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检索条件"任意字段=International Conference on Intelligent and Smart Computing in Data Analytics, ISCDA 2020"

共 3245 条记录，以下是1141-1150 订阅

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Toward Effective and Sustainable smart City Model Case study exploration of varying smart city approaches and outcomes 20

Toward Effective and Sustainable Smart City Model Case study...

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21st Annual international conference on Digital Government Research (DGO) - intelligent Government in the intelligent Information Society

作者： Ahn, Michael Chen, Yu-Che Cho, KiHaing Huang, Chengyu (Victor) Kim, Younhee Myeong, Seung-Hwan Univ Massachusetts Dept Publ Policy & Publ Affairs Boston MA 02125 USA Univ Nebraska Digital Governance & Analyt Lab Omaha NE 68182 USA Busan Metropolitan City Busan South Korea Univ Nebraska Aviat Inst UAS Lab Coll Publ Affairs & Community Serv Omaha NE 68182 USA Penn State Harrisburg Sch Publ Affairs Middletown PA USA Inha Univ Dept Publ Adm Incheon South Korea

ISBN: (纸本)9781450387910

This panel aims to explore selected cases of smart city projects to improve our understanding of the critical institutional factors and processes that lead to effective and sustainable smart city outcomes. This panel discusses compelling smart city cases, including Busan Metropolitan City, Songdo, Gimpo, and Namyang-ju. These cases apply different approaches to run smart city practices that are characterized as either a large-scale, top-down, capital-intensive and hardware-focused smart city project or a small-scale, bottom-up, less capital-intensive and data-training focused (as opposed to hardware-focused) smart city project. This panel will highlight the varying outcomes and impacts of different smart city approaches and identify key institutional factors and strategies that contribute to effective and sustainable smart city outcomes.

关键词： smart government smart government models government innovation data analytics drone

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Observation and Control of smart Grid Using IoT and Cloud Technology 1st

Observation and Control of Smart Grid Using IoT and Cloud Te...

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1st international conference on intelligent computing in Control and Communication, ICCC 2020

作者： Tiwari, Salil Agrawal, Vatsal Jain, Sanjiv Kumar Shrivastava, Piyush Kumar Department of Electrical Engineering Medi-Caps University Rau Indore Madhya Pradesh453331 India

ISBN: (纸本)9789811584381

The traditional electrical grids deals with generation, transmission and distribution have one-way communication and are centered around the distributor. They also lack in routing and interconnection of different types of generations which lead to a reduction in the reliability of supply. Hence to overcome this issue we propose the comprehensive architecture of smart Grid and it’s Observation and control using the Internet of Things (IoT) and Cloud Technology. We have Integrated the different sources of energy (thermal and renewable) in a system and introduces the automatic routing of electric power according to peak and low demand. It also incorporates the smart metering facility using IoT and Cloud Technology. It can gather, send and receive the real-time data, which provide two-way communication of data of power being consumed at customer’s end to the service producer. The whole data can be stored, accessed and analyzed on the very secured and customized API platform. We have built and thoroughly tested demonstration model of our project having Wi-Fi-based smart meter, which helped us to monitor and control the electric power and to enhance the reliability of the system. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： smart meters

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Energy-Efficient Energy analytics Using a General Purpose Graphics Processing Unit 8

Energy-Efficient Energy Analytics Using a General Purpose Gr...

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8th IEEE international conference on Big data (Big data)

作者： De, Sagnik Golab, Wojciech Univ Waterloo Elect & Comp Engn Waterloo ON Canada

ISBN: (纸本)9781728162515

smart meters allow energy providers to monitor their customers' power consumption. This fine-grained data stream generates many data points, which hides broader trends in power consumption and makes it difficult for energy providers to make decisions regarding a specific customer or a subset of customers. Since the raw power data has little direct use, various algorithms have been proposed to lower the dimensionality of data, discover trends, study relationships between different features of collected data, and summarize data. These analytical techniques make the data more palatable to the end user. Analyzing smart meter data is computationally intensive as there is a large number of households connected to one energy provider, and each household generates years of data at hourly intervals. To speed up the analysis, clusters of commodity computers have been used. Ironically, such clusters consume substantial energy - studies have shown that about 10% of the world-wide supply of electrical power is consumed by the computing infrastructure. In this paper, we describe the use of a graphics processing unit (GPU) to analyze smart meter data, and compare its performance with a conventional multi-core CPU. We discuss the technical challenges in programming a GPU effectively to process smart meter data, and demonstrate experimentally that this choice of implementation enables substantial improvements in terms of both running time and energy-efficiency as compared to the multi-core CPU.

关键词： smart grid smart electricity meters data analytics parallel processing GPU energy-efficiency scalability

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The Application of FIRD Book Positioning Technology in intelligent Library

The Application of FIRD Book Positioning Technology in Intel...

