• 전기학회논문지
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• 제63권12호
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• pp.1704-1709
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• 2014

In order to increase the performance of multi-core system processor architectures, the multi-thread branch predictor which speculatively fetches and allocates threads to each core should be highly accurate. In this paper, the perceptron based multi-thread branch predictor is proposed for the multi-core processor architectures. Using SPEC 2000 benchmarks as input, the trace-driven simulation has been performed for the 2 to 16-core architectures employing perceptron multi-thread branch predictor extensively. Its performance is compared with the architecture which utilizes the two-level adaptive multi-thread branch predictor.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.1(D)
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• pp.190-195
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• 2010

Vehicular ad hoc networks (VANETs) have a number of interesting applications to preserve road safety, notify users about changed road/traffic condition, handling post accident hazards and moreover service oriented applications to make the travel convenient to the drivers. Use of common information format for diverse applications enables the application developers to easily design flexible information dissemination system for new applications or add new features to existing application. This paper introduces a common information format for various applications in VANETs. The main goal of the paper is to design generalized distributed architectures for vehicular networks, which considers diverse application development scenarios and uses common information format. The proposed architectures enable the application developers to flexibly disseminate information to affected or interested user. In this paper, we have given a detail description of each component of the architectures and how they communicate with each other. In future, we will implement the proposed architecture using suitable simulator.

• Asia pacific journal of information systems
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• 제8권3호
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• pp.51-73
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• 1998

This paper is to evaluate the application potentials of data mining in the areas of Supply Chain Management (SCM) and to suggest the architectures of Decision Support Systems (DSS) that support data mining activities. We first briefly introduce data mining and review the recent literatures on SCM and then evaluate data mining applications to SCM in three aspects: marketing, operations management and information systems. By analyzing the cases about pricing models in distribution channels, demand forecasting and quality control, it is shown that artificial intelligence techniques such as artificial neural networks, case-based reasoning and expert systems, combined with traditional analysis models, effectively mine the useful knowledge from the large volume of SCM data. Agent-based information system is addressed as an important architecture that enables the pursuit of global optimization of SCM through communication and information sharing among supply chain constituents without loss of their characteristics and independence. We expect that the suggested architectures of intelligent DSS provide the basis in developing information systems for SCM to improve the quality of organizational decisions.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 춘계학술발표대회
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• pp.309-311
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• 2022

Oral cancer is a type of cancer that has a high possibility to be cured if it is threatened earlier. The convolutional neural network is very popular for being a good algorithm for image recognition. In this research, we try to compare 4 different architectures of the CNN algorithm: Convnet, VGG16, Inception V3, and Resnet. As we compared those 4 architectures we found that VGG16 and Resnet model has better performance with an 85.35% accuracy rate compared to the other 3 architectures. In the future, we are sure that image recognition can be more developed to identify oral cancer earlier.

• 대한원격탐사학회지
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• 제28권1호
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• pp.101-116
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• 2012

본 논문에서는 기존에 구축되어있는 위성영상처리 시스템의 구축현황을 살펴보고, 향후 국내 기상위성 영상처리 시스템 구축에서 고려해야할 사항에 대해 살펴본다. 기존의 위성영상처리 시스템은 운영 중인 개별 위성에 대한 영상의 수집, 처리, 배포 기능을 구현한 시스템이 대부분이었다. 그러나 향후 지구환경 감시를 위한 다양한 위성들의 개발에 따른 새로운 시스템의 통합, 기존 시스템에 대한 유지보수에 대한 문제점이 지적되고 있다. 미국의 NOAA, NWS, 유럽의 ESA등에서는 이러한 문제점을 해결하기 위해 기존의 시스템에 대한 개선 사업을 진행 중에 있다. 이에 본 논문에서는 현재 국내외에서 개발되는 위성영상처리시스템의 구축 현황을 살펴보고, 개발 이슈 및 개발 전략에 대해 살펴보고자 한다.

• 디지털산업정보학회논문지
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• 제4권3호
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• pp.19-31
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• 2008

Currently, RFID is receiving attention from the industry and the academy because it is considered as an enabling technology for ubiquitous computing, in particular context perception. In this paper, we survey the existing context-aware RFID systems and introduce three main issues in the systems - the context information, the context-aware services, and the context-aware RFID system architectures. We classify context information into six groups, the services into five context-aware service types, and the systems into four architecture styles. This study will help stakeholders such as customers and developers to understand their RFID systems and to develop new services.

