bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Integrated Safety and Formal Analysis for Aircraft Landing System Based on SysML
Authors: Yuan Yuan , Jiao Jian , Wei Mengwei 
Published: November 2020

Abstract
The integration and interaction of multiple factors in large-scale system such as aircraft is the main reason of safety problem. For example, the aircraft can be affected by a variety of interactive factors due to changes in pilot conditions, avionics equipment and environmental state during flight. Aiming at the process of carrier aircraft landing, this paper proposes a formal modeling method based on System Modeling Language (SysML) to describe and analyze the safety of system. Firstly, the method based on SysML is detailed to model the structural and behavioural aspects, relying on the analysis of mission and/or behavior process. Then, the integrated method of SysML and Simulink, using the TGG method, is adopted to facilitate the analysis of the behavior processes. Finally, the attitude control during the aircraft landing process is taken as an example to assess the deviation and the dangerous time variation of the system in different disturbance degrees, which will help to make a better safety strategy.
Design of Power Grid Cyber Security Framework Based on Whole Life Cycle Management
Authors: He Jindong , Wu Dan , Zhao Zhichao , Guo Qian 
Published: November 2020

Abstract
The whole process security of power information system is the key to make power grid operation safe and stable. Firstly, the concept and characteristics of whole life cycle management (WLCM) are summarized by this paper systematically. Secondly, the power network security architecture based on full life cycle security management is constructed, which is designed to protect the cyber security of power grid from three aspects: control flow, technical support system and mechanism guarantee system. Thirdly, the cyber security’s management and control flow of power grid, the technical support system of power grid cyber security (PGIS) and the mechanism guarantee system based on life cycle management are proposed. And the control flow, technical support and guarantee mechanism were designed in detail. Finally, the method proposed in this paper is carried out in a provincial power-grid company. The results show that this method can significantly reduce the power network security risk and improve the power grid network security level, which is of great significance to the operation safety of the power grid and has strong engineering application value.
Sensor Diagnosis System for Sleep
Authors: Chi Xiongfei 
Published: November 2020

Abstract
The cloud-computing-dirven and fog-computing-dirven mode have further inspired the studies of preventive medicine. If the database of physicians’ recorded clinical cognitive diagnosis can be smartly utilized in the Internet of Things( IoT) technologies for AI monitoring of sleep quality and disease risks prediction, then the preliminary diagnostic data provided by such terminal sleeping diagnosis device might be used for prevention of diseases at early-stage and, therefore, to greatly reduce medical cost, to increase accessibility of reliable medical services and to further reduce medical risk. However, the diagnostic big data is almost missing in current e-medical system. Therefore, a wearable smart sensor diagnosis system for sleeping patients is proposed in this article. Within the diagnosis system, smart devices for brain, nose, heart, lung and legs are included. All detected data is uploaded to the user’s mobile APP for preliminary comprehensive diagnosis calculation, which is called fog calculation. The refined data provided by the APP of sleeping sensor system can cover a large proportion of physicians’ cognition of each patients’ real conditions. Refined data, which has been removed redundant data by fog calculation, is uploaded to big data cloud for accurate diagnosis and treatment. The sleeping diagnosis big data, uploaded by sensor system perhaps reflected the values of the well-linked text information produced by a combined database of online and offline medical records.
Design and Implementation of Carrier Detection System Based on FPGA
Authors: Zhang Xian , Qu Taiguo , Liu Yiwen , Yin Dong , Deng Shaowei 
Published: November 2020

Abstract
In order to better monitor and manage the signal transmission in the communication system and base station, and carrier detection is more effective. This paper designs a carrier(Carrier frequency) detection system based on FPGA, including system design requirements, FPGA selection, system framework design, carrier detection method design and so on. The performance indexes of the system are tested, such as carrier frequency range, carrier search time, carrier detection number and CPU consumption rate. The system has the advantages of high flexibility and good portability, and has a good application prospect in communication system, base station and other equipment.
Safety Monitoring System Design of Cold Storage Based on Single Chip Microcomputer
Authors: Chu Zheyu , Tan Chao , Tang Xiuying , Cheng Bin 
Published: November 2020

Abstract
In order to solve the rising labor cost of cold storage management in China, and to improve the safety factor of cold storage, this paper designs a simple cold storage safety monitoring system. It is mainly to reflect the real-time monitoring information in the cold storage to the central background for unified processing, which not only reduces the harmful operations in the cold storage to save labor costs, but also improves the safety factor in the cold storage to reduce property losses. The monitoring system is fully automatic, which greatly reduces the staff’s effort in cold storage management.
Calibration Scheme for Portable Retroreflectometers of Road Traffic Signs
Authors: He Huayang , Su Wenying , Han Xiaokun , Wang Rui 
Published: November 2020

