• Management & Information Systems Review
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• v.36 no.4
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• pp.33-51
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• 2017

With the advent of 'The Forth Industrial Revolution' and the growing demand for quality of life due to economic growth, needs for the quality of medical services are increasing. Artificial intelligence has been introduced in the medical field, but it is rarely used in chronic skin diseases that directly affect the quality of life. Also, atopic dermatitis, a representative disease among chronic skin diseases, has a disadvantage in that it is difficult to make an objective diagnosis of the severity of lesions. The aim of this study is to establish an intelligent severity recognition model of atopic dermatitis for improving the quality of patient's life. For this, the following steps were performed. First, image data of patients with atopic dermatitis were collected from the Catholic University of Korea Seoul Saint Mary's Hospital. Refinement and labeling were performed on the collected image data to obtain training and verification data that suitable for the objective intelligent atopic dermatitis severity recognition model. Second, learning and verification of various CNN algorithms are performed to select an image recognition algorithm that suitable for the objective intelligent atopic dermatitis severity recognition model. Experimental results showed that 'ResNet V1 101' and 'ResNet V2 50' were measured the highest performance with Erythema and Excoriation over 90% accuracy, and 'VGG-NET' was measured 89% accuracy lower than the two lesions due to lack of training data. The proposed methodology demonstrates that the image recognition algorithm has high performance not only in the field of object recognition but also in the medical field requiring expert knowledge. In addition, this study is expected to be highly applicable in the field of atopic dermatitis due to it uses image data of actual atopic dermatitis patients.

• Journal of the Korean Chemical Society
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• v.64 no.2
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• pp.67-73
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• 2020

The study aimed to investigate in vitro lipid deposition of oleic acid, oleic acid methyl ester and cholesterol on a daily disposable (1-day lenses) and 3-days lenses over 3 days and changes of optical characteristics is also investigated. Artificial tear solutions were prepared to simulate actual tear compositions. Two types of contact lenses (1-day lenses (Senofilcon A) and 3-days lenses (silicone tripolymer)) were soaked in the artificial tear solutions within an incubator at 37 ℃ with 150 rpm for 8, 16, 24 hours. Lipid deposition (oleic acid, oleic acid methyl ester and cholesterol) were measured using high performance liquid chromatography (HPLC) instrument. In addition, measurements of oxygen transmissibility, light transmittance and observation of lens surface were conducted. The amount of lipid deposition on the 1-day lenses were 127.55 ㎍/lens for Day 1, 302.96 ㎍/lens, for Day 2, and 353.30 ㎍/lens for Day 3. The 3-days lenses were 46.22 ㎍/lens for Day 1, 66.07 ㎍/lens for Day 2, and 67.45 ㎍/lens for Day 3. Oxygen transmissibility were 81×10^-9(cm/sec)(ml O₂/ml×mmHg)(Baseline) and 48×10^-9(cm/sec)(ml O₂/ml×mmHg) (Day 3) for the 1-day lenses, it were 13.23×10^-9(cm/sec)(ml O₂/ml×mmHg)(Baseline) and 9.6×10^-9(cm/sec)(ml O₂/ml×mmHg) (Day 3) for the 3-days lenses. Transmittance of each lenses were 97.21% (Baseline) and 94.25% (Day 3) for the 1-day lenses, 97.65% (Baseline) and 95.15% (Day 3) for the 3-days lenses. Observation of surface deposition indicated greatest deposition for the 3-days lenses type on Day 3. Lipid deposition for both lens types increased by day and was greater for the 1-day lenses type. Surface deposition appeared to differ as it was greatest for the 3 days lens type, which may suggest other deposits such as protein may be present.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.575-583
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• 2021

