• Cartoon and Animation Studies
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• s.36
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• pp.237-257
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• 2014

This study is the process of performing the interdisciplinary fusion study between multiple fields by identifying the status on the previous artistic education considering the brain scientific mechanism of image creativity and brain-based learning principles. In recent years, producing the educational methods of each field as the fusion study activities are emerging as the trend and thanks to such, the results of brain-based educational fusion studies are being presented for each field. It includes artistic fields such as music, art and dance. In other words, the perspective is that by understanding the operating principles of the brain while creativity and learning is taking place, when applying various principles that can develop the corresponding functions as a teaching method, it can effectively increase the artistic performance ability and creativity. Since the animation drawing should be able to intuitively recognize the elements of movement and produce the communication with the target beyond the delineative perspective of simply drawing the objects to look the same, it requires the development of systematic educational method including the methods of communication, elements of higher cognitive senses as well as the cognitive perspective of form implementation. Therefore, this study proposes a literature study results on the artistic education applied with brain-based principles in order to design the educational model considering the professional characteristics of animation drawing. Therefore, the overseas and domestic trends of the cases of brain-based artistic education were extracted and analyzed. In addition, the cases of artistic education studies applied with brain-based principles and study results from cases of drawing related education were analyzed. According to the analyzed results, the brain-based learning related to the drawing has shown a common effect of promoting the creativity and changes of positive emotion related to the observation, concentration and image expression through the training of the right brain. In addition, there was a case of overseas educational application through the brain wave training where the timing ability and artistic expression have shown an enhancement effect through the HRV training, SMR, Beta 1 and neuro feedback training that strengthens the alpha/seta wave and it was proposing that slow brain wave neuro feedback training contributes significantly in overcoming the stress and enhancing the creative artistic performance ability. The meaning of this study result is significant in the fact that it was the case that have shown the successful application of neuro feedback training in the environment of artistic live education beyond the range of laboratory but the use of the machine was shown to have limitations for being applied to the teaching methods so its significance can be found in providing the analytical foundation for applying and designing the brain-based learning principles for future animation drawing teaching methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.430-438
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• 2018

This study was conducted to develop and evaluate a web-based infection prevention education program for children, parents and teachers. Research for development of the web-based education program was completed in four phases (analysis, design, development, and evaluation) from 1 February 2015 to 5 October 2015, and the completed website was named CHILD4HEALTH (http://uwcms.pusan.ac.kr). Educational contents pertaining to infection prevention were composed of three sections, children, parents and teachers. Subjects were divided into nine categories, animation, children's dictionary, with mom, music, games, quizzes, educational contents for parents, educational contents for teachers, school newsletters, and handouts. Six characters were developed to increase interest and educational effect. Program evaluation items comprised the website, reliability, and satisfaction. Website evaluation by parents revealed that ease of use was $3.77{\pm}0.70$, entertainment value was $4.07{\pm}0.27$, childproof was $3.82{\pm}0.67$, education value was $4.02{\pm}0.75$, and design features were rated $3.65{\pm}0.53$. According to teachers, ease of use was $3.98{\pm}0.37$, entertainment value was $4.00{\pm}0.17$, childproof was $4.34{\pm}0.60$, education value was $4.00{\pm}0.20$, and design features were $3.81{\pm}0.56$. Parents scored reliability and satisfaction as $8.33{\pm}0.62$ and $7.80{\pm}0.77$, respectively, while they were scored as $8.50{\pm}0.73$ and $8.10{\pm}0.74$ by teachers. Based on the results of this study, the developed web-based education program will help prevent infectious disease and facilitate development of future education programs regarding such diseases.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.93-110
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• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.19-36
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• 2015

Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.

