• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.382-388
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• 2007

In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• Fashion & Textile Research Journal
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• v.14 no.2
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• pp.261-268
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• 2012

The purpose of this study is to investigate problems of design, fitness, suitability for movement, and wearing comfort of jumper for Korean military tank drivers through analysis of actual wearing condition by questionnaire and field evaluation and to provide basic data for developing its improved design. The survey was done for 477 military tank drivers and evaluation was performed using thermal manikin to measure insulation. The overall satisfaction for design of jumper for military tank driver was over 3.5(likert scale). The overall satisfaction for fitness of jumper for military tank driver was also over 3.5. The satisfactions for material was between 2.39 and 3.13 and the satisfaction for pilling property was the lowest, followed by static property and shape stability after laundering. The satisfactions for movement suitability were standing(3.81), sitting(3,38), raising hand(forward: 2.90, sideward: 3.01), respectively. In insulation evaluation of jumper for military tank drivers and outwears(jacket, jumper), the insulation of jumper for military tank drivers was lower than outwear(jumper) and same with outwear(jacket). The insulation in dynamic and still condition(without wind) of jumper for military tank driver was 0.37clo and 0.31clo, respectively. Its decreation rate in dynamic condition comparing to still condition was 59% which was lower than jacket(0.73clo) and jumper(1.15clo).

• Journal of muscle and joint health
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• v.9 no.1
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• pp.28-39
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• 2002

Objective. The 12 forms of Sun-style Tai Chi exercise has been developed specifically for arthritis patients in order to reduce their symptoms and to improve physical functioning. This quasi-experimental study examined the changes in pain, balance, muscle strength and physical functioning in women with osteoarthritis at the completion of the 12 week Tai Chi exercise program. Methods. The patients with osteoarthritis who signed the consent form were screened by their primary physician according to the inclusion criteria and invited to the study. Total of 66 osteoarthritis women with an average age of 63 years were participated in the Tai Chi exercise. At the completion of 12 weeks, 34 patients completed both pretest and posttest measures with 48% of overall dropout rate. Outcome measures were physical symptoms, balance, muscle strength, physical functioning, and depression. Paired t-test was utilized to examine differences between pre and post-measures. Results. After participating in the Tai Chi exercise program, the women with osteoarthritis showed significant improvements in their physical fitness measures, and consequently in their physical functioning. In physical fitness test, there were significant improvements in balance, flexibility, muscle strengths of knee, grip, and back muscles after the Tai Chi exercise. However, No significant differences were found in pain and stiffness of their knee joints and depression measure. Conclusion. The 12 forms of Tai Chi exercise has been found safely applicable to the older women with osteoarthritis for 12 weeks, and effective in improving balance, flexibility, and muscle strengths, and consequently lessening difficulties of performing their activities of daily life.

• Journal of Fashion Business
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• v.14 no.4
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• pp.161-173
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• 2010

This study aims to examine for efficient production methods of custom-tailored clothing and application of 3D virtual clothing system in custom-tailored clothing market, by producing and analyzing both real clothing and 3D virtual clothing. For this study, a middle-aged woman is selected as the subject figure and one-piece is selected as the experimental clothes item. In real clothing, I conducted the wearing evaluation for experts and the subject figure. And In the virtual clothing, I conducted the wearing evaluation with i-Designer using 3D virtual clothing on simulation program. There are some differences between the data from body scanning and the real body size. In the custom-tailored clothing market in which the fitness is important, the research which measures the more exact data is needed. And in the case of complicate design, the functions which measure the activity and the fitness variously and correct the parts of curves are needed. This study experiments the availability of application of 3D Virtual Clothing System in custom-tailored clothing market by selecting one-piece as the experimental clothes item. So the follow-up studies for the other designs and fabrics are needed. Also, if the studies for checking the clothes pressure, the amount of composure, the space between skin and clothing when the virtual model wearing clothes is walking or shaking his arms are proceeding, then 3D virtual clothing System is applicable in custom-tailored clothing market. But there are some restrictions and lack of education in virtual clothing System yet, and it makes hard for workers in clothing market to use it in real production. However, 3D virtual clothing System will be practical in real market if there would be more research on its usability and practicality, and workers in clothing market can be easily educated on techniques of 3D virtual clothing system.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.415-420
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• 2013

U-WHS refers to a means of remote health monitoring service to combine fitness with wellbing. U-WHS is a system which can measure and manage biometric information of patients without any limitation on time and space. In this paper, we performed in order to look into the influence that the encryption module influences on the communication evaluation in the biometric information transmission gone to the smart mobile device and Hospital Information System.In the case of the U-WHS model, the client used the Objective-c programming language for software development of iOS Xcode environment and SEED and HIGHT encryption module was applied. In the case of HIS, the MySQL which is the Websocket API of the HTML5 and relational database management system for the client and inter-server communication was applied. Therefore, in WIFI communication environment, by using wireshark, data transfer rate of the biometric information, delay and loss rate was checked for the evaluation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2158-2165
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• 2007

In this paper, a Modified Fuzzy C-Means algorithm with Gaussian Weights(MFCM_GW) is presented for nonlinear blind channel equalization. The proposed algorithm searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function and Gaussian weighted partition matrix instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function(RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a simplex genetic algorithm(GA), a hybrid genetic algorithm(GA merged with simulated annealing(SA): GASA), and a previously developed version of MFCM. It is shown that a relatively high accuracy and fast search speed has been achieved.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.45-55
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• 2015

