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共 3239 条记录，以下是321-330 订阅

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Exploring Psychosocial Effects of the COVID-19 on University Students Using Visual analytics

Exploring Psychosocial Effects of the COVID-19 on University...

引用

2021 IEEE international conference on Innovative computing, intelligent Communication and smart Electrical Systems, ICSES 2021

作者： Rahman, Mosiur Akter, Sharmin Kabir, Parizatbinta City University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665435215

The coronavirus disease of 2019 (COVID-19) eruption has perpetrated desolation on educational systems all across the globe. We conducted a fast longitudinal study to find, evaluate, and synthesize research on the repercussions of this epidemic on university sophomores' psychological disorders. We created an interactive simulation to gain a better understanding of the intellectual well-being of university students. Collaborative boards analyze and exhibit actual data as visualizations, statistics, and prose, with a variety of user involvement possibilities. The widgets make it possible to derive meaningful data and present it in a simple and easy-To-understand style. We created an interactive statistics interface to show not only just the latest trends but also crucial metrics and forecasts for the future fortnight. Our panel is simple to use and optimized for effectiveness. It can forcibly temporize values and deploy on any remote server. In this study, we have compared data of pre and during COVID. The data are divided into four categories such as 1) educational impact, 2) family pressure, 3) social and mental health, and 4) stress. Our study found that during prevalent psychological impact is more negative than pre-stage. © 2021 IEEE.

关键词： Coronavirus

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Determining Spatial Co-Location Graph Influencing Factors using Mobile Applications data 3

Determining Spatial Co-Location Graph Influencing Factors us...

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3rd international conference on intelligent computing in data Sciences (ICDS)

作者： Radzi, Nur Fadzilah Mohamad Hoong, Poo Kuan Chua, Hiang-Kwang Norazman, Noor Fatin Atiqah Axiata Digital Advertising Data Sci & Engn Kuala Lumpur Malaysia

ISBN: (纸本)9781728100036

With the recent explosion of smart phone users and the usage of mobile applications, it is undeniable that mobile applications are rich data sources for data mining. In the recent studies conducted by Statista, for 2016, the number of smart phone users is forecast to reach 2.1 billion while the number of mobile phone users in the world is expected to pass the five billion mark by 2019. The ownership of smart phones also leads to the rise of mobile application usage where most of the mobile app usages help users to manage life activities, increase productivity, and constantly stay connected while on-the-go. With permission granted, some mobile applications provide devices location with reasonable high accuracy. Spatial information derived from these mobile applications allow better understanding of human lifestyle behaviors as well as determine the social influence patterns. In this paper, we investigate factors that contribute to spatial co-location graph data mining patterns for the period of three months data (October to December 2018) for three South-East Asia countries, namely Malaysia, Singapore and Thailand. Devices that are co-located are defined by determining two or more devices are appeared in close proximity within a predetermined range of distance at the same time frame. Based on these co-located devices, spatial co-location graphs were constructed to analyze factors that influence graph.

关键词： social influence co-location social advertising social network

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Fog computing for smart Grid Development and Implementation

Fog Computing for Smart Grid Development and Implementation

引用

2019 IEEE international conference on intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2019

作者： Palanichamy, Naveen Wong, Kiing Ing Multimedia University Faculty of Computing and Informatics Cyberjaya Malaysia Curtin University Faculty of Engineering and Science Miri Malaysia

ISBN: (纸本)9781538695425

The smart Grid (SG) is the emerging energy systems that are enticed by smart devices and entities to support its control and monitoring. The SGs' core challenge is how to efficiently utilize different types of smart front-end devices, such as smart meters and power assets, and process the huge volume of data from these devices. Cloud computing (CC) provides flexible services and resources to comply with SG application's computational requirements. Although the CC model is considered efficient for SG, the Quality of Experience (QoE) requirements, such as energy consumption, latency, bandwidth and network cost, for SG services are not guaranteed. Fog computing (FC) reaches the edge of a network computing providing low latency, latency-sensitive analytics and location awareness to satisfy the critical SG application's mission requirements. The aim of this work is to comprehend FC applicability to interplay with the cloud support, thus enabling to develop a new range of latency-free utilities in real time. in this paper, we provide an in-depth survey on various fog computing approaches for smart grid architecture. Also, the current state of research on the development of smart grids is presented in this survey. © 2019 IEEE.

