• Journal of the Korea Society for Simulation
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• v.20 no.1
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• pp.87-96
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• 2011

DEVS(Discrete Event Systems Specification) is a set theoretic formalism developed for specifying discrete event system. For execution of DEVS, we need an execution environment, which consists of simulation engine and models interpreted by the simulation engine. Common existing environments use hierarchical scheduling algorithm for DEVS execution. This hierarchical scheduling is a proper algorithm for DEVS execution because of hierarchical and modular characteristics. But this algorithm has overheads owing to message passing and time management. To overcome these overheads, we apply event-oriented simulation to DEVS execution and we remove hierarchical overheads. In eventoriented simulation, the scheduling of model execution is performed by events and event list. We propose three event-oriented execution environments for DEVS and experiment about the performance of our proposed environments in comparison with the existing execution environment using the hierarchical scheduling. The experimental results show our environments works better than existing environment using the hierarchical scheduling.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.31-34
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• 2010

2001년 9.11 사태 이후, 미국과 우방국들은 본격적으로 테러와의 전쟁을 시작하게 되었다. 국제화 시대의 흐름에 따라 국내의 외국인의 영향력이 커져가고 있고, 2011년 11월 11일 서울에서 개최되는 G20 세계정상회의를 앞둔 시점에서 테러에 대한 사전 대응이 중요해졌다. 이를 위해 민 관 군이 협력하여 다양한 정책과 활동을 벌이고 있는데, 데이터 마이닝의 기법 중 신경망 기법을 이용하여 효율적이고 기계적으로 잠재적 테러리스트를 식별하는 방법을 제안한다. 신경망 기법은 인간의 두뇌를 모델로 등장하였고, 입력 자료를 통해 학습한다는 것이 특징이다. 이 신경망을 여러 기관에서 발표한 테러리스트들의 정보를 입력 자료로 변환하여 학습시킨 뒤, 검증을 거쳐 실전에 적용하는 것이 본 논문에서 제안하는 신경망 기법 적용의 목표이다. 개인정보보호에 관한 법률 및 방법론이 보완된다면 실전에서 유용하게 사용될 수 있을 것이다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.85-94
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• 2017

In this paper, I proposed a sound model generation and a most frequent model search algorithm for recognizing animal vocalization. The sound model generation algorithm generates a optimal set of models through repeating processes such as the training process, the Viterbi Search process, and the most frequent model search process while adjusting HMM(Hidden Markov Model) structure to improve global recognition rate. The most frequent model search algorithm searches the list of models produced by Viterbi Search Algorithm for the most frequent model and makes it be the final decision of recognition process. It is implemented using MFCC(Mel Frequency Cepstral Coefficient) for the sound feature, HMM for the model, and C# programming language. To evaluate the algorithm, a set of animal sounds for 27 species were prepared and the experiment showed that the sound model generation algorithm generates 27 HMM models with 97.29 percent of recognition rate.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.108-115
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• 2011

This paper informs the standard guideline of electrical inspection for the University laboratories and R&D institutes. A routine electrical inspection is there to prevent an electric shock and electrical fire accident in the Lab. The main issue of this paper is to check the problem of a routine electrical inspection and this paper provides a detailed guideline of a checklist for the Lab which do not have detailed instruction. It mentions the standard model of an effective routine inspection to upgrade the weak electrical environment in the Lab. One of the main purposes of this paper is to develop a routine checklist to control the electrical environment in the Lab. The evaluation checklist we develop will then be applied to every Lab. Introducing an electrical safety checklist builds a clear standard guideline for a real safety check. This will be used as a regular routine check-up for every Lab. The goal of this paper is to enforce safety from electrical accidents in the lab and it will provide safety guidelines for every Lab.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.8
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• pp.641-653
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• 2013

Recent cyber attacks targeting control systems are getting sophisticated and intelligent notoriously. As the existing signature based detection techniques faced with their limitations, a whitelist model with security techniques is getting attention again. However, techniques that are being developed in a whitelist model used at the application level narrowly and cannot provide specific information about anomalism of various cases. In this paper, we classify abnormal cases that can occur in control systems of enterprises and propose a new whitelist model for detecting abnormal cases.

