fluidized bed. Set 1-3 belong to single size distribution and Set 4-5 have wide size distribution, respectively. The change trend of axial solid concentration distributions were investigated under different superficial gas velocities, particle size and particle density. The results showed that, with increasing superficial gas velocity, the solid concentrations in dense region decreased, but increased in dilute region. The glass bead particles whose particle size and particle density were smaller had good fluidization quality. It was also found that the joining of fine particles can significantly change the flow characteristics of the fluidized solid particles.

In order to improve the comfort of the air conditioning system in the driver's cabin of a high-velocity train and advance the distribution of air supply, a 3D simulation software is used to establish the model of the air supply pipeline of the driver's cabin. The air flow field and the rationality of the air distribution are analysed accordingly. The results indicate that the structure of the air supply pipe is optimized and the air flow rate in the left and right air chambers is solved and air flow rate in each outlet of the air supply pipe are achieved.

According to the structure of the air channel in the drying chamber of an automobile factory, a model of the original structure of the drying chamber was established. The air flow of this structure is analyzed based on the CFD simulation, and the velocity at specific points of the car shell being dried is also analyzed. The results show that the original drying chamber structure is optimized, the air flow is uniform in the drying air chamber and short circuit of air between inlet and outlet in the drying chamber is decreased.

In this paper, a kind of quasi-zero stiffness isolator with cam-roller nonlinear spring mechanism as negative stiffness mechanism is studied by sinusoidal sweep frequency experiment, sinusoidal constant frequency experiment and half-sinusoidal impact experiment. The dynamic response characteristics and impact resistance of quasi-zero stiffness isolator are analyzed. The experimental results show that when the excitation is constant, the dynamic response of the quasi-zero stiffness isolation system has a response peak, and the response acceleration and displacement all increase first and then decrease with the increase of frequency. When the excitation amplitude increases, the initial isolation frequency becomes large and the effective isolation bandwidth becomes narrow. For the half-sinusoidal acceleration impact with the pulse width less than 10ms and excitation acceleration less than 13.0g, the quasi-zero stiffness isolation system has excellent isolation and cushioning performance.

As the environment protection and energy shortage drawing more and more attention, the development of new energy vehicle, especially electric vehicle has become an important tendency in vehicle industry. Affected by this trend, electric racing events has been held in Formula SAE (FSAE) in China since 2013. To achieve the testing of vehicle control strategy before debugging, enhance develop-efficiency, reduce the risk of vehicle debugging, this paper exploited a cost-effective, perfectly functional and easily operational HIL test platform for vehicle control unit. Firstly, this paper designed a reliable electrical system and safety circuit of vehicle according to racing rules, selected type of drive motor and high voltage battery pack. The software Cruise was used to simulate and check the correctness. After then, the vehicle control unit (VCU) including bottom drive module and control algorithm was built by means of rapid prototyping software development platform. Among this, the dynamic control algorithms as energy regeneration, yaw stability control in switching, and acceleration slip regulation were came up with and employed in the VCU aiming at the characteristics of racing car during contest. At last, the economical and applicable HIL system was studied and developed according to the need of vehicle control strategy testing. The joint simulation of Carsim and Simulink was used to check dynamic control algorithm. The HIL further verified vehicle control algorithm through loading program to VCU. The open-loop check to basically logic algorithm of VCU was conducted by setting component parameters and operating signal of driver in upper machine. The closed-loop test to control strategy of VCU was carried out through loading Simulink model of vehicle to TI 28335 development board.

In recently years, there are more than 70% of power generated by coal station. Based on this, it can be shown that fossil fuels are the main consumption for generating energy. Burning fossil fuels will produce a lot of carbon dioxide and other harmful gas. Moreover, fossil fuels are unsustainable energy, which means it will run out in the future. For avoiding this situation, sustainable energy need to be exploited so that can replace fossil fuels. Currently, there are wind power, solar power, nuclear power in China. Some wind farms already built in different place of China. Due to high advantages of sea, China is paying attention to develop offshore wind farm. This essay introduces details of offshore wind farm including rules of designing facilities and outlook of each level in China.

