bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting Individual’s Posting Behaviors in Social Network with Markov Chain
Authors: Qiao Fengcai , He Su , Deng Jinsheng
Published: October 2020

Online social networks like twitter are self-organized systems with emergent behaviors from the individual interactions. Predicting the users’ behaviors like posting, replying or retweeting is one of the most important issue. In the paper, we present a method to model the twitter users’ posting behavior with the other users’ response. We also contrast the simulation precision with the model that does not involve the other users’ response. We make use of a stochastic model with Markov chain to predict a specific user’s next tweeting behavior. From the result by contrasting the simulation data and the real data, we demonstrate that the engineering method is able to predict individual posting behaviors based on time windows. In addition, the proposed model involving other users’ response is better than that only considering posting time sequences.
Fisheye Rectified Image Super-resolution Using Deep Symmetrical Neural Network
Authors: Zhang Yuanfa , Li Weili , Yin Xiaoqing , Deng Jinsheng
Published: October 2020

Influenced by the fast developments of imaging technologies, fisheye cameras have been widely applied. But the resolution of images captured by fisheye cameras is limited due to lens distortions. In our work, we use a deep symmetrical network model to deal with single fisheye rectified image super-resolution task. It is shown by the experiments that the proposed method can achieve satisfactory results for fisheye rectified image super-resolution.
Using Open-Source Learning Platform(Moodle) in University Teachers’ Professional Development
Authors: Xiao Qin
Published: October 2020

With the development of information technology, teachers’ professional development based on network has attracted more and more attention due to its ease of use, openness, sharing and knowledge accumulation. This paper studies the importance of teachers’ subjective consciousness and self-development needs in the information technology environment in the university teachers’ professional development, discusses how to update teachers’ professional development attitude and adapt to the new role of teachers in the information technology environment; Moodle(or Magic lamp in China), namely: modular object-oriented dynamic learning environment, is a course management system (CMS) designed and developed by Australian teacher Martin Dougiamas based on the theory of social constructivism. The paper analyzes the internal relationship between Moodle related functional modules and teachers’ professional development, and the possibility of realization. After in-depth analysis of characteristics and advantages of Moodle as a technology platform and the support and application value of Moodle platform for university teachers’ professional development, this paper constructs a new mode of teachers’ professional development with Moodle as the interactive platform, which is “one platform, two footholds, three ways and multi-body participation”.
The Study on Basic Fatigue Properties of the New Axles Steel and Axle Fatigue Assessment
Authors: Liu Qingfeng , Lyu Yawen , Yan Liang , Zou Hua
Published: October 2020

With the development of the high speed railway construction, we poise a higher demand for the performance of EMU. This subject is designed to get the information about the new axle materials’ S-N curve by testing the fatigue property of axle materials. With the help of finite element simulation, finite element model of wheel pair could be built. Through the method of numerical simulation, we could know the stress distributing when wheel pair are stressed, and evaluate the intensity of axles.
Foot Pronation Detection Based on Plantar Pressure Measurement
Authors: Yu Junchao , Gao Weidong , Jiang Weining
Published: October 2020

In the paper, we design a foot pronation detection system based on plantar pressure sensors. The system includes: collecting the pressure sensor signals by reasonably arranging the pressure sensors; collecting the plantar pressure signal value of the test object which has been walking for a period of time; taking the proportional calculation, determining the fuzzy sets, designing the membership function, the fuzzy processing was carried out and the fuzzy rules was established by the IF-THEN rules. Finally the gait phase was deduced according to the fuzzy output signal, and the system function was realized by pronation analysis algorithm. The experimental results show that the system has an important value for sports risk prediction.
Surface Water Quality Classification Based on MobileNetV2
Authors: Hao Jingbo , Tao Yang
Published: October 2020

Water quality detection is important for water resources protection. There is an urgent need for convenient and precise water quality detection methods. In this paper a deep learning based detection method is proposed. A MobileNetV2 classifier is constructed and tested aiming at surface water quality classification. The experimental results show that the classifier has excellent performance and can also be deployed on edge devices conveniently.
A Safety Evaluation Method of IMA Dynamic Reconfiguration Process Based on CPN
Authors: Liu Lei , Zhao Wei , Jiang Zeyong , Wang Shihai
Published: October 2020

With the rapid development of integrated modular avionics (IMA), the dynamic reconfiguration of IMA provides great advantages in resource utilization and aircraft configuration and acts as a valid means for resource failure management. Due to the complexity of dynamic reconfiguration process, it is difficult to analyze and evaluate the safety of dynamic reconfiguration process. The Architecture Analysis and Design Language (AADL) is effective in modeling such process of the embedded real-time system. Colored Petri Net (CPN) has advantages of simulation and evaluation. Therefore, this paper model the IMA dynamic reconfiguration process based on AADL, and transfer it to CPN model to analyze and evaluate the safety of the process of dynamic reconfiguration. Finally, a case study is provided to indicate the effectiveness of the method.
Data Analysis for Field Orienteering Heat Training
Authors: Yang Hui , Sun Yanfei , Xue Xiangfeng , Hou Zhibin , Yang Shuojun
Published: October 2020

