• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3293-3300
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• 2013

Recently, Korean prefer the slim and skinny body. Even though they are normal or underweight, they strive for weight control routinely. Due to the appearance-oriented trend prevalent in our society, severe losing weight for women has become a social problem. The purpose of this study is to examine the relationship between body dysmorphic disorder and depression. Health-related and health-unrelated college students were classified into three different groups according to BMI. This study was performed of 200 health-related and 200 health-unrelated college students respectively at K college in Gangwon province. A self-administered survey was conducted from September 10 to 21, 2012, and the 319 questionnaires were analyzed. The collected data were analyzed by the SPSS(statistical package for the social science) WIN 18.0. Regarding the relationship between the BMI of the female students and their unsatisfied parts of the body, the overweight female students were more dissatisfied with the entire lower parts of their body(${\chi}^2$=6.97, p<.05). About the waist and belly, the female students of normal weight were the most dissatisfied but of under weight were less dissatisfied than the other groups and the differences among them were statistically significant(${\chi}^2$=8.12, p<.05). About the chest and breasts, the female students of under weight were more dissatisfied than the other groups and there were significant differences according to BMI. As a result of analyzing the relationship between the BMI of the female students and their dissatisfied parts of the body, the female students of over weight were more dissatisfied with the entire lower parts of their body and whole body, and the female students of normal weight were more dissatisfied with their waist and belly than the other groups. The female students of under weight were more dissatisfied with their chest and breasts. But, there were no differences in the way they want to try for a change of the dissatisfied part of the body. Because this body dysmorphic disorder may be associated with depression and cause the social and cultural problems, the development of counseling programs and additional research should be needed.

• Korean Journal of Environmental Biology
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• v.29 no.3
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• pp.126-137
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• 2011

Although Sumunmulbangdui wetland at the Halla Mountain in Jeju Island, a kind of montane wetlands, has been considered to bear high biodiversity, no study has been reported on the bacterial diversity. In this study, soil and water samples were collected from the wetland in order to isolate novel bacterial species. Bacterial strains belonging to the phyla Bacteroidetes, Firmicutes, and Actinobacteria were isolated after spreading soil and water samples onto solid agar media. The 16S rRNA gene sequences of the strains assigned to the three phyla were compared to those of type strains of the species in the phyla. The strains that showed less than 98.7% 16S rRNA gene sequence similarity to the validly published species were considered to be novel species candidates. A total of 32 strains were regarded as novel species candidates in the phyla Bacteroidetes, Firmicutes, and Actinobacteria. Diversity of novel species candidates was very low; the candidates were confined to only few genera. In the Bacteroidetes, 13 novel candidate species were affiliated with the genera Mucilaginibacter, Sphingobacterium, Pedobacter, Flavobacterium, and Chryseobacterium. A total of 13 novel candidate species that assigned to the genera Paenibacillus Lysinibacillus, and Bacillus were identified in the phylum Firmicutes. Only two candidate species that belonged to the genera Mycobacterium and Nocardia were excavated in the Actinobacteria. Cultural, physiological, and chemotaxonomic characteristics have been determined for the novel species candidates, and the characteristics are described in this study.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.1
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• pp.51-60
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• 2014

In this study, ICT medical service provider's level of knowledge fire fighting safety and methods on coping with fires in the regions of Gwangju and Jeonam Province of Korea were investigated to determine the elements affecting such levels and provide basic information on the manuals for educating how to cope with the fire fighting safety in medical facilities. The data were analyzed using SPSS Win 14.0. The scores of level of knowledge fire fighting safety of ICT medical service provider's were 7.06(10 point scale), and the scores of level of recognizing how to cope with fire fighting safety were 6.61(11 point scale). level of recognizing how to cope with fire fighting safety were significantly different according to gender(t=4.12, p<.001), age(${\chi}^2$=17.24, p<.001), length of career(${\chi}^2$=22.76, p<.001), experience with fire fighting safety education(t=6.10, p<.001), level of subjective knowledge on fire fighting safety(${\chi}^2$=53.83, p<.001). In order to enhance the level of understanding of fire fighting safety and methods of coping by the ICT medical service providers it is found that: self-directed learning through avoiding the education just conveying knowledge by lecture tailored learning for individuals fire fighting education focused on experiencing actual work by developing various contents emphasizing cooperative learning deploying patients by classification systems using simulations and a study on the implementation of digital anti-fire monitoring system with multipoint communication protocol, a design and development of the smoke detection system using infra-red laser for fire detection in the wide space, video based fire detection algorithm using gaussian mixture mode developing an education manual for coping with fire fighting safety through multi learning approach at the medical facilities are required.

