Table of contents

The 8th Annual 2020 International Conference on Geo-Spatial Knowledge and Intelligence (GSKI2020) was held on December 18-19th, 2020 at Xi'an, Shanxi, China (Virtual Conference) Due to the COVID-19 situation and travel restrictions via Zoom event platform. Every authors and Committees can be received a Zoom meeting username and password from the organizer who located on Wuhan, China. Every person can attend the conference using these information. The time spent to deliver the talks by each keynote speaker is 30 minutes, 25 min presentation and 5 min question time.The time spent to deliver the talks by each oral speaker is 15 minutes, 10 min presentation and 5 min question time. Every authors can discuss with others about their session after the speech. It was held very successfully. It aims to bring researchers, engineers, and students to the areas of Geo-Spatial Knowledge and Intelligence.

GSKI2020 features unique mixed topics of smart city, spatial data acquisition, processing and management, modeling and analysis, and recent applications in the context of building healthier ecology and Resource Management. The conference will provide a forum for sharing experiences and original research contributions on those topics. Researchers and practitioners are invited to submit their contributions to GSKI2020.

We received a total of 293 submissions from various parts of the world. The International Program Committee worked very hard to have all papers peer-peer reviewed before the review deadline. The conference program is extremely rich, profound and featuring high-impact presentations of selected papers and additional late-breaking contributions. We sincerely hope that the conference would not only show the participants a broad overview of the latest research results on related fields, but also provide them with a significant platform for academic connection and exchange. All the keynote speakers are internationally recognized leading experts in their research fields, who have demonstrated outstanding proficiency and have achieved distinction in their profession. The proceedings were published by IOP Conference Series. We would like to mention that, due to the limitation of the conference venue capacity, we are not able to include many fine papers in the program. Our apology goes to those authors.

We would like to express our sincere gratitude to all the members of International Program Committee and organizers for their enthusiasm, time, and expertise. Our deep thanks also go to many volunteers and staffs for the long hours and hard work they have generously given to GSKI2020. Finally, we would like to thank all the authors, speakers, and participants of this conference for their contributions to GSKI2020.

GSKI2020 Committee

Committee of GSKI2020

List of Editors, Keynote Speakers, Honorary-Chair, Co-Chair, The Editorial Committee, Internatinal Technical Program Committee are available in the pdf

All papers published in this volume of IOP Conference Series: Earth and Environmental Science 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

All the accepted papers have been submitted to strict peer-review by 2-3 expert referees.

• Conference submission management system:

http://www.chairin.cn/login?conf=gski2020

• Number of submissions received: 293

• Number of submissions sent for review: 131(submitted for publication)

• Number of submissions accepted: 131

• Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 44.7%

• Average number of reviews per paper: 2-4

• Total number of reviewers involved: 71

• Any additional info on review process: No

• Contact person for queries: Mings Yuan, Science & Engineering Research Center, Hongkong, Email: qimingyuan@sc-center.org Tel: 15824115687

In the smart grid environment, the secure transmission of power data is a major challenge for smart devices. Due to the broadcasting characteristics of wireless media, wireless communications in the power grid are vulnerable to eavesdropping attacks. Traditional encryption implementation requires high costs in wireless environments. In order to improve the security of data transmission in the power grid, physical layer security (PLS) has attracted widespread attention. However, there are too many idealized and unrealistic assumptions about the security research results in this field. This paper analyzes a physical layer security communication scheme considering the actual erection distance. When up-layer system break by opponent, the natural randomness of the physical channel will play a role in ensuring system security. We conducted simulations and analyzed the impact of the legal user's erection distance on the physical layer security performance of data transmission in the power grid, and adopted a targeted secure transmission scheme.

LID provides a new way of thinking to solve urban waterlogging and runoff pollution, and has attracted many scholars to try to integrate the LID concept into the planning and design of residences. After comprehensive analysis of LID's application into residence planning, it is found that the existing results are not suitable for slope residences, resulting in problems such as difficulty for rainwater to gather into the center of the block, grid-type road patterns not conforming to the characteristics of mountain cities, and some LID facilities layout unsuitable for slope residences.Therefore, combining the characteristics of mountainous areas, this article designs the "hexagonal" road network on behalf of the general road structure of slope residences. Furtehr, we find LID facilities suitable for slope residences and propose the rainwater runoff organization scheme in slope residences corresponding to the LID facilities. Finally, we explore the implementation of LID applicable modes in slope residences via the four continuous levels of architecture, site, road and greenbelt. It is hoped that the current research can supply some ideas to slope residence planning oriented to rain and flood management.

Under the background of continuous urbanization in China, urban underground comprehensive pipe gallery will become an inevitable trend of urban comprehensive management in the future. After the completion of the management gallery, how to effectively manage the risks in operation and maintenance management has become a topic at this stage. Based on the classic method of AHP combined with DSM method, and through a lot of literature research, to build the relationship between the risk of an integrated pipe rack system, and has carried on the system dynamics simulation using Anylogic software, finally, the simulation results obtained a few of comprehensive pipe gallery has the greatest effect in the overall risk of several risk paths, convenient operational phase in the pipe gallery risk in the future, you can draw on the results of several path for more effective management.

Reservoir operation is an important means to realize optimal allocation of water resources. In order to reasonably distribute water resources in Shule River irrigation area and improve the utilization rate of water resources, according to the actual situation of Shule River irrigation area, taking the minimum annual water shortage and the highest irrigation guarantee rate of the whole irrigation area as the objective function, the deterministic long-term optimal operation model of reservoir group in the irrigation area is established, and the successive approximation dynamic programming ( DPSA ) is used to solve the problem, so as to realize the joint operation of Changma Reservoir, Shuangta Reservoir and Chijinxia Reservoir, and provide the basis and reference for the comprehensive management and scientific allocation of water resources in Shule River basin.

Aiming at the problem that the accuracy of passenger flow prediction is not high, this paper presents a short-term passenger flow forecasting model based on Graph Convolutional Neural Network (GCN) and Bidirectional Long-term Memory Network (BiLSTM). Firstly, the historical traffic time series is divided into three time modes: recent period, daily period and weekly period; Secondly, we construct three models based on GCN and BiLSTM to capture the spatial and temporal dependence of the three patterns; Finally, the parameter matrix is used to fuse the output of the three time modes to obtain the final prediction result. By testing the data set of subway passenger flow in a city in January 2019, the experimental results show that the root mean square error of the model is reduced by 8.515% and the average absolute error is reduced by 4.239% compared with the single BiLSTM model, it has a high fitting degree with the real passenger flow value and has certain application value for the reasonable allocation of subway capacity.

Web service discovery is to find the most relevant services to satisfy the requester queries by means of similarity matching between Web services and a service requirement. We propose a novel Web service discovery method based on semantic similarity measure combing I/O similarity and context similarity. A new similarity measurement between terms is put forward as the basis of Web service similarity. Similarity between terms is represented by the similarity of two concepts containing them, and is calculated by means of the length of the shortest path between two concepts. Three kinds of linked relations are considered, i.e. ISA, HASA and antonymy relations. The experiments demonstrate that the proposed approach can improve the accuracy of concept similarity measure. Service discovery based on the similarity measure has better query performance than previous discovery methods in the precision, recall and F-measure.

With the emergence of various low-latency application scenarios in the Internet of things (IoT), edge computing provides a series of low-latency computing modes such as real-time data processing and real-time decision-making, supports multiple terminals, and solves the problems of the existing cloud computing architecture. This paper proposes a channel fingerprint data packet authentication method based on edge computing cooperation. The edge server and smart terminal perform cooperative computing, make full use of the computing power of the smart terminal, reasonably allocate the amount of computing tasks, and effectively realize lightweight data packet authentication. The task running time is shortened and the authentication efficiency is improved.

Urban density is one of the important factors to measure the occurrence of traffic in a region. It can not only reflect the intensity of traffic demand well, but also provide a way to quantitatively analyze the influencing factors of urban traffic demand. Take Nanchang and Jiujiang, cities with different geomorphic features, for example. The spatial analysis technique of GIS is used to calculate the urban density that can reflect the density difference. According to the characteristics of urban traffic demand, urban density is divided into single density and compound density. Through spatial statistical analysis, the impacts of various urban densities on traffic occurrence, travel distance, travel time and travel mode are analyzed. The research shows that different urban density corresponds to different traffic demand characteristics; In a certain threshold range, there is an obvious monotonic relationship between urban density and traffic demand.

As a new type of pipe, bimetallic composite pipe is widely used in various industries in the chemical industry, because its internal and external tubes use different metals, so it can cope with a variety of different working conditions. At present, the application field of composite pipe is mostly inner strong and outer weak strong composite pipe, and this pipe has not been studied accordingly. In this paper, the theory of expansion of inner strong and outer weak strong composite pipe is derived, and a complete set of expansion methods and related parameter calculation formulas are obtained. Abaqus, a finite meta-analysis software, is used to simulate the expansion process and compare it with the theoretical results. The comparative results show that the theoretical formula obtained by derivation has a high degree of credibility, and the results obtained by using this set of theories are close to the results of computer simulation and can be used in industrial production.

The concealed false data injection (FDI) attack in the smart grid can successfully pass the power system state estimation commonly used in the residual bad data test without being detected by the existing algorithms, resulting in the state estimation error of the control center and disturbing the normal operation of the power system. In this paper, false data injection attack and attack detection are carried out in the actual power edge security protection system, microgrid control system and intelligent energy security protection system. Among them, the false data attack part simulates the attack of the voltage phase angle, and compares it with the ordinary attack method, and demonstrates the success of these attacks in the actual power grid system.

The main oil channel of diesel engine cylinder block is the channel of lubricating oil, Whether they are smooth directly affects the working performance of diesel engine. This paper designs an intelligent detection system with programmable controller S7-300 as the control core, which mainly uses programmable control technology, photoelectric sensor technology and touch screen technology to complete the detection of cylinder main oil channel hole. The detection time is controlled within 38 s. This paper introduces the system composition and circuit working principle of detection system, and expounds the design scheme of PLC control system with S7-300 as the core. The design improves the detection speed, eliminates the missed inspection and false inspection, and provides the basic guarantee for the diesel engine to serve industry and agriculture efficiently.

The general flame detection method is sensitive to environmental changes and has low robustness, so the detection rate is not high. In this paper, a deep learning flame detection algorithm based on the improved YOLOv3 algorithm is proposed to automatically extract flame characteristics; with the help of MobileNet's deep separable convolution to compress the deep network model, replace the YOLOv3 backbone network with MobileNet, decompose the standard convolution into deep convolution and point-wise convolution, which can effectively reduce the amount of model parameters, Use K-means clustering to generate Anchor Box at different scales, further enhance the detection effect of the model. This paper conducts data analysis experiments on the self-built flame data set. The results show that the optimized algorithm (M_YOLOv3) has achieved 97.34% average precision (AP) on the data set. The flame target detection algorithm proposed in this paper can achieve high-precision and rapid detection of multi-scale flame targets in flame images with different shapes and sizes.

The training program of teaching skills is one of the key elements for pre-service teachers who cultivated in school. Due to the advantages of vivid, image video case are admired greatly by teaching classes teachers, and then, there are many video cases support systems for pre-service teachers emerged. However, they have some common problems which are not conducive to training pre-service teachers' teaching skills, including listing integrated instructional videos and a small amount of video review. Base on this situation, the author built a training case system for pre-service teachers, which can add annotations on fragments, search, evaluate, and share the content as a whole, by using the advanced network and informational technologies, the aim is to help pre-service teachers expand the time and space on training teaching skills, and improve the research efficiency and effects on training.

