• Journal of Korean Medicine for Obesity Research
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• v.20 no.2
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• pp.178-192
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• 2020

Objectives: The present study aimed to compare the impacts of cognitive behavioral therapy (CBT) and behavioral treatment (BT) on weight loss and psychological outcomes among patients with three different subtypes of obesity: simple obesity, obesity with binge eating disorder, and obesity with depression. Methods: Embase, PubMed, the Cochrane Central Register of Controlled Trials, Research Information Sharing Service, and Korean Studies Information Service System were systematically searched for randomized controlled trials conducted on or before May 2020, that used CBT to treat obesity. Methodological quality was assessed using Cochrane's risk of bias tool 2 and publication bias was evaluated through the funnel plot using the trim and fill method, Egger's test, and Begg and Mazumdar rank correlation test. A meta-analysis was conducted using a random-effects model and the standardized mean difference with 95% confidence interval (CI) was used to determine effect size. Results: Twenty-one randomized controlled trials with a total of 22 intervention arms and 2,590 patients were included. Our study results revealed that the effects of CBT, compared with BT, on weight loss distinctly differed across all patient subgroups. In the simple obesity group, CBT was more effective than BT (Hedges' g=0.138, CI=0.012~0.264); however, in the obesity with binge eating disorder group, BT was more effective than CBT (Hedges' g=-0.228, CI=-0.418~-0.038); in the obesity with depression group, the effect of CBT was not statistically different from that of BT (Hedges' g=0.276, CI=-0.307~0.859). Further studies with larger sample sizes are required to confirm the outcomes observed in this study. Conclusions: Our results indicated that the effects of CBT on obesity treatment vary based on patient subtype. Therefore, our findings suggest that CBT or BT should be selectively recommended as a treatment strategy for different obesity subtypes.

• Journal of Korean Home Economics Education Association
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• v.34 no.2
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• pp.153-166
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• 2022

The purpose of this study is to develop and evaluate a dietary education program to improve the caring ability and multicultural acceptance of middle school students. Based on the instructional system design of ADDIE model, the dietary education program was developed to contain five sessions including four theoretical lectures and one lab session. Visual thinking technique was used to train students to express their thoughts and emotion by writing and drawing. The dietary education program was conducted for four weeks (from November 19 to December 14, 2018) at a middle school located in Seoul on a total of 69 middle school students, out of which 34 were assigned to an experimental group and 35 were assigned to a control group. Separate paired t-test were conducted for the experimental group and the control group, respectively, to determine the changes in caring ability and multicultural acceptance scores before and after the dietary education. There were significant increases in caring ability (dietary-, emotional-, behavioral- and cognitive caring) and multicultural acceptance (diversity, relationship and universality) scores among the experimental group after the dietary program. However, no differences were observed among the control group. The results indicate that the dietary education program can be an effective tool to improve caring ability and multicultural acceptance of middle school students.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.159-165
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• 2023

While the frequency of seismic occurrence has been increasing recently, the domestic seismic response system is weak, the objective of this research is to compare and analyze the seismic vulnerability of buildings using statistical analysis and machine learning techniques. As the result of using statistical technique, the prediction accuracy of the developed model through the optimal scaling method showed about 87%. As the result of using machine learning technique, because the accuracy of Random Forest method is 94% in case of Train Set, 76.7% in case of Test Set, which is the highest accuracy among the 4 analyzed methods, Random Forest method was finally chosen. Therefore, Random Forest method was derived as the final machine learning technique. Accordingly, the statistical analysis technique showed higher accuracy of about 87%, whereas the machine learning technique showed the accuracy of about 76.7%. As the final result, among the 22,296 analyzed building data, the seismic vulnerabilities of 1,627(0.1%) buildings are expected as more dangerous when the statistical analysis technique is used, 10,146(49%) buildings showed the same rate, and the remaining 10,523(50%) buildings are expected as more dangerous when the machine learning technique is used. As the comparison of the results of using advanced machine learning techniques in addition to the existing statistical analysis techniques, in spatial analysis decisions, it is hoped that this research results help to prepare more reliable seismic countermeasures.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Journal of Acupuncture Research
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• v.24 no.6
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• pp.1-14
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• 2007

