• Title/Summary/Keyword: Big6

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Big IoT Healthcare Data Analytics Framework Based on Fog and Cloud Computing

  • Alshammari, Hamoud;El-Ghany, Sameh Abd;Shehab, Abdulaziz
    • Journal of Information Processing Systems
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    • v.16 no.6
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    • pp.1238-1249
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    • 2020
  • Throughout the world, aging populations and doctor shortages have helped drive the increasing demand for smart healthcare systems. Recently, these systems have benefited from the evolution of the Internet of Things (IoT), big data, and machine learning. However, these advances result in the generation of large amounts of data, making healthcare data analysis a major issue. These data have a number of complex properties such as high-dimensionality, irregularity, and sparsity, which makes efficient processing difficult to implement. These challenges are met by big data analytics. In this paper, we propose an innovative analytic framework for big healthcare data that are collected either from IoT wearable devices or from archived patient medical images. The proposed method would efficiently address the data heterogeneity problem using middleware between heterogeneous data sources and MapReduce Hadoop clusters. Furthermore, the proposed framework enables the use of both fog computing and cloud platforms to handle the problems faced through online and offline data processing, data storage, and data classification. Additionally, it guarantees robust and secure knowledge of patient medical data.

Parental Participation and Parenting Stress According to the Big Five Personality Types of Fathers With Young Children (유아기 자녀를 둔 아버지의 Big5성격유형에 따른 양육참여 및 양육스트레스)

  • JongSeung, Yun
    • Korean Journal of Childcare and Education
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    • v.18 no.6
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    • pp.145-162
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    • 2022
  • Objective: The purpose of this study was to examine the differences in parental involvement and parenting stress according to the father's personality type. Methods: The subjects of this study were 302 fathers with children aged three to five living in Seoul, and a survey was conducted on their Big Five personality types, parental involvement, and parenting stress.The collected data were analyzed using K-means cluster analysis and covariance analysis. Results: In this study, fathers' personality types were classified into four types: 'sincerity, friendship, openness'(21.5%), 'neuroticism'(27.8%), 'sincerity'(29.4%), and 'low sincerity'(21.1%). These are the exact same Fathers in the 'sincere, friendly, open' group showed higher parental involvement and lower parental stress, while fathers in the 'neurotic' group showed lower parenting involvement and higher parenting stress. Conclusion/Implications: There was a difference in parental involvement and parenting stress according to the father's personality type.Based on these results, it is expected that the understanding of the father's personality will be come clearer and the foundation for constructing a program related to parenting which considers personality types will be established.

BigData Research in Information Systems : Focusing on Journal Articles about Information Systems (정보시스템 분야의 빅데이터 연구 흐름 분석 : Information Systems 관련 저널을 중심으로)

  • Park, Kyungbo;Kim, Juyeong;Kim, Han-Min
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.9 no.6
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    • pp.681-689
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    • 2019
  • The 46th Davos Forum of the World Economic Forum (WEF) predicts the continued growth of the 4th industry in the future. Currently, the 4th industry is attracting attention in various academic and practical fields. As a core technology of the 4th industry, Big Data is regarded as a major resource to lead the 4th industrial revolution along with artificial intelligence. As the growing interest in Big Data, researches on it are actively being done. However, literature studies on existing Big Data are focused on qualitative research, and quantitative research is insufficient. Therefore, this study aims to analyze the big data research flow in MIS field and to make academic thirst for quantification. This study has collected 145 abstracts of big data papers published in major journals in MIS field and confirmed that a majority of papers are published in Decision Support Systems Journal. Text mining and text network analysis were performed only for DSS journals to eliminate bias. As a result of the analysis, it was found out that researches on combining big data in the management field between 2012 and 2014, and researches on system development and analysis method for using big data from 2015 to 2017 were conducted.

Real-time Scheduling on Heterogeneous Multi-core Architecture for Energy Conservation of Smart Mobile Devices (스마트 모바일 장치의 에너지 보존성을 높이기 위한 비대칭 멀티 코어 기반 실시간 태스크 스케쥴링)

  • Lim, Sung-Hwa
    • Journal of Digital Contents Society
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    • v.19 no.6
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    • pp.1219-1224
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    • 2018
  • Nowaday, smart mobile devices on Internet of Things are required to process and deliver greate amount of data in real-time. Therefore, heterogeneous mult-core architecture such the big.LITTLE core architecture, which shows high energy conservation while guaranteeing high performance, are widely employed on up to date smart mobile devices. The LITTLE cores should be highly utilized to gain higher energy conservation because LITTLE cores have much higher energy efficiency than big cores. In this paper, we propose a core selection algorithm, which tries to firstly assign a real-time task on a LITTLE core rather a big core while the task can be finished within its own deadline. We also perform simulation as performance evaluation to show that our proposed algorithm shows higher energy conservation while guaranteeing the required performance.

An Analysis of Factors Affecting Quality of Life through the Analysis of Public Health Big Data (클라우드 기반의 공개의료 빅데이터 분석을 통한 삶의 질에 영향을 미치는 요인분석)

  • Kim, Min-kyoung;Cho, Young-bok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.6
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    • pp.835-841
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    • 2018
  • In this study, we analyzed public health data analysis using the hadoop-based spack in the cloud environment using the data of the Community Health Survey from 2012 to 2014, and the factors affecting the quality of life and quality of life. In the proposed paper, we constructed a cloud manager for parallel processing support using Hadoop - based Spack for open medical big data analysis. And we analyzed the factors affecting the "quality of life" of the individual among open medical big data quickly without restriction of hardware. The effects of public health data on health - related quality of life were classified into personal characteristics and community characteristics. And multiple-level regression analysis (ANOVA, t-test). As a result of the experiment, the factors affecting the quality of life were 73.8 points for men and 70.0 points for women, indicating that men had higher health - related quality of life than women.

