Table of contents

After successfully held for two times when the first one was organized in Taiwan, and the second one was held in Guilin, China, the 2020 3rd International Conference on Advanced Algorithms and Control Engineering (ICAACE 2020) was taken place on April 24 via online platform due to the pandemic of COVID-19. In light of the prevention and control of COVID-19 and travel restrictions worldwide, the organizer could not hold the conference physically, that's why we have to adjust the format to online meeting to avoid personnel gatherings, so that the conference could go ahead as scheduled. ICAACE 2020, supported by AEIC Academic Exchange Information Centre, Chongqing University and National Pingtung University of Science and Technology, aims to provide an international forum for the experts, scholars, practitioners and engineers around the globe to share their expertise, disseminate the advanced research, discuss the latest challenges and enhance their collaboration in the field of advanced algorithms and control engineering.

The committee of ICAACE 2020 was composed of over twenty experts and scholars with Prof. W. Qin from Chongqing University and Assoc. Prof. Y.H. Lin from National Pingtung University of Science and Technology as the General Conference Chair.

List of Committee member are available in this pdf.

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

The independent enrollment of colleges and universities is a heavy task for colleges and universities. With the development of information technology, when colleges and universities conduct independent enrollment, many data hit in a flash. The statistical analysis of data brings difficulties to the general independent enrollment management system. This paper relies on quantum evolution algorithm to optimize the independent enrollment system, aiming to sort out and optimize the enrollment, the work flow of student management provides real-time data query and analysis services for relevant functional departments and individuals, realizes the linkage between the enrollment system and other systems of the school, improves the efficiency and management level of enrollment management, effectively improves the efficiency of independent enrollment, opens data interface for the access of other systems, and provides new work, student information management and financial management in the later stage work provides convenient and efficient information support.

As the command and control center of the whole power grid operation, the power dispatching system has huge and complex data information, which makes the traditional power grid dispatching information platform difficult to meet the needs of power grid operation monitoring in information integration, analysis, calculation and storage. Therefore, cloud platform is introduced into the construction of power dispatching automation system. This paper takes the power dispatching automation cloud platform as the research object, studies its architecture, and proposes a cloud platform task scheduling model based on improved particle swarm optimization, aiming to improve the efficiency of cloud computing resource allocation, improve the quality of cloud services, and solve the task scheduling problem of the power dispatching automation system.

This paper mainly conducts related research on the algorithm of the Tibetan acoustic model. Firstly, a Tibetan Lhasa pronunciation dictionary is constructed based on words and monossssyllables, and then compared. The experimental results show that the phonetic dictionary constructed by words is superior to the phonetic dictionary constructed by monosyllables. At the same time, taking phonemes and single syllables as the modeling unit of the acoustic model, the modeling unit of the acoustic model was studied and a comparative experiment was carried out. Experimental results show that phonemes are better than single syllables as acoustic model modeling units.

With the continuous development of the Internet in the world today, the proliferation of network information makes it difficult for people to effectively screen out current hotspot information. In order to solve the problem of how to retrieve the current hot information quickly and accurately under the massive network information, an automatic network information retrieval method based on the improved DBSCAN clustering algorithm is proposed. The retrieved related keywords are combined to reduce the feature terms, which effectively solves the problem of repeated acquisition of public resource object neighbourhoods, greatly improves the accuracy and efficiency of the clustering algorithm, and realizes automatic retrieval of network information hot spots. The results show that the automatic network information retrieval method based on the improved DBSCAN clustering algorithm proposed in this paper can quickly and accurately find the current information hotspots on the Internet, help users to obtain the hotspot information of their own most interest, and promote the progress and development of the Internet.

During the analysis of the vertical boom of bridge inspection vehicle, it is not easy for the designer to provide a good design scheme quickly. In order to find a professional CAD software which can quickly obtain the ideal design scheme, the BP neural network algorithm is adopted to obtain the design solution by means of mapping. The better schemes of vertical boom are selected for different types of bridge inspection vehicles. These schemes are used as sample data to train the BP neural network for obtaining weights and thresholds. The trained neural network is used for the rapid design of the vertical boom of bridge inspection vehicle. As long as the design parameters are input, the design scheme of the vertical boom can be output directly.

Traditional data mining methods usually need to visit the database repeatedly to determine the frequent item set, which makes the data server burden heavier and reduces the efficiency of data mining. To solve this problem, this paper combines the immune mechanism and genetic algorithm dynamically to improve the traditional genetic algorithm (GA), and proposes a data association rule mining method based on improved immune genetic algorithm (IIGA), which realize the effective analysis of big data. The experimental results show that the algorithm we proposed is better than immune genetic algorithm and Apriori algorithm in data mining time and association rules mining accuracy, which can be better applied to data analysis. The research results have positive reference significance for the field of data mining.

At present, the electrolytic aluminum control system uses a first-order algorithm to filter the voltage of the electrolytic cell with serious hysteresis and weak tracking. Aiming at the above problems, this paper researches and designs an adaptive filter based on double fuzzy algorithm. The change of the electrolytic cell voltage measured, the absolute value of the difference between electrolytic cell measurement voltage and filtered electrolytic cell voltage are used as the two input variables of the fuzzy controller 1. The change of the electrolytic cell voltage measured,the absolute value of the difference between electrolytic cell measured voltage and corrected electrolytic cell voltage are used as the two input variables of the fuzzy controller 2. The two fuzzy controllers calculate the filter coefficient and the correction coefficient respectively through a fuzzy algorithm. Simulation results show that the tracking time of the double fuzzy algorithm is 78% shorter than that of the first-order algorithm, and the root mean square error is reduced by 70% compared to the first-order algorithm. It can provide a feasible and excellent filtering algorithm for the intelligent control of electrolytic aluminum.

Aiming at the failure of path planning in complex three-dimensional terrain, a path planning algorithm based on Hopfield neural network is proposed. According to the three-dimensional terrain, the undulating terrain and obstacles are transformed into a calculable regular figure, and the terrain function model is established according to the flow field control equation; the terrain function model is effectively integrated with Hopfield neural network algorithm. The algorithm is applied to complex three-dimensional terrain environment, can avoid undulating terrain and obstacles, and find an optimal path, which lays an important foundation for the navigation vehicle path planning.

Aiming at the restoration problems for multicast service in multi-domain optical networks, a multicast routing restoration algorithm in multi-domain optical networks based on the n-person non-cooperative game is proposed by adopting the Breadth First Search (BFS) strategy and n-person non-cooperative game theory. This algorithm optimizes the searching sequence of BFS algorithm and reduces the searching scope by the competitive selection relation of the game theory. The algorithm analysis and experimental results show that the algorithm has low time complexity, reduces the computational time of the restoration path, and reduces the blocking rate of the multicast restoration service.

Since entering the new century, Internet technology has developed rapidly and has become an important infrastructure in today's society. In recent years, with the popularization of optical fiber applications, the network bandwidth has been greatly improved, and the growth rate of network traffic has also shown explosive growth. The traditional TCP/IP network has exposed many serious problems in the face of increasing traffic. In particular, the issues of scalability, reliability, security, flexibility and mobility are more prominent. In order to solve the shortcomings of the existing Internet architecture, the current domestic and international schemes mainly include "improvement" and "revolution". Improvement is the gradual improvement of the deficiencies of the existing Internet system. However, this method cannot essentially solve these deficiencies, and it is difficult to meet the needs of future network development. The revolution is to redesign the information-centric network as the Internet system structure, completely changing the existing Internet system in terms of scalability, security and mobility, in order to adapt to the needs of future social development. Named-Data Networking (NDN) in many information-centric network architectures is a network architecture with excellent research and development. This article focuses on the research of NDN network caching technology. In terms of caching decisions, a multi-attribute probabilistic caching algorithm is proposed, which can effectively reduce the cache of redundant data in routing nodes in NDN networks and improve the utilization of routing node cache space, reduce network delay, increase the cache hit rate of routing nodes, and improve the overall performance of the NDN network.

