• Journal of Life Science
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• v.26 no.10
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• pp.1169-1181
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• 2016

The purpose of this study was to investigate the effects of the regular Upright Body Type Excercise on posture, muscle strength of leg, lung capacity and depression of people with mental illness. The subjects of this study were recruited from B mental health center (5 years and more mental illness patients, n=19) located in P city. For the exercise group, They were carried out the Upright Body Type Excercise Program during 8 weeks (60 min/time, 3 times/week). They were randomly divided into two groups. Exercise group (n=10) and Control group (n=9). And also, they were agreed with consent forms before the experiments. Research results were as follows. Through the upper body type exercise, there was significantly difference in PEF and FEV1/FVC in the trained group. And also, there was much improved in depression level in the trained group. The change of melancholy feeling before and after the program was not statistically significant. However, because of limitations of sampling size due to the peculiarities of the program participants, in consideration of the limit of statistical validation exists clearly, intended to better understand the subjective experience of attendees, qualitative analyzing(qualitative research) was carried out in parallel. It was conducted a deep interview only person accepted among program participants, thematic analysis, subject analysis tasks to be subdivided by classifying by considering the semantic units of what participants expressed, was thus carried out. It found that the degree of melancholy feeling of mental disorders who participated in the Upright Body Typed Exercise Program was reduced. The course of the experience of change in depression appered the three subjects and six sub-themes such as "the start of the change", "interest of the program", "recognition of the need of the body’s health", "physical health promotion", "recovery of physical function", "negative change of habits (attitude)", "reduction of sense of depression", "confidence that it is possible to", "hope for the future". Therefore, upper body type exercise is much helpful in lung capacity and mental health of people with mental illness. So, this type of exercise mostly needed in the people with mental illness group than the other group for the quality of life.

• The Journal of Korean Academy of Sensory Integration
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• v.15 no.2
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• pp.46-65
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• 2017

Objective : The purpose of this research is to find clinical effects of application of weighted vest during task-oriented training focused on gross motor performance and balance abilities of children with spastic diplegia. Methods : 34 subjects were divided by simple random sampling into two groups; experimental group (male : 9, female : 8, average age : 8.12) and placebo group (male : 9, female : 9, average age : 7.53). Both two groups underwent to 40 minute intervention, twice a week for 12 weeks. The intervention was task-oriented training focused on facilitating closed kinematic chain and multi-joint functional movement pattern. During the training, the experimental group received loaded-resistance weighted vest and placebo group also received weighted vest but without loaded-resistance. Participants in both groups underwent 8 to 10 reps of the task-oriented training and there were 3 minutes break time between tasks. There were pre-test of gross motor performance and balance abilities, and two times of post-tests were performed upon 6 weeks and 12 weeks after the intervention completed. And in final, an additional follow-up test was performed 12 weeks after the evaluation was finished in order to find any difference between the two groups over time. Results : There was significant difference in Gross Motor Performance Measure (GMPM) between two groups. It is found that average score of the experimental group increased more than the placebo group after 6 weeks and 12 weeks intervention (p<.05). There was significant difference in Pediatric Berg's Balance Scale (PBS) between two groups. It is found that average score of the experimental group increased more than the placebo group after 6 weeks and 12 weeks intervention (p<.05). Conclusion : Based on the results in this study, it is proposed that application of weighted vest into task-oriented training to facilitating closed kinematic chain and multi-joint movement can improve gross motor performance and balance abilities of children with cerebral palsy.

• Sleep Medicine and Psychophysiology
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• v.8 no.1
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• pp.52-58
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• 2001

Objectives: An Increased level of psychophysiologic arousal and diminished physiologic flexibility would be observed in patients with panic disorder compared with a normal control group. We investigated the differences of psychophysiologic response between patients with panic disorder and normal control to examine this hypothesis. Methods: Ten Korean patients with panic disorder who met the diagnostic criteria of DSM-IV were compared with 10 normal healthy subjects. In psychological assessment, levels of anxiety and depression were evaluated by State-Trait Anxiety Inventory, Beck's Depression Inventory and Hamilton Rating Scale For Anxiety and Depression. Heart rate, respiration rate, electrodermal response, and electromyographic activity were measured by biofeedback system (J & J I-330 model) to determine psychophysiologic responses on autonomic nervous system. Stressful tasks included mental arithmetic, video game, hyperventilation, and talking about a stressful event. Psychophysiologic responses were measured according to the following procedures : baseline(3 min)-mental arithmetic (3 min)-rest (3 min)-video game (3 min)-rest (3 min)-hyperventilation (3 min)-rest (3 min)-talking about a stressful event (3 min). Results: The baseline level of anxiety and depression, electrodermal response (p=.017), electromyographic activity (p=.047) and heart rate (p=.049) of patients with panic disorder were significantly higher than those of the normal subject group. In electrodermal response, patient group had significantly higher startle response than the control group during hyperventilation (p=.001). Startle and recovery responses of heart rate in the patient group were significantly lower than responses in the control group during mental arithmetic (p=.007, p=.002). In electrodermal response of the patient group, startle response was significantly higher than recovery response during mental arithmetic (p=.000) and video game task (p=.021). Recovery response was significantly higher than startle response in respiratory response during hyperventilation. Conclusion: The results showed that patients with panic disorder had higher autonomic arousal than the control group, but the physiologic flexibility was variable. We suggest that it is helpful for treatment of panic disorder to decrease the level of autonomic arousal and to recover the physiologic flexibility in certain stressful event.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.213-225
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• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of Korean Society of Archives and Records Management
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• v.10 no.2
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• pp.75-99
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• 2010

