• Health Policy and Management
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• v.6 no.1
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• pp.85-109
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• 1996

Telemedicine can increase accessibility to advance medical technology at the university hospital for community residents living in a remote area. This paper focused on the economic evaluation of telemedicine to identify important factors influencing costs and benefits and to understand how these factors can be changed to improve economic performance of the telemedicine. When the telemedicine project currently operating in Korea was evaluated based on the traditional cost-benefit analysis, the results showed a heavy net loss wiht a B/C ration of 0.56. As several values were added to the analysis based on the Information Economics approach, B/C ratios steadly increased. When the saving of medical expenses from the early detection of diseases was taken into a consideration, the ration exceeded the break-even point. >From the sensitivity analysis, a number of patients and the cost for equipment and communication were found to be the key factors for influencing economic performance of telemedicine.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.10
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• pp.441-446
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• 2003

The chemical mechanical polishing (CMP) process is now widely employed in the ultra large scale integrated (ULSI) semiconductor fabrication. Especially, shallow trench isolation (STI) has become a key isolation scheme for sub-0.13/0.10${\mu}{\textrm}{m}$ CMOS technology. The most important issues of STI-CMP is to decrease the various defects such as nitride residue, dishing, and tom oxide. To solve these problems, in this paper, we studied the planarization characteristics using slurry additive with the high selectivity between $SiO_2$ and $Si_3$$N_4$ films for the purpose of process simplification and in-situ end point detection. As our experimental results, it was possible to achieve a global planarization and STI-CMP process could be dramatically simplified. Also, we estimated the reliability through the repeated tests with the optimized process conditions in order to identify the reproducibility of STI-CMP process.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1999.05a
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• pp.501-504
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• 1999

In the shallow trench isolation(STI) chemical mechanical polishing(CMP) process, the key issues are the optimized thickness control within- wafer-non-uniformity, and the possible defects such as nitride residue and pad oxide damage. These defects after STI CMP process were discussed to accomplish its optimum process condition. To understand its optimum process condition, overall STI related processes including reverse moat etch, trench etch, STI filling and STI CMP were discussed. It is represented that the nitride residue can be occurred in the condition of high post CMP thickness and low trench depth. In addition there are remaining oxide on the moat surface after reverse moat etch. It means that reverse moat etching process can be the main source of nitride residue. Pad oxide damage can be caused by over-polishing and high trench depth.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.285-286
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• 2009

본 논문은 실시간 이미지 매칭을 위한 빠른 BLoG 특징점 검출방법을 제안하고 이미지 크기, 회전변화등 다양한 실험을 통하여 기존 방법과 속도와 연산량 그리고 검출 성능에 대하여 비교하고 앞으로 나아갈 방향에 대하여 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.604-606
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• 2024

컴퓨터 비전 응용은 우리 생활에서 중요한 역할을 한다. 현재, 대규모 모델의 등장으로 딥 러닝의 훈련 및 운행 비용이 급격히 상승하고 있다. 자원이 제한된 환경에서는 일부 AI 프로그램을 실행할 수 없게 되므로, 경량화 연구가 필요하다. YOLOv8 은 현재 주요 목표 검출 모델 중 하나이며, 본 논문은 다중 스케일 Ghost 컨볼루션 모듈을 사용하여 구축된 새로운 YOLOv8-pose-msg 키포인트 검출 모델을 제안한다. 다양한 사양에서 새 모델의 매개변수 양은 최소 34% 감소할 수 있으며, 최대 59%까지 감소할 수 있다. 종합적인 검출 성능은 비교적 대규모 데이터셋에서 원래의 수준을 유지할 수 있으며, 소규모 데이터셋에서의 키포인트 검출은 30% 이상 증가할 수 있다. 동시에 최대 25%의 훈련 및 추론 시간을 절약할 수 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.160-174
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• 2023

LiDAR plays a key role in autonomous vehicles, and to improve its visibility, it is necessary to improve its performance and the detection objects. Accordingly, this study proposes a shape for traffic safety signs that is advantageous for self-driving vehicles to recognize. Improvement plans are also proposed using a shape-recognition algorithm based on point cloud data collected through LiDAR sensors. For the experiment, a DBSCAN-based road-sign recognition and classification algorithm, which is commonly used in point cloud research, was developed, and a 32ch LiDAR was used in an actual road environment to conduct recognition performance tests for 5 types of road signs. As a result of the study, it was possible to detect a smaller number of point clouds with a regular triangle or rectangular shape that has vertical asymmetry than a square or circle. The results showed a high classification accuracy of 83% or more. In addition, when the size of the square mark was enlarged by 1.5 times, it was possible to classify it as a square despite an increase in the measurement distance. These results are expected to be used to improve dedicated roads and traffic safety facilities for sensors in the future autonomous driving era and to develop new facilities.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.317-329
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• 2014

