bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Machine Learning for E-justice
Authors: Metsker O , Trofimov E , Kopanitsa G 
Published: March 2021

Abstract
Decision support systems (DSS) in law enforcement have a long history. Starting from the late 50s, they have been developed through several architectural approaches. Still, having a proven capability of DSSes to improve legal practice, the real-world application is limited due to multiple issues, including lack of trust, interpretability, validity, scalability, etc. The paper develops a service-based decision support platform for machine learning applications for eGovernance and internal policy modelling and presents a case study of the application of the platform for the case of migration law enforcement. We have developed a decision support platform a number of micro services that connect with each other asynchronously via the REST protocol. The artificial intelligence core of the platform was built upon a knowledge base, which includes machine learning models and methods. In this work we have developed a method of structuring, analysis of legal data models based on machine learning. In the course of computational experiment, the efficiency of the developed method was proved and the interpretation of the obtained results was performed to provide recommendations for the enhancement of administrative regulation.
Efficient Roughness and Small Wear
Authors: Voinov Kirill 
Published: March 2021

Abstract
The reliability for the surfaces of friction directly depends on the shape and size of the roughness (and material of course) which there are on the surfaces of the mobile pair of friction (body and counter body). The movement even for the one part leads to detach small parts from the surface of friction. This process has the name wear/wear and tear or deterioration. Usually, this action is escorted with the physical phenomenon as the heating. In this case both the firmness and the wear resistance begin to fall/diminish essentially. In this article one important factor will be described in detail. It connects with the analysis how we can make all lugs in a roughness more stable during the real operation. Several ways will be demonstrated and described here. Moreover, applied calculations and figures confirm the theoretical positions as well. At last, some negative estimates during the processes of calculations and dimensions at the present time are given and the methods how to avoid them in practice using new achievements and recommendations.
Defect Identification Detection Research for Insulator of Transmission Lines Based on Deep Learning
Authors: Fan P , Shen H M , Zhao C , Wei Z , Yao J G , Zhou Z Q , Fu R , Hu Q 
Published: March 2021

Abstract
Traditional method of insulator defect identification is manually operated, which has low efficiency and high cost. Therefore, an automatic method of insulator defect identification is proposed in this paper. Firstly, image segmentation was operated by classification method of Random Forest (RF) to realize the object recognition of the insulator. Then, the method of Convolutional Neural Network (CNN) was adopted to classify the normal and defect states of insulators, and finally, the location of self-explosion defect identification was realized by Faster Region-Convolutional Neural Network (Faster R-CNN). A large number of images of insulators taken by Unmanned Aerial Vehicle (UAV) were used as experimental data to verify the method. The results show that the method in this paper could efficiently identify the defects of insulators, and the recognition rate reached 89.0%. The results can provide some references for the research of insulator defect identification of transmission lines.
Modeling of Performance Decay Prediction Based on LSTM-SVM Flexible Circuit Board Processing Roll
Authors: Huang Guanze , Li Weijie , Deng Yaohua 
Published: March 2021

Abstract
The roller is the core component of the flexible material roll-to-roll equipment, and its performance will affect the processing quality, so it is necessary to predict the health of the roller. In order to improve the prediction accuracy and effectively extract the time sequence information hidden in the signal, a LSTM-SVM-based processing roll performance degradation prediction model is proposed. By collecting the bearing vibration sensor data, extracting the characteristics of the vibration signal after normalization, using the extracted features as the input of the prediction model, inputting a part of the samples as the training set into the LSTM-SVM prediction model, and inputting the model in batches for network training, and Adjustment parameters. After the model is trained, use the test set for testing. Compared with support vector machines, the SLTM-SVM model is more effective in predicting the performance degradation of roll-to-roll equipment.
Brand-new Speech Animation Technology based on First Order Motion Model and MelGAN-VC
Authors: Chen Shaomin , Gao Xinyi , Wang Jiangtao , Xiao Yu , Zhang Yueling , Xu Gang 
Published: March 2021

