bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Improved Tracking Algorithm Based on MDNet
Authors: Wang Biyan , Guo Baolong , Li Qianying , Liu Runzhi 
Published: September 2019

Abstract
The MDNet algorithm works well on tracking problems of the video sequence, but the speed is very slow. We have made some improvements to accelerate the process of feature extraction. It enhances the expressive ability of the feature map by removing the max pooling layer and using the method of expanding convolution to increase the receptive field of each point on the feature map. In addition, MDNet is building on CNN, and there are problems that similar targets have a large interference to the results. To address this problem, We use RNN to capture the long-term dependence of the target before and after the target data in the sequence data, and introduce the RNN to model the structure information of the target object, and then fuse the RNN feature and CNN feature of the tracked target object. In addition, another new loss term is introduced to make the targets in different domains away from each other in the shared feature space, thereby improving the algorithm’s ability to discriminate similar interferers. Compared with MDNet, our improved algorithm is much faster and the accuracy is improved.
A Kind of Static Software Birthmark Based on Control Flow
Authors: Zhao Yalin , Lei Juchao 
Published: September 2019

Abstract
In traditional static k-gram birthmark algorithm, the result of plagiarism detection is inaccurate. It is a new method for plagiarism detection that using the software birthmark based on program control flow in this paper. First, it is used to the result of static that analysis of the Java program as meta information, analyze meta information to get byte stream instruction in method. Then, a byte instruction stream in the method to get the control flow structure of the program has been analyzed, and replaced the external references with external control flow structures, using this control flow structure as a software birthmark. Finally, it is calculated that the similarity between two birthmarks by VF2 algorithm, thus determining whether there is plagiarism between the two programs. It is shows that birthmark which presented in this paper are more credible than traditional SKB birthmarks in experimental results.
On-Line Parameter Identification of a Squirrel Cage Induction Motor
Authors: Li Shanshan , Zhu Ninghui , Wei Biao , Fu Yunji 
Published: September 2019

Abstract
Based on the principle of coordinate transformation, a mathematical model of induction motors in the three-phase stationary coordinate system was transformed to that in the synchronous rotating coordinate system. For motors with low-speed rotors, the multi-variable, high-order, strong-coupling and nonlinear equation of motors was further transformed to a linear equation. However, it was found difficult to solve the deduced linear equation through the method of least squares due to its high singularity. The steady-state stator resistance could be predetermined by temperature revision on the stator resistant in the motor nameplate. Identification of four motor parameters (Ls
,M, Rr
, Lr
) was followed by the recursive least-squares method. Simulations of motor parameter estimation were carried out in Simulink of Matlab. The recursive least-squares method was used to deal with the measured data. The results demonstrate that the real-time electrical parameters (Ls
, σ, Tr
) can be accurately predicted. Given the assumption of Ls
= Lr
in the classical motor theory, the other three electrical parameters (M, Rr
, Lr
) can also be identified. The identification of these parameters is of great importance for the analysis, control and fault diagnosis of induction motors.
A Pilot Study of Chaos Criteria with Hilbert Transform and Mutual Information
Authors: Chen Yahui , Zhou Yan , Li Wenshi 
Published: September 2019

Abstract
Chaos feature criteria tree has many fruits with geometric maps and calculated values. To easily understand how to study chaos identification, we propose one new learning combination solution based on Hilbert transform (HT) and mutual information (MI). The most important coding probe (x-axis) used the HT of locked uniformly distributed random number (LUSRN), so far the y-axis in contrast standard map points to LUDRN. The measure between contrast standard map and unknown map (normalized test data, HT of LUSRN) used MI values. The test cases cover five chaos equations and eighteen quasi-period functions. The results show in statistics that our new maps and corresponding MI values can classify three kinds of signals with periodic, chaotic and random states. And this work may promote rapid growth of an apple embedded in novel chaos criteria.
Asynchronous Advantage Actor-Critic Algorithms Based on Residual Networks
Authors: Tang Lili 
Published: September 2019

Abstract
Deep reinforcement learning is one of the fastest-growing technologies in machine learning. The Asynchronous Advantage Actor-Critic algorithm completely uses the actor-critic framework and utilizes the idea of asynchronous training, which greatly speeds up the training and improves performance. Although A3C algorithm puts actor-critic into multiple threads to train synchronously, effectively utilizes computer resources and improves training effectiveness, it is still difficult to train in deep neural network. Deep networks have proved to be capable of extending to thousands of layers and still have improved performance. However, every one percent increase in accuracy almost doubles the cost of layers, so it is not easy for A3C to train both actor and critic networks. In response to this problem, we innovatively utilize the residual network to apply to the asynchronous advantage actor-critic algorithm and has achieved improvement greatly in the inverted pendulum problem.
Research on the Effects of Machining Parameters on the Surface Location Error for a Milling Process
Authors: Deng Congying , Miao Jianguo , Zhang Bin , Feng Yi , Yang Kai 
Published: September 2019

