• Journal of Fashion Business
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• v.23 no.1
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• pp.14-24
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• 2019

Various types of functional bedding for inducing and maintaining sleep, are developed and launched with the importance of improving health through sleep emphasized currently. The purpose of this study is to examine development status and direction of functional bedding in the $4^{th}$ Industrial Revolution era, through systematic classification of elements of IoT-based smart bedding cases actively developed as functional bedding at home and abroad. Through previous research, literature and Internet data, characteristics and functional extension of smart bedding and the background of smart bed development was analyzed. And it was analyzed that smart bedding pursues recent functionalism and convergence of physical and digital concept such as IoT or AI, and also mental value to improve sleep quality. As bedroom where smart bedding place in has the private and limited characteristics and users are in sleep-conscious, that hard to ensure power and discomfort in carrying are moderated and the aesthetic elements are not very important, and that the smart bedding performance while sleeping were affected on developmental background. Based on CES case study and analysis on how smart beds are functionally expanded from conventional bedding, smart beds have gained information through digital sensing, and common properties that can be controlled anytime, anywhere, using a smart phone. Some set up the right environment and pose, while others stimulate nerves directly as active intervention. It is expected that smart bedding will be developed to cure user's body and mind, through active intervention when sleeping.

• Korea Journal of Hospital Management
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• v.23 no.4
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• pp.53-64
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• 2018

Purposes: The hospitals needs to generate a minimum profit, in order to perform its own role such as providing high-quality medical services. The demand for hospital management is increasing, as the social demands are diversified and the financial transparency is emphasized. The purpose of this study is to compare hospitals management based on Dupont Identity, by various hospital classification. Methodology: This study is based on '2016 Statistics for Hospital Management' provided by the Korea Health Industry Development Institute. The hospitals were classified according to the scope of care, the type of establishment, the location, and the number of beds. We analyzed the general and financial characteristics of over 337 hospitals using the method of Dupont Identity. Findings: Net profit margin (PM) has the biggest impact on return of equity (ROE). By the number of beds, general hospital with 160-299 beds have the highest return on equity (ROE). By location, hospitals in local municipalities have higher return on equity than hospitals in urban municipalities. According to the type of establishment, public hospitals have lower business performance, and although they invest more than private hospitals. Practical Implications: This study can inspire interest and provide understanding in hospital management and financial structure, by analyzing through an intuitive indicator named Dupont identity. It is possible to provide basic data for hospital management methods for each financial elements, in order to increase the profitability of hospitals.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.24-34
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• 2019

In this research, a practical deep learning framework to differentiate the lesions and nodules in breast acquired with ultrasound imaging has been proposed. 7408 ultrasound breast images of 5151 patient cases were collected. All cases were biopsy proven and lesions were semi-automatically segmented. To compensate for the shift caused in the segmentation, the boundaries of each lesion were drawn using Fully Convolutional Networks(FCN) segmentation method based on the radiologist's specified point. The data set consists of 4254 benign and 3154 malignant lesions. In 7408 ultrasound breast images, the number of training images is 6579, and the number of test images is 829. The margin between the boundary of each lesion and the boundary of the image itself varied for training image augmentation. The training images were augmented by varying the margin between the boundary of each lesion and the boundary of the image itself. The images were processed through histogram equalization, image cropping, and margin augmentation. The networks trained on the data with augmentation and the data without augmentation all had AUC over 0.95. The network exhibited about 90% accuracy, 0.86 sensitivity and 0.95 specificity. Although the proposed framework still requires to point to the location of the target ROI with the help of radiologists, the result of the suggested framework showed promising results. It supports human radiologist to give successful performance and helps to create a fluent diagnostic workflow that meets the fundamental purpose of CADx.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.3
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• pp.51-59
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• 2019

