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检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1361 条记录，以下是1311-1320 订阅

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Proceedings - 2015 IEEE international conference on Smart City, SmartCity 2015, Held Jointly with 8th IEEE international conference on Social computing and Networking, SocialCom 2015, 5th IEEE international conference on Sustainable computing and Communications, SustainCom 2015, 2015 international conference on big data intelligence and computing, datacom 2015, 5th international Symposium on Cloud and Service computing, SC2 2015

Proceedings - 2015 IEEE International Conference on Smart Ci...

引用

IEEE international conference on Smart City, SmartCity 2015

ISBN: (纸本)9781509018932

The proceedings contain 195 papers. The topics discussed include: detecting pedestrians behavior in building based on Wi-Fi signals;e-health services for elderly care based on Google cloud messaging;on interesting place finding in social sensing: an emerging smart city application paradigm;collaborative representation-based robust face recognition by discriminative low-rank representation;a self-adaptive video dual watermarking based on the motion characteristic and geometric invariant for ubiquitous multimedia;the role of big data on smart grid transition;sensing information modeling for smart city;exploration of collective pattern to improve location prediction of mobile phone users;performance modeling of preemption-based packet scheduling for data plane in software defined networks;and aspect-oriented customization of the scheduling algorithms and the resource access protocols of a real-time operating system family.

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Tutorials

Tutorials

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IEEE international Symposium on Dependable, Autonomic and Secure computing (DASC)

Provides an abstract for each of the tutorial presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conferenc... 详细信息

关键词： Medical services big data Cryptography Medical diagnostic imaging

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A Framework for Next Generation Agricultural Marketing System in Indian Context

A Framework for Next Generation Agricultural Marketing Syste...

引用

IEEE international WIE conference on Electrical and Computer Engineering (WIECON-ECE)

作者： Swapnil Shrivastava Supriya N Pal Big Data Analytics Group Centre for Development of Advanced Computing (CDAC) Bangalore India

ISBN: (数字)9781728144993

ISBN: (纸本)9781728145006

In order to curtail recent agrarian distress in the country, Prime Minister of India has set the objective of Doubling Farmer's Income by 2022. The available literature suggests that widespread adoption of organized Agricultural Marketing System has got the potential to improve economic condition of farmers. However, the prevalent Agricultural Marketing practices in India are mainly unorganized with several defects. The measures required to solve these shortcomings involve different facets such as policy, infrastructure, standardization and technology. The focus of this work is to propose framework for Next Generation Agricultural Marketing System in Indian context by making use of ICT, big data Analytics and Blockchain technologies. The proposed framework majorly comprises of Market intelligence, Food Supply Chain and One Stop Mobile App as functionalities. It also leverages on government initiatives such as DigiLocker, Aadhaar and Jan Dhan Yojna. The intent is to facilitate farmers to drive Agricultural Marketing System as a co-operative, provide ease of use of available resources to farmers and enable them to take informed decisions.

关键词： Supply chains Forecasting big data Next generation networking Machine learning Market research

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Proceedings - 2017 IEEE 15th international conference on Dependable, Autonomic and Secure computing, 2017 IEEE 15th international conference on Pervasive intelligence and computing, 2017 IEEE 3rd

Proceedings - 2017 IEEE 15th International Conference on Dep...

引用

15th IEEE international conference on Dependable, Autonomic and Secure computing, 2017 IEEE 15th international conference on Pervasive intelligence and computing, 2017 IEEE 3rd international conference on big data intelligence and computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-datacom-CyberSciTec 2017

