• Title/Summary/Keyword: User Uncertainty

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Shannon의 정보이론과 문헌정보 (Shannon's Information Theory and Document Indexing)

  • 정영미
    • 한국문헌정보학회지
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    • 제6권
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    • pp.87-103
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    • 1979
  • Information storage and retrieval is a part of general communication process. In the Shannon's information theory, information contained in a message is a measure of -uncertainty about information source and the amount of information is measured by entropy. Indexing is a process of reducing entropy of information source since document collection is divided into many smaller groups according to the subjects documents deal with. Significant concepts contained in every document are mapped into the set of all sets of index terms. Thus index itself is formed by paired sets of index terms and documents. Without indexing the entropy of document collection consisting of N documents is $log_2\;N$, whereas the average entropy of smaller groups $(W_1,\;W_2,...W_m)$ is as small $(as\;(\sum\limits^m_{i=1}\;H(W_i))/m$. Retrieval efficiency is a measure of information system's performance, which is largely affected by goodness of index. If all and only documents evaluated relevant to user's query can be retrieved, the information system is said $100\%$ efficient. Document file W may be potentially classified into two sets of relevant documents and non-relevant documents to a specific query. After retrieval, the document file W' is reclassified into four sets of relevant-retrieved, relevant-not retrieved, non-relevant-retrieved and non-relevant-not retrieved. It is shown in the paper that the difference in two entropies of document file Wand document file W' is a proper measure of retrieval efficiency.

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An Emission-Aware Day-Ahead Power Scheduling System for Internet of Energy

  • Huang, Chenn-Jung;Hu, Kai-Wen;Liu, An-Feng;Chen, Liang-Chun;Chen, Chih-Ting
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권10호
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    • pp.4988-5012
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    • 2019
  • As a subset of the Internet of Things, the Internet of Energy (IoE) is expected to tackle the problems faced by the current smart grid framework. Notably, the conventional day-ahead power scheduling of the smart grid should be redesigned in the IoE architecture to take into consideration the intermittence of scattered renewable generations, large amounts of power consumption data, and the uncertainty of the arrival time of electric vehicles (EVs). Accordingly, a day-ahead power scheduling system for the future IoE is proposed in this research to maximize the usage of distributed renewables and reduce carbon emission caused by the traditional power generation. Meanwhile, flexible charging mechanism of EVs is employed to provide preferred charging options for moving EVs and flatten the load profile simultaneously. The simulation results revealed that the proposed power scheduling mechanism not only achieves emission reduction and balances power load and supply effectively, but also fits each individual EV user's preference.

원자력발전소 위험도 평가를 위한 인간신뢰도분석 (Human Reliability Analysis for Risk Assessment of Nuclear Power Plants)

  • 정원대;김재환
    • 대한인간공학회지
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    • 제30권1호
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    • pp.55-64
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    • 2011
  • Objective: The aim of this paper is to introduce the activities and research trends of human reliability analysis including brief summary about contents and methods of the analysis. Background: Various approaches and methods have been suggested and used to assess human reliability in field of risk assessment of nuclear power plants. However, it has noticed that there is high uncertainty in human reliability analysis which results in a major bottleneck for risk-informed activities of nuclear power plants. Method: First and second generation methods of human reliability analysis are reviewed and a few representative methods are discussed from the risk assessment perspective. The strength and weakness of each method is also examined from the viewpoint of reliability analyst as a user. In addition, new research trends in this field are briefly summarized. Results: Human reliability analysis has become an important tool to support not only risk assessment but also system design of a centralized complex system. Conclusion: Human reliability analysis should be improved by active cooperation with researchers in field of human factors. Application: The trends of human reliability analysis explained in this paper will help researchers to find interest topics to which they could contribute.

ILOG를 활용한 금형 생산시스템의 일정계획 시스템 개발에 관한 연구 (A Study on Developing a Scheduling System for a Die Manufacturing System Using ILOG)

  • 정한일;정대영;김기동;박찬권;박진우
    • 산업공학
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    • 제13권4호
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    • pp.564-571
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    • 2000
  • Manufacturing companies are implementing a so-called customer-centered supply chain management to have a competitive advantage. In these efforts, collaboration not only within a company but also with suppliers, partners and customers is emphasized. The fast delivery, reducing the total lead-time from development to delivery, is pursued more than ever, though the quality and cost are still importantly regarded. Die manufacturing companies are not exception from these trends, because a die is a necessary tool for almost manufacturing industries. The planning and scheduling system plays an important role in supply chain management. In this study, we address a scheduling problem of a die manufacturing company. The problem is very complex due to many reasons including the uncertainty in environment and the complexity of constraints. Considering the importance of due-date satisfaction and human planners' roles, we designed the solution algorithm and the user interface respectively. In the implementation phase, modeling constructs and basic solution algorithms of ILOG solver and ILOG scheduler are used. In the paper, the problem and the algorithm are described with ILOG constructs, and the experience of use is also addressed.

