• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.4
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• pp.391-399
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• 2012

This study helps out-size consumers purchase swimsuits and improves fitness by classifying the torso of middle-aged obese women; in addition, it creates a size system based on each size interval for obese types. The criteria for subjects in this study were over 25kg/$m^2$ of the BMI, over 85cm of waist, and over 95cm of bust; 199 females were surveyed. Three torso types were categorized by a cluster analysis into X type (the vertical size of hip girth was the biggest of the three and the waist was slender), H-O type (larger than other groups in bust girth with more fat above the circumstance of the abdomen), and Y type (the upper half of body development type and lower body fatness were between those of type X and those of type H-O). As a consequence of size system establishment according to obesity types, the basic body sizes and reference body sizes were different according to types even in commonly-appeared size names at sections of respective types. The research findings show the necessity to understand obesity types according to bust girth and hip girth sizes that represent basic sizes as well as to design patterns in consideration of the characteristics of obese body shapes when swimsuits are designed for obese groups. The findings can be used as basic data to decide the desirable output of production according to respective body types.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.179-187
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• 2012

Power saving is one of the most important features that extends the lifetime of portable devices in mobile wireless networks. The IEEE 802.16e mobile broadband wireless access system adopts a power saving mechanism with a binary truncated exponent algorithm for determining sleep intervals. When using this standard power saving scheme, there is often a delay before data packets are received at the mobile subscriber station (MSS). In order to extend the lifetime of a MSS, the battery energy must be used efficiently. This paper presents a dynamically alternating sleep interval scheduling algorithm as a solution to deal with the power consumption problem. We take into account different traffic classes and schedule a proper sequence of power saving classes. The window size of the sleep interval is calculated dynamically according to the packet arrival rate. We make a tradeoff between the power consumption and packet delay. The method achieves the goal of efficiently reducing the listening window size, which leads to increased power saving. The performance of our proposed scheme is compared to that of the standard power saving scheme. Simulation results demonstrate the superior performance of our power saving scheme and its ability to strike the appropriate performance balance between power saving and packet delay for a MSS in an IEEE 802.16e mobile broadband wireless access system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.6
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• pp.293-305
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• 2005

This paper describes an improved Prony method in its speed, accuracy and reliability by efficiently determining the optimal sampling interval with use of DFT (discrete Fourier transformation). In the Prony method the computation time is dominated by the size of the linear prediction matrix, which is given by the number of data times the modeling order The size of the matrix in a general Prony method becomes large because of large number of data and so does the computation time. It is found that the Prony method produces satisfactory results when SNR is greater than three. The maximum sampling interval resulting minimum computation time is determined using the fact that the spectrum in DFT is inversely proportional to sampling interval. Also the process of computing the modes is made efficient by applying Hessenberg method to the companion matrix with complex shift and computing selectively only the dominant modes of interest. The proposed method is tested against the 2003 KEPCO system and found to be efficient and reliable. The proposed method may play a key role in monitoring in real time low frequency oscillations of power systems .

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.565-570
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• 2013

Previous researches on mining sequential patterns mainly focused on discovering patterns from the point-based event. Interval events with a time interval occur in the real world that have the start and end point. Existing interval pattern mining methods that discover relationships among interval events based on the Allen operators have some problems. These are that interval patterns having three or more interval events can be interpreted as several meanings. In this paper, we propose the I_TPrefixSpan algorithm, which is an efficient sequence pattern mining technique for removing ambiguity in the Interval Patterns Mining. The proposed algorithm generates event sequences that have no ambiguity. Therefore, the size of generated candidate set can be minimized by searching sequential pattern mining entries that exist only in the event sequence. The performance evaluation shows that the proposed method is more efficient than existing methods.

• Fashion & Textile Research Journal
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• v.11 no.6
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• pp.904-910
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• 2009

The aim of this study is to help out-size consumers purchase the ready-made clothes and improve clothing fitness by classifying the lower bodies of abdomen-obese adult males and by setting up some size system according to each size interval of obesity types. The including criteria for subjects in this study was over 25 kg/$m^2$ of the BMI, over 90 cm of waist, and over 0.85 of WHR, and a total of 538 adult males satisfying them were enrolled. Results are as follows; 1st, the higher the age bracket was, the more increase in each age bracket's lower-degree obesity rate there was along with the more decrease in moderate-degree, while the higher the age bracket was, the more increasing tendency toward each age bracket's abdominal obesity there was. 2nd, 3 clusters were categorized by cluster analysis, into abdominal obesity, high-degree-type, trapezoid-type and cylinder-type. And 3rd, as a consequence of size system establishment according to lower-body types, the basic body sizes and reference body sizes were different according to types even in commonly-appeared size names at sections of respective types. The research findings above suggests that it is necessary to figure out the obesity types according to waist and hip sizes representing basic sizes and to design the patterns in consideration of the characteristics of obese body shapes when lower-half body clothes are designed among obesity groups. And it may be used as a basic data to decide the desirable output of production according to respective body types.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1247-1253
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• 2008

In this paper, we propose a interval censored regression spline model with a variance function (non-constant variance that depends on a predictor). Simulation studies show our estimates from MCECM algorithm are consistent, but biased when the sample size is small because of boundary effects. Also, we examined how the distribution of $x_i$ affects the converging speed of these consistent estimates.

• Journal of Biomedical Engineering Research
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• v.31 no.4
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• pp.316-320
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• 2010

HRV(Heart rate variability) analysis parameter is widely used as an index to evaluate the autonomic nervous system and cardiac function. For reliable HRV analysis, we need to acquire the accurate ECG signals. Most of commercially available portable ECG devices have low sampling rate because of low power consumption and small size issues, which make it difficult to measure RR-interval accurately. This study is to improve the accuracy of RR-interval by developing R-wave interpolation technique, based on the morphological characteristics of the QRS complex. When the developed method was applied to ECG obtained at 200 Hz and the results were compared with 1000 Hz reference device, the error range decreased by 1.33 times in sitting and by 2.38 times in cycling exercise. Therefore, the proposed interpolation technique is thought to be useful to improve the accuracy of R-R interval in the portable ECG device with low sampling rate.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.377-393
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• 2003

Several confidence interval estimates for the difference of two binomial proportions were introduced. Bootstrap confidence interval is also suggested. We examined the over estimation property of approximate intervals and under estimation trend of exact intervals for the difference of proportions. We compared these confidence intervals based on the average coverage probability, expected width and skewness measure. Particularly actual coverage probability were calculated by using the prior distribution of parameters. Monte Carlo simulation for small sample size is conducted. Some interesting contour plots of average coverage probability and marginal plots for several interval estimates are presented.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.31-36
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• 2008

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the enviromuent. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• Journal of the Korean Society of Safety
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• v.14 no.3
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• pp.25-32
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• 1999

This study has been performed to investigate the stress distribution around defects that behave as stress concentrators. Besides, the effect of stress interaction effects on the initiation of primary cracks were also investigated by rotary bending fatigue tests which were performed with specimens drilled micro surface defects and the stress distribution was analyzed using Finite Element Method. In addition, the stress interaction effects around defects and cracks were investigated by comparing the results of experiments and F.E.M. The results obtained are summarized as follows ; 1) Area which slip and micro cracks initiated at micro surface defects is between the maximum shear stress points and this area is over than ${\pm}30^{\circ}$ from the maximum stress point along the defect edge. 2) The stress interaction effect for the small size defect is larger than that of large size defect when the interval between them is near 3) Interval which there is no shear stress interaction effect analyzed by F.E.M. is larger than that of experimental results.