Aiming at the problem of "No one at home" in China's census work, a solution based on big data of power grid to the census work is proposed. With the support of big data technology, models for identifying vacant houses and predicting households at home are established by analyzing the electricity consumption and trends of each house. Besides, a data analysis platform based on power grid big data was developed to provide census staff with data support, such as the vacancy status of residential houses and the probability of residents at home. It has been verified that the research program is effective, which can reduce the workload and improve the efficiency of the census work.

The data attack in smart grid may cause the control center to make a wrong judgment, and then interfere with the normal operation of the power grid. In the case of data attack, this paper studies the optimal allocation model of distributed energy in smart energy system. Taking the maximum net profit of microgrid system as the objective function, the constraint conditions are established by using battery charging and discharging and power exchange of large power grid to optimize the allocation of distributed energy in the system. According to the characteristics of its power load, the corresponding dispatching strategy is formulated, and the genetic algorithm is introduced to find the optimal solution of the model. The power supply composition and economic loss before and after the optimization and attack are obtained, which proves the importance of attack detection.

As a new teaching mode and method, PAD has been developed in recent years. This teaching mode has been applied in the teaching of universities, ordinary primary and secondary schools and vocational colleges. It has achieved good teaching results. In order to improve teaching effect, improve the students' autonomy and enthusiasm and cultivate the independent innovative talents needed by the society, more and more computer teachers have also begun to apply PAD to the computer classroom. "Computer Network" is a basic and compulsory course for learning computers. "transmission media" in this course is selected as the specific content, and PAD is used for teaching design.

In this paper, based on the characteristics of web design and facture course, from the course introduction, teaching existence question analysis, training mode reform aspects and so on three aspects to illustrate how to improve the teaching effect of this course, and to explore the concept of how to use the OBE complete curriculum reform in teaching practice, thus improve the computer professional and visual communication professional social practice ability of students, in order to conform to the demand of the current web design position.

With the increasing number of flights, the gap between the front and rear aircrafts is gradually reduced. The wake separation becomes one of the important factors restricting the reduction of aircraft separation, which results in the runway occupation time can not be further reduced, and the runway capacity is also restricted to a certain extent. In recent years, the wake reclassification (Recat) promoted by FAA has been applied to runway capacity the increase has played a positive role.

In this paper, the capacity of Chengdu Shuangliu International Airport is studied, and the capacity models of approach runway and departure runway are established respectively. According to the relevant characteristics of Chengdu Shuangliu International Airport, the runway capacity model under one landing operation mode is established, and the runway capacity is calculated by using MATLAB software with reference to the new American wake classification standard (Recat). Finally, it is concluded that under the condition of introducing Recat, the capacity of Chengdu Shuangliu International Airport can be increased by 12.3% in theory.

The development of artificial intelligence technology brings a lot of benefits to various fields, including education. This paper discusses how artificial intelligence leads to the opportunity to improve learning processes and develop innovative approaches to education like blended teaching. Based on that, the author tries to provide tentative suggestions on the application of blended teaching to English reading courses with the help of artificial intelligence technology, in the hope of improving teaching and learning quality of this course, benefiting both teachers and students.

With the development of new technologies such as intelligent manufacturing and additive manufacturing, it is necessary to reform and upgrade traditional major of materials forming and control engineering. In 2019, the major of materials forming and control engineering in University of Shanghai for Science and Technology successfully passed China engineering education certification. In order to meet the requirements of continuous improvement, new courses on intelligent manufacturing and additive manufacturing are added into the new training program of the major, and new major orientations are designed in the curriculum system, which can better fit the training demand of excellent talents from advanced manufacturing industries of Shanghai and Yangtze River Delta.

The construction of city information modelling (CIM) is of great significance for the formation of a new smart city. In this paper, on account of UAV tilt photography, BIM model, Internet of things traffic data, to build a CIM platform under multi-source data, a pilot study was carried out in Tiexi New City. The development platform of Terraexplorer Pro based on the Skyline system is combined with the main technical support of BIM, GIS, and IOT to construct CIM. Its purpose is to achieve static and dynamic, ground and underground, indoor and outdoor integration, and provide prospects for future urban evolution. This study can contribute a reference for other CIM planning, and equip an effective scheme for smart city system planning and urban governance.

At present, traditional campus smart blackboard detection generally uses manual detection as the main method and equipment detection as the auxiliary method to determine the fault information encountered, and it is still limited to relying on the experience of the campus smart blackboard management and maintenance personnel to judge the fault. Solve the problem. In this paper, aiming at the problems of low efficiency of traditional campus blackboard detection technology, high manual detection cost, and low classroom enthusiasm due to untimely detection, this paper proposes a campus intelligent blackboard monitoring system based on AI technology, and establishes a chain-type intelligent classroom education system. Smart classroom does not affect the development of social education level because of some disadvantages brought about by technological development.

To solve the current problems of waste classification and littering, this kind of BearPi-based waste bin with the functions of speech-controlled classification and locating is invented using the technologies of speech recognition and GPS. The device, with BearPi as its core element, uses solar panels and lithium batteries as power supply, IIC and serial interfaces for the respective control of PCA9685 steering gear driving board, an M5310_A communication module, ATGM332D locating module and SX-ASR-B speech recognition module, and finally, a GPIO and timer for the operation of the HC-SR04 module and an E18-D80NK photoelectric sensor. The devices could classify the waste through speech recognition or leave it for the users. Furthermore, it could detect the remaining capacity and location of the waste bins through the modules and update the cloud data for the users' convenience in finding and using.

This design is based on the open source Android version 8.0 system to develop the mobile phone platform client, using the eclipse integrated development environment to research and develop Bluetooth control. The remote control of the car is realized by Bluetooth technology, gravity sensor and voice. The design is mainly composed of hardware system and software system. It can realize the car's forward, backward, rear left turn, rear right turn, front left turn, front right turn and other functions. This design scheme provides a new solution for the design and implementation of wireless remote control vehicle, and also plays a certain reference role for the design of remote control smart home system in the future.

In order to realize the automatic adjustment of fan with the change of equipment working temperature and reduce the power consumption and noise pollution of military display and control equipment. Firstly, according to the complex working environment of military display and control equipment and the dispersion of high temperature area, the distributed thermistor is used to collect the ambient temperature in real time to accurately grasp the environmental temperature of each point. Then MCU is used to collect and process the collected ambient temperature. According to the temperature change of each point, the fan speed is adjusted by PWM signal output from CPLD, so as to control the working temperature of display and control equipment, which can reduce noise and save unnecessary energy consumption. The air-cooled temperature control system based on PWM adjustment technology has the advantages of convenient and flexible layout of thermistor, rich interface, strong versatility and friendly man-machine interface. It can be widely used in vehicle, shipboard, airborne and other temperature control equipment.

With the development of the Internet and computer technology, news on the Internet has gradually been able to influence the development of the economy. In some special periods, with the development of major events, the economy and finance have undergone similar development and changes. This paper proposes a simplified natural language processing method for multi-grained text. First, the news text data is classified according to sentiment, and the correlation between corporate loans and job retention ability is further analysed. The experimental results show that under certain conditions, the Loans issued to SMEs are more conducive to retaining the number of jobs than large enterprises.

Aiming at the questions existing in the teaching of "Principles of Chemical Engineering", in order to cultivate students' engineering application abilities, new technologies are integrated into the "three-transfer" theory (momentum transfer, heat transfer, and mass transfer), experimental projects are renovated, and virtual simulation experiments are added. Then, a new teaching system for chemical principles and experimental teaching on the basis of "one platform and three clients" (one cloud platform, mobile client, teacher client, and administration client) is constructed. It is a student-oriented blended teaching system driven by problems; develop abundant teaching resources, further consummate multimedia courseware, computer-aided teaching, and develop a three-dimensional teaching system with textbooks, multimedia courseware, chemical simulation software, and online classroom. To realize a student-oriented interactive process for learning and teaching with the guidance of teachers, and give full play to students' initiative, activity, and creativity during their learning process; focus on strengthening the assessment for the experimental courses of chemical principles, strengthen classroom discussion and creative practical work, and improve students' engineering application ability, as well as abilities of analyzing problems, solving problems, and raising problems by applying comprehensive knowledge.

The A* algorithm is a direct search method. It can effectively solve the shortest path problem in static routing networks. It is also an effective method to deal with a large number of search problems. The closer the artificially estimated distance value in the algorithm is to the actual value, the faster the final search speed will be. This article focuses on the heuristic A* algorithm and discusses the problem of out-of-order Rubik's Cube searching the shortest feasible solution. It discusses the implementation ideas, advantages and disadvantages, and practical application value of the A*(IDA*) algorithm based on iterative deepening. The development of heuristic algorithms presents some personal insights.

Using the 1996-2016 Chinese provincial panel data to measure and analyze the human capital structure and total factor productivity, and empirically examines the impact of human capital structure on high-quality economic growth. The results show that the human capital of higher education promotes the high-quality growth of the economy more significantly, while the human capital of secondary education plays a significant inhibiting role. The heterogeneity study from three regions further shows that the impact of different levels of human capital on the high-quality economic growth of different regions is different. The higher education human capital has a greater role in promoting the high-quality economic growth of the three regions. Basic and secondary education human capital only affects the eastern region.

With the increasing popularity of online ride platforms, more and more historical data can be used in the field of intelligent transportation. However, the taxi behavior of users is difficult to predict and has a great relationship with time and geographical location, which makes the supply and demand of vehicles show an imbalance. Reasonable vehicle scheduling can not only increase driver's income, improve service quality, but also make effective use of traffic resources. In this paper, a grid-based scheduling model is proposed. By gridding maps, the computational complexity of Donger is reduced to output vehicle scheduling actions quickly. The problem of vehicle supply and demand imbalance can be effectively solved by correcting model parameters based on return loss function. In this paper, the model is optimized from three aspects: loss function, learning rate and grid scale. The goal is to maximize the sum of orders. Compared with the traditional machine learning model, the model proposed in this paper can have deeper features and thus obtain higher prediction accuracy. The experimental results on a large number of real historical taxi order datasets show that the proposed model has high prediction accuracy.

With the development of Internet technology, there are more and more network attack modes. APT attacks, as one of them, will have a very serious impact due to its concealment, long-term nature, and purpose. Fast-flux botnets are widely used in APT attacks due to their spreading power and destructive power. This article first introduces the basic structure and related knowledge of FFSNs, and then summarizes and compares the previous papers on Fast-flux botnet research. In order to effectively detect the Fast-flux botnet, this experiment removed features that require a lot of resources and uncertain factors, and adopted a more convenient feature AA, which became a more lightweight detection model. At the same time, because the automatic update module of the detection system will promptly feedback the current traffic situation in the network, it will greatly improve the accuracy. The experimental results of the CTU-13 and ISOT public data sets show that the detection method proposed in this article Compared with other methods, the accuracy rate is increased to 98%.

