• 제어로봇시스템학회논문지
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• 제20권2호
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• pp.223-231
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• 2014

Humanoid robot is the most suitable robot platform for effective human interaction and various intelligent services. The present work addresses development of real time wireless control application of humanoid robot's forward and backward walks, and turning in walking. For convenience of human users, the application is developed on Android OS (Operating System) working on his or her smartphone. To this end, theoretic background on various-directional biped walking is proposed based on joint trajectories for forward walking, which have been shaped with a global optimization method. In this paper, backward walking is scheduled by interchange of angles and angular velocities and additional change of signs in angular velocities at all the via-points connecting cubic polynomial trajectories. Turning direction in walking is also implemented by activating the transversal hip joint initially located in the support leg in two stages. After validation of the proposed walking schemes with Matlab simulator, a smartphone application for the omnidirectional walking has been developed to control a humanoid robot platform named DARwIn-OP interconnected via Wi-Fi. Experiment result of the present wireless control of a humanoid robot with smartphone is successful, and the application will be released in application market near future.

• 한국지진공학회논문집
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• 제24권2호
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• pp.67-76
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• 2020

This study aims to optimize the cochlea-inspired artificial filter bank (CAFB) using El-Centro seismic waveforms and test its performance through a shaking table test on a two-span bridge model. In the process of optimizing the CAFB, El-Centro seismic waveforms were used for the purpose of evaluating how they would affect the optimizing process. Next, the optimized CAFB was embedded in the developed wireless-based intelligent data acquisition (IDAQ) system to enable response measurement in real-time. For its performance evaluation to obtain a seismic response in real-time using the optimized CAFB, a two-span bridge (model structures) was installed in a large shaking table, and a seismic response experiment was carried out on it with El-Centro seismic waveforms. The CAFB optimized in this experiment was able to obtain the seismic response in real-time by compressing it using the embedded wireless-based IDAQ system while the obtained compressed signals were compared with the original signal (un-compressed signal). The results of the experiment showed that the compressed signals were superior to the raw signal in response performance, as well as in data compression effect. They also proved that the CAFB was able to compress response signals effectively in real-time even under seismic conditions. Therefore, this paper established that the CAFB optimized by being embedded in the wireless-based IDAQ system was an economical and efficient data compression sensing technology for measuring and monitoring the seismic response in real-time from structures based on the wireless sensor networks (WSNs).

• Journal of Power Electronics
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• 제17권2호
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• pp.476-489
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• 2017

Under partial shading conditions (PSCs), multiple maximums may be exhibited on the P-U curve of string inverter photovoltaic (PV) systems. Under such conditions, heuristic methods are invalid for extracting a global maximum power point (GMPP); intelligent algorithms are time-consuming; and model-based methods are complex and costly. To overcome these shortcomings, a novel hybrid MPPT (MPF-IP&O) based on a model-based peak forecasting (MPF) method and an improved perturbation and observation (IP&O) method is proposed. The MPF considers the influence of temperature and does not require solar radiation measurements. In addition, it can forecast all of the peak values of the PV string without complex computation under PSCs, and it can determine the candidate GMPP after a comparison. Hence, the MPF narrows the searching range tremendously and accelerates the convergence to the GMPP. Additionally, the IP&O with a successive approximation strategy searches for the real GMPP in the neighborhood of the candidate one, which can significantly enhance the tracking efficiency. Finally, simulation and experiment results show that the proposed method has a higher tracking speed and accuracy than the perturbation and observation (P&O) and particle swarm optimization (PSO) methods under PSCs.

