• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.284-310
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• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.183-194
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• 2005

In this study, we introduce an advanced architecture of genetically optimized Hybrid Fuzzy Neural Networks (gHFNN) and develop a comprehensive design methodology supporting their construction. A series of numeric experiments is included to illustrate the performance of the networks. The construction of gHFNN exploits fundamental technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms (GAs). The architecture of the gHFNNs results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining Fuzzy Neural Networks (FNN) with Polynomial Neural Networks (PNN). In this tandem, a FNN supports the formation of the premise part of the rule-based structure of the gHFNN. The consequence part of the gHFNN is designed using PNNs. We distinguish between two types of the linear fuzzy inference rule-based FNN structures showing how this taxonomy depends upon the type of a fuzzy partition of input variables. As to the consequence part of the gHFNN, the development of the PNN dwells on two general optimization mechanisms: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gHFNN, the models are experimented with a representative numerical example. A comparative analysis demonstrates that the proposed gHFNN come with higher accuracy as well as superb predictive capabilities when comparing with other neurofuzzy models.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.2981-2988
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• 1999

A deductive database consists of facts being the extensional database and rules being the intensional database. Because of the difficulty of evaluating rules, many parallel evaluation algorithms for rules have been presented. But we have not gotten an acceptable result. This paper proposes a new methodology to evaluate proof-theoretic meaning of the linear recursion rule which contains transitive dependency by using a shared-nothing parallel architecture. As first, we prove that there exists the equivalent expression for a linear recursion rule, design the algorithm for evaluating the linear recursion rule based on the equivalent expression, and finally analyse performance of the proposed algorithm.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.1058-1067
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• 2015

Dweller's safety is one of the most important factors for the evaluation of building performance. The process of conventional safety design which is normally performed by the codes and designer's experiences is not enough to check the whole possibilities of unexpected accidents in the built environment. It means that the dwellers might be always exposed by the dangerous situation which should have been removed in the architectural design process. In order to solve this problem, this study intends to introduce a rule-based performance evaluation technology based on BIM(Building Information Modeling). The proposed technology focuses on the real time evaluation of dweller's safety in the ordinary life in the designed building alternatives and uses a commercial BIM tool as a design and evaluation platform.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.501-505
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• 2007

현재 기술 동향에 따라, 언제 어디서나 통신 및 컴퓨팅이 가능한 유비쿼터스 컴퓨팅 시스템(Ubiquitous Computing System)을 위해 사용자 및 주변 환경의 상황을 인식하는 기술(Context-Aware Computing System)이 필수적인 요소로 부각되고 있다. 하지만, Context-Aware Computing System을 구현하기 위해서 사용자 및 주변 환경으로부터 입력되는 불확실하거나 모호한 상황정보에 대한 표현과 추론에 대한 연구는 부족한 실정이다. 이를 해결하기 위해 Rule-based System을 기반으로 CRS와 DOS의 개념을 도입하여 상황인식 기술을 SoC로 구현할 수 있도록 새로운 Architecture를 제안한다. 마지막으로는 CRS와 DOS가 Network Topolgy에 적용된 RODMRP(Resilient Ontology-based Dynamic Multicast Routing Protocol)의 예를 통해 그 효용성을 입증하고, Ubiquitous Computing System에서 활용 가능한 방법 등을 제시한다.

• Journal of the Korea Society for Simulation
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• v.14 no.1
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• pp.9-18
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• 2005

Attempts to attack hosts in the network have become diverse, due to crackers developments of new creative attacking methods. Under these circumstances the role of intrusion detection system as a security system component gets considerably importance. Therefore, in this paper, we have suggested multiple intrusion detection system based on the contract net protocol which provides the communication among multiple agents. In this architecture, fuzzy rule based system has been applied for agent selection among agents competing for being activated. The simulation models are designed and implemented based on DEVS formalism which is theoretically well grounded means of expressing discrete event simulation models.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3069-3077
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• 1997

This paper is concerned with a new paradigm for parallel evaluation of linear recursion rules which contain transitive dependency in a shared-nothing parallel architecture. For parallel evaluation of rules, we consider a shared-nothing parallel architecture that consists of a set of nodes and a message passing network to these nodes. An evaluation of normalized rules is a computation of the proof theoretic meaning of a collection of rules. We shall here define normalized recursion rules which contain transitive dependency, present an equivalent expression for the rule, propose a paradigm for Parallel evaluation of normalized rule based on the equivalent expression using join, partition, and transitive closure operations, and analyze response-time complexity.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.249-257
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• 1992

An automated machining system involves concurrent use of manufacturing resources, alternative process plans, and flexible routings. High investment in the installation of automated facilities requires an efficient scheduling system that is able to allocate the resources specified for operations over a scheduling horizon. The primary emphasis of this paper is to generate schedules that accurately reflect details of the automated environment and the objectives stated for the system. In this paper, a scheduling algorithm for automated machining is presented. Using the previous simulation research for this topic, a rule-based scheduling system is constructed. An architecture for an intelligent scheduling system is proposed, and the system has a high potential to provide efficient schedules based on the task-specific knowledge for the dynamic scheduling environment

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.12
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• pp.2247-2250
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• 2007

This paper presents an automated API translator for embedded software development based on a model-driven approach. Since MDA(Model Driven Architecture) provides little support for the development of embedded software, we propose a new approach containing its advantages. First, we define #generic APIs# which do not depend on any RTOS#s but provide most of typical RTOS services. We can describe RTOS-related behaviors of target application using these generic APIs in a CIC(Common Intermediate Code). Then, we propose a transformation tool for translating between a CIC using generic APIs and a C-code for specific RTOS. The proposed API translator converts them using XML transformation rule which is defined outside. It indicates that an API translator extends to other RTOS#s by modifying or adding the transformation rule. From the experiment. we validate the proposed method.

• Journal of Information Technology and Architecture
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• v.10 no.1
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• pp.113-122
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• 2013

In this paper, we propose the method that automatically corrects the composition of a picture stylishly as well as reliably by cropping pictures based on the Rule of Thirds. The region of interest (ROI) is extracted from a picture by applying the Saliency Map and the Image Segmentation technology, the composition of the photo is amended based on this area to satisfy the Rule of Thirds. In addition, since the face region of the person is added to ROI by the Face Detection technique and the composition is amended by the various scenario according to ROI, the little more natural picture is acquired. The experimental result shows that the photo of the corrected composition was naturally amended compared with the original photo.