With the increase of the hidden layer, the weight update of the LSTM neural network model depends heavily on the gradient descent algorithm, and the convergence speed is slow, resulting in the local extremum of the weight adjustment, which affects the prediction performance of the model. Based on this, this paper proposes an optimized LSTM neural network model based on adaptive genetic algorithm (AGA-LSTM). In this model, the mean squared error is designed as the fitness function, and the adaptive genetic algorithm (AGA) is used to globally optimize the weights between neuron nodes of the LSTM model to improve the generalization ability. The experimental results show that, on the UCI dataset, the prediction accuracy of the AGA-LSTM model is greatly improved compared to the standard LSTM model, which verifies the rationality of the model.

Positive invariant sets play an important role in the system theory and a:lication of dynamic systems. Firstly, in order to judge the inclusion relation between positive invariant sets of systems, the equivalent conditions for judging the inclusion relation of special positive invariant sets are derived for two special positive invariant sets. Three specific positive invariant subsets are discussed, and the verification of the inclusion relation of positive invariant sets can be transformed into a class of numerical problem in the form of optimization, which simplify the conditions of readily implemented. Finally, numerical examples are given to illustrate our conclusion.

In this paper, ProcessLink is a user behavior judgment and recommendation algorithm based on the information system business process. The purpose is to provide users with reliable unknown process selection. The algorithm idea is as follows: firstly, collect and analyze historical data, establish the relevance feedback set of "Time-Role -Process", establish the interest relationship decision table of each role according to the process flow link behavior between users. Starting from each process node, the Apriori algorithm completes a round of initial filtering on these relationships, and obtains the similarity association degree of each role node in the process link; finally, the recommendation sorting is carried out through the recommendation algorithm model matching and scenario similarity calculation. This research realizes the accurate prediction of the user's next link and gives the corresponding opinions. The experimental results show that the algorithm is effective and accurate in the business process.

The traditional SSD algorithm has a serious abstraction of feature extraction content, which makes it difficult to achieve effective detection of small targets. At the same time, the problem of feature layer fusion is difficult due to different scales. In this paper, an improved SSD based target detection algorithm is proposed. By introducing feature enhancement method, the adjustment steps of high-level feature size are omitted, Which makes it unnecessary to reduce the dimension of features, and at the same time, it uses the multi-scale candidate area which accords with the proportion of pedestrians in the detection network to enhance the feature extraction ability of small targets, effectively improves the accuracy and operation speed of SSD algorithm, and saves the loss of the network.

The upper limb rehabilitation robot is used to assist patients with upper limb hemiplegia for rehabilitation training. During the passive rehabilitation training of the patient, the trajectory of the rehabilitation training must be as smooth as possible, so that the patient will not feel discomfort when pulling the affected limb. The passive control algorithm of the existing upper limb rehabilitation robot is not ideal for the lag processing of the system. This paper designs a passive control algorithm based on PI hysteresis compensation. The hysteresis effect of the system can be greatly reduced by introducing the hysteresis compensation term u_c. Experimental results show that the algorithm can effectively eliminate the hysteresis effect of the system.

Salp Swarm Algorithm (SSA) is a novel optimization algorithm which is widely used in engineering problems. An improved SSA inspired by quantum computing is proposed in this paper. The principles of quantum computing, such as qubits and quantum states, are introduced into the original SSA in order to overcome the defect of trapping into local optimum easily. Instead of updating the salp position directly, the quantum angle related to the quantum state is updated to increase the diversity of states. Two multidimensional benchmark functions are used to verify the proposed improved SSA, the result shows that the introduction of quantum computing can successfully prevent the SSA from falling into the local optimum and increase the accuracy.

The problem of multi underwater vehicle cooperative seizing is an important part of the research of multi-underwater-vehicle cooperative task self-organization, which is widely used in military, rescue and other fields. In this paper, the problem of multiple underwater vehicles (AUVs) encircling is a group of AUVs, which can encircle a target body through cooperative cooperation. The stability of the system can be improved by applying the wolf swarm algorithm to the multi underwater robot system. In this paper, we mainly study the problem of multiple underwater vehicles in two-dimensional space. Wolf swarm algorithm abstracts three kinds of swarm intelligence behaviors, calling wandering behavior, summoning behavior and preying behavior, puts forward a new swarm intelligence algorithm by simulating Wolf-swarm predation. The effectiveness of the algorithm is verified by numerical simulation.

It is benefit for college students to explore the characteristics of online entertainment consumption and give them appropriate guidance. The Online entertainment consumption of some undergraduate students is investigated in this paper, and the K-means algorithm is used in the survey to carry out clustering analysis. The results show that in terms of online entertainment consumer behaviour, the consumption amount is polarized, consumption is gender-differentiated, consumer contents are diversified, consumer has more copyrighted-awareness., etc. From the clustering results, the K-means algorithm is more effective for analyzing the characteristics of online entertainment consumption behavior.

The peak period for the decommissioning of new energy vehicle power batteries in China is approaching, and it is imminent to establish a complete and efficient waste battery recycling system. In order to improve the recovery efficiency of waste batteries in China, this paper constructs a new type of waste battery recovery system, and proposes a new method to solve the location problem of the waste battery recovery center by using a method of goal ranking and a heuristic algorithm of greedy take-off. The grey prediction method of amplitude compression is used to simulate and predict the total battery recycling amount of each recycling station in a city, and then establishing a dual-target location model with the goal of maximizing total revenue and optimizing brand serviceability. Finally, the model is solved by the heuristic algorithm of greedy take-off to obtain the optimal location scheme of recycling center, which proves the feasibility of the model.

The server backend operating system for the Servers and scientific computing necessities is a big market, and the majority market share of this market is hold by the Linux based Operating System for a very long time period. However, as running in backend lack of humanity monitoring, and the default signature-based security measures are ineffectual for detecting stealth attacks, the Linux OS needs an intelligent intrusion detection solution. This paper proposed an automatous method to inspect the contiguous system call traces and identify the abnormal system call pattern only by analyzing a trace of small window size, rather than probing the full traces.

In order to monitor the OSPF (Open Shortest Path First) large-scale autonomous system in real time, for the shortcomings of current topology discovery methods based on OSPF protocol, firstly a hierarchical modelling method of OSPF large-scale autonomous system is proposed, which describes the autonomous system quantitatively. Secondly, a topology generation algorithm based on the link state database and an autonomous system model comparison algorithm are put forward in this paper. Finally, the experiment of monitoring the autonomous system in the actual network is carried out. The link state database is collected on any router in each OSPF area. The experiments show that the model and algorithm can be used to obtain the network topology map completely and accurately without the extra network burden, and to monitor the changes of network topology in real time. The model and algorithm proposed in this paper are helpful to realize the topology generation and monitoring of the large-scale autonomous system.

In order to improve the detection efficiency and quality of pressure vessels, a pressure vessel inspection robot control system based on programmable logic controller PLC is designed. First, the basic structure of the inspection robot is briefly introduced, and then the software and hardware of the control system of the inspection robot are designed in detail. Hardware design includes overall hardware design, hardware selection, hardware electrical circuit design, actual layout of hardware, etc. Software design includes software design process and program design, among which Mitsubishi FX5U series PLC and FX5-40SSC-S motion control module are the core of the control system. Finally, it is experimentally verified that the control system can control the detection robot well and has high engineering value.

