• Macromolecular Research
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• 제15권7호
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• pp.682-687
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• 2007

The equation of state developed herein is predicated on a hard-sphere reference with perturbations introduced via a potential function to account for electrostatic forces and for attraction between protein particles. During this process, the generalized Lennard-Jones (GLJ) pair potential function is employed. The GLJ pair potential function is employed to represent the protein-protein interaction in two-protein systems. Via the use of the relation between the equation of state and the chemical potential, the phase behavior in the aqueous two-protein system can be estimated. The partition coefficients can be obtained via these processes. The calculated values of the coefficients agree fairly well with the experimental data in the given pH and ionic strength range, with no additional adjustable model parameters.

• Bulletin of the Korean Chemical Society
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• 제20권11호
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• pp.1288-1294
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• 1999

We show that Shaw's optimized nonlocal model potential (OMP) in combination with the perturbative hyper-netted-chain equation for pair correlation functions can be successfully applied to predict pair structures of compressed and expanded liquid rubidium. For compressed rubidium, it is possible to apply the OMP to a state for which the model radius is even close to the Wigner-Seitz radius. In addition, our results are parallel to those from Chihara and Kahl's quantal hypernetted-chain equation in that it supports the uniform compression model up to 6.1 GPa. Calculation also shows that the pair structure is relatively insensitive to the choice of the exchange-correlation function for the electron liquid. Discussions are also given for compressed and expanded cesium.

• Macromolecular Research
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• 제17권10호
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• pp.763-769
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• 2009

A chromatographic method is used to measure interactions between dissimilar proteins in aqueous electrolyte solutions as a function of ionic strength, salt type, and pH. One protein is immobilized on the surface of the stationary phase, and the other is dissolved in electrolyte solution conditions flowing over that surface. The relative retention of proteins reflects the mean interactions between immobile and mobile proteins. The osmotic cross second virial coefficient calculated by assuming a proposed potential function shows that the interactions of unfavorable proteins depend on solution conditions, and the proposed model shows good agreement with the experimental data of the given systems.

• 한국생산제조학회지
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• 제7권1호
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• pp.9-21
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• 1998

This paper a new solution approach to moving obstacle avoidance problem of a mobile robot. A new concept avoidability measure (AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function (VDF), is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF ,an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1998년도 춘계학술대회 논문집
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• pp.88-93
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• 1998

This paper presents a new solution approach to moving obstacle avoidance problem for a mobile robot. A new concept avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terns of the VDF, an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived form the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• 한국컴퓨터정보학회논문지
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• 제19권8호
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• pp.27-34
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• 2014

이 논문에서는 hybrid projection 함수와 rank order 필터를 이용하여 눈동자를 검출하는 방법을 제안한다. 눈썹을 눈동자로 검출하는 오류를 줄이기 위하여, hybrid projection 함수를 이용하여 얼굴 영역에서 눈썹을 검출하고 눈썹이 포함되지 않도록 눈 영역을 설정한다. 눈 영역에서 rank order 필터를 사용하여 눈동자 후보점을 찾고 위치를 보정한다. 두 눈동자 후보점을 기하학적인 제약조건을 기반으로 쌍으로 묶고 각 쌍의 두 눈에 대한 유사도를 정합을 이용하여 측정하여가장작은값을 갖는 쌍을 최종눈동자로 결정한다. BioID 얼굴데이터베이스의 얼굴 영상 700개에 대한 실험 결과 92.4%의 검출율을 얻었으며 기존 방법보다 약 21.5% 개선된 결과를 얻었다.

• 제어로봇시스템학회논문지
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• 제3권2호
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• pp.169-178
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• 1997

This paper presents a new solution approach to moving obstacle avoidance problem of a robot. A new concept, avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of three state variables: the distance from the obstacle to the robot, outward speed of the obstacle relative to the robot, and outward speed of the robot relative to the obstacle. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid a moving obstacle in real time. Since the algorithm considers the mobility of the obstacle and robot as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• 한국정보통신학회논문지
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• 제16권7호
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• pp.1383-1390
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• 2012

이 논문에서는 얼굴 영상에 대해 rank order 필터와 화소 값 차이를 사용하여 강인하게 눈동자를 찾는 방법을 제안한다. 개선된 rank order 필터를 사용하여 얼굴 영상에서 눈동자 후보점을 찾는다. 눈동자와 흰자위의 경계에서 화소값 변화가 크다는 사실을 이용하여 눈썹 등 눈동자가 아닌 위치에 있는 눈동자 후보점들을 제거한다. 눈동자 후보점을 두 점간의 거리와 각도를 이용하여 쌍으로 묶고 눈동자 영역에서의 밝기 정보를 이용한 적합도 함수를 적용하여 최종 눈동자를 추출한다. BioID 얼굴 데이터베이스에 있는 얼굴 영상 400개에 대한 실험 결과 90.25%의 눈동자 추출율을 보여 기존 방법보다 4% 개선된 결과를 얻었으며, 특히 안경을 착용한 얼굴 영상의 경우 기존 방법보다 약 12% 개선된 결과를 얻었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권3호
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• pp.522-538
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• 2013

Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

• KSBB Journal
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• 제26권2호
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• pp.131-138
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• 2011

Some computational approaches are needed for clarifying RNAi sequences, because it takes much time and endeavor that almost of RNAi sequences are verified by experimental data. Incorrectness of RNAi mechanism and other unaware factors in organism system are frequently faced with questions regarding potential use of RNAi as therapeutic applications. Our massive parallelized pair alignment scoring between dsRNA in Genebank and expressed sequence tags (ESTs) in Caenorhabditis elegans Genome Sequencing Projects revealed that this provides a useful tool for the prediction of RNAi induced cosuppression details for practical use. This pair alignment scoring method using high performance computing exhibited some possibility that numerous unwanted gene silencing and cosuppression exist even at high matching scores each other. The classifying the relative higher matching score of them based on GO (Gene Ontology) system could present mapping dsRNA of C. elegans and functional roles in an applied system. Our prediction also exhibited that more than 78% of the predicted co-suppressible genes are located in the ribosomal spot of C. elegans.