bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Scene Deblurring of Multi-Scale Progressive Attention Network
Authors: Huang Wenzhuo , Deng Yueming , Liu Yiming , Wu Jun , Li Xiaojun
Published: April 2021

In order to enhance the attention to the image foreground targets in dynamic scenes and better suppress the generation of image edge artifacts, a multi-scale progressive attention network (MSPA) deblurring algorithm is proposed, MSPA is based on the GAN structure. In the feature extraction stage, MSPA designs multi-scale width perception and pyramid perception residual blocks to help our skeleton network better extract multi-scale local features and reduce the difficulty of network training, and In order to better obtain the semantic information of the image, the channel attention mechanism is used to correct the deep features of the blurred image; in the feature fusion stage, the progressive channel and spatial attention network (PCSA) is designed to enhance the receptive field, and selectively integrate multiple levels semantic information and enhance the non-local connection between features in progressive method. A large number of experiments show that the MSPA algorithm is superior to many advanced algorithms on the GoPro and Kohler datasets.
High-Resolution Virtual Try-On Network with Coarse-to-Fine Strategy
Authors: Lyu Qi , Wang Qiu-Feng , Huang Kaizhu
Published: April 2021

In this paper, we propose a high-resolution virtual try-on network model based on 2D images, which can seamlessly put on given clothing to a target person with any pose. Under the coarse-to-fine strategy, we firstly transform the given normal clothes to warped clothes to well match the pose of the person by a clothing matching module, then these two generated images are combined to generate one fitting image of the person put on the given clothes by a try-on module, lastly utilize a Very Deep Super Resolution (VDSR) module to refine the generated fitting image. Compared to the 3D based methods that are computationally prohibitive, our method only needs 2D images, which is much faster. We evaluate our proposed model both quantitatively (i.e., in terms of SSIM) and qualitatively on a public virtual try-on dataset (i.e, Zalando). The experimental results demonstrate the effectiveness of the proposed method: generating visually better quality of images, our new method can improve the SSIM by 1.5%.
Research on Intelligent Damage Assessment System for Time-sharing Rental Vehicles Based on Image Recognition
Authors: Zhu Qianqian , Liu Yingnan , Shen Ying , Zhao Zihao
Published: April 2021

With the popularity of the concept of sharing, car sharing has become a new hot spot. Currently, there are more than 100 brands operating car sharing in the market. The group composition of car rental is relatively complex, and most of them are novices in driving technology. Some minor scratches and other injuries are easy to occur during the driving of rental vehicles, which poses new challenges to the car-sharing operation platform. Therefore, in the operation of car-sharing business, it is very important to realize the automatic determination of vehicle damage in the process of each use. This paper presents a method and system for automatic damage determination of vehicles based on the shared vehicle four-corner images. By comparing the damage information before and after renting each vehicle, this scheme can effectively save labor cost, realize rapid damage recognition, clear responsibility definition, and improve user experience and damage treatment efficiency.
Freehand Sketching Portrait Recognition with Least Square CycleGAN
Authors: Gou Xiaosa , Liu Bingguo , Liu Guodong , Lu Binghui , Gan Yu , Chen Fengdong
Published: April 2021

Freehand sketching portrait recognition refers to the recognition of sketched portraits and face photos drawn by artists. Existing research mainly involves inputting a given real portrait and converting it into a similar sketch portrait, and then matching the face with the sketch portrait in the real portrait database. This paper starts from the idea of inputting a sketch image to identify the real portrait in the database, focuses on the research based on the method of portrait synthesis, and introduces the existing methods of sketch portrait identification. We use the CycleGAN improved by least squares to achieve the translation from sketch to portrait, and finally PCA was used to complete face matching. The results show that LS_CycleGAN has certain advantages. Compared with other methods, its synthesis results are most close to the portrait. The average score of SSIM and PSNR is 0.844 and 17.331, and the average success rate of recognition is 88.2% for Rank10.
Diversity Regularized StarGAN for Multi-style Fonts Generation of Chinese Characters
Authors: Zeng Jinshan , Chen Qi , Wang Mingwen
Published: April 2021

