• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.201-202
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• 1998

In this paper we suggested an automated method for detecting and counting rapid eye movement(REM) using EOG during sleep. This method is formulated by two step fuzzy logic. At first step, the velocity and the distance of single channel eye movement are used for the fuzzy input to get the possibility of being REM at each EOG. At second step, the two possibility values of both EOG from the first step and the correlation coefficient of both eye movements are used for the fuzzy logic input, and the output is the final possibility of being Rapid Eye Movement. We applied this algorithm to the normal and narcoleptic sleep data and compared the difference. We found the possibility that the count of REM can be a parameter that has significant physiological meanings.

• The Korean Journal of Cytopathology
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• v.8 no.2
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• pp.129-134
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• 1997

To distinguish reactive mesothelial cells from malignant cells in body fluid, we applied silver staining of nucleolar organizer regions(AgNORs) to ethanol fixed cytologic preparations. Fifty aspirated samples of benign(22 cases) and malignant(26 cases) body fluids were studied using the one step silver staining method. Two cytologically atypical samples were also included in the study. In malignant cases the mean AgNOR count was $3.56{\pm}0.81$, while in benign cases the mean AgNOR count was $2.02{\pm}0.33$. The difference of AgNOR counts between these two groups were statistically significant(p<0.001). The mean of atypical cases was 2.91. Both were diagnosed as malignant in follow-up cytology. In malignant effusions, there is statistically significant difference in AgNOR counts between cells forming complex papillae or clusters and singly scattered cells(p<0.05), $3.29{\pm}0.95\;and\;3.83{\pm}0.55$, respectively. We concluded that AgNOR count appears to be useful as a diagnostic tool especially when the cytologic differentiation is difficult.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.551-559
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• 2017

In this paper, a real-time training method to improve the performance of bearing fault diagnosis. The traditional bearing fault diagnosis cannot classify a condition which is not trained by the classifier. The proposed 4-step method trains and recognizes new condition in real-time, thereby it can classify the condition accurately. In the first step, we calculate the maximum distance value for each class by calculating a Euclidean distance between a feature vector of each class and a centroid of the corresponding class in the training information. In the second step, we calculate a Euclidean distance between a feature vector of new acquired data and a centroid of each class, and then compare with the allowed maximum distance of each class. In the third step, if the distance between a feature vector of new acquired data and a centroid of each class is larger than the allowed maximum distance of each class, we define that it is data of new condition and increase count of new condition. In the last step, if the count of new condition is over 10, newly acquired 10 data are assigned as a new class and then conduct re-training the classifier. To verify the performance of the proposed method, bearing fault data from a rotating machine was utilized.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.491-491
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• 2000

In this paper, we report the results about the rotational control count on DC motor to drive the mobile vehicle as a first step of the research for the realization of the mobile vehicle with the artificial brain. First of all, we introduce the configuration of the mobile vehicle. This mobile vehicle has one CCD camera driven by a rear wheel. Secondly we show the control methods. This research is adopted the various controls. Finally we report the experimental methods and results and we describe the conclusion of this research.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.9
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• pp.420-422
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• 2006

This paper proposes a new method to count the number of steps for personal navigation systems. The proposed method resolves the mis-counting problem caused by the variation of the ground and walking behavior. To this end, a 2-axis accelerometer is utilized and a reliable step counting algorithm is developed. Experimental test was carried out to show the effectiveness of the proposed method. Test results show that the proposed method gives a robust performance for several types of ground and walking behavior.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.177-187
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• 2020

This article is concerned with the issue of forecasting and evaluation of threshold-asymmetric volatility models for time series of count data. In particular, threshold integer-valued models with conditional Poisson and conditional negative binomial distributions are highlighted. Based on the parametric bootstrap method, some evaluation measures are discussed in terms of one-step ahead forecasting. A parametric bootstrap procedure is explained from which directional measure, magnitude measure and expected cost of misclassification are discussed to evaluate competing models. The cholera data in Bangladesh from 1988 to 2016 is analyzed as a real application.