Abstract
Speech animation has huge application potential in instant messaging and entertainment media fields such as videophones, virtual meetings, audio and video chats. The traditional voice-driven speech animation has the problem of a single adaptation language, and the performance-driven speech animation has the problem of high cost of capture equipment and difficult mass production. Based on the above existing problems, we propose a new method of speech animation generation, that is, given a static portrait of a person and a face-driven video, finally generate a face animation video of the character in the given portrait. The conversion system consists of two parts: face conversion and voice conversion. We noticed that the final generated face animation video has problems such as low definition, not smooth playback, and metallic sound. On this basis, this article proposes to increase the animation enhancement experiment and replace the encoder measures for improvement. Through comparative experiments, the above measures are proved to be effective.
Research and Application of Train Online Health Status Detection Based on Feedforward Neural Network
Authors: Zuo Jianyong , Feng Furen , He Yixin 
Published: March 2021

Abstract
A large amount of data is generated during train operation. By using PHM technology, we can analyse the health status of train systems and equipment which guide train operation and maintenance scientifically and effectively. Based on the feedforward neural network, the paper introduces some research of train on health status, such as remaining life prediction. To better verify the method, an online health analysis equipment suitable for train CAN bus is designed. The method and equipment are tested based on the data of a real train braking system, and the results show that the remaining predicted mileage of the brake system decreased by 1.1%, and the remaining predicted maintenance time decreased by 2.3% because of the impact of fault injection technology on brake cylinder performance. The result proved the effectiveness of the method and equipment for the online health status analysis of trains.
Scale Adaptive Block Target Tracking Based on Multi-layer Convolution Features and Kernel Correlation Filter
Authors: Zhang Ting , Hu Dong , Zhang Jing 
Published: March 2021

Abstract
Target tracking is currently a hot research topic in Computer Vision and has a wide range of use in many research fields. However, due to factors such as occlusion, fast motion, blur and scale variation, tracking method still needs to be deeply studied. In this paper, we propose a block target tracking method based on multi-convolutional layer features and Kernel correlation filter. Our method divides the tracking process into two parts: target position estimation and target scale estimation. First, we block the target frame based on the condition number. Second, we extract the features by the convolutional layer and apply it to the kernel correlation filter to get the center position of different block targets. With the reliability of different blocks measured by the Barker coefficient, the overall target position center is obtained. Then, the affine transformation is adopted to achieve the scale adaptation. The algorithm in this paper is evaluated by the public video sequences in OTB-2013. Numerous experimental results demonstrate that the proposed tracking method can achieve target scale adaptation and effectively improve the tracking accuracy.
Research on the Effects of DC Grounding Electrode of Yanmenguan Converter Station on the Earthing Network of Substation and Windfarm Based on CDEGS Software
Authors: Cheng Xiaosheng , Zhao Yanping , Shi Weiguang , Wang Kesheng , Liu Wei , Cai Xinjing 
Published: March 2021

Abstract
It is of importance to assess the electromagnetic influcence of HVDC converter station on buried metal facilities of AC substations, fossil-fuel plants, windfarms and pipelines. Electromagnetic interference model was established based on the experimental measurement of soil resistivity and actual physical location. It was shown that the grounding potential rise (GPR) of Yijing 220kV substation, Banjing wind farm, Nanhuashan wind farm, Jiyangshan wind farm, Liugou wind farm and Limin wind farm exceeded the standard. The effects of distance, soil resistivity and injected current on GPR were also investigated. The results can provide reference significance for design and maintance of HVDC transmission engineering.
Key Technology and Open Test Method of Rail Train Field bus
Authors: Song Jianwei , Cui Jinxue 
Published: March 2021