The generation of stylish Chinese fonts plays a central role in many applications such as the design of art fonts and Chinese calligraphy generation. Most of existing methods focus on the generation of a single-style Chinese font, while few works focus on the multi-style font generation. In this paper, we exploit the star generative adversarial networks (StarGAN), a very popular generative adversarial networks (GAN) model recently developed in the literature, to realize the generation of multi-style Chinese fonts via a single model. Furthermore, in order to tackle the generation issue of Chinese characters having similar strokes for StarGAN, i.e., generating the same mode for these different but similar Chinese characters, we introduce a diversity regularizer such that the generator can generate high-quality characters with better diversity. A series of experiments are conducted on a handwritten Chinese character dataset called CASIA-HWDB1.1 and three standard printing font datasets to show the effectiveness of the proposed method. The experiment results show that the proposed method can effectively tackle the generation issue of Chinese characters having similar strokes in terms of the quality and diversity of generated results, via comparing to the baseline StarGAN, and is scalable to the multi-font generation via comparing to existing methods for the single-style font generation.
ResNet-50 based Method for Cholangiocarcinoma Identification from Microscopic Hyperspectral Pathology Images
Authors: Deng Yingjiao , Yin Jintao , Wang Yan , Chen Jiangang , Sun Li , Li Qingli
Published: April 2021

As the second most common primary liver tumour, the early detection of cholangiocarcinoma is very important. Computer-aided diagnosis based on deep learning using pathological tissue images is often used in cancer diagnosis. Compared with traditional RGB pathological images, hyperspectral image has more advantages in deep learning based automatic pathological diagnosis because it contains spectral dimension information. In this paper, a ResNet-50 based method is used to identify cholangiocarcinoma from microscopy hyperspectral images. The microscope hyperspectral choledoch tissue images are captured by our microscopy hyperspectral imaging system (MHIS) and annotated by experienced pathologists manually. After pre-processing and data argumentation, we split them in to training set (6800 images) and testing set (210 images) and choose ResNet-50 structure to train the classification model. The classification model can automatically classify the choledich tissue images into cancerous and non-cancerous regions. Our experimental results show that the accuracy of proposed method is 82.4% in case of ResNet-50 structure.
Design Innovation Driven by Artificial Intelligence AI Multifunctional Wheelchair Design Based on the Needs of Patients with ALS
Authors: Liyao Rong
Published: April 2021

With the maturity of artificial intelligence technology, the integration of artificial intelligence and the medical and health fields has become more and more closely. The improvement of technology has played an important role in the development of the medical and health industry and has provided more possibilities for the treatment and rehabilitation of rare diseases. In mechanical design, integrated and innovative design methods can better discover the needs of patients, better reflect the advantages of technology and solve practical problems. Under the guidance of design thinking and inclusive design, this article will study the life needs of patients with amyotrophic lateral sclerosis (ALS) and the nursing needs of nursing staff, and integrate artificial intelligence technology to propose innovative solutions to users Solution-Design an AI multifunctional wheelchair dedicated to ALS patients to provide intelligent methods and paths for the rehabilitation and care of ALS patients.
Construction and Application of Comprehensive Evaluation Model of “Golden Classroom”
Authors: Zhang Deran , Chen Rui , Yuan Yunyun
Published: April 2021

The survey shows that the intensity of learners’ interest in courses is the strong positive energy for the construction of “Golden Lessons”, and the optimization of classroom teaching is the primary factor among many factors in the construction of “Golden Lessons”. The director who constructs the “golden lesson” is the teacher, the main body is the student, and the measurement of the “golden content” is the classroom teaching. Therefore, the continuous “Golden Classroom” is an inevitable move to build a “Golden Lessons”, it is imperative to find the evaluation standard of “Golden Classroom” scientifically and reasonably. Based on this, through the combination of qualitative and quantitative, using the principle of fuzzy mathematics, a comprehensive evaluation model of “Golden Classroom” is constructed, and the standard score of the final evaluation result is used to give the threshold of “Golden Classroom”. For the objective determination of “Golden Classroom”, building “Golden Lessons” has certain theoretical enlightenment and application value.
Optimization of E-Commerce Logistics System Based on Artificial Intelligence Technology
Authors: Lv Jian
Published: April 2021