In vision measurement systems based on structured light, the key point of detection precision is to determine accurately the central position of the projected laser line in the image. The purpose of this research is to extract laser line centers based on a decision function generated to distinguish the real centers from candidate points with a high recognition rate. First, preprocessing of an image adopting a difference image method is conducted to realize image segmentation of the laser line. Second, the feature points in an integral pixel level are selected as the initiating light line centers by the eigenvalues of the Hessian matrix. Third, according to the light intensity distribution of a laser line obeying a Gaussian distribution in transverse section and a constant distribution in longitudinal section, a normalized model of Hessian matrix eigenvalues for the candidate centers of the laser line is presented to balance reasonably the two eigenvalues that indicate the variation tendencies of the second-order partial derivatives of the Gaussian function and constant function, respectively. The proposed model integrates a Gaussian recognition function and a sinusoidal recognition function. The Gaussian recognition function estimates the characteristic that one eigenvalue approaches zero, and enhances the sensitivity of the decision function to that characteristic, which corresponds to the longitudinal direction of the laser line. The sinusoidal recognition function evaluates the feature that the other eigenvalue is negative with a large absolute value, making the decision function more sensitive to that feature, which is related to the transverse direction of the laser line. In the proposed model the decision function is weighted for higher values to the real centers synthetically, considering the properties in the longitudinal and transverse directions of the laser line. Moreover, this method provides a decision value from 0 to 1 for arbitrary candidate centers, which yields a normalized measure for different laser lines in different images. The normalized results of pixels close to 1 are determined to be the real centers by progressive scanning of the image columns. Finally, the zero point of a second-order Taylor expansion in the eigenvector's direction is employed to refine further the extraction results of the central points at the subpixel level. The experimental results show that the method based on this normalization model accurately extracts the coordinates of laser line centers and obtains a higher recognition rate in two group experiments.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.2
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• pp.89-94
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• 2016

This paper proposed a facial expression recognition approach using SIFT feature and SVM classifier. The SIFT was generally employed as feature descriptor at key-points in object recognition fields. However, this paper applied the SIFT descriptor as feature vector for facial expression recognition. In this paper, the facial feature was extracted by applying SIFT descriptor at each sub-block image without key-point detection procedure, and the facial expression recognition was performed using SVM classifier. The performance evaluation was carried out through comparison with binary pattern feature-based approaches such as LBP and LDP, and the CK facial expression database and the JAFFE facial expression database were used in the experiments. From the experimental results, the proposed method using SIFT descriptor showed performance improvements of 6.06% and 3.87% compared to previous approaches for CK database and JAFFE database, respectively.

• Journal of Korea Game Society
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• v.19 no.6
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• pp.99-106
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• 2019

This paper addresses a method to compute the closest approach distance between two ellipsoids in their inter-center direction. This is the key technique for collision detection and response between ellipsoids. We formulate a set of conditions with the inter-center distance, the contact point and the contact normal vector of the two externally-contacting ellipsoids. The equations are solved robustly and efficiently using a hybrid of Newton's method and the bisection method with root bracketing. We demonstrate the robustness and efficiency of the proposed method in various experiments.

• Ocean and Polar Research
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• v.34 no.2
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• pp.265-273
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• 2012

A new algorithm was developed, not only to detect the existence of a thermocline, but also to extract the thermocline parameters (such as thermocline thickness, mixed layer thickness, maximum temperature gradient, and temperature difference of thermocline), using the vertical profile of water temperature. According to Kappa analysis, in order to find adequate threshold values of vertical water temperature gradients ${\Delta}T$ ($^{\circ}C/m$), agreement and reliability were 87% and 0.74 respectively, in the conditions of maximum ${\Delta}T{\geq}0.5$ and surface and bottom layers ${\Delta}T<{\mid}0.2{\mid}$. Also, three different kinds of methods, viz. 1. Gradient method, 2. Hyperbolic tangent method, and 3. Differential hyperbolic tangent method, were tested to extract the key parameters of a thermocline. Comparing the results of three different methods, the differential hyperbolic tangent method was the most appropriate to extract the start and end point of a thermocline curve.