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Embedded Intelligence for Safety and Security Machine Vision Applications 21st

Embedded Intelligence for Safety and Security Machine Vision...

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21st international conference on Image Analysis and Processing (ICIAP)

作者： Lioupis, Panagiotis Dadoukis, Aris Maltezos, Evangelos Karagiannidis, Lazaros Amditis, Angelos Gonzalez, Maite Martin, Jon Cantero, David Larranaga, Mikel Inst Commun & Comp Syst ICCS Zografos 15773 Greece Fdn Tekniker Inaki Goenaga 5 Eibar 20600 Spain

ISBN: (纸本)9783031133244;9783031133237

Artificial intelligence (AI) has experienced a recent increase in use across a wide variety of domains, such as image processing for security applications. Deep learning, a subset of AI, is particularly useful for those image processing applications. Deep learning methods can achieve state-of-the-art results on computer vision for image classification, object detection, and face recognition applications. This allows to automate video surveillance reducing human intervention. At the same time, although deep learning is a very intensive task in terms of computing resources, hardware and software improvements have emerged, allowing embedded systems to implement sophisticated machine learning algorithms at the edge. Hardware manufacturers have developed powerful co-processors specifically designed to execute deep learning algorithms. But also, new lightweight open-source middleware for constrained resources devices such as EdgeX foundry have emerged to facilitate the collection and processing of data at sensor level, with communication capabilities to cloud enterprise applications. The aim of this work is to show and describe the development of smart Camera Systems within S4AllCities H2020 project, following the edge approach.

关键词： Horizon2020 Edge EdgeX foundry Machine vision Artificial intelligence Deep learning

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A Novel Approach to Stock Market Analysis and Prediction Using data analytics 4th

A Novel Approach to Stock Market Analysis and Prediction Usi...

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4th international conference on Information and Communication Technology for intelligent Systems, ICTIS 2020

作者： Kumari, Sangeeta Chaudhari, Kanchan Deshmukh, Rohan Naik, Rutajagruti Deshmukh, Amar Department of Computer Engineering Vishwakarma Institute of Technology Pune411037 India Connecticus Technologies Private Limited Pune India

ISBN: (纸本)9789811570612

Stock market is one of the most versatile sectors in the financial system. Historically, stock market movements have been highly unpredictable as there are many factors that affect it. Immense research about financial history, as well as the current trends, must be done before thinking of investing in a particular company. For the prospective buyer to get a better sense of future, predictive models of machine learning can be used to predict whether the stocks will go high or low and how much. While no one can say with certainty that a stock will go up in value, taking the time to evaluate the past few years of the company’s growth can give some insight into the possibility. Employing traditional methods like fundamental and technical analysis may not ensure the reliability of the prediction. In this paper, we attempt to take financial historic data for the stock and try to get more detailed insights and derive parameters that we will use to predict the stock behavior. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： data analytics

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3rd international conference on Security and Privacy in New computing Environments, SPNCE 2020

3rd International Conference on Security and Privacy in New ...

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3rd international conference on Security and Privacy in New computing Environments, SPNCE 2020

ISBN: (纸本)9783030669218

The proceedings contain 31 papers. The special focus in this conference is on Security and Privacy in New computing Environments. The topics include: Forward Secure Searchable Encryption with Conjunctive-Keyword Supporting Multi-user;alarm Elements Based Adaptive Network Security Situation Prediction Model;A3BAC: Attribute-Based Access Control Model with Anonymous Access;Blockchain-Based Decentralized Privacy-Preserving data Aggregation (BDPDA): Scheme for smartGrid;watermark Based Tor Cross-Domain Tracking System for Tor Network Traceback;research on IoT Security Technology and Standardization in the 5G Era;MIMEC Based Information System Security Situation Assessment Model;IoTFC: A Secure and Privacy Preserving Architecture for smart Buildings;a Secure Experimentation Sandbox for the Design and Execution of Trusted and Secure analytics in the Aviation Domain;Research on a Hybrid EMD-SVR Model for Time Series Prediction;preface;a Characterisation of smart Grid DoS Attacks;distant Supervision for Relations Extraction via Deep Residual Learning and Multi-instance Attention in Cybersecurity;user Identity Linkage Across Social Networks Based on Neural Tensor Network;an Efficient and Privacy-Preserving Physiological Case Classification Scheme for E-healthcare System;a Multi-class Detection System for Android Malicious Apps Based on Color Image Features;PUF-Based Two-Factor Group Authentication in smart Home;An Authentication Framework in ICN-Enabled Industrial Cyber-Physical Systems;access Control for Wireless Body Area Networks;FIDO – That Dog Won’t Hunt;blockchain-Enabled User Authentication in Zero Trust Internet of Things;security Analysis and Improvement of a Dynamic-Hash-Table Based Auditing Scheme for Cloud Storage;security and Privacy in 5G Applications: Challenges and Solutions;a Secure and Verifiable Outsourcing Scheme for Machine Learning data.

