• Title/Summary/Keyword: ICT 기반 시스템

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Flood Disaster Management for Local Government (지자체 맞춤형 홍수재해관리)

  • Cho, Wan Hee;Park, Jeong Su;Kim, Jong Rae;Shin, Cheol Kyun;Lee, Yong Shin
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.114-114
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    • 2015
  • 최근 기후변화로 인해 지구촌 곳곳은 이전에 경험하지 못한 극한 홍수재해로 몸살을 앓고 있다. 2011년 태국에서는 짜오프라야강 범람으로 국토의 70% 이상이 침수되었고, 2013년 인도 북부지역에서는 갠지스강 및 지류의 범람, 산사태, 가옥붕괴 등으로 1,000여명이 숨지고 관광객 및 순례객 7만여명의 발이 묶이는 피해가 발생하였으며, 2014년 발칸반도에서는 120년만의 폭우로 인하여 30여명이 사망하고 100만명의 이재민이 발생하였다. 국내의 경우 2011년 수도권을 중심으로 하루에 300mm가 넘는 기록적 호우가 쏟아지면서 주택과 도로의 침수, 산사태 등으로 많은 인명 및 재산피해가 발생하였다. 또한 2014년 8월 경남 부산지역에는 시간당 130mm가 넘는 국지성 호우에 따른 산사태, 침수 등으로 도심기능이 마비되는 피해가 발생하기도 하였다. 이처럼 대부분의 자연재난은 태풍 및 집중호우 등 물재해로 발생하고 있으며, 국내의 경우 2012년 전체 자연재난의 95.6%, 2013년 전체 자연재난의 93%를 물재해가 차지하였다. 이에 구조적 비구조적 홍수 재해 저감대책 수립 및 시행 등 지속적인 물관리 노력으로 대하천에서 발생하는 홍수피해는 크게 감소하였으나, 지자체를 중심으로 운영 관리되고 있는 중소하천에서의 피해는 오히려 점차 증가하고 있다. 조사에 따르면 최근 5년간(2007~2011) 홍수피해의 98% 이상이 중소하천을 중심으로 발생한 것으로 발표된 바 있다. 특히 지자체의 경우 전문인력 및 기술력 부족, 열악한 재정 등으로 피해가 반복되고 있는 실정이다. 이에 따라 중소하천과 같이 소외된 지역의 물복지 향상을 위해서는 홍수재해 상황에 신속하고 효과적으로 대응하기 위한 과학적 체계적인 선진 홍수재해 관리체계의 구축이 요구되는 바이다. 이에 물관리 전문기관인 K-water에서는 지난 2010년부터 ICT기반의 우수한 물관리 기술력과 홍수대응 Know-How를 활용하여 '지자체 맞춤형 홍수재해관리시스템' 구축을 지원하고 있다. 본 시스템은 상 하류의 다양한 재난 정보를 수집 통합하고, 수집된 정보를 활용한 홍수분석을 통해 예방적 재난대응 체계를 구축하는 것으로, K-water는 지난 2010년 남원시를 시작으로 무주군, 군산시, 진안군 등의 시스템 구축을 지원하고 있다. 재난은 복구보다 예방이 우선되어야 함은 모두 다 아는 사실이지만 예산문제 등으로 항상 소 잃고 외양간 고치는 일이 아직까지 반복되고 있다. K-water는 물관리 전문 공기업으로써의 역할을 다하고, 예방 위주의 재난관리 체계 마련을 위해 '지자체 맞춤형 홍수재해관리시스템' 구축 지원을 지속적으로 확대해 나갈 것이다.

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Cyber KillChain Based Security Policy Utilizing Hash for Internet of Things (해시를 활용한 사이버킬체인 기반의 사물인터넷 보안 정책)

  • Jeong, So-Won;Choi, Yu-Rim;Lee, Il-Gu
    • Journal of Digital Convergence
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    • v.16 no.9
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    • pp.179-185
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    • 2018
  • Technology of Internet of Things (IoT) which is receiving the spotlight recently as a new growth engine of Information Communications Technology (ICT) industry in the $4^{th}$ Industrial Revolution needs trustworthiness beyond simple technology of security. IoT devices should consider trustworthiness from planning and design of IoTs so that everyone who develop, evaluate and use the device can measure and trust its security. Increased number of IoTs and long lifetime result in the increased securituy vulnerability due to the difficulty of software patch and update. In this paper, we investigated security and scalability issues of current IoT devices through research of the technical, political and industrial trend of IoT. In order to overcome the limitations, we propose an automatic verification of software integrity utilizing and a political solution to apply cyber killchain based security mechanism using hash which is an element technology of blockchain to solve these problems.

