• Journal of Korean Home Economics Education Association
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• v.35 no.3
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• pp.47-66
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• 2023

The purpose of this study was to develop an educational smart app for classes by reconstructing some of the teaching-learning contents of the clothing preparation planning within the 'clothing preparation planning and selection' curriculum unit. To this end, a teaching-learning process plan was planned for the classes, a smart app was developed for classes, and feedback from home economics teachers and app development experts was received for the developed app. The main composition of the developed app consists of five steps. The first step is to set up a profile using a real photo, ZEPETO or Galaxy emoji, or iPhone Memoji. In the second step, students make a list of clothes by figuring out the types, quantities and conditions of their exisitng wardrobe items. Each piece of clothing is assigned an individual registration number, and stduents can take pictures of the front and back, along with describing key attributes such as type, color, season-appropriateness, purchase date, and current status. Step three guides students in deciding which garments to retain and which to discard. Building on the clothing inventory from the previous step, students classify items to keep and items to dispose of. In Step 4, Deciding How to Arrange Clothing, students decide how to arrange clothing by filling out an alternative scorecard. Through this process, students can learn in advance the subsection of resource management and self-reliance, laying the foundationa for future learning in 'Practice of Rational Consumption Life'. Lastly, in the fifth stage of determining the disposal method, this stage is to develop practical problem-oriented classes on how to dispose of the clothes to be discarded in the thirrd stage by exploring various disposal methods, engaging in group discussions, and sharing opinions. This study is meaningful as a case study as an attempt to develop a smart app for education by an instructor to align teaching plans and educational content with achievement standards for the class. In the future, upgrades will have to be made through user application.

• Journal of Christian Education in Korea
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• v.75
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• pp.83-102
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• 2023

Purpose of Research: The purpose of this study is to emphasize that the understanding of the elderly must change to a more positive one as a way to resolve social problems caused by aging. And this study proposes understanding and education about the human rights of the elderly as one of the measures. Research Contents and Methods: The research aims to achieve its purpose through the following contents and methods. First, this study examines the issue of elder abuse that occurs in old age to understand the importance of human rights for the elderly in the context of aging. One of the causes of elder abuse is the lack of understanding of the human rights of the elderly. What are the rights of the elderly? To this end, the text explains the understanding of the human rights of the elderly according to UNESCO, as well as the policy on the human rights of the elderly in Korea. Based on this, the importance of human rights education for the elderly was argued. This is because an increase in awareness has a significant impact on improving the human rights of the elderly. In particular, this study argues that the church is also affected by the aging phenomenon. Therefore, it is argued that the church should also take an interest in the human rights of the elderly. And it was emphasized that human rights education for the elderly should be approached from a Christian perspective. Results/Conclusions: In conclusion, this study emphasizes the importance of protecting the human rights of the elderly and proposes three aspects of christian human rights for the elderly. First, there is a need for self-dignity education for the elderly. Second, it is necessary to learn about and empathize with the lives of the elderly in order to recognize and respect their rights across different generations. Third, education on mutual respect was proposed as a means to alleviate conflicts between the elderly and other generations, and to promote harmony and respect for rights. It is believed that this will play an important role in bridging the generation gap caused by aging. Unfortunately, this study has a limitation in that it does not address methodological approaches and education, as it primarily focuses on theoretical proposals. Therefore, it is hoped that further studies will continue to be conducted to develop specific alternatives aimed at enhancing the human rights of the elderly.

• Journal of the Daesoon Academy of Sciences
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• v.49
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• pp.187-227
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• 2024