Orienteering is a kind of intelligent sport that the athletes are selected on the base of integrative evaluation of the physical, skill and psychological qualities. In this paper, a method is supposed to evaluate and select the seeded player with data such as total time consumption, split time, positioning efficiency and operation efficiency. It can be concluded with data series collected from two distinctive heat training courses that, 1) the operation efficiency and it’s standard deviation of 5th player achieved the optimization, and 2) the solution in this paper can be popularized for selective heat training in common primary school or college with limited training equipment.
Comparison of Chinese Character Correct and Error Classifier for Overseas Students Based on Handwriting Motion Characteristics
Authors: Zhang Jun , Zhang Xiwen
Published: October 2020

The quality of Chinese characters written by foreign students is reflected not only in the result of writing, but also in the writing movement. 25 characteristics of handwriting movement were selected from 39 parameters, such as time, space, movement and pressure. Based on the feature of handwriting motion, 6 classifiers, such as Decision Tree and Artificial Neural Network, are selected to compare the performance of them. Experiments show that the accuracy of DT algorithm is the best regardless of whether the target characters are known or not. Handwriting movement features are effective representations of the quality of Chinese characters written by foreign students.
U-shaped Feature Extractor Used on Mask R-CNN for Cell Nuclei Image Segmentation
Authors: Zhu Qing , Huang Xiaoyang , Wang Liansheng , Li Jonathan
Published: October 2020

The cell nuclei segmentation of is a challenging task in microscopy image analysis. The problems of noise, small cell nuclei, and few training data samples in the data set will all affect the effectiveness of the model to varying degrees. This paper presents a new approach to nuclear image segmentation based on convolutional neural networks. Our approach is based on Mask R-CNN with some modification, which combines low-level semantic features for model training. In order to make the model specific to each low-level feature map, the attention mechanism was used to assign weights to each low-level feature map, making the model learning more purposeful. Our method achieves an average precision value of 62.8%, which is 2.7% higher than that of the Mask R-CNN (ResNet50) basic model and 6.3% of the Mask R-CNN (ResNet101) basic model.
An Improved Random Forest Algorithm
Authors: Yu Ying , Wang Lingyun , Huang Hao , Yang Wenwen
Published: October 2020

A random forest algorithm with an improved decision tree and an optimal tree integration is proposed. First, an improved ID3 decision tree is proposed. Next, when the trees are integrated, each decision tree is assigned a voting right consistent with the out-of-bag accuracy of the decision tree. Finally, the experimental results show that the improved random forest algorithm is efficient and the classification performance is improved compared with the traditional random forest algorithm.
Research on Attack Detection Method of Microgrid Central Controller Based on Convolutional Neural Network
Authors: Xi Wei , He Shengguo , Chen Rui , Xu Yongjun , Li Weifan , Zhou Guoqi , Yu Weiguo , He Hongyan , Huang Zhiwei , Yu Yang , Yao Hao , Liu Hui , Xiao Shengyuan , Yue Zhihui , Liu Wei
Published: October 2020

The microgrid central controller (MGCC) integrates the functions of control, monitoring, and communication in microgrid system, and has powerful capabilities of information collection and data processing. However, with the development of microgrid system worldwide, the information security management capabilities of the MGCC are poor, If information / network attacks cannot be actively detected and identified, it will easily reduce the reliability of the microgird system operation. Attackers can use abnormal information or use the MGCC as a springboard to further attack the upper-layer system. Aiming at the above problems, this paper presents an attack detection method based on convolutional neural network, and a detailed design process of attack detection model of the MGCC is proposed. In the attack detection method, the important data streams in the MGCC are used as the input of the convolutional neural network model, then the convolutional neural network model detects or classifies these data streams, finally, intercept the data flow with attack behavior and give a warning prompt, and forward data without attack behaviors normally.
RETRACTED: Data Analysis and Application Research in Sports Field under Big Data Environment
Authors: Ding Peng
Published: October 2020

