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检索条件"任意字段=5th IEEE International Conference on Big Data Intelligence and Computing, DataCom 2019"

共 603 条记录，以下是61-70 订阅

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Research on Power Grid Topology Analysis Based on Graph database 5

Research on Power Grid Topology Analysis Based on Graph Data...

引用

5th ieee international conference on Cloud computing and intelligence Systems (CCIS)

作者： Zhou, Aihua Qiu, Hongbin Pan, Sen Hu, Bin Global Energy Interconnect Res Inst Co Ltd Beijing Peoples R China Power Syst Artificial Intelligence Joint Lab SGCC Beijing Peoples R China

ISBN: (纸本)9781538660058

In order to better solve the problems of low efficiency and slow service startup in power grid topology analysis, this paper uses graph database technology to efficiently solve the data modeling, storage, and processing problems in power grid asset data management represented by power grid topology analysis systems. the power grid topology analysis application framework based on graph database is constructed, and the key technologies and difficulties of power grid topology analysis based on graph database are analyzed in detail from the aspects of graph database management for power grid topology management and power grid topology analysis based on a graph database in order to provide theoretical and technical support for the application of graph database technology in power grid topology analysis.

关键词： Graph database Power grid Topology analysis

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Privacy-friendly Blockchain based data Trading and Tracking 5

Privacy-friendly Blockchain based Data Trading and Tracking

引用

5th international conference on big data computing and Communications (bigCOM)

作者： Wu, Zhenan Zheng, Han Zhang, Lan Li, Xiang-Yang Univ Sci & Technol China Sch Comp Sci & Technol Hefei Peoples R China

ISBN: (纸本)9781728140247

data trading has become a promising way to bridge numerous data islands and benefit a wide range of data driven applications. However, due to the high risk of data privacy, the easy-to-copy feature of data, and potential malicious behaviors of users, there still lacks data trading solutions to provide privacy protection, copyright/ownership protection and auditability of user behaviors. In this work, we propose a blockchain and smart contract based framework to keep tamper-proof records of data trading transactions, which also preserves users' identity, behavior and data privacy. data fingerprint is introduced to track data and protect data ownership. A set of protocols are also designed to prevent dishonest behaviors and ensure the security of data trading.

关键词： block chain data tracking data trading

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Short-Term Photovoltaic Output Forecasting Based on Multivariable Phase Space Reconstruction and Support Vector Regression 5

Short-Term Photovoltaic Output Forecasting Based on Multivar...

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5th ieee international conference on Cloud computing and intelligence Systems (CCIS)

作者： Dou, Chunxia Bian, Zhongwei Zhang, Tengfei Nanjing Univ Posts & Telecommun Inst Adv Technol Nanjing 210023 Jiangsu Peoples R China Jiangsu Engn Lab Big Data Anal & Control Act Dist Nanjing 210023 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Coll Automat Nanjing 210023 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Coll Artifical Intelligence Nanjing 210023 Jiangsu Peoples R China

ISBN: (纸本)9781538660058

A comprehensive forecasting method of the short-term photovoltaic output is presented in this paper to forecast the short-term output of two types: the days with weak weather fluctuates (sunny days) and the days with strong weather fluctuations. Firstly, the support vector regression (SVR) is used to forecast and track the reconstructed irradiated intensity and temperature, the forecasted data of the radiation intensity and temperature are used as the input of the forecasting model. At last, the high nonlinear fitting of the photovoltaic output is realized by the SVR model also. through the analysis of the actual data of photovoltaic power plants, the rationality and effectiveness of this method are verified in this paper. Compared with the traditional forecasting method using SVR only, the useful information contained in the historical data of photovoltaic output can be further explored and the accuracy of the PV output forecasting is also improved.

关键词： short-term photovoltaic output multivariable phase space reconstruction the support vector regression

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Design and Development of a Mobile EEG data Analytics Framework 5

Design and Development of a Mobile EEG Data Analytics Framew...

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5th ieee international conference on big data computing Service and Applications (ieee bigdataService) / Workshop on big data in Water Resources, Environment, and Hydraulic Engineering / Workshop on Medical, Healthcare, Using big data Technologies

作者： Gutierrez, Luis Husain, Mohammad Cal Poly Pomona Comp Sci Pomona CA 91768 USA

ISBN: (纸本)9781728100593

In this paper, we discuss the design and development of EEG Workbench: a prototyping framework for building electroencephalography (EEG) data analytics framework for the Android platform EEG data describe the activity of neuron populations in the brain and are acquired via electrodes placed on specific positions in the skull EEG signals have been shown to be sufficiently different between individuals and therefore suitable for use in the authentication process. the relatively recent introduction of consumer-grade EEG acquisition devices has made the utilization of EEG research more accessible to ubiquitous computing devices such as smartphones;however, the software developed in EEG research lacks specific implementations for Android. EEG Workbench aims to provide developers with a tool to build electroencephalography (EEG) data analytics framework for the Android platform.

关键词： EEG Brainwave Benchmark data Analysis Android

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Hybrid-Asynchronous Low Powered Multicore Architecture for improved battery life in future mobile computing devices 5

Hybrid-Asynchronous Low Powered Multicore Architecture for i...

