bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection of spinal fracture lesions based on Improved Yolov3
Authors: Sha Gang , Wu Junsheng , Yu Bin 
Published: July 2020

Abstract
Yolo[1]algorithm has a good detection effect in target detection. Because of its high detection accuracy and fast detection speed, it is widely used in practice. Because of the problem that the complexity of spine CT images, the irregular shape of vertebral boundary, which needs doctors’ prior knowledge and clinical experience to determine lesions location in CT images, so it can not meet the clinical real-time needs. In this paper, We use deep learning to process the CT images of spine, and to detect and locate lesion of (cervical fracture, cfracture), (thoracic fracture, tfracture), (lumbar fracture, lfracture) by the improved YOLOv3. Through using lesions bounding box dimensional cluster, multiscale transformation of input CT images, and change NMS to MAX value to improve detection efficiency and accuracy. The experiment shows the results are more accurate, and mAP (mean average precision) of detection algorithm is 73.63%, detection rate is 0.027 seconds per detection, and IOU((Intersection-over-Union) is 75.9, which can basically meet the clinical real-time needs.
An Immune Chaotic Niche Genetic Algorithm for Monitoring Distribution Problem in Self-Organizing Wireless Sensor Network
Authors: Zhou Jie , Xu Mengying , Yang Rui , Lu Yi 
Published: July 2020

Abstract
Due to the sensors are restricted in sensing capabilities, monitoring distribution has become a challenging problem in self-organizing wireless sensor network (SOWSN). Micro nodes are self-organized tiny devices with limited sensing capabilities. Careful monitoring distribution scheme can be a suitable optimizing means for achieving the required high target detection rate goals, comprising sensing capacity restrictions. However, the monitoring distribution problem is a typical NP-hard combinatorial stochastic optimization problem. In this study, an immune chaotic niche genetic algorithm (ICNGA) to enhance the target detection rate is explored. Advanced operators such as immune operator and chaotic operator are also incorporated into the ICNGA to increase the explore capacity. The represented immune selection and chaotic generation depending on ICNGA with global search capability can simultaneously optimize multiple variables. Simulation results identify that the proposed algorithm can get a higher target detection rate over SFLA and SA. Besides that, the convergence speed of the presented ICNGA is much higher than that of SFLA and SA. So the proposed method significantly enhanced the efficiency.
Elite Adaptive Parallel Evolutionary Algorithm for Sensor Nodes Clustering Optimization in High Density Sensor Network
Authors: Zhou Jie , Xu Mengying , Yang Rui , Lu Yi 
Published: July 2020

Abstract
Minimizing the communication energy consumption has always been a key aspect of the research of High Density Sensor Network (HDSN). HDSN is a group of small devices with restricted battery capacities. Accordingly, the objective of the clustering technique is to design a best set of sensor nodes clustering result for the combination that minimize the communication energy consumption. The ideal clustering problem with discrete variables is a np-hard problem in its accurate formulation. In this study, an improved elite adaptive parallel evolutionary algorithm (EAPEA) is proposed to lower the communication energy consumption in HDSN. The suggested algorithm is tested by a fitness function, and new adaptive operator and elite operator have been designed to speed up the convergence rate. The EAPEA merges the merits of the adaptive adjusting and elite selection. By the mechanism of adaptive adjusting, its overall exploit capacity is fully applied for finding the overall optimal solution. EAPEA simultaneously develop a large number of results to explore the explore area and to avoid local optima. A convergence analysis is carried out, and extensive experiments are carried out that compare EAPEA with two other heuristics. Our experimental simulations denote that the represented EAPEA technique, when used into HDSN, is competent to offer better performance and a low communication energy consumption compared to two other heuristics.
Network Application Classification with DNN Model
Authors: Dong Ligang , Suo Tongpeng , Jiang Xian 
Published: July 2020

Abstract
Due to the development of information technology, there are many kinds of Internet applications. Many network applications not only bring great challenges to the quality of network services but also have an impact on Internet security. In order to efficiently use network resources and provide effective management and control measures for network managers, network traffic needs to be classified. At present, many traffic classification algorithms are not accurate enough, which affect the evaluation and further study of the network. Therefore, the innovation of this paper is to propose a network application classification model. This model uses Deep Neural Network (DNN). Different pretreatment methods are used for data sets to increase the accuracy. This model is compared with other models to prove the effectiveness of the work.
Research and Implementation of Handwritten Numbers Recognition System Based on Neural Network and Tensorflow Framework
Authors: Bai Jing , Fei Jie 
Published: July 2020