The detection of weak fault signals is realized by applying non-resonant parametric excitation to Lu chaotic system. Periodic signals far larger than the characteristic frequency of the system are taken as input, the sharp change of the system attractor is observed, and the existence of weak signals is detected. The conditions that the parameters of the detection system should meet are deduced by using the averaging method and Lyapunov method. Numerical research shows that the detection system can quickly reach a stable state. When the amplitude of the detected weak signals changes slightly, the attractor state changes abruptly, and the system is sensitive to the input. Through the "butterfly effect" of the system, feature signals that are difficult to extract by traditional methods can be detected. And the system has strong anti-interference performance.

Evasive maneuvers of fighter only consider the objective of miss distance in traditional air combat decision problems. The amalgamative tactical demands of achieving self-conflicting evasive objectives in actual air combat are taken into account in this paper. A method to generate a strategy of evasive maneuvers based on tactical preference is proposed. Tactical preference is given to higher miss distance, less energy consumption, and higher terminal superiority. The evasion problem in air combat is defined and reformulated into a multi-objective optimization problem, which is solved by a multi-objective evolutionary algorithm. Simulation results show the feasibility and effectiveness of the proposed method, and a set of approximate Pareto-optimal solutions are obtained to satisfy the tactical preference.

With the continuous improvement of socio-economic level, the current level of science and technology is also constantly developing. At the same time, China's power industry is also developing at a relatively fast pace. The rapid development of the power industry has made vital contributions to the development of our national economy and the improvement of people's living standards. In the development of the power industry, the automation technology of distribution network feeders is an important part of the development of power system automation. Therefore, the research and analysis of distribution network feeder automation technology must be carried out to improve the application level of distribution network feeder automation technology, so as to promote the modern development of China's power industry.

A kind of method about fault diagnosis of optical measurement equipment based on fault tree analysis(FTA) is proposed. Firstly the system is decomposed into several subsystems by control loop, and then generated the fault tree for each control loop. The whole fault tree of the system is obtained by the event status with fault tree of all control loops deduced. Moreover, a set of system platform was developed with the Visual Basic software. Finally, a photoelectric encoder fault case of optical measurement equipment is analysed with the platform and method. It shows that the proposed method in this paper improves the automation of fault tree construction and has certain utility and better future for application.

The investigation and analysis of personalized training of vocational education based on big data system has the characteristics of simplicity, operation and persuasiveness. This article comprehensively elaborates on the characteristics and meaning of personalized education, combines the big data analysis method and selects five colleges and universities in Guangzhou to conduct a questionnaire survey, to find out the problems in the personalized training of vocational education, and to propose measures.

Based on the diagnostic architecture of AUTOSAR, this paper presents the architecture of AUTOSAR diagnostic system and implementation of application fault diagnostic function. The interaction between the application software components and the BSW modules is emphasized. The hardware-in-the-loop test platform verifies that the development of application diagnostic system fulfills the requirements of design.

Sleep monitoring is widely used in health monitoring. Sleep respiratory rate is an important indicator of sleep quality. This paper designs a respiratory frequency monitoring system based on millimeter-wave radar, WiFi communication module and an Android-based mobile terminal APP. The respiratory data collected by the millimeter-wave radar is transmitted to the mobile phone through WiFi module. The phone can directly display the respiratory frequency data and the respiratory frequency in a curve manner. After testing, the system runs stably and reliably, has real-time performance and strong portability, and provides a new application method for millimeter-wave radar.

ETCS on-board equipment is a typical safety-critical system, its reliability plays a vital role in the safe driving of trains. ETCS on-board equipment has huge functions, complicated structure, a large number of test cases and difficult implementation. Introducing automated testing into on-board equipment testing is a problem that needs to be solved urgently. Based on the interface and functional characteristics of ETCS on-board equipment, this paper adds the design of test management unit, the division of test engine and the separation of test scripts based on the existing test environment, and develops a set of simple and efficient ETCS on-board equipment dedicated automation test environment. The application shows that this set of test environment realizes the automatic test of all test sequences of ETCS on-board equipment, which can significantly improve the test efficiency, reduce the tester's work intensity, and improve the test accuracy.

The advantages and disadvantages of existing walking aids on the market are analyzed and improved. The overall structure is designed and analyzed, and the length of each segment is considered comprehensively from the perspective of adapting to human body. The 3D model was established in SOLIDWORKS, and the motion simulation analysis was conducted in ADAMS to obtain the speed, step distance and other parameters during the movement. The results were compared and analyzed with the applicable human motion parameters to verify its feasibility.

China has the largest number of elderly people in the world, and many of them have the problem of mobility. At present, there are some problems in the market, such as single function, difficult operation and lack of safety protection. The walking aid robot can not only meet the demands of the old people, satisfy the basic requirement of walking or the transfer between sitting and standing, but can also help the old grab objects from the further place. It has the advantages of simple operation, abundant functions, low cost in maintenance, high degree in safety index and so on, which can completely meet the needs of modern society.

Respiratory state analysis based on respiratory strain monitoring plays an increasingly important role in the assessment of the continuous dynamic physiological state of the human body. The proposed respiratory strain monitoring system uses the STM32F411 single-chip microcomputer as the main control chip, combined with the FDC2214 capacitor-to-digital converter, collects the capacitance value of the flexible cloth-based capacitive strain sensor through the IIC method, and sends the collected result to the upper computer for processing and analysis through Bluetooth. The device collects the respiratory strain signal of the chest in three motion states: stationary, walking, and running. Through data acquisition and algorithm processing, it can clearly display the waveform of respiratory strain, and the extraction accuracy of the respiratory rate is ±1rpm. The experimental results show that the system has good stability and accuracy, strong anti-interference ability, and can meet the requirements of continuous dynamic high-precision respiratory rate monitoring.

Based on the basic theory of thermodynamics and finite element, the thermal characteristics and structural mechanics simulation are carried out taking an automobile IGBT packaging module as the research object. Then the distribution of temperature, thermal stress and deformation of IGBT are obtained. The thermal force coupling performance of the structure is judged according to the analysis results, so as to provide theoretical reference for the design and selection of subsequent radiators.

In feed industry, a lot of dust will be produced in the process of raw material comminution, which will cause environmental pollution and be harmful to the health of workers and so on. In this paper, a kind of bag filter for micro pulverizer in feed industry is designed. The bag filter was firstly carried out, including the design of the overall scheme, the calculation of filtering wind speed, the filter bag parameters, the blowing component system, and the specific structure design of the dust collector according to the dust processing capacity and dust characteristics. The test proves that this bag filter has an average dust removal efficiency of more than 96%, which can effectively deal with the dust generated by the micro pulverizer, and provide an application reference for solving this type of dust pollution treatment.

In the current era, human-computer interaction design has penetrated into environmental design and it has played a huge role. At The application of planning in environmental design has become the focus of people's research. Public facilities are an important carrier of In addition to being practical, it also undertakes the task of beautifying the city. When new social phenomena and residents' needs change, under the restrictions, functional compounding of public facilities is the inevitable way. This article analyzes the status of public facilities an The reasons for the introduction of functional composites in the design of public facilities are discussed, and the integration of emotional c The article comprehensively analyzes and summarizes the research on the human-computer interaction design of public facilities in the env The integration of technology and technology is to provide users with a convenient and practical service experience on the basis of aestheti The product of a higher level of human needs, its application in design meets the emotional communication of people, people and product The design must be planned according to the characteristics of the overall environment, combining the colors and forms of the surrounding One consideration, so that it cannot only meet the emotional concept and interaction design of environmental design, but also give full pla Function and utility.