The economy of East Asia is related to the overall development of Asia and even the whole world. Use ArcGIS to analyze the spatial-temporal evolution and the time series from 2004 to 2018 to construct the correlation effect model of FDI from China, Japan and South Korea to ASEAN to analyze the correlation effect of cumulative impulse response and variance decomposition. The results show that FDI from China, Japan and the South Korea in ASEAN increased significantly, and the investment location choice of the three countries in the ASEAN was relatively stable and had similarities and differences. The FDI from China and Japan to ASEAN mainly focuses on cooperation and synergy for a long time, while there is competition between Japan and South Korea, and the FDI from Japan to ASEAN has a deep influence on China and South Korea. The FDI from China, Japan and South Korea to ASEAN is not a zero-sum game. It is also known as the investment cooperation mode that multiple parties make investment in the same region over time, in different industries in the same period and in different locations.

In order to study the structural performance of freight ropeway under the influence of dynamic factors, a method for dynamic analysis and calculation of freight ropeway is proposed. Based on the theory of finite particle method, this method gives the expressions of the interaction force between the carrying rope and running trolley, and the haulage rope and running trolley. The motion equations of the particle of the carrying rope, traction rope and running trolley are established respectively, and the coupling force calculation of the carrying rope and traction rope is realized. The influence of load quality, starting speed and starting position on the tension of working-rope of freight ropeway is analysed with the proposed calculation method, which can provide more scientific and reasonable reference for the design of freight ropeway.

The emergence of edge computing technology brings new development direction to the construction of power grid industry. At present, for the edge computing technology of China is still in the exploratory stage, the combination of power grid and edge computing may face new security risks. This paper analysed the security risks that may occur in grid edge computing under the circumstances of identification system, communication technology, equipment protection and resource constraints, and put forward the relevant security risk analysis model and defence, aiming at solving the security problems of grid edge computing and promoting the better development of power grid.

Asian Pacific Space Geodynamics (APSG) geodetic Very Long Baseline Interfero-metry (VLBI) observing sessions are being regularly performed to improve the accuracy of the geocentric coordinates of the participating stations in the Asia-Pacific region. Two small antennas, located at Jilin and Sanya, have been built and operated by the National Time Service Center (NTSC). They have a wide frequency coverage of 1.2-9.0 GHz and no standard geodetic recording mode available. We conducted mixed-mode observations with participation of those two NTSC stations in APSG40 and APSG46 experiments. The observational data have been correlated and analysed at Shanghai. For the first time we derived the coordinates of JILIN and SANYA at 1 cm level by means of geodetic VLBI technique. The difference of coordinates of JILIN station between two APSG experiments is about 2 cm if the comparison is made on the same epoch of observations. Here we present the experiment setup, data processing method and analysis results.

As a typical product of the transitional stage of urban development, the color steel buildings (CSBs) are easy to cause fire, which is difficult to be extinguished effectively and quickly. This paper aims at the particularity of the geographic location of the CSBs and the lack of joint application with Point of Interest (POI) and fire points in the study of urban fire risk., this paper investigated the fire risk of Lanzhou city based on above three types of data acquired in 2017. The involved data were meshed by kernel density analysis and superposition analysis. Afterward, the pairwise spatial coupling relationship of the data were visualized by two-factor cartography, through which the condition of spatial coupling were obtained. The relationship between the obtained regions and urban fire risk was further compared. The research results show that CSBs and the POI Point are highly coupled with the fire locations of Lanzhou spatially. Thus, the joint application of the two factors can be effectively utilized to evaluate the fire risk in Lanzhou. The phenomena that the CSBs outnumbered the POI Points indicates that the corresponding areas are not well urbanized and have high incidence of fire.

Airport clearance safety management is an important part of airport operation indicators. Controlling obstacle height is one of the most important tasks in airport clearance management. The current program design and evaluation in China currently uses the obstacle restriction surface (ILS) and Obstacle Evaluation Surface (OAS). The current program design in our country rarely uses the collision risk mode (CRM), but the obstacles around the airport are gradually increasing. At this stage, the OAS surface is more conservative. A simplified model with a collision probability of approximately 1×10-7 is constructed and compared with the OAS surface to improve it. The results show that the slope of the original OAS surface is larger than that of the simplified model. The improved OAS surface meets the target safety level and solves the problem of being too conservative.

In order to meet the business needs of power inspection. The requirement is to identify the target quickly and in batches. In this paper, yolov4 convolution neural network is used as the technical to realize the target detection process of power inspection photos. Firstly, the training data set of power patrol inspection is accurately labeled by labelimg. Then it is trained by the deep learning framework of Darknet. And the results are satisfactory. The test results show that tthe Precision is 0.92 and the Recall is 0.904 after training by the self-designed training data set of electric power inspection target detection.This detection effect can meet part of the requirements of target detection in power inspection. However, there are two problems in this test: the lack of data annotation set in power inspection and the serious overlap of different objects in some photos of the data set. The author of this paper hopes the relevant researchers to correct and supplement.

Liquid holdup is an important indicator to evaluate fuel efficiency during high-speed refueling. This paper carried out a numerical study on the fluid flow as refueling a fuel tank based on the volume-of-fluid method in the commercial software FLUENT, and the effects of inlet velocity, injection angle, nozzle diameter, and the shape of the tank on impact phenome-non were examined and the corresponding relationships between these factors and the liquid holdup were found by a series of single-variable numerical experiments. The results indicate that: a smaller impact angle (30°-60°), lower inlet velocity (2.5-10 m/s), and larger nozzle diameter (36-40 mm) could result in a higher liquid holdup, and a tank with a square cross-section presents higher and more stable liquid holdup than that of a racetrack-like one. Besides, the effect due to the tank shape is greater than those of the inlet velocity, injection angle, and then the nozzle diameter. This work could be helpful for the design and control of a high-speed refueling equipment.

Aggregate plays an important role in the performance of asphalt mixture. In order to complete the intelligent online monitoring of asphalt aggregate quality, an automatic classification algorithm for coarse aggregate particle size based on LightGBM classification algorithm is proposed. Firstly, OpenCV is used to extract the two-dimensional morphological features of coarse aggregates, and then the correlation between these features and the classification of aggregates is analyzed. Finally, the accurate classification of coarse aggregate particles is achieved through grid search and cross-validation optimization model. The results show that the average classification precision of coarse aggregate can reach 84.7%. Compared with the classification method based only on image processing technology, the precision is increased by about 20%, and the efficiency of classification is greatly improved.

With the development of information technology and the blooming of artificial intelligence, human activity recognition (HAR) has become a hot research topic. HAR has a certain prospect and practical value for mobile medicine and security monitoring, which has attracted the attention of many researchers. However, most of the existing HAR methods rely on the shallow feature learning mechanism, and the features learned by these methods are not completely consistent with the actual activities. To solve this problem, a human motion recognition method based on residual network (ResNet) is proposed. In addition, we modified the internal structure of ResNet by limiting the number of its network layers within a certain range to prevent over fitting and degradation. Our proposed method has better recognition performance than methods using pure convolutional neural networks(CNN), and it achieves 95.66% recognition accuracy.

In this paper, Xiyan Village and Dongyan Village of Jiyang County, Jinan City were taken as the research areas to conduct research and analysis on the spatial distribution law of soil salinity in the spring of 2019. Spatial distribution of soil salt ions in different soil layers were drawn to research spatial distribution characteristics of soil ions. The results show that soil in the research areas was highly mineralized and the negative ions in the chemical components were mainly SO42- and Cl-. In the horizontal direction, the content of Mg2+ and Cl-in all layers all presented the trend of increasing gradually from northwest to southeast. The peak value of ion content occurred in the Midwest.

Considering massive amounts of location data will consume excessive memory and inefficient when performing a spatial query, a new ship position-encoding device was designed by combing the navigation, positioning and communication functions of the Beidou navigation satellite system and Geohash coding technology. An efficient index algorithm based on Geohash encoding was applied to improved efficiency, especially to solve the problem that massive ship position data occupies massive amounts of memory resources when searching for rescue ships near a wrecked ship, improve rescue efficiency, reduce energy consumption, realize high device utilization, one-key multi-use, and higher automation. Experimental results prove the ship position encoding method is better than the traditional device in terms of the spatial query of nearby ships and reducing the storage space consumption.

Removing dangerous tree barrier is an important condition to ensure the safe operation of transmission line. A tree barrier measurement technology based on Unmanned Aerial Vehicle (UAV) is proposed in this paper. The technology detects the tree barrier near the transmission line by carrying Three Dimensional (3D) Lidar and on-board computer, de-noises the data obtained during the scanning process, aggregates and classifies the tree barrier data model. Combined with tree barrier measurement algorithm, a real-time tree barrier measurement system and method are formed. Field experiments show that the system can effectively improve the accuracy and efficiency of traverse tree barrier measurement, which is conducive to the realization of information, intelligence and safety of transmission line inspection, and has practical application value for the safe operation of the line.

3D modeling is the important foundation of virtual reality and scene simulation. The technology of UAV oblique photogrammetry provides a new way for 3D modeling, and the accuracy becomes the key of its application. Since there are a lot of uncertainties in 3D modeling of UAV oblique photogrammetry, this paper proposed a fuzzy comprehensive evaluation approach to deal with this uncertain problem. Firstly, according to the composition of 3D modeling system based on UAV oblique photogrammetry, the main impact factors of 3D modeling accuracy are determined, and the indicator system of accuracy evaluation is therefore constructed. Secondly, by using the method of analytic hierarchy process, the weights and membership degrees of each indicator are calculated. Finally, the proposed approach is applied and validated in the case study. After the fuzzy mapping by the dot multiplication performance between the indicator weights and membership degrees, the comprehensive evaluation sets of different cases are obtained, and their corresponding 3D modeling accuracies can be determined based on the maximum membership degree principle. It is concluded that the fuzzy comprehensive evaluation approach proposed in this paper can quickly and correctly assess the 3D modeling accuracy of UAV oblique photogrammetry.

Diabetes is one of the three major chronic diseases in the world. At present, the number of diabetic patients in the world is increasing year by year, which has become one of the main threats to us. Therefore, it is very important to monitor blood glucose level. Clinically, blood glucose is measured by collecting fingertip blood, but this method has many disadvantages. In this paper, PPG signals are used to estimate BGL using deep neural networks (DNN). Finally, we found that the success rate of our DNN blood glucose estimation model reached 90.25%, and achieved good results. It provides a choice for the commercialization of noninvasive blood glucose detection technology.

Phase unwrapping is one of the most critical steps in InSAR data processing. Filter-based phase unwrapping methods can perform phase unwrapping and noise removal simultaneously, and show a clear advantage in dealing with high noise and density fringe interferograms. Based on the precision estimation theory of nonlinear functions in Extended Kalman Filter (EKF) and Cubature Kalman Filter (CKF) algorithms, we derive and analyze in detail the estimated precision of the EKF and the CKF on nonlinear observation equations in the phase unwrapping model. Results show that both EKF and CKF algorithms have similar precision in areas with better phase quality. However, in poorer quality areas, the precision of the two shows a certain difference and there is no consistent superiority for each algorithm. Experiments using simulated and measurement data confirm the validity of our theoretical analysis.

