bluuebunny/crossref_metadata_2025_split huggingface dataset:
User Behavior Set: Medley of User Behaviors to Eliminate Data Spatio-Temporal Sparsity
Authors: Huang Yangjun , Hu Xuanrui , Lian Jieyu , Jiang Xingpeng 
Published: March 2021

Abstract
A sequential recommendation system is war-ranted, and several models have been created to meet this need. However, sparsity is a major problem in this field. In order to deal with the space-time sparsity problem in a sequential recommend-dation system and avoid the unreliability caused by manually generated data, we have established the UBS structure. We treat user behavior sequences in batches. Each batch gets the inte-grated data set UBS after K iterations through a two-step cycle of clustering and merging. The results are connected as inputs of a sequential neural model. We use three baseline deep learning algorithms –Caser/SASRec/HGN to evaluate the model. We compared the UBS model with the original model in terms of normalized discounted cumulative gain ms(NDCG) and Recall. It is found that when the UBS model is applied to a short sequence of user behaviors and the iteration number K=2, it can improve the recommendation efficiency compared with the original algorithm (represented by K=0).
Research on Modern Construction Cost Economic Management Based on the Whole Process of Genetic Algorithm
Authors: Chen Guo 
Published: March 2021

Abstract
Genetic algorithm and neural network are both ideas and algorithm skills. The flexibility of this method provides a stage for many researchers and applications. In view of the complexity of general construction engineering valuation problems and the advantages of genetic algorithm and neural network algorithm, this article proposes a new construction engineering valuation model. Taking the actual residential project as an example, the feasibility and reliability of the genetic algorithm to optimize the neural network model are verified, and it is better than the simple neural network model, which provides an effective method for actual project investment estimation.
Research on Data Secure Transmission and Processing Method of a LoRa IoT System
Authors: Gu Jiting , Li Zhiqiang 
Published: March 2021

Abstract
The smart grid covers the traditional power grid and the Internet of Things network, including smart meters, which helps manage and monitor various customer consumption patterns in near real-time. To achieve data reading and effective management of terminal, smart meters connected to the power metering system, the article proposes using low-power wireless network (LPWAN) technology to connect terminal, smart meters to data gateways and private power clouds to achieve smart power metering Technical solutions. The solution uses the LoRa wireless module to realize the two-way interaction of power metering data and has the advantages of reliable operation, low cost, low power consumption, and remote access. This article also focuses on using emerging LPWAN technology to help build smart meter wireless access solutions and demonstrates the system implementation for smart meter end-to-end LoRa connection.
VSSHA: A Vehicle Scheduling Scheme for Tourist Attractions Based on Intelligent Heuristic Algorithm
Authors: Lin Yuan 
Published: March 2021

Abstract
With the development of tourism, vehicle traffic scheduling in scenic spots has gradually become a research hotspot. Aiming at the problem of vehicle scheduling and route planning at multiple service points in the scenic spot, we propose a method to minimize the total cost of vehicle scheduling and route planning tasks at the service point under the constraints of the weight of the required goods and the vehicle volume. First, we classify the demand points and assign the corresponding service points; then we aim to minimize the cost of vehicle scheduling and establish a nonlinear programming model under the constraints of the weight of the demand product and the volume of the vehicle; then, we will The model is reduced to a single service point TSP problem, and based on the improved ant colony algorithm, a solution model based on TSP is designed. The experimental results show that our model and algorithm can make the distribution cost of multiple service points the lowest and the iteration speed is faster.
A Novel Computer-Aided Cloud Type Classification Method Based on Convolutional Neural Network with Squeeze-And- Excitation
Authors: Li Guanshen 
Published: March 2021

Abstract
Clouds have a huge impact on the energy balance, climate and weather of the earth. Cloud types have different cloud radiation effects, which is an important indicator of cloud radiation effects. Therefore, determining the type of cloud is of great significance in meteorology. In this paper, the Convolutional neural network with Squeeze & Excitation Networks (SENet) are mainly used to solve this probelm. CNN can automatically learn the filters that need to be manually set before, and can learn complex edge, spatial and texture information in the image which are difficult for traditional methods to learn and extract. Moerover, a website and a deep learning framework are established to showcase the results of this article and to further develop our models and methods through open source methods.
Research on Computer Simulation Big Data Intelligent Collection and Analysis System
Authors: Liu Hongying 
Published: March 2021