The purpose of this article is to examine the prospects of the religious cultural experience program of Daesoon Jinrihoe by referring to the current status of Korea's Buddhist temple stays, which began with the 2002 World Cup and have become a regular program for the general public with the establishment of the Cultural Corps of Korean Buddhism in 2004. The motivation for Korean participation is mainly rest, while foreigners tend to be more interested in Korean traditional culture. During the experience, the perceived value felt by the participants led to satisfaction and an intention to revisit. Temple stays have contributed to the globalization of Korean Buddhism. The temple stay of Daesoon Jinrihoe is a religious cultural experience program for the public. If it became a regular program, the target could be expanded to include foreigners who wish to experience Korean culture. The activities such as wearing Hanbok, taking a Dojang Tour, praying, and dialogue over tea can be allocated to the program. As a result, the perceived value by participants could be taken as a cognitive value. For instance, they could learn about Sangje's Reordering of the Universe that transformed the order of Sanggeuk (Mutual Contention) into the order of Sangsaeng (Mutual Beneficence). They way that they live their lives could change as a result of these new understandings. The emotional value of the experience would come from experiencing traditional Korean religious culture. The prospect of implementing such a program is twofold: firstly, there are the tasks of proper preparation, and secondly, there are the positive effects. The tasks would first involve creating a systematic and organized center point. Next there would be the matter of preparing spaces for the temple stay, and lastly, an online platform for advertisement, recruitment, and application would also be greatly beneficial. This is a vision that could contribute to the improving public image of the order, its globalization, and to the overall improvement of the facilities and management that would produce a more socially friendly environment.

• Journal of Korean Ophthalmic Optics Society
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• v.18 no.1
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• pp.75-84
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• 2013

Purpose: Changes of refractive correction value in different age group were investigated. Regarding the inhibitive effects against myopia progression after wearing reverse geometry contact lenses and myopia control lenses (MC lenses), the effects after wearing single vision lenses were compared. Methods: We organized children between the ages of six and fifteen into three groups by age, and distributed fifty-seven reverse geometry contact lenses, fifty-six MC lenses and seventy-eight single vision lenses among them to be worn. Group 1 consisted of children aged ten and under, Group 2 consisted of children between the ages of eleven and fifteen, and Group 3 represents all of the study participants. The aim of this study was to learn the inhibitive effects against myopia progression attained by changes of refractive correction value and to verify their statistical significance at twelve months and under, thirteen to twenty-four months and twenty-five to thirty-six months. Results: Changes of refractive correction value by each length of use in Group 3 were as follows. For the age group of under twelve months, participants using the reverse geometric contact lens showed no change, while those using the MC or single vision lens had significant changes (P<0.05) of $-0.36{\pm}0.10$ D and $-0.67{\pm}0.52$ D, respectively. Users of all three lens types displayed significant change (P<0.05), in the age group of between thirteen and twenty-four months, of $0.18{\pm}0.49$ D, $0.60{\pm}0.42$ D and $1.37{\pm}0.72$ D for users of the reverse geometry contact lens, the MC lens and the single vision lens, respectively. There were significant changes (P<0.05) of $0.29{\pm}0.61$ D, $0.93{\pm}0.57$ D and $1.72{\pm}0.78$ in the same respective order as the above in the age group of twenty-five to thirty-six months. Refractive correction value showed changes with different age group. Group 1 displayed significant changes (P<0.05) of $0.29{\pm}0.73$ D, $1.07{\pm}0.59$ D and $1.75{\pm}0.74$ D for users of the reverse geometry contact lens, MC lens and single vision lens, respectively, up to thirty-six months of lens wearing; Group 2, also up to thirty-six months, displayed significant changes (P<0.05) of $0.28{\pm}0.42$ D, $0.75{\pm}0.49$ D and $1.70{\pm}0.84$ D in the same respective order, and changes in refractive correction for the age group under ten years was significantly greater (P<0.05) for the age group of eleven and older. Conclusions: The results found in this study demonstrate that there were no changes of refractive correction value for the case of wearing reversing geometry contact lens up to twelve month or less. MC lens showed less changes in variations of visual acuity for all users which might be resulted in inhibiting progression of myoptia. When both reverse geometry contact lens and the MC lens are wearing for the period from 13 to 36 month, both lens showed less changes in variation of visual acuity for all users. The results suggested that the less changes in variation of visual acuity of both lens had an effect on inhibiting progression of myopia.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• The Korean Journal of Rehabilitation Nursing
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• v.2 no.2
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• pp.257-270
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• 1999