Abstract
With the continuous development of the rail transit field, the communication between trains and vehicles has received extensive attention. Therefore, various international organizations have studied and formulated various communication network standards. At present, the field buses used in rail transit at home and abroad (except Japan) are mainly TCN (Train Communication Network), WorldFIP bus and LonWorks bus. This article describes and compares these three types of field buses.
Analog Considerations for Designing a Potentiostat in a PSoC: Sources of Errors and Compensation Techniques
Authors: Lopin Prattana , Lopin Kyle V 
Published: March 2021

Abstract
Designing with a Programmable System on a Chip (PSoC) allows for entire circuit designs to be implemented with a single commercially available chip and eliminates the need to physically assemble electronic components. This is possible as the PSoC incorporates a microcontroller with digital and analog components into a single package. While this design allows for much easier implementation of circuits, there are some drawbacks. In this paper we will demonstrate one of those drawbacks, high routing resistance in parts of the analog mesh that connects the analog parts and external pins. We show how this resistance can cause measurement errors when the PSoC is implemented as a single chip potentiostat. As the internal analog routing resistance is in the kΩ range, measuring currents in the Kॅ range can cause mV errors, leading to lose of voltage control during electrochemical experiments. We also demonstrate a calibration routine to compensate for this voltage error that reduced the error by over 90%.
Research on Transmission Equipment Defect Detection based on Edge Intelligent Analysis
Authors: Shen H M , Fan P , Wei Z , Zhao C , Zhou S , Wu Q R 
Published: March 2021

Abstract
In the transmission system, the continuous load operation and the external environment will make the equipment fault hidden danger, which will affect the stable operation of the transmission system. In this paper, an edge intelligent analysis system of transmission equipment defect image recognition is proposed. The system migrates the cloud image recognition to the edge. Feature Pyramid Network(FPN) is introduced into Single Shot MultiBox Detector(SSD) object detection algorithm based on MobileNet v1 feature extraction network to detect defects of different sizes in large-size, small-size, tower and insulator equipment. So as to realize the rapid positioning of defects and upload the results to the cloud. The results of system application show that the accuracy and recall rate of the proposed system are high. In the case of ensuring the detection accuracy, it meets the real-time requirements of detection. The system can effectively improve the automation level of transmission equipment operation and maintenance. While improving the operation and maintenance efficiency of transmission lines, the safe operation of the transmission system is ensured.
Coordination Control and Suitability Evaluation of Multiple Ice-Storage Tanks in an Air-conditioning System Under Unreliable Communication
Authors: Yu Meng , Hu Wenbo , Huo Weiqiang , Cui Cui , Zhu Liangliang , Liu Jiaji , Wang Yao 
Published: March 2021

Abstract
Electric energy is an important part of building energy consumption, and air-conditioning accounted for most of the consumption of electric energy. Ice storage air conditioning is widely concerned because of its strong adjustability. Due to the limited space, it is often necessary to use multiple ice storage devices simultaneously to meet the application requirements. In this paper, a distributed coordination method for multiple ice storage devices is presented, which can allocate storage tasks according to the capacity of the device. Each device only needs to communicate with its neighbouring cold storage device, and finally achieve the control goal through distributed iteration. The convergence of the proposed algorithm is analysed by rigorous mathematics. If the communication topology between devices is connected, the algorithm can converge to the expected point. Finally, the validity and suitability of the algorithm and the correctness of theoretical analysis are verified and evaluation by digital simulation.
Design and Implementation of An Intelligent Vehicle Monitoring System
Authors: Sheng Xiaohua , Chen Hao , Wan Mengyi , Gu Gongchuan , Liu Zhicheng , Wang Xixi 
Published: March 2021

Abstract
Illegal behaviours often occur in using public cars in the enterprise. To detect abnormal vehicle usage, we propose an intelligent vehicle monitoring system. This system adopts the architecture of separating the front end and back end. Automatically alarm for exceptional vehicle usage by data analyzing and show the statistical results in the form of dynamic charts. This system enables enterprises and institutions to effectively grasp the shared data resources and promotes the informatization, standardization, integration and intelligence of vehicle management, so as to improve work efficiency and economic benefits.
Proof-of-Concept (POC) of Restaurant’s food requests in the Lisk Blockchain/sidechain
Authors: Alves Davi 
Published: March 2021

