• 산업경영시스템학회지
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• 제44권3호
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• pp.117-124
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• 2021

The development of IOT technology and artificial intelligence technology is promoting the smartization of manufacturing system. In this study, data extracted from acceleration sensor and current sensor were obtained through experiments in the cutting process of SKD11, which is widely used as a material for special mold steel, and the amount of tool wear and product surface roughness were measured. SVR (Support Vector Regression) is applied to predict the roughness of the product surface in real time using the obtained data. SVR, a machine learning technique, is widely used for linear and non-linear prediction using the concept of kernel. In particular, by applying GSVQR (Generalized Support Vector Quantile Regression), overestimation, underestimation, and neutral estimation of product surface roughness are performed and compared. Furthermore, surface roughness is predicted using the linear kernel and the RBF kernel. In terms of accuracy, the results of the RBF kernel are better than those of the linear kernel. Since it is difficult to predict the amount of tool wear in real time, the product surface roughness is predicted with acceleration and current data excluding the amount of tool wear. In terms of accuracy, the results of excluding the amount of tool wear were not significantly different from those including the amount of tool wear.

• 재활치료과학
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• 제12권1호
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• pp.23-35
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• 2023

목적 : 본 연구는 국내 감각통합치료의 임상 관찰 평가 사용실태와 세부 항목별 결과 측정의 어려움 및 중요도를 알아보고 이를 통해 임상 관찰 측정에 있어 AI 측정 기술의 적용 유용성과 세부 항목별 적용 필요도를 확인하고자 하였다. 연구 방법 : 연구 과정은 국내 작업치료사 31명에서 온라인 설문지 배포를 통해 조사 연구를 실시하였다. 설문지는 일반적 정보, 감각통합 평가 도구 사용 실태, 임상 관찰의 세부 항목별 측정의 어려움, AI 측정 기술의 유용성, 세부 항목별 평가의 중요성 및 AI 측정 기술 개발의 필요성을 조사하는 내용으로 구성되었다. 조사의 결과를 빈도분석과 기술통계를 사용하여 분석하였다. 결과 : 조사에 참여한 작업치료사들은 Sensory Profile(96.8%)을 가장 많이 사용하였고 그다음으로 임상 관찰(90.3%)을 많이 사용하였다. 임상 관찰 시 측정이 어려운 세부 항목은 Finger-to-nose Test와 Postural Control(on the 이었으며, 다음으로 Eye Movement와 Protective Extension Test(67.7%)였다. 임상 관찰 시 AI 측정 기술 적용은 83.9%의 연구 대상자들이 모두 유용할 것으로 응답하였다. AI 측정 기술 적용이 필요하다고 응답한 가장 높은 항목은 Postural Control(on the ball)(90.3%)이었고, 다음으로 Eye Movement(83.9%), Prone Extension과 Protective Extension Test(77.4%) 순으로 나타났다. 결론 : 본 연구의 결과는 국내 아동 작업치료 현장에서 임상 관찰이 중요한 평가도구이며 임상 관찰 평가의 측정 정확성을 향상하기 위해서 AI 기술 적용이 필요하다는 작업치료사들의 인식을 확인할 수 있었다.

• Journal of Biosystems Engineering
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• 제18권2호
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• pp.133-143
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• 1993

In developing an Expert System(ES), there are two ways. One is to develop an ES using AI(artificial Intelligence) languages and another using ES-development tools. CLIPS is an ES-development tool and has a powerful inference engine in it. Using the tool like CLIPS, knowledge engineer can concentrate on constructing a knowledge base without wasting time in developing an inference engine. However, CLIPS is lack of user-friendly interfaces for both knowledge enginners and users. Because CLIPS was developed in USA, it can not afford to use Korean language. Therefore, several user-friendly interfaces including hmenu, htille, hpcxdisplay were develpoed and added to CLIPS. CLIPS with the interfaces is called HCLIPS(Hangul CLIPS) in this paper. HCLIPS provides a new I/O device to be utilized for expert systems in Korean. HCLIPS can be efficiently used for developing expert systems in agriculture and consulting farmers interactively who are not familiar with computer programming and ES itself.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1245-1248
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• 1996

This paper describes a cell programming environment that deals with problems associated with programming Flexible Manufacturing Cells(FMCs). The environment consists of the cell programming editor and the automatic generation module. In the cell programming editor, cell programmers can develop cell programs using task level description set which supports task-oriented specifications for manipulation cell activities. This approach to cell programming reduces the amount of details that cell programmers need to consider and allows them to concentrate on the most important aspects of the task at hand. The automatic generation module is used to transform task specifications into executable programs used by cell constituents. This module is based on efficient algorithm and expert systems which can be used for optimal path planning of robot operations and optimal machining parameters of machine tool operations. The development tool in designing the environment is an object-oriented approach which provides a simple to use and intuitive user interface, and allows for an easy development of object models associated with the environment.

• Journal of Preventive Medicine and Public Health
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• 제22권1호
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• pp.57-64
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• 1989

A decision support system (DSS) was developed to support doctor's decision-making in diagnosing hearing loss. The final diagnosis encompassed 41 diseases with the problem of hearing loss. The system was developed by integrating model-oriented DSS technique and artificial intelligence technology. The system can be used as both diagnosis tool and teaching tool for medical students. Furthermore, the AI technology obtained from this study may also be used in developing DSS for hospital management.