This paper analyzes the trade between the UK and Commonwealth of nations from the perspective of time and space .We use a detailed trade data to analyze the volume and structural change of trade in the 21st century, the findings show that the trade volume of goods between the UK and the Commonwealth is only 8.27% of the UK's total foreign trade of goods, the degree of closeness and dependence of trade show a decreasing trend, and the bilateral trade shows significant spatial differences. Then we use vector auto-regressive model to analyze the impact of the UK's trade with the Commonwealth on its economy and there exists a long-term stable trend. Trade shock has a positive effect on the UK's economic growth.

The detection and recognition of moving objects has always been a hot topic in computer vision. With the development of computer vision, the demand of video intelligent tracking is higher and higher. This project realizes video tracking and extraction based on OpenCV. It can read and display a single target video signal, track the feature points of a single target in the video signal, identify and extract the single target according to the change of target action. Codebook background modeling and three-frame difference method are mainly used to identify the movement changes of moving targets. The system identification effect is good.

China is an ancient civilization with a long history. However, in the long history, horses have played a key role in the production and life of the people, so later generations compare the performance evaluation to "sweat horse work". From a certain point of view, the role played by horses in the formation and development of civilization is far more than that of human beings. Unlike other animals, the power, speed, and value of the horse have a positive effect on people's daily lives. Since the domestication of the horse, it has contributed more profoundly to the development of China's way of life and the process of social history and has also made remarkable contributions to the far-reaching development of ancient Chinese agriculture and industry. Therefore, for different ethnic groups in different regions, their roles in the production of the local people at that time were also varied, so each region gradually formed equine culture in line with its own regional development. Besides, the horse culture has also influenced other aspects of human beings. However, nowadays, with the continuous development of science and technology, the status of horses in human life or production is declining rapidly. The article introduces the connotation and characteristics of equine culture and big data, deeply analyzes the main relationship between big data and ethnic culture communication, the problems of equine culture communication in the current stage, and proposes strategies to solve them, so as to provide a reference for the communication of equine culture under the background of big data in the new era.

In order to further understand and grasp the impact of load on the vibration and noise characteristics of the transformer, this article analyzes the impact of load factors, power factor, harmonic current, three-phase unbalance and other load factors on transformer vibration and noise from the perspective of transformer vibration mechanism. A 10kV/200kVA three-phase oil-immersed distribution transformer was used as the object. Experiments were conducted to study the changes in the spectrum distribution, noise intensity and A-weighted sound pressure level of the transformer vibration and noise under the influence of different load factors. The results show that: when the frequency increases, the amplitude of the 100Hz fundamental frequency in the vibration noise signal increases, and the noise level increases accordingly; when the power factor increases, the amplitude of the odd frequency components in the vibration noise signal gradually decreases with the increase of the power factor. There is no obvious fluctuation in amplitude except 100Hz. When the harmonic current and the three-phase are unbalanced, the spectral components become complicated and accompanied by a large number of odd-order frequency multiplication components. With the increase of harmonic content, the amplitude of vibration noise signal and A-weighted sound pressure level increase significantly; the degree of unbalance and the occurrence of unbalance have a greater impact on the amplitude of vibration noise signal and A-weighted sound pressure level. The research in this paper provides a reference for the noise suppression of power equipment and the fault diagnosis technology based on vibration and noise signals.

Metro TOD plays an important role in the development of commercial economy and promotes the local industry and economy. Reasonable combination of Metro TOD and tourism economy will help to form a more diversified development model. This paper puts forward a new development mode of Nanjing Shijiu Lake Metro TOD.

As a complex process, road transportation is restricted by many factors. In order to carry out safety management of road transportation, this paper puts forward an evaluation index system with multiple risk factors for the service providers of satellite positioning system (GPS) for tourist buses, long-distance passenger vehicles and dangerous goods vehicles. Through the construction of multi-level analytic hierarchy process (AHP) for the comprehensive evaluation of safety production and related management of satellite positioning operators, the weight evaluation model is obtained; and the evaluation results are compared with the neural network model by using linear regression model. The experimental results show that: in terms of evaluation, the average absolute error of neural network model is 0.137, and the hierarchical model is 0.232, the former is slightly better than the latter; in terms of stability, the hierarchical model performs best. Comprehensive comparison shows that hierarchical model has better performance in evaluation accuracy and stability. The method proposed in this paper provides technical support for the evaluation of satellite positioning operators.

Electric power sensor data is a typical time-series data. Their anomalies are not only abnormal points, but also continuous data fragments named anomaly patterns. Based on the analysis of the abnormal patterns of electric power sensor data, we propose an abnormal pattern detection method to handle the anomaly of spatial density of power sensor data. The proposed method trying to discover abnormal density distribution in the super high-dimensional space. It takes the spatial distribution of the sensor data to build a density model. Moreover, density value of each sensor is computed by matching original sensor data with the density intervals in the model. Furthermore, anomalies are detected according to the density values. In order to verify effectiveness of the method, exclusive experiments are conducted on the real data of power plants. Experimental results show that the proposed method has high recall rate, low false alarm rate and high accuracy while low cost of time when detecting abnormal data patterns

The construction of marine environment parallel corpus is based on the translation of The World Ocean Review. The text translation has been completed, and a term list has been built. The next step is to construct the parallel corpus, and the researchers should design the corpus in order to avoid some problems before starting. During the translation process, the researchers also find some problems and try to solve them which could supply some suggestion to the future E-C translation of scientific text.

Deep learning has made breakthroughs in recent decades and has been widely used in many domains. However, most of those methods heavily rely on large labeled datasets, which results in poor performance when provided with limited labeled data. Few-shot learning (FSL), which aims at learning a novel task with limited samples, has attracted a lot of research recently. The previous metric-based methods ignore the internal bias between the training and testing datasets since the categories of the testing dataset are completely different from the training set. Transfer learning methods also suffer from few labeled data and tends to be overfitting in this situation. This paper proposes Transductive Mutual Information Encoder Network (TMIN) for few-shot learning problems. TMIN typically trains a convolutional neural network with a mutual information maximization module in an unsupervised manner. The trained network maps images to a high dimensional embedding space. Then the embeddings are exploited to measure the similarity between samples by a distance metric. Experiments indicate that the proposed model achieves competitive performance compared with the counterparts.

In order to effectively solve this problem that that the traditional level set method needs to mark the initial contour manually, a novel method that automatic initialization by utilizing deep learning is proposed in this paper. Firstly, a target detection network based on Faster-RCNN is used for target detection of ochotona curzoniae. Secondly, the detected target boxes are regarded as the initial contour of level set models, and ochotona curzoniae images are segmented by level set models, by which the problem of manually plotting the initial contour required by traditional level set models is solved. The experimental results of ochotona curzoniae image segmentation show that there is little difference between the level set segmentation method in which the initial contour of the target is automatically generated by deep learning(LSECA) is used to automatically target initial contour and the level set segmentation method where initial contour needs to be manually plotted. Therefore, the experimental results prove that it is feasible to automatically obtain the target initial contour through deep learning.

The linguistic scholars has used word frequency for research for a long time. With the rising of corpora study, researchers pay a lot attention to words and their frequency information, and even develop the teaching approach and teaching book. The Lexical Syllabus, The Lexical Approach and Data-Driven Leaning introduced by this paper are the representative of the development of corpora. From the background of this research, this paper gives the definition of some relative concepts, and discusses the arrangement of lexical syllabus and teaching content, and uses examples to explain the practice of The Lexical Approach.

Extrinsic Information Transfer(EXIT) characteristics are extensively used in iterative detection and decoding of turbo type processing. This paper makes an exploratory study of the issue of EXIT characteristic analysis for Low-Density Parity Check (LDPC) coded Interleaver Division Multiple Access (IDMA) system in Multiple Access Channel(MAC) condition. By using simulation method and extrinsic information calculation, the a priori information of the IDMA detector and the extrinsic information can be gained. In the same way, the a priori information and extrinsic information of the LDPC decoder in the system can be procured. The EXIT characteristic of the detector illustrates the convergence the detection algorithm of IDMA, while the EXIT characteristic of the LDPC decoder illustrates the convergence nature of the optimized degree profile,which shows the reasonability of LDPC coded IDMA system and the reliability of the optimized degree optimized algorithm for multiple access channel.

As one of the key elements of climate change, the temperature changes can affects the energy balance and hydrological cycle. The variations and trend of mean annual maximum temperature (T_max) and minimum temperature (T_min) were analyzed by using linear regress for 44 stations inside and surrounding the Qilian Mountains for period of 1960-2017. The results have shown that the variations of mean annual T_max and T_min have significant increasing in whole study regions. The warming trend of mean annual T_mix is higher than that of T_max. Both the trend of mean annual T_max and T_min in the southern slope is warmer than those in the northern slope of Qilian Mountains. In spring, the warming trend of T_max is significantly weaker inside than that outside the Qilian Mountains. For all seasons, the trend of T_max and T_min is the highest in winter, and is weakest in spring.

This paper collects the interpretive panels from scenic spots in China and abroad and then establish two corpora ("CTETIPC" and "CETIPA" ). It analyzes and compares the linguistic features of translated and original English tourism interpretive panels from the aspects of STTR, MWL/MSL, nominalization, tense and voice. It is concluded that the translated English tourism interpretive panels are in some aspects non-standard. It is advised to take into consideration the different way of English expressions so as to better achieve the communicative effects.

The remote tower technology can provide remote control services for small airports in remote areas with low passenger and cargo throughput[2].In the 1990s, European and American countries began the research and development of remote towers. In 2015, Sweden's Sundsval Airport approved the use of remote tower operations. In 2019, China Xinjiang Airport Group started the remote tower pilot construction. As a new thing, the remote tower system is different from the traditional tower, and its safety and reliability have not been systematically studied in China. This article introduces several methods that can be used to analyze the reliability of the remote tower system in detail. These methods are analyzed and compared. Finally, this article summarizes the methods applicable to the reliability analysis of China's remote tower system.

Training with tank driving simulator is an important method to improve equipment operation skills. In view of the deficiency that it is difficult to find knowledge and rules from complex training data by statistical analysis method in the past driving simulation training, this paper proposes CSAGA-LSSVM algorithm to analyze tank driving simulation training data. Selecting key points to quickly generate shapelets, reducing the number of candidate shapelets; combining shapelets according to distance and time interval to enhance the ability of feature identification; designing adaptive genetic algorithm to dynamically adjust the probability of crossover and mutation to find the optimal parameter solution of least squares support vector machine. The algorithm is applied to the classification mining of shift operation data from a certain tank driving simulator to extract the operation characteristics of personnel.

The kinetics of biogas production on anaerobic fermentation with anionic surfactants added was evaluated using the sigmoidal models (the modified Gompertz and Logistic). The mesophilic anaerobic co-fermentation experiments under different anionic surfactants concentrations were conducted with mixed cow dung and corn straw as feedstocks. The results showed that the anionic surfactants in appropriate concentrations on anaerobic fermentation increased the cumulative biogas yields while prolonged the lag phase time. The modified Logistic model performed better than modified Gompertz model in fitting the experimental results of anaerobic co-fermentation with anionic surfactants added. The results of this study were expected to provide theoretical guidance for studying the impact of anionic surfactants and modelling the kinetic process of anaerobic co-fermentation.