Abstract
As a characteristic of big data, the individual data in it is no longer isolated, and the data and its underlying mechanisms have complex associations, which make all data into an indivisible whole. The dynamic generation and disappearance of data will change its original relationship and affect the overall characteristics of the data. This feature of big data makes the subject-oriented analysis methods such as data mining present limitations: the presupposition of the subject and the analysis by subject split the interaction relationship between the subjects, leading to the loss of the implicit mechanism in these relationships. Aiming at the problems of traditional network big data multi-resolution acquisition methods such as high acquisition cost, long completion time and low acquisition accuracy, a JA-va3D-based big data network multi-resolution acquisition method is proposed, and average interactive data is introduced. The extraction method estimates the power spectral density of the network data multi-resolution acquisition, and uses the ADASYN algorithm to remove the invalid multi-resolution data, and realizes the large data multi-resolution accurate acquisition. Experimental results show that the proposed method has lower acquisition cost, shorter completion time, and higher acquisition accuracy; it has certain practical value and can be widely used in various fields.
Application of Artificial Intelligence in Rehabilitation Assessment
Authors: Mu Pengyu , Dai Mingyu , Ma Xuenan 
Published: March 2021

Abstract
Assessment is the core and fundament of rehabilitation, which can guide the whole treatment process. In the rehabilitation, doctors or therapists need to assess the function of patients in upper/lower-limb, based on subjective assessment and objective assessment. While it may cause large error and high cost by traditional ways. Therefore, artificial intelligence technology is applied to the field of medical rehabilitation. This review will summarize the application of objective assessment methods which are base on artificial intelligence including not limited, trajectory error feature, joint angels and joint angular velocity, sEMG signal feature. Finally, the review concludes that existing objective methods are generally affected by the scale of data and the number of feature. This review will give instruction for a lager application in rehabilitation field.
Template-Based Collaborative Design Task Management for Complex Products
Authors: Zhou Junhua , Xue Junjie , Shi Guoqiang 
Published: March 2021

Abstract
The task template system of this system combines the business requirements of the work and provides the classification management function of work packages and work package templates. At the same time, data integration with other systems such as the main data system and resource library is realized. Through this system, users can instantiate a single work package to form a single work item, and can also establish the front and back relationship of the work package through the work package template, thereby realizing the instantiation of the work package process.
Design of Intelligent Electronic Boundary Pile Based on IoT
Authors: Min Youjia , Pan Jicong , Xia Weiran , Jia Bowen 
Published: March 2021

Abstract
Boundary pillars are important symbols of the junction, and at present, the most common way of managing boundary pillars in China is to employ a full-time boundary pillar maintainer in order to maintain the pillars themselves better. Damage to or loss of reference materials such as the "borders" can cause considerable problems in resolving boundary disputes and controversies.
In recent years, the Geographical Information System (GIS) has been in a stage of rapid development, both theoretically and in terms of application. With the advancement of network information technology and the increasing maturity of GIS technology, WebGIS combining the two has gradually been widely used in various industries, while the Internet of Things (IoT) is also developing rapidly, on which a more complete set of intelligent electronic boundary pillars based on IoT technology has the theoretical basis to emerge.
An improved ant colony algorithm for TSP application
Authors: Jiao Deqiang , Liu Che , Li Zerui , Wang Dinghao 
Published: March 2021

Abstract
Aiming at the problems of slow convergence speed and easy to fall into the optimal solution of ant colony algorithm, genetic algorithm and nonlinear optimization are used to optimize ant colony algorithm. After the initial iteration of the ant colony, the solution formed by all paths is the initial population, and then the genetic algorithm is used for selection, crossover and mutation to improve the ability of global search. Finally, the nonlinear optimization algorithm is used to increase the ability of local search of the algorithm. Through this improvement, the convergence speed of the ant colony algorithm is improved and the problem of easy to fall into the optimal solution is solved, which is applied to the traveling salesman problem.
Research on Computer Assisted English Teaching in Foreign Language Teaching in Colleges
Authors: Zhu Weihua 
Published: March 2021

Abstract
The continuous development of network technology in the information age has provided hardware guarantees for networked teaching, and the deepening of computer-assisted teaching research has promoted the development of networked computer-assisted teaching. With the popularization and application of informatization in colleges and universities, the use of modern information technology to change the traditional teaching mode has become the focus of attention. The C++ network-assisted teaching system uses computers and networks as the main means to develop network-based teaching and learning auxiliary teaching methods. This system is a mixed mode of network teaching and traditional teaching, which can enhance the communication between teachers and students, and can also play the role of the student-based teaching mode in network teaching.
Reliability analysis of logic control system of automatic ground control neutral section passing
Authors: Song Yuwei , Xiao Baodi 
Published: March 2021

