• Osteoporosis and Sarcopenia
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• v.3 no.3
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• pp.117-122
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• 2017

Sarcopenia is the degenerative loss of muscle mass and function with aging. Recently sarcopenia was recognized as a clinical disease by the International Classification of Disease, 10th revision, Clinical Modification. An imbalance between protein synthesis and degradation causes a gradual loss of muscle mass, resulting in a decline of muscle function as a progress of sarcopenia. Many mechanisms involved in the onset of sarcopenia include age-related factors as well as activity-, disease-, and nutrition-related factors. The stage of sarcopenia reflecting the severity of conditions assists clinical management of sarcopenia. It is important that systemic descriptions of the disease conditions include age, sex, and other environmental risk factors as well as levels of physical function. To develop a new therapeutic intervention needed is the detailed understanding of molecular and cellular mechanisms by which apoptosis, autophagy, atrophy, and hypertrophy occur in the muscle stem cells, myotubes, and/or neuromuscular junction. The new strategy to managing sarcopenia will be signal-modulating small molecules, natural compounds, repurposing of old drugs, and muscle-specific microRNAs.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.227-232
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• 2003

Recently, support vector learning attracts an enormous amount of interest in the areas of function approximation, pattern classification, and novelty detection. One of the main reasons for the success of the support vector machines(SVMs) seems to be the availability of global and sparse solutions. Among the approaches sharing the same reasons for success and exhibiting a similarly good performance, we have KFD(kernel Fisher discriminant) approach. In this paper, we consider the problem of function approximation utilizing both predetermined basis functions and the KFD approach for regression. After reviewing support vector regression, semi-parametric approach for including predetermined basis functions, and the KFD regression, this paper presents an extension of the conventional KFD approach for regression toward the direction that can utilize predetermined basis functions. The applicability of the presented method is illustrated via a regression example.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.183-191
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• 2020

Today, taking photos using smartphones has become an essential element of modern people. According to these social changes, modern people need a larger storage capacity, and the number of unnecessary photos has increased. To support the storage, cloud-based photo storage services from various platforms have appeared, and many people are using the services. As the number of photos increases, it is difficult for users to find the photos they want, and it takes a lot of time to organize. In this paper, we propose a cloud-based photo management service that facilitates photo management by classifying photos and recommending unnecessary photos using deep learning. The service provides the function of tagging photos by identifying what the subject is, the function of checking for wrongly taken photos, and the function of recommending similar photos. By using the proposed service, users can easily manage photos and use storage capacity efficiently.

• Physical Therapy Korea
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• v.28 no.4
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• pp.245-250
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• 2021

Background: The International Classification of Functioning, Disability, and Health-Child and Youth version (ICF-CY) is designed to record the characteristics of developing children and examine the influence of a child's environment on their health. Objects: This study was designed to determine the relationship between the clinically extracted ICF-CY items and The Pediatric Evaluation of Disability Inventory (PEDI) and Gross Motor Function Measure (GMFM) items. Methods: Thirty patients (17 males and 13 females) who were hospitalized in a pediatric and youth patient unit of a rehabilitation hospital were included in the study. Four health professionals (two physical therapists and two occupational therapists) working independently linked the PEDI and GMFM-66 items to the activity and participation domains of the ICF-CY. Results: There were strong negative correlations between the ICF-CY subdomains and the PEDI subdomains (r = 0.76-0.95; p < 0.05). There were positive strong correlations between the ICF-CY subdomains and the GMFM-66 (r = 0.76-0.95; p < 0.05). Conclusion: The extracted ICF codes were a valid tool for evaluating the mobility and selfcare conditions of cerebral palsy in the pediatric rehabilitation area.