Reasonable evaluation of the development potential of power grid is an important guarantee for power planning and investment. In this paper, the evaluation index system of power grid development potential is constructed, and based on the operation status of the existing equipment of the power grid, as well as the operation capacity of incremental equipment after the projects under construction and planning are put into operation, the evaluation model of power grid development potential considering the existing / incremental equipment is constructed. Finally, through the verification of Tianjin Power Grid, the index system and method mentioned in this paper are easy to implement and can evaluate the development potential of power grid comprehensively and accurately.

Considering the control delay, grid-current-feedback-active-damping(GCFAD) method can ensure the stability of the system through the reasonable design of parameters, but when the grid impedance changes, the system may be unstable because the LCL resonance peak cannot be effectively suppressed. In this paper, a notch correction strategy is proposed. The amplitude drop characteristic of the notch filter is used to effectively suppress the LCL resonance peak in this paper, so as to ensure that the system has sufficient amplitude margin when the grid impedance changes. The robustness of the system is greatly improved to the grid impedance when the GCFAD method is adopted. Finally, the simulation model verifies the effectiveness of the proposed strategy.

The fluctuation of load and new energy will have an important impact on the operation mode of microgrid. In order to balance the economy and reliability of microgrid, a chance constrained model of microgrid is established firstly. Based on the reliability cost, the operation cost of microgrid under different confidence levels is calculated, and a reasonable confidence level of rotating reserve is obtained. This paper analyzes the impact of energy storage charge and discharge loss and conventional unit start-up cost on the economic operation of the isolated micro grid; for the grid connected micro grid, the economy of its own operation and the effect of auxiliary large grid peak load shedding are taken as the objective function, and the multi-objective programming method proposed in this paper is used to solve the problem. The example analysis shows that the multi-objective programming method in this paper, by combining with particle swarm optimization algorithm, can optimize the weight of different objectives reasonably, which can not only help the large power grid to cut peak and fill valley, but also realize the economy of microgrid operation.

Among the methods used for mitigation of harmonic resonance, modal analysis theory and modal sensitivity can be used to illuminate the nature and properties of this phenomenon, and are thus widely applied. In this paper, an improved modal sensitivity-based method is proposed to reliably suppress the harmonic resonance. First, we show that the current resonance mitigation schemes that are guided by traditional modal sensitivity are not always robust in some cases. Then, through a theoretical analysis, the roots of the shortcomings of the traditional modal sensitivity are determined. The key factor is that the modal sensitivity of a network component is not always constant but tends to vary with adjustment of the component parameters. Finally, to quantify this sensitivity variation and improve the robustness of the analysis results, a second-order modal sensitivity and a critical index are proposed. The results of the test system indicate that the proposed indexes can accurately show the effects of each network component on the resonance, thus are useful in the design of the corresponding mitigation scheme.

Because of its cold light source and adjustable spectrum characteristics, light-emitting diode (LED) is widely used in modern agriculture, it can promote the growth and photomorphogenesis of the plant, also can improve yield and quality. Here, we introduce the advantages of LED over traditional light sources, and analyze the effects of different wavelengths of light on phototrophic plants and the ways in which different light detection systems interact in plants. We also analyze the effects of LED illumination on plants, the response of plants to LED illumination systems. In addition, we summarize the typical LED supplement light devices and intelligent control system in the world, and introduce their working methods and advantages respectively. Finally, we look forward to the future development direction and application prospects of LED with the intelligent control and machine in modern agriculture.

Using virtual impedance technology to optimize the double closed-loop control structure can improve the equivalent output impedance of the inverter to be inductive, improve the power distribution accuracy of traditional sensibility droop control strategy in low-voltage microgrid, and effectively restrain the circulation. But rarely consider the impact of virtual impedance on system stability. Therefore, Derive the transfer function of the three loop control structure including virtual impedance, line impedance and common point voltage, establish a parallel models of inverters with different voltage levels considering virtual complex impedance and simplify the model using Thevenin's equivalent. According to the Nyquist stability criterion Analyze the effect of virtual impedance on system stability under various operating conditions. The analysis results show that the multi-inverter parallel system can maintain stable operation after adding the virtual impedance.

PT ferroresonance occurred frequently in distribution network, which seriously threatened the safety of personnel and equipment of substation, and seriously affected the power supply reliability of distribution network. In order to reveal the real cause of PT ferro resonance, to propose the solutions. In order to solve the problem of PT resonance and provide theoretical basis for PT resonance prevention and control, this paper carried out the analysis of PT resonance mechanism, PT excitation characteristics and PT frequency division resonance self-mechanism.