• Journal of Power Electronics
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• 제11권2호
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• pp.228-236
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• 2011

The ${\Delta}\;V_{10}$ or 10-Hz flicker index, as a common method of measurement of voltage flicker severity in power systems, requires a high computational cost and a large amount of memory. In this paper, for measuring the ${\Delta}\;V_{10}$ index, a new method based on the Adaline (adaptive linear neuron) system, the FFT (fast Fourier transform), and the PSO (particle swarm optimization) algorithm is proposed. In this method, for reducing the sampling frequency, calculations are carried out on the envelope of a power system voltage that contains a flicker component. Extracting the envelope of the voltage is implemented by the Adaline system. In addition, in order to increase the accuracy in computing the flicker components, the PSO algorithm is used for reducing the spectral leakage error in the FFT calculations. Therefore, the proposed method has a lower computational cost in FFT computation due to the use of a smaller sampling window. It also requires less memory since it uses the envelope of the power system voltage. Moreover, it shows more accuracy because the PSO algorithm is used in the determination of the flicker frequency and the corresponding amplitude. The sensitivity of the proposed method with respect to the main frequency drift is very low. The proposed algorithm is evaluated by simulations. The validity of the simulations is proven by the implementation of the algorithm with an ARM microcontroller-based digital system. Finally, its function is evaluated with real-time measurements.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.596-599
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• 2004

The robotic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. To achieve this above objective, Taguchi method was employed using five different process parameters (tip gap, gas flow rate, welding speed, arc current, welding voltage) as a guide for optimization of process parameters.

• 지능정보연구
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• 제11권1호
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• pp.191-205
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• 2005

전자상거래의 확산에 따라 인터넷 쇼핑몰에서의 구매활동은 일반적인 현상이 되었다 그 결과, 유사한 업종이나 업태의 인터넷 쇼핑몰이 범람하게 되었고 업체들 간의 경쟁도 심화되어 차별화 된 서비스를 제공하지 않는 업체는 도태되기 쉬운 상황이다. 본 연구에서는 치열한 경쟁환경 하에서 인터넷 쇼핑몰들의 차별화 된 마케팅 서비스의 수단으로써 이용되고 있는 상품추천시스템의 개선된 모형을 제시하고자 한다. 본 연구에서 제안하는 모형은 전역 최적화 기법 중의 하나인 유전자 알고리즘을 데이터 마이닝의 도구로 활용한 인터넷 쇼핑몰에서의 개인화 된 상품추천시스템 모형이다. 유전자 알고리즘은 추출하기가 어려운 소비자의 성향을 데이터를 통해 추출하고 이에 맞는 상품군을 선택할 수 있도록 해 주는 최적화 기법으로 상품추천시스템의 추천엔진으로써 유용할 것으로 기대된다 본 연구에서는 제안하는 유전자 알고리즘에 기반한 추천규칙들이 장착된 웹 기반의 개인화 된 상품추천시스템의 프로토타입을 개발하고 이에 대한 실제 사용자들의 이용 만족도를 확인함으로써 렬 연구에서 제안한 방법론의 유용성을 확인하고자 한다.

• 지능정보연구
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• 제12권1호
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• pp.139-161
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• 2006

본 논문에서는 새로운 조합경매(combinational auction)모형인 다자간 최적화 경매모형(N-Bilateral Optimized Combinatorial Auction; N-BOCA)을 제시하였다. N-BOCA는 다수의 공급자 및 다수의 구매자간 최적화된 거래를 지원하는 조합경매모형이다. 특히 아키텍처, 거래규약, 거래전략 세가지 관점에서 N-BOCA 시스템을 설계하였다. 경매시장 참여자인 경매자들과 입찰자들은 특정 아키텍처 및 거래규약하에서 최적 거래 대상자 선정을 위한 다양한 전략을 가지게 되며 이러한 거래전략에 따른 유연한 의사결정 모델링 지원을 필요로 한다. 이에 본 논문에서는 최적의 입찰 및 경매자 선정을 위한 Integer Programming 모형 기반의 에이전트 시스템을 제시하였다. 아울러 N-BOCA모형의 유용성을 입증하기 위해 프로토타입과 실험결과를 제시하였다. 실험결과, 기존의 일대다 조합경매 모형 대비 높은 거래 성과를 나타내었다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 한국지능정보시스템학회
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• pp.389-398
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• 2007

