• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.401-401
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• 2000

A mobile manipulator-a serial connection of a mobile robot and a task robot is redundant by itself. Using its redundant freedom, a mobile manipulator can move in various modes, and perform dexterous tasks. An interesting question,

• 한국운동역학회지
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• 제24권3호
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• pp.229-238
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• 2014

This study comparatively analyzed the speed and segment coordination characteristics of Taekwondo hand techniques, while different attention focusing strategies were utilized. Ten elite Taekwondo poomsae athletes participated, and three different strategies (no focus, target focus, body focus) were utilized in random order. The hand velocity and upper body segment coordination characteristics were analyzed, with the following results. First, the maximum magnitudes of the hand velocity differed between the focus conditions for the Araenaereomakgi and Momtongjireugi techniques. Second, the angular velocity and kinetic energy transfer patterns of the segments differed between the focus conditions, and in the case of the body focus condition, the movement was more correct according to the theory. Third, the shoulder and elbow joint coordination patterns differed between the focus conditions, with more efficient movement shown with the body focus condition. In conclusion, we confirmed the potential of effectively using an attention focusing strategy in a taekwondo teaching situation. However, the effect on the movement coordination and results of the movement could be changed by a difference in the cue provided or the type of the task. In addition, depending on the task, the attention focusing strategy could affect the efficiency of the movement. Therefore, coaches and masters of Taekwondo will have to constitute determine the appropriate attention focusing cues based on the task.

• 한국정보통신학회논문지
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• 제9권6호
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• pp.1395-1401
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• 2005

이동매니퓰레이터란 이동로봇과 작업로봇을 직렬로 결합하여 이동능력과 작업능력을 가지는 로봇이다. 이동매니퓰레이터의 중요한 특징중의 하나는 잉여의 자유도를 가진다는 것이다. 이를 이용하여 이동매니퓰레이터는 여러 가지 모드로 이동이 가능하고 다양한 작업을 수행할 수 있다. 이동매니퓰레이터는 고정베이스 구조의 로봇에 비해 넓은 작업공간과 특이자세 회피 및 장애물 회피에서 더 좋은 성능을 가진다. 두 대의 로봇이 협동하여 작업을 수행할 때 주어진 작업공간에서 여유자유도를 가지고 있는 이점을 이용하여 작업의 성능을 향상시킬 수 있다. 본 논문은 이동매니퓰레이터가 수행되어질 작업을 세분화 시키고 로봇의 작업 성능 지수를 사용하여 로봇이 최적자세로 작업을 수행할 수 있는 연구를 하였다. 제안된 알고리즘을 검증하기위해 이동매니퓰레이터를 제작하였고, 실험에 사용한 이동매니퓰레이터 PURL-II는 3자유도를 가지는 이동로봇과 5자유도를 가지는 작업로봇으로 구성되어 있다.

• 대한인간공학회지
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• 제5권1호
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• pp.11-18
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• 1986

The object of this research is to develop an interactive computerized graphic program for graphic output of velocity, acceleration and motion range of body task reference point. Human motions can be reproduced by scanning (rate = 1/60) the vidicon image, at same time, C.O.G of body segment group, and the results are stored in an Apple II P.C. memory. The results of this study can he exteneded to simulation and reproduction of human motions for optimal task design.

• 한국대기환경학회지
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• 제34권5호
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• pp.735-747
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• 2018

Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we propose to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collect a new video dataset and propose a procedure to calculate refined rainfall depth from the original meteorological data. We also propose to utilize the differential frame as well as the optical flow image for better recognition of rainfall depth. Under the Temporal Segment Networks framework, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. The final model is able to achieve high performance in the single-location low sensitivity classification task and reasonable accuracy in the higher sensitivity classification task for both the single-location and the multi-location case.

• 한국운동역학회지
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• 제28권4호
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• pp.213-218
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• 2018

Objective: The purpose of this study was to examine the effect of the core muscle strength enhancement of the elderly on 8 weeks training using the core exercise equipment for the elderly on the ability to control the whole-body center of mass in posture stabilization. Method: 16 females (10 exercise group, 6 control group) participated in this study. Exercise group took part in the core strength training program for 8 weeks with total of 16 repetitions (2 repetitions per week) using a training device. External perturbation during standing as pulling force applied at the pelvic level in the anterior direction was provided to the subject. In a UCM model, the controller selects within the space of elemental variables a subspace (a manifold, UCM) corresponding to a value of a performance variable that needs to be stabilized. In the present study, we were interested in how movements of the individual segment center of mass (elemental variables) affect the whole-body center of mass (the performance variable) during balance control. Results: At the variance of task-irrelevant space, there was significant $test^*$ group interactions ($F_{1,16}=7.482$, p<.05). However, there were no significant main effect of the test ($F_{1,16}=.899$, p>.05) and group ($F_{1,16}=1.039$, p>.05). At the variance of task-relevant space, there was significant $test^*$ group interactions ($F_{1,16}=7.382$, p<.05). However, there were no significant main effect of the test ($F_{1,16}=.754$, p>.05) and group ($F_{1,16}=1.106$, p>.05). Conclusion: The results of this study showed that the 8 weeks training through the core training equipment for the elderly showed a significant decrease in the $Vcm_{TIR}$ and $Vcm_{TR}$. This result indicates that the core strength training affects the trunk stiffness control strategy to maintain balance in the standing position by minimizing total variability of individual segment CMs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.16-37
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• 2022