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"smart City" Governance Technologies Development in the Era of the 4th Industrial Revolution

"Smart City" Governance Technologies Development in the Era ...

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intelligent Systems conference (IntelliSys)

作者： Kuznetsov, Mikhail Nikishova, Maria Belova, Anna Lomonosov Moscow State Univ Leninskie Gory 1s46 Moscow 119234 Russia

ISBN: (纸本)9783030295134;9783030295127

The authors investigate main trends of smart-city topic, describe the features and differences of "smart city" from the cities of the 20th century, attract attention to the fact of difference between smart-city management and smart-city governance. After that the authors show challenges connected with smart-city governance and provide a tool for the effective smart-city governance - "smart city governance analytical panel". "smart city governance analytical panel" is the authors solution for city governance improvement. The main idea of this tool is to combine space modelling with socio-economic predictive analytics, to produce a complex strategic planning tool for future city development, which allows all stakeholders and citizens participate in discussions and decision making. Due to the effectiveness of this decision, it is important to identify the risks of smart city management in general and the risks of using this panel in particular. In this connection, the authors continue to improve the described panel, planning the introduction of artificial intelligence for predictive analytics based on big data and artificial intelligence, which requires further theoretical study and justification from a scientific position.

关键词： smart-city City management City governance Urban governance Artificial intelligence smart city governance analytical panel

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Enterprise of Future: Leveraging Information, Communication and Technology (ICT) and Social Interactions (SI) for Growth 3rd

Enterprise of Future: Leveraging Information, Communication ...

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3rd international conference on smart computing and Informatics (SCI)

作者： Swain, Sukanta Chandra Singh, Ramnish KIIT Deemed Univ Sch Humanities Bhubaneswar India Amazon Web Serv Washington DC USA

ISBN: (纸本)9789813296909;9789813296893

This paper discusses enterprise of future (EoF), an enterprise which takes advantage of the advances in information, communication and technology (ICT) and social interactions (SI) for its growth. The paper first discusses the current trends and then maps these trends to enterprise of future and showcases how enterprises can empower their employees and reap benefits of these advances. The paper also traces the day in a life of an employee who transitions between multiple devices, multiple connections and multiple locations with seamless access to application and data.

关键词： Information Communication and technology Social interactions Social Mobility Cloud analytics Big data Enterprise of future

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Generalized Dynamic Multilayer Fog computing Architecture 4th

Generalized Dynamic Multilayer Fog Computing Architecture

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4th international conference on Internet of Things and Connected Technologies (ICIoTCT)

作者： Arjun, K. P. Bhanu, S. Mary Saira Natl Inst Technol Tiruchirappalli 620015 Tamil Nadu India

ISBN: (纸本)9783030398750;9783030398743

The concept of smart city and smart Home is a promising and challenging one which defines the future of urban infrastructure development by integrating the Internet of Things (IoT) with Cloud computing. Fog computing with its latest framework on multilayering where each layer focuses on the different aspect of the architecture has proven useful in its goal to reduce space, time and computation overhead from cloud perspectives, due to its traffic offloading and edge device proximity for computation. But, a need for platform generalization and dynamic behavior still exists as most of the smart home needs to operate in multiple environments whereas the existing system mainly works on a rigid model with single infrastructure support. In this paper, a modified version of multilayer fog architecture has been proposed with scope for generalization and dynamic operation in terms of data management and placement. The proposed system consists of five sections - the Lower Fog Layer for end device collection operation and prioritization, Dockerized Middle Layer for node-specific operations like event detection and filtered data propagation, ICFN (Interconnecting Fog Node) Layer for interconnecting fog nodes, Cloud Server for data analytics and Fog Maintenance Remote Server for platform customization. The additional platform customization and multiple service support in the proposed architecture have also made significant improvements with regards to data distribution, request bandwidth, and request failure rate.