• 제어로봇시스템학회논문지
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• 제8권2호
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• pp.126-135
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• 2002

The study is concerned with an approach to the design of new architectures of fuzzy neural networks and the discussion of comprehensive design methodology supporting their development. We propose an Adaptive Fuzzy Polynomial Neural Networks(APFNN) based on Fuzzy Neural Networks(FNN) and Self-organizing Networks(SON) for model identification of complex and nonlinear systems. The proposed AFPNN is generated from the mutually combined structure of both FNN and SON. The one and the other are considered as the premise and the consequence part of AFPNN, respectively. As the premise structure of AFPNN, FNN uses both the simplified fuzzy inference and error back-propagation teaming rule. The parameters of FNN are refined(optimized) using genetic algorithms(GAs). As the consequence structure of AFPNN, SON is realized by a polynomial type of mapping(linear, quadratic and modified quadratic) between input and output variables. In this study, we introduce two kinds of AFPNN architectures, namely the basic and the modified one. The basic and the modified architectures depend on the number of input variables and the order of polynomial in each layer of consequence structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the AFPNN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed AFPNN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제2권3호
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• pp.111-116
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• 2013

공정 기술의 발전으로 인해 내장형 시스템에서 소프트 에러 발생 비율이 크게 증가하고 있다. 고성능, 저전력을 특징으로 하는 VLIW 아키텍처가 내장형 시스템에 널리 사용되어 왔는데, 이러한 VLIW 아키텍처에서 명령어 복제를 통해 소프트 에러를 감지하여 신뢰도를 높이고자 하는 연구가 진행되어 왔다. 하지만 기존 연구는 대부분의 상용 VLIW 아키텍처가 코드 크기 감소를 위해 사용하는 VLES 를 고려하지 않고 이루어졌다. 명령어 복제를 통한 신뢰도 향상을 위한 연구가 실용성 및 적용성을 갖추기 위해서는 VLES 를 지원하는 VLIW 아키텍처에 대해 이루어져야 한다. 이에 본 논문에서는 VLES 를 지원하는 VLIW 아키텍처에서 명령어 복제를 위해 필요한 설계 방법을 논하고 이에 따른 실험 결과를 제시하였다. 실험 결과 VLES 를 지원하지 않을 경우에 비해 약 4% 정도의 추가적인 하드웨어 비용을 들여 평균 64% 정도에 달하는 코드 크기 감소 효과를 얻을 수 있었고, 또한 실행 시간에는 추가적인 손실이 발생하지 않음을 알 수 있었다.

• 전자공학회논문지S
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• 제35S권8호
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• pp.12-20
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• 1998

전광 통신망(All-Optical Network)은 근거리와 원거리 통신망을 위한 차세대 광대역 통신먕이며 이를 위한 많은 광교환기들이 제안되고 있다. 특히 파장 분할 다중화 기법을 적용한 광교환기는 전광 통신망에서 B-ISDN 서비스를 위한 망의 투명성과 토폴로지 측면에서 많은 장점을 갖는다. 본 논문에서는 광링크 기반의 고속 ATM 망을 위한 두 종류의 넉아웃 광교환기 구조를 제안하였다. 제안된 구조는 파장 분할 다중화 기법을 이용하여 전광 영역에서 동작할 수 있도록 하였으며, 구조-Ⅰ과 구조-Ⅱ로 명명하였다. 각 구조는 구성 소자수 및 소자 종류에 의하여 다른 특성을 갖으며, 시스템의 성능과 복잡도도 많은 영향을 받는다. 제안된 두 종류의 광교환기 구조에 대한 해석적 분석과 시뮬레이션을 실시하였으며, 셀 손실률, 구성 소자의 복잡도, 요구되는 버퍼링 속도 관점에서 성능을 비교 분석하였다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.214-217
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• 1996

Early decision support systems (DSS) were the "passive" decision support systems in the sense that the systems only able to do what the users explicitly direct them to do. But some researchers such as Raghav Rao et al. [51 showed architectures to suggest general idea of the innovative DSS systems which offer active form of decision support, say, "active Intelligent Decision Support Systems(active IDSS)". The system can perform not only what the users want to do but some voluntary (or involuntary) intelligent works. This paper presents the issues in the design of the active IDSS in the domain of investment evaluation, a domain area where few researchers have suggested frameworks or architectures to discriminate good investment from bad one. We propose a new paradigm, by utilizing historical investment results using neural network and Multivariate Discriminant Analysis(MDA), to identify goodness of investment. A new active IDSS architecture which consists of neural network, expert system and three components of the traditional passive DSS is suggested with some scenario based results.nario based results.