Accurate liver segment segmentation based on radiological images is indispensable for the preoperative analysis of liver tumor resection surgery. However, most of the existing segmentation methods are not feasible to be used directly for this task due to the challenge of exact edge prediction with some tiny and slender vessels as its clinical segmentation criterion. To address this problem, we propose a novel deep learning based segmentation model, called Boundary-Aware Dual Attention Liver Segment Segmentation Model (BADA). This model can improve the segmentation accuracy of liver segments with enhancing the edges including the vessels serving as segment boundaries. In our model, the dual gated attention is proposed, which composes of a spatial attention module and a semantic attention module. The spatial attention module enhances the weights of key edge regions by concerning about the salient intensity changes, while the semantic attention amplifies the contribution of filters that can extract more discriminative feature information by weighting the significant convolution channels. Simultaneously, we build a dataset of liver segments including 59 clinic cases with dynamically contrast enhanced MRI(Magnetic Resonance Imaging) of portal vein stage, which annotated by several professional radiologists. Comparing with several state-of-the-art methods and baseline segmentation methods, we achieve the best results on this clinic liver segment segmentation dataset, where Mean Dice, Mean Sensitivity and Mean Positive Predicted Value reach 89.01%, 87.71% and 90.67%, respectively.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 추계학술발표대회
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• pp.300-302
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• 2022

Palm vein identification has attracted attention due to its distinct characteristics and excellent recognition accuracy. However, many contactless palm vein identification systems suffer from the issue of having low-quality palm images, resulting in degradation of recognition accuracy. This paper proposes the use of U-Net architecture to correctly segment the vascular blood vessel from palm images. Attention gate mechanism and residual block are also utilized to effectively learn the crucial features of a specific segmentation task. The experiments were conducted on CASIA dataset. Hessian-based Jerman filtering method is applied to label the palm vein patterns from the original images, then the network is trained to segment the palm vein features from the background noise. The proposed method has obtained 96.24 IoU coefficient and 98.09 dice coefficient.

• 대한의용생체공학회:의공학회지
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• 제37권1호
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• pp.15-20
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• 2016

Essential tremor is a neurological disorder with a tremor of the arms and hands. It is well known that essential tremor is characterized by the postural tremor and the action tremor. There has been no report on the quantitative difference in the characteristics of two tremor types. The purpose of this study was to investigate the possible difference in tremor characteristics of postural and action tremors. Seventeen patients with essential tremor ($68.9{\pm}7.9years$, 7 men, 10 women) participated in this study. Patients performed the tasks of postural maintenance (arms outstretched) and daily actions (spiral drawing). Three-axes (pitch, roll and yaw) gyro sensors were attached on index finger, back of hand and forearm, from which the segment and the joint angular velocities were calculated. Outcome measure was the tremor amplitude defined as the root-mean-square mean of the vector-sum angular velocity at segments and joints. Two-way ANOVA showed that task and joint had main factor on the tremor amplitude (p < 0.05). Post-hoc analysis revealed that tremor amplitude at the metacarpo-phalangeal joint was not affected by task (p > 0.05). However, tremor amplitude at the wrist joint differed among the tasks (p < 0.05), and it was greater in the action tasks than in postural task. Tremor was greater at finger segments than at hand and forearm and it increased in action tasks. The results of this study would be helpful for the understanding and task-specific treatments of the essential tremor.

• 한국유기농업학회지
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• 제15권3호
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• pp.237-256
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• 2007

Organic farming is promoted financially in the Republic of Korea since 2000. The, entire segment shows a very dynamic development since that time. Now, a large bouquet of measures are offered which target the promotion of organic farming. This article presents a study about the Task and Valuation on farm animal welfare for Organic Livestock. Among the supports are grants for organically managed livestock farm, investment incentives, the promotion of organic livestock husbandry, the promotion of producer co-operatives, the development of farm animal right index for animal health and animal welfare, publicity measures and measures to raise consumer awareness as well as the support of training, extension and research in the field organic livestock farming. Government must ensure that necessary incentives and sanctions are in place to maintain and improve animal welfare standards and they must be delivered appropriately. Animal welfare legislation provides essential protection for economy, environment, animals and society as a whole, must be properly observed.