bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sentence Similarity Computation in Question Answering Robot
Authors: Si Shijing , Zheng Weiguo , Zhou Liuyang , Zhang Mei 
Published: July 2019

Abstract
Computing semantic similarity between sentences or texts is vital in many natural language processing (NLP) tasks such as search, query suggestion, and question answering (QA). Many methods have been developed, based on lexical matching, distributional semantics, etc. However, lexical features, like string matching, fail to capture semantic similarity. In this research, our focus lies on the implementation of distributional representations and how to tune parameters when obtaining representations of words with commonly used word embedding techniques, e.g., Word2Vec and GloVe. We conduct experiments in the setting of Chinese semantic sentence matching tasks on the finance-domain. We examine the goodness of word embedding by both the cosine similarity of semantically similar sentence pairs and semantically dissimilar pairs. Based on our experiments, Word2Vec performs better than GloVe in the sense that Chinese character embedding from Word2Vec yield larger disparity of cosine distances between similar sentence pairs and dissimilar pairs. Also we report the optimal parameters for Word2Vec continuous bag-of-word (CBOW) through our trials, with window size being 6 and embedding dimension being 400, which can be good initial values for other projects.
Big Data Technology Progress And Development Trend
Authors: Jin Wei 
Published: July 2019

Abstract
In the era of Internet+, big data technology has been widely used in all walks of life, and has achieved good application results, including university education industry. From the perspective of the overall structure, big data technology can not only maintain campus network security, but also improve the university education platform, assist students to obtain valuable information, and promote effective communication between teachers and students. This article will layer on the progress and development of big data technology, and put forward some personal opinions.
Fourier transform and correlation analysis for CSEM data processing
Authors: Li Guang , Xu Congcong , Li Jin , Mu Liangyin , Lin Huangzhou , He Jinjian , Liu Jun 
Published: July 2019

Abstract
Controlled Source Electromagnetic Method (CSEM) has the advantages of large depth of exploration and high efficiency. It has a wide range of applications in resource exploration and engineering surveys. However, CSEM data is often contaminated by strong cultural noise. In this paper, a novel method for CSEM data processing is proposed by combining the Fourier transform and correlation analysis. First, the observed data is performed by the Fourier transform, and the power-line noises are accurately removed in the frequency-domain. Second, the inverse Fourier transform is performed to the de-noised spectrum. Third, the correlations between transmitted and received data are calculated to quantitatively evaluate the data quality. Finally, high quality received data are selected by setting a proper threshold of correlation. We applied our approach to measured CSEM data. As a conclusion, the results obtained using our scheme are greatly improved over the previous.
Study on Naphthalene Sulfonic Acid Formaldehyde Condensate by Ultraviolet Absorption Spectrum
Authors: Yan-Min Zhang 
Published: July 2019

Abstract
Naphthalene sulfonic acid formaldehyde condensate is a kind of surfactant with excellent performance, which is widely used in printing, dyeing, cement, paint and other industries. There are various analytical methods for naphthalene sulfonic acid formaldehyde condensate, such as optical density analysis, electrophoresis, chromatographic analysis and spectral analysis. A series of formaldehyde condensates were synthesized from naphthalene, formaldehyde solution and concentrated sulfuric acid solution. The products were qualitatively analyzed by infrared and ultraviolet absorption spectra.
Discrete Bare Bones Particle Swarm Optimization Algorithm for Solving Multidimensional Knapsack Problem
Authors: Liu Shengjian , Yang Yan , Luo Lin 
Published: July 2019

Abstract
Aiming at the characteristics of multi-dimensional knapsack problem, the widely used bare bones particle swarm optimization algorithm is discretized, and the traditional objective function based on large penalty parameters is improved. The infeasible solution is transformed into a feasible solution by using the repair mechanism. The typical examples of 10 multi-dimensional knapsack problems are simulated and compared with four intelligent optimization algorithms. The simulation results show that the discrete bare bones particle swarm optimization algorithm has good convergence efficiency, high precision and good robustness when solving multi-dimensional knapsack problem.
Mathematical analysis for phase noise characterization of pulse modulation signal
Authors: Peng Cuiling , Chen Xiaolong , Huan Huiting , Nian Fushun , Yang Baoguo 
Published: July 2019

Abstract
Pulse modulation is of great importance in radar system. The performance of pulse modulated oscillating signal is usually characterized by its phase noise. The phase noise of pulse modulated signal can be hardly measured by phase demodulation. The correlation between the carrier and modulated signal needs to be established for the purpose of noise characterization. In this work, a mathematical form of phase noise of pulse modulated signal was proposed in the frequency domain. After pulse modulation, phase noise distribution of the oscillator shifts and superimposes upon the harmonics of the modulating pulse. Experiments were carried out to verify the phase noise property. The obtained results show that by referring to the phase noise of carrier, the phase noise measured by instrument is in good agreement with the mathematical prediction. The phase noise of pulse width modulated signal can be well depicted by the proposed mathematical form.
Cluster analysis of Xi’an restaurants by Self-organizing maps
Authors: Kong Jie , Ren Meng 
Published: July 2019

