• 제목/요약/키워드: Visualization of Risk

검색결과 106건 처리시간 0.023초

빅데이터 처리 프로세스에 따른 빅데이터 위험요인 분석 (The Analyzing Risk Factor of Big Data : Big Data Processing Perspective)

  • 이지은;김창재;이남용
    • 한국IT서비스학회지
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    • 제13권2호
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    • pp.185-194
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    • 2014
  • Recently, as value for practical use of big data is evaluated, companies and organizations that create benefit and profit are gradually increasing with application of big data. But specifical and theoretical study about possible risk factors as introduction of big data is not being conducted. Accordingly, the study extracts the possible risk factors as introduction of big data based on literature reviews and classifies according to big data processing, data collection, data storage, data analysis, analysis data visualization and application. Also, the risk factors have order of priority according to the degree of risk from the survey of experts. This study will make a chance that can avoid risks by bid data processing and preparation for risks in order of dangerous grades of risk.

발전된 보안 시각화 효과성 결정 모델 (Decision Model of the Effectiveness for Advanced that Security Visualization)

  • 이민선;이경호
    • 정보보호학회논문지
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    • 제27권1호
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    • pp.147-162
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    • 2017
  • IT 환경의 변화 속에서 다양한 서비스와 기기의 출현으로 인하여, IT 규모의 증가와 더불어 데이터의 복잡도가 높아지면서 많은 조직에서 보안 상황 인지를 위한 대량의 데이터 분석 및 처리에 어려움을 겪고 있다. 이에, 조직의 위험관리에 있어서 보안 상황의 인지와 대응이 늦어지는 문제의 해결을 위해, 시각화를 통한 보안 상황 인지 효과의 향상을 제안한다. 이를 위해, 본 연구에서는 시각화와 관련한 다양한 관점에서의 선행 연구를 통해 사용자 유형, 상황 인지 단계, 정보 시각화의 속성 등을 고려하여 효과적 시각화를 위한 평가 요인과 대안을 선정하고 AHP 계층 모델을 수립하였다. 이를 토대로, 다 기준 의사결정 문제의 해결을 위한 AHP 기법을 활용하여 효과적 시각화를 위한 요인과 요인별 대안의 중요도를 산정함으로써, 시각화의 목적 및 사용자 유형에 따라 보안 상황의 인지 효과를 향상할 수 있는 시각화 방안을 제시하고자 한다.

스플라인 알고리즘을 이용한 비드 가시화 (Bead Visualization Using Spline Algorithm)

  • 구창대;양형석;김맹남
    • Journal of Welding and Joining
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    • 제34권1호
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    • pp.54-58
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    • 2016
  • In this research paper, suggest method of generate same bead as an actual measurement data in virtual welding conditions, exploit morphology information of the bead that acquired through robot welding. It has many multiple risk factors to Beginners welding training, by we make possible to train welding in virtual reality, we can reduce welding training risk and welding material to exploit bead visualization algorithm that we suggest so it will be expected to achieve educational, environmental and economical effect. The proposed method is acquire data to each case performing robot welding by set the voltage, current, working angle, process angle, speed and arc length of welding condition value. As Welding condition value is most important thing in decide bead form, we would selected one of baseline each item and then acquired metal followed another factors change. Welding type is FCAW, SMAW and TIG. When welding trainee perform the training, it's difficult to save all of changed information into database likewise working angle, process angle, speed and arc length. So not saving data into database are applying the method to infer the form of bead using a neural network algorithm. The way of bead's visualization is applying the spline algorithm. To accurately represent Morphological information of the bead, requires much of morphological information, so it can occur problem to save into database that is why we using the spline algorithm. By applying the spline algorithm, it can make simplified data and generate accurate bead shape. Through the research paper, the shape of bead generated by the virtual reality was able to improve the accuracy when compared using the form of bead generated by the robot welding to using the morphological information of the bead generated through the robot welding. By express the accurate shape of bead and so can reduce the difference of the actual welding training and virtual welding, it was confirmed that it can be performed safety and high effective virtual welding education.

