bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research and Design of Wireless Network Time Synchronization Module Based on IEEE1588 Protocol
Authors: Shan Feilong , Yu Jianguo , Wang Zhifang , Li Kaile , Dong Junguo 
Published: July 2020

Abstract
Wireless network systems have many problems, such as low data transmission rates, limited coverage, limited measurement node capacity, and low time synchronization accuracy, especially the millisecond-level time synchronization accuracy can no longer meet the needs of the market.Therefore, it is urgent to find a more accurate time synchronization technology solution. At the same time, the accuracy of the time synchronization of the IEEE1588 protocol in a distributed wired network can reach the nanosecond level, so it is extremely important to introduce it into a wireless network to achieve more accurate time synchronization in the wireless network. This paper is the research and design of high-precision time synchronization module for wireless network based on IEEE1588 protocol. It mainly uses ARM + FPGA + WLAN structure to design time synchronization module. According to the actual test of the module, it can be known that the time synchronization accuracy that the wireless network time synchronization mode can achieve is as high as 150ns, which can fully meet the needs of the wireless market for time synchronization accuracy.
Method for Calculating the Weights of Internet + Government Service Data Quality Assessment Indexes Based on Analytic Hierarchy Process
Authors: Ya Li , Heliang Song , Yingcheng Xu 
Published: July 2020

Abstract
In this paper, research and analysis have been carried out on the theories related to Internet + government service data quality. Based on the principles of scientificity, systematicness, development, and operability, an Internet + government service data quality assessment index system suitable for China’s big data era has been proposed, this index system is proposed from five aspects: inherent quality of data, quality of data expression, system-related scenario quality, utility quality of data, and user experience quality of data. The analytic hierarchy process method has been used to analyze the relationship between indexes at the criterion layer, the sub-criterion layer and the objective layer, and the weights of the data quality assessment indexes at each layer were determined. The method proposed in this paper provides an idea for the assessment of government service data quality and has certain practical significance, laying a theoretical foundation for the related work of Internet + government service data quality assessment.
Simulation of the FPT for Multi-Dimensional Wiener Process with Dynamic Thresholds
Authors: Gao Hongda , Wang Cheng , Liu Rui , Cui Weiping , Liu Wei 
Published: July 2020

Abstract
Reliability modeling and analysis has becoming an essential issue in complex system management. Degradation system reliability modeling is an important part of the reliability field due to that the failure data is more and more difficult to obtain. Degradation data can well describe the failure process of a system or product. In the stochastic process, the Wiener process has been widely used in literature due to its good properties. Multidimensional diffusion Wiener process describes the multidimensional degradation process of products. First passage time is the lifetime of a system to reach a threshold value. In this paper, a generalized model is developed for evaluating the reliability of the multidimensional degradation process. Meanwhile, we use the Monte Carlo method for the solution of the FPT with dynamic threshold value. The comparisons show that the results of the proposed model agree well with the Monte Carlo results. The research can support decision making in the reliability improving.
Investigation on Taxi Trip Characteristics Based on Taxi GPS Trajectory
Authors: Xu Weiyan , Huang Yumei 
Published: July 2020

Abstract
Knowledge of urban taxi trip characteristics is crucial at many levels of urban transportation planning, operations, and traffic management. In this paper, we investigate the characteristics of taxi trip through analyzing approximately 3,000 taxis spanning seven consecutive days in Lanzhou. The characteristics of taxi trip such as taxi trip speed, service time, vacation time, and spatio-temporal patterns of taxi trip are analyzed. The results show that the average speed of taxis varies between 17 km/h to 22 km/h from 7 am to 8 pm. Moreover, the average service time and vacation time are 20 minutes and 6 minutes, respectively. Although, the net flow ratio in heart of the city goes around zero, the flow direction of taxi trip is obviously different in the morning rush and the evening rush. Moreover, The rural-urban fringes have a strong positive net flow ratio which indicates that the strength of inflow is greater than that of outflow.
Loss Analysis for Networks based on Heavy-Tailed and Self-Similar Traffic
Authors: Zhuang Danna , Li Chuanhuang 
Published: July 2020

Abstract
Many businesses on the computer network appear heavy-tailed self-similarity (long range dependency), which means network traffic exists burst. Various service source with burst characteristic which show self-similar have a significant effect on transmission performance, network traffic control strategy and network performance indicators such as loss. Loss is an important QoS parameter at the network node, which need to be considered and controlled in all types of traffic, but there is no paper study loss analysis based on heavy-tailed self-similarity. Thus, only analyze and evaluate loss under self-similar traffic can reduce the adverse effects which caused by traffic self-similarity and optimize network performance. We adopt stochastic network calculus approach to bewrite loss lssue. Based on this, we present the loss analysis in the case of a single node network using heavy-tailed service curve and heavy-tailed self-similar arrival curve, and loss analysis under cross traffic, multi-node networks with concatenation. And we also get the relational graph between the loss and the arrival rate, service rate.
Virtual Sample Generation for Retraining the Malicious PDF Detection Model
Authors: He Kang , Liu Long , Lu Dong-Zhe , Zhu Yuefei 
Published: July 2020

