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smart Vehicle-Zone: Device to Device Handoff Techniques in Vehicle Ad Hoc Networks 2nd

Smart Vehicle-Zone: Device to Device Handoff Techniques in V...

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2nd international conference on Communication, Networks and computing, CNC 2020

作者： Kulanthaiyappan, Sivakumar Chellaih, Chandrasekhar Department of Computer Science Periyar University Tamilnadu Salem India

ISBN: (纸本)9789811688959

Nowadays, the time-slot synchronization of rapid network devices offers an excellent strategy for 5G networks. The intelligent vehicle communications, mainly so that a massive of rapid changing devices on the different cell’s with the edge, can be managed concurrently. The transport technologies with their updated information, the vehicle network has been quickly established by numerous cluster or zone connections, which link multi-tier layers, clouds, loads, etc. So, the knowledge on the device selection of related objective is missing in this scenario. It’s difficult to obtain rapid information about the network and several-variety of equipment in advance. The awareness of accessibility, charge, and active handoff sessions for the proposed system will be chosen in the same way. This paper has a collaborative transfer method using D2D (Device to Device) multi-cast and D2D zones to tackle extreme resource contention caused by devices with high density and mobility. This data transfer brings vehicles, sensors, equipment, software, and roadside systems to a perfect zone link. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Vehicles

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Detecting False Messages in the smartphone Fault Reporting System 4th

Detecting False Messages in the Smartphone Fault Reporting S...

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4th international conference of Reliable Information and Communication Technology (IRICT)

作者： Rajoo, Sharmiladevi Magalingam, Pritheega Samy, Ganthan Narayana Maarop, Nurazean Idris, Norbik Bashah Shanmugam, Bharanidharan Perumal, Sundaresan Univ Teknol Malaysia Razak Fac Technol & Informat Skudai Malaysia Int Islamic Univ Malaysia Gombak Malaysia Charles Darwin Univ Sch Engn & Informat Technol Casuarina Australia Univ Sains Islam Malaysia Fac Sci & Technol Gombak Malaysia

ISBN: (纸本)9783030335823;9783030335816

The emergence of the Internet of Things (IoT) in smart City allows mobile application developers to develop reporting services with an aim for local citizens to interact with municipalities regarding city issues in an efficient manner. However, the credibility of the messages sent rise as a great challenge when users intentionally send false reports through the application. In this research, an evidence detection framework is developed and divided into three parts that are a data source, IoT device's false text classification engine and output. Text-oriented digital evidence from an IoT mobile reporting service is analyzed to identify suitable text classifier and to build this framework. The Agile model that consists of define, design, build and test is used for the development of the false text classification engine. Focus given on text-based data that does not include encrypted messages. Our proposed framework able to achieve 97% of accuracy and showed the highest detection rate using SVM compared to other classifiers. The result shows that the proposed framework is able to aid digital forensic evidence experts in their initial investigation on detecting false report of a mobile reporting service application in the IoT environment.

关键词： Internet of Things smartphone Application Reporting services smart City Text classifiers

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Understanding of Time-Based Trends in Virtual Learning Environment Stakeholders' Behaviour 21st

Understanding of Time-Based Trends in Virtual Learning Envir...

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21st international conference on Interactive Collaborative Learning (ICL) / 47th IGIP international conference on Engineering Pedagogy - Teaching and Learning in a Digital World

作者： Drlik, Martin Constantine Philosopher Univ Nitra Tr A Hlinku 1 Nitra 94974 Slovakia

ISBN: (纸本)9783030119324;9783030119317

The analysis of data collected from the interaction of users in the virtual learning environment attracts much attention today as a promising approach for advancing the current understanding of the learning content development, learning process in general as well as VLE stakeholders' behaviour. The learning analytics research has not frequently focused on analysing of time-based trends in VLE stakeholders' behaviour or their preferences in the same VLE over different years of deployment, as well as on analysing of temporal trends in the selection of different activity types over a typical period. Therefore, the paper deals with several methods, which can be used for analysing VLE stakeholders' behaviour over several academic years. The paper introduces a case study, which shows that several analytical and data mining methods can give useful insight into the changing behaviour of the stakeholders of the VLE over a longer period. Finally, the paper summarises the obtained results and discusses possible implications and limitations of the applied approach from different perspectives in the context of the management of the virtual learning environment, VLE stakeholders and educational content improvement at the institutional level.