With the improvement of China’s social and economic development level, the requirements for logistics efficiency are becoming more and more stringent. Artificial intelligence technology is the current direction of vigorous development. With the development of the Chinese era, in order to better promote the development of China’s urbanization, this technology has been widely used in various fields in our country and occupies an important position in various fields. With the continuous innovation of artificial intelligence technology, various industries are undergoing industrial upgrading and format conversion. E-commerce logistics bear the brunt. This article mainly discusses the application of artificial intelligence in the e-commerce logistics system, and applies it to the e-commerce logistics industry. With the help of artificial intelligence algorithms, it is used to accurately calculate the supply and demand relationship of goods and the optimal path of actual logistics distribution. The selection provides algorithm-level support. The use of artificial intelligence can not only accurately predict inventory, but also play a role in optimizing inventory measures. With this technology, the automation level of the logistics sorting period can be effectively improved, highlighting the application value of artificial intelligence technology and promoting China the development process of modern e-commerce logistics industry makes it possible to develop in the direction of intelligence and automation. The experimental results show that the e-commerce logistics industry has great convenience for the sales and transportation of goods under the condition of combining artificial intelligence technology, and it has higher efficiency than traditional e-commerce logistics.
Analysis on the Application of Cause Intelligence Financial Management System Based on Artificial Intelligence Environment
Authors: Zhu Xiangping
Published: April 2021

In recent years, artificial intelligence has made great progress in the field of science and technology, and has played a substantial role in the development of real life. At present, China’s financial management system is still in the basic stage, mainly relying on manual work, financial software informatization has achieved results, but the promotion of intelligence is relatively slow, cannot provide good prediction and decision-making scheme for people. This paper analyzes the current situation of the application of artificial intelligence technology in intelligent financial management system, and puts forward the application analysis of the cause intelligent financial management system based on the artificial intelligence environment. In this paper, through the investigation and analysis of 220 financial personnel and system R & D personnel, as well as the comparative analysis of the specialization, rationalization and intellectualization of the financial management system after the application of artificial intelligence, and the discussion and analysis of the results, put forward the application advantages of artificial intelligence in the financial management system, which provides guarantee for the development of intelligent financial management system. The research in this paper is of great significance to the further integration and development of the two, to find problems and to put forward constructive suggestions on the application of artificial intelligence technology in the cause intelligent financial management system.
The Influence of 5g on the Development of Electronic Information Engineering
Authors: An Na , Wang Lei , He Zhenquan
Published: April 2021

With the rapid development of the times, our quality of life is also rising rapidly. At present, our technology has undergone a round of rapid development and achieved certain results. The era of artificial intelligence based on computer technology has come, and our life begins to embrace and contain this new technology, so modern life is the era of artificial intelligence. So, the new technology has brought many changes. For example, in Information Engineering, we can replace manual operation with preset programming to increase efficiency and reduce error rate. So, how to program is a difficult problem. Therefore, this paper studies the influence of 5g on the development of electronic information engineering. In order to better carry out the experiment, we first set the general direction and overall tone of the experiment we need to do after consulting a large number of literatures. Then we borrowed a period of time from the laboratory to conduct real experiments. But before that, we also carried out simulation experiments to reduce errors, and then conducted real experiments (in this case, we used interactive system to model and calculate the number) According to the rationality, the experimental results are obtained. The experimental results show that after the improvement of artificial intelligence, 5g can increase the reliability of NC programming and the simulation of machining process.
Application Research on the Integration of Civil Engineering and Computer-aided Building System Based on the Development of BIM
Authors: Liu Bing
Published: April 2021

Building informatization and industrialization are mutually advancing in the development process. After BIM technology is widely used in the construction industry, the modeling functions of BIM include standardized components for building building models, “error and leakage collision” inspection, and simulation simulation construction. These functions are in Building industrialization has great advantages in the construction process of prefabricated buildings, especially the standardized design process in the engineering project design stage, which helps to vigorously promote the standardized construction. There is a certain correlation between the improvement of civil engineering construction quality standards and the background of intelligent development. People are more concerned about the quality of engineering projects, and social publicity has been reached for the safety and green environmental protection of buildings. It is imperative to realize technological innovation in civil engineering. The fusion technology of civil engineering technology and computer-aided building system combines building technology, civil engineering technology, control technology, etc. with computer support systems to develop a new type of intelligent building technology. The integration and application of civil engineering and computer-aided building systems are highly valued by the country, which will lead the development direction of the wood construction industry. For colleges and universities, the research and study of the integration and application of civil engineering and computer-aided building systems not only puts forward new requirements for student learning, but also provides new ideas for the direction of employment, and at the same time has a deeper understanding of the relevant research system of universities change. The article mainly explains the working principle of BIM, based on the BIM development background and the integration advantages of civil engineering and computer-supported building systems for specific applications in construction projects, with the goal of promoting the further development and popularization of this technology.
Intelligent Environment System Based on CIM
Authors: Wang Jianyu , Sheng Xing , Dong Yingnan
Published: April 2021