Abstract
The surface location error is an inevitable phenomenon which is caused by the forced vibration under a stable machining process. The surface location error (SLE) is dependent on the machining parameters. Therefore, this paper proposes a method to study the effect of each machining parameter on the surface location error. An algorithm based on the cutting force dynamic model is proposed to predict the SLE in frequency domain. And then a case study is performed on the milling process of a real vertical machining center. The variation ranges of the spindle speed, axial cutting depth, radial cutting depth and feed rate per tooth are first determined. Eight specific values of each machining parameter is selected, and an orthogonal experiment table is established to arrange the schemes to predict the corresponding SLEs. Then the range analysis is used to analyse the values of the machining parameters and the obtained SLEs. Results show that the spindle speed is the most dominant factor affecting the SLE and an optimal machining parameters combination related to a minimum SLE is determined based on the optimal level of each machining parameter.
Flow Control and Optimization Technologies of Information System
Authors: Li Xianyu , Wang Hua , Chen Zhiyuan , Liu Weina 
Published: September 2019

Abstract
On the basis the description of information flow connotation, the paper describes the information flow system frame, proposes the flow construction method and information flow utilization mode, puts forward flow modelling technology, semantic comprehension technology, data excavating technology and process optimization technology, and presents related test analysis and flow improvement of the information system, so as to further strengthen policy decision function, and enhance the timeliness and accuracy of situation disposition and information processing of information system.
An Anonymous Network Website Fingerprinting Attack Method Based on Wavelet Transformation
Authors: Lai Qi , Ling Jie 
Published: September 2019

Abstract
The anonymous network in protecting user privacy information, but also for the use of criminals, for its illegal acts, and increase the cover monitoring, tracking and obstacle of the government organs forensics, Aiming at the problem of anonymous network, this paper proposes a website fingerprinting attack method for TOR anonymous network. Wavelet transform is introduced to deal with the traffic generated by visiting the website. SVM algorithm is used to learn and generate classifiers, establish fingerprint feature library, and then compare the data generated by the target visiting website with the feature library to confirm its visiting website. In this way, the experimental results show that the average recognition accuracy of target visited websites is 96.7% under all known features of websites, which is superior to literature [17].
Identifying Behavioural Intents in a Complex Search Process Management System
Authors: Zhu Mengliang , Xu Ruikang , Sun Mingzhen , Zhang Yin 
Published: September 2019

Abstract
Understanding search intents is essential for improving search results and query recommendations. Currently, most search intent identification methods work on plain form search logs consisting of queries and clicks. Meanwhile, new search tools are being introduced by the CHI/HCI communities, allowing users to perform more types of behaviors than querying and clicking, and generating rich form search logs with more information than that in plain form search logs. In this paper, we seek to identify search intents by considering various types of behaviors performed in a complex search process management system. We use random forest to identify search intents based on the behaviors performed. Experimental results show that search intents could be identified by analyzing search behaviors, and certain types of behaviors can be good indicators of search intents.
Application Status of Intelligent CAD in Mechanical Manufacturing
Authors: Huang Jiangge , Tao Bo , Li Gongfa 
Published: September 2019

Abstract
Machinery manufacturing takes up a very heavy proportion in the national economy, which is the core industry as well as the cornerstone of a country’s national economy. Mechanical manufacturing has been slowed down because the manufacturing process is complex. With the development of social economy, and the advent of the era of science and technology, the production manufacturing technology level is increased sharply in order to promote the development of China’s industrialization process, gradually in the mechanical manufacturing will be tedious manual production mode transformation to the intelligent technology development, the automation and intelligent technology applications, the application of intelligent CAD is one of them. The application of intelligent CAD technology in machinery manufacturing is conducive to improve the development level of machinery manufacturing industry and it is an important measure for the transformation of industrial production towards digitalization and modernization. This paper analyses the application status of intelligent CAD technology in mechanical manufacturing and discusses its future development trend Introduction.
Research Status and Trend of Fault Diagnosis Based on Deep Belief Network
Authors: Xiong Bitao , Tao Bo , Li Gongfa 
Published: September 2019

AbstractModern industrial systems are moving towards large-scale, complex, and high-speed. It is difficult to solve a series of technical problems that rely on traditional fault feature extraction methods. Since the concept of deep learning has been proposed, it has shown obvious advantages in many aspects. It includes feature extraction and pattern recognition. Therefore, many scholars have conducted deep learning to solve the problems of complex industrial system fault diagnosis. The deep belief network is the typical deep learning technologies in the field of control. This paper mainly introduces the deep belief network and describes its main ideas and methods. Finally, the paper summarizes the problems faced by the current deep belief network in the area of fault diagnosis and the future research direction.
A Novel Similarity Search Approach for Streaming Time Series
Authors: Ding Yiming , Luo Wei , Zhao Yufei , Li Zhen , Zhan Peng , Li Xueqing 
Published: September 2019