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불확실성 매개변수 상관관계 분석 (Uncertainty parameter correlation analysis)

  • 심규범;연종상;김응석;정건희
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2015년도 학술발표회
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    • pp.19-19
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    • 2015
  • 최근 기후변화로 인해 집중호우 및 게릴라성 폭우의 발생빈도가 증가하고 있다. 또한, 도시화 및 산업화로 인해 불투수지역이 증가하여 첨두강우의 도달시간은 짧아지고, 강우강도는 증가하는 현상을 보이고 있다. 이로 인해 도시유역에서는 우수관의 통수능 부족으로 인한 홍수가 빈번히 발생하고 있다. 본 연구에서는 EPA-SWMM User's manual에서 제공하는 예제 관망도를 이용하여 SWMM 모형 매개변수들 간의 상관관계 분석을 수행하였다. 사전 조사 및 분석을 통해 유역폭, 관조도계수, 불투수유역 조도계수, 투수유역 조도계수, 불투수면적 비율 등 총 5개의 매개변수를 분석 대상으로 선정하였다. 매개변수들 간의 상관관계를 분석한 결과 유역폭-관조도계수, 유역폭불투수유역조도계수, 불투수면저 비율-투수유역 조도계수가 양의 기울기를 가지는 1차 선형함수 형태를 보였다. 즉, 예로 유역폭이 증가하면 관조도계수 또한 증가하는 경향을 보였다. 반대로 유역폭-불투수면적비율, 불투수유역 조도계수-관조도계수의 경우 음의 기울기를 가지는 상관관계를 보였으며 특히, 유역폭-불투수면적비율의 경우 2차 회귀곡선을 가지는 감소경향을 보였다. 본 연구의 결과를 활용하여 향후 우수관 설계를 수행한다면 내수침수 저감에 실무적인 도움을 줄 수 있을 것으로 판단된다.

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인공지능 머신러닝 기술을 이용한 주식 종목 매수/매도 추천시스템의 분석 및 설계 (Analysis and Design of Stock Item Buy/Sell Recommend System using AI Machine Learning Technology)

  • 조병호
    • 한국인터넷방송통신학회논문지
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    • 제21권4호
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    • pp.103-108
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    • 2021
  • 주식이 오를지 내릴지를 예측하는 것은 주식의 불확실성으로 매우 어렵다. 인공지능 기술을 이용한 주가예측 방법에 대한 연구가 오랫동안 이루어져왔다. 최근에는 증권 회사에도 로봇 어드바이저라는 이름으로 인공지능 기술을 이용한 주식 매수/매도 추천 프로그램이 사용되고 있다. 본 논문에서는 인공지능 머신러닝 기술을 이용한 매수/매도 추천 시스템을 개발하기 위하여 여러 가지 기술적 분석 방법의 결과를 활용하는 이 시스템의 핵심인 엔진을 설계한다. 또한 객체지향 분석 방법을 이용한 요구사항 분석 및 플로우차트, 화면 설계 등을 보여여줌으로써 효과적인 인공지능 머신러닝 기술을 이용한 매수/매도 추천 시스템의 소프트웨어 분석 및 설계 방법을 제시하고자 한다.

Identification of Contaminant Injection in Water Distribution Network

  • Marlim, Malvin Samuel;Kang, Doosun
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2020년도 학술발표회
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    • pp.114-114
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    • 2020
  • Water contamination in a water distribution network (WDN) is harmful since it directly induces the consumer's health problem and suspends water service in a wide area. Actions need to be taken rapidly to countermeasure a contamination event. A contaminant source ident ification (CSI) is an important initial step to mitigate the harmful event. Here, a CSI approach focused on determining the contaminant intrusion possible location and time (PLoT) is introduced. One of the methods to discover the PLoT is an inverse calculation to connect all the paths leading to the report specification of a sensor. A filtering procedure is then applied to narrow down the PLoT using the results from individual sensors. First, we spatially reduce the suspect intrusion points by locating the highly suspicious nodes that have similar intrusion time. Then, we narrow the possible intrusion time by matching the suspicious intrusion time to the reported information. Finally, a likelihood-score is estimated for each suspect. Another important aspect that needs to be considered in CSI is that there are inherent uncertainties, such as the variations in user demand and inaccuracy of sensor data. The uncertainties can lead to overlooking the real intrusion point and time. To reflect the uncertainties in the CSI process, the Monte-Carlo Simulation (MCS) is conducted to explore the ranges of PLoT. By analyzing all the accumulated scores through the random sets, a spread of contaminant intrusion PLoT can then be identified in the network.