Abstract
Portable retroreflectometers are widely used for engineering measurements and are equipped with a set of work plates that are used to fit fitting curves and switch the working curve in the intrinsic software (self-calibration). The measuring principle employed is the substitution method. Therefore, the accuracy of the work plate values and curve-fitting ability of the internal software are important factors related to the accuracy of the instrument’s measurement results. A calibration scheme for portable retroreflectometers is proposed in this paper. This scheme not only considers calibration in the laboratory, but also on-site measurements. The work plate values can be obtained by a standard retroreflection measurement system, or by a matching portable retroreflectometer. When the work plate values are obtained through the matching instrument, a set of reference plate values must be obtained first. The reference plates, the color and coefficients of retroreflection of which are similar to those of the work plates, were calibrated by the standard retroreflection measurement system using the direct illuminance method. The reference plates were used to adjust the fitting curve in the internal software of the instrument. The work plates were then measured by the matching instrument to obtain a set of work plate values. The reference plates were measured by a self-calibration portable retroreflectometer, and the relative error between the instrument’s results and reference values was calculated.
Effect of Seabed Instability on Pile Soil Pressure
Authors: Zhang Yongli , Zhao Yi , Yuan Zhenxia 
Published: November 2020

Abstract
In a narrow sense, the seabed instability means that the shear failure, liquefaction or scour occurs in the seabed; in a broad sense, the seabed instability means that the soil displacement occurs in the seabed. The seabed instability widely exists in the ocean environment, however, it has not been considered in the current design and calculating methods of the marine pile foundation, consequently, the accuracy and reliability of design results can not be guaranteed, which may induce that the ocean buildings are not safe enough. Therefore, it is necessary to found one new method to calculate the pile soil pressure with the influence of seabed instability, before which, one approximate mathematical model shall be established. Thus, based on Biot consolidation theory and fictitious pile technique, this paper firstly establishes a mathematical model describing pile-soil interaction considering the seabed instability, the soil pressure obtained through which can cover such factors as ocean environment, seabed soil condition and pile condition etc. And then, this paper introduces one mathematical solver (FlexPDE) to get the numerical solutions of the mathematical model presented. Finally, based on the numerical solutions, this paper discusses the effects of pile deflection, wave height, water depth, soil modulus, pile length and diameter on soil pressure, and some conclusions are obtained, which can be referenced in the design of ocean pile foundation.
Preventive Seismic Protection Technologies to Museum Collections: Quanzhou Museum of China Case Study
Authors: Qin Jie , Ma Botao , Song Maomao , Zhang Mansheng , Guan Zhizhong , Zhang Ling , Ge Jiaqi 
Published: November 2020

Abstract
The destruction of museum collections caused by earthquakes in China has attracted many scholars’ attention. Taking the implementation of the project of Quanzhou Museum for example, this paper introduces the application of the preventive seismic protection technologies to museum collections in aspects like the seismic design method, the verification of the performance of the anti-seismic products for showcases and museum collections, the implementation and effects of anti-seismic products. Through the implementation of the seismic protection and monitoring system for museum collections, an effective long-term mechanism for the seismic protection of museum collections in Quanzhou Museum is proposed. Finally, the successful demonstration of the preventive conservation of museum collections in Fujian is summarized.
Design Research of the Household Diagnosis & Treatment Products for Middle-aged and older Diabetic Patients
Authors: Yao Shanliang , Zhang Ying 
Published: November 2020

Abstract
The purpose of this research is to improve the user’s experience and product treatment effect by improving the humanized product design in response to the functional and emotional needs of Household Diagnosis & Treatment Products for middle-aged and older diabetes patients. We were investigated the existing Household Diagnosis & Treatment Products, analyzed the problems. We combined with the physiological and psychological characteristics of the patients, then we observe and researched the diagnosis and treatment process and summarized the needs of patients° At the end, we put forward the improved design method of Household Diagnosis & Treatment Products. The physiological and psychological needs of patients, especially the middle-aged and elderly patients, should be considered its rationality of Household Diagnosis & Treatment Products. It’s order to alleviate the negative emotions in the process of recuperation, improve the user experience of products, and then improve the treatment effect.
Experimental Study on Carbon Fiber Concrete Beams
Authors: Wang Xiaochu , Nie Xiaomei , Xiong Long 
Published: November 2020

