• Journal of the Korean Society for information Management
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• v.9 no.2
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• pp.43-79
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• 1992

This study proposes a Korean aut.omatic abstracting system in microbiology by applying Case Grammar, Concept Dependency Grammar, and Unification-Based Grammar(PATR- I[. DCG). The sample abstracts are analyzesd to clarify the ideal structure of abstract-a purpose sentence as first sentcnce, 2-3 method and result sentences as middle sentences, and a conclusion sentence as last sentences. To extract and refine the representative sentences constructing an automated abstract requires tht. rules giving the role features to nouns. And t.he rules rearranging the extracted sentences and the rules generating the abstract sentences arc also required. Evaluat.ing the effic~ency of this system. the method used in this automatic abstracting system needs thc more precise role features and the rules of sentence generation to reach the level of the author abstracts.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.51-51
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• 2003

국민건강보험재정건전화특별법 (제정 2002.1.19 법률 제 6620호)은 건강보험의 재정적자를 조기에 해소하고 재정수지의 균형을 이루도록 함으로써 건강보험제도의 발전과 국민건강 증진 도모를 그 목적으로 하며, 제14조(특수의료장비의 설치ㆍ운영)에서 의료기관은 보건복지부장관이 고시한 특수의료장비를 설치ㆍ운영하고자 하는 때에는 보건복지부령이 정하는 바에 따라 이를 등록하여야 하며 설치 인정 기준에 적합하게 설치ㆍ운영하여야 하고 정기적인 품질관리를 받아야한다고 명시하였다. 특수 의료장비의 설치 및 운영에 관한 규칙 (제정 2003.1.14 보건복지부령 제235호)은 국민건강보험재정건전화특별법이 제정됨에 따라 특수의료장비의 적정 한 설치와 활용을 위하여 의료기관에서 설치ㆍ운영하는 특수의료장비의 등록절차 설치인정기준 및 품질관리 절차 등을 정하고 특수의료장비에 대한 관리체계를 확립하려는 것이다. 특수의료장비의 설치 및 운영에 관한 규칙의 주요 골자는 가. 의료기관에서 특수장비를 설치ㆍ운영하고자 하는 경우 보건복지부장관 또는 시ㆍ도 지사에게 등록하도록 하였는바, 이 등록에 대한 절차와 특수의료장비의 설치인정기준을 정함, 나. 특수의료 장비에 대한 정기적인 품질관리검사를 서류검사와 정밀감사로 구분하여 서류검사는 1 년마다, 정밀검사는 3 년마다 받도록 함, 다. 품질관리검사기관의 장은 특수의료장비품질관리검사성적서를 신청인에게 교부하고, 보건복지부 또는 시ㆍ도지사 및 건강보험심사평가위원장에게 검사결과를 통보하도록 함, 라. 특수의료정비를 설치ㆍ운영하는 의료기관의 개설자 또는 관리자 및 품질관리검사기관의 장이 작성ㆍ비치ㆍ보존하여야할 서류를 정함이다. 보건복지부장관에게 등록하여야할 특수의료장비는 자기공명영상촬영장치와 전산화단층촬영 장치이며, 시ㆍ도지사에게 등록하여야할 특수의료장비는 유방촬영용장치이다. 본 발표에서는 특수의료장비의 설치 및 운영에 관한 규칙에 대한 개요와 연세의료원 세브란스병원에서 시행하고 있는 특수의료장비의 정도관리 검사, 팬텀영상검사, 그리고 임상영상검사를 소개하고자한다.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.7
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• pp.1234-1243
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• 1992

A systematic procedure to design fuzzy PID controllers is developed in this paper. The concept of local fuzzy control cell is proposed by introducing both an adequate global control rule and membership functions to simplify a fuzzy logic controller. Fuzzy decision is made by using algebraic product and parallel firing arithematic mean, and a defuzzification strategy is adopted for improving the computational efficiency based on nonfuzzy micro-processor. A direct method, transforming the typical output of quasi-linear fuzzy operator to the digital compensator of PID form, is also proposed. Finally, the proposed algorithm is applied to an DC-servo motor. It is found that this algorithm is systematic and robust through computer simulations and implementation of controller using Intel 8097 micro-processor.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.9-20
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• 2007

Groups of genes control the functioning of a cell by complex interactions. Such interactions of gene groups are tailed Gene Regulatory Networks(GRNs). Two previous data mining approaches, clustering and classification, have been used to analyze gene expression data. Though these mining tools are useful for determining membership of genes by homology, they don't identify the regulatory relationships among genes found in the same class of molecular actions. Furthermore, we need to understand the mechanism of how genes relate and how they regulate one another. In order to detect regulatory relationships among genes from time-series Microarray data, we propose a novel approach using frequent pattern mining and chain rules. In this approach, we propose a method for transforming gene expression data to make suitable for frequent pattern mining, and gene expression patterns we detected by applying the FP-growth algorithm. Next, we construct a gene regulatory network from frequent gene patterns using chain rules. Finally, we validate our proposed method through our experimental results, which are consistent with published results.