• Journal of the Korean Society of Costume
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• v.62 no.5
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• pp.125-137
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• 2012

This study examines the stage costumes of the creative musical 'Hyecho', which was performed six times in the Chung Ang Art Center hosted by Chung-Ang University's performance & media agency from December 20 to 22 in 2006. The stage costumes were made based on these basic design elements of stage costumes that were dyed : line, silhouette, material, and color. First, the creative musical 'Hyecho' presents a new form of fusion theatre, which blends Korean traditional music and dance with videos. Thereby, the musical has opened a new phase in Korea's creative performing arts. Second, in musical performances that combines dance and songs, stage costumes should be made not only to attract the audience's eyes, but also not to interrupt actors' vocalizations and movements by taking their physical features into account. Also, costumes should be made in consideration of their relationships with visual elements, including stage settings and lighting. Third, the musical features fusion-style stage costumes, which combines Hanbok, the Korean traditional costume, and Indian traditional costumes with modern costumes. For the line and silhouette, costumes show the beauty of curves through the curves of Hanbok and India's traditional costumes and also through irregular pleats of pants. Also, by using cotton materials, which is easy to dye and not readily deformed, costumes feature colors that are found in nature through a gradation dyeing technique. In doing so, it offers visual amusement to the audience by making stage costumes look like a beautiful painting. Fourth, the stage costumes of the chorus feature costumes that use lining and pleated skirts using belts, and various accessories, including necklaces that use strings in order to express evil spirits. Since there is not much time to change costumes during a performance, using such items are helpful to show the unique characteristics of actors effectively during the limited time. Also, coordinating with the lighting director allows the costume designer to make better costumes for the chorus and make the performance more dramatic. Finally, it was not necessary to wash the costumes of the chorus of the fusion musical Hyecho 2006 since it was performed only six times. However, when using dyed costumes for the long-term performance, it might cause problems such as bleaching that result from the washing of costumes and low durability that can result in the deformation of costumes. As performing arts are made in various forms and are diversified, it is needed for stage costumes to change accordingly through new attempts and various ways of expression.

• Information Systems Review
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• v.14 no.1
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• pp.105-128
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• 2012

The Culture and Arts Website, one of the parts of providing information related to culture and art utilizing internet, is the website that giving information of arts genre like theater, music, art, architecture, video, and literature. As growing interest in the field of culture and arts, market of this website has been increasing and providing customized content which each customer wants in the field of culture and arts. Developers of culture and arts website consider the website media for increasing and developing awareness about culture and arts. They are accelerating development of various business models and application of culture and arts website service which it meets trend of the times and customers needs. This study will seize about influencing factors to culture and arts website service of domestic website users and analyze how these factors affect loyalty through satisfaction and word of mouth. This study presented research model applied main parameters of PAD(Pleasure, Arousal, Dominance) theory emphasized human's emotions that they are expected to affect the loyalty of culture and arts website service users based on satisfaction and word of mouth. The researcher in this study surveyed students of Seoul S University who had experiences with such culture and arts website to validate the model empirically. The results, firstly, if you experienced feeling related to pleasure and dominance in culture and arts website, you would satisfy this website and it could lead to loyalty. Secondly, the feeling related to ventilation does not affect the loyalty through satisfaction and word of mouth. Thirdly, the results show that all of three factors of emotional responses do not influence the loyalty through word of mouth.

• Journal of Korean Academy of Nursing
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• v.29 no.2
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• pp.429-444
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• 1999

