• Journal of Applied Biological Chemistry
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• v.57 no.3
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• pp.267-277
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• 2014

Objective of this paper is to assess the available data on the pesticide uses and regulations in the golf courses, and provide the nationwide systematic management options. Numbers of golf courses in Korea are rapidly increasing from 2000s and reached at 421 sites by the end of 2011. Accordingly pesticide usage has been increased with years in direct proportion to the increasing number of golf courses. Amounts of pesticide applied in 2011 were 118,669 kg as of an active ingredient and were in the orders of fungicides (54.9%) > insecticides (24.4%) > herbicides (13.3%) > growth regulators (0.1%). Average pesticide usages in 2011 were 280.9 kg per golf course and $5.4kg\;ha^{-1}$. Frequencies of the residual pesticide detections in green and turf were higher than those in fairway and soil, respectively. Residue of highly toxic pesticides was not detected in golf courses. Ministry of Environment in 2010 has developed the 'golf course pesticide monitoring and management system' which is the advanced online registry for kind and amount of pesticides applied in each golf course. This system is intended for monitoring of the pesticide uses and residual levels and protecting the environmental pollution from pesticides in the golf course. In 2009, management of pesticides in the golf courses became the task of Ministry of Environment, being merged from many federal agency and ministries. The protocol for the site-specific best management practices, on which to base results from the risk assessment, should be set for pesticides in the golf to minimize the environmental impacts.

• Information Systems Review
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• v.17 no.2
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• pp.193-218
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• 2015

The purpose of this study is to investigate the effects of closed-type SNS use (i.e., Naver Band) on the perception and behavior of the Korean Army soldiers. In contrast to open-type SNS (e.g., Facebook or Twitter), Naver Band is an online communication service system mostly based on confined offline social network. Therefore, it increases communication between acquaintances who have previously formed relationships. Although the Korean Army recently began to use Naver Band as a method of communication between soldiers, their parents/acquaintance, and Army commanders (or leaders), little research has been done about how this use directly affects army soldiers. Hence, applying the motivation opportunity ability theory of behavior, this study examines how enjoyment (Motivational factor), social ties (Opportunity factor), and social intelligence (Ability factor) affect soldiers' belongingness to their organization and organizational citizenship behavior (OCB). We also hypothesize that army soldiers' belongingness and OCB may enhance their individual performance. Survey results show that enjoyment, social ties, and social intelligence increase army soldiers' belongingness, which leads to OCB. Also, enhanced OCB increases individual performance. However, the effect of enjoyment and social ties on soldiers' OCB is non-significant and soldiers' belongingness does not have influence on individual performance. Theoretical and practical implications are presented.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.1
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• pp.35-45
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• 2020

This study focused on the park as a space to support the behavior of urban citizens in modern society. Modern city parks are not spaces that play a specific role but are used by many people, so their function and meaning may change depending on the user's behavior. In addition, current online data may determine the selection of parks to visit or the usage of parks. Therefore, this study analyzed the change of behavior in Yeouido Park, Yeouido Hangang Park, and Yangjae Citizen's Forest from 2000 to 2018 by utilizing a time series analysis. The analysis method used Big Data techniques such as text mining and social network analysis. The summary of the study is as follows. The usage behavior of Yeouido Park has changed over time to "Ride" (Dynamic Behavior) for the first period (I), "Take" (Information Communication Service Behavior) for the second period (II), "See" (Communicative Behavior) for the third period (III), and "Eat" (Energy Source Behavior) for the fourth period (IV). In the case of Yangjae Citizens' Forest, the usage behavior has changed over time to "Walk" (Dynamic Behavior) for the first, second, and third periods (I), (II), (III) and "Play" (Dynamic Behavior) for the fourth period (IV). Looking at the factors affecting behavior, Yeouido Park was had various factors related to sports, leisure, culture, art, and spare time compared to Yangjae Citizens' Forest. The differences in Yangjae Citizens' Forest that affected its main usage behavior were various elements of natural resources. Second, the behavior of the target areas was found to be focused on certain main behaviors over time and played a role in selecting or limiting future behaviors. These results indicate that the space and facilities of the target areas had not been utilized evenly, as various behaviors have not occurred, however, a certain main behavior has appeared in the target areas. This study has great significance in that it analyzes the usage of urban parks using Big Data techniques, and determined that urban parks are transformed into play spaces where consumption progressed beyond the role of rest and walking. The behavior occurring in modern urban parks is changing in quantity and content. Therefore, through various types of discussions based on the results of the behavior collected through Big Data, we can better understand how citizens are using city parks. This study found that the behavior associated with static behavior in both parks had a great impact on other behaviors.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.79-93
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• 2015

With the rapid development of information technology, the ways of usage have changed drastically. The ways and efficiency of traditional service application to data processing already could not satisfy the requirements of modern users. Nowadays, users have already understood the importance of data. Therefore, the processing and saving of big data have become the main research of the Internet service company. In China, with the rise and explosion of 115 Cloud leads to other technology companies have began to join the battle of cloud services market. Although currently Chinese cloud services are still mainly dominated by cloud storage service, the series of service contents based on cloud storage service have been affirmed by users, and users willing to try these new ways of services. Thus, how to let users to keep using cloud services has become a topic that worth for exploring and researching. The academia often uses the TAM model with statistical analysis to analyze and check the attitude of users in using the system. However, the basic TAM model obviously already could not satisfy the increasing scale of system. Therefore, the appropriate expansion and adjustment to the TAM model (i. e. TAM2 or TAM3) are very necessary. This study has used the status of Chinese internet users and the related researches in other areas in order to expand and improve the TAM model by adding the brand influence, hardware environment and external environments to fulfill the purpose of this study. Based on the research model, the questionnaires were developed and online survey was conducted targeting the cloud services users of four Chinese main cities. Data were obtained from 210 respondents were used for analysis to validate the research model. The analysis results show that the external factors which are service contents, and brand influence have a positive influence to perceived usefulness and perceived ease of use. However, the external factor hardware environment only has a positive influence to the factor of perceived ease of use. Furthermore, the perceived security factor that is influenced by brand influence has a positive influence persistent intention to use. Persistent intention to use also was influenced by the perceived usefulness and persistent intention to use was influenced by the perceived ease of use. Finally, this research analyzed external variables' attributes using other perspective and tried to explain the attributes. It presents Chinese cloud service users are more interested in fundamental cloud services than extended services. In private cloud services, both of increased user size and cooperation among companies are important in the study. This study presents useful opinions for the purpose of strengthening attitude for private cloud service users can use this service persistently. Overall, it can be summarized by considering the all three external factors could make Chinese users keep using the personal could services. In addition, the results of this study can provide strong references to technology companies including cloud service provider, internet service provider, and smart phone service provider which are main clients are Chinese users.

