• 융합신호처리학회논문지
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• 제2권4호
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• pp.77-84
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• 2001

신경망을 이용한 선형프로그랭 회로를 홉프필드가 제안한 이후로 이에 관한 많은 논문들이 발표되었으며, 그 중에는 비선형 프로그래밍 문제에 관한 것들도 많다. 그래서 비용함수가 비선형인 경우는 해결이 되었으나 제한조건이 비선형인 경우에는 해결되지 못한 상태이다. 이 논문에서는 제한조건이 비선형인 경우를 포함하는 즉 비용함수와 제한조건 모두 비선형인 경우를 풀 수 있는 일반적인 비선형프로그래밍 신경망을 제안하고자 한다.

• 경영과학
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• 제23권2호
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• pp.161-174
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• 2006

In this paper, we consider a network optimization problem arising from the deployment of BcN access network. BcN convergence services requires that access networks satisfy QoS meausres. BcN services have two types of traffics : stream traffic and elastic traffic. Stream traffic uses blocking probability as a QoS measure, while elastic traffic uses delay factor as a QoS measure. Incorporating the QoS requirements, we formulate the problem as a nonlinear mixed-integer Programming model. The Proposed model seeks to find a minimum cost dimensioning solution, while satisfying the QoS requirement. We propose two local search heuristic algorithms for solving the problem, and develop a network design system that implements the developed heuristic algorithms. We demonstrate the computational efficacy of the proposed algorithm by solving a realistic network design problem.

• Journal of Communications and Networks
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• 제17권2호
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• pp.184-197
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• 2015

This paper builds on a recent method, chain routing with even energy consumption (CREEC), for designing a wireless sensor network with chain topology and for scheduling the communication to ensure even average energy consumption in the network. In here a new suboptimal design is proposed and compared with the CREEC design. The chain topology in CREEC is reconfigured after each group of n converge-casts with the goal of making the energy consumption along the new paths between the nodes in the chain as even as possible. The new method described in this paper designs a single near-optimal Hamiltonian circuit, used to obtain multiple chains having only the terminal nodes different at different converge-casts. The advantage of the new scheme is that for the whole life of the network most of the communication takes place between same pairs of nodes, therefore keeping topology reconfigurations at a minimum. The optimal scheduling of the communication between the network and base station in order to maximize network lifetime, given the chosen minimum length circuit, becomes a simple linear programming problem which needs to be solved only once, at the initialization stage. The maximum lifetime obtained when using any combination of chains is shown to be upper bounded by the solution of a suitable linear programming problem. The upper bounds show that the proposed method provides near-optimal solutions for several wireless sensor network parameter sets.

• 대한산업공학회지
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• 제27권3호
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• pp.250-259
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• 2001

Given a tree structured network in which each node has its own demand and also stands for a candidate location of a potential facility, such as plant or warehouse, a capacitated facility location problem on the network (CFLPOT) is to decide capacitated facility locations so that the total demand occurred on the network can be satisfied from those facilities with the minimum cost. In this paper, we first introduce a mixed integer programming formulation for CFLPOT with two additional assumptions, the indivisible demand assumption and the contiguity assumption and then show that it can be reformulated as a tree partitioning problem with an exponential number of variables. We then show that it can be solved in O($n^2b$) time by utilizing the limited column generation method developed by Shaw (1993), where n is the total number of nodes in the network and b is the maximum facility capacity. We also develop a depth-first dynamic programming algorithm with a running time of O(nb) for finding the locally maximal reduced cost which plays an important role in the limited column generation method. Finally, we implement our algorithms on a set of randomly generated problems and report the computational results.

• Journal of information and communication convergence engineering
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• 제6권4호
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• pp.448-453
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• 2008

This study describes design and development techniques of estimation models for process modeling. One case study is undertaken to design a model using standard gas furnace data. Neural networks (NN) and genetic programming (GP) are each employed to model the crucial relationships between input factors and output responses. In the case study, two models were generated by using 70% training data and evaluated by using 30% testing data for genetic programming and neural network modeling. The model performance was compared by using RMSE values, which were calculated based on the model outputs. The average RMSE for training and testing were 0.8925 (training) and 0.9951 (testing) for the NN model, and 0.707227 (training) and 0.673150 (testing) for the GP model, respectively. As concern the results, the NN model has a strong advantage in model training (using the all data for training), and the GP model appears to have an advantage in model testing (using the separated data for training and testing). The performance reproducibility of the GP model is good, so this approach appears suitable for modeling physical fabrication processes.

