• Knowledge Management Research
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• v.11 no.2
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• pp.75-93
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• 2010

Even though there have been many efforts on driver's route recommendation, driver still should get involved to choose the driving path in a manual manner. Uncertain traffic information provided to the driver delays his arrival time and hence may cause diminished economic values. One of the solutions of reducing the uncertainty is to provide various kinds of traffic information, rather than send real-time information. Therefore, as the wireless communication technology improves and at the same time volume of utilizable traffic contents increases in geometrical progression, selecting traffic information based on driver's context in a timely and individual manner will be needed. Hence, the purpose of this paper is to propose a methodology that efficiently sends the rich traffic contents to the personal in-vehicle navigation. To do so, driver preference is modeled and then the recommendation algorithm of traffic information contents was developed using the preference model. Secondly, ontology based traffic situation analyzation method is suggested to automatically inference the noticeable information from the traffic context on driver's route. To show the feasibility of the idea proposed in this paper, an open API service is implemented in consideration of ease of use.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1159-1166
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• 2010

Today, detecting the location of moving object has been traced as various methods in our world. In this paper, we preset the system to improve the estimation accuracy utilizing detail localization using radar sensor based on WSN and situational awareness for a calibration (context aware) database, Rail concept. A variety of existing location tracking method has a problem with receiving of data and accuracy as tracking methodology, and since these located data are the only data to be collected for location tracing, the context aware or monitering as the surrounding environment is limited. So, in this paper, we enhanced the distance aware accuracy using radar sensor utilizing the Doppler effect among the distance measuring method, estimated the location using the Triangulation algorithm. Also, since we composed the environment data(temperature, illuminancem, humidity, noise) to entry of the database, it can be utilized in location-based service according to the later action information inference and positive context decision. In order to verify the validity of the suggested method, we give a few random situation and built test bed of designed node, and over the various test we proved the utilizing the context information through route tracking of moving and data processing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.253-255
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• 2015

In a variety of network environments, the provision of context-aware services, it is difficult to integrate and share because of the heterogeneity problem between distributed data. This paper proposes the integration model using the ontology as a method for solving the above. This uses an ontology to integrate the context-aware informations that are collected. The ontology is generated by the acquisition, semantic analysis and inference of the metadata of the context-aware information. This is the basis of the analysis and analysis of the additional system. Accordingly, this paper studies ways to create an ontology and apply them. The advantage of the proposed scheme can be used without modifying the existing tools, it is possible to easily perform the expansion and consolidation of the system.

• The Korean Journal of Community Living Science
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• v.18 no.2
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• pp.265-276
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• 2007

The purpose of this study was 1) to find out the consumer patronage mix of department and fashion outlet stores, 2) to compare the clothing and price attitudes among store patronage groups and 3) to compare the importance of the stores' attributes among the store patronage groups. The subjects were 381 female consumers in the Seoul and Gyeonggi areas. Questionnaires were used to collect the data. The data was analyzed by frequency, factor analysis, ANOVA, Duncan's Multiple Range Test and Cronbach's Alpha. The results were as follows. First, clothing purchasing attitudes of the total respondents were classified by three factors: fashion/confident oriented, appearance oriented, and brand-name oriented. Also, clothing price attitudes were composed of three factors: price/quality-prestige inference, discount/low price pursuit and benefit/value pursuit. In addition, the importance of the store's attributes was composed of five factors: convenience/service, concern of fashion outlet store, brand-name/fashionability, awareness of fashion outlet store, and practical advantage of the store. Second, the department store patronage group was significantly different from the fashion outlet store patronage group in clothing attitude, price attitude, and the importance of the store attribute. Third, the responses of the department store patronage group were significantly different from those of the fashion outlet store patronage group in product reliability and awareness of the fashion outlet store.

• Korean Journal of Adult Nursing
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• v.20 no.5
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• pp.707-718
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• 2008

Purpose: The present study was designed to understand the conceptual definition and attributes of the clinical critical thinking ability(CCTA) in nursing and to grasp the characteristics of clinical critical thinking abilities. Methods: The data were analyzed using the Hybrid model of Schwartz-Barcott and Kim(2000). Results: Having the skills and dispositions to think critically, CCTA refers to something that implies the cognizant ability to interpret contextual meanings, analyze the relationships between materials or circumstances, draw out the best conclusions, predict things using relevant information and evaluate the reliability of information and the strength of inference on the one hand and the emphatic disposition to be curious, open-minded, intellectually integral, systematic and creative and to reflect on things in contextual terms on the other. Conclusion: CCTA is characterized by clinical circumstances, such as guessing the reasons for facts, predicting things, connecting theory to practice and approaching individual situation in total terms as well as by the Korean circumstances, such as taking another person's perspective. Hence, this study proposes developing the tools to measure the clinical critical thinking ability and the strategies to improve the clinical critical thinking ability and seeking to verify their validity, on the basis of the findings.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.200-204
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• 2006