Abstract
Neutral section passing technology in railway power supply had always been a technical problem in current domestic traction power supply industry. In recent years, there are many technical schemes for passing neutral section. There are two main schemes of automatic neutral section passing at present: the vehicle control neutral section passing and automatic ground control neutral section passing, the automatic ground control neutral section passing is a relatively popular technical route in both schemes. Now incorporating fail-safe principle of signal specialty in automatic ground control neutral section passing and proposing the logic control system of automatic ground control neutral section passing based on the idea of "fail safe" in the interlocking system, and the risk identification and safety analysis are carried out based on the dynamic fault tree and HAZOP method. The fault tree is constructed based on the results of HAZOP analysis. Finally, the system reliability is quantitatively calculated through the fault tree.
Face Recognition Based on CD-RBM and BM-ILM
Authors: Qiao Weisong , Chen Binbin , Zhao Jiabao , Guo Shudong 
Published: March 2021

Abstract
In recent years, the application of neural networks in face recognition has improved its accuracy greatly. However, it still suffers from the disappearance of the network gradient and the training cost. In this paper, we propose a new hybrid method which combines the contrast divergence algorithm (CD) accelerated Restricted Boltzmann Machine (RBM) and the Integrated Learning Method (ILM) with the Boosting algorithm (BM). First, we use RBM to establish a minimum energy model of the sample distribution. Then we use CD to speed up the feature extraction of samples in RBM. And then we build a multi-classifier with heterogeneous samples for ILM by BM. Finally, we experience our proposed method on the ORL database and the AR database. The results show that, with a simpler neural network determined by CD-RBM and BM-ILM, the recognition accuracy is better than that without the proposed method.
Research on the Attribute Extraction Algorithm of People and Vehicles Based on Video Structure
Authors: Zhang Chaoying , Liang Baolin , Ma Sicong , Xiang Chao , Bai Zhen , Wang Jianxiu 
Published: March 2021

Abstract
With the development of sensor technology and computer vision, the speed of video generation is increasing exponentially. The workload of video browsing and the amount of stored data are increasing. In order to achieve fast browsing and efficient storage, video structure technology is increasingly important. This paper focuses on the video structure technology in the construction of smart cities, outlines the system process of video structure, and studies the extraction algorithm of human and vehicle target attributes based on deep learning. And combined with the actual video monitoring scene, the experiment is carried out. Compared with traditional image processing methods, the video structure target attribute extraction model based on deep learning has high detection accuracy and strong algorithm generalization ability. The intelligent analysis and processing of data by video structure technology is conducive to quickly increasing the speed of target search, reducing storage capacity, solving the problem of long-term storage, and realizing full automation of surveillance video.
Automatic Machine Learning Method for Hyper-parameter Search
Authors: Su Minglan , Liang Baolin , Ma Sicong , Xiang Chao , Zhang Chaoying , Wang Jianxiu 
Published: March 2021

Abstract
Automatic Machine Learning (AutoML) uses automated data-driven methods to realize the selection of hyper-parameters, neural network architectures, regularization methods, etc., making machine learning techniques easier to apply and reducing dependence on experienced human experts. And hyper-parameter search based on automatic machine learning is one of the current research hotspots in the industry and academia. We mainly introduce the hyper-parameter search framework based on automatic machine learning and the common hyper-parameter search strategies. Combined with specific data sets, the classification accuracy of the model under different hyper-parameter search strategies is compared to find the model parameter configuration that can maximize the classification accuracy. Compared with the experience-based parameter adjustment method, the hyper-parameter search based on automatic machine learning can reduce labor costs, improve training efficiency, and automatically construct a dedicated convolutional neural network to maximize the model effect.
A Convolutional Neural Network-based UHF Partial Discharge Atlas Classification System for GIS
Authors: Zhang Congcong , Wang Gang , Gao Dong , Yin Wei , Wang Kai , Lu Ming , Liu Yingnan 
Published: March 2021

Abstract
In order to solve the difficult problem of partial discharge pattern recognition caused by large amount of partial discharge detection data and complex multi-source, a partial discharge pattern recognition algorithm based on VGG-16 convolution neural network is proposed. The parameters of VGG-16 network model are optimized in convolution layer, pool layer and connection layer by means of migration learning. The VGG-16 model is superior to LeNet-5 model and has higher recognition accuracy.
RETRACTED: Research on the Development Quality of College Student Party Members Based on the Internet Environment
Authors: Pan Yihui , Pan Yajing , Tu Keqin 
Published: March 2021

Abstract
With the wide popularization of computer network at any time, students’ computer technology operation level has been greatly improved than before, and students have more channels to obtain information. In the Internet environment, the development of high-quality student party members is an extremely important work for the party’s construction, and has practical significance for the realization of the two centenary goals and the great rejuvenation of the Chinese nation.
Research on Providing Data and Space Calculation Support for Site Selection of Power Transmission and Transformation Projects
Authors: Jin Yao , Yu Wenxing , Zhao Jie , Song Zhuoyan , Li Hongzhu , Liu Bo , Xie Dan , Zheng Yaobin , Duan Shengchao , Zhao Zhipeng 
Published: March 2021