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international conference on Application of intelligent Systems in Multi-modal Information analytics, MMIA 2020

作者： Zhao, Yu Jilin Engineering Normal University ChangchunJilin130052 China

ISBN: (纸本)9783030514303

With the rapid development of wireless technology in our country, many colleges and universities vigorously build digital intelligent campus, and many advanced science and technology are widely used in digital library. The development of 4G network and wireless technology has changed the behavior and demand of readers. It can not only make full use of mobile information technology, but also improve the efficiency of library operation and promote the development of library modernization. With the great development of economic material, the cultural demand has been greatly enhanced. With the application of Internet and big data, the amount of information has exploded exponentially, which requires the modern library to move towards the intelligent step faster and faster. The use of library should be more people-oriented and enhance personalized service. The technology of FIRD positioning is the basic technology for library to realize automation and improve efficiency. It is an important part of library collection service and Book Circulation application. The purpose of this paper is to explore the research on the application of FIRD book positioning technology in the intelligent library, so as to update the existing model of the library with the application of Internet of things. In this paper, we will use the research method of specific analysis to compare the data and come to a conclusion. The results of this study show that the development and upgrading of intelligent library, integration of human and resource matching, improve the efficiency of library operation, reduce costs. It is urgent to construct a new ecology and scene of intelligent Library Based on the current development of intelligent library. © 2021, Springer Nature Switzerland AG.

关键词： Information services

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Computer Performance Determination System Based on Big data Distributed File

Computer Performance Determination System Based on Big Data ...

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international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Lu, Kong Jiangxi Modern Polytech Coll Nanchang 330095 Jiangxi Peoples R China

ISBN: (纸本)9783030152352;9783030152345

The high concurrency, high scalability, high performance, high availability, and large capacity of the distributed file system make it an ideal choice for storing large amounts of data. To determine the performance of the distributed computer in big data analysis, it is necessary to compare the performance test of different distributed file systems. This paper compares the different distributed file systems, analyzes the computer performance characteristics of distributed files, and summarizes the rules of different characteristics.

关键词： Big data Distributed file system Performance decision

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Graphical Perception for Immersive analytics 27

Graphical Perception for Immersive Analytics

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27th IEEE conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Whitlock, Matt smart, Stephen Szafir, Danielle Albers Univ Colorado Boulder CO 80309 USA

ISBN: (纸本)9781728156088

Immersive analytics (IA) uses immersive virtual and augmented reality displays for data visualization and visual analytics. Designers rely on studies of how accurately people interpret data in different visualizations to make effective visualization choices. However, these studies focus on data analysis in traditional desktop environments. We lack empirical grounding for how to best visualize data in immersive environments. This study explores how people interpret data visualizations across different display types by measuring how quickly and accurately people conduct three analysis tasks over five visual channels: color, size, height, orientation, and depth. We identify key quantitative differences in performance and user behavior, indicating that stereo viewing resolves some of the challenges of visualizations in 3D space. We also find that while AR displays encourage increased navigation, they decrease performance with color-based visualizations. Our results provide guidelines on how to tailor visualizations to different displays in order to better leverage the affordances of IA modalities.

关键词： Human-centered computing Visualization Empirical studies in visualization Human-centered computing Human computer interaction (HCI) Interaction paradigms Mixed / augmented reality Human-centered computing Human computer interaction (HCI) Interaction paradigms Virtual reality

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Augmenting the Existing CBPM Maintenance Philosophy Currently in Use in the Marine Sector with intelligent Predictive—CBPM Philosophy

Augmenting the Existing CBPM Maintenance Philosophy Currentl...

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international conference on Recent Trends in Machine Learning, IOT, smart Cities and Applications, ICMISC 2020

作者： Gautam, Minakshi Ramu, Vaishnavi S. Sinha, Sachin Reddy, Pranay Kumar Kondur, Monica Kumar, S. Suresh CSE Presidency University Bangalore India

ISBN: (纸本)9789811572333

The maintenance philosophy of equipment/system used in maritime environment which is highly corrosive follows CBPM (Condition-Based Predictive Maintenance) philosophy, where the maintenance of any equipment/system is based on the existing running condition of the same. Based on the running condition of the equipment/system, they are subjected to maintenance so as to have enhanced exploitation of the equipment/system. Among the various maintenance philosophy of equipment/system in our ecosystem, predictive maintenance has become a widely used term and the same is finding deep roots in maritime applications. The concept of predictive maintenance is being constantly updated by engineers and researchers based on monitoring historical data, modelling, simulation, and failure probabilities to predict fault and system deterioration over their useful life. Leveraging on various existing data science techniques and thereby sensor adaptation(s), the current paper proposes real-time predictive analytical techniques using R/PYTHON/JULIA and its associated libraries, such that the source of defect is localized thereby resulting in enhanced and better exploitation of the equipment/system with minimal downtime. The authors et al. are of the opinion that the real-time (existing) CBPM techniques that are currently being followed in maritime environment are time-consuming and require enhanced level of human monitoring and intervention for enhanced exploitation of the same. The authors et al. have also designed a customized self-healing RS (Recommender System) that liquidates majority of problems onboard a marine vessel utilizing advanced ML concepts and the same also recommending to the watchkeeper/EOW/Bridge in audio/video mode of possible upcoming defects on any maritime equipment/system. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Predictive analytics