This paper expounds data mining theory and sports data analysis theory, such as data mining concept, mining method and mining flow. Taking the data analysis in basketball and track and field as an example, this paper discusses the application of data mining in the field of sports industry, mass physique monitoring and physical education data analysis at home and abroad, and analyzes the influence of big data on sports, mainly changing the methods of competitive sports training, promoting the innovation of sports research methods and the transformation of sports communication methods, and promoting the development of the world sports industry.
Architecture Design and Key Technologies Study of Omnichannel Business Platform for Electric Power Marketing
Authors: Lin Hong , Ouyang Hong , Fang Xuemin , Wang Jinzhi , Yuan Bao , Yang Wei
Published: October 2020

Building the omnichannel business platform for the electric power marketing and integrating all online service resources, with the features of customer aggregation, business integration and data sharing, are an inevitable pathway for the power grid enterprise to establish the customer-centric modern service system and realize its digital transformation strategy. The overall architecture of the omnichannel business platform is proposed and the detailed design for the eight shared service centres are given respectively for user centre, ticket centre, electronic bill centre, payment centre, order centre, points centre, online customer service centre, and messaging centre. Some typical application scenarios are described to illustrate the internal working mechanism of the shared service centres and the cooperation mechanism among them, such as management of comprehensive energy business, online interaction service for the electric power customer, and instant messaging delivery. The key technology applications and practices are discussed for the implementation of the business platform, such as improving data processing capabilities, building integrated services with fast response, and developing digital operational capabilities. The development prospects of the business platform are concluded finally, whose service centres would be gradually be evolved into an important component of the strategic business platform for the power grid enterprise by continuously precipitating the business capabilities and establishing the competent service centres.
Analysis of Key Problems in the Optimal Design of Satellite-based Precise Point Positioning Messages
Authors: Liu Cheng , Zhang Weixing , Liu Xiaolei , Gao Weiguang , Lu Jun
Published: October 2020

Precise point positioning (PPP) technology for satellite navigation has received considerable attention because of its wide area coverage, uniform accuracy, and small number of ground reference sites. The use of satellite-based broadcasting technique enables the realization of PPP at the globe, even for users on the oceans. However, due to limited and valuable satellite downlink resources, the optimal design of satellite-based broadcasting message is of great significance. In this study, the influences of some key factors on the accuracy loss of products are analyzed, including the PPP message broadcasting interval, the message data bit width, and the scale factor. On this basis, the effect on the final positioning accuracy of the user is evaluated. Broadcasting design ideas and suggestions for major augmentation products, including Global Navigation Satellite System satellite orbits and clock corrections, through a simulation calculation based on a precise ephemeris are given, thereby providing references for the optimal design of satellite-based augmentation PPP service messages.
The Design of the Control System of Fire Control and Smoke Extraction Robot Based on PLC
Authors: Jiao Hongwei , Ma Zhenming , Hua Wanren
Published: October 2020

The purpose of this paper is to design a plc-based control system of fire control and smoke extraction robot, which can realize the purpose of water cannon, vehicle body movement and non-line-of-sight operation. This control system is mainly composed of PLC control system, video system, remote control system, motor drive system. PLC Through CANopen message transmission protocol, the function of distributed control system is realized. The main task is to receive the CAN command of remote control, so as to realize the command control of vehicle body action (multi-way valve), yuntai action and water cannon action. The design meets the design requirements, has good operability and reliability, in the industry has a certain promotion significance.
Improved Fuzzy Hierarchical Clustering Algorithm and its Application in Software Re-architecting
Authors: Gao Sheng , Lu Chenghua , Miao Ning
Published: October 2020

Computer technology changes with each passing day. As a member of software system, the architecture of legacy system becomes complex and difficult to adapt to complex software functional requirements in the process of evolution. It has not only affected the late legacy system maintenance work, but also to the enterprise has brought serious losses. In order to solve the above problems, this paper presents a Fuzzy Hierarchical Clustering algorithm Based on Information Loss, FHCBIL. There are two improvements in FHCBIL algorithm: On the one hand, this algorithm extends the weights allocation of entity features, which solves the problem that the two element relation can not reflect the influence degree of entity feature on entity. On the other hand, FHCBIL algorithm uses the information loss as a similarity calculation method, avoiding the problem of sensitive data set to the irregular data set in the clustering process. In this paper, we further apply FHCBIL algorithm in software re-architecting, give the model of software re-architecting, and implement new nested software architecture. In order to evaluate the quality of the new architecture, we evaluate the new architecture from two aspects: the rationality of the new architecture hierarchy and the accuracy of entity division. The experimental results show that the new architecture based on FHCBIL algorithm has high cohesion and low coupling. And the accuracy of the new architecture is high.
Language Governance of International Cities in Artificial Intelligent Technology Age
Authors: Zhang Jing
Published: October 2020