Backgrounds : Rheumatoid Arthritis(RA) is known as the chronic inflammatory diseasethat induces persistent inflammation in the joint cavity. The destruction of cartilage occurs as the result of bones destoyed by pannus, several influential cytokines induced by the synovial capsulitis, varieties of proteinases, $O_2$ radicals, and the secondary degenerative changes of articular cartilage. The type 2 collagen-induced arthritis model is used in recent experimental research on rheumatoid arthritis. Cervus elaphus sibiricus (Nockyong) has the effect of relieving pain by nourishing the muscles, joints, and bones. It is also known to be efficacious in promoting and enhancing the immune system. The objective of this study was to investigate the effect of Cervus elaphus sibiricus herbal acupuncture to inhibit the generation of proinflammatory enzyme on type 2 collagen-induced arthritis. I investigated the inhibition of mRNA transcription of MIF(macrophage migration inhibitory factor), $TNF-{\alpha}$(Tumor necrosis $factor-{\alpha}$) and MMP-9 (matrix metalloproteinase-9) of Cervus elaphus sibiricus herbal acupuncture using an in vitro test. Also investigated was the inhibition of differentiation of Th 1 cells and activation of cytokines(MIF, $TNF-{\alpha}$, IL-6, MMP-9), which are known to cause initial RA ,and are also related to the morphology of the synovial membranes of the joint capsule, by an in vivo test, using CIA(collagen induced arthritis) model mice. Materials & methods : The laboratory animals used in this experiment were 4 week-old DBA female mice, weighing approximately 20 grams, and adjusted to the laboratory environment. The experiment was divided into the normal group(NOR)-no treated group, control group(CON)-CIA induced group, and sample group(SAM)-Cervus elaphus sibiricus herbal acupuncture treated group. RA was induced in the mice via injection of $50{\mu}{\ell}$ C II mixed CFA. The Cervus elaphus sibiricus herbal acupuncture solution was applied on $GB_{35}$(陽陵泉) for 26 days from the 3rd day of RA inducement. The concentration of the solution was determined via a MTT assay. To research the effect on the expression of MIF, $TNF-{\alpha}$ and MMP-9 mRNA, RT-PCR was performed on synovial membrane cells from the knee joint of CIA mice. C II induced RA knee joint's histo-chemical synovial membrane was observed using a specimen model via the Hematoxilin and Eosin dying technique. Results : The expression of mRNA of RA-related cytokines such as MIF, $TNF-{\alpha}$, and MMP-9 dosedependently decreased in the cell from the synovial membranes of the joint, which is treated with Cervus elaphus sibiricus herbal acupuncture solution. In mice treated with Cervus elaphus sibiricusherbal acupuncture, the damage of synovial membranes of the joint was lessened, and differentiation of Th 1 cells was suppressed. The activation of RA-related cytokines such as MIF was suppressed, and the generation of $TNF-{\alpha}$ and MMP-9 showed a statistically significant decreas. Conclusions : It is speculated that Cervus elaphus sibiricus herbal acupuncture has the therapeutic effect of palliating the damage of the tissue impaired by RA by inhibition of the initial RA progression and by regulating excessive differentiation of Th 1 cell as it suppresses the generation of RA-related cytokines during the highest stage of RA by acting on pro-inflammatory enzymes.

• Journal of Korean Society of Forest Science
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• v.97 no.6
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• pp.627-633
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• 2008