Abstract
With the acceleration of urban construction, the urban electricity load has increased rapidly, and electricity shortages have also appeared in various places. However, the rapid development of cities has resulted in a shortage of land. The location of substations and the selection of transmission lines are particularly important in planning. In this paper, distributed power transmission and transformation project to optimize network access with locating and sizing problems, establish an annual loss of power as the objective, and consider the output load timing characteristics of multi-period optimal power flow model. Use representative scenes to simulate the situation throughout the year, and give a method for determining scenes and their weights.
Design and Implementation of office automation network security system
Authors: Nan Tianwei 
Published: March 2021

Abstract
Socket based network communication is a flexible, easy to implement, low cost method. It can run on a variety of networks that use THE TCP/IP protocol as the communication protocol. So the design in VC++ environment, through the Socket to establish the original Socket, monitoring network traffic, and suspicious data through Access database records, to provide reference for administrators, so as to achieve network security.
Research on Seeker Servo Platform Based on BP neural network controller
Authors: Tang Wei , Jiang huhai , Pu bin , Zhang Tongtong , Mao Rui 
Published: March 2021

Abstract
Seeker is the core of precision guided weapon. The performance of its servo mechanism has a decisive impact on the accuracy of guidance weapon. The controller design of seeker servo system is of great significance to improve the function of seeker servo system. The mathematical model of the seeker servo system in the form of transfer function is built. The traditional PID control and BP neural network PID control methods are used to design the controller respectively. Aiming at the limitation of BP neural network, the BP neural network is improved. Finally, the simulation experiment is carried out in Matlab/Simulink. Simulation results show that the neural network PID controller has better performance than the traditional PID controller, so that the system has better adaptability and robustness.
A Combination of Lexicon-Based and Classified-Based methods for Sentiment Classification based on Bert
Authors: Zhang Jiaxin 
Published: March 2021

Abstract
Sentiment classification is a crucial problem in natural language processing and is essential to understand user opinions. There are two main approaches to solve this problem, one is the classified-based method, the other is the lexicon-based method; however, both methods perform not well on the long-sequence methods, and each method has its advantages and disadvantages. This paper introduced a new method called Lexiconed BERT, which cream off the best and filter out the impurities from the above two methods. The evaluation shows that our model achieves excellent results in the long sequence sentence and reduce resource consumption significantly.
Research on Station Balance of Robot Production Line Based on Improved Double Population Genetic Algorithm
Authors: Zhou Zheng , Meng Qingyu , Du Lifeng , Wang Xin , Liu Yang 
Published: March 2021

Abstract
Aim to solve the balance problem of robot production line, an improved double population genetic algorithm is proposed. The priority relation of production process is treated as the constraint condition, the selection function of crossover probability and mutation probability is designed according to the individual fitness of the population. Then the beat optimization algorithm is used to optimize the production rhythm of a switch shell welding line. The simulation result show that the balance rate of this robot welding line is improved and the production rhythm is optimized.
A Multi-objective Tracking Task Assignment Algorithm Based on Game Theory
Authors: Quan Bei , Lu Xuanmin , Zhang Yumeng , Mou Zhiying 
Published: March 2021

Abstract
Aiming at the relationship between competition and cooperation among sensors in multi-target tracking task allocation, this paper proposes a game theory-based method to allocate sensor resources for multi-target tracking tasks. The dissertation first establishes a target tracking model and designs a game theory payment function based on the model. Then a multi-sensor multi-target tracking task allocation game model is designed. Finally, a multi-target tracking task allocation algorithm based on game theory is given. Compared with other allocation algorithms, the average tracking error of the proposed allocation algorithm is reduced from 68.5630m to 19.7601m through experiments.
Intelligent Content-Centric Networking Routing Strategy: A Bacterial Quorum Inspired Pattern
Authors: Yang Hong , Guo Xiong , Li Mengliang 
Published: March 2021

Abstract
In recent years, the Content-Centric Networking (CCN) has attracted much attention from the global Internet experts, especially it has demonstrated the outstanding effect on the application in the field of Internet of Things (IoT). At present, the routing technique of ICN is subjected to the dynamic change of network environment with the development of mobile Internet. Therefore, this paper proposes an Intelligent CCN routing strategy based on Bacterial Quorum pattern (ICBQ). The ICBQ tries to simulate the behaviors of bacteria, including quorum sensing and adaptive chemotaxis. Meanwhile, the quorum sensing can obtain the parameter information on bandwidth, delay and error rate to facilitate the subsequent forwarding of packets; The adaptive chemotaxis can select the optimal interface to forward the packets through the information measurement. The simulation is driven based on the real Netflix dataset over the GTS network topology, and the experimental results show that the proposed ICBQ has better performance in terms of routing success rate, routing delay and load balance.