• Journal of Nutrition and Health
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• v.38 no.10
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• pp.880-894
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• 2005

The purposes of this study were to a) measure the IC identified of CFMC (contract foodservice management company) ,b) examine IC circumstance of CFMC, c) evaluate practically IC measurement tool of CFMC, and d) present information for selecting an adequate CFMC to clients. The questionnaires of IC measurement were handed out to 108 CFMCs, there composing of main office employees, foodservice managers, customers, and clients of 207 school,38 hospital, and 86 husiness/industry foodservices. The statistical data analysis was completed using SPSS Win (ver 12.0) for descriptive analysis, t-test, Mann-Whitney U test. First, CFMCs had operational experience for an average of 8 years and 8 months, and served an average of 38,540 meals a day. Most of the respondent companies specialized in the school foodservice field and managed an average of 66 clients for the contract period of 2 years and 3 months. Second, the respondent companies had gotten a score of 77.78 points for the total average, 77.7 points in the large enterprise group and 78.1 points in the small and medium-sized enterprise group. Therefore, the minimum number of points for the accrediting license on Qualification is suggested to be over 70 out of a 100 point scale; this study would be serve as reference for the certification license on qualification. On the level of evaluation category, the scores were 14.15 to 20 points on $\ulcorner$finance$\urcorner$, 19.24 to 25 points on $\ulcorner$customer$\urcorner$, 19.33 to 25 points on $\ulcorner$process$\urcorner$, 14.31 to 20 points on $\ulcorner$human resource$\urcorner$, and 8.6 to 10 point on $\ulcorner$renewal and development$\urcorner$ . $\ulcorner$Renewal and development$\urcorner$ and $\ulcorner$customer focus$\urcorner$ received better grades than other evaluation categories. Third, $\ulcorner$Finance$\urcorner$ indicated similar distribution overall. Small and medium-sized companies had lower grades than large companies on 'market ability' of $\ulcorner$customer$\urcorner$ , but, clients of small and medium-sized companies had higher grade for 'client satisfaction' than large companies. Most of the companies supported 'infrastructure support for foodservice operation' of $\ulcorner$process$\urcorner$ by the main office of CFMCs, but, the branch chain offices of CFMCs were not applied efficiently. Large companies made more effort to improve the 'employee ability' of $\ulcorner$human focus$\urcorner$ than small and medium-sized CFMC. The 'research and development cost' of $\ulcorner$renewal and development$\urcorner$ was increased compared to the previous year. In conclusion, if CFMCs were to perform self-evaluation and a routine checkups by utilizing CFMC's IC measuring tool, improvements in CFMC operational capacities as well as foodservice quality can be noted. (Korean J Nutrition 38(10)'880$\sim$894,2005)

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.6
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• pp.1034-1042
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• 2004

This study was carried out to investigate preparation of reconstructed red peppers, effects of pungency and redness of red peppers on the Kimchi quality using central composite design and response surfaces methodology. Capsaicinoids and ASTA (American Spice Trading Association) value put in X$_1$, X$_2$ of independent variable. The result of response surface regression analysis of reconstructed red peppers, correlation coefficient ($R^2$) of overall pungency intensity, persistence and degree of redness was 0.935, 0.935 and 0.821, respectively. After it was made Kimchi samples with reconstructed red peppers, it was examined pH, titratable acidity and lactic acid bacteria of its during fermentation. In the initial fermentation period of Kimchi, it showed pH of 5.46∼5.78, titratable acidity of 0.27∼0.31%, salt content of 2.26∼2.48% and lactic acid bacteria of 4.05${\times}$10$^{5}$ ∼6.23${\times}$10$^{5}$ , respectively. And it showed traditional fermentation pattern in the pH, titratable acidity and microbes of the middle (appropriate fermentation) and last (excessive) fermentation period. While capsaicinoids content in the Kimchi decreased a little according to extend fermentation period, ASTA value showed low correlation reconstructed red pepper and fermentation period. Also, it was analyzed correlation coefficient ($R^2$) of independent variables (capsaicinoids, X$_1$; ASTA value, X$_2$) between sensory attribute in the Kimchi during fermentation. The result of regression analysis, $R^2$ in the overall pungency intensity, persistence and degree of redness showed 0.515, 0.675, 0.784, respectively.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.4
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• pp.423-432
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• 2019

