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A Landscape of XML data from analytics Perspective 1

A Landscape of XML Data from Analytics Perspective

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1st international conference on smart Sustainable intelligent computing and Applications, ICITETM 2020

作者： Singh, Pratima Sachdeva, Shelly Department of Computer Science and Engineering National Institute of Technology Narela New Delhi India

The journey of the database started with a relational database followed by transactional, eXtensible Markup Language (XML)[10,11], Not only SQL (NoSQL), and Hybrid Transactional/Analytical Processing (HTAP) database[2]. Analytic functions in SQL are used to process analytical databases, XQuery is used to process XML databases and NewSQL queries are used to process Hybrid Transactional and Analytical Processing (HTAP) databases. In the current scenario, the research related to the XML database and analytics on the XML database is an important area of concern. Numerous enterprises use XML as a data exchange format. Considering all the benefits of XML and its use in the field of web applications, various works elaborate to adopt it as a data storage technology. In this work, an attempt has been made to perform analytical functions using XQuery on an XML data and compare its performance with Analytical SQL queries in terms of execution time. A sample set of queries has been performed on a sample dataset. According to the results, it is concluded that Analytic SQL is dominating XQuery to perform analytical functions. In experimentation, we explained the persistence of XML data (electronic health records dataset) in eXist-DB and BaseX and executing queries on that data. The finding is that the performance of XML data in a health care environment is better if we use BaseX instead of eXist-DB. © 2020 The Authors. Published by Elsevier B.V.

关键词： XML

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Efficient Network Administration for smart Grid data Center 22

Efficient Network Administration for Smart Grid Data Center

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22nd IEEE international conference on Advanced Communication Technology (ICACT)

作者： Jeong, Seonyong Shin, Seungwon Korea Adv Inst Sci & Technol Grad Sch Informat Secur Daejeon South Korea Korea Adv Inst Sci & Technol Sch Elect Engn Daejeon South Korea

ISBN: (纸本)9791188428045

Nowadays, the smart grid systems, which are intelligent electrical grid systems, are being installed in the real world. According to the statistics, about 79 million Advanced Metering Infrastructure is deployed in the United States and these devices generate terabytes to petabyte levels of electricity data. As IT technology developed, the energy provider can get beneficial information by processing the data in the way such as Machine Learning or Deep Learning. So smart grid administrator utilizes a data center to store the energy data and to process them. The amount of power data is increasing rapidly and the type of power data becoming more and more diverse. In addition, as computing power improves, a lot of advantageous applications such as blackout prediction is developed. In the smart grid, the importance of the data center becomes higher and higher. However, the traditional data center is designed in strict. Because the traditional data centers are designed by vendors, the operations of each component of centers are ineffective on the smart grid system. So in this paper, we applied the Software-Defined data Center, which controls the data center in a virtualized and programmable manner, to operate the data in a more flexible and interoperable way.

关键词： SDDC SDN smart Grid Network Slicing Access Control

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Research on Water Resources intelligent Management of Thermal Power Plant Based on Digital Twins

Research on Water Resources Intelligent Management of Therma...

引用

IEEE international conference on Cloud computing and Big data Analysis (ICCCBDA)

作者： Haihong Ji Jing Li Shanshan Zhang Qiaoling Wu Huadian Electric Power Research Institute Co. LTD Hangzhou China

With the development of industry digitization, and the convergence of industry and the internet, the digital twin technology was widely used in many industries, thermal power plants were big users of water, the intelligent management of the whole plant water resource system had become inevitable. This paper expounded the digital twin theory, and the power plant in Shandong province was taken as an example, the theory and method of digital twinning were applied, advanced information technologies such as internet of things technology, cloud computing and big data analysis were used, the thermal power plant water resource intelligence management system had been constructed, the intersection and fusion among physical layer, data layer, model layer and function layer were completed, and the application of water resource intelligence management system in thermal power plants was analyzed. The results show that: this system had realized the factory water balance figure of automatic updates, water balance, dynamic test and application analysis, the water system of water, water quality of three dimensional display, dynamic analysis and evaluation, trend prediction, etc. It guided the water adjustment and optimization of the whole plant, the electricity consumption had been reduced, water use efficiency and efficiency were improved, the discharge of wastewater had been reduced, the amount of water extracted per unit of generating capacity was reduced from 1.90m³/MW to 1.21m³/MW in this plant, it could reduce the fresh water intake by about 800,000 tons per year, which had good economic and social benefits. It would be an important part of future smart power plants to set an example for the intelligent management of water resources for the whole plant.