• Korean Journal of Artificial Intelligence
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• v.8 no.1
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• pp.1-6
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• 2020

The Recently there has been a growing interest in health care due to the COVID-19 situation. In this paper, we intend to develop a healthcare monitoring system to provide users with smart healthcare systems in line with the healthcare 3.0 era. The system consists of a wireless network between various sensors, Android smartphones, and OLEDs using Bluetooth, and through this, a health care monitoring system capable of collecting user's biometric information and managing health by receiving data values of sensors connected to Arduino. In conclusion, the user's BPM value was calculated using the heart rate sensor, and the exercise intensity can be adjusted through this. In addition, a step derivation algorithm is implemented using an acceleration sensor, and calorie consumption can be measured using the step and weight values. As such, the heart rate, step count, calorie consumption data can be transmitted to a smartphone application through a Bluetooth module and output, and can be output to an OLED for users who are not easy to access the smartphone. This healthcare monitoring system can be applied to various groups and technologies.

• Journal of the Korean Dietetic Association
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• v.11 no.2
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• pp.159-169
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• 2005

The purpose of this study was to assess the energy expenditure and investigate the relationship between related variables in 70 female university students. Resting energy expenditure estimated by Harris-Benedict formula, WHO/NAO/FAO formula and various formulas based on body weight and body surface area were 1366.9$\pm$74.4kcal/day, 1287.8$\pm$106.6kcal/day, 1171.4$\pm$155.8kcal/day and 1342.0$\pm$97.4kcal/day. Measured resting energy expenditure by indirect calorimetry(Model : Metavine and TrueOne2400) were 1582.0$\pm$150.1kcal/day and 1268.2$\pm$152.9kcal/day, respectively. Average step number per day was 11981.2$\pm$3014.4 steps and average step number per hour was 746.1$\pm$198.0 steps/hr. Daily energy expenditure by using Harris-Benedict formula, body weight formula, body surface area formula, WHO/NAO.FAO formula and 15-min check list formula were 2374.7$\pm$249.6kcal, 2033.5$\pm$313.2kcal, 2331.2$\pm$266.0kcal, 2240.8$\pm$185.5kcal and 2195.5$\pm$398.3kcal. Meanwhile energy intake of subjects was 1714.9$\pm$551.2 kcal. Daily energy expenditure has positive correlation(r=0.262) with daily step number. And there was significant positive correlations(r=0.35-0.68) between various daily energy expenditures and muscle mass. These results suggested that increase of daily step number by using pedometer is good method to increase daily energy expenditure. In particular, increase in step number can reinforce the amounts of muscle.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.569-575
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• 2013

This paper proposes a method for PDR (Pedestrian Dead-Reckoning) using a low cost IMU. Generally, GPS has been widely used for localization of pedestrians. However, GPS is disabled in the indoor environment such as in buildings. To solve this problem, this research suggests the PDR scheme with an IMU attached to the pedestrian's waist. However, despite the fact many methods have been proposed to estimate the pedestrian's position, but their results are not sufficient. One of the most important factors to improve performance is, a new calibration method that has been proposed to obtain the reliable sensor data. In addition to this calibration, the PDR method is also proposed to detect steps, where estimation schemes of step length, attitude, and heading angles are developed. Peak and zero crossings are detected to count the steps from 3-axis acceleration values. For the estimation of step length, a nonlinear step model is adopted to take advantage of using one parameter. Complementary filter and zero angular velocity are utilized to estimate the attitude of the IMU module and to minimize the heading angle drift. To verify the effectiveness of this scheme, a real-time system is implemented and demonstrated. Experimental results show an accuracy of below 1% and below 3% in distance and position errors, respectively, which can be achievable using a high cost IMU.

• Food Science and Biotechnology
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• v.15 no.5
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• pp.773-777
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• 2006

Growth of Bacillus cereus was assessed during the storage of seasoned soybean sprouts at 0,5, 10, and $15^{\circ}C$. No lag time in its growth curve was observed and thus the specific growth rate of B. cereus in the exponential growth phase was estimated for bootstrapped microbial count data. The distribution of the specific growth rate could be explained by the BetaGeneral distribution function, and temperature dependence was described by the Ratkowsky square root model. The temperature dependence of the growth could be successfully incorporated into the differential equation of microbial growth to predict the B. cereus count on the seasoned soybean sprouts under fluctuating temperature conditions. Safe shelf lives with different probabilities to reach $10^5\;CFU/g$ were presented at four different temperatures, considering the variation in initial contamination and specific growth rate by the Monte Carlo method and 2-step bootstrapping, respectively. Safe shelf lives defined as the time with a probability of less than 0.1% of reaching the critical limit, were 13.4, 5.2, 3.6, and 2.8 days at 0, 5, 10, and $15^{\circ}C$, respectively.