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Consumer Loyalty toward Organic Food Retail Stores: Perceived Value and Value Co-creation Behavior

  • Myeongeun PARK;Soye YOU;Xianxia WU
    • 유통과학연구
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    • 제22권7호
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    • pp.107-117
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    • 2024
  • Purpose: Consumers have become more interested in eating organic food in recent decades because of the effect of merchants' advertising. Eating organic food is also shown to strengthen immunity, especially during the recent COVID-19 pandemic. However, consumers may find it more difficult to choose organic food retailers than to purchase conventional goods. This is because of the uncertainty characterizing the process of selecting organic food retailers, despite the growing rivalry across supermarket chains that sell organic goods. This study explores how consumers' perceived image (social responsibility and ability image) of organic food stores affects consumer loyalty. Research design, data and methodology: The data for the analysis were collected using Macromill Embrain, an online research service agency. The data were analyzed using SPSS 26 and Smart PLS 4.0. Results: Based on structural equation modeling, the findings of the study demonstrate that store image positively impactsstore loyalty, and that the mediator (perceived value) affects the relationship between the two variables. Conclusions: Organic food stores must understand consumers to improve store loyalty. Efforts such as providing a user community that enables joint behavior by sharing experiences among customers or launching campaigns to improve consumers' perceived brand identity can increase store loyalty.

포스트 코로나 시대의 원격진료 앱 사용 의도에 대한 연구: 테크노 스트레스의 영향을 중심으로 (The Impact of Technostress on Telemedicine App Usage Intentions in the Post-COVID19 Era)

  • 이동언;정세윤
    • 대한안전경영과학회지
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    • 제26권1호
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    • pp.1-8
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    • 2024
  • This study explores the impact of technostress on the intention to use telemedicine applications (apps) in the post-COVID19 era, a period marked by the rapid popularization of such apps to mitigate COVID19 infection risks. Utilizing the Technology Acceptance Model (TAM), the study identifies variables and proposes a research model. A questionnaire survey involving 364 adults is analyzed through Partial Least Squares-Structural Equation Modeling. Results indicate positive significance for variables linked to the TAM (perceived usefulness, perceived ease of use, attitude, and intention to use). Notably, techno-complexity negatively affects perceived ease of use, while techno-unreliability negatively impacts perceived usefulness and ease of use. Surprisingly, techno-uncertainty has a positive effect on both perceived usefulness and ease of use. Techno-overload, although negatively impacting perceived usefulness and ease of use, does not reach statistical significance. The study underscores the need to consider both positive and negative aspects, including technostress, when evaluating telemedicine app usage. Additionally, recognizing the varying impact of technostress based on users' ICT(Information and Communication Technology) confidence levels is crucial. Overall, these findings contribute academically to telemedicine app adoption literature and hold industrial significance by providing a user perspective on these apps.

신재생에너지 국가참조표준 시스템 구축 및 개발 - 모델 기반 표준기상년 (System Construction and Data Development of National Standard Reference for Renewable Energy - Model-Based Standard Meteorological Year)

  • 김보영;김창기;윤창열;김현구;강용혁
    • 신재생에너지
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    • 제20권1호
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    • pp.95-101
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    • 2024
  • Since 1990, the Renewable Big Data Research Lab at the Korea Institute of Energy Technology has been observing solar radiation at 16 sites across South Korea. Serving as the National Reference Standard Data Center for Renewable Energy since 2012, it produces essential data for the sector. By 2020, it standardized meteorological year data from 22 sites. Despite user demand for data from approximately 260 sites, equivalent to South Korea's municipalities, this need exceeds the capability of measurement-based data. In response, our team developed a method to derive solar radiation data from satellite images, covering South Korea in 400,000 grids of 500 m × 500 m each. Utilizing satellite-derived data and ERA5-Land reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), we produced standard meteorological year data for 1,000 sites. Our research also focused on data measurement traceability and uncertainty estimation, ensuring the reliability of our model data and the traceability of existing measurement-based data.