bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thinking on the construction of big data service for public security in megacities -- a case study of Chongqing
Authors: Liu Ge 
Published: May 2020

Abstract
According to the national outline of development of Big Data, combined with the current situation of big data development in Chongqing and the action plan of urban development in Chongqing, this paper, from the perspective of Chongqing public security, analyses the social risks, subjective and objective conditions related on big data, puts forward the Big Data construction goal of Chongqing Municipality public security, and gives the construction and development strategies and suggestions for the implementation of the Big Data project.
Deep Feature Attention and Aggregation for Real-Time Head Semantic Segmentation
Authors: Zhang Zhiqin , Zhang Bo 
Published: May 2020

Abstract
This paper proposes a mobile CNN(Convolutional Neural Networks) architecture named FAANet(Feature Attention Aggregation Net), which focused on self-attention and feature aggregation for real time head semantic segmentation using limited computation resource. The proposed network is based on a single lightweight backbone cnn network and aggregates discriminative features through multiple different scale feature maps, and the different feature maps are fused using self-attention sub-block. Using the proposed multi-scale feature communication and propagation, FAANet substantially reduces the size of model, but still achieves big receptive field and strengthen the generalization ability, which achieves a balance between the computation cost and performance. Experiments on head segmentation dataset demonstrate the improved performance of FAANet with 10 times less FLOPs and 3times faster than the existing state-of-the-art fast semantic segmentation methods and the proposed method can achieve comparable accuracy. Specifically, when computed on one NVIDIA Titan X card, it can achieve 98.3% Mean IOU on our mixed test dataset with only 1.2 GFLOPs and 100 FPS while inferring on a 1024*1024 input image.
Rule Extraction of Generalized Incomplete Variable Multi-granularity Rough Set
Authors: Mo Jing-Lan 
Published: May 2020

Abstract
According to the advantages and disadvantages of feature relation and multigranularity decision rough set in generalized incomplete information system, a multi-granularity rough set model based on feature relation is proposed. Firstly, a variable multi-granularity rough set model is proposed, and an optimistic and pessimistic variable multi-granularity decision rough model based on feature relation is constructed. By combining variable multi-granularity and approximate distribution reduction, the variable multi-granularity approximate distribution reduction is proposed, and all the decision rules and possible decision rules are obtained. The results show that the method of variable multi-granularity approximate distribution reduction and rule acquisition is more reasonable and effective than the original method of single granularity approximate distribution reduction and decision acquisition.
Analysis of Tourism City Image Based on Big Data of Network Text—Take Guangzhou as an Example
Authors: Yang Sen , Zhang Ling , Xu Liping 
Published: May 2020

Abstract
Based on 16979 tourist reviews of six scenic spots in Guangzhou by ctrip.com, using the triple process of open coding, spindle coding and selective coding based on grounded theory, it is found that the tourist image of Guangzhou is mainly composed of cognitive image, emotional image and conative image; the tourists are satisfied with a high degree of willingness to revisit and recommend to their relatives and friends; the tourists are emotional towards Guangzhou tourism High evaluation and strong willingness of tourists to travel.
Vehicle-specific retrieval based on aerial images
Authors: Yang Guoliang , Tang Zhigang , Huang Jianchen 
Published: May 2020

Abstract
UAVs(Unmanned Aerial Vehicle) are currently widely used in civil and military fields. Collecting ground information through UAVs is their main application direction. This paper proposes a vehicle retrieval system based on aerial images, which can retrieve the corresponding target vehicle according to the set conditions. For the retrieval algorithm, we optimized its feature extraction network based on YOLO v3, and optimized it as a two-way residual based on the original residual module to improve its ability to detect small targets. Considering that the position deviation of the prediction frame in the actual detection will greatly affect the detection result, the GIoU position calculation index is adopted to improve the network’s sensitivity to the position information. At the same time, retrieval conditions such as vehicle type and color are added on the basis of detection, so that the model can complete the retrieval of specific vehicle targets. The test results of the finally optimized network on the VEDAI dataset reached 91.2%mAP.
Classification of Diabetic Retinopathy Using Adversarial Training
Authors: Wu Dawen , Liu Shishi , Ban Jian 
Published: May 2020

Abstract
In recent years, the classification of medical images has become more and more important. With the help of the deep learning approach, the classification accuracy of diabetic retinopathy has been greatly improved, and it has brought great benefits to the residents living in the suburbs. However, the researchers found that these neural network models became extremely vulnerable when confronted with an adversarial example. Specifically, some minor changes to the samples can fail the model immediately. In this paper, we use adversarial training methods instead of traditional training methods to improve the model robustness against adversarial example. Experiments showed that using this method in APTOS data set the adversarial accuracy increased from 43% to 83%.
Implementation of Distribution Network Integrated Blackout Management Platform Based on Business Central Platform
Authors: Zhang Jiang-Feng , Zhao Fu-Quan , Ye Su , Zeng Liang-Liang , Wang Zi-Xiang 
Published: May 2020

