bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electric Power Equipment Image Recognition Based on Deep Forest Learning Model with Few Samples
Authors: Yao Nan , Cheng Ke 
Published: January 2021

Abstract
Power system equipment have many characteristics, such as many kinds, single color, similar appearance and complex environment of transmission and substation. These characteristics make it difficult for traditional image recognition technology to achieve good recognition results. If there are few training data samples, the performance of in-depth learning recognition declines sharply. To solve these problems, this paper designs an optimization and training recognition method based on the combination of generating confrontation network and deep forest. Firstly, the generated countermeasure network is used to expand the samples of power equipment, and then the active learning method is used to optimize the generated samples. Secondly, the traditional model-enhanced sample expansion method is used to expand the optimized samples twice. Finally, the robust network model is obtained by using the deep forest method to accurately identify the power equipment. Experiments show that this method has high recognition accuracy and is superior to many other algorithms.
Cricket Video Events Recognition using HOG, LBP and Multi-class SVM
Authors: Abbas Qamber , Li Youmeng 
Published: January 2021

Abstract
The world has witnessed a growth in multimedia data, especially video data over the past few years due to increased internet bandwidth and higher processing power of computers. Having a large number of video data also require techniques to store, summarize, index and information retrieval. More attention has been given in recent years to develop techniques which summarize, index and retrieve sports videos due to its commercial aspects. This paper proposes a framework which classifies a cricket video into one of the four events namely Bowled Out, Caught Behind, Catch Out and LBW Out. The framework uses training videos from each category of event and summarizes the videos into key frames. HOG and LBP features are computed for key frames and fused to form a single feature vector which will be labeled accordingly which represents a single event in video. Feature vector is given to a Multi-Class SVM which classifies the video into one of the four events. The experimental results show that the Precision of our technique is 77.23%, Recall is 77.86%, F-Measure is 77.55% and the Accuracy is 65.62%. The evaluation metrics of our technique are promising, because in the literature there is no other technique present so far for event detection & classification in cricket videos.
Malicious Traffic Classifier in android using Neural Networks
Authors: Abbas Qamar , Abbas Qamber , Jin Jesse S. 
Published: January 2021

Abstract
Now a day’s android is the fastest growing package in hand-held operating system. And it has become the most appealing and practical goal of malicious applications. This principal platform has approved itself not only in the mobile global but also in the Internet of the Things (IOT) devices. The most real risk of Android clients is malware contamination by means of Android application markets. The huge diffusion of malware in cellular platform is plaguing customers. Threat of malicious software has come to be an essential element within the protection of smartphones. The war between protection analyst and malware intellectual is abiding as contraption grows. The proposed methodology demonstrated the common precision 94% a tagged mobile malware datasets visitors with a lot of applications contains benign and twelve very different groups of all malware and adware in particular and complicated nature of malware is converting quickly and therefore emerge as harder to understand. We assessed different blends of oddity location calculations, include determination strategy and the quantity of the top highlights to decide the mix that gives the best activity in distinguishing new malware on Android. This research condenses the malware progression recognition procedures backed machine learning algorithms devoted to the Android OS.
Automatically Trimming Profile Based On Triangular Mesh Model
Authors: Kong Jihong , Wu Chao , Qiu Enhua , He Man , Lv Yisong 
Published: January 2021

Abstract
The article introduces an automatic algorithm for cutting contour based on triangular mesh model, which realizes the solid section, automatic filling and material inheritance of the 3D model in the virtual reality environment, which can be accurately visualized in the virtual reality environment. It can not only describe the solid section of the 3D model, but also inherit the material texture relatively accurately, and it has a good real-time. The algorithm is applied to the immersive virtual reality simulation platform of the hydropower plant, which can allow students to perform real-time 360-degree viewing and cutting of the equipment of the power plant, and improve the knowledge level of the employees of the power plant on the internal structure of the equipment.
Research and Application of Multipath Network Time Service System
Authors: Xu Jie , Wu Jing 
Published: January 2021