Abstract
Time series similarity search has been widely used in many applications, such as financial data analysis, meteorological data forecasting, and multimedia data retrieval. The original task of this research was to find time series in a database similar to the query sequence, where both the results and the query sequence are static. However, along with the arrival of Industry 4.0 era, a large number of detecting instruments in various fields have produced a large amount of time series stream data. The new challenges for Similarity-based time series retrieval can be attributed as one-pass search and real time response. In this paper, we propose a novel multi-resolution search scheme to find a set of sequences similar to the query sequence in streaming time series efficiently and exactly. The scheme performs multi-resolution filtering on the raw data, and most dissimilar sequences can be filtered out at a lower level to avoid unnecessary computation and to improve the search efficiency. Extensive experiments on different kinds of typical time series datasets have been conducted to demonstrate the superiorities of our method.
Use Big Data + Internet Thinking to Solve the Problem of Data Governance
Authors: Zhou Guixian , Chen Kaijian 
Published: September 2019

Abstract
Nowadays, with the development of cloud computing, Internet of things and mobile Internet, big data is exerting a huge influence on the global economy and society. The era of big data has brought new challenges to social governance, requiring us to grasp the characteristics of social governance in the era of big data, change the research methods of social governance, and meet the needs of social governance in the era of big data. Government affairs open service platform to integrate distributed and heterogeneous system of information resources, eliminate the “information island” phenomenon, through the open service platform, service background, e-government service management platform, monitoring platform four subsystems to achieve between different institutions, different application system and database based on the different transmission protocol of data exchange, information sharing and business collaboration, thus to provide good data to support the government and the enterprise information construction environment.
Implementation of High Order QAM Modulation on SDR
Authors: Wu Hao , Lu Min , Li Yan , Liu Mengrong 
Published: September 2019

Abstract
Nowadays, SDR (software-defined radio) has increasingly occupied a place in scientific research and teaching with its powerful signal processing capability and custom ability. XSRP is a development platform which uses an SDR architecture. In this paper, we develop a wireless real-time audio transmission system with high order modulation (64QAM) based on XSRP platform. We use LabVIEW and MATLAB to write the program’s overall framework and functions. We also analyse the performance of different modulation modes by comparing the constellations and waveforms of the transmitter and receiver under the real situation. The results show that high order QAM modulation achieves a good balance between efficiency and quality.
Adaptive RSA Encryption Algorithm for Smart Grid
Authors: Wang Fang , Wang Zhenyu , Zhu Yan 
Published: September 2019

Abstract
Information security has been paid more and more attention as it is a high-weight factor that affects many aspects in our life. Many technologies have been introduced to improve information security. Encryption algorithm is one of the most frequently used method. There are many encryption algorithms. RSA algorithm, which uses asymmetric encryption method, is a secure encryption algorithms. RSA’s encryption effect is pretty good due to difficulty in cracking its private key. Smart grid is the upgrade of power grid, which is based on integrated, high-speed two-way communication network. In smart grid, there are lots of data to be transferred along the network. In order to ensure that the data are not stolen or tampered with, it is necessary to encrypt the data during transferring. However, it is ineffective to use conventional RSA algorithm directly in smart grid. To solve the problem, we propose an adaptive RSA algorithm to generate primes, which modifies the application scope of RSA algorithm, so that the algorithm can be successfully applied in smart grid. According to the time limit of the encryption algorithm, the prime number is generated adaptively, so that the encryption time of the algorithm is reasonably controlled. The data is encrypted by generating the public key and the private key used for encryption through the generated prime number. The experiments verified the effectiveness of the algorithm.
Search Engine and Performance Optimization of Drupal-based Websites
Authors: Song Jie , Du Hui , Huang Qi 
Published: September 2019

Abstract
In view of incomplete and in-depth of research on search engine and performance optimization of Drupal-based websites, using the method of documentation, the common solutions are summarized. Their implementation methods are described and put into practice. Reference and guidance are provided for the search engine and performance optimization of Drupal-based websites.
Development Status of Equipment Testability Verification Technology
Authors: Luo Jian-Hua , Wang Qing-Shu , Li Hua 
Published: September 2019

