• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.63-64
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• 2007

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.798-803
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• 1988

This paper is concerned with a computer-aided supporting system to a systematic check of mechanical drawings. The problems treated in this paper are limited to the checking of the omissions and mis-writings of dimensioning in the mechanical drawings made by a CAD system. A drawing check system has been made up on a personal computer with Basic and Pascal. The feasibility of the proposed drawing check system is confirmed for omissions and mis-writings of dimensioning in mechanical drawings.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.104-107
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• 2002

Direct Metal Manufacturing (DMM) is a new additive process that aims to take die making and metalworking in an entirely new direction. It is the blending of five common technologies : lasers, computer-aided design (CAD), computer-aided manufacturing (CAM), sensors and powder metallurgy. The resulting process creates parts by focusing an industrial laser beam onto a tool-steel work piece or platform to create a molten pool of metal. A small stream of powdered tool-steel metal is then injected into the melt pool to increase the size of the molten pool. By moving the laser beam back and forth, under CNC control, and tracing out a pattern determined by a computerized CAD design, the solid metal part is built line-by-line, one layer at a time. DMM produces improved material properties in less time and at a lower cast than is possible with traditional fabrication.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.497-498
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• 2006

Powder Injection Molding (PIM) has recently been recognized as an advanced manufacturing technology for low-cost mass production of metal or ceramic parts of complicated geometry. With this regards, design technology of dental scaler tip PIM mold, which has complex shape, with the help of computer-aided analysis for powder injection molding process was developed. Compter aided analysis results, such as filling pattern, weldline formation, and air vent position prediction were investigated and eventually showed good agreements with experimental results.

• Journal of Engineering Education Research
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• v.11 no.1
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• pp.85-100
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• 2008

The purpose of this study is development of 'F1 in Schools Program' for elementary school student and validation of the program. Fifteen students were originally chosen from the W elementary school in Cheongju, Chungcheogbuk-Do. The children were tested on their understanding of science and 'F1 in Schools Program'. After developing the 'F1 in Schools Program', it was used in the classroom to evaluate applicability and to examine the responses from students, parents and schools. The program consists of 60 classes and the time of each class is 40 minutes. This study was conducted for 10 days from January 22nd, 2007 to February 2nd, 2007. CAD(Computer Aided Design), CFD(Computation Fluid Dynamics), CAM(Computer Aided manufacturing) and CNC Machine were used in this study and proved to be good materials for students in that they increased the students' participation and imagination. However, the children's cognitive and creative abilities as well as manuals written in English hampered the process. Most students, parents, schools seemed to be satisfied with use of the program. However, the schools showed that there was not enough understanding of the program as a whole. The processes with which students build and inspect using the $CO_2$Model Car not only improves the processing of the model but also enhanced the students scientific understanding related to the car speed.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1202-1208
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• 2022

Techniques based on computer vision are becoming increasingly important in construction safety monitoring. Using AI algorithms can automatically identify conceivable hazards and give feedback to stakeholders. However, the construction site remains various potential hazard situations during the project. Due to the site complexity, many visual devices simultaneously participate in the monitoring process. Therefore, it challenges developing and operating corresponding AI detection algorithms. Safety information resulting from computer vision needs to organize before delivering it to safety managers. This study proposes a framework for computer vision-aided construction safety monitoring using collaborative 4D BIM information to address this issue, called CSM4D. The suggested framework consists of two-module: (1) collaborative BIM information extraction module (CBIE) extracts the spatial-temporal information and potential hazard scenario of a specific activity; through that, Computer Vision-aid Safety Monitoring Module (CVSM) can apply accurate algorithms at the right workplace during the project. The proposed framework is expected to aid safety monitoring using computer vision and 4D BIM.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.928-933
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• 2018

Nowadays, gastropathy is a common disease. As endoscopic equipment are developed and used widely, it is possible to provide a large number of endoscopy images. Computer-aided Diagnosis (CADx) systems aim at helping physicians to identify possibly malignant abnormalities more accurately. In this paper, we present a CADx system to detect and classify the abnormalities of gastric lesions which include bleeding, ulcer, neuroendocrine tumor and cancer. We used an Inception module based deep learning model. And we used data augmentation for learning. Our preliminary results demonstrated promising potential for automatically labeled region of interest for endoscopy doctors to focus on abnormal lesions for subsequent targeted biopsy, with Az values of Receiver Operating Characteristic(ROC) curve was 0.83. The proposed CADx system showed reliable performance.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.7
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• pp.3651-3658
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• 2016

Computer-aided diagnosis of breast cancer is an important medical approach. In this research paper, we focus on combining two major methodologies, namely fuzzy base systems and the evolutionary genetic algorithms and on applying them to the Saudi Arabian breast cancer diagnosis database, to aid physicians in obtaining an early-computerized diagnosis and hence prevent the development of cancer through identification and removal or treatment of premalignant abnormalities; early detection can also improve survival and decrease mortality by detecting cancer at an early stage when treatment is more effective. Our hybrid algorithm, the genetic-fuzzy algorithm, has produced optimized systems that attain high classification performance, with simple and readily interpreted rules and with a good degree of confidence.

• Journal of Korea Foundry Society
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• v.25 no.6
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• pp.240-248
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• 2005

The rheocasting characteristics are strongly influenced by the microstructural morphology such as particle size, form factor and contiguity. In this study, the effect of structural morphology on fluid flow characteristics of A356 semi-solid alloy was investigated with a vacuum suction fluidity test. Semi-solid metal slurry was made by the mechanical stirring, the liquidus casting, and H-NCM to be analysed. H-NCM could obtain uniform and fine globular microstructures of 0.9 form factor and 55 ${\mu}m$ particle size. Inoculation was found to be effective for reducing particle size, however, for H-NCM it should be avoided due to the cause of increasing contiguity. The fluidity test indicated that the non-stirring method had higher fluidity and smaller liquid segregation in the same solid faction of 0.4 than the stirring method, for smaller particle size and higher form factor. It was observed that liquid segregation decreased as the particle size is smaller and form factor is higher. The results of die-casting experiment were a good agreement with those of fluidity test.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.34-43
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• 2010

Texture information plays an important role in object recognition and classification. To perform an accurate classification, the texture feature used in the classification must be highly discriminative. This paper presents a novel texture descriptor for texture-based image retrieval and its application in Computer-Aided Diagnosis (CAD) system for Emphysema classification. The texture descriptor is based on the combination of local surrounding neighborhood difference and centralized neighborhood difference and is named as Combined Neighborhood Difference (CND). The local differences of surrounding neighborhood difference and centralized neighborhood difference between pixels are compared and converted into binary codewords. Then binomial factor is assigned to the codewords in order to convert them into high discriminative unique values. The distribution of these unique values is computed and used as the texture feature vectors. The texture classification accuracies using Outex and Brodatz dataset show that CND achieves an average of 92.5%, whereas LBP, LND and Gabor filter achieve 89.3%, 90.7% and 83.6%, respectively. The implementations of CND in the computer-aided diagnosis of Emphysema is also presented in this paper.