Abstract
To investigate the segmentation features of restaurants in Xi’an, China, the Self-organizing maps are applied in this study to analyse the information of online reviews obtained from Dazhong Dianping, which is a famous Chinese social network. Through the clustering and visualization performed by Self-organizing maps, 10 segments of restaurants are identified and some representative features are summarized. The findings of this study could help managers to improve restaurant competitiveness, as well as customers’ decision making.
The cross-project defect prediction based on PSO and Feature Dependent Naive Bayes
Authors: Yao Zhexi , Sun Li , Zhang Tao , Wang Jinbo 
Published: July 2019

Abstract
The software defect prediction often assumes that the software under test has rich historical information, which is a harsh condition in reality. Cross-project defect prediction can predict projects with rare historical information by using historically informative projects. The differences in software architecture and code environment pose challenges to cross-project software defect prediction. Based on the characteristics of software defect prediction sets, this paper introduces a two-stage algorithm based on particle swarm optimization algorithm and Feature Dependent Naive Bayesian classifier.
Multi Channels Data Fusion Algorithm on Quantum Genetic Algorithm for Sealed Relays
Authors: Qian Xin , Wang Shujuan , Li Chao , Wang Guotao 
Published: July 2019

Abstract
Particle Impact Noise Detection (PIND) is a screening test that must be done before the sealed relay is released. PIND signals are mostly occasional weak, which are difficult to measure and identify. In this paper, the three channel sensor is used to detect the remainder signals, and the weak signal is enhanced by weighted data fusion. For the first time, quantum genetic algorithm (QGA) is used to self-adaptively configure the weight, taking the place of arti-ficial settings. Experiments show that after data fusion, and the variance is only about 20% of the single input signal, which verifies the effectiveness of the algorithm. The computational complexity of QGA is offered.
Research on Security Protocol of RFID System Based on Public Key Cryptography
Authors: Wang Song , Zhang Bo 
Published: July 2019

Abstract
As one of the key technologies of the Internet of Things, RFID technology has increasingly become a part of people’s daily life. Because of the openness of the RFID system, its security problem becomes more and more serious. This paper improves the public key encryption authentication protocol and proposes a new protocol scheme. This scheme can provide better security authentication for the RFID system by using random number and session key, and it can satisfy the requirements of the RFID system in performance.
Research on Missile Data Security Based on Blockchain
Authors: Wang Yidong , Cong Linhu , Fang Yi , Deng Jianqiu , Chen Yuliang 
Published: July 2019

Abstract
Existing aviation missile business data records and storage have the disadvantage of being tampered with easily, being traced difficultly, and other security risks. Aiming at these problems, this paper applies blockchain technology to the data recording and storage scene of aviation missile business, carries on the network structure design, uses the current mainstream encryption algorithm and the encryption technology, constructs the block chain based aviation missile service data recording storage system, and describes the system working principle and how the system protects the data. Security analysis shows that the system can effectively protect the security record and storage of data, and lays a certain foundation for further exploring the application of blockchain in military.
Research on Intelligent Campus Monitoring Management System Based on Deep Neural Network Algorithm
Authors: Liu Xia , Wang Xuelong , Ren ChangLin 
Published: July 2019

Abstract
With the development of the economy and the advancement of science and technology, the informationization of education management has become an inevitable trend, and the construction of a intelligent campus cannot be delayed. In order to comply with the current social development, major universities have invested heavily in IoT equipment to improve the management level of the school. Based on the large number of video cameras installed in colleges and universities, this paper uses the monitoring image big data and the CNN algorithm to train a set of graphical features that are easy to manage, without adding additional hardware purchases. In addition, combined with the camera position and other information, an intelligent campus monitoring system is built to help the campus administrator to understand the people flow, traffic flow and physical condition in real time, which is convenient for enhancing the effective monitoring and management of campus crowds, environment and security.
Study on Optimization of automatic train operation based on Grey genetic algorithm
Authors: Gao Fan , Li Fan , Yu Zhe , Wang Huihui 
Published: July 2019