This paper presents a planar two-degree-of-freedom cable-driven robot for detecting the surface defect of the boiler pipes. The mechanism is first described and inverse solution laws of position, velocity and acceleration are studied based on the dynamic model of the cable-driven robot. A linear trajectory planning approach is developed, which is based on the position discrete differential and trapezoidal speed planning. An example trajectory is presented, then simulating and analyzing the change law of the length and velocity of the driving cable based on the point-to-point linear trajectory planning algorithm. The research shows that the length of the cable is continuously changed, which ensures that the end-effector of cable-driven robot can run smoothly, continuously, and accurately during the industrial detection.

In this paper, a simple and practical two axis UAV self-stabilizing PTZ is designed and implemented. By connecting UAV and camera, UAV can stably track and shoot specific targets.

The screw-type centrifugal pumps with different impellers are studied. The structure of single-rotary and multi-rotary impellers are designed by the CAD method. The governing equation of fluid flow and SST k-ω model are applied to simulate the internal flow field by computational fluid dynamics method. The pressure distribution and vorticity distribution are calculated and analyzed. It is found that the pressure distribution and vorticity distribution of the two types of impellers are significantly different. The pressure distribution of single-rotary impeller is relatively uniform. The vorticity of single-rotary impeller is larger than multi-rotary impeller.

Numerical simulations of wake flow field of ducted propellers with and without pre-swirl stator are carried out by means of k-ω model. Then the velocities and the pressure fluctuations of the wake flow at different positions from the propeller are analyzed. The result shows that both the near-propeller blade velocity and the overall averaged velocity are obviously increased by the pre-swirl stator. Moreover, the pre-swirl stator can improve the surface pressure distribution near the blade but at the same time can enhance the pressure pulsation in the wake flow, especially at the downstream region.

The replacement of tower is an important part of the technical reform of power grid lines. To analyze the rationality of the cost of the technical reform of tower, it is necessary to deal with the abnormal engineering data based on the cost data of previous projects. In this paper, the unit cost of tower replacement is sorted out by using 3δ principle and boxplot method, and the reasonable cost range is obtained to provide a basis for project investment.

The ejection theory is widely used in industrial fields such as drainage, cooling, vacuum. Many ejection devices are applied in civil aircraft due to their simple design and easy layout. This article introduces several types of ejection applications in multiple systems of civil aircrafts. Then a CFD simulation of the APU (Auxiliary Power Unit) compartment drainage ejector is conducted to analyse the influence on the drainage function by different arrangements.

The cause of cabin odors is usually hard to be identified when there is no specific crew alerts or indications, which could have a catastrophic effect on civil aircrafts. Fault analysis has been conducted based on FTA (Fault Tree Analysis) in this paper to locate fault sources of cabin odors. A checklist is recommended to be performed during the flight or ground tests afterwards, which could provide quantitative references. An actual case applying the troubleshooting and analysis method above is shared at the end.

This experiment investigates the effect of time on the quality of the film during the micro-arc oxidation of magnesium alloys. The micro-arc oxidation surface morphology, the thickness of the film layer, and the influence on the corrosion resistance of the magnesium alloy were studied at different times. The experiment found that when the micro-arc oxidation time is controlled at 9 minutes, the surface quality of the film layer is the best, and the improvement of the corrosion resistance is more obvious.

Different from the traditional smart home control method, this article uses the PAJ7620U2 chip gesture recognition to add to the smart home system.PAJ7620U2 gesture recognition can recognize 9 different gestures. Based on this performance, a simulated smart home system based on gesture recognition is designed. It contains home intelligent electronic photo frames, audio and video entertainment modules, intelligent security monitoring, ZigBee wireless communication environment detection, and light control. The experimental results show that the system is simple to operate and powerful, and is integrated into the traditional smart home control method without gaps.

Using the prediction method of surface element method and particle swarm optimization algorithm to study the multi-parameter optimization design of ducted propeller. Hicks-Henne function and Bezier function are used to fit the parameter curve of the ducted propeller. Taking the open water efficiency of the ducted propeller as the optimization target, the numerical simulation was performed. By analyzing the result, the multi-parameter coupling optimization design of the ducted propeller can be achieved. After optimization, the open water efficiency and thrust coefficient at the design points have been improved. Among the two fitting methods, the Bezier function gives a better result, which is consistent with the actual engineering. Within the range of the common speed coefficient of each ducted propeller, the efficiency and thrust are improved and meet the requirements. The feasibility and effectiveness of the multi-parameter coupling design of the ducted propeller are verified.

With the progress of science and technology, the influence of artificial intelligence has gone deep into the judicial field. At present, the use of artificial intelligence in the court mainly includes information data-based, multi-body litigation service system, online dispute resolution platform, prediction and supervision of the results of entity judgment and other forms. At present, the application of artificial intelligence in the judicial field mainly includes the lack of authenticity and integrity of data, the limitation of its own characteristics by artificial intelligence, and the weak acceptance of judges. China's courts at all levels are promoting the construction of "intelligent courts", which is an important part of the national network power strategy, as well as the embodiment of E-government in the judicial field. Through artificial intelligence technology, the judicial procedures such as service, signature, evidence, trial, debate, record and judgment in the process of litigation are managed and controlled in a unified way. However, there are many problems to be overcome in the application of artificial intelligence technology in the judicial field. Therefore, it is the foundation of long-term and steady development to find out the problems in time and propose solutions.

With the continuous development of modern information and communication engineering, the management of the whole process of the standardization construction of fire information and communication operation management pays more attention to the intensification, standardization and standardization of project management. This is because fire fighting communication is an important part of fire fighting work and is the nervous system of fire fighting dispatch and organization and command. Therefore, the whole-process management can be sorted out, standardize the management process, establish a centralized management platform, and cover various aspects such as reserve project initiation, plan issuance, construction implementation, acceptance and payment, etc. However, in the standardization construction of individual fire information communication operation and management, the standardization construction of communication management system has not received high attention from relevant staff. This paper analyzes the current situation of standardization and disorder of fire fighting information communication operation management based on remote communication, and puts forward suggestions and solutions, which are conducive to the sustainable development of fire fighting industry in the future.

In view of the lack of efficiency evaluation index system of intelligent weapon system and insufficient quantification and refinement of technical indexes, the research on the index system will be carried out from the perspective of completing the task of intelligent weapon system, and the verification index system will be established to realize the evaluation of weapon system efficiency, clarify the use background of intelligent weapon system, and analyze the strength composition of intelligent weapon system, Finally, Delphi method is used to build the effectiveness evaluation index system of the intelligent weapon system, which can be used as a reference for the comprehensive evaluation of the capability of the weapon system.

CLC number: TJ02 Document identification code: A

Crosslinked polyethylene(XLPE) cable is one of the most important tools to transmit electric energy and electrical signals, but its insulation material is vulnerable to damage due to the complex working environment. If the aging cable is not replaced in time, it will easily cause fire and threaten the safety of life and property. Life prediction of cables is essential to ensure reliable operation. Hence, the objective of this study is to provide a theoretical basis for cable replacement. This paper, firstly, focuses on the thermal aging mechanism of cable. Based on Arrhenius Model, multivariate nonlinear regression method was used to process the data and the thermal aging life prediction model of cable had been derived. From the real operation perspective, the reliability of the model was analyzed. 50% of retention of elongation at break was measured as an indicator of the failure point, the life evaluations of cable was carried out. The result indicates that the service life of cable at 90 °C is 32.2 a.

Aiming at the uncertainty problem of crosstalk attack detection and attack source localization in multi-domain optical networks, a new crosstalk attack detection and location method in multi-domain optical networks is proposed by using distributed PCE architecture and monitoring point placement strategy based on grey theory. Meanwhile, an example is given. The experimental results show that the proposed method is effective.