A Research on stock price prediction based on Deep Learning and Economic Indicators (거시지표와 딥러닝 알고리즘을 이용한 자동화된 주식 매매 연구)

  • Hong, Sunghyuck
    • Journal of Digital Convergence
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    • v.18 no.11
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    • pp.267-272
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    • 2020
  • Macroeconomics are one of the indicators that are preceded and analyzed when analyzing stocks because it shows the movement of a country's economy as a whole. The overall economic situation at the national level, such as national income, inflation, unemployment, exchange rates, currency, interest rates, and balance of payments, has a great affect on the stock market, and economic indicators are actually correlated with stock prices. It is the main source of data for analysts to watch with interest and to determine buy and sell considering the impact on individual stock prices. Therefore, economic indicators that impact on the stock price are analyzed as leading indicators, and the stock price prediction is predicted through deep learning-based prediction, after that the actual stock price is compared. If you decide to buy or sell stocks by analysis of stock prediction, then stocks can be investments, not gambling. Therefore, this research was conducted to enable automated stock trading by using macro-indicators and deep learning algorithms in artificial intelligence.

A study on implementation of background subtraction algorithm using LMS algorithm and performance comparative analysis (LMS algorithm을 이용한 배경분리 알고리즘 구현 및 성능 비교에 관한 연구)

  • Kim, Hyun-Jun;Gwun, Taek-Gu;Joo, Yank-Ick;Seo, Dong-Hoan
    • Journal of Advanced Marine Engineering and Technology
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    • v.39 no.1
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    • pp.94-98
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    • 2015
  • Recently, with the rapid advancement in information and computer vision technology, a CCTV system using object recognition and tracking has been studied in a variety of fields. However, it is difficult to recognize a precise object outdoors due to varying pixel values by moving background elements such as shadows, lighting change, and moving elements of the scene. In order to adapt the background outdoors, this paper presents to analyze a variety of background models and proposed background update algorithms based on the weight factor. The experimental results show that the accuracy of object detection is maintained, and the number of misrecognized objects are reduced compared to previous study by using the proposed algorithm.

Design and Implementation of Problem-Based Learning System Based on Video Communication Technology (화상통신기술을 활용한 문제중심학습 시스템 설계 및 구현)

  • Kim, Bum-Shik;An, Sung-Hun;Kim, Dong-Ho
    • Journal of The Korean Association of Information Education
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    • v.8 no.2
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    • pp.167-176
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    • 2004
  • Due to the development of information communication technology, educational environment has undergone much change and various types of teaching and learning methods based on information communication technology has been suggested. Recently, remote education using the internet are also spreading. However, in current classrooms, students are asked to do an teacher-centered assignment, which they are required to collect and report some information using the internet. This method does not help students use the advantages of learning using the internet, which stimulate students-students interaction and teacher-students interaction.Thus, this study focused on the problem-based learning system based on video communication technology. The researcher designed the problem-based learning system based on video communication technology and applied the system to classes at elementary school. The results were analyzed in terms of students-students interaction and teacher-students interaction in the internet. This research found that the problem-based learning system stimulates teacher and students communication and has positive effects on students' attitude and interest in learning. This research proposes that the traditional teacher-centered teaching method can be supplemented with cyber space learning, which has the merit of problem-based learning model.

