• Multiscale and Multiphysics Mechanics
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• 제1권4호
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• pp.327-340
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• 2016

Poly(${\epsilon}$-caprolactone) (PCL) diol, with good biodegradation and biocompatibility, is one of the widely used soft segments (SSs) in composing bio-polyester-urethanes (Bio-PUs), which show great potential in both biomedical and tissue engineering applications. Properties of Bio-PUs are tunable by combining SS monomers with different molecular weights, structures, modifications, and ratio of components. Although numbers of research have reported many Bio-PUs properties, few studies have been done at the molecular scale. In this study, we use molecular dynamic (MD) simulation to construct atomistic models for two commonly used PCL diol SSs with different molecular weights 1247.58 Da and 1932.42 Da. We compare the simulation results by using two widely used classical force fields for organic molecules: Consistent Valence Force Field (CVFF) and CHARMM General Force Field (CGenFF), and discuss the validity and accuracy. Melt density, volume, polymer conformations, transition temperature, and mechanical properties of PCL diols are calculated and compared with experiments. Our results show that both force fields provide accurate predictions on the properties of PCL diol system at the molecular scale and could help the design of future Bio-PUs.

• 한국음향학회지
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• 제20권6호
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• pp.51-56
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• 2001

최근 잡음이 심한 환경에서 음성인식을 신뢰성있게 하기 위하여 입모양의 움직임과 음성을 같이 사용하는 방법이 활발히 연구되고 있다 본 논문에서도 이러한 목적으로 영상언어인식기와 음성인식기의 결과에 각각 가중치를 주어 결합하는 방법을 제안한다. 특히 가중치를 입력음성의 잡음의 정도에 따라 자동적으로 결정하는 방법을 제안한다. 가중치의 결정을 위하여 입력샘플간의 상관도와 LPC분석의 잔여 오차를 이용한다. 모의실험 결과, 이런 방식으로 결합된 인식기는 잡음이 심한 환경에서도 약 83%의 인식성능을 보이고 있다.

• ETRI Journal
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• 제42권6호
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• pp.886-898
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• 2020

Unusual data patterns or outliers can be generated because of human errors, incorrect measurements, or malicious activities. Detecting outliers is a difficult task that requires complex ensembles. An ideal outlier detection ensemble should consider the strengths of individual base detectors while carefully combining their outputs to create a strong overall ensemble and achieve unbiased accuracy with minimal variance. Selecting and combining the outputs of dissimilar base learners is a challenging task. This paper proposes a model that utilizes heterogeneous base learners. It adaptively boosts the outcomes of preceding learners in the first phase by assigning weights and identifying high-performing learners based on their local domains, and then carefully fuses their outcomes in the second phase to improve overall accuracy. Experimental results from 10 benchmark datasets are used to train and test the proposed model. To investigate its accuracy in terms of separating outliers from inliers, the proposed model is tested and evaluated using accuracy metrics. The analyzed data are presented as crosstabs and percentages, followed by a descriptive method for synthesis and interpretation.

• 한국수자원학회논문집
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• 제48권9호
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• pp.757-768
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• 2015

최근 기후변화는 짧은 시간의 지역적인 집중호우와 예상치 못한 폭우에 영향을 미치고 이는 생명과 재산의 손실에 영향을 준다. 본 연구에서는 침수위험도를 결정하기 위한 방법으로 산술평균방법, 가중평균방법, 주성분 분석방법을 이용하여 침수위험도에 따른 순위를 결정하였다. 재해연보 및 도시계획 현황에서 선택한 인자들에 대한 표준화를 통해 단위를 통일시켰으며 표준화를 통한 산술평균방법, 상관관계분석을 통한 가중평균방법, 상관도가 높은 인자들을 묶어 분석한 주성분 분석방법을 통해 침수위험도를 결정하고 그 순위를 나타내었다. 본 연구에서 사용된 산술평균방법의 경우 간단하기는 하지만 각각의 인자들이 동일한 가중치를 가지는 문제점이 있고 가중평균 방법의 경우 각각의 인자들이 다른 가중치를 갖기는 하지만 많은 변수들 때문에 변수들 간의 상관관계가 복잡해지는 문제점이 있다. 이러한 문제점을 극복하기 위해 주성분 분석방법을 사용하였으며 각 지역의 수방능력 및 재해위험을 고려한 침수위험도를 결정하였다.