关键词： Industries Cloud computing Digital twin Water quality Big data Thermal management Thermal analysis

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The improvement of news communication mode by data mining and visualization technology

The improvement of news communication mode by data mining an...

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

作者： Yang, Jiao Dianchi College of Yunnan University KunmingYunnan650228 China

ISBN: (纸本)9789811525674

With the development of technologies, the emergence of the data mining and the visualization technology is quietly affecting people’s daily life. How to make better use of this technology to make rational use of the information has become a problem faced by all walks of life. At the same time, the mode of news communication has also changed, from the contents of the report and the ways of presentation to the production process. Based on this, this paper studies the improvement of the news communication mode by the data mining and the visualization technology from the aspects of accelerating the process of the media integration, using the social TV products to attract audiences, the digital communication and the network communication, strengthening the visual news communication, and increasing the interactive participation and so on. The use of the data mining and the visualization technology for the traditional news communication has brought a new revolution, and also has brought new vitality for the impact of the new media in the declining news industry. © Springer Nature Singapore Pte Ltd. 2020.

关键词： data mining

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2020 international conference on Advancement in data Science, E-Learning and Information Systems, ICADEIS 2020

2020 International Conference on Advancement in Data Science...

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2020 international conference on Advancement in data Science, E-Learning and Information Systems, ICADEIS 2020

ISBN: (纸本)9781728182728

The proceedings contain 15 papers. The topics discussed include: correlation and evaluation analysis using the information system success model in implementation of enterprise resource planning (ERP) supply chain management for oil and gas industry;accuracy analysis transliteration Balinese script-to-Latin text using hexadecimal labeling method;learning-analytics based intelligent simulator for personalized learning;IoT based smart small scale solar energy planning using evolutionary fuzzy association rule mining;age group based document classification in Bahasa Indonesia;RGB channel analysis for glaucoma detection in retinal fundus image;Internet of things based smart small scale solar energy planning using evolutionary fuzzy association rule mining;and classification of building cracks image using the convolutional neural network method.

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A Hybrid Optimization Algorithm for Pathfinding in Grid Environment 3rd

A Hybrid Optimization Algorithm for Pathfinding in Grid Envi...

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international conference on data Management, analytics and Innovation (ICDMAI)

作者： Booba, B. Prema, A. Renugadevi, R. Vels Inst Sci Technol & Adv Studies VISTAS Sch Comp Sci Dept Informat Technol Chennai Tamil Nadu India Vels Inst Sci Technol & Adv Studies VISTAS Dept Comp Sci Sch Comp Sci Chennai Tamil Nadu India

ISBN: (纸本)9789813299498;9789813299481

Grid computing has been highly effective in the area of life sciences, financial analysis, research collaboration, and engineering. This paper is a study of existing algorithms like Swarm Intelligence (SI) algorithms such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC-PSO), and Parallel Particle Swarm Optimization (PPSO) to opt for the optimal path in a grid computing environment. These algorithms were used to solve the complex optimization problems in finding the path between source node to destination node effectively. Nature computing techniques based on the study of the collective behavior of ants, particle swarms, and bees are used to find the optimal path, improve the optimization methods and scalability in a set of representative problems. The hybridization of a grid computing environment and nature-inspired computing algorithms such as ACO, PSO, ABC-PSO, and PPSO has resulted in a class of solutions that differ in structure and design from the peer-to-peer network algorithms and the evaluated results showed the effectiveness of the pathfinding problem. ACO is implemented on a dynamic grid computing environment to demonstrate scalability and a solution for pathfinding. A class of four algorithms is used to find an optimal path and improve the optimization methods and shorten the computational time in a grid computing environment.

关键词： ACO PSO ABC-PSO PPSO Grid computing Nature-inspired computing Pathfinding Swarm intelligence

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Attacking the Dialogue System at smart Home 16th

Attacking the Dialogue System at Smart Home

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16th EAI international conference on Collaborative computing: Networking, Applications, and Worksharing, CollaborateCom 2020

作者： Deng, Erqiang Qin, Zhen Li, Meng Ding, Yi Qin, Zhiguang School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu China Institute of Electronic and Information Engineering of UESTC Chengdu China Institute of Electronic and Information Engineering of UESTC in Guangdong Guangdong523808 China

ISBN: (纸本)9783030675363

intelligent dialogue systems are widely applied in smart home systems, and the security of such systems deserves concern [1, 2]. In this paper, we design a threatening scenario of dialogue systems at a smart home. A trojan robot is disguised as one part of the whole system but generates dialogue adversarial examples to attack the normal robots according to the information of users. To achieve the goal in such a scenario, the responding speed, the correctness of the grammar, and the consistency of semantic is necessary. Based on these requirements, we propose a novel method named Attention weight Probability Estimation Attack (APE) to allocate the keys words in dialogue and substitute these words with synonyms in real-time. We perform our experiments on popular classification datasets in the DNN model, and the result shows that APE effectively attacks the system with low responding time and a high success rate. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Semantics

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intelligent Correction Algorithm for Energy Metering data for Lean Management

Intelligent Correction Algorithm for Energy Metering Data fo...