ISBN: (纸本)9781538619551

The proceedings contain 203 papers. The topics discussed include: semantic neuron networks based associative memory model;an integrative and precise approach in personality computing based on ontic personae modeling;deep convolution neural network discriminator for distinguishing seborrheic keratosis and flat warts;pairwise preference over mixed-type item-sets based Bayesian personalized ranking for collaborative filtering;design considerations for cyber security testbeds: a case study on a cyber security testbed for education;detecting Android malware based on extreme learning machine;a survey of semantics-aware performance optimization for data-intensive computing;identifying image tags from Instagram hashtags using the HITS algorithm;caching scheme with edge nodes for mobile cyber physical systems;a study on communication network reliability for advanced metering infrastructure in smart grid;interference management for physical layer security in heterogeneous networks;a real example of Jong Nang and tomb gate of cyber biology Jeju island: its fundamental principle of DNA code;MMHG: multi-modal hypergraph learning for overall survival after D2 gastrectomy for gastric cancer;respiratory sounds feature learning with deep convolutional neural networks;a bus arrival time prediction method based on GPS position and real-time traffic flow;and re-thinking online offenders' SKRAM: individual traits and situational motivations as additional risk factors for predicting cyber attacks.

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Developing Adaptive Islamic Law Business Processes Models for Islamic Finance and Banking by Text Mining the Holy Qur'an and Hadith

Developing Adaptive Islamic Law Business Processes Models fo...

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IEEE international conference on Pervasive intelligence and computing

作者： Munir Majdalawieh Farhi Marir Issam Tiemsani College of Technological Innovation Zayed University Department of Finance& Economics Qatar University

ISBN: (纸本)9781538619575

A large number of conventional financial institutions, especially banks are moving to an Islamic financial model that's comply with the Shari'a Law with little change to current conventional practices (reverse eningineer current business processes) to accommodate the market for Islamic finance. This study is an attempt to design and develop the business processes for the Islamic financial institutions' (IFIs) products by investigating and collecting information through Islamic literature, surveys and interviews of experts in Islamic jurisprudence, regulators, academic and Islamic finance and banking practitioners. Then the findings will be assessed and evaluated using a Qur'anic Financial Corpus and use computational and analytical approaches to mine the Qur'an and the Hadith to find hidden knowledge on Islamic financial business processes. The knowledge acquired from this investigation will be translated into an Islamic financial process model to be adapted by Islamic and non-Islamic financial institutions. The outcome of this research will influence the future development, growth and diversification of Islamic financial services worldwide.

关键词： Islamic Finance Shari'a law Business processes Qur'anic corpus Murabaha big data Text mining

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Intelligent Subevent Detection based on Social Network data

Intelligent Subevent Detection based on Social Network Data

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IEEE international conference on Pervasive intelligence and computing

作者： Diogo Nolasco Jonice Oliveira Programa de Pos-Graduacao em Informatica Universidade Federal do Rio de Janeiro Departamento de Ciencia da Computacao Universidade Federal do Rio de Janeiro

ISBN: (纸本)9781538619575

Event Detection and Tracking has been a big challenge with the growth and diversification of data sources, especially in large urban centers. As components of a complex event, subevents have not received many attempts of detection by applications and studies. This work uses a human as a sensor approach via social network data to automatically detect subevents within events reported by media. These kind of data usually consists of short texts with colloquial language which provides an additional challenge for automated applications. To overcome these challenges, a scalable topic modeling based algorithm is proposed to identify and label the subevents to ease the analysis by humans. Evaluation is made in Brazil's 2013 political protests scenario, comparing subevents detected with news published by mainstream media regarding the same subjects. Results show that even with the particular data extracted from social media, the majority of subevents detected corresponded to real subevents published in official and traditional media. These results can open new applications in event tracking and emergence scenarios as social media usually has a minimum delay between an event and a report.

关键词： Topic labeling Topic modeling Subevent detection Social networks

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FOG-Engine: Towards big data Analytics in the Fog

FOG-Engine: Towards Big Data Analytics in the Fog

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14th IEEE international conference on Dependable, Autonomic and Secure computing, DASC 2016, 14th IEEE international conference on Pervasive intelligence and computing, PICom 2016, 2nd IEEE international conference on big data intelligence and computing, datacom 2016 and 2016 IEEE Cyber Science and Technology Congress, CyberSciTech 2016, DASC-PICom-datacom-CyberSciTech 2016

作者： Mehdipour, Farahd Javadi, Bahman Mahanti, Aniket Tech Futures Lab Unitec Institute of Technology Auckland New Zealand Western Sydney University SydneyNSW Australia University of Auckland Auckland New Zealand

ISBN: (纸本)9781509040650

Existing platforms fall short in providing effective solutions for big data analytics while the demands for processing large quantities of data in real-time are increasing. Moving data analytics towards where the data is generated and stored could be a solution for addressing this issue. In this paper, we propose a solution referred as FOG-engine, which is integrated into IoTs near the ground and facilitates data analytics before offloading large amounts of data to a central location. In this work, we introduce a model for data analytic using FOG-engines and discuss our plan for evaluating its efficacy in terms of several performance metrics such as processing speed, network bandwidth, and data transfer size. © 2016 IEEE.

