• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.387-392
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• 2007

Turbomachinery such as turbines, pumps and compressors, which are installed in transportation systems such as warships, submarines and space vehicles, etc., often perform crucial missions and are exposed to potential dangerous impact environments such as base-transferred shock forces. To protect turbomachinery from excessive shock forces, it may be needed to accurately analyze transient responses of rotors, considering the dynamics of mount designs to be applied with. In this study a generalized FE transient response analysis model, introducing relative displacements, is firstly proposed to accurately predict transient responses of a flexible rotor-bearing system with mount systems to base-transferred shock forces. In the transient analyses the state-space Newmark method of a direct time integration scheme is utilized, which is based on the average velocity concept. Results show that for the identical mount systems considered, the proposed FE-based detailed flexible rotor model yields more reduced transient vibration responses to the same shocks than a conventional simple model or a Jeffcott rotor. Hence, in order to design a rotor-bearing system with a more compact light-weighted mount system, preparing against any potential excessive shock, the proposed FE transient response analysis model herein is recommended.

• Convergence Security Journal
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• v.11 no.3
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• pp.19-24
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• 2011

Software failure time presented in the literature exhibit either constant monotonic increasing or monotonic decreasing, For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, time series analys is used in the simple moving average and weighted moving averages, exponential smoothing method for predict the future failure times, Empirical analysis used interval failure time for the prediction of this model. Model selection using the mean square error was presented for effective comparison.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.3
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• pp.8-16
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• 2013

Determining relative importance among many quality attributes under financial constraints is an important task. The weighted value of an attribute particularly in QFD, will influence on engineering characteristics and this will eventually influence the whole manufacturing process such as parts deployment, process planning, and production planning. Several scholars have suggested weighting formulas using CSC (Customer Satisfaction Coefficient) in the Kano model. However, previous research shows that the validity of the CSC approaches has not been proved systematically. The aim of the present study is to address drawbacks of CSC and to develop APC (Average Potential Coefficient), a new approach for weighting of quality attributes. For this, the current study investigated 33 quality attributes of e-learning and conducted a survey of 375 university students for the results of APC, the Kano model, and the direct importance of the quality attributes. The results show that the proposed APC is better than other approaches based on the correlation analysis with the results of direct importance. An analysis of e-leaning's quality perceptions using the Kano model and suggestions for improving e-learning's service quality are also included in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4816-4834
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• 2020

This paper proposes transfer learning and fine-tuning techniques for a deep learning model to detect three distinct brain tumors from Magnetic Resonance Imaging (MRI) scans. In this work, the recent YOLOv4 model trained using a collection of 3064 T1-weighted Contrast-Enhanced (CE)-MRI scans that were pre-processed and labeled for the task. This work trained with the partial 29-layer YOLOv4-Tiny and fine-tuned to work optimally and run efficiently in most platforms with reliable performance. With the help of transfer learning, the model had initial leverage to train faster with pre-trained weights from the COCO dataset, generating a robust set of features required for brain tumor detection. The results yielded the highest mean average precision of 93.14%, a 90.34% precision, 88.58% recall, and 89.45% F1-Score outperforming other previous versions of the YOLO detection models and other studies that used bounding box detections for the same task like Faster R-CNN. As concluded, the YOLOv4-Tiny can work efficiently to detect brain tumors automatically at a rapid phase with the help of proper fine-tuning and transfer learning. This work contributes mainly to assist medical experts in the diagnostic process of brain tumors.

• Journal of Animal Science and Technology
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• v.65 no.3
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• pp.627-637
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• 2023

As the population and income levels rise, meat consumption steadily increases annually. However, the number of farms and farmers producing meat decrease during the same period, reducing meat sufficiency. Information and Communications Technology (ICT) has begun to be applied to reduce labor and production costs of livestock farms and improve productivity. This technology can be used for rapid pregnancy diagnosis of sows; the location and size of the gestation sacs of sows are directly related to the productivity of the farm. In this study, a system proposes to determine the number of gestation sacs of sows from ultrasound images. The system used the YOLOv7-E6E model, changing the activation function from sigmoid-weighted linear unit (SiLU) to a multi-activation function (SiLU + Mish). Also, the upsampling method was modified from nearest to bicubic to improve performance. The model trained with the original model using the original data achieved mean average precision of 86.3%. When the proposed multi-activation function, upsampling, and AutoAugment were applied, the performance improved by 0.3%, 0.9%, and 0.9%, respectively. When all three proposed methods were simultaneously applied, a significant performance improvement of 3.5% to 89.8% was achieved.

