• Korean Journal of Cognitive Science
• /
• v.10 no.1
• /
• pp.13-24
• /
• 1999

In this paper, we propose a classifier based on modular networks using an unsupervised learning method. The structure of each module is designed through stochastic analysis of input data and each module classifier data independently. The result of independent classification of each module and a measure of the nearest distance are integrated during the final data classification phase to allow more precise c classification. Computation time is decreased by deleting modules that have been classified to be incorrect during the final classification phase. Using this method. a neural network sharing the best performance was implemented without considering. lots of of variables which can affect the performance of the neural network.

• Journal of Science of Art and Design
• /
• v.5
• /
• pp.5-34
• /
• 2003

This study aims at the observation of some analytical levels-especially those of syntactico-semantical- of the visual expressions in general. As far as the syntactical parts are concerned, there were two steps to be approached. One is to select the paradigms according to the Saussure-Hambidgean suggestions, the other to derive syntagmas from what is called the 'chaos-system', one of nonlinear dynamics. In result, paradigms could be acquired 5 sorts with its so many varieties, as visual templates(VT), supplemented by their reciprocals(R) and complements(CLE), and syntagmas five orbits from each constant c=0 to c=10. In additional, in connection with semantic parts, the study introduced a Gremasian model of discourses and narratives for the interpretation of signifiers. By this, we could cover the conjunctive relationships(+) and the disjunctive(-) of the whole structure of visual expression. Finally, we certified that the above could be fully approved in terms of recent worldly cognitive scientic psychological discoveries.

• Journal of Communications and Networks
• /
• v.15 no.5
• /
• pp.486-495
• /
• 2013

In this article, we suggest a two-dimensional genetic algorithm (GA) method that applies a cognitive radio (CR) decision engine which determines the optimal transmission parameters for multicarrier communication systems. Because a CR is capable of sensing the previous environmental communication information, CR decision engine plays the role of optimizing the individual transmission parameters. In order to obtain the allowable transmission power of multicarrier based CR system demands interference analysis a priori, for the sake of efficient optimization, a two-dimensionalGA structure is proposed in this paper which enhances the computational complexity. Combined with the fitness objective evaluation standard, we focus on two multi-objective optimization methods: The conventional GA applied with the multi-objective fitness approach and the non-dominated sorting GA with Pareto-optimal sorting fronts. After comparing the convergence performance of these algorithms, the transmission power of each subcarrier is proposed as non-interference emission with its optimal values in multicarrier based CR system.

• Transactions on Control, Automation and Systems Engineering
• /
• v.1 no.1
• /
• pp.54-61
• /
• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. By using the FCM, authors have proposed FCM-based fault diagnostic algorithm. However, it can offer multiple interpretations for a single fault. In process engineering, as experience accumulated, some form of quantitative process knowledge is available. If this information can be integrated into the FCM-based fault diagnosis, the diagnostic resolution can be further improved. The purpose of this paper is to propose an enhanced FCM-based fault diagnostic scheme. Firstly, the membership function of fuzzy set theory is used to integrate quantitative knowledge into the FCM-based diagnostic scheme. Secondly, modified TAM recall procedure is proposed. Considering that the integration of quantitative knowledge into FCM-based diagnosis requires a great deal of engineering efforts, thirdly, an automated procedure for fusing the quantitative knowledge into FCM-based diagnosis is proposed by utilizing self-learning feature of neural network. Finally, the proposed diagnostic scheme has been tested by simulation on the two-tank system.

• The Journal of the Korea Contents Association
• /
• v.5 no.5
• /
• pp.33-42
• /
• 2005

In this paper, we propose a new training algorithm for improving pattern classification performance of ART neural network. The proposed train algorithm restricts unnecessary cluster generation and transition, applies the location extraction algorithm, and operates the reset system based on the agreement between the present learning pattern and the initial pattern. As a result, repetitive input of a pattern does not generate a new cluster and mis-recognition rate decreases.