The prevention of runway incursion in hot spot of airports has always been one of the research hot spots in the field of international civil aviation. The detection of aircraft and vehicles in hot spots of airports has important significance in preventing runway incursion. This paper briefly introduces and analyzes several major technical systems used in the detection of active targets in hot spots of airports, and points out that microwave phased-array radar can provide parameters such as the distance, angle, speed, and direction of detection of targets. Compared with the traditional detection technology system, microwave phased-array radar has the advantages of high detection accuracy, low comprehensive cost, and easier acceptance.

In this paper, a real-time detection method of FFSN is designed. The response delay time of domain name is extracted by passive method. According to the self-similarity of response delay time of legitimate domain name and the difference of response delay time between legitimate domain name and FFSN, VTP analysis method based on Hurst exponent is used to detect FFSN. In order to avoid false alarm caused by the network itself, the suspected network also needs to be used the active method to judge the fast flux attribute in order to confirm the existence of FFSN. Our method can not only detect the existence of FFSN in real time, but also give the specific FFSN domain name. The experimental results show the effectiveness of our method.

In order to improve the accuracy of internal and external fault identification of T-connected transmission lines, a new method for identifying internal and external faults of T-connected transmission lines based on general regression neural network and traveling wave power angle was studied. The initial voltage and current traveling wave measured by each traveling wave protection unit of T-connected transmission line are transformed by S-transform, and the single frequency power angle after fault is calculated to form the sample set of fault eigenvector of T-connected transmission line. The established general regression neural network intelligent fault recognition model is used to train and test the sample data to identify internal and external faults. The simulation results show that the algorithm can accurately identify the internal and external faults of the T-connected transmission line under various operating conditions.

Aiming at the problems of low efficiency, difficult debugging and poor reusability of program in developing vision program by using text editing, a graphical program development technology is developed for vision program development. In this paper, the image processing algorithms and functions in the OpenCV vision library are studied and encapsulated according to the IEC61131-3 Function block specification. The interface model and program model of vision Function block are established. According to these two models, the vision Function block interface and the vision Function block program are described by using XML language, and the programming specification and instruction set of the vision Function block are established. The editing and compiling algorithm of the Function block program is researched to realize the configuration development environment and operate environment of the vision Function block program by using C plus plus language. Finally, the function of the software is tested and verified.

How to reduce the energy consumption and prolong the network lifetime is one of the most important issues in Wireless Sensor Networks (WSNs). This paper proposed a Compressed Data Gathering (CDG) scheme based on Hierarchically Diffused Connected Dominating Sets (HDCDS). In the proposed scheme, a connected dominating set was constructed as the backbone of the network. All of the other nodes, i.e., non-backbone nodes, are connected to the backbone. Nodes in the backbone collect data from non-backbone nodes using the traditional data collection scheme. Data within the backbone are transmitted to the base station in CDG manner. Theoretical analysis and simulations showed that, when compared to the LEACH methods and traditional compressive sensing-based data collection methods, HDCDS-CDG not only reduces the consumption of network resources but also increases the lifetime of the network.

With the continuous expansion of artificial intelligence in power system, the reliability, security and operation ability of power system have been greatly improved. With the massive collection of data for transmission and transformation operation and maintenance, in-depth learning, as a typical representative of data-driven in the system of artificial intelligence methods, is increasingly appearing in the application scenarios of intelligent state assessment of transmission and transformation equipment. Its excellent robustness can eliminate many kinds of interference in complex environment background, accurately identify and evaluate the target points under test, and greatly reduce the detection of transportation and inspection personnel. The workload of data analysis, processing, evaluation and other links can improve work efficiency and accuracy. This paper attempts to summarize the development process of in-depth learning, relevant landmark achievements and typical applications in the operation and inspection of power transmission and transformation equipment. This paper attempts to summarize the research progress of target recognition, target segmentation, image classification algorithms in depth learning in different spectral cameras of visible light, ultraviolet corona imaging and infrared thermal imaging.

Based on directional antenna, the capability of the intra-flight data link such as anti-jamming and low interception can be greatly improved. However, it also brings some problems: obtaining the destination node location information, meeting the real-time requirement of the burst traffic and sharing situation information with directional antenna, etc. To solve the problems, DP-CLMA (Dynamic Priority-Chain Link Multiple Access) protocol based on directional antenna is proposed, and some corresponding mechanisms are described in detail. By analyzing time delay performance of DP-CLMA protocol, the results show that DP-CLMA protocol adapts to intra-flight tactical data transmission.

Ratio expansion is a recently proposed, remarkable method for reversible data hiding in 3D meshes. The capacity and distortion are the two most common performance measures for data hiding. This paper analyses the ratio expansion method, and a novel mathematical framework is introduced and described, which proves that the magnitude of the distortion depends on three parameters. By appropriately selecting two of these parameters and a factor called "reference value", the proposed method achieves reduction of the distortion. Another novel coding and decoding phrase is also proposed to get higher capacity. The experimental results show that this method improves the embedding capacity significantly without affecting the visual quality of 3D mesh model.

With the development of technology, precision guided weapon is becoming more and more important in modern war. In order to launch our recent guidance system on medium and small guided weapons, we propose a method to obtain the LOS rate by combining information from both camera and gyroscope. To be specific, we firstly calculate the body LOS angle through transforming the image pixel coordinate system into the image physical coordinate system according to camera internal parameters; then subtract the missile motion information contained in the measurement signal of the seeker and finally the LOS rate is deduced. Comparing with traditional gimballed seekers, our strap-down seekers with camera have significantly reduced costs and influences caused by external environments on platform.

Cryptography is a fundamental mechanism for security, various cryptographic algorithms are widely used in IoT firmwares, and identifying cryptographic algorithms is paramount for IoT security. RSA algorithm is the most popular asymmetric key cryptographic algorithm in use. Insecure RSA padding mode may result in padding oracle attack, causing certificate leakage, random number prediction, and plaintext recovery. In this paper, we show how to extract binaries from IoT firmwares, then describe 7 padding modes in RSA algorithm, and identify RSA padding in two methods -- function-name matching and IR expression constant analysis. We use Angr VEX model to translate specific code block into intermediate representation, and analyze their constant value to track RSA parameter int padding. We collect and filter 159 firmwares from 6 different vendors, analyze 7 kinds of RSA paddings using function-name matching, and 4 kinds of RSA paddings in RSA functions which contain parameter int padding using IR expression constant analysis. Then we identify 335 RSA paddings, and find out that flawed padding is still broadly in use in IoT environment.

Computer networking of academic journals refers to the traditional paper academic journals, which publish electronic texts at the same time as paper academic journals, so that relevant researchers such as experts and scholars can quickly and conveniently share journal results and information through network means process. In the internet new media environment, the computer network development of academic journals faces many problems and challenges. It is necessary to actively adapt to the development trend of internet new media, and better promote the computer networked development of academic journals through the construction of websites, academic platforms, and the use of WeChat platforms.

With the development of big data intelligence, deep learning, brain-like intelligence, autonomous control and other new generation of artificial intelligence technologies, the integration of artificial intelligence and education has become an inevitable development trend. Intelligent education system, such as virtual reality, educational robot, intelligent tutoring system, online learning system, learning analysis and so on, needs the seamless integration of human and machine cognitive intelligence. Understanding-based teaching is the fundamental way to realize the high integration of human and machine cognitive intelligence. In this paper, the experimental research of understanding-based teaching is carried out, and the results show that understanding-based teaching in the network environment can promote the development of students' creativity more than traditional teaching.