• Journal of Preventive Medicine and Public Health
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• v.33 no.3
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• pp.343-348
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• 2000

Objectives : This study was conducted to integrate the results of studies assessing the association between chronic noise exposure and blood pressure. Methods : Using a MEDLINE search with noise exposure, blood pressure and hypertension as key words, we retrieved articles from the literature that were published from 1980 to December 1999. The criteria for quality evaluation were as follows: 1) the study subjects must have been workers employed at a high noise level area 2) The paper should use average and cumulative noise exposure as method for exposure evaluation. 3) Blood pressure in each article should be reported in a continuous scale Among the 77 retrieved articles, six studies were selected for quantitative meta-analysis. Before the integration of the regression coefficients for the association between blood pressure and noise level, homogeneity tests were conducted. Results : All studies were a cross-sectional design and the study subjects were industrial workers. Five papers used a time-weighted average for noise exposure and only one paper calculated the cumulative noise exposure level. The measurement of blood pressure in the majority of studios were accomplished in a resting stale, and used an average of two or more readings. The homogeneity of studies was rejected in a fixed effect model, so we used the results in a random effect model. The results of the quantitative meta-analysis, the weighted regression coefficient of noise associated with systolic blood pressure and diastolic blood pressure were 0.05 (95% confidence interval [CI]: -0.03, 0.13) and 0.06 (95% CI: -0.01, 0.13), respectively. Conclusions : Our results suggested that chronic exposure to industrial noise does not cause elevated blood pressure.

• The Journal of Korean Association of Computer Education
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• v.10 no.3
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• pp.19-29
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• 2007

The informationization policies undertaken in concentration only on the national economic growth invited the unbalance between technology and social culture, displayed the serious reverse function phenomena, and these problems threatened the personal identity of individual in the cyber space. In this study, we developed an index model on the information and communication ethics where the national level of information and communication ethics can be examined. For this purpose, based on diverse previous research data, the areas of the ethical indicators in information and communication has been developed through the brain storming of the research staff. Through the consultation with experts, the feasibility and representation as index was heightened, and the weighted values to the each index was provided by the AHP method. The outcome of questionnaires from the information users and information providers (great portals) was also reflected in simple average method into the calculation of the weighted value to the each index element.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.179-184
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• 2004

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for process quality improvement. SPC reduces process variability by detecting and eliminating special causes of process variation, while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been need for an integrated process control (IPC) procedure which combines the two strategies. This article considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process disturbance model under consideration is an IMA(1,1) model with a location shift. The EPC part of the scheme adjusts the process, while the SPC part of the scheme detects the occurrence of a special cause. For adjusting the process repeated adjustment is applied by compensating the predicted deviation from target. For detecting special causes the two kinds of exponentially weighted moving average (EWMA) control chart are applied to the observed deviations: One for detecting location shift and the other for detecting increment of variability. It was assumed that the adjustment of the process under the presence of a special cause may change any of the process parameters as well as the system gain. The effectiveness of the IPC scheme is evaluated in the context of the average cost per unit time (ACU) during the operation of the scheme. One major objective of this article is to investigate the effects of the process parameters to the ACU. Another major objective is to give a practical guide for the efficient selection of the parameters of the two EWMA control charts.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.457-468
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• 2007

This paper proposes an adaptive moving average (A-MA) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI A-MA chart is to adjust sampling intervals as well as to accumulate previous samples selectively in order to increase the sensitivity. The VSI A-MA chart employs a threshold limit to determine whether or not to increase sampling rate as well as to accumulate previous samples. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI A-MA chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The control length L is introduced to prevent small mean shifts from being undetected for a long period. A Markov chain model is employed to investigate the VSI A-MA sampling process. Formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI A-MA chart is proposed. Comparative studies show that the proposed VSI A-MA chart is uniformly superior to the adaptive Cumulative sum (CUSUM) chart and to the Exponentially Weighted Moving Average (EWMA) chart, and is comparable to the variable sampling size (VSS) VSI EWMA chart with respect to the ATS performance.

• Korean Journal of Optics and Photonics
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• v.14 no.3
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• pp.272-278
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• 2003

We studied patterned ITO layers of PDP thin films on glass substrates using spectroscopic ellipsometry. The optical property of ITO is expressed with the optical model based on two Lorentz oscillators. The effect of patterned ITO is calculated by taking the weighted average of reflectance in proportion to ITO coverage. The relative coverage of ITO is determined by using the model analysis of spectroellipsometric data. The difference of ITO coverage obtained by the best-fit model analysis of ellipsometric spectra to the expected one is critically examined and suggestions are made to minimize the observed discrepancy.