• 지능정보연구
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• 제28권1호
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• pp.217-242
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• 2022

AI 기술이 결합된 지능형 제품은 기술적 차별화를 실현하며 시장 경쟁력을 높일 수 있는 잠재성을 지닌다. 하지만 시장 수용도를 극대화 할 수 있는 AI 기반의 신제품 개발 방법론은 부재하다. 본 연구는 AI 기반의 지능형 제품 개발에 대한 방법론으로서 KANO-QFD 통합 모델을 제안한다. 실증적인 분석을 위한 구체적 사례로 탈모 예측 및 치료 기기에 대한 소비자 요구조건(Customer Requirements)의 유형을 분류하고, 이를 구현하기 위한 기술적 요구사항(Engineering Characteristics)의 상대적 중요도 및 우선순위를 도출하여 지능형 메디컬 신제품 개발의 방향을 제시하였다. 소비자 130명을 대상으로 실시한 설문조사 분석 결과, KANO 카테고리 중 매력적 품질(Attractive Quality) 요소로 미래 탈모 진행 상황에 대한 정확한 예측, 미래 탈모 모습 및 치료 후 개선된 미래 모습을 실물화하여 스마트폰으로 보고, 세련된 디자인, 레이저와 LED 빛 복합 에너지를 이용한 치료 등이 도출되었다. QFD의 품질의 집(House of Quality)을 기반으로 분석한 결과, 탈모 진단 및 예측을 위한 학습 데이터, 두피 스캔용 Micro 카메라 해상도, 탈모 유형 분류 모델, 맞춤화를 위한 개인별 계정 관리, 탈모 진행상황 진단 모델 순으로 상대적 중요도 및 우선순위가 도출되었다. 본 연구는 기존에 선행되지 않았던 AI 기반의 지능형 메디컬 제품 개발에 대한 방향을 제시하였다는 면에서 의의를 지닌다.

• 한국안전학회지
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• 제23권6호
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• pp.7-13
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• 2008

It is important to prevent roll failure in hot rolling process for reducing maintenance cost and production loss. The relationship between rolling pass schedule and the work roll wear profile will be presented. The roll wear pattern is related with roll catastrophic failure. The irregular and deep roll wear pattern should be removed by On-line Roll Grinder(ORG) for roll failure prevention. In this study, a computer roll wear prediction model under real process working condition is developed and evaluated with hot rolling pass schedule. The method of building wear calculation functions for center portion abrasion and marginal abrasion respectively was used to develop a work roll wear prediction mathematical model. The three type rolling schedule are evaluated by wear prediction model. The optimum roll grinding methods is suggested for schedule tree rolling technique.

• 한국정밀공학회지
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• 제10권3호
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• pp.69-80
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• 1993

It is important to prevent roll failure in hot rolling process for reducing maintenance coat and production loss. Roll material and rolling conditions such as the roll force and torque have been intensively investigated to overcome the roll failures. In this study, a computer roll life prediction system under working condition is developed and evaluated on IBM-PC level. The system is composed and fatigue estimation models which are stress analysis, crack propagation, wear and fatigue estimation. Roll damage can be predicted by calculating the stress anplification, crack depth propagation and fatigue level in the roll using this computer model. The developed system is applied to a work roll in actual hot rolling process for reliability evaluation. Roll failures can be diagnosed and the propriety of current working condition can be determined through roll life prediction simulation.

• 대한기계학회논문집B
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• 제28권10호
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• pp.1247-1254
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• 2004

In momentum exchange theory the loss models for the circulatory flow is critically important. But because of lack of loss model on the circulatory flow, analysis model on regenerative turbomachines is not available in the open literature. In the present study circulatory loss is evaluated by combining bend's losses. Through the comparison with the previous experimental data on linear pressure gradient, a combination factor is suggested in terms of the aspect ratio of a channel. Applying this factor to two kinds of regenerative blowers the predicted results are found to be in good agreement with the experimental data of the overall performance and the head distribution along the rotational direction. Especially, the comparison with the head distribution demonstrates the accuracy of hydraulic model and loss model suggested in the present study. And the comparison with the overall performance confirms the validness of physical models as well as loss models suggested in the present study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.3913-3934
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• 2021

Real-time prediction of Web service of quality (QoS) provides more convenience for web services in cloud environment, but real-time QoS prediction faces severe challenges, especially under the cold-start situation. Existing literatures of real-time QoS predicting ignore that the QoS of a user/service is related to the QoS of other users/services. For example, users/services belonging to the same group of category will have similar QoS values. All of the methods ignore the group relationship because of the complexity of the model. Based on this, we propose a real-time Matrix Factorization based Clustering model (MFC), which uses category information as a new regularization term of the loss function. Specifically, in order to meet the real-time characteristic of the real-time prediction model, and to minimize the complexity of the model, we first map the QoS values of a large number of users/services to a lower-dimensional space by the PCA method, and then use the K-means algorithm calculates user/service category information, and use the average result to obtain a stable final clustering result. Extensive experiments on real-word datasets demonstrate that MFC outperforms other state-of-the-art prediction algorithms.