Abstract
The speed controller is the kernel module of Automatic Train Operation system, and is also a key core technology of the intelligent high-speed train. The research of the intelligent speed controller of ATO system is of great significance for automatic high-speed train operation. Through the analysis of the principle and function of CTCS-3 system, the scheme of adding the speed controller of ATO system in CTCS-3 system was proposed. The connection way between the speed controller of ATO system and ground equipment was designed to realize information interaction. The model of speed controller of ATO system for high-speed trains which is researched by grey system theory was used for prediction and decision making. In the grey prediction module, the metabolic GM (1,1) model was established, and the optimal strategy was generated by the multi-objective intelligent weighted grey target decision. Finally, a reasonable control strategy of train automatic operation was obtained. The optimal control strategy was got by using genetic algorithm. Designing software for the simulation test, the simulation results show that the method achieves automatic high-speed train operation under the CTCS-3+ATO system through the actual line data, and the efficiency of train operation, the energy saving index and all the performance indexes of the train were improved.
Research and Analysis in Fine-grained Sentiment of Film Reviews Based on Deep Learning
Authors: Zheng Jin , Zheng Limin , Yang Lu 
Published: July 2019

Abstract
Films are one of the main entertainment ways for people. By exploring, analyzing and summarizing the reviews that people published on the internet, audiences can make better viewing choices, while investors can get a more convenient way to understand the audience’s feedback. The text proposes a method of deep learning to perform fine-grained sentiment analysis on the film reviews, and restores the user’s real emotion as much as possible. The method first preprocesses the data, and converts the words into vectors using the Word2Vec model, then inputs the word sequence in the Long Short-Term Memory network (LSTM) to learn the semantic dependence. Finally, the logical regression classifier is used to classify. Compared with Naive Bayes (NB), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Back Propagation Neural Network (BPNN), and Convolutional Neural Network (CNN) models, the method achieves 83.6% accuracy in the binary classification, and 76.1% and 51.2% accuracy in the positive and negative fine-grained emotional classification, which has achieved the best results proved by experiments.
Sleep Quality Assessment of the Elderly Based on Intelligent Mattress Monitoring Data
Authors: Huang Yongfeng , Xiao Bo , Liang Liwei 
Published: July 2019

Abstract
Due to the special nature of the elderly in nursing homes, their sleep problems are difficult to evaluate conveniently and in a timely manner. Based on the guardian data of smart mattresses in nursing homes, according to the sleep characteristics of the elderly, combined with the opinions of medical experts, the Analytic Hierarchy Process(AHP) was used to construct the sleep evaluation model for the elderly in nursing homes. The results of sleep evaluation model is compared with the results of the professional sleep evaluation scale. The correlation coefficient between Pearson Correlation Coefficient and Spearman Correlation Coefficient is 0.930 and 0.956, respectively, The experimental results show that there is a strong correlation between the two. And consistency, proved the reliability of this model.
Multi-feature analysis fatigue driving based on Conditional Local Neural Fields algorithm detection method
Authors: Wan Yan , Liu Min , Fan Jinghua , Zhao Yingbin , Jiang Jiangpeng , Yao Li 
Published: July 2019

Abstract
In order to effectively strengthen the monitoring technology of fatigue driving and reduce the incidence of traffic accidents, this paper proposes a new method based on conditional local neural fields algorithm for comprehensive evaluation of fatigue driving state. At present, most of the fatigue driving detection algorithms are based on extracting a single characteristic index, which is strict in environmental requirements and not high in detection. In this paper, the HOG feature is combined with the CLNF algorithm to implement face detection and feature point localization. Then, the EPnP algorithm is used to estimate the head anomaly frequency based on the feature point information, and the blink frequency is calculated according to the EAR eye length aspect ratio concept according to the feature points around the eye. Finally the threshold set by the P80 fatigue detection standard in the PERCLOS method is integrated, and the distributed information fusion strategy is used for fatigue evaluation. Experimental results confirm the effectiveness of the method.
Research on of the Sausage Flavour by GC-MS and Electronic Nose
Authors: Yang Xin , Zheng Limin , Yang Lu 
Published: July 2019

Abstract
To rapidly and objectively evaluate the flavour of sausages using an electronic nose, the experiment extracted the volatile components of 6 different kinds of sausages of a certain sausages brand manufacturer and identified them using gas chromatography-mass spectrometry (GC-MS).Sensory evaluation and an electronic nose were used to evaluate the flavour attributes of sausages. Partial least squares discrimination analysis(PLS-DA) was used to identify and classify the electronic nose data of different varieties of sausages samples; The volatile components were identified by the method of variable important in the projection (VIP); The correlation between critical flavour components and the sensory attribute was established by partial least squares regression(PLSR). According to the PLS-DA results, the electronic nose has good distinguishing ability for different kinds of sausages and different production batches of the same kind of sausages; A total of 118 volatile flavour compounds were identified in sausages.; Through the method of VIP, 44 kinds of differential characteristic substances were obtained and classified by PLS-DA discriminant analysis, which was consistent with the electronic nose classification result mapping relationship; The PLSR shows that sensory attribute has a good correlation with the differential flavour components. Therefore GC-MS, electronic nose and sensory analysis can comprehensively evaluate the flavour differences of the sausages.
Design and Implementation of Oracle Database Incremental Data Capture Based on Trigger and Identification Table
Authors: Hu Qiangqiang , Gan Zhichun , Zhang Bin 
Published: July 2019