• Journal of Life Science
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• v.30 no.3
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• pp.313-319
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• 2020

Recently, cattle epidemic diseases are caused by a pathogen such as a virus or bacterium. Such diseases can spread through various pathways, such as feed intake, respiration, and contact between livestock. Diagnosis based on the ELISA (Enzyme-linked immunosorbent assay) and PCR (Polymerase chain reaction) methods has limitations because these traditional diagnostic methods are time consuming assays that require multiple steps and dedicated equipment. In this review, we propose the use of the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) Cas system based on DNA and RNA levels for early point-of-care diagnosis in cattle. In the CRISPR/Cas system, Cas effectors are classified into two classes and six subtypes. The Cas effectors included in class 2 are typically Cas9 in type II, Cas12 in type V (Cas12a and Cas12b) and Cas13 in type VI (Cas13a and Cas13b). The CRISPR/Cas system uses reporter molecules that are attached to the ssDNA strands. When the Cas enzyme cuts the ssDNA, these reporters either fluoresce or change color, indicating the presence of a specific disease marker. There are several steps in the development of a CRISPR/Cas system. The first is to select the Cas enzyme depending on DNA or RNA from pathogens (viruses or bacteria). Based on that, the next step is to integrate the optimal amplification, transducing method, and signal reporter. The CRISPR/Cas system is a powerful diagnostic tool using a gene-editing method, which is faster, better, and cheaper than traditional methods. This system could be used for early diagnosis of epidemic cattle diseases and help to control their spread.

• Archives of design research
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• v.20 no.3 s.71
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• pp.61-72
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• 2007

Having started with "Space War", the first game produced by MIT in the 1960's, the gaming industry expanded rapidly and grew to a large size over a short period of time: the brand new games being launched on the market are found to contain many different elements making up a single content in that it is often called the 'the most comprehensive ultimate fruits' of the design technologies. This also translates into a large increase in the number of things which need to be considered in developing games, complicating the plans on the financial budget, the work force, and the time to be committed. Therefore, an approach for analyzing the elements which make up a game, computing the importance of each of them, and assessing those games to be developed in the future, is the key to a successful development of games. Many decision-making activities are often required under such a planning process. The decision-making task involves many difficulties which are outlined as follows: the multi-factor problem; the uncertainty problem impeding the elements from being "quantified" the complex multi-purpose problem for which the outcome aims confusion among decision-makers and the problem with determining the priority order of multi-stages leading to the decision-making process. In this study we plan to suggest AHP (Analytic Hierarchy Process) so that these problems can be worked out comprehensively, and logical and rational alternative plan can be proposed through the quantification of the "uncertain" data. The analysis was conducted by taking FPS (First Person Shooting) which is currently dominating the gaming industry, as subjects for this study. The most important consideration in conducting AHP analysis is to accurately group the elements of the subjects to be analyzed objectively, and arrange them hierarchically, and to analyze the importance through pair-wise comparison between the elements. The study is composed of 2 parts of analyzing these elements and computing the importance between them, and choosing an alternative plan. Among these this paper is particularly focused on the Delphi technique-based objective element analyzing and hierarchy of the FPS games.

• Radiation Oncology Journal
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• v.10 no.1
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• pp.27-34
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• 1992