Abstract
PDF files are adopted for launching cyberattacks because of their popularity and the increasing number of relative vulnerabilities. Machine learning algorithms are developed to detect the maliciousness of PDF files. As the exploits of new vulnerabilities occur, the assumption that the training data and the test data share the same distribution does not hold and the ability of origin model to detect exploits of new vulnerabilities weakens gradually. In a real environment, it is very difficult to obtain numerous samples of exploits with the same CVE. and the machine learning models are difficult to be improved by retraining. Virtual sample generation could be used to generate sufficient virtual samples by small sample sets to improve the generalization of the existing model. A new VSG algorithm based on prior knowledge is proposed in this paper, which performs better than other VSG algorithms in improving the detection on exploits of new vulnerabilities.
Scale-adaptive Correlation Filter Tracking Algorithm Combined with Statistical Color Histogram Feature
Authors: Wang Xinying , Wei Haiping , Yu Hongfei 
Published: July 2020

Abstract
The algorithm based on kernel correlation filtering shows excellent performance. Aiming at the problem that traditional correlation filtering algorithms are sensitive to deformation and cannot solve the tracking failure caused by scale changes, this paper proposes a scale-adaptive correlation filtering algorithm combining statistical color feature. Firstly, predict and train the HOG features of the correlation filter and the color histogram features to obtain the respective response values, namely the template response and the histogram response. Then adopt the block method, and perform scale prediction based on the position of each response point. Finally, the final fusion response is calculated. The experimental results demonstrate that compared with traditional KCF, when the target scale has large scale change and deformation, the improved algorithm in this paper performs better, and can still track stably.
Design and Implementation of BIM-based Fire Risk Assessment System
Authors: Zhang Hui 
Published: July 2020

Abstract
Integrating BIM with fire risk assessment, this thesis adopts the fire risk index method and analytic hierarchy process to assess the risk of buildings and establish fire risk assessment index system. With Microsoft Visual Studio 2015 as the development platform and C # as the development language, the secondary development was carried out based on BIM technology, which is characterized by efficiency, reliability and scientificity, and a fire risk assessment system based on BIM was successfully designed, which can realize the fire risk assessment of four types of buildings: residential building, public buildings, factory building and warehouses. The system can directly import the fire protection data of buildings needed by fire risk assessment from BIM to complete the building fire risk assessment, which not only can make fire risk assessment process simplified with less costs, but also can enable the fire risk assessment to be widely used in all kinds of buildings, thereby further promoting the fire safety level of buildings.
Research on Institutional Invalidation Caused by “Potential Rules”
Authors: Wang Yu , Tao Ding 
Published: July 2020

Abstract
Through the simulation study of multi-equilibrium game with “Potential Rule” strategy, we find that the behaviour of “Potential rule” can be evolved through repeated game without considering any other social preferences of the subject and any prior knowledge of the game. This paper will analyse the endogenous evolution of the third strategy, namely the “Potential Rules”, between the choices of fair and unfair strategies from the perspective of interest transmission. The experimental results show that the subjects who own the third strategy with the characteristics of “Potential Rules” will spread to other subjects in a certain institutional environment by imitating learning and adjusting strategies. The third strategy will become a guide to the behaviour of the subjects and form a deviation of the institution, which will lead to institutional failure.
A Model Driven Approach to Constructing Knowledge Graph from Relational Database
Authors: Sun Shanxin , Meng Fanchao , Chu Dianhui 
Published: July 2020

Abstract
Relational database is one of the main data sources in the construction of vertical domain knowledge graph. How to establish the mapping relationship between the concepts in relational database and the corresponding concepts in knowledge graph is the key to improve the efficiency of the construction of vertical domain knowledge graph. To solve this problem, this paper proposes a model driven approach to automatically constructing knowledge graph from relational database based on the Model Driven Architecture (MDA). First of all, a model driven framework is proposed to describe the relational database and knowledge graph using standard XML Schema. Then, a model driven approach is proposed, which extracts database models and data to XML, defines the conversion functions, transforms models and data from database to knowledge graph, and builds knowledge graph according to the expression forms. Finally, using a case to validate the approach. This paper uses the idea of model driven to realize the high-quality transformation from relational database to knowledge graph.
Dynamic performance improvement in motor drive systems of electric vehicle by z-source inverter
Authors: Yong-yu Wang 
Published: July 2020