The construction of smart city has added a lot of charm to our country, and has been paid attention to by everyone, but there are still environmental pollution problems. The emergence of urban information model technology (CIM) makes the construction of three-dimensional composition combined with environmental perception to solve this problem. In this paper, the intelligent environment system based on CIM is studied, which is based on the requirements of intelligent environment system. Starting from the basic content of CIM, the smart city construction and CIM technology are combined, and the architecture of CIM intelligent environment system is established through data collection, wireless communication, micro processing and other aspects. Aiming at the non-uniformity of the system itself and the inaccuracy of the temperature measurement distance, the error caused by the temperature perception of the furnace wall is corrected. The Kalman filter algorithm is used to eliminate the noise and redundancy, and the accuracy of the collected data is improved. The experimental results show that the system can monitor the environmental problems intelligently in real time, and the accuracy rate is as high as 89.38%. It can effectively monitor environmental changes and prevent large-scale environmental pollution.
Tuberculosis in Epidemic Prevention and Control Based on Big Data Technology
Authors: Tan Jiao , Ma Yonghong , Men Ke , Lei Jing , Zhang Hairui , Feng Yancheng
Published: April 2021

Tuberculosis has been a serious threat to the health of people in all countries for many years. This study mainly explores the application of tuberculosis in the prevention and control of epidemics based on big data technology. First, collect data on tuberculosis epidemics. Tuberculosis epidemic information according to the statutory infectious disease reporting system in the China Disease Prevention and Control Information System, case data of reported cases of tuberculosis in mainland China in the past three years was collected according to the review date. Next, collect map data and statistics of demographic data. Finally, clean and organize the data. Check whether there are outliers, duplications, missing and logical errors in the case data, and unify the units of the variables. The reported incidence rate was the highest in the third year and the lowest in the first year, which were 104.90 cases per 100,000 and 71.89 cases per 100,000, respectively. The number of reported cases in the three years was basically similar to the reported incidence rate. This research will effectively improve the accuracy of tuberculosis diagnosis and provide decision support for tuberculosis diagnosis.
Research on the Classification and Selection Strategy of Physical Education Teaching Model Based on Modern Information Technology
Authors: Shigang Xu , Sheng Wang
Published: April 2021

Because the future education of the information age has the characteristics of creativity, diversity, flexibility, and individuality, backward physical education methods and closed teaching models can no longer meet the needs of future education. The information environment has greatly impacted traditional sports In teaching, the closed teaching mode is “using classrooms and sports fields as the environment, teachers as the center, and low-media teaching materials as tools”. Based on this, this article puts forward a research on the classification and selection strategy of physical education model based on modern information technology. This article will focus on the analysis of the classification and selection of the physical education model, and put forward guiding strategies, and compare the information technology-based physical education model with the traditional physical education model. Studies have shown that the use of modern information technology can optimize the basic conditions of physical education, allowing teachers and students to effectively share information technology-based physical education resources, and better meet the actual demands of students for independent learning and physical exercise; not only to develop students’ physical skills With interest in learning, physical education can move towards a higher quality, and it can also improve the pertinence of physical education and physical training, which has important practical significance for the development of personalized physical education and the improvement of students’ physical quality.
Study on Economic Growth Calculation Method Based in Big Data
Authors: Xia Tiantian , Lin Xiaoying , Wang Hui
Published: April 2021

In this study, firstly, the qualitative analysis of big data industry statistical classification system is carried out, and the idea of quantitative verification of big data industry statistical classification system is proposed, so as to determine a scientific and reasonable big data industry statistical classification system. Secondly, the input-output table of big data is compiled. Especially for the “non pure” big data industry sector size measurement. Finally, the contribution of big data industry to economic growth is deduced.
Application Research and Analysis of Geographic Information System in Intelligent City Surveying and Mappinge
Authors: Shan Xiaoli , Wang Yuanyuan , Dong Mingyu , Xia Jie
Published: April 2021

With the rapid development of information, the development of geographic information system (GIS) is also very rapid, and the development of information has laid a solid foundation for geographic information. In the process of practical application, geographic information system has obvious advantages compared with traditional surveying and mapping technology, which can reduce the influencing factors of external environment and has strong anti-interference ability. Establishing and perfecting the information surveying and mapping system is of great significance to the healthy and orderly development of society. In the surveying and mapping of smart city, as a kind of pre construction scanning positioning system, GIS has high measurement accuracy and data processing ability, so it is paid more and more attention by construction enterprises and construction enterprises in urban construction. In this context, this paper discusses some functions of GIS, analyzes its application in Intelligent City Surveying and mapping, which makes GIS more widely used.
Research on Information Construction and Management of Education Management Based on Data Mining
Authors: Zheng Changbao , Zhou Wenrui
Published: April 2021