기상정보와 Adaboost 모델을 이용한 깎기비탈면 위험도 지도 개발 연구 (Research on the Production of Risk Maps on Cut Slope Using Weather Information and Adaboost Model)

  • 우용훈;김승현;김진욱;박광해
    • 지질공학
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    • 제30권4호
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    • pp.663-671
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    • 2020
  • 최근 국내에서는 산림지역 뿐만 아니라 대도시지역에서도 자연재해가 많이 발생하고 있으며, 이에 대한 국가적인 요구사항은 증가하고 있다. 특히 국도 비탈면 붕괴에 대하여 체계적으로 관리할 수 있는 사전 재해정보 시스템은 전무한 실정이다. 본 연구에서는 CSMS(Cut Slope Management System)에서 관리하는 강원도와 경상도 지역의 국도 비탈면 붕괴 정밀조사 보고서와 비탈면 기초조사를 토대로 비탈면 붕괴 유발 인자에 대한 빅데이터 분석을 실시하였다. 분석 결과를 바탕으로 붕괴 비탈면 위치와 기상정보를 반영하여 분류 기반 머신러닝 모형인 Adaboost를 통한 비탈면 붕괴 위험도 예측모형을 구축하였다. 또한 시각화 프로그램인 비탈면 붕괴 위험도 시각화 지도를 개발하여 기상여건 변화에 따른 비탈면 위험도 파악을 통한 선제적 재해재난 예방대책에 활용할 수 있음을 보여주고 있다.

수상함 개발에서 기술성숙도, 난이도 및 중요도 기반의 위험도 평가 방안 (On a Risk Assessment Methodology based on the Technology Readiness Levels, Degrees of Difficulty, and Technology Need Values in the Development of Naval Surface Ships)

  • 김경환;이재천
    • 대한안전경영과학회지
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    • 제14권3호
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    • pp.151-158
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    • 2012
  • The objective of this paper is to propose a method of how to perform risk assessment in the early stage of defense research and development for the acquisition of weapon systems. An advanced method for risk assessment and its associated objective functions are developed first based on the concept of systems engineering. The developed method is then applied to carry out the analysis of alternatives in the trade-off environments. As a case study, the multi-purpose training ship is considered, where it is performed using the notions of technology readiness levels, degrees of difficulty, and technology need values to facilitate design space visualization and decision maker interaction. It is noted that decision makers can benefit from our approach as an improved risk assessment method in the context of multi-criteria decision making.

A Study on Intuitive Technique of Risk Assessment for Route of Ships Transporting Hazardous and Noxious Substance

  • Jeong, Min-Gi;Lee, Moon-Jin;Lee, Eun-Bang
    • 한국항해항만학회지
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    • 제42권2호
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    • pp.97-106
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    • 2018
  • Despite the development of safety measures and improvements in preventive systems technologies, maritime traffic accidents that involve ships carrying hazardous and noxious substances (HNS) continuously occur owing to increased amount of HNS goods transported and the growing number of HNS fleet. To prevent maritime traffic accidents involving ships carrying HNS, this study proposes an intuitive route risk assessment technique using risk contours that can be visually and quantitatively analyzed. The proposed technique offers continuous information based on quantified values. It determines and structures route risk factors classified as absolute danger, absolute factors, and influential factors within the assessment area. The route risk is assessed in accordance with the proposed algorithmic procedures by means of contour maps overlaid on electronic charts for visualization. To verify the effectiveness of the proposed route risk assessment technique, experimental case studies under various conditions were conducted to compare results obtained by the proposed technique to actual route plans used by five representative companies operating the model ship carrying HNS. This technique is beneficial not only for assessing the route risk of ships carrying HNS, but also for identifying better route options such as recommended routes and enhancing navigation safety. Furthermore, this technique can be used to develop optimized route plans for current maritime conditions in addition to future autonomous navigation application.

재해분석을 위한 텍스트마이닝과 SOM 기반 위험요인지도 개발 (On the Development of Risk Factor Map for Accident Analysis using Textmining and Self-Organizing Map(SOM) Algorithms)

  • 강성식;서용윤
    • 한국안전학회지
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    • 제33권6호
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    • pp.77-84
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    • 2018
  • Report documents of industrial and occupational accidents have continuously been accumulated in private and public institutes. Amongst others, information on narrative-texts of accidents such as accident processes and risk factors contained in disaster report documents is gaining the useful value for accident analysis. Despite this increasingly potential value of analysis of text information, scientific and algorithmic text analytics for safety management has not been carried out yet. Thus, this study aims to develop data processing and visualization techniques that provide a systematic and structural view of text information contained in a disaster report document so that safety managers can effectively analyze accident risk factors. To this end, the risk factor map using text mining and self-organizing map is developed. Text mining is firstly used to extract risk keywords from disaster report documents and then, the Self-Organizing Map (SOM) algorithm is conducted to visualize the risk factor map based on the similarity of disaster report documents. As a result, it is expected that fruitful text information buried in a myriad of disaster report documents is analyzed, providing risk factors to safety managers.