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A Review on Edge to Cloud: Paradigm Shift from Large data Centers to Small Centers of data Everywhere 5

A Review on Edge to Cloud: Paradigm Shift from Large Data Ce...

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5th international conference on Inventive Computation Technologies (ICICT)

作者： Uddin, Mohammed Yousuf Ahmad, Sultan Prince Sattam Bin Abdulaziz Univ Coll Comp Engn & Sci Al Kharj Saudi Arabia

ISBN: (纸本)9781728146850

In present, Information Communication Technologies is shifting from large data centers to small and micro data centers, bringing data analytics and storage near to the devices at the edge of networks. This helps to deal with latency and data transition overhead that helps to make real-time operations more efficient. Advent of IoT and smart mobile technologies, new devices are joining networks and generating enormous data. Instead of cloud servers performing data analysis and storage, edge devices and edge servers are sharing the load of cloud servers which will enable hyper-efficient and smart ecosystem for enterprises. This research work addresses the key benefits of edge-to-cloud computing, its challenges and limitations. It also explored the edge architecture and application which are applicable in the current scenario and future possibilities of edge to cloud computing.

关键词： Cloud computing Edge computing Edge Architecture IoT Edge-Center

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On data Integrity Attacks against Industrial Internet of Things 18

On Data Integrity Attacks against Industrial Internet of Thi...

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18th IEEE international conference on Pervasive intelligent and computing (PICom)

作者： Xu, Hansong Yu, Wei Liu, Xing Griffith, David Golmie, Nada Towson Univ Towson MD 21252 USA NIST Gaithersburg MD 20899 USA

ISBN: (纸本)9781728166094

Industrial Internet of Things (IIoT) is predicted to drive the fourth industrial revolution through massive interconnection of industrial devices, integrating advances in smart machinery and data analytics driven by computing, networking and artificial intelligence techniques. The massive interconnections between industrial devices increase not only information exchange, productivity, and resource efficiency, but also cybersecurity risks and their impact on the Industrial Internet of Things (IIoT) system. In this paper, we investigate the evolutionary process, which captures the natural interactions and evolutions of both attackers and defenders, as well as their strategies to launch data integrity attacks and protect the IIoT system, respectively. We leverage the wireless cyberphysical simulator (WCPS) as a realistic IIoT environment to implement and evaluate strategies at different levels of evolution. The experimental results indicate the effectiveness of defensive strategies in guarding against various forms of data integrity attacks with increase in time and knowledge throughout the evolutionary process.

关键词： Industrial Internet of Things data Integrity Attacks Evolutionary Process and Cyber-Physical System

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A Study of Deterioration in Classification Models in Real-Time Big data Environment 4th

A Study of Deterioration in Classification Models in Real-Ti...

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

作者： Uddin, Vali Rizvi, Syed Sajjad Hussain Hashmani, Manzoor Ahmed Jameel, Syed Muslim Ansari, Tayyab Hamdard Univ Fac Engn Sci & Technol Karachi Pakistan Univ Teknol PETRONAS Dept Comp & Informat Sci Seri Iskandar Perak Malaysia

ISBN: (纸本)9783030335823;9783030335816

Big data (BD) is participating in the current computing revolutions. Industries and organizations are utilizing their insights for Business Intelligence (BI). BD and Artificial Intelligence are one of the fundamental pillars of Industrial Revolution (IR) 4.0. IR 4.0 demands real time BD analytic for prediction and classification. Due to complex characteristics of BD (5 V's), BD analytics is considered a difficult task in offline mood. However, in real time or online mood, BD analytic become more challenging and requires Online Classification Models. In real time mood, the nature of input streams (input data) and target classes (output class) are dependent and non-identically distributed, which cause deterioration in OCM. Therefore, it is necessary to identify and mitigate the causes of this deterioration in OCM and improve OCM performance in RTBDE. This study investigates some fundamental causes of deterioration of Online Classification Models and discusses some possible mitigation approaches. This study also presents some experimental results to show the deterioration in OCM due to real time big data environment. In the future, this study will propose a method to mitigate deterioration in Online Classification Models.

关键词： Big data Real-time machine learning Stream analytics Online Classification

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