Along with an increase in marine activities every year, the frequency of marine accidents is on the rise. Accordingly, various research activities and policies for marine safety are being implemented. Despite these efforts, the number of accidents are increasing every year, bringing their effectiveness into question. Preliminary studies relying on annual statistical reports provide precautionary measures for items that stand out significantly, through the comparison of statistical provision items. Since the 2000s, large-scale marine accidents have repeatedly occurred, and case studies have examined the "accident response." Likewise, annual statistics or accident cases are used as core data in policy formulation for domestic maritime safety. However, they are just a summary of post-accident results. In this study, limitations of current marine research and policy are evaluated through a literature review of case studies and analyses of marine accidents. In addition, the ontology of the marine accident information classification system will be revised to improve the current limited usage of the information through an attribute analysis of boating accident status reports and text mining. These aspects consist of the reporter, the report method, the rescue organization, corrective measures, vulnerability of response, payloads, cause of oil spill, damage pattern, and the result of an accident response. These can be used consistently in the future as classified standard terms to collect and utilize information more efficiently. Moreover, the research proposes a data collection and quality assurance method for the practical use of ontology. A clear understanding of the problems presently faced in marine safety will allow "suf icient quality information" to be leveraged for the purpose of conducting various researches and realizing effective policies.

• Korean Journal of Forensic Psychology
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• v.11 no.3
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• pp.287-307
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• 2020

Child sexual abuse (CSA), under the age of 13, has increased over the past ten years, but research on the perceptions of perpetrators and victims have mainly focused on sexual violence against adults. Differentiating the age of the perpetrator into child, adolescent, and adult, the present study examined differences in perceptions of perpetrators and victims of child sexual abuse. The study also investigated differences by the gender of respondents, and examined the effects of Sexual Violence Myths (SVM) and Authoritarian Personality on perceptions of child sexual abuse. A total of 210 people in their 20s to 60s evaluated the degree to perpetrator blaming, perpetrator punishment, victim responsibility, and pain of the victim, and responded to the SVM scale and Authoritarian Personality scale. The correlation analysis, one-way ANOVA, independent samples t-test, and mediation analysis were conducted. The difference in the perception of perpetrator punishment by the age of the perpetrator was significant, indicating that respondents thought that adolescent perpetrators should be more severely punished than child perpetrators. Male respondents compared to female respondents were more likely to attribute the responsibility of sexual assault to the victim, to accept sexual violence myths and to be authoritarian. Sexual Violence Myths mediated the effects of the gender of respondents on the perception of victim responsibility, and Authoritarian Personality moderated these mediation effects. Finally, the limitations and implications of the study were discussed.

• Journal of Korea Trade
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• v.27 no.2
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• pp.115-129
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• 2023

Purpose - This study empirically analyzes the consumer value of risk management associated with illegal, unreported, and unregulated (IUU) fishing of fishery products imported to Korea. The global regulatory paradigm for IUU fishing has shifted from production-centered to market-centered. As a result, changes in the international fisheries trade environment emphasizing "transparency" and "legality" of the production process are accelerating. Therefore, changes in the management systems of fishery products entering the country are also needed. Accordingly, this study estimated the consumer value for risk management of IUU fishing, targeting major fish species imported to Korea, and derived the feasibility of introducing related policies. Design/methodology - This study used the choice experiment as an analysis model to estimate consumers' willingness to pay for the "possibility to check for IUU fishing." The choice experiment assumes that the value of a good or service is composed of separable attributes and that the sum of the part-worth of these individual attributes becomes the total value. In this study, respondents were presented with profiles comprising three attributes (country of origin, price, and possibility of checking IUU fishing) and the levels of frozen poulp squid, the subject of the analysis. The participants were asked to select their preferred profile. The marginal willingness to pay for each attribute was derived from the results of the respondents' choices using conditional logit model estimates. Findings - There is a marked difference in utility based on the preference of the country of origin of fishery products among consumers. In addition, the utility of fishery products that have undergone IUU fishing verification was observed to be higher, with the utility marked to be higher for lower prices. Originality/value - Estimating the policy value of the risk management in IUU fishing of imported fisheries products in this study is a novel attempt that has never been conducted before. Several studies have been conducted to assess the risk of IUU fishing associated with the import of fishery products internationally. However, such studies are yet to be conducted in Korea. Instead, policies and studies have focused on issues related to complying with trading partners' legal and transparent standards for exporting fishery products. This study should be the beginning of more in-depth empirical and theoretical explorations to establish order in the domestic seafood market and respond to changes in international regulations on IUU fishing.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.81-96
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• 2013