Abstract
Testability verification of equipment refers to the test and evaluation for testing whether the testability of equipment given by design and manufacture meets the specified testability requirements. Testability verification can lay a theoretical and technical foundation for the testability and maintainability transformation of active equipment, and provide a development platform for the development of equipment maintenance support equipment and system of grass-roots units. Its research work has very important military and economic significance for improving the overall level of information and intelligence of equipment and the security of use. This paper summarizes the development status of testability test and verification technology of equipment at home and abroad, analyses the key technologies of testability verification, and points out the key and difficult problems to be solved urgently at present. Finally, based on the comprehensive analysis of the current testability physical verification and non-physical verification technology schemes, some suggestions are given for further research and development of testability verification technology schemes.
An overall scheme design and application of a wheeled robot for martial arts challenge competition
Authors: Huang Shanshan 
Published: September 2019

Abstract
With the rapid development of artificial intelligence, driven by the government’s strong support and the transformation and upgrading of traditional industries, the research on robot continues to gain popularity, and robot competitions are attracting more and more attention. In this study, an overall scheme design of a wheeled robot for martial arts challenge competition is introduced. It had been successfully applied in the robot competition of colleges and universities in Jilin province of China in 2018 and the robot fighting competition of the world in 2018. The author achieved good ranks. This shows that the scheme has strong operability.
Catenary Fault Identification Based on PSO-ELM
Authors: Yi Lingzhi , Zhao Jian , Yu Wenxin , Liu Yue , Yi Chuyang , Jiang Dan 
Published: September 2019

Abstract
Catenary has been exposed outdoors for a long term, and its failure rate is very high, which has seriously affected the operation and development of traction power supply system. Due to the problems of long detection time, backward detection means and influenced by human factors in traditional catenary fault identification methods, this paper proposed a fault identification method based on PSO-ELM. This method could reduce the hidden layer nodes of traditional ELM and improve the accuracy of identification. In this paper, this method was compared with ELM, GA-ELM, BP, GA-BP and PSO-BP. A sample of catenary detection data of a power supply section in 2018 was selected. The results show that PSO-ELM is an efficient method for the fault identification of catenary.
Optimal Trajectory Planning of Eye-head Gaze Shifts for Bionic Robot Vision System on Orchard Environment Perception
Authors: Ma Jianping , Cheng Yuanhao , Wang Sun’an 
Published: September 2019

Abstract
To make orchard robots obtain environmental information quickly and smoothly, this paper studies the neuro-mechanism of primates’ gaze shifts. Meanwhile, according to the optimal control theory, this paper considers time and energy as factors of formulating cost function and then analyses kinematic relationship between eye and head during gaze shifts to find constraint conditions. Solving the two-point boundary value differential equations of optimal control, this paper can extract the best control signal of coordinated eye and head movements. By building a multi-degree-of-freedom robot vision system corresponding to the biological model, this paper simulates primates’ gaze shifts and verifies the feasibility and validity of the method proposed.
The Application of Artificial Intelligence in Electronic Commerce
Authors: Song Xia , Yang Shiqi , Huang Ziqing , Huang Tao 
Published: September 2019

Abstract
With the rapid development of science and technology and economic society, the application of artificial intelligence(AI) is more and more common, its development has a profound impact on our work and lifestyle. In the field of e-commerce, AI technology has also been well applied and achieved good results. AI has become an important driving force for the development of e-commerce. This paper simply described the e-commerce development situation and prospects of AI technology, analyzes the present situation of the application of AI technology in the field of e-commerce, mainly study and discuss in detail from the aspect of assistant of AI, intelligent logistics, recommendation engine and the optimal pricing application through the research of e-commerce intelligent operation instance - Baidu take-away, probes into the important impact and great significance on the e-commerce development of artificial intelligence.
Research on Small Sample Image Recognition Based on Transfer Learning
Authors: Yang Guhai , Tang Baihui , Cao Sanxing 
Published: September 2019

Abstract
With the improvement of electronic hardware configuration performance, high-speed computing of large and complex data can be realized, and artificial intelligence, which requires a large amount of data calculation has been rapidly developed. Nowadays, artificial intelligence has developed rapidly in image recognition, natural language processing and speech recognition, and also has achieved good results in these areas. Among them, the convolutional neural networks plays an important role in image recognition. Some excellent convolutional neural networks such as VggNet, GoogleNet and ResNet have reached more than 90% in image recognition accuracy. But these convolutional neural network models are based on big data, consume a lot of computing time, which is very costly. Therefore, when data is limited, hardware configuration is low, and time is tight, a research on small sample image recognition based on transfer learning becomes very necessary. In this paper, the inception-V3 model is used to transfer learning. The training nodes of the model are skillfully used to train the model on the data set of ten kinds of fruits. The model is tested by the training model and good accuracy is obtained. The advantage of the experiment is that the training time is short, the required data set is small, and the image recognition accuracy is high