Abstract
The influence of the length of carbon fiber on the deflection and strain of carbon fiber concrete beams was studied by testing the flexural capacity of the normal section of four carbon fiber concrete beams. The results show that the length of carbon fiber has a certain influence on the strength of reinforced concrete beams. The failure deflection of fiber concrete beams increases with the increase of the length of carbon fiber. Carbon fiber can improve the brittle failure of concrete beams. No matter how long the carbon fiber is, the cracking load and ultimate load of CFRC beam are not different from that of ordinary concrete beam.
Research on Entity Coreference Resolution Technology Oriented to Military Knowledge Graph
Authors: Hu Ruijuan , Li Zhufeng , Li Jian 
Published: November 2020

Abstract
Data processing in military field is in the stage of fusion disambiguation. The way of addressing the same thing is complex and difficult to integrate. Entity coreference resolution can effectively solve this problem. At the same time, entity coreference resolution is also an important part of knowledge fusion stage in the process of building military knowledge graph. This paper studies and implements Chinese coreference resolution from two aspects: Named Entity Recognition and coreference resolution. Firstly, use the BiLSTM+CRF model of neural network to realize NER in military field. By mining Wikipedia corpus, construct a pattern base, and iteratively find the coreference relationship in text based on pattern, and finally establish a model. To complete the rapid and effective construction of a total of 220,000 thesaurus, covering the military field of aircraft and ships two types of objectives, to achieve the military field entity coreference resolution, to provide strong support for the construction of military knowledge graph.
Design of Infrared Imaging System in Front of Vehicle
Authors: Gong Jianchun , Liu Lei , Zhou Zhen , Wang Yiwen 
Published: November 2020

Abstract
In recent years, due to the driver can not see the road ahead or safety distance is not enough to overtake caused by a variety of traffic accidents are common. In order to reduce the accidents, the design microcontroller, infrared emission and receiving module is implemented to detect whether there is the rear bodywork obstacles (such as people, animals, or other objects), and voice alarm system and LCD display alert the driver in front of the road, the speed and distance, etc., and introduces the design of the system in detail.
The Research on Integrated Production of Large Scale 3D Products Based on Mass Multi-angular Images
Authors: Wen Caihuan , Wang Wendong 
Published: November 2020

Abstract
Aim at the problems of high cost and low efficiency of traditional large scale 3D (three-dimensional) products acquisition methods, this paper provides an integrated production of large scale 3D products based on massive multi-angular Images. Firstly, multi-angular images were obtained according to oblique photogrammetric technique. After the operation of aerial triangulation and 3D construction, the real 3D model is achieved. On these base, integrated production of large 3D products were done. Through the statistical analysis of 3D products accuracy, its precision completely meets the requirements of large-scale data specification, which provides a technical guarantee for rapid and efficient data revision of basic geographic information.
Optimal Design of Deep Residual Network Based on Image Classification of Fashion-MNIST Dataset
Authors: Tang Yusi , Cui Hanguo , Liu Shuyong 
Published: November 2020

Abstract
With the increasing number of layers of deep neural network, the performance of the model tends to be saturated gradually. As a very deep network architecture, the deep residual network shows beneficial characteristics in precision and convergence. This paper deeply studied the essence of deep residual network and intended to design an optimal model for classification in Fashion-MNIST dataset. Due to the significant effects of the hyper-parameters in neural network models, the method of designing model structure and optimizing training process were investigated. Next, the performances of the training models under different conditions were compared, and finally an optimal training model whose accuracy was up to 96.21% was obtained. The experimental result shows that the performance of the model can be improved by partly widening the network and selecting more advanced training process.
Research on Generalized Error Control Mechanism of Monocular Vision Ranging Method
Authors: Xue Lixia , Li Meian , Sun Aixia , Jin Xiaoxin , Zhang Yongan 
Published: November 2020

Abstract
Distance perception is the basis and necessary prerequisite of environment perception, attitude perception and obstacle avoidance of intelligent vehicle and unmanned vehicle. Monocular vision ranging method is one of the mainstream distance sensing methods at present. In order to improve the accuracy of monocular vision ranging, a monocular vision ranging method based on machine learning is proposed. The monocular vision ranging method studied in this paper has the advantages of high accuracy, simple training data, simple ranging formula and can be explained, but the uncontrollable generalization error is one of the disadvantages of this method. Therefore, in order to explore the relationship between generalization error and training error, according to the monocular vision ranging method based on the pinhole imaging principle and a large number of measured data, this paper uses the polynomial method in the curve fitting toolbox of MATLAB to fit the functional relationship between coordinates and image distance, so as to obtain the model parameters. Finally, the threshold value of the optimal model is 0.5%, 49 training data and 21 test data. The extreme value of the ratio of the generalization error to the threshold value of the training error is 1.68, which can be used to control the generalization error of the monocular vision ranging method.
Course Achievement Evaluation Using Concept Map in Traditional Learning
Authors: Huang Peihan , Lin Shaohui , Yuan Junying , Chen Haishan 
Published: November 2020