Technological advances, especially the development of mobile Internet and artificial intelligence are playing a more important role on urban language life. Thus, exploring the new phenomena and new challenges that language life in international cities may face, especially the role that intelligent technology can play in multilingual communication has important theoretical and practical significance for the governance of urban language life. This study takes the international metropolitan cities as the research scope in order to analyze the language governance in the international metropolitan cities based on AI technologies. It hopes that the results of this study could provide some implications and insights to enhance people’s ability of using AI technologies and mobile apps to solve communication problems.
Monitoring Method of Internet of Things for Classified Recovery of Medical Waste
Authors: Wang Chao , Ma Yanxia , Meng Fanwen
Published: October 2020

In order to overcome the shortcomings of the existing technology and hit the medical waste disposal of black industry chain, this paper provides an IoT monitoring method for medical waste treatment, which can strictly monitor medical waste from the source, processing by digital, back in any link problems, the use of big data to find abnormal problems, guide the development of medical enterprise, to ensure the safety of people’s life.
Botnets Attack Detection Using Machine Learning Approach for IoT Environment
Authors: Htwe Chaw Su , Thant Yee Mon , Su Thwin Mie Mie
Published: October 2020

The era of the Internet of Things (IoT) is very rapidly developing with millions of devices that are useful in the smart home, smart city, and many other smart systems for education, organization and so on. On the other side, attackers are mostly targeting these devices. After infecting the malware attacks on these devices, they become bots that are controlled by attackers, and these will be targeted to the organizations not only for stealing important information but also for breaking down the network. Although some security mechanisms have developed to protect against cyber-attacks, most such systems are rule-based systems, like public IDS systems. And also, the formal rule-based detection could be circumvented by the malware attackers’ knowledge. Therefore, the machine learning-based detection scheme is the replacement for the lack of previous detection techniques. The proposed detection architecture is based on machine learning methodology, like the CART algorithm and public IDS dataset, named N-BaIoT. The experimental results indicate that the detection accuracy of the selected classifier, CART is significantly better than that of the Naïve Bayes classifier, and the overall detection rate using CART is reached up to 99%.
Research on the Evaluation Model and Method of “Generaliztion, Serialization, Combination” Degree of Naval Gun
Authors: Wang Hongguang
Published: October 2020

In China, there are some problems about the degree evaluation of “generaliztion, serialization, combination” of naval gun, such as the lack of inheritance, the incompleteness of the standard evaluation system, the limitation of the evaluation scheme, and the disunity of the evaluation standard system. In order to solve this problem, this paper established of the degree evaluation model and method of “generaliztion, serialization, combination” of naval gun, by which define the coefficient of generalized number of pieces and the coefficient of generalized type spectrum. This method provides certain data support for the development and production of naval gun series.
Architecture Design of Emotion Recognition Early Warning System Based on AE-TAN Algorithm
Authors: Zhang Yongxiong , Huang Xiangzheng , Wang Liangming
Published: October 2020

In order to improve the analysis effect of human emotion text data, this paper proposed NB algorithm, TAN algorithm and AE-TAN algorithm model method. In addition, three index parameters, precision, recall and F1 value, are compared and analyzed under three different algorithm model scenarios. The experimental results show that the AE-TAN algorithm is superior to the other two algorithms in Chinese text emotion analysis. Based on the AE-TAN algorithm, the architecture design scheme of emotion recognition early warning system was proposed in this paper, which has the characteristics of high concurrency and high availability, thus laying a technical foundation for the system that can quickly and accurately warn people of psychological problems.
Resource Management Method of Distributed Parallel Database Based on Directed Graph
Authors: Shi Yingjie , Zhang Huayun , Wang Xiang , Zhou Yuchao , Jiang Shusong
Published: October 2020

A distributed parallel database resource management method based on directed graph is proposed. By using content distributor based on distributed unstructured P2P network association, the high performance and stability of distributed parallel database system in dynamic changing environment are guaranteed. The problem of network congestion caused by too many redundant messages and the “barrel effect” caused by resource imbalance due to differential configuration is solved, through resource search algorithm based on directed graph lookahead, and the query node cached the resource information of two-level neighbor nodes. By adopting the Linux cgroups resource management mechanism, fully considering the multi tenant and multi factor based resource scheduling strategy, reduce resource fragments and better meet the problem of distributed parallel database storage or hot spot processing.
A Study of Internet-Based Collaborative Translation Model for Chinese American Literature
Authors: Shao Juanping
Published: October 2020

The Internet has brought great changes to our study, life, interpersonal communication and so on. With the popularization of the Internet, “Internet +” has become a new model that promotes the rapid development of various industries and nobody can escape from it. The Internet collaborative translation model can improve translating efficiency and quality, and it is conducive to the communication and broadcast of different cultures. So, it can be taken as a new possibility and attempt to translate Chinese-American literature. But, there are also some problems such as inconvenient management of translating process, great differences in styles and quality of translated texts, and so on.
The Design and Realization of Intelligent Greenhouse Control System Based on Cloud Integration
Authors: Zhao Hong , Kong Dongyi
Published: October 2020