With the continuous expansion of college enrollment, education has become flexible and diverse. Most colleges and universities are facing the contradiction between the sharp increase in the number of students and the increasing shortage of teaching resources, which has brought unprecedented challenges to education management. More and more teaching resources are pouring into higher education, and at the same time, strict requirements are put forward for higher education management. Data mining technology improves the application of data from low-level query operation to higher-level applications such as decision support, analysis and prediction. How to use information technology to serve the school management and decision-making better and more effectively has become an important symbol to measure the teaching management level and school strength of colleges and universities. The popularization and application of data mining technology is an exploration of informationization of teaching management in colleges and universities under the new situation. This paper summarizes the definition of data mining technology, analyzes its application methods and key points, and further studies and discusses the application of data mining technology in the informationization of teaching management in colleges and universities, in order to promote the development of education.
Path Analysis of University Education Management Based on Big Data Technology
Authors: Huang Jingying
Published: April 2021

Management is also productive. In a way, management is more important than other elements. Education and management of big data is a new stage in the development of higher education management. We can find value through big data. Big data makes universities adopt a more intelligent way to stimulate and produce new wisdom. There are fundamental differences between big data in university education management and big data in the business field. The big data in Colleges and universities take the correlation relation as the breakthrough, finally seeks the special correlation relations. The use of large data, cloud computing and Internet of things technology is an important tool and basis for higher education to improve the efficiency of running a school and to promote the transformation of higher education management from incremental development to quality development. At present, there are not many systematic research results on the combination of big data and university education management in the academic field, and the depth and breadth are not enough, and there is also lack of specific empirical research.
Key Technologies of Large Data Stream System
Authors: Zhang Dong
Published: April 2021

In general, a large number of data streams are regarded as a continuous, continuous and infinite data series. It is used in network monitoring, sensor network, aerospace, meteorological measurement and control, financial services and other fields. Stream computing has the characteristics of large data scale, continuous, fast and disordered data arrival, easy data loss and diverse data processing. In view of these characteristics, there are new challenges in resource scheduling, data distribution and fault tolerance in task management of flow computing. This paper uses multi-layer Association big data rules to process the data wheel. The experimental results show that compared with the traditional task management method, the proposed method can provide the efficiency and accuracy of task management.
Segmented Translation Algorithm of Complex Long Sentences Based on Semantic Features
Authors: Shi Yu
Published: April 2021

The progress of the times is inseparable from communication. If a country wants to develop well, it must learn from each other. Accurate language translation can better let people understand what they want to express. Therefore, language translation is becoming more and more important in the current social communication. Although there is a lot of research on translation, in many cases there will be inaccurate translations. Therefore, finding an accurate translation method is what many people need. Aiming at the problem that the translation of complex long sentences is prone to errors, this paper proposes a sentence segmentation algorithm, which is a method of dividing the long sentence into multiple independent clauses and then translating it. The segmentation algorithm uses the semantic features of the Concept Hierarchical Network (HNC) theory to segment clauses. The segmentation algorithm is integrated with a rule-based baseline translation system. The BLEU value of the integrated translation system reaches 0.1898, which is higher than that before the integration. The system has increased by 30%. Experimental results prove that the proposed method can effectively improve the effect of patent translation.
Correlation Analysis of Influencing Factors of Labor Education Level Based on Neural Network Model
Authors: Yuliang Lu
Published: April 2021

Based on the neural network model, this paper analyzes the correlation of influencing factors of labor education level. This paper compares the income changes of 23-30-year-old workers before and after receiving labor education and the changes of income influencing factors. The results show that the new labor market and the whole labor market show a trend of differentiation before and after education. In the background of the increasing role of the whole labor market education into income, the “value” of the education of the new labor force has declined. Among the various factors that affect the income of the new labor force, some of the education types with the same education level are greatly affected by the negative impact. Gender and work area play a more prominent role, while work experience and other factors have no significant correlation with income. The results have a certain reference value for the correlation study of influencing factors of labor education level.
Research on the Application of Computer Technology in the Field of Art under Big Data
Authors: Zhang Xuelin
Published: April 2021