With the wide use of graph convolution network (GCN) in various NLP tasks, researchers introduce GCN to aspect-based sentiment analysis. They utilize GCN over dependency tree to capture the syntactic information and obtain the final representation by modeling the interaction between the semantic and syntactic information. However, due to the unreliability of the construction of dependency tree, these interaction-based models may suffer from the side effect of unreliable syntactic information. To tackle the problem, we propose a multi-channel aspect-specific attention mechanism to ease the possible side effect by retaining and exploiting the original semantic information, which is not affected by the syntactic information. We also propose a dynamic weighted concatenation mechanism to sufficiently utilize the multi-channel information by dynamically assigning weights to the multi-channel information. The extensive experiments on five benchmark datasets indicate the effectiveness of the proposed mechanisms.

Suspension spanning frame is widely used in the construction of newly constructed overhead transmission lines, and plays an important role in protecting the safety of the objects being crossed. The temporary beam of the suspension cable-type span is installed on the transmission tower, and the impact load in the event of an accident will be transmitted to the transmission tower through the temporary beam.Therefore,the installation of temporary beams will have an important impact on the safety of transmission towers. This paper analyzes the typical installation method of the suspension cable spanning frame on the transmission tower, discusses the dynamic simulation method of the suspension cable spanning frame and the transmission tower under the impact of the conductor, selects a 500kV transmission line crossing project to carry out the wire breakage Analysis of the impact of the lower impact load on the transmission tower. The results show that the wrong installation method will have a significant adverse effect on the safety of the transmission tower. Based on the analysis results, suggestions for the installation of temporary beams were proposed, which provided a reference for the suspension construction of the suspension bridge.

The compression molding process of CFRP(Carbon Fiber Reinforced Polymer) is a multi-parameter coupled system, and its molding mechanism is very complex. Based on the Gel point and the glass transition temperature of the matrix material, the compression molding process of CFRP is divided into three sub-processes: thermal-chemical process, flow-compaction process and residual stress-deformation process, and the mathematical constitutive model of each sub-process is established. On the basis, the interaction and calling relationship of each sub-process are determined, which lays a foundation for the molding process simulation of CFRP and further analysis of its multi-parameter coupling effect mechanism.

To obtain the influence mechanism of lithologic characteristics when rock bust shock waves transmit through rock, the waves in different rock were monitored with fiber Bragg grating (FBG). The result shows that the wave will change the period Λ and effective refractive index n of FBG, and further affect the initial wavelength value. The amplitude, phase and frequency of shock wave are directly related to the wavelength drifts of FBG. The transmitting velocity of shock wave in rock is affected by lithologic characteristics. The Elastic modulus, density and Poisson's ratio of rock influence the initial wavelength value of FBG in the form of $I = \sqrt {\frac{{2E}}{{\rho (1 + \upsilon )}}}$, and are Cosine related to wavelength drifts. The experiments of shock waves monitoring were carried out in sandstone, limestone and marble respectively. The result shows that the lithologic parameters of rock were Cosine related to the initial wavelength value of FBG. This study provided a theoretical basis and practical application guidance for coal or rock burst monitoring with FBG sensing.

Through the process of making impeller model by Fused Deposition Modeling (FDM), the error of 3D printing forming process was analyzed, including principle error, forming error and post-processing error. The error caused by measurement is analyzed, and the causes of the error and the solving methods are expounded in detail. By analyzing the errors in the size of impeller models, the possible causes of errors can be analyzed. Combining the forming conditions and the actual situation, the optimization method of process parameters is analyzed, which can provide a certain reference for 3D printing production and testing the best process parameters.

The deformation behavior of the 1.15C-4.00Cr-3.00V-6.00W-5.00Mo powder metallurgy high speed steel in hot working processes was investigated by the isothermal compression tests carried out at the temperature of 1000-1150°C and the strain rate of 0.001-1.0s⁻¹ with the height reduction of 60%. The processing maps were constructed, identification of the instability regions and optimization of hot deformation parameters. Different types of instability criteria of PRASAD, MALAS, GEGEL, MURTY and SEMIATIN were compared. It was found that the hot working process of the steel can be carried out safely in the domain of 1040-1130 °C/0.01-1.0 s⁻¹. Furthermore, the temperature and the strain rate had a great effect on microstructures. To obtain a homogeneous microstructure with fine grain, the hot working process should be carried out under the condition of 1050-1100 °C/0.01-0.06 s⁻¹.

Inhomogeneity is the inherent attribute of precipitation and is usually an important factor affecting the occurrence of hydrological disasters such as floods and debris flows. Based on the monthly precipitation data of 27 national meteorological stations in the past 50 years, the spatial and temporal distribution characteristics of precipitation concentration degree (PCD) and precipitation concentration period (PCP) in Gansu Province were assessed in this study. The results indicated that: (a) the annual precipitation had distinct regional differences (annual average values were between 43.3-605.4 mm) and strong inter-annual fluctuations (coefficient of variation was usually above 0.20, some up to 0.40-0.45); (b) the main range of PCD was from 0.52 to 0.67, with significantly reduced inter-annual fluctuation and a long-term trend of gradual decrease; (c) the spatial-temporal variation of PCP was generally small, mainly concentrated in 192.8°-205.0°(mid-late July), and showed a slightly advanced variation tendency. Under the overall background of warming and wetting, Gansu Province presents evolution characteristics of PCD weakening and PCP advancing, and the formation mechanism and potential effects of this phenomenon require further attention.

with the rapid development of e-commerce, many changes have taken place in customer relationship management under the environment of e-commerce. From this point on, this paper analyzes the requirements and characteristics of customer relationship management system in e-commerce environment, and discusses how to effectively integrate customer relationship management system with other information systems to better meet customer needs.

Understanding the mechanisms of the natural environment that affect the interaction between consumers and resources is the key to understanding the stability and function of ecosystems. Although the effects of many environmental factors on predator-prey interactions have been well studied, turbidity in aquatic ecosystems is not one of them. Turbidity is ubiquitous and can be important because it is related to water pollution and can significantly reduce visibility of both predator and prey. In this study, the effect of turbidity on the interaction between the shore crab Carcinus maenas and the gammarid amphibians Echinogammarus marinus is studied. The functional response of the predator (crab) under different turbidity levels (consumption rate under different prey (shrimp) densities) was quantified, and it was found that turbidity increased the search speed and handling time. In zero turbidity, that is, completely clear water, the performance of the predator (crab) is not as good as the performance under low turbidity conditions. This may be caused by many reasons, such as the crab is get used to low turbidity conditions because they live at the bottom of intertidal and they will stir up sand at the bottom when they are moving. However, in order to better understand how the interaction between consumers and resources responds to turbidity, more research is needed.

As our country urbanization and economic development accelerating, traffic problems become increasingly serious. In urban road network, the intersection delay has a major influence on road impedance even the choice of the path. In order to reflect the actual situation of traffic flow distribution more accurately, the transportation network assignment model was established based on the intersection flow of delays and traffic control.

By comparing delay models of signal control and analyzing the intersection impedance, the intersection optimization model was built based on delay, queuing and traffic capacity. Then, we analyzed the structure of the road network topology and traffic assignment models, researched the advantages and disadvantages of the allocation algorithm in detail. Finally, the balanced allocation algorithm for FW algorithm convergence slowly was improved. The feasibility of the algorithm was verified by examples.

Power distribution of Internet of Thing technology develops quickly nowadays, however, the basic information structure of power distribution IoT is still in research and development. This article raises a new information model of Power Distribution IoT and discusses logical topology, matching of measurement value for measurement point and isomorphic model of map location, it provides a consistent algorithm for information model of power distribution IoT as well. Based on existed research, a new hypothesis is raised, which focuses on the structure of connected data product of power distribution IoT and it discusses the process of how to realize the architecture further. Lastly, article introduces a successful research and development case of information model of Power Distribution IoT to prove practicability of it.

This paper takes the ecological security of the Chongqing Three Gorges Reservoir area as the research object, establishes five subsystems of policy, population, water environment, economy, and biology, and uses the analytic network process to calculate the impact weights of different indicators in each layer of the system. The results show that the weight of the water environment indicator layer is the largest, and other indicators have varying degrees of impact on ecological security. On this basis, construct a system dynamics model, select the main constraints of environmental factors in the Three Gorges Reservoir area, set three different development scenarios, and observe their impact on CODcr And determine the range of ecological safety thresholds.

In view of the situation that the fault monitoring is not timely and the accuracy of fault diagnosis is low due to only indoor monitoring equipment but not outdoor monitoring equipment, an intelligent diagnosis method based on neural network is proposed. Firstly, according to the different operating environment and influencing factors of the track circuit, the method of orthogonal test is designed to obtain the information of each component There are three kinds of track circuit monitoring variables with complex environmental factors, and then the track circuit fault types are divided into three categories: sending channel fault, receiving channel fault and track fault. On the basis of rapid location of track circuit fault location, 21 kinds of specific fault types are distinguished. The simulation results show that: when using this method for track circuit fault diagnosis, even without outdoor monitoring data, it can quickly locate the location of the fault, and the location accuracy can be up to 100%. When identifying 21 fault types, the accuracy of fault diagnosis can still be up to 90%, the diagnosis rate is high and the judgment is fast, which can assist the field maintenance personnel judge faults accurately and quickly.

How to generate a color image with as much information as possible from hyperspectral images on a trichromatic display is a subject of great concern. In a sense, effective bands containing important information can be extracted from hyperspectral data for image visualization through the method of band selection. In this paper, two improved methods are proposed for the linear prediction (LP) band selection algorithm. According to the information entropy, the band with the greatest difference in information domain is selected as initial band.Then, the max pooling method is used to select the pixel which can better reflect the image features. Finally, the band similarity is used to select the most distinctive band for hyperspectral image visualization. The experimental results are measured by the metrics such as feature separability, standard deviation, operation efficiency and image displaying detail.The final experimental results show that fast linear prediction (LP) algorithm is an effective method for hyperspectral image visualization.

Baseflow is the main source of supplement for rivers during dry seasons. The reliable separation methods play an important role in baseflow research and water resources management and utilization. Based on the daily runoff data of Changmabao hydrological station in the upper reaches of Shule River from 1957to 2016. Based on the parameter calibration of the single-parameter digital filter method, the single-parameter digital filter method is used to study the baseflow separation of the study area. The results show that that the optimal parameter combination is when the filtering parameter is 0.975 and the filtering times is 3. The multi-year average BFI value obtained by the single-parameter digital filtering method is 0.742. The high Nash-Sutcliffe efficiency coefficient and the average relative error is less than 10%, indicating that the baseflow estimation results of this method is stable, reliable and accurate.

Objective: Based on theoretical research, this article conducts social surveys, finds problems through surveys, understands the status quo of college students' ecological civilization education, finds out its existing problems, and conducts in-depth analysis of their causes, in order to enhance college students' ecological civilization education The effectiveness of this article provides some useful references. Methods: Using questionnaire survey and interview methods, this article randomly selected students from Hunan Biomechanical Vocational and Technical College, Shaoyang College, Hunan Agricultural University, and Central South University on issues related to ecological civilization education. Results: In terms of college students' awareness of ecological civilization, college students have more than 55% understanding of some common environmental problems, especially the deepest understanding of smog, straw burning, and greenhouse effect; in college students' awareness of ecological civilization In terms of the situation, 28.33% of the surveyed college students believe that the current environmental situation in our country is very serious, 35.28% of the students think it is fair, and 35% of the students think it is not serious or unclear; what do you think is the relationship between environmental protection and economic development? The survey showed that 18.44% of the students thought it was related, and 33.33% of the students thought that the relationship was not close, and some students who were close thought it was not related or unclear. When asked, "Will you notice the environmental protection signs when you shop?" On the issue, only 5% of the students said they would pay attention, 55% of the students choose not to look at it, and 18.44% of the students are completely unaware of white pollution. The ecological civilization education of college students has achieved certain results, showing a positive development trend, but at the same time, it should be noted that there are still some college students who are indifferent to ecological civilization, and the phenomenon of environmental damage still exists. These are problems that need further solution attention.