This study aims to analyze Taekwondo trends according to news articles by year by applying topic modeling. In order to examine the Taekwondo trend through media reports, articles including news articles and Taekwondo specialized media articles were collected through Big Kinds of the Korea Press Foundation. The search period was divided into three sections: before 2000, 2001~2010, and 2011~2020. A total of 12,124 items were selected as research data. For topic analysis, pre-processing was performed, and topic analysis was performed using the LDA algorithm. In this case, python 3 was applied for all analysis. First, as a result of analyzing the topics of media articles by year, 'World' was the most common keyword before 2000. 'South and North Korea' was next common and 'Olympic' was the third commonest topic. From 2001 to 2010, 'World' was the most common topic, followed by 'Association' and 'World Taekwondo'. From 2011 to 2020, 'World', 'Demonstration', and 'Kukkiwon' was the most common topic in that order. Second, as a result of analyzing news articles before 2000 by topic modeling, topics were divided into two categories. Specifically, Topic 1 was selected as 'South-North Korea sports exchange' and Topic 2 was selected as 'Adoption of Olympic demonstration events'. Third, as a result of analyzing news articles from 2001 to 2010 by topic modeling, three topics were selected. Topic 1 was selected as 'Taekwondo Demonstration Performance and Corruption', Topic 2 was selected as 'Muju Taekwondo Park Creation', and Topic 3 was selected as 'World Taekwondo Festival'. Fourth, as a result of analyzing news articles from 2011 to 2020 by topic modeling, three topics were selected. Topic 1 was selected as 'Successful Hosting of the 2018 Pyeongchang Winter Olympics', Topic 2 was selected as 'North-South Korea Taekwondo Joint Demonstration Performance', and Topic 3 was selected as '2017 Muju World Taekwondo Championships'.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.1-16
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• 2023

Due to imbalances in supply and demand within the labor market, start-ups have emerged as crucial players in the generation of high-quality employment opportunities, particularly in stagnant job markets. In response to this trend, governments are allocating substantial financial and human resources to initiatives that support start-up development. This has led to an increasing rate of engagement in start-up ventures across diverse age groups, not limited to younger individuals. Start-ups are enterprises focused on the commercialization of innovative ideas with the aim of achieving profitability in the marketplace. Research concerning the successful market integration of new products and the attainment of sustainable growth is pivotal. Such research is instrumental not only for the success of start-ups but also for realizing the broader social functions and contributions that these enterprises can offer. Previous research has often examined new product market-entry strategies, often referred to as new product marketing, particularly for large companies and SMEs. However, there is a gap in studies focusing on prototype marketing strategies specific to start-ups. Thus, this study aims to examine the impact of Pre-announcing marketing strategies on the market attention garnered by start-ups with low recognition and limited infrastructure, and how such attention contributes to their sustainable growth. Specifically, the study aims to uncover the causal relationship between information attributes like relevance, vividness, and novelty in building customer relationships, and their impact on purchase intentions influenced by performance expectations and hedonic motivations. In terms of Pre-announcing information attributes, relevance, vividness, and novelty positively influence performance expectations and hedonic motivations as outlined in the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). These factors, in turn, positively impact the purchase intention for pre-announced new products from start-ups. These findings are expected to provide both theory and practical insights into the factors influencing market entry through the use of Pre-announcing marketing strategies for start-up new products.

• Korean Journal of Heritage: History & Science
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• v.57 no.3
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• pp.24-35
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• 2024

Recently, research using deep learning technologies such as artificial intelligence, convolutional neural networks, etc. has been actively conducted in various fields including healthcare, manufacturing, autonomous driving, and security, and is having a significant influence on society. In line with this trend, the present study attempted to apply deep learning to the classification of archaeological artifacts, specifically ancient Korean roof-end tiles. Using 100 images of roof-end tiles from each of the Goguryeo, Baekje, and Silla dynasties, for a total of 300 base images, a dataset was formed and expanded to 1,200 images using data augmentation techniques. After building a model using transfer learning from the pre-trained EfficientNetB0 model and conducting five-fold cross-validation, an average training accuracy of 98.06% and validation accuracy of 97.08% were achieved. Furthermore, when model performance was evaluated with a test dataset of 240 images, it could classify the roof-end tile images from the three dynasties with a minimum accuracy of 91%. In particular, with a learning rate of 0.0001, the model exhibited the highest performance, with accuracy of 92.92%, precision of 92.96%, recall of 92.92%, and F1 score of 92.93%. This optimal result was obtained by preventing overfitting and underfitting issues using various learning rate settings and finding the optimal hyperparameters. The study's findings confirm the potential for applying deep learning technologies to the classification of Korean archaeological materials, which is significant. Additionally, it was confirmed that the existing ImageNet dataset and parameters could be positively applied to the analysis of archaeological data. This approach could lead to the creation of various models for future archaeological database accumulation, the use of artifacts in museums, and classification and organization of artifacts.