Cis-Platinum (DDP) was utilized as a radiosensitizer in a pilot study for stage III and IV squamous cell carcinoma between 1984-1987, and DDP 20 $mg/M^2$/day was administered for 4 days at 3 week interval with concurrent radiotherapy. This study consisted of three phases: cytoreduction phase, eradicative treatment phase and adjuvant phase. Total 59 patients were subjected to evaluate a tumor response and its toxicity. During the eradicative phase,27 patients underwent surgery (group I ), 29 patients were treated with radiotherapy only (group II) and 3 patients did not complete the second phase of therapy. At the cytoreduction phase, $95\%$ response rate with complete response (CR) $47.5\%$ and partial response (PR) $47.5\%$ was observed. Complete tumor clearance (CTC) rate following 2nd phase of therapy was $84\%$ (47/56) with 26/27($96\%$) in group I achieved CTC with surgery and 21/29 ($72\%$) patients In group II achieved CTC following 2nd phase. $67\%$ of primary lesions and $70\%$ of nodal diseases in group I showed no tumor in the surgical specimen. $34\%$ of patiets who achieved CTC at 2nd phase developed recurrence and median time to recur was 8 months. Actuarial disease free survival at 4 years was $59\%$ and $51\%$(24/27) of patients who achieved CTC at 2nd phase were alive without any evidence of disease at median follow-up 31 months (range, 10-48 months). There was no significant difference in overall and disease free survival between group I and II between CR and PR group following 1st Phase. Only significant Prognostic factor in this study was the complete tumor clearance following 2nd phase theapy. In general, toxicity was not excessive. Author concludes that this study confirmed the significant radiosensitizing effect of DDP with the acceptable toxicity and warrant the prospective study to determine optimum scheduling for DDP and radiotherapy which maximizes the therapeutic gain.

• Journal of Plant Biotechnology
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• v.44 no.4
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• pp.356-363
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• 2017

ARice is an important staple food in the world and rice yield is one of the main traits for rice breeding. Several genes involved in increasing the yield have been identified through map-based gene cloning within natural variations in rice. These identified genes are good targets for introducing a genetic trait in molecular breeding. Here, we chose five genes reported to be involved in increasing grain number per panicle in rice; Gn1a, dep1, Apo1, Ghd7, and Nal1. We developed In/Del markers for Gn1a, and dep1, Apo1, and applied the reported SNP markers for Ghd7 and Nal1. We were easily able to examine the genotype of each gene on agarose gel. We tested the genotypes on 479 rice resources that we held with evaluated molecular markers. According to the genotype of each gene, rice resources were divided into 13 haplotypes, and most of the Indica and Japonica varieties were included in haplotypes 1 and 13, respectively. When we examined the effect of each gene on grain number per panicle and panicle number per plant, panicle number per plant in the yield negative allele group for each gene was reduced by approximately 0.3 to 0.8 compared to that in the yield positive allele group. However, the number of yield positive alleles for each gene was higher by about 21 to 27 grains per panicle than that of yield negative alleles. Although most of the varieties were grouped in haplotypes 1 and 13, we believe that this genotype information with evaluated molecular markers will be useful in rice breeding for increasing the yield with grain number per panicle.

• Journal of Korean Society of Transportation
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• v.20 no.2
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• pp.105-115
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• 2002

For many rears, traffic accident statistics are the most direct measure of safety for a signalized intersection. However it takes more than 2 or 3 yearn to collect certain accident data for adequate sample sizes. And the accident data itself is unreliable because of the difference between accident data recorded and accident that is actually occurred. Therefore, it is rather difficult to evaluate safety for a intersection by using accident data. For these reasons, traffic conflict technique(TCT) was developed as a buick and accurate counter-measure of safety for a intersection. However, the collected conflict data is not always reliable because there is absence of clear criteria for conflict. This study developed objective and accurate conflict criteria, which is shown below based on traffic engineering theory. Frist, the rear-end conflict is regarded, when the following vehicle takes evasive maneuver against the first vehicle within a certain distance, according to car-following theory. Second, lane-change conflict is regarded when the following vehicle takes evasive maneuver against first vehicle which is changing its lane within the minimum stopping distance of the following vehicle. Third, cross and opposing-left turn conflicts are regarded when the vehicle which receives green sign takes evasive maneuver against the vehicle which lost its right-of-way crossing a intersection. As a result of correlation analysis between conflict and accident, it is verified that the suggested conflict criteria in this study ave applicable. And it is proven that estimating safety evaluation for a intersection with conflict data is possible, according to the regression analysis preformed between accident and conflict, EPDO accident and conflict. Adopting the conflict criteria suggested in this study would be both quick and accurate method for diagnosing safety and operational deficiencies and for evaluation improvements at intersections. Further research is required to refine the suggested conflict criteria to extend its application. In addition, it is necessary to develope other types of conflict criteria, not included in this study, in later study.