• Title/Summary/Keyword: multimedia big data

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SNS using Big Data Utilization Research (빅데이타를 이용한 SNS 활용방안 연구)

  • Shin, Seung-Jung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.6
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    • pp.267-272
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    • 2012
  • IT convergence, social media, and the companies' customer service industry advancement, data collection activities, explosion of multimedia content with increased smartphone penetration, SNS activation networks to expand the pool of things, 10 years ago, the amount of data eunneun evenly across industries, EDW (Enterprisehad increased the demand for the Data Warehouse).Recent proliferation of SNS users and applied research background with Big Data as a new study is proposed to proceed.

Sensors Network and Security and Multimedia Enhancement

  • Woo, Seon-mi;Lee, Malrey
    • International Journal of Internet, Broadcasting and Communication
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    • v.8 no.1
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    • pp.64-68
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    • 2016
  • These fields are integrated to visualize and finalize the proposed development, in simulation environment. SCADA (supervisory control and data acquisition) systems and distributed control systems (DCSs) are widely deployed in all over the world, which are designed to control the industrial infrastructures, in real ways. To supervise and control the various parts of designed systems; trends to require a deep knowledge to understand the overall functional needs of industries, which could be a big challenge. Industrial field devices (or network sensors) are usually distributed in many locations and are controlled from centralized site (or main control center); the communication provides various signs of security issues. To handle these issues, the research contribution will twofold: a method using cryptography is deployed in critical systems for security purposes and overall transmission is controlled from main controller site. At controller site, multimedia components are employed to control the overall transmission graphically, such as system communication, bytes flows, security embedded parameters and others, by the means of multimedia technology.

Analysis Model Evaluation based on IoT Data and Machine Learning Algorithm for Prediction of Acer Mono Sap Liquid Water

  • Lee, Han Sung;Jung, Se Hoon
    • Journal of Korea Multimedia Society
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    • v.23 no.10
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    • pp.1286-1295
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    • 2020
  • It has been increasingly difficult to predict the amounts of Acer mono sap to be collected due to droughts and cold waves caused by recent climate changes with few studies conducted on the prediction of its collection volume. This study thus set out to propose a Big Data prediction system based on meteorological information for the collection of Acer mono sap. The proposed system would analyze collected data and provide managers with a statistical chart of prediction values regarding climate factors to affect the amounts of Acer mono sap to be collected, thus enabling efficient work. It was designed based on Hadoop for data collection, treatment and analysis. The study also analyzed and proposed an optimal prediction model for climate conditions to influence the volume of Acer mono sap to be collected by applying a multiple regression analysis model based on Hadoop and Mahout.

A Generation and Accuracy Evaluation of Common Metadata Prediction Model Using Public Bicycle Data and Imputation Method

  • Kim, Jong-Chan;Jung, Se-Hoon
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.287-296
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    • 2022
  • Today, air pollution is becoming a severe issue worldwide and various policies are being implemented to solve environmental pollution. In major cities, public bicycles are installed and operated to reduce pollution and solve transportation problems, and operational information is collected in real time. However, research using public bicycle operation information data has not been processed. This study uses the daily weather data of Korea Meteorological Agency and real-time air pollution data of Korea Environment Corporation to predict the amount of daily rental bicycles. Cross- validation, principal component analysis and multiple regression analysis were used to determine the independent variables of the predictive model. Then, the study selected the elements that satisfy the significance level, constructed a model, predicted the amount of daily rental bicycles, and measured the accuracy.

Analysis of Traffic Accident using Association Rule Model

  • Ihm, Sun-Young;Park, Young-Ho
    • Journal of Multimedia Information System
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    • v.5 no.2
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    • pp.111-114
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    • 2018
  • Traffic accident analysis is important to reduce the occurrence of the accidents. In this paper, we analyze the traffic accident with Apriori algorithm to find out an association rule of traffic accident in Korea. We first design the traffic accident analysis model, and then collect the traffic accidents data. We preprocessed the collected data and derived some new variables and attributes for analyzing. Next, we analyze based on statistical method and Apriori algorithm. The result shows that many large-scale accident has occurred by vans in daytime. Medium-scale accident has occurred more in day than nighttime, and by cars more than vans. Small-scale accident has occurred more in night time than day time, however, the numbers were similar. Also, car-human accident is more occurred than car-car accident in small-scale accident.

