• 한국컴퓨터정보학회논문지
• /
• 제22권7호
• /
• pp.75-82
• /
• 2017

Correct prediction of emotion is essential for developing advanced health devices. For this purpose, neural network has been successfully used. However, interpretation of how a certain emotion is predicted through the emotion prediction neural network is very tough. When interpreting mechanism about how emotion is predicted by using the emotion prediction neural network can be developed, such mechanism can be effectively embedded into highly advanced health-care devices. In this sense, this study proposes a novel approach to interpreting how the emotion prediction neural network yields emotion. Our proposed mechanism is based on HRV (heart rate variability) measurements, which is based on calculating physiological data out of ECG (electrocardiogram) measurements. Experiment dataset with 23 qualified participants were used to obtain the seven HRV measurement such as Mean RR, SDNN, RMSSD, VLF, LF, HF, LF/HF. Then emotion prediction neural network was modelled by using the HRV dataset. By applying the proposed mechanism, a set of explicit mathematical functions could be derived, which are clearly and explicitly interpretable. The proposed mechanism was compared with conventional neural network to show validity.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제31권6호
• /
• pp.716-727
• /
• 2004

컴포넌트 기반 소프트웨어 개발 (CBD) 기술은 재사용 가능한 컴포넌트를 조합하여 효율적으로 소프트웨어를 개발함으로써 개발 노력과 상품화 시간을 줄여주는 새로운 기술로 정착되고 있다. 이러한 CBD 컴포넌트는 한 도메인의 표준이나 공통적인 기능을 제공하여야 재사용성이 높아진다. 특히, 공통성 안의 미세한 가변적인 부분도 모델링하고, 이 가변성을 각 어플리케이션의 특성에 적합하게 특화 할 수 있도록 설계되어야 한다. 기존의 CBD 방법론에서도 이 중요성이 강조되고 있지만, 체계적이며 구체적인 개발 프로세스, 적용 지침 및 산출물 양식의 제공이 미흡하여, 도메인 컴포넌트의 개발은 비체계적인 프로세스와 개발자의 경험에 의존해 왔다. 본 논문은 컴포넌트 설계를 위한 체계적인 프로세스와 기법을 제안한다. 이 프로세스는 여러 단계와 활동으로 구성되며, 각 활동에 대한 세부 지침과 표준 양식도 포함하여 보다 효과적인 컴포넌트 개발을 도모한다. 제안된 기법의 실효성 검증을 위하여 금융 도메인에 적용한 사례연구를 제시하며, 다른 기법들과의 비교 평가도 다룬다. CBD의 공통 컴포넌트 개발에 제안된 프로세스와 지침의 사용함으로써 보다 재사용성과 적용성이 높은 컴포넌트가 비용 및 시간에 있어서 효율적으로 개발될 것으로 기대된다.

• 대한안전경영과학회:학술대회논문집
• /
• 대한안전경영과학회 1999년도 추계학술대회
• /
• pp.217-236
• /
• 1999

Engineering process control (EPC) is one of the techniques very widely used in process. EPC is based on control theory which aims at keeping the process on target. Statistical process control (SPC), also known as statistical process monitoring. The main purpose of SPC is to look for assignable causes (variability) in the process data. The combined SPC/EPC scheme is gaining recognition in the process industries where the process frequently experiences a drifting mean. This paper aims to study the difference between SPC and EPC in simple terms and presents a case study that demonstrates successful integration of SPC and EPC for a product in drifting industry. Statistical process control (SPC) monitoring of the special causes of a process, along with engineering feedback control such as proportional-integral-derivative (PID) control, is a major tool for on-line quality improvement.

