• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2003년도 춘계학술대회
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• pp.271-285
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• 2003

In the conduct of this study, a web-enabled healthcare system for the management of hypertension was implemented through a hyperlink-based inference approach. The hyperlink-based inference platform implemented using the hypertext capacity of HTML which ensured accessibility, multimedia facilities, fast response, stability, ease of use and upgrade, and platform independency of expert systems. Many HTML documents, which are hyperlinked to each other based on expert rules, were uploaded beforehand to perform the hyperlink-based inference. The HTML documents were uploaded and maintained automatically by our proprietary tool called the Web-Based inference System (WeBIS) that supports a graphical user interface (GUI) for the input and edit of decision graphs. Nevertheless, the editing task of the decision graph using the GUI tool is a time consuming and tedious chore when the knowledge engineer must perform it manually. Accordingly, this research implemented an automatic generator of the decision graph for the management of hypertension. As a result, this research suggests a methodology for the development of Web-enabled healthcare systems using the hyperlink-based inference approach and, as an example, implements a Web-enabled healthcare system for hypertension, a platform which peformed especially well in the areas of speed and stability.

• 대한전기학회논문지:전력기술부문A
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• 제48권6호
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• pp.789-799
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• 1999

In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

• 한국IT서비스학회지
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• 제9권3호
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• pp.123-144
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• 2010

As knowledge becomes a critical success factor of companies nowadays, lots of rule-based systems have been and are being developed to support their activities. Large number of rule-based systems serve as Web sites to advise, or recommend their customers. They usually use a backward chaining inference algorithm based on backtrack to implement those interactive Web-enabled rule-based systems. However, when the users like customers are using these systems interactively, it happens frequently where the users do not know some of the answers for the questions from the rule-based systems. We are going to design a backward chaining inference methodology considering unknown facts based on backtrack technique. Firstly, we review exact and inexact reasoning. After that, we develop a backward chaining inference algorithm for exact reasoning based on backtrack, and then, extend the algorithm so that it can consider unknown facts and reduce its search space. The algorithm speeded-up inference and decreased interaction time with users by eliminating unnecessary questions and answers. We expect that the Web-enabled rule-based systems implemented by our methodology would improve users' satisfaction and make companies' competitiveness.

• 정보보호학회논문지
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• 제33권6호
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• pp.1111-1123
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• 2023

최근 생성 모델이 발전함에 따라 생성 모델을 위협하는 연구도 활발히 진행되고 있다. 본 논문은 Text-to-Image 모델에 대한 멤버십 추론 공격을 위한 새로운 제안 방법을 소개한다. 기존의 Text-to-Image 모델에 대한 멤버십 추론 공격은 쿼리 이미지의 caption으로 단일 이미지를 생성하여 멤버십을 추론하였다. 반면, 본 논문은 Textual Inversion을 통해 쿼리 이미지에 personalization된 임베딩을 사용하고, Adversarial Prompt 생성 방법으로 여러 장의 이미지를 효과적으로 생성하는 멤버십 추론 공격을 제안한다. 또한, Text-to-Image 모델 중 주목받고 있는 Stable Diffusion 모델에 대한 멤버십 추론 공격을 최초로 진행하였으며, 최대 1.00의 Accuracy를 달성한다.

• 한국시뮬레이션학회논문지
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• 제25권3호
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• pp.117-123
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• 2016

본 연구는 다중서버 대기행렬시스템의 관측이 제한되어 있는 경우에 시스템 내부 행태를 추론하는 데에 그 목적이 있다. 대기행렬시스템 분석에 있어 도착 및 서비스시간에 자기상관성이 존재하면 이론적으로 모형화하기가 매우 복잡하고 어렵다. 이에 따라 다양한 분석 기법 및 확률과정 모형들이 개발되었다. 본 논문에서는 외부 관측치에 존재하는 자기상관성과 내부 행태를 관측하기 어려운 경우에 대한 추론 방법을 소개한다. 선행연구의 가정을 완화하여 추론 방법을 제시하고 그에 대한 보조정리 및 정리를 제시한다. 제시된 비모수적 방법을 적용하면 서비스시간에 자기상관성이 존재하더라도 외부 관측치만을 사용하여 다중서버 대기행렬의 내부 행태를 추론할 수 있다. 주요 내부 추론 결과로는 대기시간과 서비스시간을 사용하였다. 또한 제시된 방법의 타당성 검증을 위해 실험 결과를 제시하였다.