• Proceedings of the Korean Society for Cognitive Science Conference
• /
• 2000.06a
• /
• pp.411-418
• /
• 2000

Hausser (1999)와 이기용 (1999a, 1999c)에서는 데이터베이스 관리 시스템(DBMS)을 이용하여 자연언어의 의미를 다루는 데이터베이스 의미론을 제안하였다. 특히 이기용 (1999c)에서는 수형도(tree), 논리 형태(logical fomulas), 자질 구조(feature structure)와 같은 다양한 언어 표상 형식들을 관계형 데이터베이스 관리 시스템(DBMS)의 표상 형식인 테이블 형식으로 전환 가능함을 보임으로써 데이터베이스 의미론에 관계형 데이터베이스 관리 시스템을 도입할 수 있음을 제시하였다. 한편, Lee (2000)에서 제시한 데이터베이스 의미론 모형에서는 데이터베이스 관리 시스템과 사용자(end-user)를 연결하는 언어 정보 처리 시스템(LIPS; Linguistic Information Processing System)을 제안하였다. 이 언어 정보 처리 시스템은 사용자에 의해 입력된 언어 자료를 처리하여 그 분석 결과를 데이터베이스 관리 시스템에 전달하고, 이를 통해 구축된 데이터베이스에서 추출한 정보를 다시 사용자에게 전달하는 시스템이다. 이 논문은 한국어 '이, 히, 리, 기' 피동형을 전산처리 할 수 있도록, 데이터베이스 의미론에서 핵심 요소인 언어정보 처리 시스템과 데이터베이스 관리 시스템을 구현하는 것이 목적이다.

• ETRI Journal
• /
• v.37 no.5
• /
• pp.917-921
• /
• 2015

We consider a multiserver system with two classes of customers with preemption, which is a widely used system in the analysis of cognitive radio networks. It is known that the optimal admission control for this system is of threshold type. We express the expected total discounted profit using the total number of customers, thus reducing the stochastic optimization problem with a two-dimensional state space to a problem with a one-dimensional birth-and-death structure. An efficient algorithm is proposed for the calculation of the expected total discounted profit.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.97-98
• /
• 2007

In this paper, we investigate the throughput capacity of a multi-hop relay network with cognitive radio (CR) enabled relay stations (RS). We suggested a TDMA/FDMA based frame structure where RSs dynamically select unused channels to communicate with the base station (BS) using CR techniques to analyze the throughput capacity. We developed the throughput capacity model for the proposed system based on utilization factor. The analytical results based on those equations show significant improvement in throughput capacity for CR enabled multi-hop relay system.

• Journal of information and communication convergence engineering
• /
• v.20 no.4
• /
• pp.273-279
• /
• 2022

Owing to the need to establish a cooperative-intelligent transport system (C-ITS) environment in the transportation sector locally and abroad, various research and development efforts such as high-tech road infrastructure, connection technology between road components, and traffic information systems are currently underway. However, the current central control center-oriented information collection and provision service structure and the insufficient road infrastructure limit the realization of the C-ITS, which requires a diversity of traffic information, real-time data, advanced traffic safety management, and transportation convenience services. In this study, a network construction method based on the existing received signal strength indicator (RSSI) selected as a comparison target, and the experimental target and the proposed intelligent edge network compared and analyzed. The result of the analysis showed that the data transmission rate in the intelligent edge network was 97.48%, the data transmission time was 215 ms, and the recovery time of network failure was 49,983 ms.

• World Technopolis Review
• /
• v.5 no.2
• /
• pp.108-118
• /
• 2016

There are very few studies on governance structure for the collaboration between HEIs and science and technology parks until today. Major activities between science parks and HEIs are R&D activities, collaborative researches, technology transfer, space provision for BIs and Technology BIs in the science parks, provision of technical, legal and financial services for start-ups and venture firms. Governance structure for the collaboration of high education institutes with science and technology parks is the handling of complexity and management of dynamic flows of collaboration between two groups. Three models on the governance structure for the collaboration are suggested in this study. The first model is a governance structure that links R&D system such as universities, public research institutes and private research institutes with industrial production cluster such as a group of companies and industrial parks. The second model is a governance structure that has four layers of hierarchy. This hierarchical governance model is composed of four levels of organizations such as central government, three actors, one center for collaboration and many individual research performers. The third model is a governance structure that networks all the stakeholders horizontally. Under this structure, governance is conducted by the network members with no separate and unique governance entity.