Purpose : To evaluate the effect of comprehensive art therapy on physical function and activities of daily living in children with cerebral palsy (CP). Methods : Ten ambulant children with diplegic (n=8) or hemiplegic (n=2) CP participated in this study. All were randomly assigned to either the art therapy group (n=5) or the control group (n=5). Both groups received physical therapy based on neurodevelopmental techniques for 20 minutes a day, 1 day a week, for a period of 12 weeks. Children in the art therapy group received additional comprehensive art therapy for 70 minutes once a week for 3 months. Tests for various measurements-Motricity Index (MI) for strength, Trunk Control Test (TCT) for trunk ability, Gross Motor Function Measure (GMFM) and Gross Motor Function Classification System (GMFCS) for gross motor function, Denver Developmental Screening Test-II (DDST-II) for developmental milestones, Functional Independence Measure of Children (WeeFIM) for abilities to complete daily activities, Leg and Hand Ability Test (LHAT) for limb function-were performed before and after treatments. Results : The upper extremity and whole extremity strengths of MI, self-care and total scores of WeeFIM, and leg and arm functions of LHAT improved significantly only for individuals in the art therapy group after the art therapy (p<.05). The value of MI after treatment was at the upper extremity and whole extremity strengths the leg function of LHAT was also significantly improved compared to the control group (p<.05). Conclusion : This study revealed that comprehensive art therapy along with physiotherapy was effective in increasing upper extremity strength and leg ability in children with CP. This suggests that comprehensive art therapy may be a useful adjunctive therapy for children with CP.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.49-55
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• 2019

This paper presents a marker image evaluation method based on analysis of object distribution in images and classification of images with repetitive patterns for effective marker-based augmented reality (AR) system development. We measure the variance of feature point coordinates to distinguish marker images that are vulnerable to occlusion, since object distribution affects object tracking performance according to partial occlusion in the images. Moreover, we propose a method to classify images suitable for object recognition and tracking based on the fact that the distributions of descriptor vectors among general images and repetitive-pattern images are significantly different. Comprehensive experiments for marker images confirm that the proposed marker image evaluation method distinguishes images vulnerable to occlusion and repetitive-pattern images very well. Furthermore, we suggest that scale-invariant feature transform (SIFT) is superior to speeded up robust features (SURF) in terms of object tracking in marker images. The proposed method provides users with suitability information for various images, and it helps AR systems to be realized more effectively.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.5
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• pp.277-286
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• 2019

In this paper, we propose an efficient hyperplane generation technique to classify human activity from combination of events and sequence information obtained from multiple-event sensors. By generating hyperplane efficiently, our machine learning algorithm classify with less memory and run time than the LSVM (Linear Support Vector Machine) for embedded system. Because the fact that light weight and high speed algorithm is one of the most critical issue in the IoT, the study can be applied to smart home to predict human activity and provide related services. Our approach is based on reducing numbers of hyperplanes and utilizing robust string comparing algorithm. The proposed method results in reduction of memory consumption compared to the conventional ML (Machine Learning) algorithms; 252 times to LSVM and 34,033 times to LSTM (Long Short-Term Memory), although accuracy is decreased slightly. Thus our method showed outstanding performance on accuracy per hyperplane; 240 times to LSVM and 30,520 times to LSTM. The binarized image is then divided into groups, where each groups are converted to binary number, in order to reduce the number of comparison done in runtime process. The binary numbers are then converted to string. The test data is evaluated by converting to string and measuring similarity between hyperplanes using Levenshtein algorithm, which is a robust dynamic string comparing algorithm. This technique reduces runtime and enables the proposed algorithm to become 27% faster than LSVM, and 90% faster than LSTM.

