• Human Ecology Research
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• v.60 no.4
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• pp.484-496
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• 2022

The purpose of this study was implementing the high-school 'Food Safety and Health' curriculum using the workbook, and to evaluate the educational impact on, and satisfaction of student who participated in class. A total of 109 lessons were undertaken in home economics classes by referring to the 'Food Safety and Health' workbook for 1,154 students attending seven high schools located in seven cities and provinces across the Korea. In order to examine the effects of classes by referring to workbooks, pre- and post-evaluations were conducted by devising a questionnaire about dietary behavior associated with food safety, creative problem-solving abilities, community capacities, and social cooperation capacities. The results of the analysis of the collected data from 674 students who participated in the pre- and post-evaluations are as follows. First, according to the results of the paired t-test conducted to examine the effects of using the workbook in classes on dietary behavior, significant positive changes were observed in the dietary behavior related to food safety, creative problem-solving skills, community consciousness, and social cooperation capabilities. Second, as a result of the students' evaluation of classes by referring to the 'Food Safety and Health' workbook, both satisfaction and interest in the class using the workbook were high, and the difficulty level was deemed to be appropriate. Additionally, it was found that the students actively participated in learning activities. The reason for this appears to be that the aforementioned workbook consisted of various student activities such as experiments, practical exercises, and group activities aimed at strengthening the link between life and education, thus enabling increased student participation.

• Korean Journal of Community Nutrition
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• v.28 no.4
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• pp.329-339
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• 2023

Objectives: This study aims to explore consumer awareness and usage patterns of local food in Jecheon city during the COVID-19 pandemic, contributing to the establishment of the Jecheon City Food Plan. Methods: Surveys were conducted from July 24 to August 24, 2021, using a combination of web-link and self-administered methods for adults living in Jecheon city (n = 250). Descriptive analysis, t-test, importance and satisfaction analysis (ISA) of local food choice attributes were performed using SPSS Statistics. Results: Participants prioritized freshness when purchasing agricultural products. The freshness of Jecheon local food was the selection attribute with the highest consumer satisfaction and could provide purchase motivation. Approximately 73.6% of respondents understood the concept of local food, and 70% were familiar with Jecheon's local food. Notably, 94.8% expressed an intention to purchase but held negative views on selling local food in other areas. The need to increase the supply of local food to vulnerable populations and public school catering was highly recognized. The ISA identified 'affordable price', 'delivery service', and 'product information' as areas requiring improvement. On the other hand, 'freshness of products', 'quality for the price', and 'support for local farmers and economy' were identified as attributes to be maintained and strengthened. Conclusions: Consumers in Jecheon city recognized local foods as more than just 'consumer goods'. Our findings suggest the need for further research on local food revitalization and more comprehensive local food planning to enhance consumer satisfaction.

• Korean Journal of Community Nutrition
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• v.28 no.3
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• pp.181-191
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• 2023

Objectives: The incidence of inflammatory bowel disease (IBD) is increasing globally, and excessive added sugar consumption has been identified as one of the contributing factors. In the context of IBD, it is essential to explore functional sweeteners that can improve metabolic health and minimize the risk of IBD-related symptoms. This review article aims to shed light on the effects of natural mono- and di-saccharides as alternative sweeteners, specifically focusing on potential benefits for IBD. Methods: A comprehensive literature review was performed using PubMed and Google Scholar databases with articles published after the year 2000. The search terms 'IBD', 'added sugar', 'sweeteners', 'mono-saccharide', and 'di-saccharide' were combined to retrieve relevant articles. A total of 21 manuscripts, aligning with the objectives of the study, were selected. Papers focusing on artificial or high-intensity sweeteners were excluded to ensure relevant literature selection. Results: Multiple studies have emphasized the association between the high consumption of added sugars such as simple sugars and the increased risk of developing IBD. This is suggested to be attributed to the induction of pro-inflammatory cytokine productions and dysbiosis of the gut microbiota. Consequently, there is a growing demand for safe and functional sweeteners, in particular mono- and di-saccharides, that can serve as alternatives for IBD patients. Those functional sweeteners regulate inflammation, oxidative stress, and Intestinal barrier protection, and restore microbiome profiles in various IBD models including cells, animals, and humans. Conclusions: Understanding these mechanisms resolves the link between how sugar consumption and IBD, and highlights the beneficial effects of natural alternative sweeteners on IBD when they were administered by itself or as a replacement for simple sugar. Further, exploration of this relationship leads us to recognize the necessity of natural alternative sweeteners in dietary planning. This knowledge could potentially lead to more effective dietary strategies for individuals with IBD.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.04a
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• pp.165-166
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• 2010