In this paper, we consider curriculum mining as an application of process mining in the domain of education. The basic objective of the curriculum mining is to construct a registration pattern model by using logs of registration data. However, subject registration patterns of students are very unstructured and complicated, called a spaghetti model, because it has a lot of different cases and high diversity of behaviors. In general, it is typically difficult to develop and analyze registration patterns. In the literature, there was an effort to handle this issue by using clustering based on the features of students and behaviors. However, it is not easy to obtain them in general since they are private and qualitative. Therefore, in this paper, we propose a new framework of curriculum mining applying K-means clustering based on subject attributes to solve the problems caused by unstructured process model obtained. Specifically, we divide subject's attribute data into two parts : categorical and numerical data. Categorical attribute has subject name, class classification, and research field, while numerical attribute has ABEEK goal and semester information. In case of categorical attribute, we suggest a method to quantify them by using binarization. The number of clusters used for K-means clustering, we applied Elbow method using R-squared value representing the variance ratio that can be explained by the number of clusters. The performance of the suggested method was verified by using a log of student registration data from an 'A university' in terms of the simplicity and fitness, which are the typical performance measure of obtained process model in process mining.

• PNF and Movement
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• v.19 no.3
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• pp.331-340
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• 2021

Purpose: The purpose of this study was to investigate the differences in body composition, upper and lower limb muscle strength, and functional physical ability in urban-dwelling elderly women with or without obesity. Methods: All study participants were assigned to the normal weight group (n=8, BMI<25) and the obesity group (n=7, BMI>25) based on their obesity rate. Anthropometric measurement was conducted and body composition was measured. For the upper and lower limb strength, grip strength and maximal isometric knee extension and flexion were evaluated by a dynamometer. The senior fitness test was performed to measure functional ability. Data analysis was conducted by the independent t-test and the alpha level was set at 0.05. Results: The waist, hips, and thighs of obese elderly women were thicker than those of normal-weight elderly women. This physical difference resulted from body fat mass, not muscle mass. Despite a similar level of limb muscle mass between the two groups, the upper limb grip strength was higher (24.00% for left, 19.95% for right) in the normal-weight women than the obese women (p<0.05), but otherwise there was no difference in maximal knee flexion or extension isometric strength. Functional physical ability showed no difference in a 30-second chair sit and stand test and a six-minute walk test, but a 30-second arm-curl (11.00% for left, 14.81% for right), back stretch (8.54cm for left, 8.99cm for right), chair sit and reach (9.22cm for left, 6.24cm for right), and 2.44 meter round trip walk (0.62 sec, 9.39%) were faster in performance for normal-weight elderly women than obese elderly women (p<0.05). Conclusion: Taken together, despite similar levels of upper and lower extremity muscle mass, normal-weight elderly women showed higher performance in upper limb strength, flexibility, and agility than obese elderly women, but there was no difference in lower extremity functional muscle strength and cardiopulmonary endurance.

• Advances in concrete construction
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• v.14 no.3
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• pp.185-194
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• 2022

For producing cement and concrete, the construction field has been encouraged by the usage of industrial soil waste (or) secondary materials since it decreases the utilization of natural resources. Simultaneously, for ensuring the quality, the analyses of the strength along with durability properties of that sort of cement and concrete are required. The prediction of strength along with other properties of High-Performance Concrete (HPC) by optimization and machine learning algorithms are focused by already available research methods. However, an error and accuracy issue are possessed. Therefore, the Enhanced Deep Neural Network (EDNN) based strength along with durability prediction of HPC was utilized by this research method. Initially, the data is gathered in the proposed work. Then, the data's pre-processing is done by the elimination of missing data along with normalization. Next, from the pre-processed data, the features are extracted. Hence, the data input to the EDNN algorithm which predicts the strength along with durability properties of the specific mixing input designs. Using the Switched Multi-Objective Jellyfish Optimization (SMOJO) algorithm, the weight value is initialized in the EDNN. The Gaussian radial function is utilized as the activation function. The proposed EDNN's performance is examined with the already available algorithms in the experimental analysis. Based on the RMSE, MAE, MAPE, and R² metrics, the performance of the proposed EDNN is compared to the existing DNN, CNN, ANN, and SVM methods. Further, according to the metrices, the proposed EDNN performs better. Moreover, the effectiveness of proposed EDNN is examined based on the accuracy, precision, recall, and F-Measure metrics. With the already-existing algorithms i.e., JO, GWO, PSO, and GA, the fitness for the proposed SMOJO algorithm is also examined. The proposed SMOJO algorithm achieves a higher fitness value than the already available algorithm.

• Korean Medical Education Review
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• v.23 no.1
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• pp.37-45
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• 2021

In light of the need for a tool to evaluate the clinical practice education environment as perceived by medical and nursing students, this study is was conducted to develop and validate the Korean version of the Undergraduate Clinical Education Environment Measure (K-UCEEM) as a measurement tool for managing the clinical practice education climate and quality of education. For validation, the UCEEM consisting of 25 items developed by Pia Strand in 2013 was adapted according to standard translation procedures. The K-UCEEM questionnaire was administered to 73 medical students and 135 nursing students who participated in clinical practice at one medical institution. Exploratory factor analysis and confirmatory factor analysis were conducted to confirm the validity of the instrument's structure. In order to determine referential validity, the relationships among stresses in clinical practice were examined, and differences in factor scores were compared by gender and college. It was confirmed that the scale of 24 items and five factors showed a moderate model fitness index. The reliability of the factors ranged from 0.786 to 0.867. In addition, all five factors were found to have negative correlations with the clinical practice stress sub-factor, and there were statistically significant differences by gender and college. Through this study, the validity and reliability of the K-UCEEM were verified. In the future, it is expected that further verification of the scale, as well as evaluation and improvement of the clinical practice education environment based on this scale, will occur.