In view of the quick development of modern computer technology, more pictures of natural scenes have been collected and analyzed for application in military fields, scientific research, and computer vision fields related to object detection. However, the sharpness of these pictures collected will be affected by rain and snow, which will reduce the visibility of things in the pictures. This will not only affect the viewing, but also affect scientific research fields such as autonomous driving and video surveillance. Therefore, the research on image rain removing is very practical. An improved algorithm model named pixel-GAN is proposed in this article, which based on conditional Generative Adversarial Networks (cGAN). This new method regards the problem of removing rain from specific images as the style conversion problem. What we improved is that a VGG-16 module is added to the original network to extract perceptual loss as a new part of the loss function. We show the excellent rain-removing ability of the improved algorithm and also illustrate the reason why we add the perceptual loss. Compared with other existing methods, there is no need to set a prior model, the training speed is faster and the proposed model finally generates higher quality pictures.

Image processing is to transform the image into digital matrix by mathematical formula, then store the data in the computer, and enhance the source bitmap by computer, including gray-scale processing, median filtering and binarization. Then the image is cut, including contour edge processing, seed filling and so on. In this paper, the image is recognized and processed based on pattern recognition, and then a pre classifier is designed to build a system model of fruit intelligent classification. After the fruit is taken by industrial camera, the corresponding image processing and feature value extraction are carried out. Then the extracted eigenvalues are used for classification. Through this method to achieve a variety of fruit classification effect.

Affected by the COVID-19 epidemic, smart city and logistics in China have been developed significantly. This study is based on the accelerated development of smart cities and smart logistics after the outbreak of COVID-19 in China, and combined with literature, it puts forward the update of smart cities and the trend of gradually centralized, intelligent and intensive development of China's logistics industry.

In the current era, with the continuous development of China's science and technology, the development of electronic information technology has also been significantly improved. Electronic information technology plays an irreplaceable role in people's daily production and work, which helps to entirely improve work efficiency. In addition, the Internet of Things technology has developed rapidly in Internet era. In the process of the Internet of Things technology, electronic technology has a good role in promoting it. Therefore, the use of electronic information technology is very important and helps promote the comprehensive development of the Internet of Things in the current era.

Determination of filter order and transmission zeroes is the precondition of synthesizing cross-coupled filters. Firstly, we propose a method to determine them according to given filter specifications using Genetic Algorithm. The effective objective function is proposed for Genetic Algorithm. We can obtain the least filter order and the optimum locations of transmission zeros to fulfil filter specifications by this method.

During the deformation process of power transmission iron tower base along with the ground surface settlement, the conductor and ground wire can support the iron tower structure to some extent. Through defining the influential coefficient of coupling effect of tower line, we have obtained the influential coefficients of coupling effect of tower line under two working conditions, i.e. base settlement and horizontal slipping, and evaluated the influence of the tower line coupling effect on bearing performance of iron tower during the base deformation process. The research shows that the shaft force of main material of tower leg during the base deformation process is slightly increased, and the increasing amplitude is within 10%, and the influence of the tower line coupling effect on the bearing performance of iron tower during the base deformation process can be neglected basically.

This paper utilizes the CFD simulation analysis method, calculates and analyzes the distribution characteristics of streaming around the typical steel tubular transmission tower body and the pressure field, researches the change law of wind load force (torque) coefficient along with each main shaft direction o tower body, and then compares it with corresponding wind tunnel test result, and verifies the adaptability of this CFD simulation result. The result shows that the pole member in the upwind direction on the steel tubular tower has obvious disturbance and shielding effect to wind speed distribution around the pole member of downwind direction. The wind direction has obvious influence on the aerodynamic (torque) parameters of tower body, especially the steel tubular - angle steel combined tower body. The above research result provides a certain theoretical support and value taking basis for the wind-resistant design of steel tubular transmission tower body.

Encouraging college students to become entrepreneurs has become the policy orientation of many countries including China and entrepreneurship policy is an important macro environment for college students to innovate and engage in entrepreneurial activities.This paper focuses on the entrepreneurial policy of college students in Changzhou. Based on text data mining and big data, it analyzes the quantity, form, subject, theme and use of policy tools in Changzhou and discusses the macroscopic development trend and logical path of Changzhou college students' entrepreneurial policies. Provide theoretical guidance for the analysis of policies in the future through the construction of, the check of, and the classification of text big database.

Relational reasoning is ability to reason about entities and their interactions, which is not applicable for many deep neural networks. Recurrent relational networks, introduced by Palm et al. (2017), increase the complexity of the reasoning tasks they can address [1]. In this paper, we introduce Stacked Attention Recurrent Relational Networks (SARRN) to answer natural language questions from facts, which fundamentally hinge on multiple steps of relational reasoning and improve the ability of reasoning. Our model is a stacked attention model that use recurrent attention to focus on fine-grained parts of the documents. We apply our model to the BaBi tasks, which have a set of proxy tasks that evaluate reading comprehension via question answering. Our model solve 19/20 tasks and the experimental results on the test sets tasks show that our model yields great improvement. We also use qualitative analysis to show the result intuitively.

When the sweep of the variable sweep folding wing missile changes, the lift-drag ratio is improved so that the missile is able to adapt to subsonic flight, transonic flight and supersonic flight. This paper designs different 3D models of variable sweep wing missile aerodynamic shape and completes the aerodynamic characteristics analysis of the missile by CFD according to the Basic Aerodynamics, Missile General Design Principle, Flight Dynamics of Missile. The simulation analysis of the missile in different flight conditions with different sweeps is carried out, and the wing sweeps applicable to different flight conditions are summarized.

At present, HAZOP analysis and LOPA analysis are widely used to analyze and control the risk of process flow, but few people manage HAZOP and LOPA for risk during operation. Through the research of HAZOP and LOPA analysis methods, combined with long-term work experience in the field, the author proposes to combine HAZOP and LOPA analysis methods into operational process safety risk analysis, and use the same subject expert team to identify the risks in the operation process. Control and control results also help to re-revise the operating procedures, conduct risk management and control from the operational level, and improve the completeness of safety evaluation. This paper introduces the basic method of HAZOP_LOPA joint analysis operation process, clarifies the analysis points, and lists the commonly used 8 types of guidance words. Finally, the risk of maintenance and maintenance operation of quick-open blind filter is analyzed by examples. The results show that Based on HAZOP_LOPA, operational risk analysis can quantitatively evaluate the reliability of existing protection measures, eliminate or reduce safety risks, and achieve safety risk review of operational procedures. This method improves the reliability of operating procedures and enhances the safe operation level of employees. It is of great significance.

Transient stiffness formula of dynamic load of asymmetric gear is deduced. Considering the effect of transient stiffness and transfer error, the formula of dynamic load of asymmetric gear is deducted and programmed using MATLAB, the variation regulation of dynamic load was obtained. That is the foundation of doing transient EHL analysis of asymmetric gear. The asymmetric gear model program has been made using VBA, and modal analysis of asymmetric gear has been done using ANSYS, which is the foundation of dynamic response of structural calculation and analysis.

The SST k-ω model is used to simulate the open water performance of the ducted propeller, and the hydrodynamic performance is compared with the experimental results. The SST k-ω model is validated to effectively predict the hydrodynamic performance of ducted propellers. Based on the analysis of the optimization of the ducted propeller, guide blades are installed in front of the blades to improve the performance of the ducted propellers. The performance of the ducted propellers on the ducted propellers is analyzed, and the influence laws are studied to provide a theoretical basis for the subsequent improvement of the ducted propellers.

