• Journal of agricultural medicine and community health
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• v.27 no.2
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• pp.127-136
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• 2002

This study was taken to provide data for the approaches of day care service for the elderly in community health practitioner's post through the study on the utilization rate, characteristics and health promotion that the elderly used the day care services. Data collection used three records that case management in take sheet, dementia check list and ADL record during the one year, from June 21, 2001 to June 30, 2002. During the one year, the elderly used day care services were 119 persons that 26.9% of the total elderly population, 1.5 time per used the elderly, and female elderly(88.9%) more used than male elderly. 39.5%of the elderly user have chronic diseases that was arthritis and hypertension and etc. 41.2% of the elderly users have dementia state that score was $17.39{\pm}7.17$(handicapped elderly), $18.43{\pm}7.36$(healthy elderly), but statistically not significant PADL score was $2.18{\pm}0.55$(handicapped elderly), $2.78{\pm}0.30$(healthy elderly), IADL score was $1.78{\pm}0.51$(handicapped elderly), $2.47{\pm}0.60$(healthy elderly) that were statistically significant. One year later, PADL and IADL of the elderly users were improved that statistically significant(p=0.01). The elderly users were wanted rehabilitation service(22.2%), talking service(20.6%), bath service(12.7%), food service(9.5%) of day care services in CHP's post. We are recommended that day care service for the elderly in CHP's post was very useful and contributed to promote ADL functions.

• Journal of Bio-Environment Control
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• v.15 no.4
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• pp.296-305
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• 2006

The heterogeneity of crop transpiration is important to clearly understand the microclimate mechanisms and to efficiently handle the water resource in greenhouses. A computational fluid dynamic program (Fluent CFD version 6.2) was developed to study the internal climate and crop transpiration distributions of greenhouses. Additionally, the global solar radiation model and a crop heat exchange model were programmed together. Those models programmed using $C^{++}$ software were connected to the CFD main module using the user define function (UDF) technology. For the developed CFD validity, a field experiment was conducted at a $17{\times}6 m^2$ plastic-covered mechanically ventilated single-span greenhouse located at Pusan in Korea. The CFD internal distributions of air temperature, relative humidity, and air velocity at 1m height were validated against the experimental results. The CFD computed results were in close agreement with the measured distributions of the air temperature, relative humidity, and air velocity along the greenhouse. The averaged errors of their CFD computed results were 2.2%,2.1%, and 7.7%, respectively.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.217-244
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• 2008

Consumers' overall satisfaction on a specific library use is inferred to be primarily accrued from their performance perception and use satisfaction on the library information service system as recent information technology is being rapidly improved and more libraries are being equipped with advanced information technologies. However, prior research has been conducted only on general library service quality and visitors' satisfaction, leaving the important aspects of visitors' library use and information performance perception. Thus, the objectives of this research are to examine the effect of library use patterns such as general visit for book reading and more professional information search, coupled with service quality, on the library users' performance perception on the information system that in turn, affects library use satisfaction on the same information system. More specifically, this study examines whether library visitors perceive differenltly the information system performance according to their library use patterns such that professional library users may have less positive on information system service due to their higher expectation or more positive perception on it due to variety of information uses and positive judgment on advanced information system. Next, three dimensions of service quality, consisting of interaction, outcome, and physical evidence quality in visitors' library use situations, are hypothesized to affect performance perception on library information system. Thirdly, the performance perception on library information system is hypothesized to influence the system use satisfaction while these two constructs are to affect visitors' overall satisfaction. we develop the following research model in accordance with the above theoretical reasoning. All variables used in this study(General Use Patterns, Professional Use Patterns, Interaction Quality, Outcome Quality, Physical Evidence Quality, Information Performance Perception, Information Use Satisfaction, Overall Satisfaction) were defined operationally based on the underlying prior studies. A survey was conducted with prepared questionnaires to about 400 visitors of a specific university library. Among them, 353 proper questionnaires were finally used for the analyses. Two-step approach was used to test the hypotheses. First, confirmatory factor analysis was conducted to guarantee the validity and reliability of variables. The results showed that all variables had not only convergent and discriminant validity, but also reliability. Then, research model was examined with a structural equation using LISREL 8.30 version. The fitness of the research model was found to be within the acceptable level. The findings of this study are as follows. The professional library use pattern was found to affect the users' performance perception on the library information system while the general library use pattern was not. Second, three dimensions of service quality (interaction, outcome, physical evidence) were found to influence the information system performance respectively while none of them was not to information use satisfaction. Third, library users' performance perception on the information system operation was found to affect the information system use satisfaction, both of which also influence users' overall satisfaction of the library. The findings of this study suggest that contemporary libraries strengthen their advanced information system operation in a way of user orientation and more importantly maximize their visitors' utilization of information system, accompanying proper material and various program development. This study conceptualized the new constructs of library users' performance perception on the information system and information use satisfaction which could better explain library users' overall satisfaction. Thus, furture study related with library service could utilize the constructs of information system performance and satisfaction as well as the variety of library use patterns in the users' viewpoints.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.4
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• pp.64-74
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• 2010