Today, because the international community recognized happing of environmental crisis on the world the international environmental agreements and advanced country's environmental regulations are very tight. Especially, port cities are posed strong threats to the environment due to receiving high pollution from ships and cargo vehicle emissions. So many advanced country (ex. United States, Japan, EU) implement Natural-friendly Port Policy and Program. Environmental-Regulations become more stringent in the future, management of low carbon dioxide emissions brings the competitiveness.(중략)

• Journal of Korean Elementary Science Education
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• v.28 no.1
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• pp.46-54
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• 2009

The purpose of this study was to examine the perception of students about pseudo-science in consideration to their personality traits, cognitive style, and awareness of the nature of science, which might all have a great impact on their behavior and thinking. The subjects of this study were 129 sixth-grade school children in a small urban community in Gyeonggi province. The way they looked at pseudo-science was investigated after three kinds of traits were selected as variables, including personality traits, cognitive style, and awareness of the nature of science. Four different instruments were utilized, which respectively covered personality traits, cognitive style, awareness of the nature of science and perception of pseudo-science. The results of the study were as follows: First, the children with higher emotional stability and liveliness showed higher permeability towards pseudo-science, while made no significant difference on their view of pseudo-science. Second, their cognitive style made no significant difference to their outlook on pseudo-science. Third, as for link between awareness of the nature of science and pseudo-science, the students with a poor understanding of the nature of science were significantly different from those who had a better understanding of it in perception of pseudo-science(p<.05).

• Journal of Soil and Groundwater Environment
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• v.22 no.3
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• pp.18-26
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• 2017

The increasing frequency of droughts has been increasing the necessity of utilizing subsurface dams as reliable groundwater resources in areas where it is difficult to supply adequate agricultural water using only surface water. In this study, we analyzed the current status and actual conditions of five agricultural subsurface dams as well as the effect of obtaining additional groundwater from subsurface dams operated as one aspect of the sustainable integrated water management system. Based on the construction methods and functions of each subsurface dam, the five subsurface dams are classified into three types such as those that derive water from rivers, those that prevent seawater intrusion, and those that link to a main irrigation canal. The classification is based on various conditions including topography, reservoir location, irrigation facilities, and river and alluvial deposit distributions. Agricultural groundwater upstream of subsurface dams is obtained from four to five radial collector wells. From the study, the total amount of groundwater recovered from the subsurface dam is turned out to be about 29~44% of the total irrigation water demand, which is higher than that of general agricultural groundwater of about 4.6%.

• Smart Structures and Systems
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• v.3 no.3
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• pp.321-340
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• 2007

Structural control technologies have attracted great interest from the earthquake engineering community over the last few decades as an effective method of reducing undesired structural responses. Traditional structural control systems employ large quantities of cables to connect structural sensors, actuators, and controllers into one integrated system. To reduce the high-costs associated with labor-intensive installations, wireless communication can serve as an alternative real-time communication link between the nodes of a control system. A prototype wireless structural sensing and control system has been physically implemented and its performance verified in large-scale shake table tests. This paper introduces the design of this prototype system and investigates the feasibility of employing decentralized and partially decentralized control strategies to mitigate the challenge of communication latencies associated with wireless sensor networks. Closed-loop feedback control algorithms are embedded within the wireless sensor prototypes allowing them to serve as controllers in the control system. To validate the embedment of control algorithms, a 3-story half-scale steel structure is employed with magnetorheological (MR) dampers installed on each floor. Both numerical simulation and experimental results show that decentralized control solutions can be very effective in attaining the optimal performance of the wireless control system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.453-466
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• 2006

The increasing popularity of the Internet has led to the emergence of online service delivered by websites. Given large investments in these websites, it is important to retain existing customers in online service contexts. In order to understand how website information and system attributes may influence perceived usefulness of using the websites, customer satisfaction, and ultimate continuous usage behaviors, we develop a model to integrate user satisfaction with technology acceptance. Furthermore, this integration is sharpened through the synthesis with research on continuous usage of online service based on customer satisfaction. We then test the model using a sample of 236 respondents who have used one of the most popular Internet blog and community service in South Korea within the last three months. The analysis results suggest that website information and system attributes play key roles in forming continuous intention of the service and perceived playfulness serves as an important moderator toward customer satisfaction. Our model is more likely to help link website design and invesment decisions to the strategy for retaining existing customers in the context of online service.