Abstract
It is difficult for a computer to recognize handwritten numbers with a high accuracy because of many factors such as shape, size and others. This paper applies a neural network based on Tensorflow framework to implement the handwritten numbers recognition system. The system is compiled and run in vim under Mac operating system with an 8g RAM. This system first builds a neural network, then trains the model on the MNIST dataset to output the accuracy of handwritten numbers recognition. We can input the handwritten picture and get the prediction result through this system. Then we optimize this system on neural network, activation function, loss function, learning rate and generalization to improve the accuracy. Finally, we prove that this system has a higher accuracy closed to 98% for recognizing.
Single Object Tracking for Dynamic Programming based on Fine-grained Network
Authors: Jiang Jianguo , Jin Kaiyuan , Wu Jingjing , Qi Meibin , Wang Qian 
Published: July 2020

Abstract
Single target tracking has always been a key and challenging research field in computer vision. Currently, an increasing number of researchers are focusing on extracting better tracking features and designing the best tracker. This paper proposes a new single target tracking network that uses fine-grained features and dynamic programming (DPFNet). In order to extract superior features, we added an attention module to the regression network enabling us to extract finer-grained and discriminative features to achieve regression. Besides, we did observe that different objects have varying moving rates; for different moving targets, the magnitude of the changes in target position within two adjacent frames is not the same either. Although an area search of 4 times the target’s size can be applied to most objects, targets with large position changes may appear in other image areas outside the search area and the target would not be located as a result. Aiming at solving this problem, when designing the tracker, this paper analyzes some of the indicators for predicting the location and uses the analysis results to determine whether the search area is appropriate, so as to dynamically adjust the extent of the search area thereby significantly improving the tracking function. In other words, the size of the search area can be dynamically recalibrated for different images. Subsequent experiments prove that the method put forward in this paper achieves State-of-the-Art results.
Iterative Learning Control for Generalized Projective Synchronization of Fractional-order System with Unknown Local Lipschitz Function
Authors: Wang Liming 
Published: July 2020

Abstract
This paper is devoted to the generalized projective synchronization problem of fractional-order systems subject to the unknown local Lipschitz conditions. Based on the definition of the fractional integral, a suitable variable is defined, thereby the generalized projective synchronization problem between leader and follower is transformed into the stabilization problem of the system consisting of the newly defined variable. An adaptive iterative learning controller is proposed to control the fractional-order systems. Based on the composite energy function method, the convergence of learning process is analysed. Consequently, the sufficient conditions are derived to guarantee that the leader-following FOSs can achieve the generalized projective synchronization in the finite time interval as the iteration step goes to infinity. Finally, a numerical simulation example is presented to demonstrate the effectiveness of the proposed method.
Application of ControLogix Control Platform in the Coke Oven Dedusting System
Authors: Sheng Zhai , Zhao Xu , Zhichao Xu , Jiaming Chan 
Published: July 2020

Abstract
Taking the coke oven dedusting system of a chemical plant as the research object, the coke oven dedusting monitoring system is designed. This system mainly uses the software and hardware of the ControlLogix control platform of Rockwell Company. In the system design, the process flow of coke oven dedusting system is analyzed, the system control scheme and the configuration of software and hardware are given in details. In addition, the control software and human-machine interface are designed and developed, and the design idea is provided. The practical results show that the system is good at dedusting effect, convenient in maintenance, and reliable and stable in operation. It has achieved good economic and social benefits.
Research on Sensorless Control System of PMSM Based on Adaptive Fuzzy Sliding Mode Observer
Authors: Tian Zhewen , Shen Kaiyuan 
Published: July 2020

Abstract
The vector control system of permanent magnet synchronous motor needs to use encoder and other speed measuring devices, which will increase the cost of the system and bring reliability problems. In order to solve these problems, this paper proposes a sensorless control system of PMSM Based on adaptive fuzzy sliding mode observer. Firstly, in order to suppress the chattering problem of the traditional sliding mode observer, the continuous sigmoid function is used as the switching function of the sliding mode observer to improve the stability of the system. Then, the adverse effect of the fixed sliding mode gain on the system performance is analysed. Observer Combined with the fuzzy control theory, the error function is selected as the fuzzy input, the fuzzy rules are formulated, and the fuzzy controller is designed to adjust the sliding-mode gain adaptively. Finally, the simulation model of sensorless control system of PMSM is established. The simulation results verify the feasibility of the proposed scheme.
Research on an Intelligent Search Function Architecture in Distribution Network Situation Awareness System
Authors: Meng Hailei , Fang Mu , Li Longtan , Wang Zhiqiang , Cao Qingtao , Liu Chunxiu 
Published: July 2020