When a single-channel pump is used to transport living things, the rotating action of the impeller will cause damages to the living things. To improve the survival rate of the single-channel pump for transporting living things and improve the performance, the effect of the impeller wrap angle on the performance of the single-channel pump was studied by numerical simulation. The external characteristic curve is analyzed and the change of the pressure field of the flow field in the flow channel with the wrap angle is grasped. The pressure pulsation at the monitoring points is analyzed, and the influence law of the wrap angle on the performance of the single-channel pump is obtained. This law lays the foundation for subsequent single-channel pump design

Taking the wind speed and ice thickness field measurement data in Southwest China during November 2016 to March 2018 as analytical sample, the probability distribution of the wind speed and ice intensity were analyzed and fitted by using Gumbel distribution model, Weibull distribution model and Generalized extreme value distribution (GEV) model, respectively. The goodness of fitting results had been compared. After the determination of marginal distribution functions for wind speed and ice intensity, 500-year pseudo wind speed and ice intensity samples were generated based on the Monto Carlo method. Five Copula functions were employed in the construction of joint probability distribution function and the most suitable Copula function was chosen for building the wind-ice joint probability distribution model. On the basis of the model, the return periods for 30 years, 50 years and 100 years had been calculated, respectively. The analysis results show that the GEV model well matches the characteristics of wind speed and ice intensity. As for binary Copula function, the Frank Copula function has the best goodness for the joint probability distribution of wind speed and ice intensity. The return period calculations show that the design value of wind-ice joint return period (JRP) is larger than that of co-occurrence return period (CRP) and the value of Kendall return period (KRP) is between that of JRP and CRP. Considering that the dangerous areas of return periods are different, the return period for design should be determined by the combination analysis of different kinds of the return periods. Meanwhile, the importance and the failure results of the project should be taken into account.

Combining with the understanding of the "Procedures for Testing and Evaluating the Carrying Capacity of Highway Bridges" (JTG/T J21-2011) and practical engineering applications, it is found that there are some deficiencies in the process of carrying out the carrying capacity testing and evaluation of bridges by using the "Procedures for Testing and Evaluating the Bearing Capacity of Highway Bridges" Some points, such as the difference in the calculation results of the bearing capacity check coefficient Z1, the ambiguity of some concepts in the specification, and the actual operability still need to be improved, etc., and put forward some suggestions for these problems.

Aiming At Removing the Motion Blur to Restore Images, a deblurring Method of Infrared Image Based on Wavelet Transform is Proposed. Determining Whether There is Motion Blur by Using Wavelet Transform to Extract and Analyze the High Frequency Information of Level Subband; Blur Direction and Blur Length Are Calculated by Rotating the Image; the Image Deblurring and Recovery Are Completed by the Optimization Program of Wiener Filtering Algorithm. the Experiments Show That the Proposed Method Can Effectively Removes Motion Blur, and Provide Clear Infrared Images for the Next Image Processing, It Has the Characteristics of Strong Robustness, Good Real-Time Capability and Higher Application Value.

The importance of data source integrity to ADS-B monitoring performance is analyzed in this paper, and the corresponding monitoring algorithm is given. At present, ADS-B monitoring data mainly comes from GNSS, and GPS, as the main component of GNSS at this stage, its public data is relatively easy to obtain. Therefore, GPS is selected as ADS-B data source, the integrity of the navigation data source is analyzed and the data of an airport is verified by simulation in this paper.

In the field of image classification, graph neural network (GNN) is a kind of structured data modeling architecture with larger functions. However, there are still some problems, such as low efficiency of updating nodes, fixed network parameters and the inability to effectively model the information features of some edges in the graph. In order to solve these problems, this paper introduces attention mechanism on the basis of GNN to improve it, proposes a graph attention network (GAT), establishes a double-layer GAT model, and uses regularization method in model iterative training to achieve image classification. The model is applied to three datasets for experiments. The experimental results show that the average classification accuracy of the proposed model is high and it has good application performance.

This paper is trying to analyze the dynamic process of air defense operations by using queuing theory synthetically, targeting at the firepower optimization and effectiveness evaluation in air defense operations of surface vessel formation. It also establishes the service model of intercepting air targets by single type and multi type ship to air missiles, and finally comes up with the optimization model of air defense firepower. Vaule for formation configuration, optimization of air defense firepower and effectiveness evaluation.

The parameter selection of the traditional BP neural network (BPNN) has randomness, which makes the network prone to local extreme values during the calculation process. In order to solve this problem, this paper introduces the bat algorithm(BA) to optimize the parameter selection process of the BPNN and apply the algorithm to evaluate the enterprises' operating condition, a corresponding evaluation model of the enterprises' operating condition is established, and the evaluation model is applied to the prediction of the enterprises' future operating condition and compared with the prediction effect of the traditional BPNN model. The prediction accuracy of the BPNN optimization algorithm is higher than the prediction accuracy of the traditional BPNN. The established enterprise operation evaluation model can effectively predict the future operation of the enterprise.

A suspension is an indispensable part of a vehicle. It is of great significance for passengers' comfort and vehicle stability. This paper proposes a semi-active vehicle suspension model with negative stiffness, and analyzes the effect of negative stiffness characteristics upon vehicle response. When analyzing the performance of semi-active vehicle suspension, a quarter vehicle suspension model is established, and the space state model is built for numerical simulation. After contrasting and analyzing the response of semi-active passive suspension with negative stiffness and semi-active suspension controlled by Skyhook damping algorithm, we conclude that semi-active suspension with negative stiffness decreases the vibration speed of the vehicle body and the deflection of the tire in the low-frequency stage, and improves the smoothness and stability of the suspension. Hence, the negative stiffness characteristic is beneficial to improve the comfort and stability of the vehicle.

RS422A differential signal is a kind of bipolar pulse signal formed by level conversion of TTL signal through RS422A differential transmission device.Using shielded twisted pair transmission, the signal level is determined by the voltage difference between the two twisted pairs at the same time. It has the characteristics of long transmission distance and strong anti-interference ability.The time system signal is a standard RS422 differential signal, which plays an important role in the fire control system. The complex programmable logic device CPLD, the high-precision temperature-compensated crystal oscillator, and the standard RS422A differential transceiver device are used as the control device in this article. The control methods for generating, detecting, sending and receiving, adjusting the pulse width and synchronizing the timing signals are elaborated in detail.This method has the characteristics of simple circuit, high reliability, flexible control, high control accuracy, etc. It is widely used in fire control systems.

Frequent-pattern mining is a common approach to reveal the valuable hidden trends behind data. However, existing frequent-pattern mining algorithms are designed for DRAM, instead of persistent memories (PMs), which can lead to severe performance and energy overhead due to the utterly different characteristics between DRAM and PMs when they are running on PMs. In this paper, we propose an efficient and Wear-leveling-aware Frequent-Pattern Mining scheme, WFPM, to solve this problem. The proposed WFPM is evaluated by a series of experiments based on realistic datasets from diversified application scenarios, where WFPM achieves 32.0% performance improvement and prolongs the NVM lifetime of header table by 7.4× over the EvFP-Tree.

Compared with the previous inertial navigation calibration equipment using a single controller method, the IMU calibration equipment control system based on multiple control methods can be more customized and more flexible. The spindle controller uses a self-developed algorithm. It is realized in real-time control system, which has the advantages of high control positioning accuracy and high rate stability; the automatic turning device controller adopts mature industrial controllers and uses sequential function diagrams to realize the automation process, which is simple, stable and reliable, and can realize complex automation testing process. The two control methods use the way of TCP/IP communication to combine the advantages of the two controllers, shorten the development time, save costs, and achieve high performance, high efficiency and accurate testing.

