• Title/Summary/Keyword: detection theory

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IR and SAR Sensor Fusion based Target Detection using BMVT-M (BMVT-M을 이용한 IR 및 SAR 융합기반 지상표적 탐지)

  • Lim, Yunji;Kim, Taehun;Kim, Sungho;Song, WooJin;Kim, Kyung-Tae;Kim, Sohyeon
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.11
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    • pp.1017-1026
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    • 2015
  • Infrared (IR) target detection is one of the key technologies in Automatic Target Detection/Recognition (ATD/R) for military applications. However, IR sensors have limitations due to the weather sensitivity and atmospheric effects. In recent years, sensor information fusion study is an active research topic to overcome these limitations. SAR sensor is adopted to sensor fusion, because SAR is robust to various weather conditions. In this paper, a Boolean Map Visual Theory-Morphology (BMVT-M) method is proposed to detect targets in SAR and IR images. Moreover, we suggest the IR and SAR image registration and decision level fusion algorithm. The experimental results using OKTAL-SE synthetic images validate the feasibility of sensor fusion-based target detection.

Detecting malicious behaviors in MMORPG by applying motivation theory (모티베이션 이론을 이용한 온라인 게임 내 부정행위 탐지)

  • Lee, Jae-hyuk;Kang, Sung Wook;Kim, Huy Kang
    • Journal of Korea Game Society
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    • v.15 no.4
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    • pp.69-78
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    • 2015
  • As the online game industry has been growing rapidly, more and more malicious activities to gain economic benefits have been reported as well. Game bot is one of the biggest problems in the online game industry. So we proposed a bot detection method based on the ERG theory of motivation for the first time. Most of the previous studies focused on behavior-based detection by monitoring patterns of the specific actions. In this paper, we applied the motivation theory to analyze user behaviors on a real game dataset. The result shows that normal users in the game followed the ERG theory of motivation in the same way as it works in real world. But in the case of game bots, the theory could not be applied because the game bot has specific reasons, unlike normal game users. We applied the ERG theory to users to distinguish game bot users from normal users. We detected the game bot with high accuracy of 99.78% by applying the theory.

A Quantitative Vigilance Measuring Model by Fuzzy Sets Theory in Unlimited Monitoring Task

  • Liu, Cheng-Li;Uang, Shiaw-Tsyr;Su, Kuo-Wei
    • Industrial Engineering and Management Systems
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    • v.4 no.2
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    • pp.176-183
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    • 2005
  • The theory of signal detection has been applied to a wide range of practical situation for a long time, including sonar detection, air traffic control and so on. In general, in this theory, sensitivity parametric index d' and bias parametric index $\beta$ are used to evaluated the performance of vigilance. These indices use observer's response "hit" and "false alarm" to explain and evaluate vigilance, but not considering reaction time. However, the reaction time of detecting should be considered in measuring vigilance in some supervisory tasks such as unlimited monitoring tasks (e.g., supervisors in nuclear plant). There are some researchers have used the segments of reaction time to generate a pair of probabilities of hit and false alarm probabilities and plot the receiver operating characteristic curve. The purpose of this study was to develop a quantitative vigilance-measuring model by fuzzy sets, which combined the concepts of hit, false alarm and reaction time. The model extends two-values logic to multi-values logic by membership functions of fuzzy sets. A simulated experiment of monitoring task in nuclear plant was carried out. Results indicated that the new vigilance-measuring model is more efficient than traditional indices; the characteristics of vigilance would be realized more clearly in unlimited monitoring task.

Big Data Analysis of Software Performance Trend using SPC with Flexible Moving Window and Fuzzy Theory (가변 윈도우 기법을 적용한 통계적 공정 제어와 퍼지추론 기법을 이용한 소프트웨어 성능 변화의 빅 데이터 분석)

  • Lee, Dong-Hun;Park, Jong-Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.11
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    • pp.997-1004
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    • 2012
  • In enterprise software projects, performance issues have become more critical during recent decades. While developing software products, many performance tests are executed in the earlier development phase against the newly added code pieces to detect possible performance regressions. In our previous research, we introduced the framework to enable automated performance anomaly detection and reduce the analysis overhead for identifying the root causes, and showed Statistical Process Control (SPC) can be successfully applied to anomaly detection. In this paper, we explain the special performance trend in which the existing anomaly detection system can hardly detect the noticeable performance change especially when a performance regression is introduced and recovered again a while later. Within the fixed number of sampling period, the fluctuation gets aggravated and the lower and upper control limit get relaxed so that sometimes the existing system hardly detect the noticeable performance change. To resolve the issue, we apply dynamically tuned sampling window size based on the performance trend, and Fuzzy theory to find an appropriate size of the moving window.