In order to solve the problems of high cost and large input resources of traditional greenhouse management system, this paper designs an intelligent greenhouse management and control system. The core control part of the system uses a cloud integration design architecture chip, based on China’s Alibaba dominated YoC platform to realize the cloud integration design. The end side design with a master control board which using a 485 bus communication, and polling mode was adopted to realize the sensor data acquisition and actuator control; The cloud side creates Topic list on the cloud platform of Internet of things, communicates with the end side through the subscription and publication mechanism of MQTT protocol, and realizes data upload and cloud instruction acquisition. Finally, the function test is carried out in the environment of greenhouse simulation mode.
Design and Research of Elevator Group Control System Based on PLC
Authors: Zhang Xuexia , Shang Ying
Published: October 2020

This paper is based on the research of elevator group control system based on PLC, aiming at the phenomenon of elevator in the running process of long time elevator phenomenon, on the basis of improving the utilization of elevator, put forward the overall design structure of elevator group control system, through the communication and control between group control and single elevator, to achieve the unified coordination of elevator scheduling. Considering the riding comfort of passengers, the shortest waiting time of passengers is shortest, and the algorithm of elevator group control scheduling system is analyzed according to the time delay algorithm. At the same time, the elevator control system is analyzed in detail, using PLC to achieve the hardware circuit design, complete the elevator control signal processing, through the inverter control motor operation, to achieve the elevator uplink and downlink. In the design of elevator control software, the overload detection and the delay treatment of the switch door are set up to improve the safety of the elevator, so that the elevator can develop in the direction of intelligent.
Application of Human Body Recognition Technology in Scientific Research Sites
Authors: Liu Yugang , Zhang Xiaofeng
Published: October 2020

In schools and various scientific research institutes, there are a lot of confidential places, such places usually have a person in charge of the management of the scientific research platform. It is an effective method to detect people entering the secret place by video surveillance and give early warning and warning to outsiders. In the video monitoring in normal use, the recognition method of human body is a kind of dynamic pattern recognition, in order to be able to quickly form to the variety of the human body for effective identification, this paper uses the fuzzy clustering method to filter the static image elements in the video image, in view of the dynamic pixel area, by using convolutional neural network to identify the human form, improve the system recognition robustness for optimized recognition effect.
Research Based on the Python Networkx Toolbox Analysis of the Trade Network Structure from an Information Flow Perspective
Authors: Zhong Bingcheng , Hu Yang , Yang Junyu
Published: October 2020

Based on the python networkx toolbox analysis of the trade network structure form an information flow perceptive, studies show that China’s import and export trade with some areas along the “The Belt and Road Initiative” has declined, but overall, whether it is Both import demand and export demand are rising year by year, which shows that China and the various regions along the “The Belt and Road Initiative” line have become closer in terms of trade and international trade trends have become more apparent.
Design of Intelligent Pedestrian and Vehicle Guidance System for Zebra Crossing Based on Millimeter Wave Radar
Authors: Guo Peng , Xiang Hong , Wu Shengguang , Pu Tian , Chen Dongyang
Published: October 2020

In order to protect the life safety of the pedestrian and strengthen the intelligent management of urban traffic, this paper’s proposes is a set of low-cost and easy-to-install intelligent transportation pedestrian and vehicle guidance system. The system can be applied to the non-crossroads zebra crossing. On the premise of ensuring the safety of crossing pedestrians, it would reduce the waiting time of vehicles when there are no pedestrians or scattered pedestrians passing by, to improve the vehicle traffic rates and avoid the traffic accidents about people and vehicles snatch the right of way, so as to effectively guide pedestrians and vehicles to pass. The system uses STM32L431RCT6 microcontroller as the main control chip, uses millimeter wave radar technology to monitor the number of pedestrians in front of the zebra crossing, intelligently controls the time of pedestrian passing, and coordinate the traffic lights on both sides of the road for countdown display by Lora, and switches the traffic status of vehicles and pedestrians, for realize the function of traffic command. At the same time, the system will automatically upload the number of pedestrian to OneNET, providing access and management interface for superior applications, so that the transportation department can master the travel rules, and provides travel data for the construction of smart city. The system also can receive data returned from OneNET, and flexibly control the time of pedestrian passing at that moment.
Design of Operating Platform for Intelligent Charging Pile Based on Micro-service
Authors: Pan Xueyuan , Hu Shejiao
Published: October 2020