소셜네트워크분석 접근법을 활용한 글로벌 금융시장 네트워크 분석 (Investigating the Global Financial Markets from a Social Network Analysis Perspective)

  • 김대식;곽기영
    • 한국경영과학회지
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    • 제38권4호
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    • pp.11-33
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    • 2013
  • We analyzed the structures and properties of the global financial market networks using social network analysis approach. The Minimum Spanning Tree (MST) lengths and networks of the global financial markets based on the correlation coefficients have been analyzed. Firstly, similar to the previous studies on the global stock indices using MST length, the diversification effects in the global multi-asset portfolio can disappear during the crisis as the correlations among the asset class and within the asset class increase due to the system risks. Second, through the network visualization, we found the clustering of the asset class in the global financial markets network, which confirms the possible diversification effect in the global multi-asset portfolio. Meanwhile, we found the changes in the structure of the network during the crisis. For the last one, in terms of the degree centrality, the stock indices were the most influential to other assets in the global financial markets network, while in terms of the betweenness centrality, Gold, Silver and AUD. In the practical perspective, we propose the methods such as MST length and network visualization to monitor the change of the correlation risk for the risk management of the multi-asset portfolio.

[Retracted]Relationship between Corporate Governance and Risk Disclosure: A Systematic Literature Review Using R-Tools

  • Ag Kaifah Riyard, KIFLEE;Nornajihah Nadia, HASBULLAH;Suddin, LADA;Faerozh, MADLI
    • The Journal of Asian Finance, Economics and Business
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    • 제10권2호
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    • pp.355-365
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    • 2023
  • This study examined the relationship between corporate governance and risk disclosure via a systematic literature review and bibliometric visualization analysis. The study aimed to present evidence of risk disclosure intellectual structure, volume, and development knowledge trends. Data was extracted from Scopus and analyzed with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and RTools. In turn, 64 articles were extracted from the Scopus database. The results demonstrated that the number of corporate governance and risk disclosure publications increased significantly from 2015 to 2019 compared to before 2015. RTools revealed the most prominent journals, authors, and interests in the field. The co-occurrences map was constructed based on 208 keywords from 64 articles, where the keywords were required to appear once in the research. Interestingly, the keyword search yielded new concepts relatively unexplored in the risk disclosure field. The 13 clusters were generated, which contained 1987 total links and 1567 direct citations. Based on the scientific analysis discussion, corporate governance and risk disclosure is an interesting topic that has produced many publications. Applying research keywords arguably aided in producing and publishing papers in top journals. Despite the number of publications decreasing due to the COVID-19 pandemic, the pandemic also presented new opportunities for future research.

시계열 방사축과 원통좌표계를 이용한 네트워크 트래픽 공격 시각화 (Visualization of network traffic attack using time series radial axis and cylindrical coordinate system)

  • 장범환;최윤성
    • 한국융합학회논문지
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    • 제10권12호
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    • pp.17-22
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    • 2019
  • 네트워크 트래픽 세션 데이터를 이용한 공격 분석 및 시각화 방법들은 세션 데이터 내의 송신지 및 수신지 IP주소 및 연결관계를 시각화하여 네트워크 이상 현상들을 감시한다. 트래픽의 송수신 방향은 이상 현상을 탐지하는데 있어서 매우 중요한 특징이지만, 단순히 송신지와 수신지 IP주소를 좌·우 또는 상·하 대칭적으로 시각화하는 것은 분석을 난해하게 만드는 요소가 된다. 또한, 시계열적인 트래픽 세션들의 시간 특성을 고려하지 않고 시각화 인터페이스를 설계할 경우에는 시간별 보안 상황 정보가 손실되는 위험을 감수해야 한다. 본 논문에서는 방사축을 이용하여 시계열 트래픽 데이터를 시각화하고 IP주소를 네트워크 부분과 호스트 부분으로 분할 및 원통좌표계에 표출시켜 효과적으로 네트워크 공격을 감시할 수 있는 시각화 인터페이스와 분석 방법을 제안하고자 한다. 제안하는 방법은 네트워크 공격을 직관적으로 인지하고 공격 활동을 시간흐름에 따라 파악할 수 있는 장점을 가진다.