This study was conducted to estimate volume growth rates for major Quercus species distributed in Korea, and based on the data collected from the 5th National Forest Inventory. Volume growth rates were estimated by each age class for each species, and their similarity or distinction was statistically analyzed. It was also intended to compare the resulted volume growth rates with the existing growth rates, and to develope a volume growth rate estimation model for the Quercus species. Six major Quercus species were considered in this study; Quercus acutissima, Quercus aliena, Quercus serrata, Quercus variabilis, Quercus dentata, and Quercus mongolica. Based on the data collected from the 5th National Forest Inventory, the diameter growth rates and the height growth rates were estimated for each species, and then the volume growth rates were estimated with the given diameter and height growth rates. To examine the distinction between species or age classes, statistical analyses such as ANOVA and Duncan's multiple range test were applied. The results indicated that the volume growth rate was 10% in the age class II, 6% in the age class III, and lower in the subsequent classes. In addition, the volume growth rates of Quercus acutissima, Quercus aliena, and Quercus serrata were relatively high compared to those of Quercus variabilis, Quercus dentata, and Quercus mongolica. According to their growth rates, the six Quercus species were classified into two groups; high-growth-rate group and low-growth-rate group. Statistical analysis conducted to examine the difference between and within the groups showed that there is no significant difference within groups, while significant between groups. Based on the results, volume growth rate estimation model were finally developed for each group. The classification of the Quercus species suggested in this study was not the same with that of existing volume growth estimation. Thus, it is necessary to improve the existing volume growth rate or its estimation system.

• Journal of Korean Home Economics Education Association
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• v.15 no.4
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• pp.115-132
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• 2003

The purpose of this study is aimed at giving proof that helps the elementary practical arts education system accomplish as the effects are turned out experimentally. Two classes of the sixth grade of J elementary school in Dae-gu have been selected in order to be experimented. One was chosen as an experimental group, the other was done as a comparative group. The creative-problem-solving learning-model was applied to the experimental group, and the traditional way of teaching was applied to the comparative group. For four classes of the sixth grades, ‘chapter 8: Making with recycled materials’ was proceeded as the content. Then. tests about the way of environmental awareness and creativity were carried out twice. After that, the results of pre and after-test in the comparative and experiment groups were compared using the t-test method. Following the analysis of the data collected in this study. the following major observations were obtained: First, children who were educated the creative problem-solving in a practical arts education achieved higher scores than before. Therefore, it turns out that the CPS method is an effective way to improve the environmental awareness in children. It showed that it included lots of daily habits connected with daily life and it made the intention to carry out the environment-preservation stronger and children´s attitude towards the environment improved. Moreover, making with recycled materials was used to solve an environmental problem, affecting in a positive way in our life. It also made the positive recognition about the environment. Second. the application of the creative problem-solving class of the practical arts education can make positive results to children. It helped children to have more interest in the environment around them. Children´s fluency, flexibility and originality in their ideas were improved as much as possible while they were solving problems. Consequently, the application of the creative problem-solving class model of elementary practical arts environmental education lets children expand environment consciousness and creativity.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.177-200
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• 2009

AIn the advanced - economy, the services industry hasbecome a dominant sector. Evidently, the services sector has grown at a much faster rate than any other. For instance, in such developed countries as the U.S., the proportion of the services sector in its GDP is greater than 75%. Even in the developing countries including India and China, the magnitude of the services sector in their GDPs is rapidly growing. The increasing dependence on service gives rise to new initiatives including service science and service-dominant logic. These new initiatives propose a new theoretical prism to promote the better understanding of the changing economic structure. From the new perspectives, service is no longer regarded as a transaction or exchange, but rather co-creation of value through the interaction among service users, providers, and other stakeholders including partners, external environments, and customer communities. The purpose of this study is the following. First, we review previous literature on service, service innovation, and service systems and integrate the studies based on service dominant logic. Second, we categorize the ten propositions of service dominant logic into conceptual propositions and the ones that are directly related to service provision. Conceptual propositions are left out to form the research model. With the selected propositions, we define the research constructs for this study. Third, we develop measurement items for the new service concepts including service provider network, customer network, value co-creation, and convergence of service with product. We then propose a research model to explain the relationship among the factors that affect the value creation mechanism. Finally, we empirically investigate the effects of the factors on firm performance. Through the process of this research study, we want to show the value creation mechanism of service systems in which various participants in service provision interact with related parties in a joint effort to create values. To test the proposed hypotheses, we developed measurement items and distributed survey questionnaires to domestic companies. 500 survey questionnaires were distributed and 180 were returned among which 171 were usable. The results of the empirical test can be summarized as the following. First, service providers' network which is to help offer required services to customers is found to affect customer network, while it does not have a significant effect on value co-creation and product-service convergence. Second, customer network, on the other hand, appears to influence both value co-creation and product-service convergence. Third, value co-creation accomplished through the collaboration of service providers and customers is found to have a significant effect on both product-service convergence and firm performance. Finally, product-service convergence appears to affect firm performance. To interpret the results from the value creation mechanism perspective, service provider network well established to support customer network is found to have significant effect on customer network which in turn facilitates value co-creation in service provision and product-service convergence to lead to greater firm performance. The results have some enlightening implications for practitioners. If companies want to transform themselves into service-centered business enterprises, they have to consider the four factors suggested in this study: service provider network, customer network, value co-creation, and product-service convergence. That is, companies becoming a service-oriented organization need to understand what the four factors are and how the factors interact with one another in their business context. They then may want to devise a better tool to analyze the value creation mechanism and apply the four factors to their own environment. This research study contributes to the literature in following ways. First, this study is one of the very first empirical studies on the service dominant logic as it has categorized the fundamental propositions into conceptual and empirically testable ones and tested the proposed hypotheses against the data collected through the survey method. Most of the propositions are found to work as Vargo and Lusch have suggested. Second, by providing a testable set of relationships among the research variables, this study may provide policy makers and decision makers with some theoretical grounds for their decision making on what to do with service innovation and management. Finally, this study incorporates the concepts of value co-creation through the interaction between customers and service providers into the proposed research model and empirically tests the validity of the concepts. The results of this study will help establish a value creation mechanism in the service-based economy, which can be used to develop and implement new service provision.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.57-78
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• 2023