The introduction of “new energy vehicle charging pile” as one of the contents of “new infrastructure” indicates that the field of charging pile is facing a new round of technological innovation, deployment difficulties and other shortcomings are no longer suitable for its charging operation of the growing business needs. In view of this, a design method based on microservice architecture is proposed. The open source distributed framework Spring Cloud and its components are used to realize the mechanism of service registration discovery, load balancing, service fault tolerance and so on. The reformed operation system has a clear structure, stable operation, timely monitoring and processing of abnormal information such as charging pile fault, and has a broad application prospect.
On-line Detection of Malicious Activities Based on Edge Computing in Micro-grid System
Authors: Lei Wenxin , Xu Aidong , Lin Haojie , Hou Wenjing , Zhang Yunan , Jiang Yixin , Mao Zhongqi , Wen Hong
Published: October 2020

With the continuous deployment of smart grids, various new smart technologies applied to the power grids have emerged, and the security boundaries of the power systems have gradually blurred, so that the power security protection measures urgently need to be updated. Aiming at the smart micro-grid system based on edge computing, this paper introduces a non-intrusive load monitoring (NILM) method, combined with the advantages of edge computing, and designs an online detection mechanism for malicious activities of terminal devices. This method is dedicated to achieving device-level security assurance.
Design of Man Hour Management Information System on SpringBoot Framework
Authors: Chen Jian , Pan Hailan
Published: October 2020

This paper introduces an information system based on SpringBoot framework of man hour management, by analysing the problems existing in the man hour management workflow and process in an industrial design and assembly company. Like fraud timesheet, confusion of validation, etc. This paper designs the different function modules and provides the overview of the system, and explains the reason of using SpringBoot framework. Finally, describe the improvement for the company in both controlling and processing level.
Enhancing the Security of Mobile Device Management with Seccomp
Authors: Niu Yingjiao , Wang Yuewu , Jia Shijie , Zhou Quan , Lei Lingguang , Zhang Qionglu , Zhao Xinyi
Published: October 2020

Mobile devices today have been increasingly used to store and process sensitive information, and Mobile Device Management (MDM) solution is provided in Android systems to manage the mobile devices. MDM solution enforces device policies through calling Device Administration APIs provided in Android system. However, these APIs are usually implemented in user space, thus make the system more vulnerable to be attacked. Potential adversary may bypass these secure policies by breaking through the isolation between processes. In this paper, we propose an approach based on the seccomp mechanism of Linux kernel to enforce device management policies on Android. Seccomp can restrict the system calls of Android process to enforce device management policies in a more secure way. Experiments results demonstrate that our work may work well and incur negligible overhead.
Study on Intelligent Perception Internet of Things Apply in Mine Safety
Authors: Xu Liangchen , Sun Lin , Wang Daoyuan , Li Jingzhao
Published: October 2020

Due to the complexity, multi-source and heterogeneity of mine safety scene perception information, the mine safety monitoring system has some problems, such as slow perception, communication lag, lack of effective information extraction and intelligent decision-making, a mine safety situation perception self configuration system based on the Internet of things is proposed in this paper, the architecture and perception model of mine safety situation perception system are established, and the embedded neuron is designed mine safety monitoring system based on perceptual node and distributed neural network. The unscented Kalman filter is used to adjust the BP neural network to reconcile and process the multi-sensor parameter information. The simulation results show that the system has good fault tolerance and high precision of intelligent decision-making, which plays an important role in improving mine intelligent level and safety production.
Efficiency Analysis of Collaborative Based Recommendation System
Authors: Khalid Waleed , Xing Xing , Julius Aikodon , Niu Yong , Tahir Osama , Ihsan Imran
Published: October 2020

Over the recent times, there has been great enhancement towards online shopping and platforms that provide commerce. Hence, great research and work has been done and is being done in field of recommendation systems. With this great development, there has been an exponential increase in online inventory due to the great number of users excessing these online platforms for buying and selling purposes and companies are often looking for advanced recommendation systems to provide their customers with the best online experience in respect towards each individual customer. It is believed that recent advancements in Deep Learning may provide an optimal solution for better recommendation systems, but it requires validation. The main aim of this paper is to follow through different research and investigate whether modern Deep Learning algorithms live up to the expectations and demands. Different reviews have been given in support with experiments. This literature review provides an analysis of different practices, state of the industrial methodologies and current research.
A Surrogate Model Based Genetic Algorithm for Complex Problem Solving
Authors: Pei Ying , Gao Hao , Han Xiaosong
Published: October 2020