• Physical Therapy Rehabilitation Science
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• v.8 no.3
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• pp.125-133
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• 2019

Objective: To compare the postural control between non-specific chronic low back pain (NSCLBP) subgroups and healthy people during dynamic balance performance using a modified Star Excursion Balance Test (mSEBT). Design: Cross-sectional study. Methods: Eighteen NSCLBP subjects (9 active extension pattern [AEP], 9 flexion pattern [FP]), and 10 healthy controls were enrolled in this study. All subjects performed mSEBT on their dominant leg on a force plate. Normalized reach distance and balance parameters, including the center of pressure (COP) displacement and velocity, were recorded. Results: There were significant differences in mean reach distances in both posterolateral and posteromedial (PM) reach directions between AEP and healthy subjects (p<0.001) and between FP and healthy subjects (p<0.001). However, there were no significant differences among the three groups in the anterior reach direction. Also, the results showed no significant differences in mean COP variables (velocity and displacement) between pooled NSCLBP and healthy subjects. However, the subjects were reclassified into AEP, FP and healthy groups and the results showed a significant difference in mean COP velocity in the PM direction between AEP and FP subjects (p=0.048), and between AEP and healthy subjects (p=0.024). Conclusions: The findings in this study highlight the heterogeneity of the individuals with NSCLBP and the importance of identifying the homogenous subgroups. Individuals with AEP and FP experience deficits in dynamic postural control compared to healthy controls. In addition, the findings of this study support the concept of the Multidimensional Classification System.

• Genomics & Informatics
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• v.16 no.4
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• pp.31.1-31.7
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• 2018

The prevalence of metabolic syndrome (MS) in the nonobese population is not low. However, the identification and risk mitigation of MS are not easy in this population. We aimed to develop an MS prediction model using genetic and clinical factors of nonobese Koreans through machine learning methods. A prediction model for MS was designed for a nonobese population using clinical and genetic polymorphism information with five machine learning algorithms, including naïve Bayes classification (NB). The analysis was performed in two stages (training and test sets). Model A was designed with only clinical information (age, sex, body mass index, smoking status, alcohol consumption status, and exercise status), and for model B, genetic information (for 10 polymorphisms) was added to model A. Of the 7,502 nonobese participants, 647 (8.6%) had MS. In the test set analysis, for the maximum sensitivity criterion, NB showed the highest sensitivity: 0.38 for model A and 0.42 for model B. The specificity of NB was 0.79 for model A and 0.80 for model B. In a comparison of the performances of models A and B by NB, model B (area under the receiver operating characteristic curve [AUC] = 0.69, clinical and genetic information input) showed better performance than model A (AUC = 0.65, clinical information only input). We designed a prediction model for MS in a nonobese population using clinical and genetic information. With this model, we might convince nonobese MS individuals to undergo health checks and adopt behaviors associated with a preventive lifestyle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5860-5876
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• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

• Food Science of Animal Resources
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• v.39 no.2
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• pp.332-344
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• 2019

The objective of this study was to investigate slaughtering performance, carcass grade, and quantitative traits of cuts according to seasonal influence by each month in pigs slaughtered in livestock processing complex (LPC) slaughterhouse in Korea, 2017. A total of 267,990 LYD ($Landrace{\times}Yorkshire{\times}Duroc$) pig data were used in this study. Results of slaughter heads, sex distribution, carcass weight, backfat thickness, grading class, total weight, and fat and lean meat percentages of each cut predicted by AutoFom III were obtained each month. The number of slaughtered pigs was the highest in early and late fall but the lowest in midsummer. Only in midsummer that the number of females was higher than that of castrates. During 2017, carcass weight was the lowest in late summer. Backfat thickness was in the range of 21-22 mm. In mid and late spring, pigs showed high 1+ grade ratio (37.05% and 36.15%, respectively). For traits of 11 cuts predicted by AutoFom III, porkbelly showed lower total weight, lean weight, and fat weight in midsummer to early fall but higher lean meat percentage compared to other seasons. Weights of deboned neck, loin, and lean meat were the highest in midfall compared to other seasons (p<0.05). In conclusion, characteristics of slaughtering, grading, and economic traits of pigs seemed to be highly seasonal. They were influenced by seasons. Results of this study could be used as basic data to develop seasonal specified management ways to improve pork production.