• 한국정보과학회논문지:정보통신
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• 제37권1호
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• pp.8-15
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• 2010

본 연구에서 우리는 복합 이벤트(complex event)와 관점지향 프로그래밍(aspect-oriented programming)을 함께 고려하여 확장된 복합 이벤트 모델을 제시한다. 우리는 이 두 모델의 통합을 통해 이벤트 상관 기반의 네트워크 관리 시스템에 적합한 진보된 이벤트 명세 방법을 제안한다. 구체적으로, 계층적 이벤트 구조를 지원하도록 모델을 확장하고 관점지향 프로그래밍의 교차점(point cut)을 이벤트로 인식하도록 한다. 또한 이벤트 명세를 인스턴스(instance) 단위로 할 수 있도록 이벤트 연산자를 제공하고 시간적 관계를 원활하게 표현할 수 있도록 한다. 마지막으로 다른 이벤트 모델과의 비교를 통해 본 이벤트 모델의 장점을 제시한다.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1995년도 제4회 멀티미디어 산업기술 학술대회 논문집
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• pp.3-19
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• 1995

시스템 Technology ★ Server Technology - 운영환경구축 ★ Network 구성설계 - ATM, FDDI, NMS ★ Client/Server시스템 구성별 Bench Marking ★ Windows 메뉴 및 GUI 설계 ★다기능 PC 운영환경 설정 시스템 Technology ★ Data Base Technology - DB Administration - BB Performance Tuning ★ System Integration Technology - Application Integration - System Flow Control - Task Control - Applicational Interface - S/W Down Load 시스템 Technology ★ Memory Optimization ★ IBM/Facom Host API ★ 영상전화 Customizing - Intel Proshare ★ Auto Dialing - CTI Link ★ IC-Card Interface 시스템 Technology ★ Sound 처리 - Voice Mail - 음절 처리 ★ Image 처리 ★도움말 처리 - Hyper Text 시스템 Technology ★ Socket Programming - 긴급메일 - Peer to peer message switching ★ Set Up Programming -Install Shield ★ DB Access Programming - DB-Library ★ TCP/IP Programming(중략)

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.105-112
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• 2022

The development and spread of IT-technologies has raised interest in teaching programming pupils. The article deals with problems related to programming and ways to overcome them. The importance of programming skills is emphasized, as this process promotes the formation of algorithmic thinking of pupils. The authors determined the level of pupils' interest to programing learning depending on the age. The analysis has showed that the natural interest of younger pupils in programming is decreasing over the years and in the most productive period of its study is minimized. It is revealed that senior school pupils are characterized by low level of interest in the study of programming; lack of motivation; the presence of psychological blocks on their own abilities in the context of programming; law level of computer science understanding. To overcome these problems, we conducted the second stage of the experiment, which was based on a change in the approach to programing learning, which involved pupils of non-specialized classes of senior school (experimental group). During the study of programming, special attention was paid to the motivational and psychological component, as well as the use of game technologies and teamwork of pupils. The results of the pedagogical experiment on studying the effectiveness of teaching programming for pupils of nonspecialized classes are presented. Improvement of the results provided the use of social and cognitive motives; application of verbal and non-verbal, external and internal means; communicative attacks; stimulation and psychological setting; game techniques, independent work and reflection, teamwork. The positive effect of the implemented methods is shown by the results verified by the methods of mathematical statistics in the experimental and control groups of pupils.

• 전자공학회논문지B
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• 제31B권7호
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• pp.179-189
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• 1994

A two-phase neural network finds exact feasible solutions for a constrained optimization programming problem. The time-varying programming neural network is a modified steepest-gradient algorithm which solves time-varying optimization problems. In this paper, we propose a time-varying two-phase optimization neural network which incorporates the merits of the two-phase neural network and the time-varying neural network. The proposed algorithm is applied to system identification and function approximation using a multi-layer perceptron. Particularly training of a multi-layer perceptrion is regarded as a time-varying optimization problem. Our algorithm can also be applied to the case where the weights are constrained. Simulation results prove the proposed algorithm is efficient for solving various optimization problems.

• 한국멀티미디어학회논문지
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• 제11권6호
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• pp.807-815
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• 2008

A simple efficient method of spotting and recognizing hand gestures in video is presented using a network of hidden Markov models and dynamic programming search algorithm. The description starts from designing a set of isolated trajectory models which are stochastic and robust enough to characterize highly variable patterns like human motion, handwriting, and speech. Those models are interconnected to form a single big network termed a spotting network or a spotter that models a continuous stream of gestures and non-gestures as well. The inference over the model is based on dynamic programming. The proposed model is highly efficient and can readily be extended to a variety of recurrent pattern recognition tasks. The test result without any engineering has shown the potential for practical application. At the end of the paper we add some related experimental result that has been obtained using a different model - dynamic Bayesian network - which is also a type of stochastic model.