COVID-19, which started in Wuhan, China in November 2019, spread beyond China in 2020 and spread worldwide in March 2020. It is important to prevent a highly contagious virus like COVID-19 in advance and to actively treat it when confirmed, but it is more important to identify the confirmed fact quickly and prevent its spread since it is a virus that spreads quickly. However, PCR test to check for infection is costly and time consuming, and self-kit test is also easy to access, but the cost of the kit is not easy to receive every time. Therefore, if it is possible to determine whether or not a person is positive for COVID-19 based on the sound of a cough so that anyone can use it easily, anyone can easily check whether or not they are confirmed at anytime, anywhere, and it can have great economic advantages. In this study, an experiment was conducted on a method to identify whether or not COVID-19 was confirmed based on a cough sound. Cough sound features were extracted through MFCC, Mel-Spectrogram, and spectral contrast. For the quality of cough sound, noisy data was deleted through SNR, and only the cough sound was extracted from the voice file through chunk. Since the objective is COVID-19 positive and negative classification, learning was performed through XGBoost, LightGBM, and FCNN algorithms, which are often used for classification, and the results were compared. Additionally, we conducted a comparative experiment on the performance of the model using multidimensional vectors obtained by converting cough sounds into both images and vectors. The experimental results showed that the LightGBM model utilizing features obtained by converting basic information about health status and cough sounds into multidimensional vectors through MFCC, Mel-Spectogram, Spectral contrast, and Spectrogram achieved the highest accuracy of 0.74.

• Journal of The Korean Association For Science Education
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• v.36 no.1
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• pp.177-190
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• 2016

The purpose of this study is to validate learning progressions for Earth's motion and solar system from two different perspectives of validity. One is construct validity, that is whether a hypothetical pathway derived from our study of LPs is supported by empirical evidence of children's substantive development. The other is consequential validity, which refers to the impact of LP-based adaptive instruction on children's improved learning outcomes. For this purpose, 373 fifth-grade students and 17 teachers from six elementary schools in Seoul, Kangwon province, and Gwangju participated. We designed LP-based adaptive instruction modules delving into the unit of 'Solar system and stars.' We also employed 13 ordered multiple-choice items and analyzed the transitions of children's achievement levels based on the results of pre-test and post-test. For testing construct validity, 64 % of children in the experimental group showed improvement according to the hypothetical pathways. Rasch analysis also supports this results. For testing consequential validity, the analysis of covariance between experimental and control groups revealed that the improvement of experimental group is significantly higher than the control group (F=30.819, p=0.000), and positive transitions of children's achievement level in the experimental group are more dominant than in the control group. In addition, the findings of applying Rasch model reveal that the improvement of students' ability in the experimental group is significantly higher than that of the control group (F=11.632, p=0.001).