• International Journal of Contents
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• v.8 no.2
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• pp.7-12
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• 2012

Imbalanced data sets are difficult to be classified since most classifiers are developed based on the assumption that class distributions are well-balanced. In order to improve the error back-propagation algorithm for the classification of imbalanced data sets, a new error function is proposed. The error function controls weight-updating with regards to the classes in which the training samples are. This has the effect that samples in the minority class have a greater chance to be classified but samples in the majority class have a less chance to be classified. The proposed method is compared with the two-phase, threshold-moving, and target node methods through simulations in a mammography data set and the proposed method attains the best results.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.59-64
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• 2015

In this paper, we found the usefulness of the deep belief network (DBN) in the fields of brain-computer interface (BCI), especially in relation to imagined speech. In recent years, the growth of interest in the BCI field has led to the development of a number of useful applications, such as robot control, game interfaces, exoskeleton limbs, and so on. However, while imagined speech, which could be used for communication or military purpose devices, is one of the most exciting BCI applications, there are some problems in implementing the system. In the previous paper, we already handled some of the issues of imagined speech when using the International Phonetic Alphabet (IPA), although it required complementation for multi class classification problems. In view of this point, this paper could provide a suitable solution for vowel classification for imagined speech. We used the DBN algorithm, which is known as a deep learning algorithm for multi-class vowel classification, and selected four vowel pronunciations:, /a/, /i/, /o/, /u/ from IPA. For the experiment, we obtained the required 32 channel raw electroencephalogram (EEG) data from three male subjects, and electrodes were placed on the scalp of the frontal lobe and both temporal lobes which are related to thinking and verbal function. Eigenvalues of the covariance matrix of the EEG data were used as the feature vector of each vowel. In the analysis, we provided the classification results of the back propagation artificial neural network (BP-ANN) for making a comparison with DBN. As a result, the classification results from the BP-ANN were 52.04%, and the DBN was 87.96%. This means the DBN showed 35.92% better classification results in multi class imagined speech classification. In addition, the DBN spent much less time in whole computation time. In conclusion, the DBN algorithm is efficient in BCI system implementation.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.11-18
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• 2019

One of the key objectives of control systems is to maintain a system in a specific stable state. To achieve this goal, a variety of control techniques can be used and it is often uses a feedback control method. As known this kind of control methods requires mathematical model of the system. This article presents seesaw unstable system with two propellers which are controlled without use of a mathematical model instead. The goal was to control it using training data. For system control we use a logistic regression technique which is one of machine learning method. We tested our controller on the real model created in our laboratory and the experimental results show that instability of the seesaw system can be fixed at a given angle using the decision boundary estimated from the classification method. The results show that this control method for structural equilibrium can be used with relatively more accuracy of the decision boundary.

• Journal of Environmental Science International
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• v.12 no.2
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• pp.145-149
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• 2003

This study was carried out to present rural functional resources through classification and preparation of checklist for ecological and cultural resources which considered various aspect of agriculture and rural area. In this study the function of ecological and cultural resources classified 6 functions such as natural environment, free environmentally agricultural products, experience of agricultural products, recreational places, rural life experience, and Interchanges of human resources. Prepared evaluation list through this study can explain a local characteristics based on 6 functions of agricultural and mountain village. This evaluation list was focused on the magnitude of the resources which motivate the visiting of city-dweller as a consumer, for an actual regional plan, investigation of the inhabitant consciousness survey should be needed, simultaneously.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.27-32
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• 2002

In this paper, we would study the applicability of neural networks to the recognition process of Korean stenographic character image, applying the classification function, which is the greatest merit of those of neural networks applied to the various parts so far, to the stenographic character recognition, relatively simple classification work. Korean stenographic recognition algorithms, which recognize the characters by using some methods, have a quantitative problem that despite the simplicity of the structure, a lot of basic characters are impossible to classify into a type. They also have qualitative one that It Is not easy to classify characters fur the delicacy of the character farms. Even though this is the result of experiment under the limited environment of the basic characters, this shows the possibility that the stenographic characters can be recolonized effectively by neural network system. In this system, we got 90.86% recognition rate as an average.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1148-1154
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• 2009

This study focus on the suggestion of application manual using assembling reference plane design & standard finish material basis upon material classification code. We see it will function as a tool of a linkage between building design and construction standarization in order to enlarge the applicability of house building material that is produced by the module plan. For a estabilishing of this condition, it is neccessary to link the standardization's result of material--design--construction field. According to this neccessity, we are going to suggest information factor that can make relative business manager easily approach to the standardization practical task.