With the continuous expansion of the field of computer application technology in today’s era, all aspects of life are closely related to the application of computer technology, and people’s work and daily living do not leave the help of computer technology. Therefore, the widespread use of big data has prompted a large number of industries to innovate the methods of computer technology. Computer technology also has an indispensable position in the field of art. The convenience of computer technology operating system greatly improves the efficiency of production and design of works of art. In the process of processing graphics, computer technology makes the work more perfect through the later processing of works of art. This paper summarizes the advantages and concepts of computer technology, and introduces the application of computer technology in different fields of art under big data in detail
The Application of Computer Cartography in Interior Design
Authors: Deng Jun
Published: April 2021

With the continuous development of science and technology, computer software and network information technology are also developing, computer graphics technology has been widely used in various fields. With the continuous improvement of people’s living standard, all kinds of interior design emerge in endlessly, and the quality requirements of interior design have gradually changed. More and more design institutions use computer technology to improve the contents of interior design, so as to continuously improve the quality and efficiency of interior design, and make interior design more standardized and scientific and technological. This paper introduces the computer drawing technology and the concrete application and method in interior design, in order to improve the working method, improve the level of interior design and realize the leapfrog development of interior design in the future work and life.
Research on the Application of Computer-Aided Software in Interior Design
Authors: Yi Lu
Published: April 2021

Computer network technology brings people a cross-epoch change. The computer has changed from a behemoth to a small object that is now easy to carry; from the beginning, the computer can only be used for computing, and now it can search for all kinds of information in the network, not only to calculate any questions, but also to shop directly on the Internet. The development of computer technology also promotes the continuous updating of computer aided software. It is because of the emergence of computer-aided software that the traditional way of interior design has changed obviously. Computer aided design makes interior design more convenient and fast. This paper introduces several common computer-aided software and analyzes the application research measures of computer-aided software in interior design.
Scheduling Optimization for Batch Processing Machines Using Advanced Genetic Algorithm
Authors: Wang Yimeng
Published: April 2021

Semiconductor manufacturing is widely recognized as one of the most complex production processes today, with a great deal of batch processing equipment scheduling problems. At the same time, more and more research and efforts have been made to optimize the process of decision making in scheduling batch processing machines. Based on previous studies that often combine machine learning algorithms with practical production applications, this paper provides a new approach to the scheduling process using an advanced genetic algorithm. Specifically, this paper offers an algorithm concerning both productivity and efficiency, provides the specific steps of the algorithm. Finally, a few possible future directions for the algorithm are discussed.
Evaluation Method of Pipe Corrosion Based on the Natural Frequency I: Corrosion of external surface of pipe
Authors: Chen Yonghong , Ming Tingtao , Shen Bin , Luo Wengye , Wang Han , Zheng Yiting
Published: April 2021

All Corrosion destroys the continuity of the pipe and has an impact on the mechanical properties of the material. It is very important to evaluate the corrosion state of pipe. Based on the damage of corrosion to the mechanical properties of materials, the mass loss factor of corroded pipe is defined, and the elastic modulus of pipe materials is equivalent. According to the modal analysis theory of elastic materials, a modal analysis model of corroded pipe was established, and the relationship between the modal of the corroded pipe and the mass loss factor was analyzed. The results indicate that it is effective and feasible to equivalence the elastic modulus of corroded pipe, at the same time, the model can be used to evaluate the corrosion rate of corroded pipe by monitoring and analyzing the modal.
The Multi-Task Deep Model-Based Pneumonia Detection
Authors: Ai Xingfang , Li Zhongliang , Cao Min , Li Xuechen
Published: April 2021

As a common lung disease, pneumonia affects millions of people worldwide each year and is often detected during physical examination using chest X-ray images (CXRs), which are usually diagnosed by radiologists. This time-consuming task often leads to fatigue-based diagnostic error and cannot be performed in countries or areas lack of radiologists. In this work, we proposed a multi-task learning model: Mt-pnet. We learn from the experience of imaging doctors in the diagnosis of pneumonia, let the network pay attention to the patient’s gender and age information in the diagnosis of pneumonia. The combined information is helpful for the network to learn robust image features for pneumonia diagnosis. At the same time, we also found that using multi-task model is helpful to improve the recall of patients with pneumonia, which has important clinical significance.
Research on Hierarchical Clustering Method of Urban Rail Transit Passengers Based on Individual Portrait
Authors: Xue Jingwen , Si Bingfeng , Cui Hongmeng , Zhu Shiguang
Published: April 2021