Abstract
Data synchronization technology is one of the key technologies of data storage in distributed database. At present, it is an effective method to achieve data synchronization between source database and target database by capturing incremental data and transferring incremental files. Based on the research of Oracle database and the analysis of commonly using incremental data capture methods, this paper designed DML trigger and incremental data identification table to store incremental identification data in the identification table, and generated incremental XML files for network transmission according to the identification table. Finally, the feasibility of this method was tested. Tests showed that the method was reliable and stable, and could be applied to data synchronization in distributed databases.
Research on the Design of Cloud Computing Platform in Intelligent Campus
Authors: Zijiao Tang 
Published: July 2019

Abstract
Constructing intelligent campus is the inevitable trend of educational informationization development. With the development of technology and the deepening of application, users demand a more humane and intelligent user experience, and put forward new functional requirements for the construction of intelligent campus. The construction of cloud-based IT system platform and its application mode can solve the above problems fundamentally, so as to promote the leap-forward development of educational informationization construction.
A Signal Processing Algorithm Proposed for OFDR Distributed Sensing System to Enhance Its Performance
Authors: Li Bingjian , Cui Jiwen , Zhang Xuping , Dang Hong , Sun Xun , Jiang Dong , Feng Kunpeng 
Published: July 2019

Abstract
A novel OFDR processing algorithm is proposed to improve the measurable range. The high local similarity found between the reference and measurement Rayleigh scattering spectrum (ReS and MeS). The spectrum shift of the Rayleigh backscatter which is the function of strain is measured using an improved optical frequency-domain reflectometry (OFDR). This method is improved by matching local ReS on MeS rather than a direct cross-correlation between whole ReS and MeS in conventional OFDR methods. By this method, a larger measurable range (0∼3000µε) OFDR method with a high level spatial resolution (3mm gauge) is experimentally achieved comparing to conventional OFDR methods.
Anti-short girth serial update decoding algorithm of GF(q) LDPC codes
Authors: Chen Xin , Li Bo , Chen Yanbin 
Published: July 2019

Abstract
A serial Fast Fourier Transform Belief Propagation (FFT-BP) algorithm with low complexity of non-binary LDPC codes decoding is presented in this paper to reduce the effects of short girth. During iteration, part of the variable nodes with short girths will just send messages to its neighbor, which are in the same short girth and avoid the messages from them. In the next iteration decoding, this part of the nodes updates and the newly updated node with sort girth stops updating. Simulations show that the proposed algorithm achieves a better gain to the standard algorithm and reduces complexity at the same time.
Design and optimization of automatic conveying equipment for cargo bags of cargo spacecraft
Authors: Hailin Dai , Ruizhao Du , Weifeng Yuan , wei Wang , dong Li , qian Zhao 
Published: July 2019

Abstract
Cargo transportation equipment is commonly used for ground loading in aerospace. Taking flexible cargo bags as a transport carriers and taking a cargo ship hatch as the target container, a kind of cargo bag transportation system is designed according to the transportation process and function requirements. On the basis of the analysis of structure and working procedure, the working principle of the mechanical subsystem as well as the structure design of key components is proposed in detail. To improve the performance of support plate’s stiffness, a topological optimization is implemented and the optimized result is hence achieved. Finite element simulation shows that the performance of the stiffness is improved significantly. The approach presented in this research benefits the design of cargo transportation equipment.
A quantitative evaluation method of aircraft wire performance based on infrared characteristic
Authors: Yu Xiangyang , Yao Linghong , Yu Shoumiao , Yu Chunfeng , Aiming He 
Published: July 2019

Abstract
As the “neural network” of airborne electrical system, the working state of aircraft conductor directly determines the reliability of the system platform. By the analysis of the performance degradation mechanism based on the thermal state model, it is concluded that local thermal stress is the common cause of apparent failure. The rated stable temperature rise of the wire is related to the working current value and the performance of insulating materials. The wiring mode is the actual influencing factor that determines the heat dissipation coefficient and surface area of the conductor. By analyzing the infrared characteristics of different wiring methods, a method is proposed to obtain the surface temperature spectrum to determine the thermal state. The relatively stable temperature rise and overflow rate are taken as the characteristic parameters, which can more accurately describe the sensitivity of wiring methods to thermal factors and realize qualitative analysis and quantitative evaluation. The feasibility of applying thermal imaging technology to the performance evaluation of aircraft electrical circuits is verified, and it can also provide reference for the active prevention and online diagnosis of line faults.