It is well known that when the fitness function is relatively complex, the optimization time cost of the genetic algorithm will be extremely huge. To address this issue, the surrogate model was employed to predict the fitness value of the optimization problem, to reduce the number of actual calculated fitness values. In this paper, BP neural network, the least square method and support vector machine were fused in the genetic algorithm to evaluate partial individuals’ fitness. Sufficient benchmark numerical experiments were conducted, and the results proved that the strategy could reduce the calculating counts of fitness function on similar accuracy basis compared with simple genetic algorithm.
A Three-stage Multiple Criteria Decision Making Model Based on AHP-TOPSIS and AFS Concept Description
Authors: Tao Lili
Published: October 2020

In this paper, we propose an integrated model to solve the multi-criteria decision making problem.Firstly, AHP method is applied to calculate the weight value of each attribute on all the alternatives; secondly, TOPSIS method is used to get the preference value based on the weights calculated in the first step; finally, AFS concept description algorithm is employed to give the semantic descriptions of performance characteristics for all the alternatives. Compared with other models, this model can not only consider the comprehensive preference value, but also consider the specific performance characteristic of the alternative, which makes the decision more scientific. The supplier selection problem is applied to explain the application ability of this model.
A CIM-Digital Heterogeneous Accelerating System with Analog Interconnection for Neural Networks
Authors: Xu Rui , Xiang Zikun , Tao Linfeng , Jin Xi
Published: October 2020

In recent years, computing in memory (CIM) has been regarded as a promising competitor for low-power accelerators for neural networks. Different implementations based on various memories like ReRAM and flash memory have been proposed. However, a ‘cloud’ is hovering on the horizon of CIM. The limited frequency and high power consumption of DACs and ADCs have become major obstacles of further improvement of the power efficiency of CIM accelerators. The method of utilizing a more advanced process to increase the frequency and reduce the power consumption of DACs and ADCs can hardly be used because of the tight coupling of memory process and CMOS logic process in CIM accelerators. To solve this problem, this paper proposes a CIM-digital heterogeneous neural network accelerating system with analog interconnection. It decouples the CMOS logic process and the memory process in CIM accelerators by using analog interconnection, and implements ADCs and other units in an independent CMOS process. According to experimental results, compared to prior CIM accelerators, the proposed architecture can achieve an increase in the sampling rate of 26.7 times, to 100 MHz, and an increase in the performance of 26.7 times accordingly. The power efficiency can be improved 5.8 times.
Research on the Path of Internationalization of Higher Vocational Education Based on Computer Aided Technology under the Background of One Belt One Road
Authors: Hu Anlin
Published: October 2020

The internationalization of higher vocational education has become an important trend in the development of vocational education, which is an important indicator of the construction of “double first-class” higher vocational education. The introduction and implementation of the “one belt and one way” national strategy has provided a direction for China’s higher vocational education, which has brought tremendous opportunities and challenges to the internationalization of education. This paper uses computer-aided technology to first analyze the significance of internationalization of higher vocational education. Then, this paper puts forward some questions. Finally, some suggestions are put forward.
Specific Strategies for Selection of 5G Networks Based on Computer NDN Technology
Authors: Pu Baoqing , Sa Zhimin
Published: October 2020

5G network is the main point of mobile communication research, as a new generation of mobile communication system, compared with 4 G network over-frequency utilization and energy efficiency, transmission rate and resource utilization is higher, user communication quality has been improved. This paper analyzes the 5 G fusion network access selection strategy under the framework of NDN technology network to determine the most suitable analysis method and algorithm to reduce the influence of various factors.
Research on Intelligent Traffic Monitoring System Based on Image Recognition Technology
Authors: Wei Bin
Published: October 2020

With the rapid development of China’s national economy, the number of cars on domestic expressways and in cities has greatly increased. Cities have more and more facilities, such as roads and parking lots, while traffic control and safety management requirements are increasing. In Japan and overseas, Intelligent Transportation System (ITS) has become the main direction of current traffic management development and image recognition based on image recognition technology. As one of the core technologies of computer intelligent transportation system, computer technology is an important part of intelligent transportation system. The wide application of this technology will make a great contribution to the automation of traffic management in China.
Research on the Safe and Efficient Utilization of Computer Technology in the Large-scale Development of New Energy Power
Authors: Chen Bingqian
Published: October 2020

New energy mainly refers to various forms of energy other than traditional energy, including wind energy, solar energy, hydropower, geothermal energy, etc. New energy power generation refers to relying on these new types of energy for power generation, rather than relying solely on Traditional energy sources such as coal and petroleum generate electricity. The use of new energy methods to generate electricity can not only realize the sustainable use of resources, but also optimize resource allocation, convert idle resources into usable resources and improve resource utilization. In order to promote the management of power projects in an orderly manner, we need to establish a scientific and effective computer system, so that we can effectively guide the development of power project management and effectively improve its development efficiency.
RETRACTED: Research on the Influence of Electrified Railway Interference on Outdoor Signals Based on Computer Simulation Analysis under High Speed Rail and Heavy Load Conditions
Authors: Wu Bo
Published: October 2020