• International Journal of Advanced Culture Technology
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• 제12권1호
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• pp.305-310
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• 2024

The purpose of this study is to implement game content within the generative artificial intelligence module Chat-GPTs, grounded in the humanistic discourse of self-reflection. This content aims to empower the dignity of the silver generation, which has been marginalized by digital technology. Simultaneously, we intend to prototype a digital psychotherapeutic tool. The development of a flexible device that adapts to the silver generation's living environment and temporal constraints is also part of our plan. However, there are still few commercially available products, and digital therapeutics developed in the form of content are virtually nonexistent. The goal is to implement game content that allows the elderly, who have been marginalized by digital technology, to find their true dignity. Simultaneously, we plan to commercialize a prototype of digital psychotherapy that can flexibly adapt to the range of living environments and time constraints of the elderly. This study has been extended based on the game content 'Daily Run' created by Hyein Kwon, an undergraduate student at Kyungil University.

• Steel and Composite Structures
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• 제39권3호
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• pp.319-335
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• 2021

This study proposes a new and highly-accurate artificial intelligence model, namely ANN-IP, which combines an interior-point (IP) algorithm and artificial neural network (ANN), to improve the axial compression capacity prediction of elliptical concrete-filled steel tubular (CFST) columns. For this purpose, 145 tests of elliptical CFST columns extracted from the literature are used to develop the ANN-IP model. In this regard, axial compression capacity is considered as a function of the column length, the major axis diameter, the minor axis diameter, the thickness of the steel tube, the yield strength of the steel tube, and the compressive strength of concrete. The performance of the ANN-IP model is compared with the ANN-LM model, which uses the robust Levenberg-Marquardt (LM) algorithm to train the ANN model. The comparative results show that the ANN-IP model obtains more magnificent precision (R² = 0.983, RMSE = 59.963 kN, a20 - index = 0.979) than the ANN-LM model (R² = 0.938, RMSE = 116.634 kN, a20 - index = 0.890). Finally, a new Graphical User Interface (GUI) tool is developed to use the ANN-IP model for the practical design. In conclusion, this study reveals that the proposed ANN-IP model can properly predict the axial compression capacity of elliptical CFST columns and eliminate the need for conducting costly experiments to some extent.

• 시스템엔지니어링학술지
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• 제16권2호
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• pp.67-77
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• 2020

Traditionally nuclear thermal hydraulic and nuclear safety has relied on numerical simulations to predict the system response of a nuclear power plant either under normal operation or accident condition. However, this approach may sometimes be rather time consuming particularly for design and optimization problems. To expedite the decision-making process data-driven models can be used to deduce the statistical relationships between inputs and outputs rather than solving physics-based models. Compared to the traditional approach, data driven models can provide a fast and cost-effective framework to predict the behavior of highly complex and non-linear systems where otherwise great computational efforts would be required. The objective of this work is to develop an AI algorithm to predict the peak fuel cladding temperature as a metric for the successful implementation of FLEX strategies under extended station black out. To achieve this, the model requires to be conditioned using pre-existing database created using the thermal-hydraulic analysis code, MARS-KS. In the development stage, the model hyper-parameters are tuned and optimized using the talos tool.

• Design & Manufacturing
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• 제16권4호
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• pp.1-6
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• 2022

Fine blanking is a press processing technology that can process most of the product thickness into a smooth surface with a single stroke. In this fine blanking process, shear is an essential step. The punches and dies used in the shear are subjected to impacts of tens to hundreds of gravitational accelerations, depending on the type and thickness of the material. Therefore, among the components of the fine blanking mold (dies), punches and dies are the parts with the shortest lifespan. In the actual production site, various types of tool damage occur such as wear of the tool as well as sudden punch breakage. In this study, machine learning algorithms were used to predict these problems in advance. The dataset used in this paper consisted of the signal of the vibration sensor installed in the tool and the measured burr size (tool wear). Various features were extracted so that artificial intelligence can learn effectively from signals. It was trained with 5 features with excellent distinguishing performance, and the SVM algorithm performance was the best among 33 learning models. As a result of the research, the vibration signal at the time of imminent tool replacement was matched with an accuracy of more than 85%. It is expected that the results of this research will solve problems such as tool damage due to accidental punch breakage at the production site, and increase in maintenance costs due to prediction errors in punch exchange cycles due to wear.

• 대한영상의학회지
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• 제83권6호
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• pp.1298-1311
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• 2022

목적 흉부 X선 사진에서 척추측만증을 조기진단 할 수 있는 딥러닝 기반의 스크리닝 소프트웨어를 준지도학습(semi-supervised generative adversarial network; 이하 GAN) 방법을 이용하여 개발하고자 하였다. 대상과 방법 두 곳의 상급종합병원에서 촬영된 흉부 X선 사진에서 척추측만증을 조기진단할 수 있는 스크리닝 소프트웨어를 개발하기 위하여 GAN 방법이 이용되었다. GAN의 훈련과정에서 경증에서 중증의 척추측만증을 보이는 흉부 X선 사진들을 사용하였으며 upstream task에서 척추측만증의 특징을 학습하고, downstream task에서 정상과 척추측만증을 분류하도록 훈련하였다. 결과 수신자 조작 특성 곡선의 곡선하면적(area under the receiver operating characteristic curve), 음성예측도, 양성예측도, 민감도 및 특이도는 각각 0.856, 0.950, 0.579, 0.985, 0.285이었다. 결론 우리가 GAN 방법을 이용하여 개발한 딥러닝 기반의 스크리닝 소프트웨어는 청소년의 흉부 X선에서 척추측만증을 진단하는데 있어서 높은 음성예측도와 민감도를 보였다. 이 소프트웨어가 건강검진을 목적으로 촬영한 청소년의 흉부 X선 사진에 진단 스크리닝 도구로써 이용된다면 영상의학과 의사의 부담을 덜어주며, 척추측만증의 조기진단에 기여할 것으로 생각된다.