Abstract
After the establishment of the distribution network situation awareness system, it faces the problem of large-scale data search technology. We implement path analysis through a complete intelligent search function, and propose a big data search engine framework suitable for situational awareness systems, and solve the problem of data sharing and intelligent access in multiple systems. Especially in the collection and display of cross-region data, we combed the calling relationship between the systems in detail, and based on this, carried out the exploration of the optimal technical path of the intelligent search technology adapted to the situation awareness of the distribution network. Finally, the overall framework of the intelligent search engine in the current operating mode of the power system is proposed, and the specific analysis of the implementation path is given.
Real-time Task Assignment Method of Two-load AGV under Dynamic Change of Goods Urgency in Logistics Warehouse
Authors: Kang Yuyun , Feng Guifang , Wang Zhenhai , Sun Jie 
Published: July 2020

Abstract
A real-time task assignment method based on the least time is proposed to solve the problem of automatic assignment of two-load Automatic Guided Vehicle (AGV) transportation tasks when the urgency of outbound goods is changing dynamically. Firstly, the urgency of goods going out of the warehouse is defined, and it is time-dependent and divided into two categories: urgent and non-urgent. Secondly, the location of AGV consists of three classes and the current task status of AGV is also detailed to three classes. Thirdly, the same vehicle factor is determined according to whether the adjacent outgoing goods are in the same vehicle. Fourthly, according to the order of issued task and taking the above factors into consideration, the delivery time is analyzed and enumerated under different shipment orders and different AGV status. Finally, a decision tree is built and the real-time task assignment method is proposed considering the least time.
Application Research of Engineering Foundation Pit Support Based on3D Geological Modeling Platform-ITASCAD
Authors: Zhang Bentao , Xu Cheng 
Published: July 2020

Abstract
Foundation pit support is the key link in the construction of engineering construction, and it is also an important guarantee for the overall safety of engineering construction. At present, the country and society have higher and higher requirements for the quality of engineering construction, and the construction conditions of engineering projects are more and more complex, which makes the traditional engineering foundation pit support design and construction methods exposed more and more disadvantages. ITASCAD is to create an international level of large software for the geotechnical industry. Therefore, this paper expounds the problems existing in the design and construction of engineering foundation pit support, and discusses the typical application cases of Itascad technology in engineering foundation pit support. Based on the study of several practical cases, this paper analyses the breakthrough and innovation brought by the application of Itascad technology for engineering foundation pit support, and provides a new thinking direction for the development of foundation pit support technology.
Application of ECG Signal Denoising and T-wave Automatic Detection Based on Computer Deep Learning
Authors: Xu Bingxin 
Published: July 2020

Abstract
To address the problems of time-consuming, laborious and costly ECG expert diagnosis in the long-term massive ECG signal automatic denoising and T-wave automatic detection system, resulting in the difficulty to extract features, as well as the poor adaptability and low accuracy of the abnormal diagnosis model, we proposed an ECG signal denoising and T-wave automatic detection method based on deep learning. The method mainly includes four steps as follows: ECG signal denoising preprocessing, segmentation of ECG signal and unification of sampling points, unsupervised heartbeat feature learning, denoising and T-wave automatic detection. The structure of the deep faith network FCMDBN model and the learning denoising and T-wave automatic detection algorithm are proposed. Based on the MIT-BIH heart rate anomaly database, the simulation experiment shows that the signal diagnosis method proposed in this paper has relatively high adaptability and accuracy compared with the denoising and T-wave automatic detection by artificial design based on traditional ECG features.
Research on the Relationship between Physical Exercise, Psychological Flexibility and Positive Emotion of College Students Based on Computer Mathematical Model
Authors: Xia Bo , Ma Zhichao , Hu Yingyue 
Published: July 2020

Abstract
In the 1970s and 1980s, the study of mental resilience emerged in the field of psychology in the United States and quickly became a hot topic in the field of international psychology. The field studies the psychological adaptation and development of children, adolescents (and later adults) in adversity. The extensive research on the psychological resilience of college students can enlighten the complexity of their psychological development. Throughout life, people inevitably encounter setbacks and adversities, and are under pressure from all sides at all times. With the development of society and the intensification of competition, college students are facing more and more pressure. Some college students can adapt to pressure and grow up healthily, while others cannot adapt to adversity, which leads to psychological problems. In the era of computer big data, relevant experience shows that physical exercise has certain help in forming mental resilience and positive emotions. Therefore, this paper analyzes the relationship between physical exercise, mental resilience and positive emotions of college students by using computer technology and mathematical model, so as to provide help for college students to form healthy psychology.
The Application of Computer Modeling Technology in Art Design
Authors: Zhang Bo 
Published: July 2020

