• Title/Summary/Keyword: Intelligent level

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On Top-Down Design of MPEG-2 Audio Encoder

  • Park, Sung-Wook
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.1
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    • pp.75-81
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    • 2008
  • This paper presents a top-down approach to implement an MPEG-2 audio encoder in VLSI. As the algorithm of an MPEG-2 audio encoder is heavy-weighted and heterogeneous(to be mixture of several strategies), the encoder design process is undertaken carefully from the algorithmic level to the architectural level. Firstly, the encoding algorithm is analyzed and divided into sub-algorithms, called tasks, and the tasks are partitioned in the way of reusing the same designs. Secondly, the partitioned tasks are scheduled and synthesized to make the most efficient use of time and space. In the end, a real-time 5 channel MPEG-2 audio encoder is designed which is a heterogeneous multiprocessor system; two hardwired logic blocks and one specialized DSP processor.

Ordinary Smooth Topological Spaces

  • Lim, Pyung-Ki;Ryoo, Byeong-Guk;Hur, Kul
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.1
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    • pp.66-76
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    • 2012
  • In this paper, we introduce the concept of ordinary smooth topology on a set X by considering the gradation of openness of ordinary subsets of X. And we obtain the result [Corollary 2.13] : An ordinary smooth topology is fully determined its decomposition in classical topologies. Also we introduce the notion of ordinary smooth [resp. strong and weak] continuity and study some its properties. Also we introduce the concepts of a base and a subbase in an ordinary smooth topological space and study their properties. Finally, we investigate some properties of an ordinary smooth subspace.

Negative Selection Algorithm for DNA Sequence Classification

  • Lee, Dong Wook;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.2
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    • pp.231-235
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    • 2004
  • According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

Adaptive Quantization of Image Sequence using Block Activity Level and Edge Feature Classification (블록의 활성 레벨과 에지 특성의 분류를 이용한 동영상의 적응 양자화)

  • 안철준;공성곤
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1997.11a
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    • pp.191-194
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    • 1997
  • 본 논문에서는 2D-DCT 변환된 동영상 프레임 사이의 오차 블록들의 활성 레벨(atcivity level)과 에지의 특성을 분류하여 동영상의 적응적인 양자화를 제안한다. 각 블록에서는 활성 레벨이 각기 다르고, 같은 활성 레벨이라 할지라도 에지의 특성도 각기 다르게 나타난다. 적응적인 양자화를 위해서, 2D-DCT 변환된 영상 오차의 각 블록의 활성레벨 뿐만 아니라 AC 계수들의 분포에 따른 에지 특성을 분류하면, 블록의 활성 레벨만을 일률적으로 적용한 Sorting 방법의 경우보다 향상된 영상을 복원할 수 있다. 블록의 활성 레벨은 AC energy에 의해서 측정하고, 에지 특성은 AC 계수들의 분포에 의해 결정하게 된다.

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Central limit theorems for fuzzy random sets (퍼지 랜덤 집합에 대한 중심극한정리)

  • Kwon Joong-Sung;Kim Yun-Kyong;Joo Sang-Yeol;Choi Gyeong-Suk
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.3
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    • pp.337-342
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    • 2005
  • The present paper establishes the improved version of central limit theorem for sums of level-continuous fuzzy set-valued random variables as a generalization of central limit theorem for sums of independent and identically distributed set-valued random variables.

An Authoring Tool based on Student Model for Intelligent Tutoring System - on the 300-Certification Program of English Conversation - (지능형 교육 시스템을 위한 학습자 모델 기반의 저작 도구 - 생활영어 300인증제 중심으로 -)

  • Kim, Jee-Youn;Lee, Young-Seok;Cho, Jung-Won;Choi, Byung-Uk
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.805-806
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    • 2006
  • In many of ITS(Intelligent Tutoring System), they only evaluate student level or simple some student character. We propose student model for considering many student characteristics. Our student model contains student level and student's weak problem type, domain field, problem situation. We can provide optimum problem to individual student by student model.

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Specialized Product-Line Development Methodology for Developing the Embedded System

  • Hong Ki-Sam;Yoon Hee-Byung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.3
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    • pp.268-273
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    • 2005
  • We propose the specialized product-line development methodology for developing the embedded system of an MSDFS (Multi Sensor Data Fusion System : called MSDFS). The product-line methodology provides a simultaneous design between software and hardware, high level reusability. However this is insufficient in requirement analysis stage due to be focused on software architecture, detailed design and code. Thus we apply the business model based on IDEF0 technique to traditional methodology. In this paper, we describe the processes of developing Core-Asset, which are requirement analysis, feature modeling, validation. The proposed model gives the efficient result for eliciting features, and ensures the high level reusability of modules performing on embedded system.

Performance Evaluation of High-Level Ozone Prediction Model Based on the Confidence Level Test (신뢰수준평가에 기반한 고농도 오존 예측모델의 성능평가)

  • 정재룡;안항배;송치권;배현;전병희;김성신
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.195-198
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    • 2002
  • 고농도오존이 발생되는 원인과 환경적 요인의 상호관계를 모델링하기 위해 신경회로 망과 같은 지능제어 기법들이 많이 적용되어 왔다 분석과 모델링을 위해 유전자 알고리즘과 같은 최적화 방법을 적용하기도 하지만, 고농도 오존이 발생되는 메커니즘이 매우 복잡하고, 비선형적이며, 패턴파악이 어렵기 때문에 고농도 오존의 예측 모델링에는 여전히 문제점이 있다 따라서 본 논문에서는 신뢰수준과 신뢰구간을 이용하여 초농도 오존을 예측할 수 있는 모델링 방법을 서술하였다 예측값의 신뢰수준의 평가는 예측에 대한 실측값을 구하여 신뢰구간내의 데이터의 개수를 파악함으로써 신뢰성을 평가할 수 있다. 또한 이 테스트는 우리가 가지고 있지 않은 데이터에 대한 유효성을 평가하는데 적용될 수 있다 그리고 본 논문에서는 GMDH(Group Method of data handling)의 전형적인 알고리즘에 바탕을 두고 있는 DPNN(Dynamic Polynomial Neural Network)를 이용하여 예측 모델을 구성하였다. DPNN은 데이터 해석이 용이하고 비선형적인 동적 시스템 예측에 유용하게 적용될 수 있는 장점을 가지고 있다.

Intelligent consistency checking method for the use case model

  • Lee, Eun-young;Shim, Woo-gon;Paik, In-sup
    • Proceedings of the KAIS Fall Conference
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    • 2003.11a
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    • pp.50-56
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    • 2003
  • In the development of complex software system, it is important to use hierarchical use case model due to the complex scope of development procedure. The use case model is core factor of the OMG (Object Management Group)'s UML (Unified Modeling Language) diagrams. In this paper, we propose a novel method to check syntactic consistency automatically in use case models at the different level of abstraction. This method is a rule-based approach which utilizes actor tree, use case tree and use case description. The proposed method is simulated on ITS (Intelligent Transportation System) architecture for the verification.

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