Video information retrieval has become a very important issue because of the explosive increase in video data from Web content development. Meanwhile, content-based video analysis using visual features has been the main source for video information retrieval and browsing. Content in video can be represented with content-based analysis techniques, which can extract various features from audio-visual data such as frames, shots, colors, texture, or shape. Moreover, similarity between videos can be measured through content-based analysis. However, a movie that is one of typical types of video data is organized by story as well as audio-visual data. This causes a semantic gap between significant information recognized by people and information resulting from content-based analysis, when content-based video analysis using only audio-visual data of low level is applied to information retrieval of movie. The reason for this semantic gap is that the story line for a movie is high level information, with relationships in the content that changes as the movie progresses. Information retrieval related to the story line of a movie cannot be executed by only content-based analysis techniques. A formal model is needed, which can determine relationships among movie contents, or track meaning changes, in order to accurately retrieve the story information. Recently, story-based video analysis techniques have emerged using a social network concept for story information retrieval. These approaches represent a story by using the relationships between characters in a movie, but these approaches have problems. First, they do not express dynamic changes in relationships between characters according to story development. Second, they miss profound information, such as emotions indicating the identities and psychological states of the characters. Emotion is essential to understanding a character's motivation, conflict, and resolution. Third, they do not take account of events and background that contribute to the story. As a result, this paper reviews the importance and weaknesses of previous video analysis methods ranging from content-based approaches to story analysis based on social network. Also, we suggest necessary elements, such as character, background, and events, based on narrative structures introduced in the literature. We extract characters' emotional words from the script of the movie Pretty Woman by using the hierarchical attribute of WordNet, which is an extensive English thesaurus. WordNet offers relationships between words (e.g., synonyms, hypernyms, hyponyms, antonyms). We present a method to visualize the emotional pattern of a character over time. Second, a character's inner nature must be predetermined in order to model a character arc that can depict the character's growth and development. To this end, we analyze the amount of the character's dialogue in the script and track the character's inner nature using social network concepts, such as in-degree (incoming links) and out-degree (outgoing links). Additionally, we propose a method that can track a character's inner nature by tracing indices such as degree, in-degree, and out-degree of the character network in a movie through its progression. Finally, the spatial background where characters meet and where events take place is an important element in the story. We take advantage of the movie script to extracting significant spatial background and suggest a scene map describing spatial arrangements and distances in the movie. Important places where main characters first meet or where they stay during long periods of time can be extracted through this scene map. In view of the aforementioned three elements (character, event, background), we extract a variety of information related to the story and evaluate the performance of the proposed method. We can track story information extracted over time and detect a change in the character's emotion or inner nature, spatial movement, and conflicts and resolutions in the story.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.6
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• pp.894-902
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• 2016

The purpose of this study was to analyze the attributes considered as important by parents in the selection of laver for infants through conjoint analysis techniques. A total of 917 questionnaires were distributed in January 2016, of which 211 were completed (23.0%). Statistical data analyses were performed using SPSS/Win 21.0 for descriptive statistics and conjoint analysis. The conjoint design was applied to evaluate the hypothetical laver for infants. According to the analysis of attributes and levels of laver for infants, the relative importance of each attribute was follows: seasoning (26.55%), flavor (19.33%), texture (18.75%), oil (15.15%), size (10.61%), and certification (9.61%). The results of the conjoint analysis indicate that parents raising infants preferred laver with the characteristics of non-seasoning, general flavor, softness, half-size, organic certification, and perilla oil. The most preferred laver for infants gained a 53.7% potential market share from choice simulation compared with laver being sold. Using utility and relative importance, the laver market for infants was classified into two segments. As a result of market segmentation, parents of cluster 1 preferred the laver model being sold (soy seasoning) while parents of cluster 2 preferred the optimized laver model (non-seasoning).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.63 no.2
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• pp.98-105
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• 2018

The sale of brown rice batches composed of rice produced in different years is prohibited in Korea. Thus, new methods for the identification of the year of production are critical for maintaining the distribution of high quality brown rice. Here, we describe the exploitation of an enzyme that can be used to discriminate between freshly harvested and one-year-old brown rice. The degree of enzyme activity was visualized through freshness test with Guaiacol, Oxydol, and p-phenylenediamine reagents. With electronic eye equipment, we selected 29 color codes for identifying new brown rice and old brown rice. The discrimination power of selected color codes showed a minimum of 0.263 to a maximum of 0.922 and an average value of 0.62. The accuracy with which new brown rice and old brown rice could be identified was 100% in principal component analysis (PCA) and discriminant function analysis (DFA). The DFA analysis had greater discriminatory power than did the PCA analysis. A verification test using new brown rice, old brown rice, or a mixture of the two was then performed to validate our method. The accuracy of identification of new and old brown rice was 100% in both cases, whereas mixed brown rice samples were correctly classified at a rate of 96.9%. Additionally, in order to test whether the discriminant constructed in winter can be applied to samples collected in summer, new and old brown rice stored for 8 months were collected and tested. Both new and old brown rice collected in summer were classified as old brown rice and showed 50% identification accuracy. We were able to attribute these observations to changes in enzyme content over time, and therefore we conclude, it will be necessary to develop discriminants that are specific to distinct storage periods in the near future.