Abstract
This paper present an integral sliding-mode controller based on equivalent control to overcome the disadvantages of non-minimum phase system, which the z-source inverter has when it is used in the motor drive system of electric vehicles. Based on the pseudo-output, which is defined by measured capacitor voltage and inductor current on z-source network, a constant capacitor voltage control strategy for z-source inverter is given. With the reaching condition imposed, the controller can guarantee the stability of closed-loop system and the robustness of system output. The simulation results show that the closed-loop control system for z-source inverter can achieve better global robustness with zero steady error, and that the capacitor voltage on z-source network can be stabilized with good performances of motor drive system.
Analysis on Demand and Development Direction of Smart Grid under the Background of Two-network Convergence
Authors: Ye Gangjin , Shang Jiayi , Yang Xuan , Wu Mengyao , Chen Zhiyuan 
Published: July 2020

Abstract
With regard to development strategy of “two networks integration”, based on improvement of power supply capacity, power supply security and reliability, fault response, information collection capability as well as improvement, intelligence, integration and automation upgrade on real-time monitoring capability, “two networks integration” planning strategy and implementation plan, such as planning for distribution network, distribution itself, ubiquitous power Internet of Things, are made to greatly improve overall capacity of distribution network, which further provides reference for similar projects, such as high-quality, stable, efficient and green power supply.
Study on Power Supply Structure of AC / DC Distribution Network Considering Different Proportion of New Energy Access
Authors: Yang Yanhui , Xue Yu , Liu Wenxia , Fu Mengdi , Li Yueqiao 
Published: July 2020

Abstract
Considering the diversification of energy and load, according to the different situation of new energy access to distribution network, three typical AC-DC hybrid distribution network power supply modes are summarized. On the basis of these three power supply modes, the indexes of AC-DC hybrid distribution network are extracted, and the comprehensive evaluation index system is established. A comprehensive evaluation model of AC / DC hybrid distribution network suitable for new energy access is proposed, which aims to maximize economic benefits. The example shows that the optimal power supply mode can be selected through the evaluation model when the proportion of new energy is different, which can lay a foundation for the future distribution network to better serve users on the premise of distribution network profitability.
Power Grid Fault Diagnosis Based on Improved Deep Belief Network
Authors: Zhang Yihui , Zhang Yuansheng , Wen Libin , Cui Zhimei , He Yini , Liu Guangshi 
Published: July 2020

Abstract
It is of great significance to quickly and accurately identify power system faults. This paper introduces the idea of deep learning into power system fault diagnosis research and proposes a fault diagnosis model based on improved deep confidence network. Construct a set of 30-dimensional original features that can reflect the fault characteristics of the power system as the model input, and the fault diagnosis result is the model output. Use multi-layer Boltzmann machines to train the mapping relationship between grid faults and system features. Finally, the extreme learning machine is used to supervise the labeled samples to modify the network parameters. Different system failure scenarios were set up on the New England 10-machine 39-node system to test the diagnosis ability of the model. Simulation results show that the improved deep belief network has a strong feature extraction capability. The improved deep belief network has higher accuracy and faster speed in fault categories, fault areas, and fault locations than common artificial intelligence methods.
Power transaction security check optimization model and system of AC / DC hybrid power grid applied in China Southern Power Grid
Authors: Liu Chunxiao , Wang Tao , Su Yinshen , Li Zhiyong 
Published: July 2020

Abstract
With the continuous and in-depth promotion of China electric power reform, the annual and monthly trading volume of electric power is increasing, the power transaction security check is mainly based on the artificial experience to add and subtract the power components that is difficult to analyse the unit group with member coupling and the power restriction relationship between transmission sections. China Southern Power Grid has developed a set of power transaction security check system using improved SCUC optimization model. The system is able to effectively locate the reason for the power transaction security check exceeding the limit and give the optimization and adjustment suggestions. The efficiency and calculation speed of the power transaction security check optimization algorithm for large scale of AC / DC hybrid power grid are successfully improved. The IEEE RTS 96 system and CSG power system are used to test the efficiency of the algorithm under different grid scales. The calculation time is proved to be reduced about 50% and generation cost is almost the same as the conventional algorithm. The construction and application of the system helps CSG to solve the surplus hydropower consumption problem.
Research on power supply reliability of AC/DC Micro-grid System in “Multi-station Fusion” Project
Authors: Zhou Xing , Liu Jiangmin 
Published: July 2020