The purpose of this study is to investigate factors related to the intent of using home nursing of chronic disease patients who got out of a university hospital. For the purpose, the study selected 153 patients who were hospitalized and left K university hospital with diagnoses of cancer, hypertension, diabetes and cerebral vascular accident and ordered to be discharged and performed interviews with them and surveys on their medical records to obtain the following results. For this study a direct-interview survey and medical record review was conducted from June 28 to Aug. 30, 1998. The frequency and mean values were computed to find the characteristics of the study subjects, and $X^2$-test, t-test, factor analysis and multiple logistic regession analysis were applied for the analysis of the data. The following results were obtained. 1) When characteristics of the subjects were examined, men and women occupied for 58.8% and 41.2%, respectively. The subjects were 41.3 years old in aver age and had the monthly aver age earning of 0.99 million won or below, which was the most out of the total subjects at 34.6%. Among the total, 87.6% resided in cities and 12.4 in counties. The most left the hospital with diagnosis of cancer at 51.6%, followed by hyper tension at 24.2%, diabetes at 13.7% and cerebral vascular accident at 7.2%. 2) 93.5% of the selected patients had the intent of using home nursing and 6.5%, didn't. Among those patients having the intent, 85.6% had the intent of paying for home nursing and 14.4%, didn't. The subjects expected that the nursing would be paid 9,143 won in aver age and 47.7% of them preferred national authorities as the main servers. 86.3% of the subjects thought that home nursing business had the main advantage of making it possible to learn nursing methods at home and thereby contributing to improving the ability of patients and their facilities to solve health problems. 3) Relations between the intent of use and characteristics of the subjects such as demography-related social, home environment, disease and physical function characteristics did not show statistically significant differences among one another. Compared to those who had no intent of using home nursing, the group having the intent had more cases of male patients, the age of 39 or below, residence in cities, 5 family member s or more, no existence of home nursing servers, leaving the hospital from a non-hospitalized building, disease development for five months or below, hospitalization for ten days or more, non-hospitalization with in the recent one month, two times or over of hospitalization, leaving the hospital with no demand of special treatment, operation underwent, poor results of treatment, leaving the hospital with demand of rehabilitation services, physical disablement and high evaluation point of daily life. 4) Among those patients having the intent of using home nursing, 47.6% demanded technical nursing and 55.9%, supportive nursing. As technical nursing,' inject into a blood vessel ' and 'treat pustule and teach basic prevention methods occupied for 57.4%, respectively, topping the list. Among demands of supportive nursing, 'observe patients 'status and refer them to hospitals or community resources as available, if necessary' was the most with percent age point of 59.5. Regarding the intent of paying for home nursing, 39.2% of those patients wishing to use the nursing responded paying for technical services and 20.2, supportive services. In detail, 70.0% wanted to pay for a service stated as 'inject into a blood vessel', highest among the former services and 30.7%, a service referred to as 'teaching exercises needed to make the body of patients move', highest among the latter. When this was analyzed in terms of a relation between the need(the need for home nursing) and the demand(the intent of paying for home nursing), The rate of the need to the demand was found two or three times higher in technical nursing(0.82) than in supportive nursing(0.35). In aspects of tech ical nursing, muscle injection(1.26, the 1st rank) was highest in the rate while among aspects of supportive nursing, a service referred to as 'teach exercises needed for making patients move their bodies normally'(0.58, the 1st rank). 5) factors I(satisfaction with hospital services), II(recognition of disease state), III(economy) and IV(period of disease) occupied for 34.4, 13.8, 11.9 and 9.2 percents, respectively among factors related to the intent by the subjects of using home nursing, totaled 59.3%. In conclusion, most of chronic disease patients have the intent of using hospital-based home nursing and satisfaction with hospital services is a factor affecting the intent most. Thus a post-management system is needed to continue providing health management to those patients after they leave the hospital. Further, supportive services should be provided in order that those who are satisfied with hospital services return to their community and live their in dependent lives. Based on these results, the researcher would make the following recommendation. 1) Because home nursing becomes more and more needed due to a sharp increase in chronic disease patients and elderly people, related rules and regulations should be made and implemented. 2) Hospital nurses specializing in home nursing should be cultivated.