To reveal the real causes of two explosion faults of potential transformer (PT) on a substation connecting to PV plant, an on-line monitoring equipment with a sampling rate of 40 MS/s for the transient voltage was installed on the secondary side of the PT. By switching the 35kV bus bar onto the main transformer, the switching transient processes on the PT were obtained. The field measured transient process indicated that the switching transient voltage caused by switch operation induced the resonance between the charging circuit and the PT and the resonance may be the direct cause of the PT explosion. The effective measures to suppress resonance in this substation are proposed.

The accurate measurement of over-voltage is very important to ensure the safety and stability of power grid. Therefore, the frequency response characteristics of the over-voltage monitoring device employing capacitive voltage transformer (CVT) under different load conditions are tested and analysed in this paper, and the effect of load change on the frequency response characteristics without and with interior low-voltage capacitor is studied. The results show that: for the case without interior low-voltage capacitor, when the secondary side of CVT is no-load or rated load, the frequency characteristics are roughly the same, but when the load is heavy, the frequency characteristics are greatly different from the situation under rated load. When there is an interior low-voltage capacitor, the presence of the interior low-voltage capacitor has almost no effect on the frequency characteristics of CVT under different load conditions, and there is also little effect on the frequency characteristics of the interior low-voltage capacitor high-voltage side under rated load and no-load conditions.

On the basis of the traditional ABC classification method, this paper determines another standard to subdivide the goods, that is, hierarchical ABC classification method. The calculation shows that, based on the hierarchical ABC classification method, the efficiency of multi-layer horizontal rotating shelves is increased by 26.94% and vertical shelves by 37.25%. The partition design scheme is helpful to optimize the operation efficiency of the rotating shelf warehousing system and verifies the validity and rationality of the partition design.

To meet the demand of high spectrum requirement and high-speed wireless communication in future, millimetre waves (mm-Wave) can play a very important role for it. Millimetre waves starting from 30 GHz and ending at 300 GHz can solve the problems like high throughput, faster data rates and capacity. Millimetre waves can help to achieve higher gain by using high dimensional antenna array technology. Beamforming and spatial multiplexing are very famous techniques that can help to increase the gain when antenna arrays are used. Channel modelling plays a very important role in determining the possibility of deploying the wireless communication system. In this research paper, the major challenges regarding the mm-Wave channel modelling are identified and the statistical behaviour of mm-Wave channel at 28GHz and 73 GHz is explained with the help of NYUSIM software. The power loss, power delay profile and path loss, angle of arrival and departure are simulated in this work. These simulations are performed using multiple antennas configuration along with considering the effect of atmospheric impairments like rain, humidity and temperature.

By applying multi-model adaptive control technology in data fusion of integrated navigation system, the multi-mode adaptive Kalman filter in the integrated navigation system is designed to overcome the problem of filtering accuracy reduction of inertial navigation system due to the changes in the external sensor status parameter with single mode Kalman filter model in the integrated navigation system. The simulation analysis is carried out on the system noise interference vector caused by the change of external environment and the change of the noise interference vector of measurement. The simulation results of a single model filter and the simulation results of multi-model adaptive filter are obtained. Based on the simulation results, it can be seen that compared with the single model Kalman filter, the multi-model adaptive filter is more accurate in the state error estimation of the system, and shows strong adaptability to the changes of the external environment.

In the remote sensing satellite system, the main function of the data transmission subsystem is to receive all the data transmitted by the payload subsystem and then transmit it accurately to the data receiving station on the ground. In the absence of satellite payloads, to meet the requirements of the joint remote sensing satellite test link, we studied and designed a load data simulation source that can simultaneously output four channels of continuous data at different rates, and there are two operating modes to choose from. This design adopts Kintex UltraScale series FPGA with configurable Microblaze embedded soft core as the core controller, and the peripheral circuit includes four pieces of 2GB DDR4 memory, power supply and LVDS interface output. The actual test results show that the load data simulation source has high stability and good universality, and can perfectly meet the ground debugging and testing requirements of remote sensing satellite data transmission subsystem.

