• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.1-10
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• 2019

Since big-data text mining extracts many features and data, clustering and classification can result in high computational complexity and low reliability of the analysis results. In particular, a term document matrix obtained through text mining represents term-document features, but produces a sparse matrix. We designed an advanced genetic algorithm (GA) to extract features in text mining for detection model. Term frequency inverse document frequency (TF-IDF) is used to reflect the document-term relationships in feature extraction. Through a repetitive process, a predetermined number of features are selected. And, we used the sparsity score to improve the performance of detection model. If a spam mail data set has the high sparsity, detection model have low performance and is difficult to search the optimization detection model. In addition, we find a low sparsity model that have also high TF-IDF score by using s(F) where the numerator in fitness function. We also verified its performance by applying the proposed algorithm to text classification. As a result, we have found that our algorithm shows higher performance (speed and accuracy) in attack mail classification.

• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.6
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• pp.67-74
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• 2010

Because of the difference between the actual and computed eccentricity of buildings, symmetrical buildings will be affected by torsion. In provisions, accidental eccentricity is intended to cover the effect of several factors, such as unfavorable distributions of dead- and live-load masses and the rotational component of ground motion about a vertical axis. The torsional amplification factor is introduced to reduce the vulnerability of torsionally imbalanced buildings. The effect of the torsional amplification factor is observed for a symmetric rectangular building with various aspect ratios, where the seismic-force-resisting elements are positioned at a variable distance from the geometrical center in each direction. For verifying the torsional amplification factor in provisions, nonlinear reinforced concrete models with various eccentricities and aspect ratios are used in rock. The difference between the maximum displacements of the flexible edge obtained between using nonlinear static and time-history analysis is very small but the difference between the maximum torsional angles is large.

• Electronics and Telecommunications Trends
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• v.13 no.6 s.54
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• pp.94-107
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• 1998

연구 개발의 주된 내용은 SDL(Specification Description Language)을 위한 정형기법 지원도구 중 명세상에서 행위 부분에 대한 동적 특성을 검정하는 검정기 개발이다. 모델 검정기는 해당 프로토콜에 대해 생성된 중간 모델 I/O FSM(Input/Output Finite State Machine)에 Modal-calculus에 의해 검정대상인 deadlock, livelock, reachability 및 liveness에 대한 표현과 I/O FSM에 대해 해당 알고리즘 적용 및 분석 기능을 C++언어로 구현하였다. 또한 SDL Editer 기능과 관련된 도구들과 통합하여 사용자들이 쉽고 편하게 쓸 수 있도록 환경 및 통합 모듈을 구현한다.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.04a
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• pp.84-90
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• 2000

인터넷을 발전에 따라 데이터의 전송량이 음성 전송량을 능가하고 있으나 현재의 네트워크로는 빠르고 신뢰성 있는 데이터의 전송을 보장할 수 없다. 데이터와 음성 모두의 빠르고 신뢰성 있는 전송과 관리를 위하여 개발된 패킷 중심 네트워크를 NGN이라 한다. NGN에서는 효율적인 전송과 관리를 위하여 기존(PSTN)의 교환기의 콜 에이전트를 소프트웨어로 구성하여 범용컴퓨터에서 운용될 수 있도록 하였다. 본 논문에서는 콜 에이전트를 소프트웨어로 설계하기 위하여 H/W 개발을 위하여 설계된 기본호처리모델인 BCSM을 객체지향방법론의 표준인 UML을 이용하여 설계를 하였다. 그리고 설계된 모델의 검증을 위하여 LSL(LarchShared Language)를 이용하여 정형명세를 하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.289-291
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• 2004

인터넷을 통한 통신의 안전성을 확보하기 위해서는 전송될 정보를 암호화해야 한다 따라서 통신의 주체간에는 공통적인 키의 공유와 상대방의 신원 확인을 위한 절차가 필요하다 정형검증기법은 이러한 네트워크상에서 통신의 안전성을 확보하기 위한 수단으로 사용되며, 본 논문에서는 무선환경기반 보안 프로토콜인 Carlsen BCY프로토콜을 모델 체커인 FDR을 사용하여 검증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.183-186
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• 2006

NPC(Non playable Character)모델은 온라인 게임뿐만 아니라 가상공간 시스템 구축 시 빠질 수 없는 중요한 요소이다. 현재 가장 널리 사용되는 인공지능 처리방식의 하나인 FSM(Finite State Machine)은 NPC의 행동양식을 표현하기 위해 유한한 개수의 상태를 이용하는 알고리즘이다. 인공지능이 적용된 NPC 모델 설계시 정확한 명세는 구현 단계에서 발생되는 자원의 손실을 막아주고 요구명세에 따른 검증을 가능하게 한다. 본 논문에서는 해저가상공간 구축 시 발생되는 어류 객체의 행동패턴을 분석하여 속성을 정의하였으며, 환경변화에 따른 행동 특성의 상호관계를 설정하여 정형화하였다. 정의된 속성을 가진 NPC 모델을 FSM 알고리즘을 적용해 설계하고 구현한다. 설계된 NPC모델은 CTL기반의 모델체커인 SMV(Symbolic Model Verification)를 통해 검증함으로써 설계에 대한 타상성을 입증하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.13-23
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• 2022

In this paper, we propose a detailed component image classification algorithm by fashion item for unstructured data retrieval in the fashion field. Due to the COVID-19 environment, AI-based online shopping malls are increasing recently. However, there is a limit to accurate unstructured data search with existing keyword search and personalized style recommendations based on user surfing behavior. In this study, pre-processing using Mask R-CNN was conducted using images crawled from online shopping sites and then classified components for each fashion item through CNN. We obtain the accuaracy for collar of the shirt's as 93.28%, the pattern of the shirt as 98.10%, the 3 classese fit of the jeans as 91.73%, And, we further obtained one for the 4 classes fit of jeans as 81.59% and the color of the jeans as 93.91%. At the results for the decorated items, we also obtained the accuract of the washing of the jeans as 91.20% and the demage of jeans accuaracy as 92.96%.

• Construction Engineering and Management
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• v.20 no.3
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• pp.61-66
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• 2019

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.103-116
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• 2003

States explosion due to composition of spaces of data, temporal, and locational values is one of the well-known critical problems which cause difficulty in understanding and analysing real-time systems specified with state-based formal methods. In order to overcome this problem, this paper presents an abstraction method for state minimization based on an abstraction in system specification and an abstraction in system execution. The first is named the syntactic in system specification and an abstraction in system execution. The first is named the syntactic abstraction, through which the patterns of the unconditionally internalized computation and the repetition and selection structures are abstracted. The latter is named the semantic abstraction, through which the patterns of the execution space represented with data. Through the abstractions, the components of a system in specification and execution model is hierarchically organized. The system can be analyzed briefly in the upper level in an skeleton manner with low complexity. The system, however, can be abstraction method for the state minimization and the decrease in analysis complexity through the abstraction with examples.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.33-39
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• 2019

As cyber attack methods are becoming more intelligent, incidents such as security breaches and international crimes are increasing. In order to predict and respond to these cyber attacks, the characteristics, methods, and types of attack techniques should be identified. To this end, many security companies are publishing security intelligence reports to quickly identify various attack patterns and prevent further damage. However, the reports that each company distributes are not structured, yet, the number of published intelligence reports are ever-increasing. In this paper, we propose a method to extract structured data from unstructured security intelligence reports. We also propose an automatic intelligence report analysis system that divides a large volume of reports into sub-groups based on their topics, making the report analysis process more effective and efficient.