As an important guarantee for the safety and reliability of the system, the signal anti-jamming of electrified railway has always been an important part of railway signal research. In the high-speed and heavy-load electromagnetic environment, the core signal equipment is also facing greater challenges. Therefore, we will use computer simulation technology to analyze the influence of electrified railway interference on outdoor signal. Based on computer simulation and analysis, this paper focuses on the impact of strong EMI on railway signal and protection technology under high-speed and heavy-haul conditions.
RETRACTED: Research on the Teaching Mode of College English Listening Based on Computer Multimedia Platform
Authors: Liu Caiyun
Published: October 2020

Single teaching environment, limited teaching conditions and backward teaching equipment hinder the development of listening teaching. In recent years, with the development of science and technology, the application of computer multimedia in the classroom has greatly improved the teaching equipment and conditions of listening class, and made the classroom teaching of English listening have a qualitative leap.
Construction of Intelligent Logistics Model Based on Big Data
Authors: Pan Canhui
Published: October 2020

The arrival of the era of big data and the rapid development of e-commerce has provided a new direction for the development of modern logistics industry. It has promoted the logistics industry to transform the past experience thinking into data thinking. The operation mode has gradually changed from the traditional extensive mode to the intelligent logistics mode characterized by informatization, data, sharing and intelligence. Based on the analysis of the characteristics of intelligent logistics under big data, this paper describes in detail the future of intelligent logistics related enterprises and technological progress trend, with a view to realizing the transformation and upgrading of logistics industry. Firstly, this paper introduces the concept of intelligent logistics under the context of big data, and then puts forward the construction of intelligent logistics framework based on big data, as well as the construction method, which provides suggestions for the stable operation of intelligent logistics and has reference significance for its better development.
Research on Mathematical Modeling Strategy Based on MATLAB from the Perspective of Innovative Ability Training
Authors: Zhu Changxin
Published: October 2020

With the development of computer, computer application technology has been widely penetrated into various industries. Among them, MATLAB is a commercial mathematical software, which is second to none in mathematical science and technology application software. In this paper, the mathematical modeling strategy is studied by MATLAB software. Mathematical modeling is an effective mode of cultivating mathematical thinking, which is of great significance to the cultivation of students’ logical thinking ability. The strong practicality of mathematical modeling cultivates students’ innovative consciousness, the diversity of problems cultivates students’ innovative ability, and the interdisciplinary nature enhances students’ innovative knowledge reserve. This paper first analyses the role of mathematics education in cultivating innovative thinking, and then puts forward effective strategies for developing mathematical modeling activities. It is hoped that the idea of mathematical modeling can be better integrated into the mathematics teaching in Colleges and universities.
RETRACTED: Application Value and Applied Research of Diversified Teaching Based on Big Data Analysis in Oil Painting Teaching in Chinese Universities
Authors: Wang Chaobin
Published: October 2020

Since the reform and opening up, China’s economy has developed rapidly. On the basis of the continuous improvement of national material living standards, people have gradually turned their attention to the field of culture and art. Nowadays, many colleges and universities have offered courses related to oil painting, hoping to cultivate professional talents through appropriate teaching and improve students’ artistic accomplishment. Therefore, it is necessary to apply diversified teaching methods. Through the diversified teaching of big data analysis, it analyzes the problems in college oil painting teaching and the impact of diversified teaching, and explores the specific application of this teaching method in college oil painting teaching.
Research the Application of Artificial Intelligence Technology in Mobile Phone Terminal
Authors: Zhang Chengnian , Tong Haifeng
Published: October 2020

Computer Science and technology are following the wheels of social development, constantly moving forward, and epoch-making artificial intelligence technology has emerged. As soon as artificial intelligence technology appeared, it quickly became popular in all industries. After applying artificial intelligence technology to the Internet, society’s demand for artificial intelligence has reached a peak.
The Application and Research of Heat Transfer Experiment Course Based on Computer Hybrid Learning Method
Authors: Ma Chuan , Liu Xiaoyan , Liu Lijun
Published: October 2020

In heat transfer experimental course, there are very common that some students only record experimental data and copy others’ experimental reports. They do not need to preview before the class, and they do not need to think during the experiment. However, as an important practical subject in experimental teaching, heat transfer experiment course will seriously affect the output quality of Chinese college graduates. This paper firstly analyzes the existing problems in the heat transfer experimental course based on computer hybrid learning method. Then, this paper puts forward the teaching mode reforming of heat transfer experiment course based on computer hybrid learning method. Finally, this paper puts forward the computer teaching mode suitable for colleges and universities at the present stage, which is combining with teaching, experiment and examination.