关键词： Learning analytics Log analysis Virtual learning environments User behaviour Time-based trends analysis

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Qualitative Collaborative Sensing in smart Phone Based Wireless Sensor Networks 18th

Qualitative Collaborative Sensing in Smart Phone Based Wirel...

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Joint conferences on 18th international conference on intelligent Systems Design and Applications, ISDA 2018 and 10th World Congress on Nature and Biologically Inspired computing , NaBIC 2018

作者： Thomas, Wilson Madhusudhana Reddy, E. Research and Development Center Bharathiar University Coimbatore India Department of CSE Guru Nanak Institutions Technical Campus IbrahimpatnamTelangana India

ISBN: (纸本)9783030166595

Collaborative sensing has become a novel approach for smart phone based data collection. In this process individuals contributes to the participatory data collection by sharing the data collected using their smart phone sensors. Since the data is gathered by human participants it is difficult to guarantee the Quality of the data received. Mobility of the participant and accuracy of the sensor also matters for the quality of data shared in such environment. If the data shared by such participants are of low quality the purpose of collaborative sensing fails. So there must be approach to gather good quality of data from participants. In this paper we propose a Truth Estimation Algorithm (TEA) to identify the truth value of the data received and filter out anomalous data items to improve the quality of data. To encourage the participants to share quality information we also propose an Incentive Allocation Algorithm (IAA) for qualitative data collection. © 2020, Springer Nature Switzerland AG.

关键词： Wireless sensor networks

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Innovation of self-service system of college mental health in the age of big data

Innovation of self-service system of college mental health i...

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Zhang, Tiantian Chen, Xu Jiangxi Vocational College of Mechanical & Electrical Technology Nangchang China Nanchang University College of Science and Technology Nanchang China

ISBN: (纸本)9789811525674

College students must not only master the professional knowledge they have learned, but also learn to interact with others. Due to various pressures, the psychological burden of students is also increasing. The service to students’ mental health is imminent. In the era of big data, information is diversified, so it is necessary to mine the information suitable for students’characteristics from the massive information. In view of the above problems, in the era of big data, this paper proposes data mining technology and mental health self-service system in Colleges and universities to achieve innovative service effect. By applying K-means clustering algorithm to data mining, it is found that 58.6% of the students choose self-resolution or let it go naturally when they encounter psychological problems. This paper further gives suggestions on the object-oriented, content and technology of mental health self-service in order to realize the innovation of mental health self-service system in Universities in the era of big data and provide reference for mental health service. © Springer Nature Singapore Pte Ltd. 2020.

关键词： data mining

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Industrial engineering major manufacturing dig data application analysis direction curriculum

Industrial engineering major manufacturing dig data applicat...

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Huang, Jui-Chan Shu, Ming-Hung Chung, Kun-Chen Yango University Fuzhou350015 China Department of Industrial Engineering and Management National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan

ISBN: (纸本)9789811525674

Based on the general application of big data and the increasingly mature background of cloud computing technology, this paper, guided by the knowledge system of industrial engineering, made a preliminary analysis on how Chinese manufacturing enterprises optimize their production management by industrial engineering. Its central idea is that manufacturing enterprises should combine the basic methods of industrial engineering with big data and cloud computing technology to improve the efficiency and reliability of production. In terms of research methods, this paper proposes and improves bp-miv algorithm to rank how big data technology is applied to industrial engineering manufacturing field. On the one hand, the research in this paper provides ideas for the course design of manufacturing based on big data. On the other hand, the improvement of bp-miv algorithm overcomes the defects of sample size and parameter selection of the traditional bp-miv algorithm. Through the improvement idea of "first classification, then calculation of difference", the paper makes a better sorting. All in all, this article made in manufacturing large data meaning, big data meaning and manufacturing technology on the basis of the data, this paper discusses the manufacture large data application analysis is an important developing direction of industrial engineering discipline, is proposed based on industrial engineering professional training manufacture large data application analysis of curriculum system and gives the manufacture process of large data application oriented curriculum content analysis technology. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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ACETA: Accelerating Encrypted Traffic analytics on Network Edge

ACETA: Accelerating Encrypted Traffic Analytics on Network E...