• Therapeutic Science for Rehabilitation
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• v.13 no.3
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• pp.51-67
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• 2024

Objective : This study investigated trends in the use of assessment tools by occupational therapists working with adults and older adults. Methods : Occupational therapists were surveyed to gather data on general characteristics, assessment tool usage, assessment time and frequency, usage trends by area, and education. The tools were categorized by the Occupational Therapy Practice Framework (OTPF) into Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), and play and leisure for occupations, and cognitive functions, motor functions, and psychosocial aspects for client factors. Data from 98 respondents were analyzed using frequency analysis and one-way ANOVA with SAS. Results : Most surveyed occupational therapists worked in university or general hospitals (40.82%). The assessment time per patient was under 30 min (62.25%), and re-assessment frequency was one~three months (68.38%). The most frequently used assessment tools by the OTPF were as follows: ADL: Modified Barthel Index (94.90%), IADL: Canadian Occupational Performance Measure (31.63%), cognitive functions: Mini-Mental Status Examination (89.80%), visual perception: Motor-free Visual Perception Test (56.12%), dementia: Global Deterioration Scale (63.27%), motor functions: Jamar Dynamometer & Pinch Gauge (59.18%), dysphagia: Video Fluoroscopic Swallowing Study (28.57%), physical examination: Range of Motion (59.18%), and psychosocial: Geriatric Depression Scale (33.67%). Conclusion : This study identified the use and rationale of assessment tools for occupational therapy in adults and older adults. These findings aim to enhance the curriculum and continuing education of occupational therapists.

• Journal of Science of Art and Design
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• v.7
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• pp.64-104
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• 2005

Visual media transmits image and information reproduced in large quantities, such as a photography, film, television, video, advertisement, or computer image. Correspondence to the students' reception and recognition of culture in the future. arrangements for the field of studies of visual culture. 'Visual Culture' implies cultural phenomena of visual images via visual media, which includes not only the categories of traditional arts like a painting, sculpture, print, or design, but the performance arts including a fashion show or parade of carnival, and the mass and electronic media like a photography, film, television, video, advertisement, cartoon, animation, or computer image. In the world of visual media, Image' functions as an essential medium of communication. Therefore, people call the culture of today fra of Image Culture', which has been converted from an alphabet convergence era to an image convergence one. Image, via visual media, has become a dominant means for communication in large part of human life, so we can designate an Image' as a typical aspect of visual culture today. Image, as an essential medium of communication, plays an important role in contemporary society. The one way is the conversion of analogue image like an actual picture, photograph, or film into digital one through the digitalization of digital camera or scanner as 'an analogue/digital commutator'. The other is a way of process with a computer drawing, or modeling of objects. It is appropriate to the production of pictorial and surreal images. Digital images, produced by the other, can be divided into the form of Pixel' and form of Vector'. Vector is a line linking the point of departure to the point of end, which organizes informations. Computer stores each line's standard location and correlative locations to one another Digital image shows for more 'Perfectness' than any other visual media. Digital image has been evolving in the diverse aspects, such as a production of geometrical or organic image compositing, interactive art, multimedia art, or web art, which has been applied a computer as an extended trot of painting. Someone often interprets digitalized copy with endless reproduction of original even as an extension of a print. Visual af is no longer a simple activity of representation by a painter or sculptor, but now is intimately associated with a matter of application of media. There is some problem in images via visual media. First, the image via media doesn't reflect a reality as it is, but reflects an artificial manipulated world, that is, a virtual reality. Second, the introduction of digital effect and the development of image processing technology have enhanced a spectacle of destructive and violent scenes. Third, a child intends to recognize the interactive images of computer game and virtual reality as a reality, or truth. Education needs not only to point out an ill effect of mass media and prevent the younger generation from being damaged by it, but also to offer a knowledge and know-how to cope actively with social, cultural circumstances. Visual media education is one of these essential methods for the contemporary and future human being in the overflowing of image informations. The fosterage of 'Visual Literacy' can be considered as a very purpose of visual media education. This is a way to lead an individual to the discerning, active consumer and producer of visual media in life as far as possible. The elements of 'Visual Literacy' can be divided into a faculty of recognition related to the visual media, a faculty of critical reception, a faculty of appropriate application, a faculty of active work and a faculty of creative modeling, which are promoted at the same time by the education of 'visual literacy'. In conclusion, the education of 'Visual Literacy' guides students to comprehend and discriminate the visual image media carefully, or receive them critically, apply them properly, or produce them creatively and voluntarily. Moreover, it leads to an artistic activity by means of new media. This education can be approached and enhanced by the connection and integration with real life. Visual arts and education of them play an important role in the digital era depended on visual communications via image information. Visual me야a of day functions as an essential element both in daily life and in arts. Students can soundly understand visual phenomena of today by means of visual media, and apply it as an expression tool of life culture as well. A new recognition and valuation visual image and media education is required to cultivate the capability of active, upright dealing with the changes of history of civilization. 1) Visual media education helps to cultivate a sensibility for images, which reacts to and deals with the circumstances. 2) It helps students to comprehend the contemporary arts and culture via new media. 3) It supplies a chance of students' experiencing a visual modeling by means of new media. 4) There are educational opportunities of images with temporality and spaciality, and therefore a discerning person becomes to increase. 5) The modeling activity via new media leads students to be continuously interested in the school and production of plastic arts. 6) It raises the ability of visual communications dealing with image information society. 7) An education of digital image is significant in respect of cultivation of man of talent for the future society of image information as well. To correspond to the changing and developing social, cultural circumstances, and the form and recognition of students' reception of them, visual arts education must arrange the field of studying on a new visual culture. Besides, a program needs to be developed, which is in more systematic and active level in relation to visual media education. Educational contents should be extended to the media for visual images, that is, photography, film, television, video, computer graphic, animation, music video, computer game and multimedia. Every media must be separately approached, because they maintain the modes and peculiarities of their own according to the conveyance form of message. The concrete and systematic method of teaching and the quality of education must be researched and developed, centering around the development of a course of study. Teacher's foundational capability of teaching should be cultivated for the visual media education. In this case, it must be paid attention to the fact that a technological level of media is considered as a secondary. Because school education doesn't intend to train expert and skillful producers, but intends to lay stress on the essential aesthetic one with visual media under the social and cultural context, in respect of a consumer including a man of culture.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.91-108
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• 2020

