• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.85-90
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• 2005

The advance of mobile and telematics technologies has produced vehicles with various convenient services for drivers. Specifically lots of researches and several technologies have been developed to provide services of a remote vehicle diagnosis and control. The existing and representative product for a vehicle control is a RCS (remote control system), but it has a problem of short control distance and fragile security. In this paper, a telematics terminal embedded with CDMA and GPS is designed, which can be connected to the Internet. It allows a driver with a cellular phone to remotely diagnosis and control a vehicle via wireless network and SMS.

• 산업공학
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• 제25권3호
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• pp.309-318
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• 2012

Forecasting probability or likelihood of technology development success has been a crucial factor for critical decisions in technology management such as R&D project selection and go or no-go decision of new product development (NPD) projects. This paper proposes an analytic network process (ANP) approach to forecasting of technology development success. Reviewing literature on factors affecting technology development success has constructed the ANP model composed of four criteria clusters : R&D characteristics, R&D competency, technological characteristics, and technological environment. An alternative cluster comprised of two elements, success and failure is also included in the model. The working of the proposed approach is provided with the help of a case study example of MRAM (magnetic random access memory) technology.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (D)
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• pp.95-99
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• 2007

본 논문에서는 EPCglobal Network 상의 물류 정보 시스템인 EPC IS(Electronic Product Code Information Services)와 EPCIS Discovery System의 기능을 확장하여 사용자 정보를 유지할 수 있도록 한다. 본 논문에서 EPC IS에 저장된 정보는 공개(Public)정보와 비공개(Private)정보로 나뉘고, 물류 정보사용자에 따라 접근 가능한 정보가 다르다는 전제하에 물류 정보 사용자가 물류 정보 접근 시 사용자 정보를 유지하는 EPCIS Discovery System과 EPC IS의 연동을 통한 물류 정보 접근 제어가 이루어질 수 있도록 방법과 절차를 제안한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1002-1005
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• 1991

It is important to express the specific growth rate of a fermentation reaction as a function of substrate and product concentration in developing bioprocess automation techniques such as modeling of the reactor and controlling it via an advanced control scheme. Typical methods of identification utilize graphical representation of the rate constant data or nonlinear regression with an appropriate noise filter. But the former method fails when the data are erroneous and the latter are mathematically complicated to apply in the field. Neural network is another candidate for the identification from time series data since it is insensitive to the random data error and easy to implement. In this study, we will develop a neural network method of specific growth rate estimation from the time series state variable data and test the performance.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.262-269
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• 2003

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Management (SCM). One of the key issues in the current SCM research area involved reducing both production and distribution costs. The purpose of this study is to determine the optimum quantity of production and transportation with minimum cost in the supply chain network. We have presented a mathematical model that deals with real world factors and constructs. Considering the complexity of solving such model, we have applied the genetic algorithm approach for solving this model computational experiments using a commercial genetic algorithm based optimizer. The results show that the real size problems we encountered can be solved In reasonable time

• Journal of applied mathematics & informatics
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• 제35권3_4호
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• pp.387-397
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• 2017

In order to react the dynamic behavior of the system more actually, it is necessary to solve the first problem of synchronization for Markovian jump complex network system in practical engineering problem. In this paper, the problem of local stochastic synchronization for Markovian nonlinear coupled neural network system is investigated, including nonlinear coupling terms and mode-dependent delays, that is less restriction to other system. By designing the Lyapunov-Krasovskii functional and applying less conservative inequality, we get a new criterion to ensure local synchronization in mean square for Markovian nonlinear coupled neural network system. The criterion introduced some free matrix variables, which are less conservative. The simulation confirmed the validity of the conclusion.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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• pp.170-177
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• 2000

Sorting cut roses according to quality is very essential to increase the value of the product. Many factors are involved in determining the grade of cut roses: length, thickness, and straightness of stem, color and maturity of bud, and extra. Among these factors, the stem straightness and bud maturity are considered to be difficult to set proper classification criteria. In this study, a prototype machine and an analysis procedure were developed to grade cut roses according to stem straightness and bud maturity by utilizing color image processing and neural network. The test results indicated 15.8% classification error for stem straightness and 10.0% for bud maturity.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2009년도 춘계학술대회 논문집
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• pp.388-395
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• 2009

The objectives of this study are to analyze the railway traffic conditions of Korea, China and Japan, and to appropriate the railway network planning for international logistics in Northeast Asia. Korea is located geographically on the main trunk route in Northeast Asia. Considering the geographical advantage and the overall potential of the economic and trade in Northeast Asia region, this area is required to connect the railway network. Recently, the scale of economic in Northeast Asia, including Korea, China and Japan, is increasing, also Northeast Asia's gross domestic product(GDP) is 22 percent of global and containers trade come up to 36 percent. Each country intend about integration of economic region for activity of mutual economic cooperation, for steady development and prosperity of each country economic all over the world, and Northeast Asia countries are in debate. There is a quite possibility of integration by a single economic region in Korea, China and Japan. Accordingly these countries should have expansion of traffic infrastructure, when the economic region is going to integration.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 3부
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• pp.322-325
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• 2007

Graphics processing unit (GPU) is used for a faster artificial neural network. It is used to implement the matrix multiplication of a neural network to enhance the time performance of a text detection system. Preliminary results produced a 20-fold performance enhancement using an ATI RADEON 9700 PRO board. The parallelism of a GPU is fully utilized by accumulating a lot of input feature vectors and weight vectors, then converting the many inner-product operations into one matrix operation. Further research areas include benchmarking the performance with various hardware and GPU-aware learning algorithms. (c) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.1041-1044
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• 2000

The enhancement to the back-propagation algorithm presented in this paper has resulted from the need to extract sparsely connected networks from networks employing product terms. The enhancement works in conjunction with the back-propagation weight update process, so that the actions of weight zeroing and weight stimulation enhance each other. It is shown that the error measure, can also be interpreted as rate of weight change (as opposed to ${\Delta}W_{ij}$), and consequently used to determine when weights have reached a stable state. Weights judged to be stable are then compared to a zero weight threshold. Should they fall below this threshold, then the weight in question is zeroed. Simulation of such a system is shown to return improved learning rates and reduce network connection requirements, with respect to the optimal network solution, trained using the normal back-propagation algorithm for Multi-Layer Perceptron (MLP), Higher Order Neural Network (HONN) and Sigma-Pi networks.