The travel behavior of urban rail transit passengers has spatial-temporal differences, which increases difficulties of accurately grasping the evolution of passenger flow and achieving accurate short-term travel forecasts. Therefore, it’s particularly significant to deeply analyze passenger travel spatial-temporal characteristics and to achieve refined passenger classification. Using the AFC data of the urban rail transit system, this paper focuses on the construction of individual travel spatial-temporal portraits. An improved DBSCAN-based method for extracting individual travel spatial-temporal characteristics is proposed, and Python software is used to realize the visual drawing of individual portraits, so as to dig out potential passenger travel rules. Furthermore, a hierarchical clustering method of passengers based on individual portraits is proposed, and the quantified extracted individual travel feature values are clustered through the two-step clustering method, and the refined classification of passengers is realized layer by layer. Finally, the passengers are divided into four categories: definite passengers, flexible passengers, random passengers and one-way ticket passengers. The rationality and accuracy of the classification results are verified from multiple angles. The study clarifies the travel spatial-temporal characteristics of different types of passengers, improves the objectivity of passenger classification, and lays the foundation for short-term travel prediction.
Improved N - Best Multiple Hypothesis Tracking Algorithm
Authors: Li Yong , Xing Xiabin
Published: April 2021

In the tracking process of the multi-hypothesis tracking algorithm, many hypothesis are made about the correlation between the track and the measured values. Although its tracking performance is better than other tracking algorithms, it needs a lot of computation time and memory resources when tracking multiple targets or in environments with large clutter due to exponential growth of hypothesis. In view of this situation, an improved N-Best algorithm is proposed to be applied to MHT. The simulation results show that this method can reduce the computation time and realize the track correlation, so it has certain practicability.
An Identity Authentication Method Based on Multi-modal Feature Fusion
Authors: Chen Jiabo , Cai Linxi , Tu Yuyang , Dong Rui , An Diankun , Zhang Baili
Published: April 2021

At present, many judicial organs have adopted the daily attendance system based on face recognition to strengthen the supervision of community correction personnels. In order to prevent a few personnels from using pre-prepared photos and videos to deceive the face recognition system, this paper proposes an identity verification scheme with liveness detection based on dynamic combination of multimodal features. The main idea is as follows. Firstly, during face verification, the user is required to read out random numbers on the screen. Secondly, generating dynamic combination of speech, voiceprint, lip-reading and other verification methods according to the user’s risk personas, so as to achieve a balance between convenience and security. In addition, in view of the low accuracy of lip-reading recognition in practice, this paper changes the traditional lip-reading recognition based on morpheme to lip-reading recognition based on classifier. By optimizing the interactive content, the distinction of pronunciation between different Chinese characters is increased, and the accuracy of lip-reading recognition is significantly improved.
Iterative parameter estimation of nonlinear systems
Authors: Yin Miao , Zhao Li
Published: April 2021

This paper discusses the identification methods for nonlinear systems. Using the negative gradient search, the gradient based iterative algorithm is derived to determine the parameters of the nonlinear system. In addition, in order to improve the computational efficiency, the gradient-based iterative algorithm based on the model transformation is derived. The basic principle is to transform a complex nonlinear system into a linear or simple nonlinear system. Finally, a numerical example is given to verify the effectiveness of the proposed methods.
Multi-target detection method based on YOLOv4 convolutional neural network
Authors: Liu Jinhui
Published: April 2021

In order to solve the problems of low detection accuracy, false detection and high miss detection rate of small targets in target detection tasks, this paper is a multi-target detection method based on YOLOv4 convolutional neural network. The proposed method is based on YOLOv4. The semantic information of high-level features is first propagated to the low-level network through FPN sampling, and then it is fused with the high-resolution information of the underlying features to improve the detection effect of small target detection objects. The information transmission path from the bottom to the top is enhanced by downsampling the feature pyramid, and finally the feature maps of different layers are fused to achieve relevant predictions. Experiments prove that the method proposed in this paper has good results.
Improved Convolutional Neural Network for Biomedical Text Classification
Authors: Ma Zhenzhen
Published: April 2021