• Journal of Nutrition and Health
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• v.51 no.5
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• pp.433-444
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• 2018

Purpose: This study examined the status and needs of school-based nutritional education programs for reducing sugars intake in elementary schools. Methods: A total of 230 elementary nutrition teachers participated in this study through an online survey in July 2017. Results: Approximately one-third of the schools conducted nutrition education on reducing sugars intake as a main topic. The most frequent educated grade and education period were $4^{th}$ and $3^{rd}$ grade, and once a year. Most of the nutrition teachers answered that nutrition education related to reducing sugars intake for children was necessary. The nutrition teachers answered that first graders were the recipients in most need of nutrition education for reducing sugars but, realistically, third graders were the most suitable for nutrition education. The appropriate education topics were limited to the lower grades, such as sugars consumption related health problems, foods containing high sugars, and behaviors to reduce sugars intake; however, a wider variety of topics were selected for the upper grades. The experiment was considered to be an effective educational method for both the lower and upper grades. The most appropriate nutrition education media appeared to be a mock-up in the lower grades, and an experiment kit in the upper grades. Games and videos were highly considered to be effective media to educate students in reducing sugars consumption by voluntary participation in free time in the classroom in both the lower and upper grades. Conclusion: Nutrition education programs focusing on sugars intake reduction were conducted in some elementary schools, but the training time was short and the types of activities were limited. The perception and demand for nutrition education was very high. Therefore, the development and dissemination of elementary school-based nutritional education programs for sugars intake reduction is urgently needed. Moreover, to develop an effective nutrition education program, the education environment and demand in the field should be fully considered.

• Journal of Korea Game Society
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• v.4 no.4
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• pp.11-18
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• 2004

The on-line games in the past were played by only two persons exchanging data based on one-to-one connections, whereas recent ones (e.g. MMORPG: Massively Multi-player Online Role-playings Game) enable tens of thousands of people to be connected simultaneously. Specifically, Korea has established an excellent network infrastructure that can't be found anywhere in the world. Almost every household has a high-speed Internet access. What made this possible was, in part, high density of population that has accelerated the formation of good Internet infrastructure. However, this rapid increase in the use of on-line games may lead to surging traffics exceeding the limited Internet communication capacity so that the connection to the games is unstable or the server fails. expanding the servers though this measure is very costly could solve this problem. To deal with this problem, the present study proposes the load distribution technology that connects in the form of local clustering the game servers divided by their contents used in each on-line game reduces the loads of specific servers using the load balancer, and enhances performance of sewer for their efficient operation. In this paper, a cluster system is proposed where each Game server in the system has different contents service and loads are distributed efficiently using the game server resource information such as CPU utilization. Game sewers having different contents are mutually connected and managed with a network file system to maintain information consistency required to support resource information updates, deletions, and additions. Simulation studies show that our method performs better than other traditional methods. In terms of response time, our method shows shorter latency than RR (Round Robin) and LC (Least Connection) by about 12%, 10% respectively.

• Journal of Nutrition and Health
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• v.53 no.2
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• pp.215-229
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• 2020

Purpose: This study examines the attitude of South Korean adults toward food aid to North Korea and factors associated with it. Methods: An online survey involving 1,000 adults aged 19-69 years was conducted between September-October 2019. Throughout South Korea, the subjects were proportionally distributed with respect to gender, age, and region, to represent South Korean adults. Results: A total of 44.6% of the respondents agreed (Agreement group), 36.7% disagreed (Disagreement group), and 18.7% neither agreed nor disagreed to food aid to North Korea. Compared to the Disagreement group, the Agreement group had a higher concern of food aid to North Korea and a more positive perception on the effect of it. The Agreement group selected "direct assistance from the government" whereas the Disagreement group chose "support through international organizations" as the most appropriate channel for food aid to North Korea. Logistic regression analysis revealed that South Korean adults showing a more positive perception on the effect of food aid to North Korea were more likely to agree to the aid (odds ratio [OR], 19.32). Moreover, compared to the conservatives, the progressives were more likely to agree to food aid to North Korea (OR, 5.94). South Korean adults in their 40-50s were more likely to agree to food aid to North Korea than those in their 20-30s (OR, 2.81). South Korean adults with a higher concern of food aid to North Korea (OR, 3.93) and a greater positive perception on Korean unification (OR, 1.88) were more likely to agree to food aid to North Korea. Conclusion: The most important factor associated with the attitude of South Korean adults toward food aid to North Korea was their perception on the subsequent effect. As strategies to draw social consensus on food aid to North Korea, we recommend systematizing the monitoring process on the effect of providing food aid to North Korea and informing the public of the outcomes.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.127-138
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• 2011

The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.