Data Mining for Scuticociliatosis Outbreak Patterns in Cultured Olive Flounder Paralichthys olivaceus in Jeju, Korea (데이터 마이닝을 이용한 제주 양식 넙치(Paralichthys olivaceus)의 스쿠티카증 발생 패턴 분석)

  • Kim, Hae-Ran;Jung, Sung-Ju;Kim, Sung-Hyun;Park, Jeong-Seon;Ceong, Hee-Taek;Han, Soon-Hee
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.53 no.5
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    • pp.740-751
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    • 2020
  • In the aquaculture industry, few studies are analyzing big data for intrinsic meaning. Fishcare Laboratory (www.fishcare.kr) diagnostic data from 2016-2018 was analyzed for scuticociliatosis (caused by Miamiensis avidus) outbreak patterns in cultured olive flounder Paralichthys olivaceus in Jeju, Korea. The scuticociliatosis monthly occurrence ratio is reported in the summary table after preparing and filtering the basic dataset model. Nonparametric test results suggest differences in the water temperature, body length, and weight between groups with and without scuticociliatosis. Data distribution visualization revealed that shorter body length and lighter weight increased the occurrence of scuticociliatosis. The association rule mining technique was applied to determine the primary clinical signs of mixed scuticociliatosis and bacterial infections. Venn diagrams were used to report clinical signs and suggest commonalities. These results may help diagnose and treat fish and provide a decision-making reference.

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.

Design and Implementation of a System for Recommending Related Content Using NoSQL (NoSQL 기반 연관 콘텐츠 추천 시스템의 설계 및 구현)

  • Ko, Eun-Jeong;Kim, Ho-Jun;Park, Hyo-Ju;Jeon, Young-Ho;Lee, Ki-Hoon;Shin, Saim
    • Journal of Korea Multimedia Society
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    • v.20 no.9
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    • pp.1541-1550
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    • 2017
  • The increasing number of multimedia content offered to the user demands content recommendation. In this paper, we propose a system for recommending content related to the content that user is watching. In the proposed system, relationship information between content is generated using relationship information between representative keywords of content. Relationship information between keywords is generated by analyzing keyword collocation frequencies in Internet news corpus. In order to handle big corpus data, we design an architecture that consists of a distributed search engine and a distributed data processing engine. Furthermore, we store relationship information between keywords and relationship information between keywords and content in NoSQL to handle big relationship data. Because the query optimizer of NoSQL is not as well developed as RDBMS, we propose query optimization techniques to efficiently process complex queries for recommendation. Experimental results show that the performance is improved by up to 69 times by using the proposed techniques, especially when the number of requested related keywords is small.

Emerging Internet Technology & Service toward Korean Government 3.0

  • Song, In Kuk
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.2
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    • pp.540-546
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    • 2014
  • Recently a new government has announced an action plan known as the government 3.0, which aims to provide customized services for individual people, generate more jobs and support creative economy. Leading on from previous similar initiatives, the new scheme seeks to focus on open, share, communicate, and collaborate. In promoting Government 3.0, the crucial factor might be how to align the core services and policies of Government 3.0 with correspoding technologies. The paper describes the concepts and features of Government 3.0, identifies emerging Internet-based technologies and services toward the initiative, and finally provides improvement plans for Government 3.0. As a result, 10 issues to be brought together include: Smart Phone Applications and Service, Mobile Internet Computing and Application, Wireless and Sensor Network, Security & Privacy in Internet, Energy-efficient Computing & Smart Grid, Multimedia & Image Processing, Data Mining and Big Data, Software Engineering, Internet Business related Policy, and Management of Internet Application.

Digital Forensic for Location Information using Hierarchical Clustering and k-means Algorithm

  • Lee, Chanjin;Chung, Mokdong
    • Journal of Korea Multimedia Society
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    • v.19 no.1
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    • pp.30-40
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    • 2016
  • Recently, the competition among global IT companies for the market occupancy of the IoT(Internet of Things) is fierce. Internet of Things are all the things and people around the world connected to the Internet, and it is becoming more and more intelligent. In addition, for the purpose of providing users with a customized services to variety of context-awareness, IoT platform and related research have been active area. In this paper, we analyze third party instant messengers of Windows 8 Style UI and propose a digital forensic methodology. And, we are well aware of the Android-based map and navigation applications. What we want to show is GPS information analysis by using the R. In addition, we propose a structured data analysis applying the hierarchical clustering model using GPS data in the digital forensics modules. The proposed model is expected to help support the IOT services and efficient criminal investigation process.