Narrow band internet of things (NB-IoT), as an important low-power wide-area coverage of 5G with independent intellectual property rights, has great potential in small data monitoring of urban power transmission and distribution. However, it is extremely easy to cause congestion and overloading of the system upon large-scaled terminal requests for random access, which will decrease network access performance and bring great challenges to promote NB-IoT in urban power Internet of Things. On this basis, a mathematical model of network load was constructed to estimate and predict load changes. Then, a dynamic adjustment functional model was set up according to dynamic adjustment of access parameter optimization based on loads. Based on above idea, a random access algorithm based on dynamic parameter adjustment in accordance to dynamic priority was developed. It increases the success rate of devices access to NB-IoT system, decreases access delay of devices, and relieves network congestion. According to simulation results, the proposed algorithm has higher access success rate, lower total delay. And it guarantees delay for important node users and more optimized network performances compared with traditional network access algorithms.

The high-precision micro-infusion automatic control system is an automatic infusion system that replaces manual infusion which solves the risk that the traditional infusion volume and speed cannot be controlled. By analyzing the system composition and configuration, it is determined that the system actuator belongs to the field of multi-body mechanics. After analysis of the system mechanics model, it is ensured that the mechanical performance of the designed system's actuator meets the requirements. At the same time, the motor control method of subdivision drive and closed-loop control used in the design is described in detail, and the dynamic characteristics of the system are simulated and analyzed. High-precision and reliability control ensure that the medicine can enter the patient's body uniformly, accurately and safely, and meet the design requirements.

The tuning of the multi-rotor UAV PID parameters is a long and iterative process, and sometimes it is impossible to find a suitable magnitude. To improve the setting efficiency of control parameters, the classic PID control algorithm is combined with the dynamic model of the UAV to build a mathematical model that describes the effect about parameters of P controller on the tension of brushless motor. Computer simulation and open-loop experimental verification were conducted under the change of parameter of P controller. The simulation and experimental results show that this mathematical model describes the effect of parameters of P controller on the UAV motor's tension under different attitude angle errors. When the parameters of the P controller are input to the UAV which has determined the parameters of the power system, the motor's tension can be calculated directly from this model, and this model can assist in determining the magnitude of parameters of the P controller.

Based on the "MicroBlog Community Massive Information Mining and Monitoring System", this paper introduced the algorithm and model construction of microblog information word processing and mining conversion core functions of microblog information subsystem, in order to obtain the information objects needed in each link of the process of microblog information mining, which provides a basis for the realization of monitoring and early warning in the MicroBlog monitoring platform.

It is of great practical significance to study the dynamic scheduling of production in flexible job-shop. In the flexible job-shop scheduling, process, cost, machine tool and processing environment constitute the constraint set of scheduling. In this paper, starting from the multi constraints of scheduling system, the multi-objective linear synthesis of cost, time, quality and resource utilization is carried out. The scheduling intelligent algorithm is improved by using the polychromatic sets contour matrix to improve the operational efficiency. On the basis of the multi-objective flexible job-shop scheduling model under this multi constraints condition, from the actual situation of production scheduling, this paper constructs a scheduling control window according to the dynamic influence domain formed by the dynamic factors in the scheduling process. Dynamic scheduling control is carried out through control window to realize flexible scheduling and intelligent production. The effectiveness and feasibility of the model are verified by dynamic scheduling analysis of a simulation example.

From the view of automobile after-sale service industry, this paper analyzes the connotation and characteristics of customer knowledge of this field, discusses on the method for acquiring customer knowledge of automobile after-sale service, and presents the ontology-based customer knowledge representation mode, thus ensuring the re-usability and consensus of automobile after-sales service knowledge.

This paper combines the semantic segmentation of scenes with Simultaneous localization and Mapping (SLAM) technology to build a three-dimensional semantic map. The input sequence is selected by ORB-SLAM for key frame selection, and the scene's semantic segmentation is performed in the corresponding point cloud data. We use a new 3D segmentation framework, which can effectively simulate the local structure of point cloud. A drift reduction mechanism based on semantic constraints and Bundle Adjustment (BA) constraints was proposed. This mechanism considers the three-dimensional objects, feature points and camera pose for semantic recognition in the scene, and integrates them into the back-end BA to optimize them. The final experimental results show that compared with the current popular ORB-SLAM, this mechanism can reduce the system's translation drift error by 18.8%.

Virtual reality technology refers to the use of computer multi-body technology to simulate the environment from many aspects, such as human smell, vision, touch and hearing, so that people can have a sense of being in it in the virtual environment constructed by computer, and can obtain all kinds of information with the help of human-computer interaction.By combining virtual reality with somatosensory interaction using gesture recognition, speech recognition and other modes, this paper develops an immersive urban scene roaming system based on Unity3D multi-mode human-computer interaction, which gives users a near-real scene roaming and somatosensory interaction experience.

Due to the scarcity and uncertainty of anomalies, anomaly detection becomes a challenging problem in communities. This paper proposes an effective time series anomaly detection network based on prediction and adversarial training. First, we employ LSTM model based on differential attention mechanism to fully extract the inner characters of time series. To prevent the over-fitting due to only normal samples used to train our LSTM model, we introduce an adversarial training strategy by adding adversarial samples to enhance the generalization of the model on normal data. The effectiveness of our model is demonstrated on several public datasets.

We have proposed an analytic compact model describing the drain current characteristics valid in all operating regions, for ultra-short channel cylindrical gate-all-around metal-oxide-semiconductor field-effect transistors considering source-to-drain tunnelling effect. The drain-induced barrier lowering had been incorporated from one two-dimensional analysis in our previous compact model. In this study, to represent the energy level profile along the device channel direction into the Wentzel-Kramers-Brillouin approximation by substituting a parabolic function, we can analytically derive the expressions of the transmission coefficients for source-to-drain tunneling. In the subthreshold region, the source-to-drain tunneling current then can be evaluated using the Landauer formula. Finally, a fully analytic compact model is proposed for representing the drain current in all operating regions. The results compared with non-equilibrium Green's function transport simulations can be obtained in a good agreement.

A new type of spherical gear is proposed, which is formed by combining the tooth profile of the plane involute annular tooth surface and spherical involute spherical cone tooth surface. 3-DOF of pitch, deflection and rotation can be realized without principle error transmission. Based on the forming principle of plane involute and spherical involute, the equations of annular tooth surface and spherical cone tooth surface are derived by coordinate transformation theory; Combined with MATLAB and Pro/E, the 3D accurate model of 3-DOF spherical gear was obtained, and the contact stress of tooth surface was analyzed based on the finite element method. The simulation results show that the stress concentration always occurs at the tooth root and the tooth top of the spherical and conical tooth surface under the condition of constant spherical distance and the same torque but different coaxial intersection angle, which can provide reference for the tooth surface modification and optimization of spherical gear.

In order to solve the contradiction between the extrusion of solid and liquid food materials and the standardization of the volume of food materials in the bowl after compaction in the process of producing bowl food. Configuration touch screen and programmable logic controller are used as the control core of the system. Position parameters are obtained by photoelectric sensor. PLC drives the servo motor to make the linear module sliding block move, and drives the stepper motor to make the pressure plate rotate. Configuration of the touch screen to achieve the man-machine interface scheme. The force in the bowl is changed by adjusting the mechanical shape of the pressure plate. The controlled parameters of the execution program stored in PLC were obtained by orthogonal experiment. To realize the numerical control function of position, speed and force Angle in the process of food compression with digital precision. In addition, the mechanical structure of the spring cover plate is added to solve the problem of overflow of soup food materials from the bowl and its ring during the volume compression of solid and liquid food materials in the bowl.

This article has been retracted by IOP Publishing following a request by the authors that brought to the journal's attention that this article contains overlap with another work by different authors without citation [1].

IOP Publishing has investigated in line with COPE guidelines and agree that this work should be retracted.

The authors agree to this retraction.

 [1] Quishi Wang, 2019, Research of ITP Surveillance Theory Based on ADS-B IN, Master's dissertation. Civil Aviation Flight University of China

Retraction published: 23 November 2022