Accident Prevention Model Using Signal Detection Theory: Case of Shipbuilding Industry

  • Pyo, Yeon;Park, Myoung Hwan;Jeong, Byung Yong
    • Journal of the Ergonomics Society of Korea
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    • v.36 no.3
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    • pp.221-230
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    • 2017
  • Objective: The purpose of this study is to draw the accident prevention model using the signal detection theory, and to implement accident prevention program, based on a health promotion and support activities in a shipbuilding company. Background: Workers' health management is perceived important from the human resource management perspective, as well as from the personal perspective. Method: This study developed an accident prevention model by analyzing the correlation between 704 workers' health examination variables, and reviewed the verification of the model through a follow-up survey on the control variables and status of hazards targeting 650 workers for four years from 2007 to 2010. Also, a health promotion program was implemented targeting a production division to improve alcohol habits, smoking, musculoskeletal pain complaints and hearing control indices, which are the control variables of the model. Results: As a result of four years' implementation, the following effects were obtained: the days away from work fell 87.5%, and accident rate dropped 71.5% in 2010, respectively, compared to 2006, before the activity was implemented. Conclusion: This study shows that the accident prevention activities based on workers' health promotion activities are effective to prevent industrial accidents and injuries. Application: The research findings will serve as a practical guideline for establishing preventive measures in the shipbuilding company.

Food quality management using sensory discrimination method based on signal detection theory and its application to drinking water (식품 품질관리를 위한 신호탐지이론(SDT) 감각차이식별분석 이론과 생수 품질관리에의 활용)

  • Kim, Min-A;Sim, Hye-Min;Lee, Hye-Seong
    • Food Science and Industry
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    • v.52 no.1
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    • pp.20-31
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    • 2019
  • Sensory perception of food/beverage products is one of the most important quality factors to determine consumer acceptability and thus sensory discrimination methodology has been a vital tool for quality management. Signal detection theory(SDT) and Thurstonian modeling provide the most advanced psychometric approach to modeling various discrimination methods. In these theories, perceptual and cognitive decisional factors are considered so that, a fundamental measure of sensory difference (d') can be computed, independent of test methods used. In this paper, sensory discrimination analysis based on SDT and Thurstonian modeling is introduced for more accurate and systematic applications of sensory and hedonic quality management in industry. Ways to realize the statistical power and relative sensitivity of sensory discrimination methods theorized in SDT and Thurstonian modeling in practice, are also discussed by using a case study of the Nongshim quality management program for drinking water in which SDT A-Not A test methodology was further optimized.

Segmentation-based Signal Processing Algorithm for Vehicle Detection (차량검지를 위한 세그먼트에 기반을 둔 신호처리 알고리즘)

  • Ko, Ki-Won;Woo, Kwang-Joon
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.306-308
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    • 2005
  • The vehicle detection method using pulse radar has the advantage of maintenance in comparison with loop detection method. We have the information about the vehicle being and position by dividing the signals into sectors in accordance with SSC method, and by applying the discriminant function based on stochastical data. We also reduce the signal processing time.

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A Path Way to Increase the Intention to Comply with Information Security Policy of Employees (조직 구성원들의 정보보안 정책 준수행위 의도에 관한 연구)

  • Yim, Myung-Seong
    • Journal of Digital Convergence
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    • v.10 no.10
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    • pp.119-128
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    • 2012
  • This study is to identify the factors that influence an intention to information security policy compliance of employees. To do this, this study is based on three theoretical backgrounds because of the lack of holistic perspective. Research results show that detection certainty and individual attachment have a positive effect on information security policy compliance intention. Detection certainty is influenced by security awareness education and training. Finally, response cost has a negative effect on information security policy compliance intention.

Damage Detection of Truss Structures Using Parametric Projection Filter Theory (파라메트릭 사양필터를 이용한 트러스 구조물의 손상 검출)

  • Mun, Hyo-Jun;Suh, Ill-Gyo
    • 한국공간정보시스템학회:학술대회논문집
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    • 2004.05a
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    • pp.29-36
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    • 2004
  • In this paper, a study of damage detection for 2-Dimensional Truss Structures using the parametric projection filter theory is presented. Many researchers are interested in inverse problem and one of solution procedures for inverse problems that are very effective is the approach using the filtering algorithm in conjunction with numerical solution methods. In filtering algorithm, the Kalman filtering algorithm is well known and have been applied to many kind of inverse problems. In this paper, the Parametric projection filtering in conjunction with structural analysis is applied to the identification of damages in 2-D truss structures. The natural frequency and modes of damaged truss model are adopted as the measurement data. The effectiveness of proposed method is verified through the numerical examples.

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An Empirical Study on the Development of Behavior Model of Insurance Fraud (보험사기행동모형 개발에 관한 실증적 연구)

  • Lee, Myung-Jin;Gim, Gwang-Yong
    • Journal of Information Technology Services
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    • v.6 no.2
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    • pp.1-18
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    • 2007
  • Many researches have been done in insurance fraud as the amount and frequency of insurance fraud have been increasing continuously. In particular, the development of insurance fraud detection system using large database management techniques including data mining or link analysis based on visual method have been the main research topic in insurance fraud. However, this kinds of detection system were very ineffective to find unintentional insurance fraud happened by accident even though it was so good to find intentional and organized crime insurance fraud. Therefore, this research suggests insurance fraud as an ethical decision making and applies TPB(Theory of Planned Behavior) for the finding of reasons and prevention strategies of unintentional insurance fraud happened by accident. The results of research show that TPB is very appropriate model to explain the behavior of insurance fraud and that insurance agents force to do insurance fraud as affecting perceived behavior control. Therefore, education and pubic relations for insurance fraud are very effective for preventing insurance fraud and developing insurance service industry.