Abstract
With the rapid development of information technology in power grid enterprises, there are many information systems in relevant business departments. It is difficult to avoid the dilemma of duplication of business functions and waste of data resources because of the “chimney” function development model oriented to business lines. Aiming at the decentralized management status of data related to blackout business such as smart grid dispatching technology support system, production management system, distribution automation system and marketing system, based on the system architecture of business center, this paper takes integrated blackout intelligent optimization as the construction goal, and optimizes blackout inspection from the standardisation of data. Repair plan, improve the coordination efficiency of relevant business departments, avoid repeated blackouts, improve the reliability of power supply, and provide decision support for power grid enterprises in blackout management.
An approach for monitoring sand mining based on sound feature
Authors: Zhou Qingmei , He Xiping 
Published: May 2020

Abstract
In order to strengthen the management of sand excavation in river courses and prevent the occurrence of illegal sand mining activities, this paper proposes an approach for monitoring sand mining based on sound. Firstly, Mel Frequency Cepstral Coefficients (MFCCs) abstractor and Autoencoder are combined to extract features of every frame of a sound sequence, and then each frame of the sound sequence is classified by a specific classifier. Finally a voting strategy is used among the frames to determine the final category of the sound sequence. Experiments show that whether the classifier is SVM, KNN, or BP neural network, the result of combined features is better than the result of features extracted by the MFCC abstractor. Therefore, it is feasible to use the artificial intelligence method based on sound features extracted through MFCC abstractor and Autoencoder to monitor sand mining.
Appearance-based Gaze Estimation Using Multi-task Neural Network
Authors: Liu Mihan , Dai Huanhuan 
Published: May 2020

Abstract
In order to improve the gaze estimation accuracy through using the information in the eye image more adequately, an appearance-based gaze estimation neural network EyeNet has been proposed in this article. On the one hand, by decomposing the main task into two subtasks, this network could gain more information during the training stage. On the other hand, EyeNet could extract features in the image more efficiently by adding an auxiliary task which is detecting the iris center and eye ball center of the eye. Experiments show that by using these two tricks, the error decreased from 5.42 degree to 5.16 degree.
The Research Status and Hotspots in the Domain of Smart Learning in China from 2012-2019
Authors: Wang HaiBin , Ming Zijing , Zhang Mengjie , He Jiaxiang , Cheng Lin , Qian Zhou 
Published: May 2020

Abstract
To explore the research status and hotspots in the domain of Smart learning in China, 118 related articles form the China National Knowledge Infrastructure (CKNI)were analyzed by the software of CiteSpace. The results showed that: (1) the area of smart learning in China began in 2012 and shows an upward trend year by year from 2012 to 2017, and the number of articles reached the historical peak in 2017 with 30 articles, but it showed a downward trend after 2017. Zhiting Zhu, Beijing Normal University and E-education Research topped the lists of contributing authors, organizations and publications respectively. (2) “smart learning”, “strategy”, “smart learning environment” and “smart education” were the top four largest clusters on the area of smart learning in China from 2012-2019.
RETRACTED: Research on the application of big data in the management and service of College Students
Authors: Sun Wenhua , Wu Lifeng , Lu Yang , Zha Xiaohong , Cui Mingyuan 
Published: May 2020

Abstract
The explosive growth of information and the maturity and application of cloud computing, data mining and analysis technology mark that today’s society has ushered in the era of big data. College student management and service work are practical, but the traditional way of it is mostly manual and single qualitative management, which has been unable to meet the growing number of students demands, gradually revealing lots of problems like low efficiency, slow speed, and poor quality. The emergence of big data will effectively improve this problem. College students’ education management workers will be able to accurately control the ideological and behavioral dynamics of students, properly carry out public opinion analysis, and promote the personalized learning and development of college students.
Research on Semantic Segmentation of Portraits Based on Improved Deeplabv3 +
Authors: Zhang Kaihui , Liu Xianhui , Chen Yufei 
Published: May 2020