• Journal of Environmental Health Sciences
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• v.17 no.2
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• pp.54-66
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• 1991

As a result of measuring illumination and making up a question at home visit directly by investigator who trained over twenty days period from October 4 to 24, 1990, in order to render help which illumination problem against house, society against eyes or framing of health instruction potgram by seizing natural lighting actual conditions of house and actual conditions of wearing spectacles and by investigating interrelationship, I can summarize as follows. 1) In property of investigation subject, woman 66.9%, In an age, the twenties was largest of 27.4%, the forties was 20.2%, the fifties was 18.6%, the thirties was 17.4%. In academic career, those of upper secondary school grauates was largest of 28.6%, those who possess university career was 25.9%, those who middle school career was 20.9%, decoding of Korean alphabet was 2%. 2) By a residence area, a big city was 43.3%, farming and fishing villages were 20.3%, the rest was a small town and the administrative office of town, township. In positon of house, the middle area was 43.6%, resident of suburb area was 38.0%. In form of house, a Korean-style house was 40.8%, a western-style house was 34.8%, an apartment house was 11.0%. In the a standard of living, the middle classes 77.2%, the lower classes were 15.3%. In residential house unit of area, from 21 to 30 unit of area was largest of 31.5%, from 10 to 20 unit of area was 19.9%, from 31 to 40 was 18.7%. 3) The wearing spectacles rate of study user was 44.1%. By the area, those who wearing spectacles was more than a half of 50.8% in the resident of big city area. As passing from the farm area to the city, that is being resident of big city was high wearing spectacles rate. In position of house, as being residence in central street showed high wearing spectacles rate. (central street was 51.5%, the middle area was 44.5% and the suburb area was 40.1%.) It seemed similarity difference a variable by position of house from wearing spectacles in standard of 1%. By form of house, wearing spectacles rate those who resident in apartment house was 49.5%, that rate those who resident in a western-style house was high of 49.0%, that rate those who resident in a Korean-style house was the lowest 39.0%. By social position of resident in room, in students case who study showed very high, as university students were very high of 62.3% idn wearing spectacles rate, middle and high school students 'were 50.0%, members of society were 47.6%, workers 20.3%. It seemed similarity difference from academic career in standard of 1%. By an age, the thirties was high of 54.1% in wearing spectacles rate, the twenties was 43.2%, the teenage was the lowest of 11.8%. 4) In illumination of study, over 200Lux was high of 40.1%. but below 99Lux which inappropriate illumination to see the books was 32.4%. Average by area, below 99Lux was 22.7% and over 400Lux was 50.0% in case of wooden floor. As examine by area, below 99Lux was high of 27.0% a case of wooden floor in the big city area, it was not good in illumination passing from the farm area(15.0%) to the city(19.0%). Average illlumination by area of the main living room below 99Lux was high of 37.5%, less than 200Lux was 58.5% of whole. In general, illumination of the main livingroom was inappropriate. By area, the big city was 32.5% below 99Lux, the middle and small city area were 33.8%, town and township area were 45.0%, farming and fishing area were 42.8%. By area, in the big city, illumination of study was 52.5% over 200Lux and 28.9% below 99Lux. In case of the middle and small city, study user of below 99Lux was 38.8% and over 200Lux was 46.9%. In case of the seat of town township, below 99Lux was 34.1% and over 200Lux was 39.7%. In case of farming and fishing area, illumination of study was 33.4% below 99Lux and 48.4% over 200Lux. It tends to high rate of inappropriate illumination. 5) By position of house, in case of wooden floor, less than 100Lux was 24.5% in central street. It was bad illumination than others position of house. In case of the main livingroom, less than 100Lux was 40.4% in the suburb area. It was bad iliumnation than others position of house. In case of study, less than 100Lux was 35.4% in the middle area, it was worse in illumination. In case of the main living room, is seemed similarity difference in standard of 1%. 6) By form of house, in case of wooden floor, illumination of less than 100Lux was 23.8% in a western-style house, it was bad illumination than others form of house. In case of the main livingroom, illumination of less than 100Lux was 47.4% in a Korean-style house, it was remarkably bad illumination than others form of house. In case of study, a Korean-style house was 38.8%, it was very bad illumination than others form of house. In case of the main livingroom and study, it seemed similatrity difference each as P < 0.01 and P < 0.05 in standard of 1%. 7) The wearing spectacles rate of those who use room of illumination over 400Lux was 40.7%, and that of those who use room of illumination less than 100Lux was 28.1%. It seemed similarity differecce in standard of 1%. 8) In period of wearing spectacles, 21.3% of total investigator-highest-was from before five years, 8.6% was from before three years. Among those who use of illumintion less than 99Lux, 34.0% began to wear spectacles from before two years 31.7% was from before five years, 30.3% was from before four years. It seemed similarity difference from period of wearing spectacles by illumination in standard of 1 %. 9) Among cause which sight grow worse, the first was that it was each 33.2% and 27.4% in response rate because watch TV nearly to wearing spectacles person and non-wearing person. The second was that a lot of seeing books was 25.3% in wearing spectacles person and response rate for dark illumination was 7.4% in nonwearing spectacles person. It seemed similarity difference in standard of 1%. (P < 0.01). 10) In experience which take medicine good for eyes, it was 50.1% in wearing spectacles person and 8.5% in non-wearing spectacles person. It seemed similarity difference in standard of 1%(P < 0.01). As we have seen above, inappropriate illumination can be a cause of wearing spectacles. Nevertheless, actually, is realities to indifferent against illumination of house. So it must learn knowledge about health obstacle of illumination through society instruction and school eduction against students as well as general residents. In case that natural lighting is inappropriate structural of house, we must be able to maintain appropriate illumination through artificial illumination. And so eyes which is core of human life have to be protected, related the authorities, related group, and all health medical personnel will organically cooperate with and make efforts.