• 한국전자파학회논문지
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• 제29권6호
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• pp.441-448
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• 2018

최근 국립전파연구원에서는 5G 이동통신 도심/부도심 지역에서 빌딩에 의한 클러터 손실을 예측하기 위해 3, 6, 10, 18, 24 GHz 대역에서 전파측정을 수행하였다. 본 연구에서는 송신안테나 높이가 85 m일 때, 도심과 부도심환경에서 주파수에 따라 측정된 클러터 손실을 비교하며, ITU-R P.2108 예측모델과의 오차를 평가하였다. 도심이나 부도심 지역에서 주파수가 높을수록 클러터 손실이 크게 나타나며, 도심 지역에서의 클러터 손실은 부도심 지역보다 더욱 강한 클러터 손실을 보이지만, ITU-R P.2108 예측 모델보다 낮은 클러터 손실을 얻어졌다. 결론적으로 측정된 데이터로부터 송신 안테나가 85 m로 높은 경우 도심/부도심 지역에서 클러터 손실에 대한 데이터를 예측모델에 반영하여 클러터 손실 예측모델을 좀 더 개선시켜 나갈 필요가 있다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 봄 학술논문 발표대회
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• pp.208-209
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• 2022

This study aims to analyze the risk factors caused by object damage and third-party damage loss in actual bridge construction based on past insurance premium payment data from major domestic insurers for bridge construction projects, and develop a quantitative loss prediction model. For the development of quantitative bridge construction loss model, the dependent variable was selected as the loss ratio, and the independent variable adopted 1) Technical factors: superstructure type, foundation type, construction method, and bridge length 2) Natural hazards: flood anf Typhoon, 3) Project information: total construction duration, total cost and ranking. Among the selected independent variables, superstructure type, construction method, and project period were shown to affect the ratio of bridge construction losses, while superstructure, foundation, flood and ranking were shown to affect the ratio of the third-party losses.

• Safety and Health at Work
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• 제11권3호
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• pp.322-334
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• 2020

Background: Spontaneous combustion of coal is one of the factors which causes direct or indirect gas and dust explosion, mine fire, the release of toxic gases, loss of reserve, and loss of miners' life. To avoid these incidents, the prediction of spontaneous combustion is essential. The safety of miner's in the mining field can be assured if the prediction of a coal fire is carried out at an early stage. Method: Adularya Underground Coal Mine which is fully mechanized with longwall mining method was selected as a case study area. The data collected for 2017, by sensors from ten gas monitoring stations were used for the simulation and prediction of a coal fire. In this study, the fuzzy logic model is used because of the uncertainties, nonlinearity, and imprecise variables in the data. For coal fire prediction, CO, O₂, N₂, and temperature were used as input variables whereas fire intensity was considered as the output variable.The simulation of the model is carried out using the Mamdani inference system and run by the Fuzzy Logic Toolbox in MATLAB. Results: The results showed that the fuzzy logic system is more reliable in predicting fire intensity with respect to uncertainties and nonlinearities of the data. It also indicates that the 1409 and 610/2B gas station points have a greater chance of causing spontaneous combustion and therefore require a precautional measure. Conclusion: The fuzzy logic model shows higher probability in predicting fire intensity with the simultaneous application of many variables compared with Graham's index.

• 한국군사과학기술학회지
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• 제26권3호
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• pp.262-272
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• 2023

A polymer-based mechanical low-pass filter(m-LPF) for high-g accelerometers makes it possible to remove high-frequency transient noises from acceleration signals, thus ensuring repeatable and reliable measurement on high-g acceleration. We establish a prediction model for performance of m-LPF by combining a fundamental vibration model with the fractional derivative standard linear solid(FD SLS) model describing the storage modulus and loss modulus of polymers. Here, the FD SLS model is modified to consider the effect of m-LPF shape factor (i.e., thickness) on storage modulus and loss modulus. The prediction accuracy is verified by comparing the displacement transmissibility(or cut-off frequency) estimated using our model with that measured from 3 kinds of polymers(polysulfide rubber(PSR), silicone rubber(SR), and polydimethylsiloxane(PDMS)). Our findings will contribute a significant growth of m-LPF for high-g accelerometers.

• Journal of Mechanical Science and Technology
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• 제15권9호
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• pp.1292-1301
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• 2001

The mean-line method using empirical models is the most practical method of predicting off-design performance. To gain insight into the empirical models, the influence of empirical models on the performance prediction results is investigated. We found that, in the two-zone model, the secondary flow mass fraction has a considerable effect at high mass flow-rates on the performance prediction curves. In the TEIS model, the first element changes the slope of the performance curves as well as the stable operating range. The second element makes the performance curves move up and down as it increases or decreases. It is also discovered that the slip factor affects pressure ratio, but it has little effect on efficiency. Finally, this study reveals that the skin friction coefficient has significant effect on both the pressure ratio curve and the efficiency curve. These results show the limitations of the present empirical models, and more resonable empirical models are reeded.