• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권4호
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• pp.298-306
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• 2013

Recent years have witnessed a growing interest in the fields of video surveillance and mobile object tracking. This paper proposes a mobile object tracking algorithm. First, several parameters such as object window, object area, and expansion-contraction (E-C) parameter are defined. Then, a modified E-C algorithm for multiple-object tracking is presented. The proposed algorithm tracks moving objects by expansion and contraction of the object window. In addition, it includes methods for updating the background image and avoiding occlusion of the target image. The validity of the proposed algorithm is verified experimentally. For example, the first scenario traces the path of two people walking in opposite directions in a hallway, whereas the second one is conducted to track three people in a group of four walkers.

• 한국정밀공학회지
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• 제26권3호
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• pp.129-136
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• 2009

The estimation of muscle force is important to understand the roles of the muscles. The static optimization method can be used to figure out the individual muscle forces. However, muscle forces during the movement including muscle co-contraction cannot be considered by the static optimization. In this study, a hybrid static optimization method was introduced to find the well-matched muscle forces with EMG signals under muscle co-contraction conditions. To validate the developed algorithm, the 3D motion analysis and its corresponding inverse dynamics using the musculoskeletal modeling software (SIMM) were performed on heel-rise movements. Results showed that the developed algorithm could estimate the acceptable muscle forces during heel-rise movement. These results imply that a hybrid numerical approach is very useful to obtain the reasonable muscle forces under muscle co-contraction conditions.

• Nonlinear Functional Analysis and Applications
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• 제28권3호
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• pp.623-646
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• 2023

In this article, we introduce the hyperbolic space version of a faster iterative algorithm. The proposed iterative algorithm is used to approximate the common fixed point of three multi-valued almost contraction mappings and three multi-valued mappings satisfying condition (E) in hyperbolic spaces. The concepts weak w²-stability involving three multi-valued almost contraction mappings are considered. Several strong and △-convergence theorems of the suggested algorithm are proved in hyperbolic spaces. We provide an example to compare the performance of the proposed method with some well-known methods in the literature.

• 한국정밀공학회지
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• 제28권6호
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• pp.670-677
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• 2011

This study is to estimate the joint torques without torque sensor using the EMG (Electromyogram) signal of agonist/antagonist muscle with Neural Network Back Propagation Algorithm during the elbow motion. Command Signal can be guessed by EMG signal. But it cannot calculate the joint torque. There are many kinds of field utilizing Back Propagation Learning Method. It is generally used as a virtual sensor estimated physical information in the system functioning through the sensor. In this study applied the algorithm to obtain the virtual senor values estimated joint torque. During various elbow movement (Biceps isometric contraction, Biceps/Triceps Concentric Contraction (isotonic), Biceps/Triceps Concentric Contraction/Eccentric Contraction (isokinetic)), exact joint torque was measured by KINCOM equipment. It is input to the (BP)algorithm with EMG signal simultaneously and have trained in a variety of situations. As a result, Only using the EMG sensor, this study distinguished a variety of elbow motion and verified a virtual torque value which is approximately(about 90%) the same as joint torque measured by KINCOM equipment.

• 대한수학회보
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• 제49권4호
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• pp.749-759
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• 2012

A globally convergent algorithm for solving equilibrium problems is proposed. The algorithm is based on a proximal point algorithm (shortly (PPA)) with a positive definite matrix M which is not necessarily symmetric. The proximal function in existing (PPA) usually is the gradient of a quadratic function, namely, ${\nabla}({\parallel}x{\parallel}^2_M)$. This leads to a proximal point-type algorithm. We first solve pseudomonotone equilibrium problems without Lipschitzian assumption and prove the convergence of algorithms. Next, we couple this technique with the Banach contraction method for multivalued variational inequalities. Finally some computational results are given.