关键词： Multilayer fog computing Dockers and Containers Cloud computing data distribution Fog generalization Fog multi-service

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Strategic Thinking on High-Quality Development of Digital Economy in Yangtze River Delta Region of China in the Era of Big data

Strategic Thinking on High-Quality Development of Digital Ec...

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international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Zhang, Ruitong Department of Economics Shanghai University Shanghai China

ISBN: (纸本)9783030627423

As the world has entered the era of big data, the digital economy, as an important part of the development of the real economy and innovation-driven development, has become a key factor in China’s implementation of major national strategies. In this paper, the Yangtze River Delta region, which ranks the top among Chinese three major urban agglomerations, is taken as the research object. At the same time, this paper combines with the experience of high-quality development of digital economy of other countries, the key elements of the development of big data industry are analyzed and summarized, and a package of enlightening suggestions for the development of big data industry are given. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Ratio Test for Time-Varying Variance of Mean Change Point Based on Big data Analysis

Ratio Test for Time-Varying Variance of Mean Change Point Ba...

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international conference on Cyber Security Intelligence and analytics, CSIA 2021

作者： Li, Caicai Jin, Hao Bai, Huihui Department of Sciences Xi’an University of Science and Technology Xi’an Shannxi710054 China

ISBN: (纸本)9783030700416

There are more and more applications involve the big data analytics. The research method of big data is particularly important in the study of time-varying volatilities. In the article, we analysis the tests for a constant mean possibly subjected to change under strong mixing dependence based on big data method. The change point methods provided here rely on ratio type test statistics based on the functional of the partial sums of residuals. The main advantage of proposed approach is that the model allows strong mixing and time-varying variance in error terms. Based on the fundamental results suggested by Cavaliere (2004, Econometric Reviews, 23, 259− 292), the limiting distribution under the original hypothesis is derived and the consistency under the alternatives is also proved. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Storing live sensor data to the platforms of internet of things (Iot) using arduino and associated microchips 1

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3rd international conference on Computational Intelligence and Informatics, ICCII 2018

作者： Pradeep, S. Sharma, Yogesh Kumar Department of CSE JJT University JhunjhunuRajasthan India

ISBN: (数字)9789811514807

ISBN: (纸本)9789811514791

Internet of Things (IoT) is one of the prominent domains of research in the segment of wireless technologies whereby the smart objects are connected with each other using wireless signals. Despite the enormous areas of research in this stream, the storage and evaluation of live sensor data are widely required so that further analytics on the sensor data can be done. In this research manuscript, the usage of Arduino is presented that is one of the key open-source hardware platforms for programming with Internet of Things (IoT). In open-source hardware platforms of Arduino and NodeMCU, the direct connectivity with the real clouds can be done and is presented in this manuscript. There exist number of open platforms of IoT for logging of data;this manuscript presents the use of ThingSpeak and Carriots so that analytics patterns of sensor data can be implemented effectively. This paper presents the assorted aspects of open-source hardware of Arduino that can be used for different sensor-based applications. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Internet of things

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Distributed computing for smart Meter data Management for Electrical Utility Applications 30

Distributed Computing for Smart Meter Data Management for El...

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30th international conference on Cybernetics and Informatics (K and I)

作者： Zainab, Ameema Refaat, Shady S. Abu-Rub, Haitham Bouhali, Othmane Texas A&M Univ Elect & Comp Engn College Stn TX 77843 USA Texas A&M Univ Elect & Comp Engn Doha Qatar

ISBN: (纸本)9781728143811

With the advent of Internet-of-Things (IoT) devices, including smart meters and sensors in the smart grid, there has been immense research interest in big data management, analytics, and parallel processing of data. However, complex hardware and software parameters configurations and in-depth understanding of the data processing design are essential for efficient utilization of big data analytics platforms. In this work, we analyze the parallelization of load prediction by utilizing spark regression python library to assess the performance with workloads of up to 8 nodes. The results of different configurations have been studied and analyzed against the performance of Apache Spark. It was found that a trade-off between the number of nodes and cores is necessary to perform efficient parallel computing. Multiple sets of combinations of nodes and cores are considered in this paper to evaluate the performance. The work also signifies the importance of high-performance computing capability for smart meters big data management. The obtained results indicate that the computational time is not only dependent on the data size but also on the number of compute nodes and the number of cores assigned to run the job.

关键词： smart grid load forecast big data parallel computing Apache-Spark high performance computing

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