Through the research on the source and mechanism of the dust generated by the tidal shotcrete in coal mine, and the inevitability analysis of the tidal shot from the aspect of construction technology, the main influencing factors of the dust are summarized, and the tidal shot,which is The direction of concrete dust reduction and related measures.

Dryland agriculture ecosystems occupy an extremely important position in ensuring global food security. However, they have faced problems of low soil organic matter content and poor long-term soil sustainability. Biochar is regarded as a new means of soil remediation and a pathway of carbon sequestration that has improved the soil structure and function of ecosystems due to its complex physical and chemical properties. Since there are few reviews of biochar's role in the carbon cycle of agricultural ecosystems, this article examines recent research about its influence on plant carbon assimilation, soil organic carbon mineralization and storage. We highlight the direct or potential effects of biochar on the relationships between plant root architecture and carbon storage, the soil priming effect and soil aggregation, to provide new perspectives on the study of its impacts on the carbon cycle and the implications for carbon management in dryland agriculture ecosystems.

A large number of monitoring indicators own strong correlation among them which help to better fill missing values in these sensor data. In this study, we propose an electric power quality data filling method based on correlation analysis. Firstly, normalized mutual information method is applied to deal with nonlinear correlation which makes up for the deficiency that the traditional Pearson correlation coefficient. Additionally, the measurement of correlation is calculated to obtain the closely correlated indicators. This study utilizes the regression model to build the strong regression model. Experimental results show that the approach can effectively improve the accuracy of filling, reduce the filling error, and improve the quality of data.

With the widespread of transfer learning, great success has been achieved in named entity recognition on languages without labeled data. Prior works can be mainly classified into two categories: direct model transfer and annotation projection. However, these works only utilize part of available data, including monolingual word embeddings, labeled data in multiple source languages, and unlabeled data in the target language. To make full use of these data and extract more information, we propose to train multiple teacher models on multiple source languages via the annotation projection method. Then a student model is trained on the unlabeled data in the target language with supervision from all labels obtained from multiple teacher models. Extensive experiments are conducted on three benchmark datasets, and the experimental results prove the effectiveness of the proposed method.

Recently, hyperspectral imaging (HSI) supervised classification has achieved an astonishing performance by using deep learning. However, most of them take the ideal assumption of 'closed set', where all testing classes have been known during training. In fact, in the real world, new classes unseen in training may appear during testing. Obviously, traditional supervised classification methods cannot operate correctly in the real world, which requires classifiers not only to classify known classes, but reject the unknown in order to avoid false positives. This challenge is called 'open set classification'(OSC). Considering the increased applications of deep learning in the real world, rejecting unknown classes during classification is of vital importance. To tackle it, we present a simple but effective HSI OSC method toward deep networks. In this method, we tighten the decision boundaries of SoftMax function of the last layer of the deep networks by using boxplots to analysis the statistical characteristics of the probability distribution of known classes and generate a proper rejection threshold for each known class. To test the performance of the proposed HSI OSC method, experiments are conducted on three HSI datasets. The results show that the proposed method outperforms existing state-of-the-art HSI OSC methods.

At present, the novel coronavirus disease 2019 (COVID-19) has spread rapidly worldwide. As COVID-19 impacts societies, governments, communities, and individuals, we want to provide information for governments and people to understand the situation better. In this paper, we perform quantitative analysis and prediction of the global COVID-19 pandemic. First, we summarize worldwide confirmed, recovered, death, and active cases. Second, we select eight representative countries and analyze their confirmed and death cases with considering their populations. Third, we exploit the AR model in machine learning to predict the cases of these representative countries for the next 30 days. Our analysis and prediction show that some countries, including the United States, Spain, and Brazil, are in and will still be in the severe COVID-19 outbreak. This work can provide reference information for the prevention and control of COVID-19.

In order to improve the contrast of images in different brightness environments, based on brightness preserving Bi-Histogram Equalization(BBHE), a Brightness configurable Bi-Histogram Equalization(BCBHE) system is proposed and implemented by FPGA in this paper. The system implements the BBHE algorithm, and adds the brightness configurable logic unit to realize the brightness configurable image contrast enhancement. The test results of the video processing platform of Genesys 2 development board show that: the design obtains BBHE images with different brightness configurations, and achieves the best contrast enhancement visual effect by setting image brightness threshold in different field environment. At the same time, based on the parallel operation characteristics of the FPGA, it meets the requirements of real-time image processing.

A fiber Bragg grating (FBG) sensor was presented and designed which was used to monitor the three-dimensional stress independently in rock strata. The sensing elements with FBGs in x, y, and z directions were combined in one intact material, and the stress/strain would be obtained without interference from other directions because each element could deform independently. By numerical modeling, the stress was applied respectively in different directions on the surface of the sensor, and the result revealed that the stress distributed in the direction applied was far more than other directions, which indicated that every element of the sensor was only sensitive to the stress in one direction. To get the relationship between applied stress and wavelength drifts of the FBG sensor, the calibration experiments were carried out, and the sensitivities in x, y, and z direction were obtained. It is of great significance for obtaining complicated stress state in rock strata and achieving intrinsically safe mining in coalmine.

In traditional malicious domain name detection algorithms, machine learning detection methods take a long time to extract features and the extraction methods are more complex; deep learning detection methods are easy to lose the semantic features of the entire domain name, and the detection results of a single neural network for different sample data sets are unstable . In response to the above problems, a malicious domain name detection method based on Doc2vec and hybrid network was proposed, and a new DLR (Doc2vec-LSTM-RNN) detection model was constructed. The word vector is constructed using the Doc2vec algorithm optimized on the basis of the Word2vec algorithm, which retains the semantic information of the domain name as a whole; and mixes the bidirectional LSTM network and the bidirectional RNN network in series to carry out deep-level feature extraction and enhance the robustness of the detection model; finally the Softmax function is used to output the classification result. Experimental data shows that this method has excellent performance in malicious domain name detection. Compared with traditional machine learning and deep learning detection methods, it has higher detection accuracy.

In the context of national strategies such as the energy revolution, "Internet +" and innovation drive, the transformation of traditional energy-based enterprises to integrated energy service providers has become a general trend. Multi-site integration is an important field of integrated energy services. This article takes the business model theory as From the perspective, based on the interpretation of the basic connotation and business model theory of multi-site integration, starting from the four-element model of the business-level business model, the four aspects of business layout and scope, value proposition, target customers, and profit model are the power grid under the energy Internet environment. Provide suggestions on the design of multi-site integrated business model for enterprises.

To better maintain the geometric similarity between the compressed trajectory and the original trajectory, this paper proposes a trajectory compression method based on Fréchet distance. This method selects the characteristic points of the trajectory based on the Fréchet distance, and keeps the similarity of the geometric shape characteristics of the compressed trajectory and the original trajectory. Compared with the traditional DP (Douglas-Peucker) algorithm and the TD-TR (Top-Down Time-Ratio) algorithm, the method in this paper can obtain better geometric similarity between the compressed trajectory and the original trajectory. At the same time, better visualization of trajectory data is obtained.

3D shape retrieval has always been a hot research topic in the field of computer vision, and the research goal is to perform fast and efficient retrieval to obtain 3D shapes that meet user needs. With the rapid development and popularization of touch screen devices, hand-drawn sketches have undoubtedly become the most convenient and user-friendly input form. However, the huge difference between the 3D shape and the 2D sketch is the main challenge that affects retrieval performance. In this paper, we propose a method of adding a sketch and view feature similarity comparison module during the training process to obtain the scores for the final feature descriptors under the premise of feature extraction of the 3D shape based on multi-view. Specifically, we render the 3D shape into 2D views from multiple different perspectives to represent the shape. Perform feature extraction on two types of inputs through two different networks, and design a similarity weighting module to calculate the scores of each view, so as to obtain the final descriptors. Finally, a final descriptor similarity metric network is trained based on contrastive loss. The experimental results on SHREC'13 dataset demonstrate the superiority and robustness of our method.

This paper proposes an improved data fusion method for water quality sensors. First, a deep learning network model is formed by stacking automatic encoder and sparse automatic encoder, so as to realize feature mining and sparse representation of sample data. Second, after large-scale sample training, the network model may fit complex nonlinear functions, and has certain generalization ability for low-quality sample data. As a result, the accuracy of prediction and classification can be improved. The experimental results demonstrate that the proposed method can obtain higher classification accuracy.

In power test units at all levels, the calibration of equipment is one of the daily tasks. Various departments have repeatedly purchased many standard equipment, and some calibration tasks require moving the standard equipment to temporarily build a corresponding calibration system, which is expensive and unfavorable for the maintenance of the standard equipment. The paper proposes a comprehensive calibration platform based on the network sharing of instruments. The platform optimizes the standard equipment configuration of each department and automatically allocates the standard equipment on the platform according to the calibration task. Then it builds the calibration platform and completes the calibration task in accordance with the calibration process. The platform can perform multiple same or different calibration tasks at the same time and generate corresponding calibration certificates, which reduces the workload of calibration personnel and improves the reliability and utilization of standard equipment. The paper gives the model architecture and workflow of the platform. Experiments verify the effectiveness of the platform.

With its short time-consuming, high-precision, and low-cost characteristics, Oblique photography technology has been widely used in surveying, remote sensing, and other fields. Due to the airport usually has airplanes in operation, it is difficult to obtain aerial images of airports, especially for antennas and other facilities that require relatively high modeling accuracy. This paper takes the airport Instrument Landing System(ILS) glideslope, a complex building with antennas, as an example, to carry out the research on the rapid modeling of a single camera with free-photo-control-point based on Oblique photography. First, to obtain a complete, high-resolution aerial image of the ILS glideslope, plan the path of the Unmanned Aerial Vehicle (UAV) photography, determine the flight height, flight radius, and other parameters; Secondly, improve the 3D airport model by adding orthophotos. Finally, by comparing the accuracy of the 3D modeling of the two sets of different parameters, obtain a strategy suitable for rapid modeling. The study shows that the proposed method can complete the high-precision 3D reconstruction of the airport's complex navigation facilities in a short time.

Remote sensing reconstruction technology has become an important research topic due to the rapid development of aerospace,remote sensing,and communication technologies. In order to improve remote sensing reconstruction image quality, we design of a rapid Gradient Projection method. In the traditional Gradient Projection method, the searching direction changes each setp. Now we propose a rapid searching method by running with fix step. Experiment results show that the rapid Gradient Projection Algorithm get the better reconstruction image. The running results are shown by two remote sensing pictures. Further research is required in remote sensing edge intelligence technology to improve its depth and breadth of application.