• Journal of KIISE
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• v.41 no.9
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• pp.686-698
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• 2014

Recently, large-scale streaming sensor data have emerged due to explosive supply of smart phones, diffusion of IoT and Cloud computing technology, and generalization of IoT devices. Also, researches on combination of semantic web technology are being actively pushed forward by increasing of requirements for creating new value of data through data sharing and mash-up in large-scale environments. However, we are faced with big issues due to large-scale and streaming data in the inference field for creating a new knowledge. For this reason, we propose the RDFS rule based parallel reasoning scheme to service by processing large-scale streaming sensor data with the semantic web technology. In the proposed scheme, we run in parallel each job of Rete network algorithm, the existing rule inference algorithm and sharing data using the HBase, a hadoop database, as a public storage. To achieve this, we implement our system and evaluate performance through the AWS data of the weather center as large-scale streaming sensor data.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.161-165
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• 2014

In this paper, we proposed the fuzzy prototype pattern classifier. In the proposed classifier, each prototype is defined to describe the related sub-space and the weight value is assigned to the prototype. The weight value assigned to the prototype leads to the change of the boundary surface. In order to define the prototypes, we use Fuzzy C-Means Clustering which is the one of fuzzy clustering methods. In order to optimize the weight values assigned to the prototypes, we use the Differential Evolutionary Algorithm. We use Linear Discriminant Analysis to estimate the coefficients of the polynomial which is the structure of the consequent part of a fuzzy rule. Finally, in order to evaluate the classification ability of the proposed pattern classifier, the machine learning data sets are used.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.21-30
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• 2002

The active database system introduces the active rules detecting specified state. As the condition evaluation of the active rules is performed every time an event occurs, the performance of the system has a great influence, depending on the conditions processing method. In this paper, we propose the conditions processing system with the preprocessor which determines the delta tree structure, constructs the classification tree, and generates the aggregate function table. Due to the characteristics of the active database through which the active rules can be comprehended beforehand, the preprocessor can be introduced. In this paper, the delta tree which can effectively process the join, selection operations, and the aggregate function is suggested, and it can enhance the condition evaluation performance. And we propose the classification tree which effectively processes the join operation and the aggregate function table processing the aggregate function which demands high cost. In this paper, the conditions processing system can be expected to enhance the performance of conditions processing in the active rules as the number of conditions comparison decreases because of the structure which is made in the preprocessor.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.194-198
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• 1999

Order Review/Release(ORR) 시스템은 생산계획 시스템과 작업현장간의 연결고리로서, 작업현장으로의 작업투입을 조절하여 작업현장에서의 체류시간과 공정중재고, 리드타임의 변동을 줄여주는 역할을 한다. 그러나, 지금까지의 ORR에 관한 연구들은 ORR의 유효성에 관하여 명확한 결론을 내지 못하고 있다. 일부는 ORR이 작업의 전체 리드타임을 증가시키는 악영향이 있음을 주장하고, 일부는 ORR을 도입함으로써 작업현장에서의 리드타임과 공정중재고가 줄어들고, 안정화될 수 있다고 주장한다. 본 연구는 어떠한 환경에서 Order Release 정책을 도입하는 것이 시스템의 성능향상에 기여할 수 있는 지 확인하는 것을 목적으로 하고, 가상의 Job Shop을 대상으로 시뮬레이션을 수행하였다. 작업장가동률 수준과 생산계획 단계에서의 계획오더 이송간격을 환경분수로 설정하고, 작업현장의 부하를 고려하여 작업투입을 통제하는 다섯 가지 Order Release 정책과 세 가지 우선순위 규칙을 적용하여 실험하였으며, 리드타임, 납기, 공정중재고 등과 관련된 8가지 척도에 대해 각 정책을 평가하였다. 그리고, 계획시스템의 부하평준화 기능이 존재할 때, Order Release 정책의 도입으로 인한 효과가 더 크다는 기존의 연구결과를 검증하기 위해, 부하평준화를 적용하였을 때 Order Release를 통제하지 않는 정책과 통제하는 정책간의 성능향상 차이가 있는지를 확인하는 실험을 수행하였다. 실험결과, ORR 보다는 우선순위규칙이 시스템의 성능을 결정하는 주요 통제정책으로 밝혀졌다. 그러나, 생산계획시스템에서 1주 간격으로 계획오더를 이송할 때는 Order Release 방법을 적용하여 작업현장에서의 평균 리드타임과 리드타임의 변동, 공정중재고가 줄어드는 결과를 보였고, 가동률 수준이 높을수록 ORR 방법간의 차이가 크게 나타났다. 그리고 부하평준화 기능은 Order Release 정책의 유효성에 별 영향을 주지 않는 것으로 나타났다. 결론적으로, Order Release 방법은 우선순위규칙간의 성능차이를 줄이거나, 대체할 수 통제 기법이라기보다는 우선순위규칙을 보완하여 공정중재고와 작업현장에서의 리드타임, 리드타임의 편차를 줄여주는 역할을 한다고 볼 수 있다. 그리고, 계획시스템이 존재하여 계획오더가 일정기간간격으로 이송되는 환경에서 특히 유용하다는 결론을 얻었다.

• Journal of KIISE
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• v.43 no.1
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• pp.80-86
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• 2016

A speech-act is a behavior intended by users in an utterance. Speech-act classification is important in a dialogue system. The machine learning and rule-based methods have mainly been used for speech-act classification. In this paper, we propose a speech-act classification method based on the combination of support vector machine (SVM) and transformation-based learning (TBL). The user's utterance is first classified by SVM that is preferentially applied to categories with a low utterance rate in training data. Next, when an utterance has negative scores throughout the whole of the categories, the utterance is applied to the correction phase by rules. The results from our method were higher performance over the baseline system long with error-reduction.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.691-700
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• 2009

An event means a flow which has a time attribute such as the a symptom of patients, an interval event has the time period between the start-time-point and the end-time-point. Although there are many studies for temporal data mining, they do not deal with discovering knowledge from interval event such as patient histories and purchase histories. In this paper, we suggest a method of temporal data mining that finds association rules of event causal relationships and predicts an occurrence of effect event based on discovered rules. Our method can predict the occurrence of an event by summarizing an interval event using the time attribute of an event and finding the causal relationship of event. As a result of simulation, this method can discover better knowledge than others by considering a lot of supports of an event and finding the significant rare relation on interval events which means an essential cause of an event, regardless of an occurrence support of an event in comparison with conventional data mining techniques.