The study is based on an urban park design that is designed in consideration of the characteristics of Uijeongbu City, applied with adequate functions for the environment and showcasing the unique scenery in relation to the relocation of the US Air Force Camp Falling Water. The bases of the design are: the reasonable convergence of the square and park in consideration of the site characteristics; the application of an urban context as the park is located near a station; and the realization of an eco-friendly space. This study is based on foundation research regarding a review of urban square patterns, particular items in planning in relation to modern urban parks and the adaptability of the park in the future. Regarding space usage, the design is applied with notable ideas that allow the space to make its own characteristics through voluntary user activity in conjunction with the environment that will allow the park to cope with changes in the future, as opposed to a space that users experience through pre-determined programs. Below are the focal points of the design. First, the park is designed as an empty space which may accommodate the urban structural context of and usage patterns for being a field of the city ecology that changes and develops, beyond a passively-created square pattern. Such open spaces have a continuity which allows it to adapt to the development of the city. In addition, the design facilitates spontaneous processes through changes in usage pattern and time. Second, the design includes the message that the park and the city, natural things and artificial things, must communicate and network with each other. Hence the park shall not be an isolated green island within the city, but is an open space accommodating the demands for open area from nearby commercial, public and residential facilities; the park shall include a field that can accommodate a variety of programs. Third, the park is designed to encourage the effect of direct and indirect practical education by reflecting a physical plan as well as interesting experience design methods to lower carbon emissions and to create and maintain an eco-friendly space, the basis of a zero-emissions city.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.1-19
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• 2010

In offline environment, unlike traditional advertising model through TV, newspaper, and radio, online advertising model draws instantaneous responses from potential consumers and it is convenient to assess. This kind of characteristics of Internet advertising model has driven the growth of advertising model among various Internet business models. There are, conventionally classified, CPM (Cost Per Mile), CPC (Cost Per Click), and CPS (Cost Per Sales) models as Internet advertising expenditure model. These can be examined in manners regarding risks that stakeholders should stand and degree of responsibility. CPM model that is based on number of advertisement exposure is mechanically exposed to users but not actually recognized by users resulting in risk of wasted expenditure by advertisers without any advertising effect. While on aspect of media, CPS model that is based on conversion action is the most risky model because of the conversion action such as product purchase is determined by capability of advertisers not that of media. In this regard, while there are issue of CPM and CPS models disadvantageously affecting only one side of Internet advertising business model value network, CPC model has been evaluated as reasonable both to advertisers and media, and occupied the largest segment of Internet advertising market. However, CPC model also can cause fraudulent behavior such as click fraud because of the competition or dishonest amount of advertising expenditure. On the user aspect, unintentionally accessed advertisements can lead to more inappropriate expenditure from advertisers. In this paper, we suggest "CPCD"(Cost Per Coupon Download) model. This goes beyond simple clicking of advertisements and advertising expenditure is exerted when users download a coupon from advertisers, which is a concept in between CPC and CPS models. To achieve the purpose, we describe the scenario of advertiser perspective, processes, participants and their benefits of CPCD model. Especially, we suggest the new value in online coupon; "possibility of storage" and "complement for delivery to the target group". We also analyze the working condition for advertiser by a comparison of CPC and CPCD models through advertising expenditure simulation. The result of simulation implies that the CPCD model suits more properly to advertisers with medium-low price products rather than that of high priced goods. This denotes that since most of advertisers in CPC model are dealing with medium-low priced products, the result is very interesting. At last, we contemplate applicability of CPCD model in ubiquitous environment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.181-186
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• 2003

The satellite navigation system is widely used for identifying a user's position regardless of weather or geographic conditions and also make effect on new technology of marine LBS(Location Based Service), which has the technology of geographic information such as the ENC. Generally, there are conceivable systems of marine LBS such as ECDIS, or ECS that use the ENC itself with powerful processor in installed type on ships bridge. Since the ENC is relatively heavy structure with dummy format for data transfer between different systems, we should reduce the ENC to small and compact size in order to use it in mobile platform. In this paper, we assumed that the mobile system like PDA, or Webpad can be used for small capability of mobile platform. However, the ENC should be updated periodically by update profile data produced by HO. If we would reduce the ENC without a consideration of update, we could not get newly updated data furthermore. As summary, we studied considerations for ENC reduction with update capability. It will make the ENC be useful in many mobile platforms for various applications.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.133-148
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• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.59-69
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• 2012