Abstract
The time source of this paper is based on Shanghai Laboratory of National Time-Frequency Measurement Center. The target of this paper is to build a multipath network timing system within the wide area network which could make sure the accuracy, reliability and safety of network time service. This Multipath Network Time Service System also playing an influential role in providing dedicated network time services for seconds-level time-demanding industries. The pharmacological analysis of the medical industry is used as a service demonstration case to verify and promote the application of the multi-path network timing system.
Image Inpainting Using Double Discriminator Generative Adversarial Networks
Authors: Zhang Chao , Wang Tong 
Published: January 2021

Abstract
The image inpainting algorithms based on GAN have problems such as color inconsistencies of the inpainted region with the surrounding part and the mode collapse during the training. This paper proposes an inpainting algorithm based on double discriminator generative adversarial networks (GANs). This algorithm introduces the loss function of WGAN-GP into a global discriminator and local discriminator independently. It combines the Mean-Square Error (MSE) and feature reconstruction loss function to train the inpainting model and repair the missing area. The algorithm uses more dilated convolutions instead of standard convolutions to obtain a larger receptive field and the skip connection to enhance the structural prediction ability of the generator. The experiment results on the labeled faces in the wild dataset show that our algorithm improves the quality of image inpainting and the stability of the training process.
Research on intelligent operation and maintenance management method of enterprise IT
Authors: Wang Xiaoshuang , Su Yaofeng , Li Qiang , Han Feng 
Published: January 2021

Abstract
With the gradual deepening of the influence of artificial intelligence technology on all walks of life, enterprise IT operation and maintenance management is also undergoing changes in a more intelligent and advanced direction. In order to change the practical problems of enterprise IT operation and maintenance management, such as single method and lack of means, this paper analyzes and studies the overall framework of enterprise it intelligent operation and maintenance management technology, and deeply analyzes the key intelligent methods in operation and maintenance management, such as fault prediction, fault analysis, operation and maintenance scheduling, so as to provide support for effectively improving the level of enterprise it intelligent operation and maintenance and systematic support ability.
Design of Surface Roughness Evaluation System Based on UWP
Authors: Sun Kaixin , Liu Na , Cai Xiaoyu 
Published: January 2021

Abstract
The surface roughness algorithm and its evaluation system is the key factor of surface morphology measurement. This paper studies the UWP (Universal Windows Platform) platform and uses C# language to realize surface roughness evaluation system. The system can accurately calculate 4 commonly used surface roughness parameters based on the established mathematical model. The system includes 3D surface data reading, surface roughness calculation, graphic interaction and other functions. Experiments results show that the system can realize rapid and multi-parameter measurement of the workpiece’s surface roughness, and is adequate for surface morphology characterization. The cross-platform evaluation system is user-friendly with visualized 3D data and reliable results.
Improved Particle Swarm Optimization Algorithm Based on Dynamic Change Speed Attenuation Factor and Inertia Weight Factor
Authors: Wang Chao , Ou Yang , Shan Zhiyong 
Published: January 2021

Abstract
Compared with other optimization algorithms, the particle swarm optimization algorithm (pso) has the advantages of fast convergence, simple calculation, and fewer parameters to be adjusted. Therefore, it has been greatly developed in the past period of time. In order to further accelerate convergence, in recent years, more efficient and convenient particle swarm optimization algorithms such as LDWPSO, NLPSO, and DPSO have been proposed.However, these algorithms have many problems such as large amount of calculation, lack of precision, and easy to fall into local optimum.Therefore, the algorithm still needs to be improved. In order to obtain an efficient global search ability early in the algorithm iteration and better local optimization performance in the later stage of the algorithm iteration, this paper proposes a special expression form of dynamic change speed attenuation factor and inertia weight factor, and in the algorithm some random parameters are added to the iterative formula and applied to the algorithm iteration formula to improve the optimization speed and optimization effect of the algorithm.Finally, the effectiveness and correctness of the algorithm are also demonstrated by computer simulation experiments.
A Novel Image Encryption Algorithm Based on Bernoulli Shift Map
Authors: Guo Youmin , Zheng Dateng , Liu Dingning , Li Fupeng 
Published: January 2021