关键词： big data

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Efficient On/Off-Line Query Pre-processing for Telecom Social Streaming data

Efficient On/Off-Line Query Pre-processing for Telecom Socia...

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作者： Wu, Cheng Fu, Jigao Zhang, Zhen Liu, Chi Harold School of Software Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781509040650

Social media are primarily generated and transmitted over Internet from mobile based applications/tools, e.g., Flickr, YouTube, etc., for sharing and discussing information among people. Most of these applications are putting forward from desktop to mobile client side, since smart devices are growing by leaps and bounds, and they tend to take fully advantage of tunnels that telecom companies offer. Like any other industries, telecom operators also face tough competitions from 'over-the-top'(OTT) service providers. Therefore, they are prone to bring in big data analytical techniques to take fully use of streaming data they possessed. To this end, in this paper, we propose a novel query system specifically designed for telecom networks that integrates both online pre-processing and offline analytics for social streaming data. Furthermore, our framework is able to speedup the query processing by creating and parsing an Abstract Syntax Tree (AST). Extensive experimental results show the effectiveness of proposed and implemented system. © 2016 IEEE.

关键词： big data

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PyramidViz: Visual Analytics and big data Visualization for Frequent Patterns

PyramidViz: Visual Analytics and Big Data Visualization for ...

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作者： Leung, Carson K. Kononov, Vadim V. Pazdor, Adam G.M. Jiang, Fan Department of Computer Science University of Manitoba WinnipegMB Canada

ISBN: (纸本)9781509040650

Frequent pattern mining aims discover implicit, previously unknown and potentially useful knowledge in the form of frequently co-occurring items, events, or objects. These discovered frequent patterns helps reveal interesting relationships such as consumer shopper behaviour. Existing mining algorithms mostly return a long textual list of frequent patterns to users. Such a long list may not be comprehensible by many users. As a picture is worth a thousand words, visual representation of frequent patterns is more comprehensible. Consequently, several visualizers have been proposed. While they are popular and benefit from a few advantages, they also suffer from some disadvantages. In this paper, we present a visual analytic solution, called PyramidViz, for visualizing and analyzing frequent patterns. PyramidViz shows frequent patterns in an informative and intuitive fashion so that users can easily get an insight about frequency of frequent patterns and relationships (e.g., prefix-extension relationships) among related frequent patterns. Evaluation results show the effectiveness and practicality of PyramidViz in visual analytics and big data visualization of frequent patterns for various reallife applications. © 2016 IEEE.

关键词： Visualization

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A big data based intelligent decision support system for sustainable regional development

A big data based intelligent decision support system for sus...

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IEEE international conference on Smart City, SmartCity 2015

作者： Zhou, Hong Noble, Christopher Cotter, Julie School of Mechanical and Electrical Engineering Faculty of Health Engineering and Science University of Southern Queensland Toowoomba Australia University of Southern Queensland Australia

ISBN: (纸本)9781509018932

Timely intelligent decision making is increasingly important for modern society. With the availability of big data and advanced artificial intelligence in decision making, more objective and evidence-based quantitative smart decisions can be made in a timely manner. This research proposed a big data based intelligent decision support system (B-IDSS) for sustainable business development. The system can be used by both the government agencies and corporate business (e.g. farms. mining) in advanced planning, collaboration and management. This paper also addresses the performance optimization as bilevel decision-making problem with one leader and multiple followers. An extended Kuhn-Tucker approach is introduced as one of the algorithms that can be adapted in the system. © 2015 IEEE.

关键词： Sustainable development

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