关键词： Fog computing

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Construction and Application of intelligent Campus in Colleges and Universities Under the Background of Big data

Construction and Application of Intelligent Campus in Colleg...

引用

international conference on intelligent Systems Applications in Multi-modal Information analytics, 2019

作者： Jia, Yanmei China West Normal University NanchongSichua637002 China

ISBN: (纸本)9783030157388

With the advent of the era of "Internet plus", information technology in Colleges and universities is facing unprecedented new situations and new challenges. intelligent campus is a new stage in the development of educational informatization. This paper analyses the connotation and characteristics of smart campus, puts forward the idea of building smart campus, and takes S University as an example to introduce the specific application of smart campus. Colleges and universities should take the construction of intelligent campus as an opportunity to continuously promote the realization of educational modernization. © 2019, Springer Nature Switzerland AG.

关键词： Informatization

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IoT system accomplishment using blockchain in validating and data security with cloud 4

IoT system accomplishment using blockchain in validating and...

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4th international conference on IoT in Social, Mobile, analytics and Cloud, ISMAC 2020

作者： Solomon Doss, J. Kingsleen Kamalakkannan, S. Department of Computer Science Chennai India

ISBN: (纸本)9781728154640

In a block channel IoT system, sensitive details can be leaked by means of the proof of work or address check, as data or application Validation data is applied on the blockchain. In this, the zero-knowledge evidence is applied to a smart metering system to show how to improve the anonymity of the blockchain for privacy safety without disclosing information as a public key. Within this article, a blockchain has been implemented to deter security risks such as data counterfeiting by utilizing intelligent meters. Zero-Knowledge Proof, an anonymity blockchain technology, has been implemented through block inquiry to prevent threats to security like personal information infringement. It was suggested that intelligent contracts would be used to avoid falsification of intelligent meter data and abuse of personal details. © 2020 IEEE.

关键词： Blockchain

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Query-Driven Descriptive analytics for IoT and Edge computing 7

Query-Driven Descriptive Analytics for IoT and Edge Computin...

引用

7th IEEE international conference on Cloud Engineering (IEEE IC2E)

作者： Symeonides, Moysis Trihinas, Demetris Georgiou, Zacharias Pallis, George Dikaiakos, Marios D. Univ Cyprus Dept Comp Sci Nicosia Cyprus Univ Nicosia Dept Comp Sci Nicosia Cyprus

ISBN: (纸本)9781728102184

With consumers embracing the prevalence of ubiquitously connected smart devices, Edge computing is emerging as a principal computing paradigm for latency-sensitive and inproximity services. However, as the plethora of data generated across connected devices continues to vastly increase, the need to query the "edge" and derive in-time analytic insights is more evident than ever. This paper introduces our vision for a rich and declarative query model abstraction particularly tailored for the unique characteristics of Edge computing and presents a prototype framework that realizes our vision. Towards this, the declarative query model enables users to express high-level and descriptive analytic insights, while our framework compiles, optimizes and executes the query plan decoupled from the programming model of the underlying data processing engine. Afterwards, we showcase a number of potential use-cases which stand to benefit from the realization of query-driven descriptive analytics for edge computing. We conclude by elaborating on the open challenges that still must be addressed to realize our vision and potential research opportunities for the academic community to further advance the current State-of-the-Art.

关键词： Edge computing Cloud computing Big data Stream Processing Query Execution

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Implementation of Industrial Cyber Physical System: Challenges and Solutions

Implementation of Industrial Cyber Physical System: Challeng...

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IEEE international conference on Industrial Cyber Physical Systems (ICPS)

作者： Yu, Wenjin Dillon, Tharam Mostafa, Fahed Rahayu, Wenny Liu, Yuehua La Trobe Univ Dept Comput Sci Inf Technol Melbourne Vic Australia Incitec Pivot Ltd Melbourne Vic Australia

ISBN: (纸本)9781538685006

The Industry Internet of Things (IIoT) and the Industry Cyber-Physical System (ICPS) for real industry are becoming vitally necessary in the smart manufacturing environment. Very large number of intelligent sensors are being available generating an exploding amount of data. Several issues come with the big data in real industry, including the a grand-scale connected network construction with the data security and access protocol issues, data quality with considerable noise when gathered from industrial factories, efficient data storage, smart interconnection with cloud services, and real-time analytics requirements. This paper proposes an integrated CPS based architecture for smart manufacturing and provides the deployment details, addressing all the potential problems in an appropriate way. It has been successfully implemented in a real industry environment, and won the Best Industry Application of IoT at the BigInsights data & AI Innovation Awards.