Digital resources are widely used in our modern society. However, we are facing fundamental problems to maintain and preserve digital resources over time. Several standard methods for preserving digital resources have been developed and are in use. It is widely recognized that metadata is one of the most important components for digital archiving and preservation. There are many metadata standards for archiving and preservation of digital resources, where each standard has its own feature in accordance with its primary application. This means that each schema has to be appropriately selected and tailored in accordance with a particular application. And, in some cases, those schemas are combined in a larger frame work and container metadata such as the DCMI application framework and METS. There are many metadata standards for archives of digital resources. We used the following metadata standards in this study for the feature analysis me metadata standards - AGLS Metadata which is defined to improve search of both digital resources and non-digital resources, ISAD(G) which is a commonly used standard for archives, EAD which is well used for digital archives, OAIS which defines a metadata framework for preserving digital objects, and PREMIS which is designed primarily for preservation of digital resources. In addition, we extracted attributes from the decision tree defined for digital preservation process by Digital Preservation Coalition (DPC) and compared the set of attributes with these metadata standards. This paper shows the features of these metadata standards obtained through the feature analysis based on the records lifecycle model. The features are shown in a single frame work which makes it easy to relate the tasks in the lifecycle to metadata elements of these standards. As a result of the detailed analysis of the metadata elements, we clarified the features of the standards from the viewpoint of relationships between the elements and the lifecycle stages. Mapping between metadata schemas is often required in the long-term preservation process because different schemes are used in the records lifecycle. Therefore, it is crucial to build a unified framework to enhance interoperability of these schemes. This study presents a basis for the interoperability of different metadata schemas used in digital archiving and preservation.

• Journal of agricultural medicine and community health
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• v.29 no.2
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• pp.303-314
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• 2004

Objectives: This study was carried out to assess exposure levels of organic dusts and ammonia in poultry farms in Korea. Methods: A total of six poultry farms were investigated. The farms were located in Namwon, Chonlabuk-do and in Kae-San, Chungchongbuk-do. This study consisted of a questionnaire and measuring organic dusts and ammonia. The questionnaire included the characteristics of the farms, work patterns and the tasks of the poultry farms. Results and Conclusions: The farmers raised the chickens 45 times a year and the average number of years in the poultry farm were eight years ranging from 2 to 12 years. They worked for seven days per week and the average hours spent caring the chickens are 6.3 hours per day. The duration of staying in the confinement buildings was 3.3 hours per day. The work time in summer was longest. The feed and the water supply systems were automatic and the control of ventilation windows used "winch curtain" was semiautomatic. They used mechanical ventilation system in winter and used dilution ventilation system in the other seasons. The geometric mean concentration of total and respirable dust sampled in the poultry confinement buildings was 4.0 mg/$m^3$and 0.9 mg/$m^3$ respectively. The ratio of respirable to total dusts range from 9 to 49 percent. There was no sample exceeding the criteria 10 mg/$m^3$ for total dust and 3 mg/$m^3$ for respirable dust in farms. The criteria have been recommended by Korean Ministry of Labor and American Conference of Governmental Industrial Hygienist. The personal respirable dusts measured during a circle work averaged geometric mean concentration 1.4 mg/$m^3$ Two personal samples were exceeded the threshold 3 mg/$m^3$. There was a positive relation between an index and the personal samples of respirable dusts($R^2$=0.98). The index is calculated by multipling the total number of chickens in the farm by the age of the chickens and then dividing by the volume of the confinement building. The geometric mean concentration of area and personal ammonia samples was 23.3 ppm and 22.2 ppm, respectively. Some of the ammonia samples, both area and personal samples, exceeded the short term exposure limit value 35 ppm.