Korea's famous soccer players are steadily performing well in international leagues, which led to higher interests of Korean fans in the international leagues. Reflecting the growing social phenomenon of rising interests on international leagues by Korean fans, the study examined the overall consumer perception in the consumption of uniform by domestic soccer fans and compared the changes in perception following the transfers of the players. Among others, the paper examined the consumer perception and purchase factors of soccer fans shown in social media, focusing on periods before and after the recruitment of Heung-Min Son to English Premier League's Tottenham Football Club. To this end, the EPL uniform is the collection keyword the paper utilized and collected consumer postings from domestic website and social media via Python 3.7, and analyzed them using Ucinet 6, NodeXL 1.0.1, and SPSS 25.0 programs. The results of this study can be summarized as follows. First, the uniform of the club that consistently topped the league, has been gaining attention as a popular uniform, and the players' performance, and the players' position have been identified as key factors in the purchase and search of professional football uniforms. In the case of the club, the actual ranking and whether the league won are shown to be important factors in the purchase and search of professional soccer uniforms. The club's emblem and the sponsor logo that will be attached to the uniform are also factors of interest to consumers. In addition, in the decision making process of purchase of a uniform by professional soccer fan, uniform's form, marking, authenticity, and sponsors are found to be more important than price, design, size, and logo. The official online store has emerged as a major purchasing channel, followed by gifts for friends or requests from acquaintances when someone travels to the United Kingdom. Second, a classification of key control categories through the convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm shows differences in the classification of individual groups, but groups that include the EPL's club and player keywords are identified as the key topics in relation to professional football uniforms. Third, between 2002 and 2006, the central theme for professional football uniforms was World Cup and English Premier League, but from 2012 to 2015, the focus has shifted to more interest of domestic and international players in the English Premier League. The subject has changed to the uniform itself from this time on. In this context, the paper can confirm that the major issues regarding the uniforms of professional soccer players have changed since Ji-Sung Park's transfer to Manchester United, and Sung-Yong Ki, Chung-Yong Lee, and Heung-Min Son's good performances in these leagues. The paper also identified that the uniforms of the clubs to which the players have transferred to are of interest. Fourth, both male and female consumers are showing increasing interest in Son's league, the English Premier League, which Tottenham FC belongs to. In particular, the increasing interest in Son has shown a tendency to increase interest in football uniforms for female consumers. This study presents a variety of researches on sports consumption and has value as a consumer study by identifying unique consumption patterns. It is meaningful in that the accuracy of the interpretation has been enhanced by using a cluster analysis via convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm to identify the main topics. Based on the results of this study, the clubs will be able to maximize its profits and maintain good relationships with fans by identifying key drivers of consumer awareness and purchasing for professional soccer fans and establishing an effective marketing strategy.