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A Study on the Document Topic Extraction System Based on Big Data (빅데이터 기반 문서 토픽 추출 시스템 연구)

  • Hwang, Seung-Yeon;An, Yoon-Bin;Shin, Dong-Jin;Oh, Jae-Kon;Moon, Jin Yong;Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.5
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    • pp.207-214
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    • 2020
  • Nowadays, the use of smart phones and various electronic devices is increasing, the Internet and SNS are activated, and we live in the flood of information. The amount of information has grown exponentially, making it difficult to look at a lot of information, and more and more people want to see only key keywords in a document, and the importance of research to extract topics that are the core of information is increasing. In addition, it is also an important issue to extract the topic and compare it with the past to infer the current trend. Topic modeling techniques can be used to extract topics from a large volume of documents, and these extracted topics can be used in various fields such as trend prediction and data analysis. In this paper, we inquire the topic of the three-year papers of 2016, 2017, and 2018 in the field of computing using the LDA algorithm, one of Probabilistic Topic Model Techniques, in order to analyze the rapidly changing trends and keep pace with the times. Then we analyze trends and flows of research.

Localization of SMART Education: Focused on Jeollanamdo (지역화 기반 스마트교육 정책 방안 모색: 전라남도를 중심으로)

  • Heo, Heeok;Lee, Hyeon Woo;Kang, Euisung;Kim, Hyeonjin;Lim, Kyu Yon
    • Journal of Digital Convergence
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    • v.12 no.5
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    • pp.25-37
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    • 2014
  • This study aims to localize the national policies of SMART education for regional educational development in Jeollanamdo province. To achieve the goal, this study analyzed the current status of ICT use in education in the province through a survey, interviews, and the existing relevant policies in national and international levels. The suggested policies were validated by experts from the field of education. As a result, 20 tasks in educational policies of 4 domains were suggested for the Jeollanamdo SMART education. Among them, the development of SMART educational models, building a professional development of teachers for successful implementation, and the development of online performance support system were prioritized for successful educational innovation for Jeollanamdo.

Development of Evaluation Indicators for Web-based Agricultural Water Information System using Mandal-Art Method (만다라트(Mandal-Art) 기법을 이용한 웹기반 농업용수 정보시스템 평가지표 개발)

  • Kim, Solhee;Kim, Chanwoo;Jung, Chanhoon;Park, Jinseon;Kim, Jeongdae;Suh, Kyo
    • Journal of Korean Society of Rural Planning
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    • v.23 no.4
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    • pp.49-59
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    • 2017
  • The importance of information system evaluation has increased according to ICT development and this evaluation is required for objective verification. The aim of this study is to develop evaluation indicators for web-based information system and verify the availability of these evaluation indicators through applying to agricultural water integrated information system. This study finds and provides eight evaluation items and 64 indicators for a web-based information system using $3{\times}3$ Mandal-Art matrix that is a tool for creating creative ideas. These evaluation items are design, contents, navigation, stability, community, convenience, usefulness, and accuracy. Total 64 evaluation indicators were presented by deriving eight evaluation items for each using $9{\times}9$ Mandal-Art matrix. When evaluating information system using evaluation indicators, it can be identified the vulnerable items in the information system. Also, the comprehensive results of the information system could be understood when appearing a single score after weighting. In addition, it can also help to prepare a questionnaire for evaluation systematically.

Binary Power plant using unused thermal energy and Neural Network Controllers (미활용 열에너지를 이용한 바이너리 발전과 신경망 제어)

  • Han, Kun-Young;Park, Sung-Dae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.10
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    • pp.1302-1309
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    • 2021
  • Recently, the Korean Government announced the Korean New Deal as a national development strategy to overcome the economic recession from the pandemic crisis and lead the global action against structural changes. In the Korean New Deal, the Green New Deal related with the energy aims to achieve net-zero emissions and accelerates the transition towards a low-carbon and green economy. To this end, the government plans to promote an increased use of renewable energy in the society at large. This paper introduces a binary power generation using unused low-grade thermal energy to accelerate the transition towards a low-carbon and green economy and examines a control system based on Neural Network which is capable maintenance at low-cost by an unmanned automated operation in actual power generation environment. It is expected that the realization of binary power generation accelerates introduction of renewable energy along with solar and wind power.

A study on the enhancement and performance optimization of parallel data processing model for Big Data on Emissions of Air Pollutants Emitted from Vehicles (차량에서 배출되는 대기 오염 물질의 빅 데이터에 대한 병렬 데이터 처리 모델의 강화 및 성능 최적화에 관한 연구)

  • Kang, Seong-In;Cho, Sung-youn;Kim, Ji-Whan;Kim, Hyeon-Joung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.6
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    • pp.1-6
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    • 2020
  • Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.