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IEEE international conference on Communications (IEEE ICC) / Workshop on NOMA for 5G and Beyond

作者： Manning, Derek Li, Peilong Wu, Xiaoban Luo, Yan Zhang, Tong Li, Weigang Elizabethtown Coll Dept Comp Sci Elizabethtown PA 17022 USA Univ Massachusetts Lowell Elect & Comp Engn Lowell MA USA Intel Corp Santa Clara CA 95051 USA

ISBN: (纸本)9781728150895

Applying machine learning techniques to detect malicious encrypted network traffic has become a challenging research topic. Traditional approaches based on studying network patterns fail to operate on encrypted data, especially without compromising the integrity of encryption. In addition, the requirement of rendering network-wide intelligent protection in a timely manner further exacerbates the problem. In this paper, we propose to leverage x86 multicore platforms provisioned at enterprises' network edge with the software accelerators to design an encrypted traffic analytics (ETA) system with accelerated speed. Specifically, we explore a suite of data features and machine learning models with an open dataset. Then we show that by using Intel DAAL and OpenVINO libraries in model training and inference, we are able to reduce the training and inference time by a maximum order of 31x and 46x respectively while retaining the model accuracy.

关键词： Encrypted Traffic Analysis DAAL OpenVINO Edge computing uCPE

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Learning analytics Based on Multilayer Behavior Fusion 13th

Learning Analytics Based on Multilayer Behavior Fusion

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13th international conference on Blended Learning (ICBL)

作者： Yang, Yu Cao, Jiannong Shen, Jiaxing Yang, Ruosong Wen, Zhiyuan Hong Kong Polytech Univ Dept Comp Kowloon Hong Kong Peoples R China

ISBN: (纸本)9783030519681;9783030519674

Learning analytics is the measurement, collection, and analysis of data about learners and their contexts for the purposes of understanding and optimizing the process of learning and the underlying environment. Due to the complex nature of the learning process, existing works mostly focus on the modeling and analysis of single learning behavior and thus bears limited capacity in achieving good performance and interpretability of predictive tasks. We propose a research framework for learning analytics based on multilayer behavior fusion which achieves significantly better performance in various tasks including at-risk student prediction. Results of extensive evaluation on thousands of students demonstrate the effectiveness of multilayer behavior fusion. We will report the insights about mining learning behaviors at different layers including physical, social and mental layers from the data collected from multiple sources. We will also describe the quantitative relationships between these behaviors and the students' learning performance.

关键词： Learning analytics Multilayer behavior extraction At-risk student prediction Automatic text scoring

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The manufacturing transfer in Shanghai based on big data

The manufacturing transfer in Shanghai based on big data

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Yu, Dongyu Shanghai University of Engineering Science Shanghai200437 China

ISBN: (纸本)9789811525674

Big data is the basis of intelligent manufacturing. Its application in mass customization of manufacturing includes data collection, data management, order management, intelligent manufacturing, customized platform, etc. The core is customized platform. Big data applications can be implemented with custom data reaching an order of magnitude. Through the mining of big data, we can achieve more applications such as popular forecasting, accurate matching, fashion management, social applications, marketing push and so on. With the economic transformation of Shanghai and the gradual maturity of the economic environment in other parts of the country, the trend of manufacturing transfer from Shanghai has increased. This transfer will generate economic development in Shanghai and production services that have a certain dependence on manufacturing. What impact? The transfer of manufacturing does not mean that the Shanghai region does not attach importance to manufacturing, but rather promotes the transformation and upgrading of the manufacturing industry and the development of high value-added industries. So what is the overall industrial structure and industrial structure in Shanghai? What is the degree of transfer and impact of manufacturing? Based on the data of Shanghai Statistical Yearbook and Statistical Bulletin, this paper uses location entropy, regional specialization and agglomeration index to measure the direction and degree of manufacturing industry transfer. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Manufacture

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Innovation of "Internet + English" teaching mode driven by big data

Innovation of "Internet + English" teaching mode driven by b...

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Li, Yongxin Department of Textile and Clothing Engineering Shandong Vocational College of Light Industry ZiboShandong255300 China

ISBN: (纸本)9789811525674

With the continuous promotion of the age of big data, "Internet + education" has further promoted the innovation and development of the English education model in China. Using big data to teach has become a learning trend, and also meets the needs of the times, ensuring the same pace of learning with the domestic and foreign society, and cultivating compound talents in line with the needs of the times. Taking English education in higher vocational colleges in China as the research object, combined with the status of English teaching in China, the reform of English teaching from the angle of big data information technology is analyzed, with a view to finding out effective and feasible English teaching methods and strategies, so as to further improve the English teaching effect and strengthen the communication ability and the overall quality of students in higher vocational colleges. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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