Abstract
At present, semantic segmentation is one of the hottest research directions in the field of computer vision, and the Deeplab series is one of the best neural network models in semantic segmentation. Based on the original Deeplab-v3 + neural network model, this paper makes a series of improvements to make it perform better on semantic segmentation of portraits: 1. Add channel attention module to speed up the convergence speed of model training and improve segmentation accuracy. 2. Improve the original AtrousSpatial Pyramid Pooling (ASPP), adjust the receptive field of the network, and improve the segmentation accuracy. Finally, this paper compares the segmentation performance of different semantic segmentation network models on human-parsing dataset and proves that the proposed neural network structure has better segmentation effect.
Application of Activity-on-arrow Network in Product Development Management
Authors: Li Linsen , Zhou Shanping , Deng Ting 
Published: May 2020

Abstract
Product development management is the core work of product preparation, which is restricted by many factors and requires regular adjustment of plans and real-time dynamic management. Taking the general process of product development management as an example, this paper adopts activity-on-arrow network in operational research to develop product management, and then draws and calculates the composition, key circuit and time parameters. Afterwards, the construction period is shorten and the consumption of cost is reduced through adopting the activity-on-arrow network in developing product management to achieve the design optimization and calculation of product development management, so as to save cost and improve economic efficiency of enterprises.
Construction of Digital Library Precision Service System under Big Data Environment
Authors: Meng Luyang , Zhang Bin , Wang Di , Jun  
Published: May 2020

Abstract
With the promotion of Internet communication technology and information technology, university digital libraries are also in the process of continuous reform and development. With the passage of time, the information resources of digital libraries accumulate more and more, coupled with the continuous update of computer technology and social networks, users will generate more and more information resources. The rapid development of communication and Internet technology in the era of big data brings opportunities to digital library’s accurate service, and at the same time, it also makes it face huge challenges. The library should rely on the massive book resources platform, combine the big data processing technology with the digital library service concept, and actively explore the data acquisition, sorting and storage technology, so as to provide more effective and humanized services for users. This paper introduces the goal of precision service of Digital Library Based on big data, expounds the characteristics of precision service of Digital Library Based on big data, and puts forward the construction method of precision service system of Digital Library under big data environment.
Computer Communication Technology and Electronic Information in Artificial Intelligence Application
Authors: Yang Yi , Fu Ying Feng 
Published: May 2020

Abstract
In the context of stable social and economic development, the core position of mankind has gradually emerged. People’s behavior is controlled by their consciousness, which in turn creates a good living environment. With the development of science and technology, manpower has been largely liberated. Social productivity is constantly growing, and socio-economic order is constantly being reformed. To take full advantage of technological innovation, artificial intelligence is the most advanced technology. Domestic big data technology is rapidly innovating, and computer communication technology is increasingly used in the field of artificial intelligence. Communication and electronic information technology are important supports for the spread of artificial intelligence and can process various data in a timely manner. Process the complex data information and upload the processing results to the artificial intelligence platform. Build different data matrix models, analyze data parameters, and finally apply them to the field of artificial intelligence. The organic integration of computer communication technology and electronic information technology to successfully complete various tasks. It fully demonstrates the close connection between information technology and artificial intelligence, and provides theoretical support for the subsequent work. This article focuses on the application of computer communication technology and electronic information in artificial intelligence, and puts forward comments and suggestions based on actual conditions.
Research on Japanese Teaching Analysis System Based on Artificial Intelligence
Authors: Yao Jing 
Published: May 2020

Abstract
As one of the current popular technology, artificial intelligence has an important impact on education. Therefore, teachers need to strengthen the use of artificial intelligence equipment in teaching so that it can play its due role in education. Japanese talents are the key required by the current country. Teachers need to analyze their Japanese mastery skills in teaching to grasp the actual learning situation of students. At this time, teachers can use artificial intelligence Japanese teaching analysis system. This article mainly researches the Japanese teaching analysis system based on artificial intelligence, hoping to provide help for Japanese teaching.
Aesthetic improvement of sheet molding compound (SMC) composite plate by using natural fiber reinforced polymer (NFRP) like jute fiber reinforced epoxy matrix composite coating
Authors: Kekare Sujay , Jogi B F , Bhise Vishal , Nair Anoop 
Published: May 2020