• Journal of Music and Human Behavior
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• v.4 no.2
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• pp.66-83
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• 2007

The purpose of this study is to learn both effects of the vocal psychotherapy on the self-consciousness and the variety of the self-consciousness on the vocal psychotherapy in return. The research for this study was performed to three subjects who were students of E university, Seoul, ten times for sixty minutes. The subjects were all volunteers for the advertisement on a music-therapy program searching for them on the web site of E university. The vocal psychotherapy program consists of four steps and each of them consists of two to four short terms again. Both before and after the experiment, examinations on self-consciousness were done to recognize the change of the subjects' self-consciousness which would be caused by the vocal psychotherapy activity. After every short term, the subjects were asked to write reports to closely analyze the change of self-consciousness according to the terms and the variety of the subjects. The effect of the vocal psychotherapy activity on the changes of scores in the self-consciousness examination is the first thing to point out on this study. There appeared some personal varieties on the total scores of the examination and scores of some sub-categories. Especially, there were different scores on the private self-consciousness, the public self-consciousness, and the social anxiety between before and after performing the vocal psychotherapy program. Subject A, who had got the best score of all on the scope of the private self-consciousness, showed the steepest decrease on the very scope. On the contrary, the subject showed decrease of scores of the public self-consciousness and the social anxiety in the relatively little rate. Subject B, who had got the highest score of the three on the public self-consciousness, showed the steepest decrease on that of all scopes and showed no difference on the social anxiety scope. In the case of the last one, subject C, who had relatively low scores on the private and public self-consciousness than the others, the private self-consciousness score increased but the public self-consciousness and the social anxiety scores decreased. The changes of the scores of each questions were examined in order to see possible other changes that had not been exposed on the changes of the total and sub-categories scores. As a result of that, of all twenty-eight questions, there were changes about one to two points. Subject A showed the difference with thirteen questions, subject B with sixteen and subject C with nineteen questions. The rate of change of subject C was relatively small but more questions changed and the change of score was wider than the others. Considering all those results, It can be possibly said that the vocal psychotherapy affects the changes of the scores of sub-categories in self-consciousness examination. The next thing to point out on this study is the change of recognition that was exposed on the subjects' report after every short term of the program. As a result of the close analyzing, according to the short terms and variety of self-consciousness, recognizing the way express subjects themselves by voice and recognizing their own voices appeared to be different. How much they cared about others and why they did so were also different. According to the self reports, subject A cared much about her inner thought and emotion and tended to concentrate herself as a social object. There appeared some positive emotional experiments such as emotional abundance and art curiosities on her reports but at the same time some negative emotions such as state-trait anxiety and neuroticism also appeared. Subject B, who showed high scores on the private and public self-consciousness like subject A, had a similar tendency that concentrates on herself as a social object but she showed more social anxiety than subject A. Subject C got relatively lower points in self-consciousness examination, tended to care about herself, and had less negative emotions such as state-trait anxiety than other subjects. Also, with terms going on, she showed changes in the way of caring about her own voice and others. This study has some unique significances in helping people who have problems caused by self-estimation activated with self-consciousness, using voices closely related to one's own self, performing the vocal skills discipline to solve the technical problems. Also, this study has a potentiality that the vocal psychotherapy activity can be effectively used as a way affects the mental health and developing personality.

• 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 Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.