Through the design of orthogonal experiments, different content of clay, steel slag powder and polycarboxylic acid water-reducing agent were mixed into ordinary Portland cement, and the grout was prepared according to different water-cement ratios. The analysis was conducted under standard curing conditions. Stone rate and compressive strength at different ages. The test results show that with the increase of the clay content, the stone rate of the grout consolidation body increases, and the compressive strength decreases. As the amount of steel slag powder increased, the stone rate and compressive strength of the slurry consolidation body decreased.

At present, the calculation method based on statics does not consider the impact of the conductor on the crossing structure under the condition of disconnection or running. Therefore, the research on the element type of the suspension crossing frame and the conductor in numerical calculation and the behaviours of conductor breaking and running were carried out. Through the free swing test of the conductor, it was found that the conductor had certain flexibility under a certain length. Truss element should be selected to discretize the fiber rope of the conductor and crossing frame and this method could simulate the physical characteristics of the conductor and fiber rope objectively and truly. In the case of running line, the horizontal velocity of the conductor had almost no change along the axial direction of the conductor, while the vertical velocity presented a fluctuating distribution along the axial direction. In the case of the broken conductor, the horizontal and vertical velocity of the conductor were fluctuating along the axial direction of the conductor. The height of the conductor not only affected the horizontal velocity of the conductor, but also affected the vertical velocity of the conductor. It had important reference significance for the numerical calculation of nonlinear dynamics of the suspension crossing frame.

During the mid-flight of the ballistic target, there are two movement modes: translational and micro-movement. The existence of translation will cause tilt and translation of the time-frequency curve of the scatter point echo, which will affect the extraction of ballistic missile micro-motion information. In response to this problem, this paper proposes a Shi-Tomasi corner detection algorithm from the perspective of image processing, which can effectively extract the corner information in the image. Afterwards, regression analysis is performed according to the obtained corner point information to realize the estimation of translational parameters. Through simulation experiments, it is concluded that the algorithm can better realize the compensation of translational components.

With the rapid development and popularization of 5G and C-V2X, services based on C-V2X are rapidly expanding. Specially, the positioning accuracy is the most basic requirement in V2X service. According to the different requirements for V2X use cases, the positioning accuracies are also different. So the positioning schemes are various according to the positioning requirements. This paper contains a study of requirements, architecture, key technologies and demonstrations in high accuracy positioning for V2X services. Combining the scene analysis and performance requirements, high accuracy positioning, as a key part of the whole C-V2X system, its architecture can be divided into device-centric positioning architecture and network-centric positioning architecture. In addition, we summarize the key technology for high accuracy positioning of vehicles and demonstrate the proposal through testing.

Through the analysis of the safety risk of dangerous goods storage and transportation in port, leakage, fire and explosion are the common accident types. The mechanism research of common accidents is carried out to understand the occurrence and development process of accidents, find out the key blocking links, and improve the efficiency of emergency disposal. A three-dimensional numerical simulation scheme of major accidents is proposed, which can simulate the whole development of accidents, and can be used for quantitative risk analysis before accidents and emergency decision-making in the process of accident disposal.

Aiming at the features of hyperspectral imges with large amount of redundant information of hyperspectral images, small correlation between features and categories, small sample size, and high-dimensions data, a model of hyperspectral image classification based on an improved mRMR band selection method and GS-CatBoost is proposed. First of all, using the mRMR improved by K-L to select the optimal band subset with high correlation between features and category, low redundancy, and large amount of information. Then, the Gabor filter is embedded in PCA and LDA combined dimensionality reduction to complete the extraction of space-spectrum joint features. Finally, using grid search to optimize the CatBoost algorithm to classify the extracted features. Experiments show that the proposed model fully and effectively extracts the space-spectrum joint features of hyperspectral images. In the Salinas Scene dataset, OA is 97.87%, AA is 99.01%, and Kappa coefficient is 0.9763.

The study of urban spatial structure is very important for understanding the relationship between people and urban infrastructure as well as urban planning . This paper selected the 2016-2019 NPP-VIIRS NTL data and POI data of Nanchang City to conduct a pixel-level correlation analysis of Nanchang urban districts and counties. Firstly, the NPP-VIIRS and POI datasets should be respectively preprocessed to synthesize NPP-VIIRS annual average dataset and the POI kernel density dataset. Secondly, these datasets were respectively subjected to logarithmic transformation. Finally, they were divided into administrative districts for linear regression analysis. Experimental results showed that the correlation coefficients between NPP-VIIRS NTL data and POIs data gradually decreased from urban to rural districts.

In 3D computer vision processing, the introduction of deep learning into 3D research has always attracted much attention. In this paper, we introduce 3D mesh deformation into the animation of ecological environment research, adopt the 3D processing tool of Pytorch3D, and propose a 3D mesh deformation method based on the interpolation Loop subdivision. To prove the superiority of this algorithm, we compare the mesh deformation under the Loop subdivision and interpolation Loop subdivision. The experimental results show that after we adopted the interpolation Loop subdivision when the mesh deformation predicts the target mesh, the result of the deformation mesh is better than the Loop subdivision in terms of details. Thus, mesh deformation can be applied in the animation of the ecological environment, such as the "camouflage" of animals, which is of great significance to the animation or film related to the ecological environment.

Under the impact of frost heave and thaw settlement of seasonal frozen soil, freezing pulling and horizontal tilt of piles often occurs. Aim to the above problems, this paper proposed a material using ceramsite replacement concrete as the foundation to reduce heat exchange with atmosphere. The results showed that when the replacement rate of ceramsite is 80%, the density of the blocks is 1896 kg/m³, which is 19.3% lower than that of plain concrete. Also, the addition of ceramsite significantly reduced the thermal conductivity of concrete. The minimum thermal conductivity of tested blocks is 0.524 W/(m.K), which is 58.6% lower than that of ordinary concrete. Meanwhile, the strength of concrete decreased the addition of ceramsite. When the replacement rate is 80%, the compressive strength and splitting tensile strength are 18.1 and 2.7 MPa, respectively, which are 54.7% and 42.6% lower than that of plain concrete. Taking the climatic environment in the Hexi area as the boundary conditions, a numerical simulation on the design and optimization of the thickness of the insulation system was carried out. It was found that the installation of 2 m insulation concrete can effectively increase the temperature of the soil in extreme environments and avoid frost heave.

Environmental factors have a great influence on the autonomous landing process of UAV. In order to enhance the environmental adaptability of UAV's landing control, this paper takes a certain high-speed UAV as the research object, analyzes the main causes of the error in UAV's landing under the wind interference, and puts forward the improvement measures. The object model was built under the Matlab/Simulink platform to simulate the closed loop control system of UAV's autonomous landing, and the Monte Carlo method was used to verify the robust performance of the control system in the presence of the wind interference. The simulation results show that the improved landing plan can effectively reduce the landing error of UAV under the wind interference and improve the landing accuracy and safety of UAV.

The urban community micro-renewal planning project represented by the first-line and new first-tier cities has begun to gradually sprung up. This paper analyzes the excellent practice of urban community renewal planning in Datangxiang of Hangzhou, summarizes the project implementation strategy and community public space planning techniques, in order to provide working ideas for urban community micro-renewal construction, in order to further improve the quality of community public space and household life satisfaction.

As technology evolution, the solution for society security system is a hot research topic. Video surveillance is an important guarantee for society security. To meet various application scenarios, quick end-to-end (E2E) response is the key of video surveillance system. Mobile edge computing (MEC) could reduce E2E delivery delay by processing data nearby the data source. This paper introduces a MEC based solution that uses special hardware, graphics processing units (GPU), to accelerate graphic data processing. Taking the limited resource of edge scenario into consideration, virtualization technology is used to share computing resource on demand. The solution also proposes deployment policy basing on functional component's requirement. Finally, this paper verifies the solution and puts forward recommendations.

Based on the analysis of spatial position of the working-rope for four-rope freight ropeway, a mechanical model of the interaction between the working-rope and running car is proposed, which comprehensively reflects the characteristics of the working-rope system. Based on the calculation method of elastic catenary, the nonlinear equations for analysing the working system of four-rope freight ropeway are established. According to the typical design conditions of four-rope ropeway, the tension calculation of four carrying ropes is completed when the length of carrying rope changes. With the increase of the length deviation between the carrying ropes, the imbalance of the tension between the ropes is obvious. The tension of the carrying rope of the four-rope ropeway is very sensitive to the change of the rope length, and the coupling effect between ropes makes the breaking risk of carrying rope increase sharply. The results provide a reference for the safety factor analysis of the four-rope freight ropeway.

"Fire-fighting" post-maintenance is the existing vehicle maintenance service mode. When the vehicle maintenance and other faults, from the demand report to the successful maintenance of service personnel needs a long time, and in the period of receiving the task, time is to grab the "lifeline". Temporary stop-trade union causes great losses to the strategic deployment of troops, so preventive maintenance of vehicles is an important guarantee system for vehicle maintenance management. Its role is not limited to compensating the physical wear of machinery to avoid the occurrence of major faults, to ensure the normal operation of vehicles, reduce maintenance costs and improve the use of economy. At the same time, useful information can be fed back to production and maintenance units to improve the quality of products and maintenance. Therefore, the performance, quality and actual use economy of some preventive maintenance equipment are very important for mechanical equipment. This paper will study and design a kind of preventive maintenance equipment, which aims to solve the problem that most preventive maintenance equipment on the market cannot control the amount of oil when adding lubricating oil to automobile engine and other mechanical parts, and it is easy to scatter the lubricating oil and contaminate other areas.

With the increasingly prominent problems of water ecology and water environment, regional overall planning and systematic management of water environment is a new mode of water pollution harnessing work under the background of the new era. The effectiveness of water environment governance largely depends on whether the scheme is reasonable or not. Therefore, intuitively reflecting the design results is the first step of water environment comprehensive treatment. At present, the scheme design mode of water environment governance mainly uses CAD to design and renderer to render, which can no longer fully meet the needs of design with a fixed perspective. Based on this, this paper proposes a scheme design method of water environment comprehensive treatment based on UAV tilt photography technology. Firstly, the three-dimensional model of the research area is obtained by UAV tilt photography, and then the scheme is designed based on the three-dimensional model. Finally, the scheme based on the three-dimensional model is compared with the traditional design scheme. The results show that the water environment comprehensive treatment scheme based on oblique photography has more diverse functions.

According to the specific characteristics of software, hardware and network protocols, the cyber security problems of satellite communication network have gradually attracted the attention of the industry in recent years. This paper proposes a technical framework including information collection and detection, vulnerability mining and penetration testing. It introduces mining methods such as taint analysis, symbol execution and fuzzy testing, and combines with machine learning algorithms to improve the efficiency and accuracy of vulnerability mining. It uses buffer overflow, SQL injection, cross-site attack and Trojan horse penetration to test the security of satellite communication network. It is helpful to improve the ability of proactive defense and security guarantee of satellite communication network.

Based on the large color steel building data of Yinchuan in 2005, 2010, 2015 and 2019, this paper uses standard deviation ellipse, kernel density estimation, nearest neighbor index and multi-distance spatial clustering method to explore the clustering characteristics and spatial-temporal pattern evolution of large color steel building in Yinchuan. The results show that :(1) from 2005 to 2019, the spatial distribution direction of large color steel building in yinchuan presents a stable "northwest to southeast" direction, and the center of gravity has been shifted to the southwest, with the transfer distance becoming smaller and smaller.(2) With 4 national and provincial industrial parks as the core cluster areas, the cluster features are obvious. As time goes on, it spreads to the periphery and tends to stabilize.(3) All the four periods presented condensed distribution and gradually weakened agglomeration. In 2010, the agglomeration intensity and agglomeration scope reached the peak, which were significantly improved compared with 2005, but they were roughly the same and gradually weakened after 2015.