Abstract
This paper puts forward a chaotic encryption algorithm based on Bernoulli Shift Map. This algorithm adopts dynamic encryption key and uses plaintext image parameters to control generation of chaotic key, and enhance connection between chaotic key and plaintext data; the iterative operation precision of chaotic map during encryption is high, avoiding cycle of chaotic system iteration process. The NPCR and UACI analysis, adjacent pixels correlation analysis and image information entropy analysis on encrypted image show this encryption algorithm has favorable encryption characteristics such as larger space for key, sensitivity to plaintext and random distribution of ciphertext.
Research on the application of Decision Tree and Random Forest Algorithm in the main transformer fault evaluation
Authors: Zhang Chenmeng , Hu Can , Xie Shijun , Cao Shuping 
Published: January 2021

Abstract
The detection and monitoring methods of power equipment are relatively complex. The analysis of a large amount of data obtained from detection and monitoring and the development of data recording methods make it possible to obtain higher-dimensional power data. If we adopt appropriate data analysis method to the data sets, we can better get the potential laws and value of power data. In this paper, we took various basic monitoring data and faults records of the 110kV main transformers into consideration, and the grid-equipment-environment data was fused. Based on the fused data, we used the decision tree and random forest algorithm to evaluate the main transformers’ defects and faults. The evaluation results of the two algorithms were obtained and compared, which proved the effectiveness of the fault evaluation algorithm and selected a more accurate fault evaluation algorithm. This paper provides new ideas for smart fault detection for power grid, and provides a reference for a more in-depth evaluation of power grid equipment.
Analysis and Risk Assessment of Heavy Metal Residues in Fish in Songhua River Basin
Authors: Chen Xin , Liu Yun , Jia Liming , Zhao Yue , Zhao Ran , Dong Yingli 
Published: January 2021

Abstract
Thirty samples of crucian carp and carp are collected in upstream pine forest, midstream Dadingzi mountain and downstream Jiamusi section in the main stream of Songhua river. The ICP method is used to test heavy metals content of the fish. The exposure health risks of exposed way of edible fish in the Songhua River is assessed by exposure to the health risk assessment model. The results show that the noncarcinogenic target risk quotient (THQ) of each heavy metals is less than 1. The biggest heavy metal of the noncarcinogenic risk is As. From high to low in the order, the THQ is As>Cu>Mn>Pb>Cd. Composite exposure non carcinogenic hazard index (HIsF) is 0.18∼0.23. As of fish exposed can cause the evident in the risk of cancer, TR is 2.89×10−5∼6.78×10−5.
Yuetian soil conditioner can enhance the output, decrease the concentration of heavy metals of areca taro and reduce soil acidity
Authors: Huang Dongfeng , Luo Tao 
Published: January 2021

Abstract
The influences of using several dosages of Yuetian soil conditioner on the output, heavy metal concentration of areca taro and soil basic fertility characteristics were studied by field plot experiment. Outcomes indicated that the output of areca taro enhanced by 6.2%∼12.8%, As concentration decreased by 28.9%∼40.0%, Hg concentration decreased by 28.6%∼50.0%, soil pH value enhanced by 4.0%∼34.9%, exchangeable acid decreased by 10.5%∼95.2%, available phosphorus decreased by 36.4%∼54.6%, and the concentration of organic matter, hydrolytic nitrogen and available K was different, but the concentration of Pb, Cd and Cr enhanced, and the concentration of Hg and As was different.
Rainfall forecast of Tongjiqiao reservoir
Authors: Sun Leilei , Guo Huifang 
Published: January 2021