• 품질경영학회지
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• 제50권4호
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• pp.793-810
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• 2022

Purpose: As improving the search performance of aviation security equipment is considered essential, this study proposes the need for research on how to find an optimized test sequence that can reduce test time and operator power during the search function test of explosive detection systems. We derive the weights and work difficulty adjustment factor required to find the optimized test order. Methods: First, after setting the test factors, the time of each test and the difficulty scale determined by the worker who performed the test directly were used to derive weights. Second, the work difficulty adjustment coefficient was determined by combining the basic weight adjustment factor and corresponding to the body part used by the test using objective rating. Then the final standard time was derived by calculating the additional weights for the changeability of the test factors. Results: The order in which the final standard time is minimized when 50 tests are performed was defined as the optimized order. 50 tests should be conducted without duplication and the optimal order of tests was obtained when compared to previously numbered tests. As a result of minimizing the total standard time by using Excel's solver parameters, it was reduced by 379.14 seconds, about 6.32 minutes. Conclusion: We tried to express it in mathematical formulas to propose a method for setting an optimized test sequence even when testing is performed on other aviation security equipment. As a result, the optimal test order was derived from the operator's point of view, and it was demonstrated by minimizing the total standard time.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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• pp.292-293
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• 2008

In this paper, we propose a face hallucination method based on example-learning. The traditional approach based on example-learning requires alignment of face images. In the proposed method, facial images are segmented into patches and the weights are computed to represent input low resolution facial images into weighted sum of low resolution example images. High resolution facial images are hallucinated by combining the weight vectors with the corresponding high resolution patches in the training set. Experimental results show that the proposed method produces more reliable results of face hallucination than the ones by the traditional approach based on example-learning.

• Journal of Communications and Networks
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• 제7권3호
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• pp.258-262
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• 2005

An adaptive beamforming system based on code filtering and differential correlation approaches is proposed. The differential correlation method was originally proposed for time delay estimation of direct sequence code division multiple access (DS-CDMA) systems under near-far ratio conditions and the code filtering correlation algorithm, on the other hand, was proposed for array response estimation in DS-CDMA systems under perfect power control. In this paper, by combining differential correlation concept with the code filtering beamforming technology, an accurate estimate of the beam forming weights and an enhanced performance of DS-CDMA systems under sever near-far ratio conditions is achieved. The system performance in terms of beam pattern and bit-error-rate (HER) shows that the proposed adaptive beamformer outperforms the conventional code filtering correlation technique.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.816-821
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• 2003

Researchers have utilized artificial evolution techniques and learning techniques for studying the interactions between learning and evolution. Adaptation in dynamic environments gains a significant advantage by combining evolution and learning. We propose an on-line, realtime evolutionary learning mechanism to determine the structure and the synaptic weights of a neural network controller for mobile robot navigations. We support our method, based on (1+1) evolutionary strategy which produces changes during the lifetime of an individual to increase the adaptability of the individual itself, with a set of experiments on evolutionary neural controller for physical robots behaviors. We investigate the effects of learning in evolutionary process by comparing the performance of the proposed realtime evolutionary learning method with that of evolutionary method only. Also, we investigate an interactive evolutionary algorithm to overcome the difficulties in evaluating complicated tasks.

• International Journal of Advanced Culture Technology
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• 제6권3호
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• pp.142-150
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• 2018

This paper describes the algorithm that lowers the dimension, maintains the object recognition and significantly reduces the eigenspace configuration time by combining the edge orientation histogram and principle component analysis. By using the detected object region as a recognition input image, in this paper the object recognition method combined with principle component analysis and the multi-layer network which is one of the intelligent classification was suggested and its performance was evaluated. As a pre-processing algorithm of input object image, this method computes the eigenspace through principle component analysis and expresses the training images with it as a fundamental vector. Each image takes the set of weights for the fundamental vector as a feature vector and it reduces the dimension of image at the same time, and then the object recognition is performed by inputting the multi-layer neural network.

• 환경영향평가
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• 제6권1호
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• pp.93-103
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• 1997

LHR(Landfill Site Hazard Ranking Model) was developed for ranking the relative hazard of landfill sites by using the method of value-structured approach. LHR consists of combining a multiattribute decision-making method with a Qualitative risk assessment approach. A pairwise com parisian method was applied to determine weights of landfill site factors related. To determine the hazard of landfill site, hydrogeological factors, waste characteristics factors and receptors factors were evaluated by LHR. LHR can help decision-makers prioritization of remediation of landfill sites through the relatively convenient and concise evaluation method of landfill site features related. LHR focuses mainly on pathways of groundwater and surfacewater for evaluating landfill hazard to receptors including humans. To validiate the applicability of LHR, Nanjido Landfill site, Metropolitan Landfill site, and Hwasung Landfill site were evaluated.