In recent years, the combination of biomedical field and computer field is booming. Obtaining useful information from a large amount of biomedical text information is a research topic of great significance. Convolutional neural network has a good ability to extract useful features, so it is widely used in the field of text classification. In this paper, a novel approach for biomedical text classification based on improved convolutional neural network is proposed to solve the problem that deep convolutional neural network has a large amount of computation and can not perceive the relationship between levels well. In this paper, we use the combination of deep separable convolution and void convolution to improve the convolutional neural network. At the same time, we use the attention mechanism to classify biomedical literature. In addition, focusing loss function is used to improve the imbalance of biomedical texts. Experimental results show that the classification model in this paper is effective for biomedical texts.
Research on the Legal Protection of Personal Information in the Big Data Era
Authors: Deng Xianghua , Yan Meiyuan
Published: April 2021

With the scale and convenience of information storage and transmission, human society has entered the era of big data. In this era, information has become the most valuable and potentially influential resource, and personal information that is closely related to citizens’ daily lives is no exception, and is used by all stakeholders. Improper collection of personal information, fraudulent use of personal information, and malicious use of personal information have disrupted the peaceful life of citizens, thereby threatening personal and property safety issues are gradually exposed. In the era of big data, personal information protection is facing new challenges of data personality shaping and modern power control. Strengthening the protection of personal information is an urgent need in the era of big data.
Lip Reading using Local-Adjacent Feature Extractor and Multi-Level Feature Fusion
Authors: Zhang Chengwei , Zhao Haotian
Published: April 2021

Lip reading is a widely used technology, which aims to infer text content from visual information. To represent lip information more efficiently and reduce the network parameters, most networks will first extract features from lip images and then classify the features. In recent studies, most researchers adopt convolutional networks to extract information from pixels which contain a lot of useless information, limiting the improvement of model accuracy. In this paper, we designed a graph structures and a lip segmentation network to effectively represent changes in the shape of the lips in adjacent frames and the ROI in local frame and propose two feature extractors, named U-net-based local feature extractor and graph-based adjacent feature extractor. We proposed a very challenging dataset to simulate extreme environments, including highly variable face properties, light intensity and so on. Finally, we designed several different levels of feature fusion methods. The experimental results on the proposed challenging dataset show that the model can effectively extract the useful information from content irrelevant information very well. The accuracy of our proposed model is 9.1% higher than that of baseline. This result shows that our proposed model can better adapt to the application of the wild environment.
Design and Implementation of Distributed Call-Center Based on Soft-Switch
Authors: Deng Yanling , Deng Yin
Published: April 2021

Traditional PSTN-based Call-Center fail to meet agent distribution deployments and lower operating costs. With the development of NGN technology, Soft-Switch-based Call-Center has solved the pain points of enterprises. This paper analyzes the special needs of distributed Call-Center system, and on the basis of analyzing and studying Soft-Switch technology, the platform architecture of distributed Call-Center system based on VoIP is given. This paper focuses on the support process of SIP protocol for call control function of Call-Center system, as well as the key equipment in Soft-Switch system. Finally, a practical Soft-Switch system implementation scheme is introduced in conjunction with the project.
Research on Image Feature Extraction of Pavement Crack Disease
Authors: Qiao Heng , Zhang Zhihua , Zhang Xinxiu , Yan Jingping
Published: April 2021

The traditional highway disease detection technology and method are inefficient and can not meet the needs of modern detection. In this paper, the identification and extraction method of pavement crack disease characteristics is proposed. In the crack disease image, the grey image is transformed to highlight the crack information and background colour. Then, the effects of various image enhancement are compared, and a better algorithm template is selected to remove the black and white noise on the grey image, and the image with high accuracy is obtained. Finally, the image is segmented by stretching threshold, and the crack features are extracted by morphological closed operation. Based on ENVI+IDL development platform, an experimental system for pavement crack disease detection is developed. The experimental results show that the experimental system can effectively detect and extract pavement crack diseases and realize batch processing of multiple disease images.
Research on Network Threat and Situation Assessment Method of Electric Power Information System
Authors: Liang Yunhui , Zhang Linghao , Wang Sheng , Zhang Jie , Zhang Juling , Wu Ming
Published: April 2021

With the rapid development of information and communication technology, the national electric power information system has been extensively developed, and the electric power information system is becoming more and more intelligent, complicated and networked. At the same time, the complexity of the power information system has also brought about the problem of network security, and various network threats have put forward higher requirements for the network security of the power information system. How to evaluate the cyber threat of power information system has become an important work of power information system network security. This article uses the network threat attribute indicators that the power information system faces, and combines the situation assessment method to conduct a situation assessment on the network security of the power information system.