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5th international conference on Artificial intelligence, big data, computing and data Communication Systems (ICABCD)

作者： Mogale, Hope Esiefarienrhe, Bukohwo Michael North West Univ Private Bag Dept Comp Sci Private Bag X2046 ZA-2735 Mafikeng South Africa

ISBN: (数字)9781665484220

ISBN: (纸本)9781665484220

In this paper we present a novel Hybrid-Asynchronous Low Powered Multicore Architecture which can be adopted for improved battery life in future mobile computing devices. Most modern mobile computing devices today are powered by traditional multicore microprocessors which consume most of the energy and battery life in mobile devices. At the heart of these multicore microprocessors lies the traditional multicore architecture which is prone to problems such as dark silicon. With a novel approach this paper presents Hybrid-Asynchronous Low Powered Multicore Architecture which utilizes Hybrid-Asynchronous cores which are energy efficient and consume less energy in battery powered mobile computing devices. A first step towards reliable battery life in mobile computing devices.

关键词： Asynchronous Cores Silicon Multicore Architectures Eco-friendly

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Precise subsidization grants for college students over big data optimized random forest 12

Precise subsidization grants for college students over big d...

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12th ieee international conference on Internet of things, 15th ieee international conference on Green computing and Communications, 12th ieee international conference on Cyber, Physical and Social computing and 5th ieee international conference on Smart data, ithings/GreenCom/CPSCom/Smartdata 2019

作者： Dai, Ranran Cheng, Shi Chen, Fengmei Huang, Tao Cheng, Xianyi Silicon Lake College JiangSu Kunshan215322 China School of Information Science and Technology NanTong University NanTong JiangSu22601 9 China

ISBN: (纸本)9781728129808

It is difficult to accurate identify and ascertain college students' grants. Open 'poorer than poor' funding mode lacks humanistic care. How to subsidize has always been a difficult problem in the education of University grants. In the past, due to the lack of data and the high cost of acquisition data, how to introduce big data processing technology and machine learning method into the accurate prediction of college student grants has been not achieved good results. We establish a prediction model in this paper, by optimizing the characteristic selection and running parameters for random forest model, also, we can precise subsidization grants for college students' based on balanced corpus strategy and big data analysis. the experiments on real data sets show that the accuracy can reach 91%, although not the most final determinative result, to improve the precision and quality of college student grant work, has the very vital significance. © 2019 ieee.

关键词： big data

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An Adaptive WKNN Outdoor Location Methodology Based on OTT and MR data 5

An Adaptive WKNN Outdoor Location Methodology Based on OTT a...

引用

5th ieee international conference on Cloud computing and intelligence Systems (CCIS)

作者： Xu, Shanshan Alexis, Huet Wang, Jibin Yu, Jian Nanjing Howso Technol Co Ltd Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538660058

Outdoor location is an important concern for mobile carriers to optimize wireless telecom network and coverage. When UPS information is not fully available, techniques such as fingerprinting can be developed to retrieve positioning. In this article, a novel fingerprint algorithm based on WKNN is proposed. this algorithm introduces additional weights computed with random forests and based on importance of each feature collected via measurement report. It also makes adaptive selection of reference points by discarding untrustworthy ones in order to refine precision of each user equipment positioning prediction. the whole methodology is implemented with Apache Spark framework and tested on real data flow from a major Chinese telecom carrier. Results show significant improvement of the methodology compared to both TA+AOA and classic WKNN fingerprinting methods.

关键词： Outdoor Positioning Fingerprinting Measurement Report Nearest Neighbors Random Forests

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datacom 2019 Committee

DataCom 2019 Committee

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big data intelligence and computing (datacom), international conference on

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big data for sustainability: a qualitative analysis 5

Big data for sustainability: a qualitative analysis

引用

5th international conference on Cloud computing and Artificial intelligence - Technologies and Applications (CloudTech)

作者： El Hilali, Wail El Manouar, Abdellah Idrissi, Mohammed Abdou Janati Mohammed V Univ Rabat Morocco

ISBN: (纸本)9781728161754

In this time and age, companies are facing difficult times to sustain their competitive advantages. the emergence of disruptive technologies, the bloody competition between rivals, the abrupt change of customer behaviors and the shortage of natural resources, all of these are drivers that push companies to think out of the box and to change the way business is done. Digital capabilities, and especially big data, comes as a new tool to use in order to continue creating and capturing value in a sustainable manner. this paper is a try to broaden the literature about this subject. A qualitative analysis was conducted inside three big size Moroccan companies in order to assess the impact of using big data on these firm's economic performances, social footprints and environmental negative externalities. the finding showed that embracing this technology has helped these companies for their quest to reach sustainability.

关键词： component big data sustainability digital capabilities digital transformation

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A Toolkit for Text Extraction and Analysis for Natural Language Processing Tasks 5

A Toolkit for Text Extraction and Analysis for Natural Langu...

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5th international conference on Artificial intelligence, big data, computing and data Communication Systems (ICABCD)

作者： Sefara, Tshephisho Joseph Mbooi, Mahlatse Mashile, Katlego Rambuda, thompho Rangata, Mapitsi CSIR Data Sci Dept Pretoria South Africa

ISBN: (数字)9781665484220

ISBN: (纸本)9781665484220

Text extraction is an important part of natural language processing (NLP) tasks. Most NLP tasks like text classification, machine translation, text-to-speech, text-based language identification, text summarization, and named-entity recognition involve the use of textual data. Such data is limited for low-resourced languages making it difficult to experiment advanced NLP techniques on these languages. this paper presents a Python-based toolkit for text analysis and text extraction from different types of images, documents, and audio files. the toolkit is built as a library that has functions that can be imported and utilized for text extraction.

关键词： natural language processing text extraction text analysis

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