• 한국정밀공학회지
• /
• 제13권3호
• /
• pp.70-79
• /
• 1996

In off-line process optimization, process parameters are controlled such that the process is robust against changes in equipment conditions and incoming materials. The off-line methods, however, are not effective when the changes are so large that process parameters need to be adjusted. On-line control can respond to such large changes, but process uniformity has not been controlled on-line due to the difficulties in modeling. This paper is aimed at developing a new on-line control methodology where the uniformity is controlled effectively. The process variability is categorized based on the physical considerations, and the process parameters are classi- fied considering their effects on the categorized process variabilities. On-line control is performed with the properly selected process parameters so that robustness may not be degraded. The developed methodology is applied to the single wafer plasma etching processes, which resulted in both higher within-a-wafer uniformity and compens- ation of the incoming material non-uniformity.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (A)
• /
• pp.52-53
• /
• 2007

• 대한안전경영과학회:학술대회논문집
• /
• 대한안전경영과학회 2004년도 추계학술대회
• /
• pp.453-457
• /
• 2004

EPC seeks to minimize variability by transferring the output variable to a related process input(controllable) variable. In the case of product control, a very reasonable objective is to try to minimize the variance of the output deviations from the target or set point. We consider an alternative EPC model with first-order autoregressive disturbance.

• 산업경영시스템학회지
• /
• 제14권24호
• /
• pp.187-192
• /
• 1991

We consider a filling process problem on a production line. Up to present this problem have examined by 100% inspection. Thus a target value is determined which takes into account the regular selling prices, the reprocess cost, the excess quality cost and the process variability and so on. However, in this paper we propose a solution under specified sampling plan when the inspection is nondestructive.

• Industrial Engineering and Management Systems
• /
• 제8권3호
• /
• pp.139-147
• /
• 2009

Control charts are used to distinguish between chance and assignable causes in the variability of quality characteristics. When a control chart signals that an assignable cause is present, process engineers must initiate a search for the assignable cause of the process disturbance. Identifying the time of a process change could lead to simplifying the search for the assignable cause and less process down time, as well as help to reduce the probability of incorrectly identifying the assignable cause. The change point estimation by likelihood theory and the built-in change point estimation in a control chart have been discussed until now. In this article, we discuss two kinds of process change point estimation when the CUSUM ($\bar{x}$, s) control chart for monitoring process mean and variance simultaneously is operated. Throughout some numerical experiments about the performance of the change point estimation, the change point estimation techniques in the CUSUM ($\bar{x}$, s) control chart are considered.

• 품질경영학회지
• /
• 제23권3호
• /
• pp.20-32
• /
• 1995

This paper is concerned with the economic selection of both the lower limit and the process mean for a continuous production process. Consider a production process where items are produced continuously. All of the items are subject to acceptance inspection. The items for which the measured values of the quality characteristic are larger than the lower limit are accepted, and those smaller than the lower limit are rejected and excluded from shipment. The process mean may be set higher to reduce the costs incurred by imperfect quality. Using a higher process mean, however, results in a higher production cost when production cost is an increasing function of the quality characteristic. Assuming that the quality characteristic is normally distributed with known variability, cost models are constructed which involve production cost, cost incurred by imperfect quality, rejection cost, and inspection cost. Methods of finding optimal values of the lower limit and the process mean are presented and numerical examples are given.

• Journal of Electrical Engineering and Technology
• /
• 제3권4호
• /
• pp.576-583
• /
• 2008

In this study, we attempt to design a real-time autonomic nervous system(ANS) evaluation system usable during exercise using heart instantaneous frequency(HIF). Although heart rate variability(HRV) is considered to be a representative signal widely used ANS evaluation system, the R-peak detection process must be included to obtain an HRV signal, which involves a high sampling frequency and interpolation process. In particular, it cannot accurately evaluate the ANS using HRV signals during exercise because it is difficult to detect the R-peak of electrocardiogram(ECG) signals with exposure to many noises during exercise. Therefore, in this study, we develop the ground for a system that can analyze an ANS in real-time by using the HIF signal circumventing the problem of the HRV signal during exercise. First, we compare the HRV and HIF signals in order to prove that the HIF signal is more efficient for ANS analysis than HRV signals during exercise. Further, we performed real-time ANS analysis using HIF and confirmed that the exerciser's ANS variation experiences massive surges at points of acceleration and deceleration of the treadmill(similar to HRV).