• 한국컴퓨터정보학회논문지
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• 제14권9호
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• pp.1-10
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• 2009

웹 서비스 조합 분야는 단일 서비스를 재사용하여 가치 있는 서비스를 생성하기 위해 등장했으며, 최근에는 차세대 웹 서비스인 시멘틱 웹을 구현하기 위해 IOPE를 기반으로 단순 검색 및 조합 대신에 규칙이나 AI를 통한 검색 및 조합 방법이 제안되고 있다. 또한 보다 효율적인 모듈화를 위해 기존의 객체지향 프로그래밍 방식보다는 관점지향 프로그래밍 방식이 도입되고 있다. 본 논문에서는 시멘틱 웹을 위해 관점지향 프로그래밍(Aspect-Oriented Programming, AOP) 및 리플렉션(Reflection)을 적용한 동적 웹 서비스 조합 및 실행 기법을 설계한다. 제안하는 기법은 웹 서비스의 메타 데이터를 동적으로 획득하기 위해 리플렉션 기법을 사용하고 아울러 동적으로 웹 서비스를 조합하기 위해 AOP 기반 접근방식을 통해 바이트 코드를 생성한다. 또한 리플렉션을 이용한 동적 프록시 객체를 통해 조합된 웹 서비스를 실행하는 방식을 제안한다. 제안하는 기법의 성능 평가를 위해 비즈니스 로직 계층과 사용자 뷰 계층 측면에서 조합된 웹 서비스를 검색하는 것에 대한 실험을 수행한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2949-2952
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• 2000

A new neural networks and learning algorithm are proposed in order to measure nonlinear heights of complexed road environments in realtime without pre-information. This new neural networks is Error Self Recurrent Neural Networks(ESRN), The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by back-propagation and each weights are updated by RLS(Recursive Least Square). Consequently. this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by ESRN and learning algorithm and control nonlinear models. To show the performance of this one. we control 7 degree of freedom full car model with several control method. From this simulation. this estimation and controller were proved to be effective to the measurements of nonlinear road environment systems.

• Journal of Communications and Networks
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• 제10권3호
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• pp.258-267
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• 2008

In this paper, we examine what changes the next-generation wireless communication systems will experience in terms of the technologies, services, and networks and, based on that, we investigate how the inter-cell interference management should evolve in various aspects. We identify that the main driving forces of the future changes involve the data-centric services, new dynamic service scenarios, all-IP core access networks, new physical-layer technologies, and heavy upload traffic. We establish that in order to cope with the changes, the next-generation inter-cell interference management should evolve to 1) set the objective of providing a maximal data rate, 2) take the form of joint management of power allocation and user scheduling, 3) operate in a fully distributed manner, 4) handle the time-varying channel conditions in mobile environment, 5) deal with the changes in interference mechanism triggered by the new physical-layer technologies, and 6) increase the spectral efficiency while avoiding centralized coordination of resource allocation of the users in the uplink channel.

• Applied Microscopy
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• 제45권4호
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• pp.214-217
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• 2015

This study introduces metal coating as an effective sample preparation method to remove charge-up caused by the shadow effect during field emission scanning electron microscope (FE-SEM) analysis of dynamic structured samples. During a FE-SEM analysis, charge-up occurs when the primary electrons (input electrons) that scan the specimens are not equal to the output electrons (secondary electrons, backscattered electrons, auger electrons, etc.) generated from the specimens. To remove charge-up, a metal layer of Pt, Au or Pd is applied on the surface of the sample. However, in some cases, charge-up still occurs due to the shadow effect. This study developed a coating method that effectively removes charge-up. By creating a converted sample stage capable of simultaneous tilt and rotation, the shadow effect was successfully removed, and image data without charge-up were obtained.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2016년도 전력전자학술대회 논문집
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• pp.357-358
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• 2016