Abstract
Request food online is daily present in the life of people, however, it is necessary to send delivery information to different restaurant systems and sometimes these restaurants share customer sensitive information with their partners without the authorization of the customer creating a security risk with customers data. Also, in most cases when a person travels to a different country and wants to request food online, it is necessary to use the local currency, requiring a currency exchange operation. This paper evaluates a proof-of-concept (POC) of the integration of blockchain in the food industry, allowing customers to order food online through a sidechain, an exclusive blockchain with specific custom transaction types for restaurants. The FoodTransaction type is responsible to order food and store cryptographically customer sensitive information that only the customer itself and the requested restaurant can read, hence it respects customer privacy. Furthermore, the blockchain cryptocurrency can be used anywhere in the world. The performance evaluation shows a great advance in throughput when compared to the use of the payment solution on Bitcoin applications. Finally, the results show the possibility to extend the restaurant sidechain business to several restaurants in the world and in different time zones.
A Data Access Control Method Based on Blockchain
Authors: Ma Jun Wei , Xue Hong Lin , Wang Feng , An Yi , Han Dong Hui , Wang Dong , Zhao Min , Bi Sheng 
Published: March 2021

Abstract
In the digital era, a large amount of data is generated every day and recorded on the storage system. Access control is an important mechanism for ensuring data privacy and security. Data accessing control model of traditional storage system is centralized, which has threatened the information security of users. As blockchain is emerging technology which is widely used in the area of data privacy preserving, in this paper we proposed a decentralized access control model via blockchain based smart contracts implementation. Once satisfying the conditions set by users, visitors could apply to the blockchain for authentication, then obtain permission to access user data and operate the data, finally achieving secure access control of user data. In our experiment, we build the blockchain system based on Hyperledger Fabric project and evaluate both the efficiency of writing and the verification of access permission. The result shows our model’s usability and efficiency.
Research on Network Security Risk Assessment Method Based on Improved AHP
Authors: Li Juan , Yan Lina , Wang Jingyu , Fu Tao 
Published: March 2021

Abstract
Aiming at the problem that the data cannot pass the consistency test in the analytic hierarchy process (AHP), an improved AHP is proposed. The implementation scheme of the improved AHP based on D-S evidence theory and gray theory is designed, and matlab is used for simulation experiment. The results show that the improved method can effectively enhance the reliability of network security risk assessment results.
Lighting Design: Facets of A Single Phenomenon
Authors: Zaeva-Burdonskaya E A , Nazarov Y V 
Published: March 2021

Abstract
Lighting design today is one of the most actively developing types of design project activities. The definition of the profession reflects a wide range of established practice, which implies the presence of various theoretical positions. However, all experts without exception note the multi-level structure of the new profession, its pronounced interdisciplinary nature, which presents an additional burden for the designer. The scope of creative, engineering and social tasks, as well as IT technologies related to lighting design, reflects the nature of a complicated stage in the formation and development of the profession. The purpose of this publication is to acquaint the professional audience with the complex nature of light design, to identify a number of disciplines that make up its basis. This will allow to outline the ways of formation of new kinds and genres of lighting design, to identify its main priorities. The task of the designer is to choose a direction of activity at various levels: functional, applied, or easel direction; adhere to traditional urban light, work in the genre of multimedia light show, author’s light sculpture, etc. The multidisciplinary nature of the profession is united methodically by the scientific platform of creative activity. The design and artistic component becomes a priority in the hierarchy of innovative professional synthesis of that particular direction. Thus, lighting design is included in the sphere of project creativity, including the scientific and technical base of the new profession. The innovative potential of that activity has a significant impact on the process of its development, on the creation of a product and - as a result - on the quality of life of a wide range of consumers. In the work on the material, an analytical method of art history research was chosen. This allowed us to describe the emerging multidisciplinary problems of lighting design in a fairly broad and comprehensive manner and to outline ways to solve its current problems. The vocational education system is called upon to play a special role in this process.
Convergent Classroom: From Nature to Digital to Cognition in Geometry Acquisition
Authors: Tello Alcides Bernardo , Tarazona Cayto Didi Miraval , Tello Elia Bernardo , Mallqui Teófanes Huerta 
Published: March 2021