关键词： Cyber-Physical System Internet of Things Industry 4.0 cloud computing big data ecosystem data quality

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Application of Image data analytics for Immediate Disaster Response 20

Application of Image Data Analytics for Immediate Disaster R...

引用

21st international conference on Distributed computing and Networking (ICDCN)

作者： Chaudhuri, Neha Bose, Indranil Indian Inst Management Management Informat Syst Kolkata W Bengal India

ISBN: (纸本)9781450377515

This study identifies a novel source of data, i.e. images from smart urban infrastructures, that would be helpful in effective disaster management decision-making. For this purpose, we collected images from disaster-hit environments of Central Mexico (2017 earthquake). Also, this study utilizes deep learning convolutional neural network to analyze this novel dataset and evaluates the model effectiveness and technical viability during crisis scenarios. TensorFlow was utilized for the image classification task. The findings have important significance for effective disaster response.

关键词： Convolutional neural networks deep learning disaster management smart urban environments image classification

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A Privacy Preserving Framework for smart Cities utilising IoT, smart Buildings and Big data 22

A Privacy Preserving Framework for Smart Cities utilising Io...

引用

22nd IEEE international conference on High Performance computing and Communications, 18th IEEE international conference on smart City and 6th IEEE international conference on data Science and Systems, HPCC-smartCity-DSS 2020

作者： Inibhunu, Catherine Carolyn McGregor, A.M. Ontario Tech University OshawaON Canada

ISBN: (纸本)9781728176499

There are many possibilities for a smart city that is enabled with smart buildings and well provisioned and managed internet of things (IoT) frameworks. The benefits of such frameworks can be felt in multiple domains. On planning an integrated city, data captured from the infrastructures within a city can be analyzed and utilized for effective resource and services provisions within the city. In urban mobility, automated planning and demand responsive to public transportation integrated with self-driven vehicles. On safety, security and health of cities and their citizens, real-Time surveillance and analytics can lead to better provision of emergency services, weather planning, early warnings on floods, tornadoes, man-made disasters and pandemics. To facilitate such services requires frameworks that can be effective at acquisition, processing and analysis of large volumes of data from vast systems as well as citizens within a city while preserving the security and privacy of data *** this paper, (a) a brief overview on the current landscape on smart cities is provided, the architectures and frameworks proposed to support data management, (b) highlights research opportunities that are still open, (c) proposes a privacy preserving computation framework that can be explored for a robust smart city ecosystem (d) and outlines the benefits possible with such a proposed framework. © 2020 IEEE.

关键词： Internet of things

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Semantics-Driven Cloud-Edge Collaborative Inference A Case Study of License Plate Detection 2

Semantics-Driven Cloud-Edge Collaborative Inference A Case S...

引用

2nd international conference on Image Processing, Computer Vision and Machine Learning, ICICML 2023

作者： Gao, Yuche Zhang, Beibei University College London Department of Statistical Science London United Kingdom Zhejiang Lab Intelligent Software Research Center Hangzhou China

ISBN: (纸本)9798350331417

With the proliferation of video data in smart city applications like intelligent transportation, efficient video analytics has become crucial but also challenging. This paper proposes a semantics-driven cloud-edge collaborative approach for accelerating video inference, using license plate recognition as a case study. The method separates semantics extraction and recognition, allowing edge servers to only extract visual semantics (license plate patches) from video frames and offload computation-intensive recognition to the cloud or neighboring edges based on load. This segmented processing coupled with a load-aware work distribution strategy aims to reduce end-to-end latency and improve throughput. Experiments demonstrate significant improvements in end-to-end inference speed (up to 5x faster), throughput (up to 9 FPS), and reduced traffic volumes (50% less) compared to cloud-only or edge-only processing, validating the efficiency of the proposed approach. The cloud-edge collaborative framework with semantics-driven work partitioning provides a promising solution for scaling video analytics in smart cities. © 2023 IEEE.

关键词： cloud computing edge computing license plate recognition smart cities video analytics

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