This study was performed to explore the effects of a dance therapy on physical and psychological characteristics in the elderly. The design of this study was a non-equivalent pre-post test experiment. The subjects consisted of elderly persons living in a facility located in Suweon and Bucheon. Fifty eight subjects, aged between 65 and 93 years who had normal cognition, sensory function, balance, and resting blood pressure. They underwent tests of balance, flexibility, muscle strength, depression, and anxiety as baseline data before dance therapy, and at 6th week and at the end of the 12nd week after following dance therapy. Twenty seven elderly persons were assigned to the experimental group and participated with the dance therapy between April and July, 1998. The dance therapy was developed by the author with the help of a dance therapist and a physiatrist. This therapy was based on the Marian Chace's dance therapy and Korean traditional dance with music. The dance therapy consists of 50 minutes session, 3 times a week for 12 weeks. One session was consisted of warming-up, expression, catharsis, sharing, and closing stage. The intensity of the dance therapy was at the 40 % of age-adjusted maximum heart rates. Data were analysed with mead standard deviation, Chi-square test, unpaired t-test, repeated measures ANOVA, and Bonferroni multiple regression using SAS program. 1. The results related to the physical characteristics were as follows : 1) The balance (standing on one leg, walking on the balancing bar), flexibility and muscle strength (knee extensor, knee flexor, ankle plantarflexor and dorsiflexor) of the experimental subjects significantly increased over time mere than that of the control subjects. 2) The experimental group had significantly higher score for balance, flexibility, muscle strength of knee extensor, and knee flexor than the control group at the 12nd week after dance therapy. 3) The experimental group had significantly higher score for muscle strength of ankle dorsiflexor and plantarflexor than the control group at the 6th week and the 12nd week after dance therapy. 2. The results related to psychological characteristics were as follows : 1) Scores of Geriatric Depression Scale, Hamilton Depression Rating Scale, and Zung's Self-rating Anxiety Scale of the experimental group were significantly decreased over time more than that of the control group. 2) The experimental group had significantly lower score for depression than the control group at the 12nd week after dance therapy. 3) The experimental group had significantly lower score for anxiety than the control group at the 6th week and the 12nd week after dance therapy. The findings showed that the dance therapy could be effective in improving the balances, flexibility, and muscle strength of lower limb, and effective in decreasing the depression and anxiety of the elderly. Additional merits of the dance therapy would be inexpensiveness, easy accessibility, and increasing interpersonal relationship. It can be suggested that the dance therapy is effective in the health promotion of the elderly.

• The Journal of the Acoustical Society of Korea
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• v.31 no.3
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• pp.115-128
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• 2012

This paper investigates the effects of diffuser on the acoustical parameters in music hall with consideration of the result of scattering coefficient measurement. A scale model hall of 600 seats with orchestra shell was used for experiments. The materials of 1:50 scale model was chosen through absorption coefficient measurement based on ISO 354. The model was matched to the computer simulation model in terms of reverberation time. In order to evaluate the effect of diffuser location, the measurements were accomplished with and without diffusers according to 7 configurations by diffuser-installed region; sidewall, balcony front, ceiling and so on. The following acoustical parameters were extracted from each measurement case; Reverberation time (RT), Early decay time (EDT), Clarity (C80), Center time (Ts), Sound strength (G) and Temporal diffusion (TD) from the auto-correlation function (ACF) of impulse responses. As a result, the absorption power and diffusion power were increased with number of diffusers. Accordingly RT, EDT and G were decreased by diffuser and the redirection of reflections was occurred briskly. Averaged TD was 6.05 to 6.30 by measurement cases. RT was found to be the most related factor to diffusion power (R = 0.94). The correlation between TD and EDT was high (R = 0.73). In addition, the effects of diffuser-installed location were discussed in terms of acoustical parameter variation.

• Journal of the Korea Concrete Institute
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• v.18 no.2 s.92
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• pp.151-159
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• 2006

The guide line of the SFRC mix design was not established, and the convenience of the practical application on the spot is not so good. In this paper, hence, the program which is optimized to result the mix proportion by the flexural strength and toughness, was developed to apply to SFRC on the practical spot. This program could minimize the number of trial mixes and get an economical and appropriate mixture. In addition, the theoretical background on which the program is based, will be the basis of the embodied method to mixing SFRC. Additionally, new algorithm, in this paper, was used to develop the mix proportioning program of SFRC. The new algorithm is the Harmony Search which is the heuristic method mimicking the improvisation of music players, Musical performances seek a best state determined by aesthetic estimation, as the optimization algorithms seek a best state determined by objected function value. And, it was developed the program about single fiber reinforced concrete, beside to the hybrid fiber reinforced concrete that two kinds of steel fibers, which have the different geometry, was reinforced. This will be able to keep the world trend to study, hence, offers the basis of the next research about hybrid fiber reinforced concrete.