Abstract
Artificial Intelligence can provide intelligent solutions for the educational system. This article uses an object detection algorithm to explore physical surroundings and extract geometric shapes from two- and three-dimensional objects in real time within or outside a classroom. Having the shapes, the geometry lesson begins. We named it “Convergent Classroom”. We have conducted a post-test only group design in which first-year pupils from secondary school participated in the sessions. Our main results show substantial statistical evidence to support pupils’ higher geometry acquisition engagement using computer vision algorithm, compared to those who did not use it. This nature-to-digital-to-cognition engagement can be further explored by neuroscience measurement to understand what happens in pupils’ brain when they connect geometrical shapes from their surroundings to geometric cognition. Furthermore, these observed significant differences call for teachers to implement the already known algorithms in future classrooms.
Towards Rebuilding the Design Model of Programs by Static Analysis and Abstraction
Authors: Wen Yanjun , Chen Liqian , Wang Ji 
Published: March 2021

Abstract
It is difficult to understand a complex software program if its detailed design is not available. A model-rebuilding approach is presented to recover the design on an abstract level. In this approach, by static analysis of the program, a design is constructed and described in an abstract program which includes all behaviour that is observable at a set of selected program points. The approach provides an effective way for the understanding of complex programs.
A Fuzzy Adaptive PID Control Algorithm with Improved Quantification Factor
Authors: Shi Yile , Qiao Zhiyong , Bai Keqiang , Chen Guo , Liu Zhigui 
Published: March 2021

Abstract
The phase-shifting full bridge digital power supply based on Fuzzy PID control is difficult to realize the full mapping from the fuzzy universe to the actual output domain, resulting in the loss of fuzzy control quantity, resulting in the dynamic performance problems of large amplitude and long time output fluctuation. In this paper, a fuzzy adaptive PID control algorithm with improved quantification factor is proposed. The online adjustment function of quantification factor in fuzzy universe is introduced in the quantification link. The function can adjust the fuzzy quantification factor in real time according to the current sampling error and error change rate of the system. In order to verify the effectiveness of the improved algorithm, the traditional PID control, the traditional fuzzy PID control and the quantification factor improved fuzzy PID control are applied to the phase-shifting full bridge small signal disturbance model respectively. The results show that the fuzzy adaptive PID control algorithm with the quantification factor online adjustment function has higher dynamic performance.
Effects of Nano-WC on Microstructure and Wear Resistance of Laser Cladding Ni-based Coating on 42CrMoA Alloy Steel
Authors: Li Y F , Shi Y , Wu Q T 
Published: March 2021

Abstract
In the paper, Ni45 coating was manufactured by laser cladding on 42CrMoA alloy steel using the 5 kW CO2 laser, four-axis CNC machines and the coaxial powder feeding system. It was investigated that the effects of nano-WC on microstructure and wear resistance of the Ni-based coating. The macromorphology and microstructures were analyzed by SEM, XRD and microhardness tester. The wear tests were conducted on the Friction and Wear tester. The microstructure was first refined and then coarsened as the increase of nano-WC addition. When the nano-WC addition is 3.0 wt.%, the coating showed the finest microstructure. The clad layers including γ-Ni, N3B, M23C6 and WC, W2C. Meanwhlie, the wear rates of coating were gradually decreased.