• 한국간호교육학회지
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• 제21권4호
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• pp.477-489
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• 2015

Purpose: The purpose of this study was to develop an instrument to assess emergency room nurses' knowledge and performance of triage nursing. Methods: The instrument was developed through the stages of conceptual construction, item development, and validity and reliability testing. For the validity and reliability testing, data collected from 48 emergency room nurses using questionnaires was analyzed through descriptive statistics, factor analysis, and reliability coefficients. Results: The knowledge part consisted of 30 items in nine areas, and its reliability was low (KR-20 =0.50). The correct-answer rate was 71.8%. The performance section derived from the factor analysis was composed of two factors with nine items in the triage domain and three factors with 12 items in the non triage domain. The explanatory powers of these factors for the domains were 66.1% and 70.4%, respectively. The overall reliability (Cronbach's ${\alpha}$) was .95, and the reliabilities for the two domains were .88 and .91, respectively. The nurses' mean performance level was 3.2(${\pm}0.45$). Conclusion: The specific contents of the triage nursing work were identified from the developed scale; further research is necessary to in order to develop a scale capable of higher reliability and validity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.976-990
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• 2020

The k-means algorithm is widely used in academia and industry due to easy and simple implementation, enabling fast learning for complex datasets. However, k-means struggles to classify datasets without prior knowledge of specific domains. We proposed the repulsive k-means (RK-means) algorithm in a previous study to improve the k-means algorithm, using the repulsive force concept, which allows deleting unnecessary cluster centroids. Accordingly, the RK-means enables to classifying of a dataset without domain knowledge. However, three main problems remain. The RK-means algorithm includes a cluster repulsive force offset, for clusters confined in other clusters, which can cause cluster locking; we were unable to prove RK-means provided optimal convergence in the previous study; and RK-means shown better performance only normalize term and weight. Therefore, this paper proposes the advanced RK-means (ARK-means) algorithm to resolve the RK-means problems. We establish an initialization strategy for deploying cluster centroids and define a metric for the ARK-means algorithm. Finally, we redefine the mass and normalize terms to close to the general dataset. We show ARK-means feasibility experimentally using blob and iris datasets. Experiment results verify the proposed ARK-means algorithm provides better performance than k-means, k'-means, and RK-means.

• 지능정보연구
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• 제28권4호
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• pp.251-273
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• 2022

최근 텍스트 분석을 딥러닝에 적용한 연구가 꾸준히 이어지고 있으며, 특히 대용량의 데이터 셋을 학습한 사전학습 언어모델을 통해 단어의 의미를 파악하여 요약, 감정 분류 등의 태스크를 수행하려는 연구가 활발히 이루어지고 있다. 하지만 기존 사전학습 언어모델이 특정 도메인을 잘 이해하지 못한다는 한계를 나타냄에 따라, 최근 특정 도메인에 특화된 언어모델을 만들고자 하는 방향으로 연구의 흐름이 옮겨가고 있는 추세이다. 도메인 특화 추가 사전학습 언어모델은 특정 도메인의 지식을 모델이 더 잘 이해할 수 있게 하여, 해당 분야의 다양한 태스크에서 성능 향상을 가져왔다. 하지만 도메인 특화 추가 사전학습은 해당 도메인의 말뭉치 데이터를 확보하기 위해 많은 비용이 소요될 뿐 아니라, 고성능 컴퓨팅 자원과 개발 인력 등의 측면에서도 많은 비용과 시간이 투입되어야 한다는 부담이 있다. 아울러 일부 도메인에서 추가 사전학습 후의 성능 개선이 미미하다는 사례가 보고됨에 따라, 성능 개선 여부가 확실하지 않은 상태에서 도메인 특화 추가 사전학습 모델의 개발에 막대한 비용을 투입해야 하는지 여부에 대해 판단이 어려운 상황이다. 이러한 상황에도 불구하고 최근 각 도메인의 성능 개선 자체에 초점을 둔 추가 사전학습 연구는 다양한 분야에서 수행되고 있지만, 추가 사전학습을 통한 성능 개선에 영향을 미치는 도메인의 특성을 규명하기 위한 연구는 거의 이루어지지 않고 있다. 본 논문에서는 이러한 한계를 극복하기 위해, 실제로 추가 사전학습을 수행하기 전에 추가 사전학습을 통한 해당 도메인의 성능 개선 정도를 선제적으로 확인할 수 있는 방안을 제시한다. 구체적으로 3개의 도메인을 분석 대상 도메인으로 선정한 후, 각 도메인에서의 추가 사전학습을 통한 분류 정확도 상승 폭을 측정한다. 또한 각 도메인에서 사용된 주요 단어들의 정규화된 빈도를 기반으로 해당 도메인의 특수성을 측정하는 지표를 새롭게 개발하여 제시한다. 사전학습 언어모델과 3개 도메인의 도메인 특화 사전학습 언어모델을 사용한 분류 태스크 실험을 통해, 도메인 특수성 지표가 높을수록 추가 사전학습을 통한 성능 개선 폭이 높음을 확인하였다.