Abstract
This paper studied the power supply reliability and structure of the AC/DC micro-grid in the “multi-station fusion” project of smart energy stations. According to study the deep integration of the energy storage unit and the design of the data center, proposed three power supply modes of energy storage unit application to the data center server, and proposed the wiring form of the DC micro-grid. Optimized the configuration and operation mode of the diesel generators and the UPS system. On the basis of ensuring the reliability of the power supply of each system, the construction cost and operation costs were reduced, and the overall energy efficiency of the power system was improved. It provides a reference for the design and operation of “Multi-Station Integration” projects of smart energy stations.
Blockchain-enabled power distribution side management: model and method
Authors: Yang Jianlin , Fei Fei , Wang Haiqun , Guo Mingxing , Lü Ran , Jia Kevin 
Published: July 2020

Abstract
With the development of the “ubiquitous power internet of things”, the shortcomings of the traditional centralized power trading mechanism in power distribution side have gradually become apparent, e.g., low flexibility in power usage. And blockchain technology gains some insight to deal with these problems due to its distributed nature. To this end, the paper implements a blockchain-based multi-channel energy management model on the Hyperledger Fabric blockchain platform to carry out a transaction-driven power management method in the power distribution side. Simulation results show its operability and effectiveness.
A Novel Model for VPP to Participate in Capacity Market Auction
Authors: Kuang Yi , Wang Xiuli , Li Nailiang , Zhao Hongyang , Qian Tao 
Published: July 2020

Abstract
With the development of intermittent renewable energy, power system needs more capacity resources to ensure the generation adequacy during peak load periods. Flexible resources such as electric vehicles(EVs) and demand response resources(DRRs) will play important roles in the capacity market auction. However, due to the uncertainty of outputs, they are not competitive enough in the market and face high investment risks. In order to deal with this situation, we integrate renewable energy resources(RESs), EVs and DRRs into a virtual power plant (VPP) and proposed a novel auction model for the VPP to participate in the capacity market. The objective function is to maximize the social welfare while satisfying the reliability of the system. This paper also presents the results of a case study with three scenarios to prove the validity. The proposed model provides a novel path for distributed flexible resources to participate in capacity market.
Research of self-adaptive PID drilling fluid level control algorithm based on differential flow
Authors: Li Lei , Deng Hu , Dong Zhigang 
Published: July 2020

Abstract
Aimed at the puzzle of traditional PID control algorithm not satisfy level control requirement when drilling fluid performance changing, the article proposed adaptive PID level control algorithm based on differential flow. Through monitoring differential flow between slurry pump outlet and buffer pry inlet, the algorithm got optimized PID control parameters and evaluated drilling fluid properties, which could be used for liquid level control under different fluid medium characteristics. In the laboratory test of drilling fluid tank, the proposed algorithm could always keep the level deviation within 5% through self-adaptive modify PID control parameters under different drilling fluid characteristics. The results shows that the algorithm has wide adaptability and high reliability, and can be applied to the liquid level control situation where the characteristics of the fluid medium change.
Network Intrusion Detection based on Deep Neural Networks for the SCADA system
Authors: Altaha Mustafa , Lee Jae-Myeong , Aslam Muhammad , Hong Sugwon 
Published: July 2020

Abstract
Security monitoring is one of the security strategies for the supervisory control and data acquisition (SCADA) systems, and the intrusion detection system (IDS) is a main tool to do security monitoring. Main task of security monitoring is to develop the SCADA-specific IDS, which reflects the semantics of the SCADA domain. In this paper, we work on developing IDS based on deep learning models for the SCADA system. The target SCADA communication protocol of the detection model is the DNP3, which is currently the most commonly utilized communication protocol in the power substation. The attack of major concern is data injection or modification attacks, which is most critical attack in the SCADA system. We extract 12 data features from distributed network protocol 3 (DNP3) packets, and use them to train the deep neural network. We measure the accuracy and loss of the detection system trained based on different deep learning algorithms, and show the comparison of the results.
Overall optimization of operation cost of the boiler and SCR in coal-fired power plants
Authors: Li Wei , Xu Qiang , Kong Dean , Zhao Xiang , Gao Ning , Lv Xuguang 
Published: July 2020

Abstract
Coal-fired power plants are usually equipped with selective catalytic reduction (SCR) systems to reduce nitrogen oxides (NOx) emissions. In this paper, we considered both the denitrification cost of the SCR system and the coal burning cost of the boiler to develop an operation cost model. Furthermore, the genetic algorithm was proposed to minimize the total operation cost by optimizing the feature parameters, including the primary air pressure, secondary air volume, overheated air volume, and NH3 injection volume. Simulation experiments were performed based on the operating data of a 1000 MW coal-fired power plant, with results showing that the total operating cost of the boiler and SCR was lowered.