Abstract
The dam site of Tongjiqiao reservoir is located in Puyang River, a tributary of Qiantang River. Tongjiqiao reservoir is the backbone flood control water conservancy project in Puyang River Basin and an important source of ecological and environmental protection tourism. It is also a reserve water source protection area for the future development of Pujiang County. The reservoir not only provides most of the industrial and agricultural production and domestic water for several major towns (streets) and economic development zones of Pujiang County, but also undertakes the ecological water supply task of Puyang river. For a long time, Tongjiqiao reservoir has played an important role in the economic and social development of Pujiang County. In this paper, the model of adaptive neural fuzzy inference system is used to predict the rainfall of Tongjiqiao reservoir. The results show that the rainfall of the reservoir area is in the average level of many years from 2020 to 2025.
Research on the Integrated Support of Equipment under Green Ecological Concept
Authors: Yang Lili , Xuan Zhaolong , Liu Tielin , Zhang Xiaoliang , Huang Xinxin 
Published: January 2021

Abstract
In the context of the country’s great efforts to build a socialist ecological development, the weaponry and equipment, as an important part of the development of the national defense, are becoming more and more important in the direction of green ecological environment. The article analysed and discussed several key ways of implementing green integrated support of equipment-----green design for equipment, green manufacturing for equipment, and green maintenance for equipment, which promotes coordinated and continuous development of military, environment and economy on the basis of expounding the connotation of green ecological environment and equipment integrated support.
Research on conflict handling mechanism of EPC project based on partnering mode
Authors: Cheng Fan , Yin Yilin 
Published: January 2021

Abstract
The concept of win-win cooperation emphasized by partnering mode can promote all parties of the project to achieve win-win, and can effectively reduce the conflict and controversy caused by the confusion of work interface, poor communication and coordination and other issues in the project. In this study, first of all, rough set method in conflict analysis theory is used to reflect the conflict degree of each participant on a certain problem and the main conflicts in the problem. Then, combined with the conflict level division and conflict ejection mechanism in partnering mode, a conflict handling mechanism of EPC project based on partnering mode is constructed, which provides a theoretical basis for conflict handling of EPC project According to and practical guidance.
Application of a novel phosphonic-functionalized polyether imidazolium ionic liquid in hydroformylation of 1-octene
Authors: Yao Jiajun , Ma Qingqing , Jin Xin 
Published: January 2021

Abstract
In this paper, based on the concept of integration of phosphine ligands and ionic liquids, a new phosphine-functionalized polyether imidazolium ionic liquid [Ph(EO)16MIM]3[P(m-C6H4SO3)3] was designed and synthesized. The phosphine-functionalized ionic liquids have the characteristics of both phosphine ligands and ionic liquids. They can be used not only as ligands to complex metal rhodium, but also as catalyst supports. Based on this unique property, we constructed a Rh-[Ph(EO)16MIM]3[P(m-C6H4SO3)3] biphasic catalytic system to catalyze the hydroformylation of 1-octene. The results show that the catalyst is not only easy to separate and recover, but also can obtain 2717 h−1 TOF value within 0.5 h. When the catalyst was reused for 15 times, there was no obvious deactivation of the catalyst, and the total conversion number TTON was as high as 43288.
Influence of Yuetian soil conditioner on output, heavy metal concentration and soil improvement of rice
Authors: Huang Dongfeng , Luo Tao 
Published: January 2021

Abstract
A field experiment was conducted to test the influences of several doses of Yuetian brand soil conditioner on dry matter output and heavy metal concentration of rice, and the influence of basic physical and chemical properties of soil. The outcomes indicated that the dry matter output of rice was increased by 1.29%∼23.42% by using different dosage of Yuetian brand soil conditioner compared with no soil conditioner treatment (treatment 1). The effect of Treatment 5 (1875kg/ha) was better on enhancing dry matter output of rice. And they could reduce Cd and Pb concentration of rice by 17.32%∼60.17% and 11.47%∼64.68%, respectively. Ttreatment 5 and 6 had a better effect on reducing heavy metal concentration in rice, and could increase the pH of the soil by 4.7%∼37.2% and decrease the exchangeable acid (latent acid) by 3.5%∼55.9% , the concentrations of soil effective Cd and Pb were reduced by 9.28%∼49.48% and 8.34%∼24.40% , respectively.
Enhancement characteristics of laser ultrasonic basin-type insulator based on carbon nanocomposites
Authors: Lu Shan , Jia Dafei , Wu Haifei , Fan Jingjing , Xia Hui 
Published: January 2021