Abstract
In current scenario, the use of composite materials in our lives has become very common and these are found in our furniture, transportation, education, sports, building and infrastructural system. Compared with conventional materials such as metal, plastics and woods, composite materials offer specific strength, specific stiffness and tailored material properties. Composites mainly classified as metal matrix, ceramic matrix and polymer matrix composites. Polymer matrix composites are used for low temperature applications such as automotive body panels, crashworthiness, bumpers etc. Mainly carbon, glass and aramid fibers are used as reinforcement for these applications. Nowadays, natural fibers such as flax, jute, coir, cotton etc. are also used for decorative and semi structural applications in automotive and furniture industry. Polymer matrix composites are mass produced by use of sheet molding compound (SMC) compression molding technology. SMC technology has been used in manufacturing automobile parts, electrical insulation cover applications, partition panels and many semi structural applications etc. The current trend of improving the surface appearance and mechanical properties of SMC’s can lead to even more applications such as exterior, structural parts and also decorative parts in automobile, furniture and other domestic applications. Automotive interior dashboard parts, door panel parts and other interiors need to be aesthetically appealing so that it feels pleasant to seat in the car. In this work, hand lay-up process is used for coating onto the SMC compression molded plate with jute fiber reinforced epoxy composite. Uncoated and coated SMC plates are compared by various characterization methods such as tensile, compression, hardness and surface roughness. Also visual appearance and gloss test were performed. Coated SMC plate has improved tensile strength, surface finish, gloss value and visual appearance. There is almost same compression strength and Rockwell hardness value obtained.
An experimental and numerical study of air flow pattern and temperature distribution of angular air distribution system in hospital operation theatre
Authors: Rahate Swati , Sarode Avinash 
Published: May 2020

Abstract
It is necessary to characterize the air flow pattern and temperature distribution in Operation Theatre (OT) to optimize the indoor air quality to enhance the high performance of hospital. Mostly Laminar air flow system is used in OT, which covered the surgical zone. The temperature draft observed between surgical and nonsurgical area which result in uncomfortable environment to patient and surgeon. To overcome such problem Angular Air Distribution (AAD) system is designed which covered the both area of OT. The performance of AAD system with varying inlet diffuser angle at constant inlet velocity on Scale model of OT is investigated with the help of CFD software and compared with experimental setup. Detail experimental investigation is done on a scale model of OT with the help of a smoke test and camera target method (CTM). Both numerical and experimental results showed a similar pattern of air and temperature distribution for the various design configurations.
A Review on Biological Building Blocks and its Applications in Nanotechnology
Authors: Jayachadran Shweta , Khetan Dhrriti , Pestonjamasp Kaizad , Sharma Aatur , Joshi Girish 
Published: May 2020

AbstractBiological building blocks are the basis of living organisms and its potentials are gaining more attention over a wide range of applications. major biological building blocks that exist in the universe have been taken into consideration in this paper, which are proteins, lipids, carbohydrates and nucleic acids. Due to their small size, they are such molecules which can be considered by the Nano level structures therefore have been incorporated in various applications of nanotechnology and microbiology. Taking into consideration the structural and chemical properties of these biological building blocks, further application on each individual biological building block has been covered in multiple fields, but mainly in the medical and pharmaceutical industry. The applications also concern optical imaging, precision measurement of biomolecules, Nano biomaterial synthesis and biosensors. Despite the various advantages of these applications like improved efficiency of various processes, the shared limitations of these applications stand to be difficult technique for synthesis and development due to Nano size dimension consideration. Thus, the future scope of use of biological building blocks in nanotechnology is very ambitious and promising.
Automotive vehicle clutch engagement characteristics for different types of force trajectories
Authors: Raghuvanshi D , Pare Vinod , Chouksey M , Rawal B R 
Published: May 2020

Abstract
Vehicle driveline of automobile, which transmit engine energy to the wheels, is complex system with nonlinear behavior. In manual transmission clutch engagement performance depends upon driver’s skill and is significantly affected by traj ectory of clutch force during engagement process. In this work different types of clutch force trajectories are analyzed based on engagement performance which can be incorporated in automated manual clutch system. A driveline of a vehicle is modeled using multi body dynamics software and simulation were carried out for different type of force trajectories i.e. linear, parabolic and spline, which is followed by clutch force during engagement. The results of simulation were used to analyze the quality of clutch engagement and vehicle performance by looking into clutch lock-up phase and vehicle launch. The clutch lock time and clutch lock speed for various types of trajectories were calculated and compared. These results were also compared with analytical results reported by researchers. The results would be useful in selecting appropriate type of clutch actuating force trajectories for automation of clutch system of automobiles.
A review on characteristics of natural fibre composite
Authors: Prakash Chaudhari Chetan , Bhole Kiran 
Published: May 2020

Abstract
Since the last we saw huge growth in innovation and research in field of natural fibre composite (NFC). Availability of Natural Fibres (like coir, abaca, banana, jute, sisal, cotton) are huge in India. It is not surprising that the natural fibre composite is attracting the researchers all around the world because of superiority of its compared to other fibre composites and their capabilities in wide range of applications. The present study aims at various applications of natural fibre composite and their mechanical characteristics. This review also provides the various aspects that affects the mechanical characteristics of natural fibre.