To address the problem of Sybil attacks in the wireless network, an unsupervised attack detection method using signal frequency bias distribution features is proposed. The method first estimates the signal frequency bias of the emitted signal of each wireless device and then calculates the signal frequency offset distribution characteristics, next it uses the DBSCAN clustering method to perform cluster analysis based on the distribution features. This method does not require prior learning of each device's signal features and is not affected by the changing of channel status. Experiments based on the real-world environment and commercial hardware show that the proposed method can effectively detect the Sybil attack and achieve high accuracy in identifying malicious devices.

This paper briefly introduces the general situation of wuhan Anjing community project, and analyzes the existing problems of this elderly community from the perspective of community planning and design on the basis of preliminary investigation. By means of low-impact transformation and micro-governance, this community is designed for transformation from the aspects of road traffic organization, transformation of main entrance and exit gates, micro-renewal of public space, etc. Through functional renewal, the vitality of the old community is explored, the overall environmental quality is improved, and reasonable suggestions are provided for its sustainable development.

By designing orthogonal experiments, mixing different amounts of clay, steel slag powder and polycarboxylic acid water-reducing agent into ordinary Portland cement, prepare grouting liquid according to different water-cement ratios, and analyze the grouting liquid under standard curing conditions. Fluidity and water separation. The test results show that: with the increase of the clay content, the fluidity and water separation rate of the slurry gradually increase. As the content of steel slag powder increases, the fluidity first increases and then decreases, but the overall trend is increasing, and the water separation rate increases.

This paper uses the survey data of 344 herdsmen in Xianghuang Banner, Siziwang Banner, and Alxa Left Banner that implement grassland ecological compensation policy in Inner Mongolia Autonomous Region, combined with the Sustainable Livelihood Framework (SLA), and quantitatively analyzes the response of all aspects of livelihood capital to herders based on the SEM model the impact of grassland ecological compensation policy behavior. The government should proceed from the difference of each livelihood capital, combine the economic benefits of herders with the response to the grassland ecological compensation policy, and put forward policy improvement opinions based on the livelihoods of herders, with a view to improving the pastoralism for the government. The enthusiasm of households to respond to the policy provides a scientific basis for achieving the strategic goal of grassland ecological compensation.

Battlefield situation is the basis of cognitive consistency of battlefield situation understanding. In the service of situation information organization, displaying and distribution is necessary to solve the problem of situation information difference between users at different levels and different combat tasks. Through the research of data Lake technology combined with advanced data science and machine learning technology, the situation recognition and processing architecture based on data lake is proposed to solve these problems .It includes the network architecture, the situation cognition and processing methods which can improve various types of data storage and big data processing problems.

Urban green space (UGS) plays indispensable role to maintain the ecological balance of a city. Remote sensing & GIS techniques can play vital role in the accurate estimation of the UGS. This study attempts at a new method of extracting the UGS from high resolution imagery data of Gaofen-2 satellite. The proposed method combines the strength of different transformation techniques i.e. KT transform, principal component analysis and NDVI in order to accurately map UGS. Different combinations were checked to classify the Gaofen-2 satellite imagery of Lanzhou city. The classified image was assessed for classification accuracy and it was observed that the overall accuracy was 89.78% with the kappa coefficient of 0.8125. It was observed that the proposed method can yield relatively high accuracy compared to the individual transformations such as NDVI thresholding.

UAVs have received extensive attention and research due to their superior mobility and flexibility, and they replace manned aircraft to perform tasks in some specific complex environments. In order to deal with the complex and changeable environment and various obstacles, it is necessary to use appropriate algorithms to plan the UAV path. This paper divides the existing UAV path planning algorithm research into three categories: traditional algorithm, intelligent algorithm and fusion algorithm. The basic principles, advantages and disadvantages of various algorithms are analyzed, and the future research and development are prospected based on the actual operation of UAV.

The research aims to discuss the path of inheriting intangible cultural heritage in Northeast China through college art education. From the perspective of cultural protection and inheritance, the feasibility of inheriting intangible cultural heritage in Northeast China through college art education is analyzed. The specific path to inherit intangible cultural heritage in Northeast China through college art education is discussed combined with the individual practice of Changchun University, so as to build a bridge of protection and inheritance between the intangible cultural heritage in Northeast China and college art education. Inheriting intangible cultural heritage through education conforms to the needs of social development and is also an effective way to protect and inherit intangible cultural heritage. It could carry out educational inheritance by four kinds of ways of changing ideas, bringing into curriculum system, reforming teaching methods and deepening scientific research, which is of important theoretical significance and practical significance for colleges and universities to create discipline characteristics and protect and inherit intangible cultural heritage.

Before India's early Buddhist view of life and death was introduced into China, the traditional view of life and death of Chinese hundred schools had already formed a relatively perfect philosophy system, such as Mohism, Taoism and Confucianism. Their philosophy has a certain height of the discussion of life and death, and in this case, through the investigation of Jiangxi Buddhist architectural culture, from the perspective of Jiangxi to explore how the Buddhist philosophy is to change itself, and actively integrate into China and Jiangxi's environmental secular world.

Due to the influence of the wall thickness, uneven heat transfer, and heat generation inside the resin during the molding of the composite material, the uneven temperature field distribution of the composite material is caused. This paper uses ABAQUS to perform finite element simulation on the temperature field of the forming process and obtains the distribution of the internal temperature field of the composite material. On the premise of obtaining the temperature field, through thermo-solid coupling simulation experiment, the influence of various factors on the entire curing process is compared. Based on the use of finite element simulation software, several comparative tests were carried out, and the residual stress problems in the curing process were verified by calling the stress and strain values of representative points. This article focuses on the analysis of temperature and energy data in heat transfer and 15 sets of stress-strain data under coupling action. On the premise of giving the reasons for each data, the accuracy and practicality of the data are analyzed.

The development of ground-based, airborne and spaceborne remote sensing has greatly facilitated the identification and diagnosis of various objects. Corresponding algorithms and methods of removing interference from remotely sensed imagery have been proposed. Nevertheless, the studies on anti-interference ability of selected features have not been fully considered. In our study, the hyperspectral reflectance of leaf-scale powdery mildew (Erysiphe graminis) on winter wheat were collected as the testing dataset. A total of seven representative spectral features of Landsat-8 Operational Land Imager (OLI) and GaoFen-1 Wide-Field-View (WFV) was selected, namely, original blue, green, red, near-infrared (NIR) bands and normalized difference vegetation index (NDVI), normalized difference greenness index (NDGI), structure insensitive pigment index (SIPI). Four hyperspectral vegetation indices including red edge (MSR) simple ratio index, NDVI, green band and SIPI were also selected. Three primary background noises including soil, cloud and white poplar (Populus alba L.) were added into the spectral signal. The correlation coefficient (R) between disease severities (0, 1, 2, 3 and 4) and spectral features was used to estimate the anti-interference ability. The results show that there is a generally similar spectral performance for the two sensors, but Landsat-8 OLI is superior to GF-1 WVF in terms of spectral response. The green band was greatly affected with the R values decreasing from 0.77 to 0.35. The MSR and NDVI showed a gradual decrease with the increase of three background noises. The study shows that background noises must be removed when acquiring spectral data and stable spectral features should be also selected by evaluating the anti-interference ability.

The supply of electricity is directly affected by the structural safety of transmission tower. The unsuitable power line type can impose extra forces on transmission tower. The failure within transmission tower results in power outage because the designed power transmission tower cannot bear the extra force loading. In this paper, the mechanical responses in transmission tower with different power line types were calculated by means of finite element software. Commercial software Abaqus was employed for analyzing the structural safety of transmission tower. Ten kinds of power line were chosen to impose static forces on transmission tower. Based on the finite element results, the maximum stress and displacement were obtained. When the dimension of power line is less than a certain value, the transmission tower is safe; otherwise, the transmission tower may collapse.

The existing maintenance service mode is basically "fire-fighting" after-the-event maintenance and repair. After the failure of mechanical equipment, it takes a time to report the requirement to the service personnel to achieve the success of maintenance. The consequences of sudden failure in the operation of mechanical equipment are very serious. In order to predict the operation status of mechanical equipment in advance and avoid causing heavy losses, the operation status of mechanical equipment can be predicted by testing the lubricant composition of mechanical equipment, which can effectively reduce or even avoid the occurrence of faults and accidents.

With the rapid development of economy, transportation, and culture, people are increasingly eager to return to nature and enrich humanity. As a bridge between nature and humanity, mountain villas are ingeniously integrated with mountains, vegetation, and architecture, forming a new pattern of mutual penetration and mutual construction of architecture and nature, which has become a new trend in the development of modern architectural patterns. This article takes a mountainous area in Shandong Province, China as an example, uses geographic information system to analyze the spatial structure of mountain villas, and conducts planning and design based on the local status quo, which provides the necessary scientific basis for the planning and design of mountain villas.

In today's Internet age, great changes have taken place in the way people live and work. Under this social background, the future development direction of libraries must be adjusted to keep pace with the times, and new technologies such as artificial intelligence should be driven to build an intelligent development mode. Taking big data as the breakthrough point, this paper summarizes the current problems faced by Chinese libraries in the process of intelligent construction, and puts forward its countermeasures from the aspects of information resources, service management mode and technical capability.

In order to solve urban development problems and achieve sustainable urban development, building smart cities has become an essential core concept for urban development in the world today. From the perspective of current smart city needs, this article introduces the concept and basic characteristics of CIM, an information technology closely related to smart cities, and analyzes its key technologies BIM (Building Information Modeling), GIS (Geographic Information System), IOT (The Internet of Things), and a brief overview of the relationship between the three, laid a preliminary foundation for further related research.

Small island states are regarded as the poster children in the resilience of global climate change, while their sustainability varies within individual states considering the complicated interactions of spatially differentiated environmental, economic, and social factors. As the typical case of sea-locked scattering atolls, Kiribati shows its dramatic sustainability variations in different spatial scales. The findings of place-specified questionnaires from Kiribati citizens show that local perspectives on sustainability vary among urban areas, rural areas, as well as remote island areas. The results of the research hopefully provide policy implications for space-specific small island sustainability resilience.

Rail transit has been playing a vital role in comprehensive transportation system, there goes without saying that rail transit will stimulate economic growth of the regions alongside railway lines, its coverage and development pattern will exert widespread and far-reaching impact on the area where railway travels through. In Xi'an-Yinchuan High-speed Railway construction setting, firstly, building an accessibility model based on the GIS platform and comparing analysis of traffic accessibility changes in the study area before and after the opening of the high-speed rail. Secondly, relying on the railway network and economic relations to establish comprehensive indicators System, build a coupling model of rail transit and regional economy in Shanxi-Gansu-Ningxia. Finally, predicting the coupling relationship between economy and transportation after the opening of high-speed rail. The experimental results show that the accessibility of cities along the line changes greatly before and after the completion of the high-speed rail. The high-speed rail line obviously promotes the economic development of the old revolutionary areas and surrounding cities along the line, and provides guiding suggestions for further improving the rapid railway network.

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: 23 September 2022