Abstract
Laser ultrasonic technology has been widely used in the field of NDT due to its advantages of non-contact and high resolution. The sensitivity of laser ultrasonic detection signal is not only related to laser excitation parameters, but also to the thermal absorption of the target. Therefore, once the measured target is determined, the sensitivity of laser ultrasonic detection based on thermoelastic effect is limited by the damage threshold of the measured target. In order to improve the sensitivity of the detection signal under the damage threshold, it is a good choice to add a layer of enhanced medium with high photoacoustic conversion efficiency on the surface of the laser target material. Based on this, a method based on CB(carbon black)-PDMS composite film was proposed to enhance the sensitivity of detection signal.
Experimental Study of Micro-electrolytic Technology on Ship Sewage Treatment
Authors: Tian Yihe , Guan Di , Wang Weijie , Zheng Jixin 
Published: January 2021

Abstract
Aims to remove oil and anionic surfactants in domestic wastewater on the ship, the micro-electrolysis treatment with fillers was applied in this paper. The effect of the system on the removal efficiency of oil and surfactants was studied, and the optimal operating conditions were determined. The results show that the removal rate of oil and LAS is 81.2% and 77.5% with safe effluent quality under the optimal working conditions.
Analysis and Research of uncertain radius in constructing geo - spatial buffer
Authors: Xu Ya-Nan , Qin Jianxin , Zhou Yunqi , Wu Tao 
Published: January 2021

Abstract
Buffer analysis is one of the most important functions in GIS spatial analysis, which is used to establish the scope of influence around spatial entities. The conventional buffer radius is fixed. However, in practical situations, the buffer radius should be dynamically adjusted by considering the specific environment of the space entity such as nature and socio-economy condition. Therefore it is able to achieve accurate and scientific spatial analysis, which aims to provide efficient decision-making services and intellectual support for the construction of the social economy and the ecological civilization. In this paper, based on analysis of the shortcomings of conventional buffer, several special buffers are discussed and the uncertain buffer radius is calculated under different conditions. Finally, an example is harnessed to illustrate the existence of uncertain buffer radius.
Passive control of a class of fuzzy time-delay systems
Authors: Wang Yanhua , Wang Zhanli , Zheng Liwen 
Published: January 2021

Abstract
In this paper, it is studied the passive control of a class of fuzzy systems with state uncertainty and time-delay. First, a class of nonlinear systems is described by using T-S fuzzy model with uncertain items and time-delay ; Secondly, by using the linear matrix inequality technique(LMI) and designing the state feedback controller, we can obtain the feedback gain matrix , the robust stability of the closed-loop system is achieved by using Lyapunov’s stability theory, at the same time, it is realized the sufficient conditions for passive control of the system. Finally, the feasibility and validity of the results are verified by simulation examples.
Notch correction strategy of LCL-type grid-connected inverters based on GCFAD
Authors: Zhang Junqi , Feng Tingting , Tang Libo 
Published: January 2021

Abstract
Considering the control delay, grid-current-feedback-active-damping(GCFAD) method can ensure the stability of the system through the reasonable design of parameters, but when the grid impedance changes, the system may be unstable because the LCL resonance peak cannot be effectively suppressed. In this paper, a notch correction strategy is proposed. The amplitude drop characteristic of the notch filter is used to effectively suppress the LCL resonance peak in this paper, so as to ensure that the system has sufficient amplitude margin when the grid impedance changes. The robustness of the system is greatly improved to the grid impedance when the GCFAD method is adopted. Finally, the simulation model verifies the effectiveness of the proposed strategy.