This paper presents a dynamic, electric-thermal model for a photovoltaic (PV) cell that combines electrical and thermal parameters. In this model, the irradiance and ambient temperature are used to calculate the PV cell temperature based on a five-layer thermal model. The cell temperature is then used in the electrical model to accurately adjust the PV cell output electrical characteristics and power. A custom experimental setup was built to test and verify the electrical and thermal characteristics of the PV cell and its surrounding layers. The electric-thermal model is validated using experimental data in realistic scenarios. This PV model can be scaled up and used to simulate PV systems in wide variety of applications, extreme environmental conditions, and fault conditions in real-time.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1997년도 춘계학술대회논문집
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• pp.107-113
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• 1997

In this paper, an interfacing method to control rehabilitation assitance system with bio-signal is proposed. Controlling with EMG signals method has certain advantage on signal-collecting, but has some drawbacks in the function resolution of EMG signals because data-processing process is not efficient. To improve function-resolution and to increase the efficiency of EMG signal interfacing with rehabilitation assistance system, Multi-layer Perception which is highly effective with static signal and hidden-Markov model for dynamic signal resolving are fused together. In proposed method. The direction and average speed of the rehabilitation assitance system are controlled by the trajectory control and estimation of the moving direction result from the fused model. From the experiment, proposed GMM and 2-level MLP hybrid-classifier yielded 8.6% perception-error rate, improving function resolution. New acceleration control method constructed with 3 nested linear filter produced continuous acceleration paths without the information of destination point. Thus, the mass output caused by non- continuous acceleration-deceleration was eliminated. In the simulation, the necessary calculation, in the case of multiplication, was reduced by 11.54%.

• 한국정밀공학회지
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• 제14권7호
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• pp.29-38
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• 1997

A closed-loop system modeling of an active/semiactive suspension system has been accomplished through an artificial neural network. A 7DOF full model as a system's equation of motion has been derived and an output feedback linear quadratic regulator has been designed for control purpose. A training set of a sample data has been obtained through a computer simulation. A 7DOF full model with LQR controller simulated under several road conditions such as sinusoidal bumps and rectangular bumps. A general multilayer perceptron neural network is used for dynamic modeling and target outputs are fedback to the a layer. A backpropagation method is used as a training algorithm. Model validation of new dataset have been shown through computer simulations.

• 대한전기학회논문지
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• 제31권9호
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• pp.74-81
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• 1982

One of the stable thin film transistor fabricated by cadmium suifide with the anodized aluminium oxide as gate material. The principle of the operation for the device is based on the control mechanism of injected majority carricrs to the wide band gap semiconductor, that is cadmium sulfide, by means of the function of the gate control. The fabricated device constructed by evaporating CdS layer in the form of microcrystalline on the oxided thin film characterized by ea, 80 as voltage amplification factor, 1/100 mho as transconductance, 8 kohm as dynamic output resistance, furthermore gain band width products is about 15 MHz.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.384-388
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• 1996

The closed-loop system modeling of an Active/semiactive suspension system has been accomplished through an artificial neural Networks. The 7DOF full model as the system equation of motion has been derived and the output feedback linear quadratic regulator has been designed for the control purpose. For the neural networks training set of a sample data has been obtained through the computer simulation. A 7DOF full model with LQR controller simulated under the several road conditions such as sinusoidal bumps and the rectangular bumps. A general multilayer perceptron neural network is used for the dynamic modeling and the target outputs are feedback to the input layer. The Backpropagation method is used as the training algorithm. The modeling of system and the model validation have been shown through computer simulations.

• 대한전기학회논문지:전력기술부문A
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• 제50권11호
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• pp.497-505
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• 2001

The power system stabilizer(PSS) is important for the suppression of low-frequency oscillation and the improvement of system stability. In this paper, An Adaptive Neurofuzzy-based Power System Stabilizer(ANF PSS) is proposed as the new PSS type. The proposed PSS employs a multi-layer adaptive network. The network is trained directly from the input and the output of the generating unit. The algorithm combines the advantages of the Artificial Neural Network(ANN) and Fuzzy Logic Control(FLC) schemes. Studies show that the proposed ANF PSS can provide good damping of the power system over the wide range of operating conditions and improve the dynamic performance of the system.