Case-based reasoning (CBR) is one of the most popular prediction techniques for medical diagnosis because it is easy to apply, has no possibility of overfitting, and provides a good explanation for the output. However, it has a critical limitation - its prediction performance is generally lower than other artificial intelligence techniques like artificial neural networks (ANNs). In order to obtain accurate results from CBR, effective retrieval and matching of useful prior cases for the problem is essential, but it is still a controversial issue to design a good matching and retrieval mechanism for CBR systems. In this study, we propose a novel approach to enhance the prediction performance of CBR. Our suggestion is the simultaneous optimization of feature weights, instance selection, and the number of neighbors that combine using genetic algorithms (GAs). Our model improves the prediction performance in three ways - (1) measuring similarity between cases more accurately by considering relative importance of each feature, (2) eliminating redundant or erroneous reference cases, and (3) combining several similar cases represent significant patterns. To validate the usefulness of our model, this study applied it to a real-world case for evaluating cytological features derived directly from a digital scan of breast fine needle aspirate (FNA) slides. Experimental results showed that the prediction accuracy of conventional CBR may be improved significantly by using our model. We also found that our proposed model outperformed all the other optimized models for CBR using GA.

• Journal of Electrical Engineering and Technology
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• 제10권5호
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• pp.1921-1929
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• 2015

The smart substation is the heart of a transmission system, which is particularly emphasized as the most significant composition of smart grids in China. In order to assess the functionality performance of substation technologies, this paper presents methods used to identify the most promising solutions for smart substation design and to evaluate the technical levels of available technologies. The multi-index optimization model is presented to address the issue of smart substation planning. A mathematical model of the planning decision problem is established with multiple objectives consisting of economic, reliability, and green key indices, and many kinds of concerns including physical and environmentally friendly operations are formulated as a set of constraints. With respect to the assessment of the technical level regarding integration of advanced technologies into a substation, a modified grey whitenization weight function is adopted to structure a novel grey clustering method. The proposed grey clustering approach is used to overcome the difficulty of insufficient quantitative assessment capacity for traditional methods. The evaluation of technical effects provides the classification definition for the development phase and the maturity level of the smart substation. The effectiveness of the proposed approaches in planning decision-making and evaluation of construction efforts is demonstrated with case studies involving the actual smart substation projects of Wenchongkou substation in China Southern Power Grid (CSG) and Mengzi substation in State Grid Corporation of China (SGCC).

• 지능정보연구
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• 제6권2호
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• pp.1-14
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• 2000

컨테이너 터미널에서의 선석 및 크레인 일정계획은 일정 기간 동안 입항 예정인 선박들을 대상으로 선석을 배정하고 접안 시기와 기간을 결정하며, 또한 각 선박별로 컨테이너를 싣고 내릴 크레인을 배정하되 각 크레인의 서비스 시작과 완료시간까지 지정하는 전 과정을 포함한다. 이 문제는 본적으로 서로 시간적 공간적으로 복잡한 제약 관계에 있는 여러 선석들과 크레인들을 충돌 없이 각 선박에 할당하여야 하는 제약조건 만족 문제인 동시에, 각 선박의 희망 입출항 시간을 최대한 존중하면서 터미널의 운영비용을 최소화할 수 있는 계획안을 도출해야 하는 최적화 문제이기도 하 다. 본 논문에서는 이 문제의 해결을 위해 제약만족 탐색기법을 동원하여 먼저 제약조건을 만족하는 해를 찾은 뒤, 제약조건을 만족하는 범위 내에서 보다 최적의 해를 유도해 내기 위해 휴리스틱 교정 기법을 제약만족 탐색기법의 틀 내에서 반복적으로 적용하는 방안을 제시하고 있다. 실제 부산 신선대 컨테이너 터미널의 데이터를 이용한 실험 결과 현장 전문가가 만족할 만한 수준의 일정 계획을 신속하게 수립할 수 있음을 확인하였다.