DC transformer (DCT) is basic and important power conversion equipment in DC distribution network. DC transformer adopts power electronic switches and high-frequency transformer, which can realize power conversion. Multi-ports DCT can connect many different types of power supply or load equipment, and can flexibly control the current, voltage and power flow of multiple ports, which is widely used in DC distribution network. In this paper, the output voltage control model of multi-ports DCT in steady state is established. Combined with the control model, the mechanism of controlling the phase-shift angle to realize the output voltage control is proved mathematically. The correctness of the control model is verified by simulation.

Photoelectric theodolite is important optical measurement equipment in pelagic aerospace TT&C systems. The visible light imaging method helps capture significant information of the observed target, photometric information is one of them. To achieve expediently and quickly target photometric measuring, it studies and realizes a measuring method, by using stars in the same field of view as the observed target in this paper. Firstly, it calculates the gray values for target and star by image processing algorithm in the image captured by theodolite. Then magnitude information of the star is obtained by using a star catalogue. Lastly, magnitude of the target is calculated by antitheses method. The approach is implemented to investigate the measuring performance and an experiment is carried out by using images containing at least two stars. The result shows good performance of the proposed method.

As the equipment with the highest attitude measurement accuracy and minimum drift, Celestial Navigation System (CNS) has widely applied and developed on various platforms, such as air-based, sea-based and land-based platforms. Aiming at the application characteristic of the CNS equipment, this article mainly analyzes the two operating modes based on gyro correction and overall estimation of INS error in the shipborne CNS/INS. Based on different selection of measurement information in CNS/INS, optimized choice is made in the integrated mode of gyro drift correction based on starlight and the integrated mode of satellite inertial navigation based on the overall estimation of inertial navigation error. This paper designs a master-slave filtering mode of CNS/INS to switch the filtering according to the observation conditions and verify through simulation analysis. This method can improve the adaptability of CNS/INS to the onboard environment; improve the positioning accuracy of about 40% compared with the single working mode during the long working of the integrated system, which can guarantee the navigation accuracy of the combined system.

Clean energy will account for a lot in the future energy structure with the emergence of Urban Regional Energy Internet. However, because of the intermittent and volatility of clean energy like wind energy, its main role in energy supply has restricted. Therefore, predicting wind power accurately is of great significance in the safe operation of the power system. In response to the above problems, this paper proposed a time series forecasting model of wind power based on BiLSTM, and analyzes the actual wind data in Urban Regional Energy Internet.

The stability of the rolling elements in the slewing bearing is an important factor that determines the smooth rotation of the slewing bearing. The slewing radius of the slewing bearing is large and the load is complicated. In this paper, the contact relationship between the rolling elements and the raceway is established by establishing a slice model of the slewing bearing. Considering the effects of axial load and radial load, respectively, the contact deformation and displacement changes of the rolling elements are analyzed. The simulation results show that the rolling elements of the two-point contact slewing bearing rotate during the load process, and the four-point contact slewing bearing is in the axial direction. Under load, the rolling contact state in the raceway with the raceway is stable without spinning; under radial load, the contact relationship between the rolling element and the four-point contact raceway at this time is essentially two-point contact, but compared to the one used Two-point contact raceway, the rolling elements have better radial stability in the newly designed raceway

Turntable bearing is widely used in heavy industry. Raceway structure is the most direct factor that affects the contact stress change between raceway and rolling element. Therefore, it is the key to improve the safety of turntable bearing and determine the processing technology reasonably to study the stress distribution of contact area in different raceways. In this paper, the finite element slicing model of rolling element and raceway in turntable bearing is established in ABAQUS. Under the action of axial load and radial load, the distribution characteristics of contact stress of raceway are compared under different raceway structures. The finite element results show that, compared with the two-point contact disc bearing, the rolling element and raceway in four point contact turntable bearing are in four point contact under axial load, The contact stress distribution of raceway is uniform, which is a pair bearing distribution. However, when only considering the radial load, the rolling element and raceway are in two-point contact, and the contact stress distribution characteristics are consistent with those of two-point contact rotary table bearing.

Based on the principle analysis of the electric power steering system (EPS), a simulation platform for electric power steering system (EPS) test is proposed, and use Matlab/Simulink to build a simulation model of the electric power steering system (EPS) test simulation platform, for the simulation analysis of the electric power steering system under various experimental conditions and working conditions, so as to get the boost current and boost torque needed in various situations, for the design and development of electric power steering systems.

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers.

The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction.

Retraction published: 16 September 2022