Abstract
The art design style of computer modeling is the hot spot of China’s art design in recent years. After entering the 21st century, the concept of art design has been constantly developed and innovated, and a series of designs such as Java and dynamic titles are all the rage. Based on computer modeling art design style of writing with different point of view of reality, tends to be the symbol, the transition of the style, let people can more easily and work more comfortable and more willing to learn the meaning, this article through to the computer modelling of the historical development of the art design style analysis, combined with the graphic sustainable theory to delve into the UI design for readers reference.
Research on ESP Hybrid Teaching Innovation based on the Computer Information Technology
Authors: Sun Chao 
Published: July 2020

Abstract
The rapid development of the educational information age has brought changes and challenges to the field of English education. The development of computer information technology has led to the reform of teaching methods. Under the guidance of constructivism theory, around the teaching concept of “teachers’ leading role and students as the main body, and the conductor combination”[1]. In this paper, based on English majors offered English course as an example, analyzed the computer information technology platform based on hybrid English teaching, in order to provide useful reference for the teaching reform of basic courses for English majors.
Research on Machining Precision Control of Mechanical Die Based on Computer Aided Technology
Authors: Guo Chen 
Published: July 2020

Abstract
In the machining process of mechanical mold, the machining accuracy must be guaranteed, only in this way can the mechanical mold’s performance be guaranteed. When we process and produce mechanical moulds, we need to fully realize the importance of precision. The combination with computer aided technology can effectively control its accuracy. In the process of machining and production, there are many factors that may cause accuracy problems. In this paper, the machining precision control of the mechanical mold was studied by computer aided technology based on the machining and production process characteristics of the mechanical mold.
Design and Communication of Digital Museum Based on Computer and Internet Technology
Authors: He Cheng , Lu Yijie 
Published: July 2020

Abstract
With the advent of the Internet era, the development of communication technology and virtual reality technology, and the increasing maturity of computer network technology, the Internet technology museum has gradually replaced the traditional museum and become a trend. With the rapid development of mobile terminal intelligence, the way of information transmission is no longer limited. The application of Internet technology to digital museums can change the fixed exhibition and single visiting mode, obtain different experience and interactive experience, and open up a new field for the development of digital museums.
The Construction Strategy of Talent Cultivation System for Tourism Informatization in the Era of Internet +
Authors: Luo Chuman , Chen Haitian , Yu Tian 
Published: July 2020

Abstract
With the rapid development of the Internet + era, the quantity and quality of China’s tourism human resources have increased rapidly, making positive contributions to the development of the tourism industry. But generally speaking, there is still a big gap between the quality and structure of human resources and the requirements of the rapid development of tourism industry, which affects and restricts the further development of China’s tourism industry to some extent. Tourism human resources is an important guarantee for the rapid development of tourism. The quality and structure of China’s tourism human resources restrict the rapid development of China’s tourism to a great extent.
Research on Internet Product Design Based on Visual Communication
Authors: Meng Cuihua 
Published: July 2020

Abstract
In this era of rapid development of information, people’s way of living is closely related to the network, the Internet has affected all areas of human society, and the survival and development of people have a broad impact. In the interface design of Internet products, color often has the advantage of taking the lead over shape, and the color of the interface will leave the first impression on people. The difference of color can give a person disparate feeling and impression, the interface that gives priority to tonal with blue or green can give a person a kind of cool and refreshing and quiet or vast and distant feeling.
Explore the Application of Computer Modeling and Rendering Technology in Rural Landscape Color Design
Authors: Li Dan 
Published: July 2020

Abstract
The model is an important factor that affects the rendering quality. In the process of model construction, the Boolean operation method is usually used. This operation method will consume a lot of computer resources. Improving this operation mode can not only improve the accuracy of the model, but also simplify Model to achieve fast rendering. Not only can the model be simplified, but there will be no discrepancies visually. If the number of sides of the model cannot be reduced, the angle of the camera should be adjusted and the rendering efficiency can be effectively improved on the basis of fully expressing the design content. When rendering rural landscapes, by adjusting the angle, only the nearby objects can be adjusted, the rendering effect can also be achieved and the rendering efficiency is improved.
An Analysis of Mainstream Animation Education in Japan and the United States Using Computer 3D Technology
Authors: Chen Danping 
Published: July 2020

Abstract
As an important part of culture and entertainment, animation is also a form of artistic expression with entertainment and educational functions. The application of computer 3D technology makes the animation more vivid and expressive. This paper USES computer 3D technology to analyze the entertainment and educational functions of American and Japanese animation, as well as the educational significance of American and Japanese animation. This paper points out that computer 3D technology not only creates new cultural connotation of American and Japanese animation content, but also is one of the important factors of its educational significance.