引用

international conference on Cyber Security Intelligence and analytics, CSIA 2020

作者： Ye, Bin Department of Mechanical and Electrical Engineering Shandong Vocational College of Light Industry Zibo255300 China

ISBN: (纸本)9783030433086

The traditional method multiplies the synthetic error and the data reading of the energy metering system, and selects the corrected measured value. The result cannot meet the accuracy requirement of the energy metering data. To this end, an intelligent correction algorithm for energy metering data for lean management is proposed. By determining the data correction value, the intelligent correction of the data error of the energy metering system is completed, and the simulation experiment is performed on the result. The experimental results show that the data of the energy metering system is accurate after the error correction is completed by the proposed method. © Springer Nature Switzerland AG 2020.

关键词： Error correction

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A big data compatible naive measure for estimating the landscape dynamics using open geospatial datasets

A big data compatible naive measure for estimating the lands...

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2020 international conference on smart Innovations in Design, Environment, Management, Planning and computing, ICSIDEMPC 2020

作者： Ghosh, Suddhasheel Dey, Saurav Jawaharlal Nehru Engineering College Department of Civil Engineering Aurangabad India Associate Research Analyst P. E. Analytics Gurgaon India

ISBN: (纸本)9781728159706

The process of urbanisation has been reported to be a driver of global climatic change. Rapid urbanisation is leading to a drastic change in the land use and land cover (LULC) pattern of any urban area. Urban LULC dynamics can be understood through the use of multi-Temporal geospatial datasets. The existence of multi-sensor and multi-Temporal remote sensing datasets enable the understanding of LULC dynamics. In this paper, we take Aurangabad as a pilot project for study. Aurangabad is a city located in the Marathwada region of the Maharashtra state in India, and is faced with the juxtaposition of the growing industry and the cultural heritage. The city has has been included in the list of 100 smart cities to be developed in India, by the Indian government. This paper proposes a new metric and area based method for the measurement of urban dynamics, and identification of hotspots. The superiority of the metric with respect to the Shannon's Entropy is also illustrated. The approach demostrated in this paper is extendable to the measurement of LULC dynamics and hotspot identification in a Big data environment as well. © 2020 IEEE.

关键词： Dynamics

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A GPU Unified Platform to Secure Big data Transportation Using an Error-Prone Elliptic Curve Cryptography 4th

A GPU Unified Platform to Secure Big Data Transportation Usi...

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4th international conference on data Management, analytics and Innovation, ICDMAI 2020

作者： Bhattacharjee, Shiladitya Chakkaravarhty, Divya Midhun Chakkaravarty, Midhun Rahim, Lukman Bin Ab. Ramadhani, Ade Wahyu Universiti Teknologi PETRONAS Seri IskandarPerak Darul Ridzuan Malaysia Faculty of Computer Science and Multimedia Wisma Lincoln Petaling JayaSelangor Darul Ehsan Malaysia

ISBN: (纸本)9789811556159

The time and space optimization, protecting data loss and safeguarding privacy as well as integrity are the priorities in any large file transmission system. However, the current literature is lacking to provide such a system which can take care of each of these aspects very strongly in a unified way. Hence, this research proposes a Graphics Processing Unit (GPU)-based error-prone elliptic curve cryptography with an advanced memory management mechanism. It comprises the elliptic curve public-key cryptography (ECC) to offer higher defiance against the various privacy and integrity attacks. It further includes an advanced dual round of error regulator which can sense and spot any numbers of discrete or continuous faults. This error control technique can regenerate the data if there is any accidental loss during transportation. The usages of advanced parallel execution with a GPU and a unique memory management mechanism make it enable to handle required memory and time during the execution very efficiently. The achieved result shows that the projected unified approach offers higher Throughput on every incident which signifies that it is time-efficient. Additionally, it offers higher SNR, Avalanche Effect and a curtailed proportion of data Loss. It specifies that the suggested mingled technique is proficient to protect privacy, integrity and mishap of data in big data hauling with the efficient management of available internal memory. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Graphics processing unit

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