• 인지과학
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• 제10권1호
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• pp.67-78
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• 1999

네트워크의 기술 발달로 웹상의 정보 제공자가 증가함에 따라 정보 사용자가 필요한 정보를 신속하고 정확하게 획득하기는 것이 더욱 어려워졌다. 이를 위해서 키워드 정합 방식의 검색 엔진이 많이 개발 보급되고 있으나 여전히 많은 부담이 사용자에게 주어지고 있는 상황이다. 이러한 문제를 해결하기 위해서 본 논문에서는 특정 영역인 동문 분야에 대한 지식 베이스를 기반으로 사용자의 의도에 보다 적합하고 해당 영역에 적절한 형태로 사용자 질이를 가공하고, 대용량의 다양한 정보로부터 사용자가 필요로 하는 정보를 제공하는 일을 해주는 지능적인 정보검색 대리자, 정보 에이전트(HIIA-la : Hongik Information Agent)를 제안한다. HIIA-la는 온톨로지 형태에 접근한 동물 관련 지식 베이스를 가지고 있으며, 이를 기반으로 사용자 또는 다른 에이전트 시스템의 정보 요청에 대해 필요한 정보를 제공할 뿐만 아니라, 관련 웹 문서 정보도 제공된다. 효율적인 웹 문서의 제공을 위하여 방대한 양의 웹 문서를 대상으로 동물 영역에 관련된 문서를 저장·색인하는 웹DB를 가지고 있다. 또한 사용자의 의도를 좀더 명확하게 표현할 수 있도록 유연한 연사자로의 질의 확장을 하였으며, 축적된 처리 결과와 사용자의 피드백 정보를 통해 학습을 하게 된다. 본 논문에서는 이와 같이 요소들을 포함하는 HIIA-la를 구현하고, 실험을 통해 시스템의 효율성을 보인다.

• 대한한의학회지
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• 제44권1호
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• pp.38-55
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• 2023

Objectives: The purpose of this study was to provide direction for future research in the field of Korean medicine by analyzing microbiome based technologies emerging as a new diagnostic and treatment paradigm. Methods: To achieve the purpose of the study intellectual property data was used. After establishing citation network from registered microbiome-related US patents, citation network was analyzed by knowledge persistence-based main path approach to understanding technological trajectories. Furthermore, community detection algorithms were used to quantitatively identifying specific technological domain in a particular time period. Results: Results shows that early technologies in livestock industry contribute most to the recent patents. Knowledge in the patents flow through the path of food and beverage technological domain, and finally are inherited to the recent development of diagnosis, treatment and prevention technic. Conclusions: This study indicate that developing diagnostic tools which can link the composition of microbiome to specific diseases should be given high priority. Researches should lead to novel therapeutic strategies. Specifically, improving reliability of pattern identification and finding effective therapeutic compositions based on principles of Korean medicine is necessary.