• Journal of agricultural medicine and community health
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• v.29 no.2
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• pp.287-301
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• 2004

Objectives: The development of internet programs for smoking cessation was motivated to quit smoking in the large group of smokers. This personalized program consisted of tailored message to consider the smokers characteristics, and contain the informations on the outcomes of smoking cessation and the skills to be used in the quit attempts. The purpose of this study was to develop the internet management program and information push-delivery system for smoking cessation to encourage the personal intention to quit smoking. Methods: We conducted in 3 steps as developing push service to encourage intention of smoking cessation, analyzing problems of smoking cessation program through the pilot test and suggesting improvements by implication stages. Results: This program is delivered for 30 days. if the participants do not fail to quit smoking. The contents consisted of 13 stages which were divided on starting period. practical period, maintenance period and success period. And push service afforded the tailored message to participants using their e-mail. According to the evaluation of pilot test, the problems of internet information push-delivery service for smoking cessation were the over-tasks per visiting time, recording style of participants, difficulty of terms and sentences, lack of visual effects, absence of follow-up module and unsuitable link with main homepage. Improvements were divided on 3 stages by implication period. The first stage included the immediate improvements as improving link with homepage, modifying menu of smoking information and upload file of notice part. The second stage included the short term improvements as alleviating condition of withdrawal, coordinating start stage of retrial, modifying errors of information push-delivery service and addition of educational materials. The third stage included the long term improvements as development of follow-up module, cost-effectiveness evaluation, reducing contents quantity, introduction of checking style, compensation of graphics effect and review for SMS utilization. Conclusions: This program contribute to improving smoking cessation rate. Therefore this program should be tested in a community to evaluate the effectiveness. To promote the effectiveness, this program should be developed the contents and the strategies for various targets, and established the follow-up system for ex-smokers.

• Korean journal of communication and information
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• v.22
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• pp.131-166
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• 2003

The opening of advertising market and introduction of the free competition doctrine make the competition harsher among advertising agencies. Advertising agencies do their best to execute their ad more efficiently and scientifically. But, it is the reality that broadcasting advertising industry in korea did not construct enough infrastructure to execute the systematic activities compared with that of advanced countries. So, we need to grasp the present conditions and draw a time-table to construct primarily necessary infrastructures. In case of hardware infrastructure in advertising industry, digitalization of broadcasting and convergence of broadcasting with telecommunication make it hurry to construct that. But as the ad agencies was in the situation to compete each other, they have a difficulty to construct common hardware infrastructure enthusiastically. Thus, it is necessary to build hardware infrastructure in advertising industry for policy. And the construction of that should be executed systematically not for the short term effects but for the long term objectives. Also, it is the most important to construct reliable Software infrastructure in advertising industry from all of ad agencies. In these days, ad agencies have a tendency not to believe the important information, like the data of ratings and advertising transaction information, in relation to the advertising activities. And they do not share and communicate about the information of the advertising industry trends, research trends, advertisement related information. So, it is also hurry to build the on-line and off-line database system. Finally, for the development of brainware infrastructure in advertising industry, it is the most necessary to activate the cooperation relation between university and advertising agencies. Universities need to invite experts in the advertising to teach the students practical knowledge and ad agencies to recruit students who want to develop their carrier in the advertising industries. In conclusion, advertising industry in korea to solve these tasks for the development of advertising industry infrastructure in the way of cooperation and harmony of each other rationally and efficiently.

• The Journal of Society for e-Business Studies
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• v.20 no.3
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• pp.59-77
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• 2015

Social networking sites (SNS), such as Facebook, provide abundant social comparison opportunities. Given the widespread use of SNSs, the purpose of the present study was to examine the impact of exposure to social media-based social comparison on user's negative emotions and discontinuous use intention on SNS. We present evidence that under the use of SNS, social comparison activities diverge into three patterns, with explicit self-evaluation desire made against similar target (lateral comparison), self-defense desire made against less fortunate target (downward comparison), and self-enhancement desire made with more fortunate target (upward comparison). Such social comparison processes frequently arise, as people are increasingly using on SNSs, the downward contacts ameliorating self-esteem with positive emotions, but the upward contacts and standard contacts with lateral status enabling a person to compare his or her situation with others and simultaneously increase negative emotions due to its differences with others. In other words, as people increasingly relying on SNSs for a variety of everyday tasks, they risk overexposure to upward or standard social comparison information that may have a cumulative detrimental impact on future intention on SNS use. This study with survey with 209 SNS users found that these negative emotions lead to negative fatigue (attitude) and then discontinuous use intention (behavior) on SNS. Our findings are among the first to explicitly examine discontinuous use intention on SNS using social comparison theory and our results are consistent with those of past research showing that upward social comparisons can be detrimental.