KISTI-ML Platform: A Community-based Rapid AI Model Development Tool for Scientific Data (KISTI-ML 플랫폼: 과학기술 데이터를 위한 커뮤니티 기반 AI 모델 개발 도구)

  • Lee, Jeongcheol;Ahn, Sunil
    • Journal of Internet Computing and Services
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    • v.20 no.6
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    • pp.73-84
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    • 2019
  • Machine learning as a service, the so-called MLaaS, has recently attracted much attention in almost all industries and research groups. The main reason for this is that you do not need network servers, storage, or even data scientists, except for the data itself, to build a productive service model. However, machine learning is often very difficult for most developers, especially in traditional science due to the lack of well-structured big data for scientific data. For experiment or application researchers, the results of an experiment are rarely shared with other researchers, so creating big data in specific research areas is also a big challenge. In this paper, we introduce the KISTI-ML platform, a community-based rapid AI model development for scientific data. It is a place where machine learning beginners use their own data to automatically generate code by providing a user-friendly online development environment. Users can share datasets and their Jupyter interactive notebooks among authorized community members, including know-how such as data preprocessing to extract features, hidden network design, and other engineering techniques.

A GPU-enabled Face Detection System in the Hadoop Platform Considering Big Data for Images (이미지 빅데이터를 고려한 하둡 플랫폼 환경에서 GPU 기반의 얼굴 검출 시스템)

  • Bae, Yuseok;Park, Jongyoul
    • KIISE Transactions on Computing Practices
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    • v.22 no.1
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    • pp.20-25
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    • 2016
  • With the advent of the era of digital big data, the Hadoop platform has become widely used in various fields. However, the Hadoop MapReduce framework suffers from problems related to the increase of the name node's main memory and map tasks for the processing of large number of small files. In addition, a method for running C++-based tasks in the MapReduce framework is required in order to conjugate GPUs supporting hardware-based data parallelism in the MapReduce framework. Therefore, in this paper, we present a face detection system that generates a sequence file for images to process big data for images in the Hadoop platform. The system also deals with tasks for GPU-based face detection in the MapReduce framework using Hadoop Pipes. We demonstrate a performance increase of around 6.8-fold as compared to a single CPU process.

The Study on Strategy of National Information for Electronic Government of S. Korea with Public Data analysed by the Application of Scenario Planning (공공데이터를 활용한 국가정보화 전략연구 - 시나리오플래닝을 적용하여 -)

  • Lee, Sang-Yun;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.6
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    • pp.1259-1273
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    • 2012
  • As a society of knowledge and information has been developed rapidly, because of changing from web environment to ubiquitous environment, a lot of countries across the world as well as S. Korea for national information with electronic Government have a variety of changes with big data. So this study is about development for national information and e-government of S. Korea with public data as big data analysed by the application of scenario planning. And then this research focused on the strategy consulting of national information with e-Government of S. Korea for utilization of public data as big data analysed by the application of 'scenario planning' as a foresight method. As a result, the future policy for utilization of public data as big data for national information with electronic government of S. Korea is to further spur the development of technology for linked data with semantic web for 'understanding of machine' than 'understanding of man'.

A Study on the Analysis of Regional Tourism in Uijeongbu Using Big Data (빅 데이터를 활용한 의정부 지역 관광 분석 연구)

  • Lee, Jong-Yong;Jung, Kye-Dong;Ryu, Ki-hwan;Park, SeaYoung
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.1
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    • pp.413-418
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    • 2020
  • The travel pattern of tourists for the development of the tourist course is designed to collect and analyze tourist information based on the big data of the carrier to improve the quality of the tourist course. In particular, the analyzed data is used to derive empirical data that can estimate the effect of tourists' inflow into tourism, and to utilize the information as basic data for the development of the tourist course. In addition, the travel pattern of tourists for the development of regional tourism courses is to collect and analyze information on the route and duration of tourists' travel based on big data collected by telecom operators, credit card companies and other data to improve the quality of tourist course development, and to derive empirical data to estimate the effect of tourist inflow through the analyzed data, based on the characteristics of the tourism course and the data needed for the development of new tourist courses in the future.

A study on the natural history virtual reality contents using depaysement (데페이즈망 기법을 활용한 자연사VR 콘텐츠 연구)

  • Park, Ki-Deok;Chung, Jean-Hun
    • Journal of Digital Convergence
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    • v.17 no.6
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    • pp.365-371
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    • 2019
  • In this study, VR contents were produced by using the rose which is the material of the tomb of the surrealistic work wrestler of Rene Magritte, an artistic genre, as a motive. In conclusion, the distortion (spatial modulation) of the image scale is connected to the dynamic-curve and texture-soft areas, and the superposition (combination of contradictory images) is called the big-size, irregular-depth area, Are connected to the positions of big-size and irregular-space regions. The theme of the work was Dream, and the plants and roses patterns were produced in each timeline, and overlap, scale, distortion, overlap, distortion, and scale were used.