• Educational Technology International
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• 제7권2호
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• pp.93-106
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• 2006

The knowledge-based society increasingly demands professionals possessing essential knowledge, and the ability to use this knowledge effectively in their work settings. In response to the requirement for these professionals, PBL is a promising educational method. This paper suggests an educational development program for faculty to implement problem-based learning(PBL). To implement PBL at the higher educational level, there is a need for a systemic approach. First, a well-designed educational plan for PBL is necessary. Before implementing PBL, both the instructor and the students should be prepared. Faculty members should be well informed on the characteristics of PBL, effective tutoring or facilitation skills, and how to design problems reflecting features of their own academic subject areas. Students also have to know the characteristics of PBL. Both of these groups need to be trained through workshops rather than through lectures. Second, a phase of design and implementation of PBL is necessary. PBL methods may seem to be intuitive and even unstructured because a problem is, in nature, unstructured and authentic. However, a closer look at PBL reveals that it is complex, carefully designed, and highly structured activity. Therefore, if it is poorly and incompletely designed, PBL can be a frustrating and exhausting experience for students and faculty members. Well-designed PBL can be an exhilarating and rewarding experience for both of them. Third, a phase of sharing PBL experiences is important: faculty members who have implemented PBL are required to share their experiences to help others enhance tutoring skills, and acquire practical information of students, contents, and what happened during PBL, and to develop PBL model in a specific domain. Based on the developed PBL model in a specific domain, PBL can be expanded and stabilized at the university level.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.147-156
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• 2022

Ontologies are knowledge containers in which information about a specified domain can be shared and reused. An event happens within a specific time and place and in which some actors engage and show specific action features. The fact is that several ontology models are based on events called Event-Based Models, where the event is an individual entity or concept connected with other entities to describe the underlying ontology because the event can be composed of spatiotemporal extents. However, current event-based ontologies are inadequate to bridge the gap between spatiotemporal extents and participants to describe a specific domain event. This paper reviews, describes and compares the existing event-based ontologies. The paper compares various ways of representing the events and how they have been modelled, constructed, and integrated with the ontologies. The primary criterion for comparison is based on the events' ability to represent spatial and temporal extent and the participants in the event.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 1999년도 춘계학술대회논문집
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• pp.213-217
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• 1999

An expert system is developed for rational and efficient design of multi-component injection molding which is a fairly new manufacturing technique to produce plastic parts by injecting two or more materials sequentially using multiple injection units in a single machine into a single rotary mold. The knowledge base used in the present design system is primarily composed of two parts ; knowledge from domain expert and knowledge from CAE analysis. The present expert system has hour main modules ; general design guidelines for injection molding specific guidelines for multi-component injection molding redesign guidelines from the result of the CAE analysis and finally troubleshooting for multi-component injection molding. To show the validity of the present design methodology two shop floor design problems were tested ; design and fabrication of timing belt cover and power window's assist knob by using multi-component injection molding.

• 산업공학
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• 제20권4호
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• pp.488-497
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• 2007

In order to provide appropriate decision supports in medical domain, it is required that clinical knowledge should be implemented in a computable form and integrated with hospital information systems. Healthcare organizations are increasingly adopting tools that provide decision support functions to improve patient outcomes and reduce medical errors. This paper proposes a process centric clinical decision support system based on medical knowledge. The proposed system consists of three major parts - CPG (Clinical Practice Guideline) repository, service pool, and decision support module. The decision support module interprets knowledge base generated by the CPG and service part and then generates a personalized and patient centered clinical process satisfying specific requirements of an individual patient during the entire treatment in hospitals. The proposed system helps health professionals to select appropriate clinical procedures according to the circumstances of each patient resulting in improving the quality of care and reducing medical errors.

• 대한전기학회논문지
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• 제39권1호
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• pp.16-21
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• 1990

A Knowledge based expert system is a computer program that emulates the reasoning process of a human expert in a specific problem domain. Expert system has the potential to solve a wide range of problems which require knowledge about the problem rather than a purely analytical approach. This papaer presents the application of knowledge based expert system to power system fault diagnosis. The contents of expert system develpped in this paper is judgement of fault section from a given alarm sets and production of all possible hypothesis for the single fault. Both relay failures and circuit breaker failures are considered simultaneously. Although many types of relay are used in actual system, experts recognize ones as several typical signals corresponding to the fault types. Therefore relays are classified into several types. The expert system is written in an artificial intelligence language "PROLOG" . Best-first search method is used for problem solving. Both forward chaining and backward chaining schemes are used in reasoning process. The application to a part of actual power system proves the availability of the developed expert system.