본 논문은 지식 기반 정보유통 플랫폼 OntoFrame-K$^{(R)}$ 상에서 추론을 이용하여 연구자 간 협업 서비스를 제공할 수 있도록 하는 DBMS 기반 추론 서비스 OntoThink-K$^{(R)}$에 대해 기술한다. 본 추론 서비스는 URI 서버를 이용하여 RDF 트리플을 생성하고 추론 규칙에 의해 해당 트리플을 확장하며 SPARQL을 통해 질의 결과를 생성해낸다. 특히 이 모든 과정은 DBMS 기반으로 설계 구현되었는데 URI 서버와 성과 비성과 등록 인터페이스를 통해 별도의 추론 엔진을 사용하지 않고도 정합성이 보장되는 지식을 생성 관리할 수 있도록 하며, 불안정한 성능을 보이는 추론 엔진을 이용하지 않기 때문에 안정적인 성능을 보장할 수 있다는 데 그 특징이 있다. OntoThink-K$^{(R)}$는 온톨로지 스키마 트리플, 인스턴스 트리플, 그리고 전방 추론을 통해 획득한 추가 트리플을 포함하는 확장 트리플을 기반 지식으로 하는데, 최종 사용되는 RDF 트리플의 크기는 지식 확장 이전 631,158개, 지식 확장 이후 1,112,100개이다.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.185-193
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• 2008

In spite of rapid development of IT-related meteorology and services, human users still ought to check the weather information manually as they did before because traditional weather information retrieval is based on pull-type and human interpretation. Furthermore, the automatic machine-driven weather information processing has been neglected for a long time although the intelligent weather information processing is expected to be very useful for personal daily life and ubiquitous computing. In this paper, we discussed a design of GRIB based ontology to enable smart weather information processing. GRIB is the general purposed and world-wildly used weather data format approved by the World Meteorological Organization. With the designed ontology and the inference system containing Jess engine, several intelligent weather applications have been implemented and tested to verify the virtue of machine-driven weather information processing.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.19-20
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• 2019

서버리스 프레임워크(Serverless Framework)는 마이크로서비스 아키텍처의 이론을 클라우드와 컨테이너를 기반으로 구현한 것으로 아마존의 AWS(Amazon Web Service)와 같은 퍼블릭 클라우드 플랫폼이 서비스됨에 따라 활용도 높아지고 있다. 하지만 현재까지의 플랫폼들은 GPU 와 같은 하드웨어의 의존성을 가진 인공지능 모델의 서비스에는 지원이 부족하다. 이에 본 논문에서는 컨테이너 기반의 오픈소스 서버리스 플랫폼을 대상으로 엔비디어-도커와 k8s-device-plugin 을 적용하여 GPU 활용이 가능한 서버리스 플랫폼을 구현하였다. 또한 인공지능 모델이 컨테이너에서 구동될 때 반복되는 가중치 로드를 줄이기 위한 구조를 제안한다. 본 논문에서 구현된 서버리스 플랫폼은 객체 검출 모델인 SSD(Single Shot Multibox Detector) 모델을 이용하여 성능 비교 실험을 진행하였으며, 그 결과 인공지능 모델이 적용된 서버리스 플랫폼의 함수 응답 시간이 개선되었음을 확인하였다.

• Mycobiology
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• v.49 no.1
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• pp.24-45
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• 2021

The occurrence of Austroboletus subflavidus and Fistulinella gloeocarpa is documented from the Dominican Republic. The latter species is reported for the first time outside its original locality in Martinique, extending the geographic range for this uncommon pinkish-spored bolete. A detailed morphological description is provided for each species and accompanied by color pictures of fresh basidiomes in habitat and line drawings of the main anatomical features. Both species represent independent lineages within their respective genera based on phylogenetic inference. In addition, A. subflavidus clusters in a sister lineage to the core Austroboletus clade (Austroboletus clade I) here named as Austroboletus clade II. In order to confirm the accuracy of species identification, their identity and relationships were subjected to multilocus phylogenetic analyses of three gene markers (ITS, nrLSU, RPB2) including genetic material already available in public databases. Austroboletus subflavidus is a widely distributed species in North and Central America, whereas F. gloeocarpa is apparently highly localized and seems to appear sparingly in the Dominican Republic, Martinque, and southern Florida. Comparisons with morphologically similar and molecularly inferred allied species are also presented and discussed.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.78-80
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• 2022

최근 딥러닝을 이용한 영상 분석은 자율주행, 감시카메라 등 다양한 서비스에 필수적으로 활용되고 있으며 실시간 처리 및 보안 요소를 만족하기 위해 기존의 클라우드 컴퓨팅 방식의 단점을 개선한 클라우드 엣지 컴퓨팅 방식을 적용하는 사례가 크게 증가하고 있다. 하지만 사용자 및 단말과 가까운 위치에서 딥러닝 추론을 진행하는 클라우드 엣지 서버는 클라우드 서버와 비교하여 컴퓨팅 자원이 충분하지 않을 경우가 많으며 기존의 딥러닝 모델을 그대로 클라우드 엣지 환경에 적용하는 것은 자원 활용 측면에서 여러가지 문제점들을 갖고 있다. 따라서 본 논문에서는 마이크로서비스 구조를 통해 자원을 보다 유연하게 활용할 수 있도록 개선된 딥러닝 모델로 대규모의 클라이언트 요청을 처리 가능한 동영상 데이터 추론 서비스인 G-Edge AI 추론 서비스 개발에 대해 설명한다.