• 복식문화연구
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• 제8권5호
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• pp.754-770
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• 2000

The definite objects of this study are as follows ; 1. The study presents concrete objects of the shape of adult women's neck and shoulder after comparing and analyzing the features of five age groups ; the former young age, the latter young age, the former middle age, the latter middle age, the latter middle age and the old age. 2. The study presents concrete objects of adult women's neck and shoulder by the body types ; bend-forward type, straight type and lean-back type in order to be examined the body types. The results of this study are as follows ; 1. The shape of neck and shoulder needs the several concrete objects of each types because of the variable factors in size and body types. But the concrete objects of the types referred in five age groups contain all the important factors and enable to design the body suitable clothes. 2. This study shows that generally bend-forward type contains rising shoulder and lean-back type contains drooping shoulder, and straight type contains average value of neck and shoulder. The results of this study developed the body-suitable clothes of bend-forward type, straight type and lean-back type.

• 대한기계학회논문집A
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• 제27권7호
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• pp.1110-1119
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• 2003

This paper deals with the synthesis of the 3-dimensional grasp planning for unknown objects. Previous studies have many problems, which the estimation time for finding the grasping points is much long and the analysis used the not-perfect 3-dimensional modeling. To overcome these limitations in this paper new algorithm is proposed, which algorithm is achieved by two steps. First step is to find the whole 3-dimensional geometrical modeling for unknown objects by using stereo matching. Second step is to find the optimal grasping points for unknown objects by using the neural network trained by the result of optimization using genetic algorithm. The algorithm is verified by computer simulation, comparing the result between neural network and optimization.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2005년도 춘계학술대회
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• pp.517-530
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• 2005

Researches for NN(nearest neighbor) query which is often used in LBS system, have been worked. However, Conventional NN query processing techniques are usually meaningless in moving object management system for LBS since their results may be invalidated as soon as the query and data objects move. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet continuous trajectory nearest neighbor query processing. The proposed technique consists of Approximate CTNN technique which has quick response time, and Exact CTNN technique which makes it possible to search accurately nearest neighbor objects. Experimental results using GSTD datasets showed that the Exact CTNN technique has high accuracy, but has a little low performance for response time. They also showed that the Approximate CTNN technique has low accuracy comparing with the Exact CTNN, but has high response time.

• 한국CDE학회논문집
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• 제16권4호
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• pp.285-291
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• 2011

A pose estimation process from medical images is calculating locations and orientations of objects obtained from Computed Tomography (CT) volume data utilizing X-ray images from two directions. In this process, digitally reconstructed radiograph (DRR) images of spatially transformed objects are generated and compared to X-ray images repeatedly until reasonable transformation matrices of the objects are found. The DRR generation and image comparison take majority of the total time for this pose estimation. In this paper, a fast DRR generation technique based on GPU parallel computing is introduced. A volume ray-casting algorithm is explained with brief vector operations and a parallelization technique of the algorithm using Compute Unified Device Architecture (CUDA) is discussed. This paper also presents the implementation results and time measurements comparing to those from pure-CPU implementation and open source toolkit.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.692-698
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• 1993

This paper presents a Bin-Picking method in which robot recognizes the positions and orientations of jumbled objects placed in a bin, then picks up distinctive objects from the top of the jumble. The jumbled objects are recognized comparing the characteristics extracted from stereo images with those in the CAD data. The 3-D information is obtained using the bipartite-matching method which compares image of one camera with the image of the other camera Then the robot picks up the object which will cause the least amount of disturbance to the jumble, and places it at a predetermined place. This paper contributes to the basic study of Bin-Picking, and can be used in an automatic assembly system without using part sorting or orienting devices.