• International Journal of Reliability and Applications
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• 제9권2호
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• pp.167-182
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• 2008

The objective of this paper is to discuss the stochastic analysis and the statistical inference of a three-states semi-Markov reliability model. Using the maximum likelihood procedure, the parameters included in this model are estimated. Based on the assumption that the lifetime and repair time of the system are gener-alized Weibull random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is derived. Many important special cases are discussed. Finally, the obtained results are compared with those available in the literature.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.674-679
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• 1987

Process failures can occur at any time during operation, so a continuous effort of fault detection, diagsis, and correction is required. Expert system paridigm has been regarded as a promising approach to real time process supervisory control especially to fault diagnosis. The most important aspects of fault diagnostic expert systems(FDES) are the problem-solving inference strategy and knowledge organizations. The necessity of FDES, the nature of diagnostic knowledge, the representation of knowledge, and the inference mechanism of FDES, et al. are described, which are announced by previous researchers. And the existing FDES are categorized and critically reviewed in this work.

• 한국융합학회논문지
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• 제9권10호
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• pp.75-80
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• 2018

본 논문에서는 헬스 빅데이터 플랫폼에서 이기종 라이프로그 마이닝 모델을 제안한다. 이는 사용자의 라이프 로그를 실시간으로 수집하고 헬스케어 서비스를 제공하기 위한 온톨로지 기반의 마이닝 모델이다. 제안하는 방법은 이기종 라이프 로그 데이터를 분산처리하고, 클라우드 컴퓨팅 환경에서 실시간으로 처리한다. 이를 이기종 온톨로지를 기반으로 구성한 환경에 적합하도록 상위 온톨로지 방식으로 지식베이스를 재구성한다. 재구성한 지식베이스는 Jena 4.0 추론엔진을 이용해 추론 규칙들을 생성하고, 규칙 기반 추론 방법으로 실시간 헬스 서비스를 제공한다. 라이프로그 마이닝을 숨겨진 관계에 대한 분석과 시계열적 생체신호에 대한 예측모델을 구성한다. 이는 관계나 추론규칙에서 포함되지 않은 음의 상관관계나 양의 상관관계를 탐색하여 사용자의 생체신호에 대한 변화를 감지하고 예방 의료 서비스를 현실화하는 실시간 헬스케어 서비스가 가능하다. 성능 평가는 제안한 이기종 라이프로그 마이닝 모델 방법이 정확도에서 0.734, 재현율에서 0.752로 다른 모델에 비해 우수하게 나타난다.

• 전기학회논문지
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• 제57권3호
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• pp.473-479
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• 2008

Generally, HDDs are widely used as data storage device in office, home and mobile machineries. So, it is used for various applications or tasks, such as file copy, file download, music and movie play etc., in various environment. In spite of this kind of varieties in tasks and environment in which HDDs perform, most commercial HDDs hardly control its operations adaptively to these varieties. Thus, it is preferred to optimize the performance and energy consumption of HDDs according to the task and/or the environment. So, this paper proposes a new fuzzy inference algorithm which adaptively controls HDDs operations and may also easily be implemented as the firmware of HDDs and run in the restricted environment such as embedded systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.15-15
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• 2000

In the past couple of years, there has been increasing interest in the fusion of neural networks and fuzzy logic. Most of the existing fused models have been proposed to implement different types of fuzzy reasoning mechanisms and inevitably they suffer from the dimensionality problem when dealing with complex real-world problem. To overcome the problem, we propose the self-organizing networks with activation nodes based on fuzzy inference and polynomial function. The proposed model consists of two parts, one is fuzzy nodes which each node is operated as a small fuzzy system with fuzzy implication rules, and its fuzzy system operates with Gaussian or triangular MF in Premise part and constant or regression polynomials in consequence part. the other is polynomial nodes which several types of high-order polynomials such as linear, quadratic, and cubic form are used and are connected as various kinds of multi-variable inputs. To demonstrate the effectiveness of the proposed method, time series data for gas furnace process has been applied.