• 전기전자학회논문지
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• 제25권1호
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• pp.212-217
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• 2021

Premature contraction arrhythmia is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Most of arrhythmia clasification methods have been developed with the primary objective of the high detection performance without taking into account the computational complexity. Also, personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Therefore it is necessary to design efficient method that classifies arrhythmia by analyzing the persons's physical condition and decreases computational cost by accurately detecting minimal feature point based on only QRS features. We propose method for personalized specific classification of premature contraction arrhythmia based on QRS features in smart healthcare environments. For this purpose, we detected R wave through the preprocessing method and SOM and selected abnormal signal sets.. Also, we developed algorithm to classify premature contraction arrhythmia using QRS pattern, RR interval, threshold for amplitude of R wave. The performance of R wave detection, Premature ventricular contraction classification is evaluated by using of MIT-BIH arrhythmia database that included over 30 PVC(Premature Ventricular Contraction) and PAC(Premature Atrial Contraction). The achieved scores indicate the average of 98.24% in R wave detection and the rate of 97.31% in Premature ventricular contraction classification.

• 한국CDE학회논문집
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• 제17권2호
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• pp.132-139
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• 2012

Presented in the paper is a procedure to extract simplified triangular mesh from a height map (terrain data). The proposed algorithm works directly on a height map that extracts a simplified triangular mesh. For the simplification, the paper employs an iterative method of edge contractions. To determine an edge to be contracted, the contraction cost of an edge is evaluated through the QEM method. Normally, an edge contraction will remove two triangles sharing the edge. Although the edge contraction can be implemented easily on a triangular mesh, it is not viable to implement the operation on a height map due to the irregular topology. To handle the irregular topology during the simplification procedure, a new algorithm is introduced.

• 한국컴퓨터정보학회논문지
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• 제22권5호
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• pp.65-72
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• 2017

Premature Ventricular Contraction(PVC) arrhythmia is most common abnormal-heart rhythm that may increase mortal risk of a cardiac patient. Thus, it is very important issue to identify the specular portraits of PVC pattern especially from the patient. In this paper, we propose a new method to extract the characteristics of PVC pattern by applying K-means machine learning algorithm on Heart Rate Variability depicted in Poinecare plot. For the quantitative analysis to distinguish the trend of cluster patterns between normal sinus rhythm and PVC beat, the Euclidean distance measure was sought between the clusters. Experimental simulations on MIT-BIH arrhythmia database draw the fact that the distance measure on the cluster is valid for differentiating the pattern-traits of PVC beats. Therefore, we proposed a method that can offer the simple remedy to identify the attributes of PVC beats in terms of K-means clusters especially in the long-period Electrocardiogram(ECG).

• 재활복지공학회논문지
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• 제1권1호
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• pp.13-19
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• 2007

본 논문에서는 복압성요실금의 병적 진행 정도를 정량적으로 진단하기 위한 진단 알고리즘을 제안하였다. 생체신호 측정 시스템을 개발하여 복압성요실금 환자로부터 골반저근의 수축압력을 측정하였고, 데이터를 분석하여 진단 파라미터를 추출하였다. 진단 파라미터의 통계적 평가를 수행하여 상관성이 높은 순서로 진단 파라미터를 분류하였으며, 상관성이 높게 나타난 파라미터로부터 Y/N 테이블을 제작하여 요실금의 정도를 정량적으로 진단할 수 있는 진단 알고리즘을 구현하였다.

• 전자공학회논문지CI
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• 제41권5호
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• pp.51-58
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• 2004

본 논문에서는 3D 모델의 체적 보존을 고려하는 메쉬 간략화 알고리듬을 제안하였다. 일반적으로 다른 대부분의 메쉬 간략화 알고리듬에서는 거리 기준을 사용한다. 거리는 기하학적인 오차를 측정하는 매우 효율적인 기준이기는 하지만 거리 기준만을 적용할 경우 원래 모델과 간략화된 모델 간에 체적 변화가 발생한다. 본 논문에서는 원래 모델의 간략화 과정 중에도 체적의 변화가 없는 메쉬 간략화 알고리듬을 제안한다. 본 알고리듬에서는 에지 하나를 줄이면서 체적의 변화가 일어나지 않는 정점 하나를 찾는 방식을 사용한다. 시뮬레이션을 통하여 제안하는 알고리듬이 비록 계산 시간은 좀 더 걸리지만 체적의 변화가 거의 없다는 장점을 가진 것을 확인하였다.