As exhibition industry, which is a part of 17 new growth engines of the government, is related to other industries such as tourism, transportation and financial industries. So it has a significant ripple effect on other industries. Exhibition is a knowledge-intensive, eco-friendly and high value-added Industry. Over 13,000 exhibitions are held every year around the world which contributes to getting foreign currency. Exhibition industry is closely related with culture and tourism and could be utilized as local and national development strategies and improve national brand image as well. Many countries try various efforts to invigorate exhibition industry by arranging related laws and support system. In Korea, more than 200 exhibitions are being held every year, but only 2~3 exhibitions are hosted with over 400 exhibitors and except these exhibitions most exhibitions have few foreign exhibitors. The main reason of weakness of domestic trade show is that there are no agencies managing exhibitionrelated statistics and there is no specific and reliable evaluation. This might cause impossibility of providing buyer or seller with reliable data, poor growth of exhibitions in terms of quality and thus service quality of trade shows cannot be improved. Hosting a lot of visitors (Public/Buyer/Exhibitor) is very crucial to the development of domestic exhibition industry. In order to attract many visitors, service quality of exhibition and visitor's satisfaction should be enhanced. For this purpose, a variety of real-time customized services through digital media and the services for creating new customers and retaining existing customers should be provided. In addition, by providing visitors with personalized information services they could manage their time and space efficiently avoiding the complexity of exhibition space. Exhibition industry can have competitiveness and industrial foundation through building up exhibition-related statistics, creating new information and enhancing research ability. Therefore, this paper deals with customized service with visitor's smart-phone at the exhibition space and designing mobile framework which enables exhibition devices to interact with other devices. Mobile server framework is composed of three different systems; multi-server interaction, server, client, display device. By making knowledge pool of exhibition environment, the accumulated data for each visitor can be provided as personalized service. In addition, based on the reaction of visitors each of all information is utilized as customized information and so the cyclic chain structure is designed. Multiple interaction server is designed to have functions of event handling, interaction process between exhibition device and visitor's smart-phone and data management. Client is an application processed by visitor's smart-phone and could be driven on a variety of platforms. Client functions as interface representing customized service for individual visitors and event input and output for simultaneous participation. Exhibition device consists of display system to show visitors contents and information, interaction input-output system to receive event from visitors and input toward action and finally the control system to connect above two systems. The proposed mobile framework in this paper provides individual visitors with customized and active services using their information profile and advanced Knowledge. In addition, user participation service is suggested as well by using interaction connection system between server, client, and exhibition devices. Suggested mobile framework is a technology which could be applied to culture industry such as performance, show and exhibition. Thus, this builds up the foundation to improve visitor's participation in exhibition and bring about development of exhibition industry by raising visitor's interest.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.195-209
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• 2021

According to the 2019-2020 social media usage survey conducted by the Seoul e-commerce center, 5 out of 10 consumers have experienced shopping through social media. The cost of traditional advertising media has been reduced and advertising spending on social media has risen by 74%, indicating that social media is becoming a more important marketing element. While the number of users of social media has increased and corporate marketing activities have increased accordingly, research has been conducted in various aspects of marketing such as user motivation for social media, satisfaction, and purchase intention. There was no subdivided study on the differences in the social media usage frequency of consumers in actual purchasing behavior. This study attempted to identify differences in consumer characteristics by cluster in the agrifood purchase situation by grouping them by type according to the frequency of use of social media for consumers who purchase agri-food online. Product involvement, product need, and online purchase channel Consumer characteristics such as demographic distribution, perceived risk, and eating and lifestyle in each cluster were checked for the three agrifood purchase situations including choice, and types for each cluster were presented. To this end, questionnaire data on the frequency of social media use and online agrifood purchase behavior were collected from 245 consumers, and the validity of the measurement variables was secured through factor analysis and reliability analysis. As a result of cluster analysis according to the frequency of social media use, it was divided into three clusters. The first cluster was a group that mainly used open social media, and the second cluster was a group that used both open and closed social media and online shopping malls; The third cluster was a group with low online media usage overall, and the characteristics of each cluster appeared. Through regression analysis, the effect on product involvement, product need, and purchase channel selection when purchasing agri-food online through each of the three clusters was confirmed through regression analysis. As a result of the regression analysis, the characteristic of cluster 1 in the situation of purchasing agri-food online is a male in his 30s living in a rural area who has no reluctance to purchase agri-food on social media or online shopping malls. The characteristics of cluster 2 are mainly consumers who are interested in purchasing health food, and the consumer characteristics are represented. In the case of cluster 3, when purchasing products online, they purchase after considering quality and price a lot, and the consumer characteristics are represented as people who are more confident in purchasing offline than online. Through this study, it is judged that by identifying the differences in consumer characteristics that appear in the agri-food purchase situation according to the frequency of social media use, it can be helpful in strategic judgments in marketing practice on social media customer targeting and customer segmentation.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.