• Fashion & Textile Research Journal
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• v.24 no.2
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• pp.241-248
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• 2022

This study aims to provide basic data to suggest guidelines for re-education and work improvement of modelists based on the analysis of the current status of modelist work and education. A survey was conducted from January 4 to May 15, 2020, targeting 44 people working in pattern, pattern CAD, and grading in domestic apparel companies. Descriptive statistical analysis and frequency analysis using SPSS 25 were employed to analyze the status of work type, work difficulties, and re-education. For pattern production, the rate of using pattern CAD for business was high. It was found that companies mainly use YUKA CAD (63.8%), and branded companies use pattern CAD (100%). It was found that 3D CAD is mostly employed by vendors (88.9%), and CLO (90%) is mainly used. Regarding difficulties in pattern making, it was found that they experienced difficulties with stretchable materials owing to the amount of shrinkage and sagging of the fabric. The work problem was the lack of requisite working hours owing to the volume of work. Regarding future re-education, 63.6% of the total respondents indicated that they required a course related to pattern correction and material. Moreover, it was found that re-education was necessary to upgrade technology and acquire new knowledge, however, information on re-education was insufficient.

• Annual Conference on Human and Language Technology
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• 2003.10d
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• pp.69-72
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• 2003

본 논문에서는 입력된 한국어 문자열로부터 형태소를 분석하고, 품사를 태깅하는 방법에 있어 개선된 통계적 모델을 제안하고, 이에 기반한 띄어쓰기 비종속 형태소 분석 및 태깅 시스템의 개발과 성능 평가에 대한 결과를 소개하고 있다. 제안된 통계 기반품사 태깅 시스템은 입력된 문자열로부터 음절의 띄어쓰기 확률값을 계산하여 유사어절을 생성하고, 유사어절 단위로 사용자 띄어쓰기와 상관없이 형태소 후보 리스트를 생성하며, 인접한 후보 형태소들의 접속 확률 계산에 있어 어절 간 접속 확률과 어절 내 접속 확률을 모두 사용함으로, 최적의 형태소 리스트를 결정하는 모델을 사용하고 있다. 특히, 형태소들의 접속 확률 계산 시 어절 간 접속 확률과 어절 내 접속 확률의 결합 비율이 음절의 띄어쓰기 확률 값과 사용자의 띄어쓰기 여부에 따라 자동으로 조절되는 특징을 가지고 있으며, 이를 통해 극단적으로 띄어 쓰거나 붙여 쓴 문장에 대해서도 평균 90%수준의 품사 태깅 성능을 달성할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.485-488
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• 2001

본 논문에서는 웹상에서 학습자의 학습능력을 진단하기 위하여 SPICE 모델에서 제시하는 능력수준을 사용하여 각 단계별로 질문을 제시하고 해당 질문의 응답 여부에 따라 자신의 학습 능력을 평가받고 향후 자신의 능력을 좀더 향상시킬 수 있는 지침을 제공하는 학습능력 진단 시스템을 개발하였다. 본 시스템은 다양한 학습자의 학습능력을 진단할 수 있도록 학습자의 직업에 따라 별도의 질문 리스트를 준비하였으며 질문 리스트와 메세지 및 가산점을 조정한다면 다양한 분야에서도 활용될 수 있을 것이다.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.3 no.1
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• pp.73-103
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• 2008

Over the past few years, "business models" has surged into the management vocabulary. But, while it has become quite fashionable to discuss business models, there has been still much confusion about what are business models and how they could make. In fact, business models can serve a positive and powerful role in corporate management. While other authors have recently offered definitions of "business model", none of them appears to be generally accepted. This paper presents the absence of the generally definition of the business models, elements of business model and classify business logic. To help start-up entrepreneurs better understand, found and check business models thus, this paper propose a method of business model, understanding, founding and checking. The dissertation will present an effective business model building method which is necessary for the start-up entrepreneurs to start business. This paper consists of three parts. first is showing the previous study of business model. The second is the re-definition business model and elements based on the first and to present a new method of business model plating and checking for start-up IT (information technology) company's entrepreneurs. The last is application of the methode. This study applied the methode to a company which is located in "DAEDEOK INNOPOLIS"; this company has specialized Information technology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1513-1526
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• 2016

Since finance companies started e-banking services, those services have been diversified and use of them has continued to increase. Finance companies are implementing financial security policy for safe e-banking services, but e-Banking incidents are continuing to increase and becoming more intelligent. Along with the rise of internet banks and boosting Fintech industry, financial supervisory institutes are not only promoting user convenience through improving e-banking regulations such as enforcing Non-face-to-face real name verification policy and abrogating mandatory use of public key certificate or OTP(One time Password) for e-banking transactions, but also recommending the prevention of illegal money transfer incidents through upgrading FDS(Fraud Detection System). In this study, we assessed a blacklist based auto detection method suitable for overall situations for finance company, a real-time based suspicious transaction detection method linking with blacklist statistics model by each security level, and an alternative FDS model responding to typical transaction patterns of which information were collected from previous e-Banking incidents.