Abstract
Concept map (CM) has been proved to be pretty efficient in learning assessment. Existing CM-based learning assessment methods tend to compare a CM delivered by a student against a standard version or expert version. This manuscript employs CM as a technique to assess students’ learning performance from the results of a bunch of traditional performance assessments. The experimental results show a more comprehensive result for interpreting students’ learning performance and provide some indications of the gap between teaching and learning for future teaching reforms.
An Optimal Initial Foot Position for Quadruped Robots in Trot Gait
Authors: He Dongqing 
Published: November 2020

Abstract
Gait planning parameters are important for quadruped robots to walk stably. In this paper, application of inverted pendulum model is widdened and a new collision model of quadruped trotting between feet and the ground that can indicate body-attitude changes in walking is established. Influences of initial foot position, walking cyclic period and stride length on walking stability are discussed. The influence varies with different initial foot positons and we get the optimal initial foot position for the quadruped in trot gait with minimum variation in body attitude and maximum walking stability. Finally, we get the optimal initial foot position and walking cyclic period with minimal collision velocity. Simulation results are presented.
Hotspots Prediction Based on LSTM Neural Network for Cellular Networks
Authors: Zhou Lixia , Chen Xia , Dong Runsha , Yang Shan 
Published: November 2020

Abstract
The tremendous growth in data traffic usage is a prominent challenge to cellular network operators. The aggregation of a small number of users’ services may lead to considerably high loads on base stations, thus generating traffic hotspots in the networks. To provide better quality of service in dynamic network scenarios efficiently, it is necessary to accurately distinguish and predict potential hotspots, so as to adjust resource configuration and allocation in advance and keep the network running smoothly. In this paper, a network traffic hotspots prediction method is proposed based on the Long Short-Term Memory (LSTM) neural network framework. To verify its effectiveness, real-world data are utilized in our experiments. Numerical results demonstrate that a time series model based on the LSTM framework can achieve 92.2% success rate for future hotspots prediction.
A Hybrid Methodology Based on Machine Learning for a Supply Chain Optimization Problem
Authors: Duc Duy Nguyen , Nananukul Narameth 
Published: November 2020

Abstract
This paper presents an advanced methodology that integrates a machine learning methodology into an optimization process. The framework of an interactive machine learning algorithm was developed to meet the challenges in solving large-scale optimization problems. An artificial neural network (ANN) is used with the knowledge gained from solving previous problems with different scenarios to define a good starting point for a solution searching process. By using an initial solution, known as “warm start”, the search space can be reduced to get more opportunity to find an optimal solution. The applicability of the proposed method was evaluated by using it to determine the optimal facility locations for a biomass supply chain problem using a real case study from Central Vietnam. The supply chain planning model is based on an optimization model, where the goal is to maximize the benefits from meeting the electricity demand minus the total cost from facility cost, penalty cost from lost demand, and operational costs form the supply chain. The structure of the ANN, the number of intermediate layers and the number of processing nodes, was determined by comparing the accuracy from different configurations. The ANN with two intermediate layers possesses the best performance from the training and testing datasets. The proposed model succeeded in predicting the facility location with more than 98% prediction accuracy. The results from our framework provide optimal solutions while saving runtime.
Recognition of Spam Messages Based on Text Mining
Authors: Fang Yajie , Zhang Ping 
Published: November 2020

Abstract
With the rapid development of science and technology, the application of artificial intelligence technology is becoming more and more extensive. The maturity of artificial intelligence technology is inseparable from big data and machine learning. Big data is the foundation of artificial intelligence, while machine learning is the core. To mine the value hidden in big data, in order to achieve text classification, data prediction, and provide strategic decision basis, we need the power of Machine Learning. This article will introduce the classic algorithm in machine learning, Naive Bayes, KNN nearest neighbor, and support vector machine algorithm, and apply them to text mining of spam text sets. It shows that Machine Learning is the fundamental way to make machines as intelligent as humans.
Analysis of High-Speed Railway Passenger’s Travel Choice Behavior Based on Deep Learning Model
Authors: Wang Shujie , He Zhenhuan 
Published: November 2020

Abstract
The analysis of railway passengers’ travel choice behavior plays an import role in railway passenger product design and transport organization. Many researchers focued on it and lots of models and methods had been proposed. With the rapid development of information technology in recent years, deep learning models are more and more widely used in many research fields, and also applied in this research. Based on the OD train ticket data of Beijing-Shanghai high-speed railway line, it studied travel choice behavior of passengers in Beijing-Shanghai high-speed railway line during the weekday, and then took attributes of ticket data (arrive-departure station, arrival-departure time, etc.) as the mapping features to study passengers’ choice of different trains, The result shows that the method given by the research has quite high fitting accuracy.