• 천문학회지
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• 제34권4호
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• pp.297-299
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• 2001

We have constructed the foundations to a series of theoretical diagnostic methods to probe the jet phenomenon in young stars as observed at various optical forbidden lines. We calculate and model in a self-consistent manner the physical and radiative processes which arise within an inner disk-wind driven magneto centrifugally from the circumstellar accretion disk of a young sun-like star. Comparing with real data taken at high angular resolution, our approach will provide the basis of systematic diagnostics for jets and their related young stellar objects, to attest the emission mechanisms of such phenomena. This work can help bring first-principle theoretical predictions to confront actual multi-wavelength observations, and will bridge the link between many very sophiscated numerical simulations and observational data. Analysis methods discussed here are immediately applicable to new high-resolution data obtained with HST and Adaptic Optics.

• 디지털융복합연구
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• 제3권1호
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• pp.149-163
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• 2005

Researches for NN(nearest neighbor) query which is often used in LBS system, have been worked. However. Conventional NN query processing techniques are usually meaningless in moving object management system for LBS since their results may be invalidated as soon as the query and data objects move. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet continuous trajectory nearest neighbor query processing. The proposed technique consists of Approximate CTNN technique which has quick response time, and Exact CTNN technique which makes it possible to search accurately nearest neighbor objects. Experimental results using GSTD datasets shows that the Exact CTNN technique has high accuracy, but has a little low performance for response time. They also shows that the Approximate CTNN technique has low accuracy comparing with the Exact CTNN, but has high response time.

• 동의생리병리학회지
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• 제27권6호
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• pp.705-709
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• 2013

We in this paper proposed a distinction method to compare objects in the Korean medicine ontology. Comparing same and different information between two objects, two scenarios to use our system were designed and implemented. One is the distinction of formulas, medicinal materials, and acupuncture points and the other is the distinction of effects, treatments, and symptoms. To compare objects easily, the decomposition of effects and treatments and the processing of medicinal materials were provided. Also, information of each object was shown through the link to the semantic search system. Our distinction method and system could be helpful to compare and distinct two objects in the diagnosis systems or search systems of Korean medicine information.

• 대한임베디드공학회논문지
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• 제17권5호
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• pp.273-280
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• 2022

Along with the advancement of deep learning technology, securing high-quality dataset for verification of developed technology is emerging as an important issue, and developing robust deep learning models to the domestic road environment is focused by many research groups. Especially, unlike expressways and automobile-only roads, in the complex city driving environment, various dynamic objects such as motorbikes, electric kickboards, large buses/truck, freight cars, pedestrians, and traffic lights are mixed in city road. In this paper, we built our dataset through multi camera-based processing (collection, refinement, and annotation) including the various objects in the city road and estimated quality and validity of our dataset by using YOLO-based model in object detection. Then, quantitative evaluation of our dataset is performed by comparing with the public dataset and qualitative evaluation of it is performed by comparing with experiment results using open platform. We generated our 2D dataset based on annotation rules of KITTI/COCO dataset, and compared the performance with the public dataset using the evaluation rules of KITTI/COCO dataset. As a result of comparison with public dataset, our dataset shows about 3 to 53% higher performance and thus the effectiveness of our dataset was validated.

• Spatial Information Research
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• 제3권2호
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• pp.179-189
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• 1995

벡터링 도구를 이용하여 원판과 같은 양질의 도면이 없는 기존 지도를 수치화하기 위해서는 지도로부터 의미있는 벡터링 대상물(도로, 등고선, 해안선, filled-area, 문자, 기호 등)을 추출하는 방법이 필요하다. 본 논문에서는, 칼라지도로부터 추출해야 할 벡터링 대상물을 크게 곡선 미 직선, filled-area, 문자/기호로 분류하였으며, 대상물의 기하학적 특성과 칼라의 분포특성을 반영한 효율적인 벡터링 대상물 추출방법을 연구하였다. 곡선 및 직선 추출을 위해, 선의 연결성과 기하학적 특성을 반영한 방향성 마스크를 설계하고 이를 이용한 선추적 방법을 개발하였다. filled-area와 문자/기호의 경유에는 NxN 블럭간의 칼라분포 유사도 비교방법과 lical thresholding 방법을 각각 이용하여 벡터링 도구에서 수용할 수 있게 해줌으로써 소규모 지리정보 응용시스템을 보다 경제적으로 구축하는데 활용될 수 있을 것이다.