• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.73-94
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• 2010

The attending system is a medical system that allows doctors in clinics to use the extra equipment in hospitals-beds, laboratory, operating room, etc-for their patient's care under a contract between the doctors and hospitals. Therefore, the system is very beneficial in terms of the efficiency of the usage of medical resources. However, it is necessary to develop a strong support system to strengthen its weaknesses and supplement its merits. If doctors use hospital beds under the attending system of hospitals, they would be able to check a patient's condition often and provide them with nursing care services. However, the current attending system lacks delivery and assistance support. Thus, for the successful performance of the attending system, a networking system should be developed to facilitate communication between the doctors and nurses. In particular, the nursing records in the attending system could help doctors monitor the patient's condition and provision of nursing care services. A nursing record is the formal documentation associated with nursing care. It is merely a data repository that helps nurses to track their activities; nursing records thus represent a resource of primary information that can be reused. In order to maximize their usefulness, nursing records have been introduced as part of computerized patient records. However, nursing records are internal data that are not disclosed by hospitals. Moreover, the lack of standardization of the record list makes it difficult to share nursing records. Under the attending system, nurses would want to minimize the amount of effort they have to put in for the maintenance of additional records. Hence, they would try to maintain the current level of nursing records in the form of record lists and record attributes, while doctors would require more detailed and real-time information about their patients in order to monitor their condition. Therefore, this study developed a system for assisting in the maintenance and sharing of the nursing records under the attending system. In contrast to previous research on the functionality of computer-based nursing records, we have emphasized the practical usefulness of nursing records from the viewpoint of the actual implementation of the attending system. We suggested that nurses could design a nursing record dictionary for their convenience, and that doctors and nurses could confirm the definitions that they looked up in the dictionary through negotiations with intelligent agents. Such an agent-based system could facilitate networking among medical institutes. Multi-agent systems are a widely accepted paradigm for the distribution and sharing of computation workloads in the scientific community. Agent-based systems have been developed with differences in functional cooperation, coordination, and negotiation. To increase such communication, a framework for a multi-agent based system is proposed in this study. The agent-based approach is useful for developing a system that promotes trade-offs between transactions involving multiple attributes. A brief summary of our contributions follows. First, we propose an efficient and accurate utility representation and acquisition mechanism based on a preference scale while minimizing user interactions with the agent. Trade-offs between various transaction attributes can also be easily computed. Second, by providing a multi-attribute negotiation framework based on the attribute utility evaluation mechanism, we allow both the doctors in charge and nurses to negotiate over various transaction attributes in the nursing record lists that are defined by the latter. Third, we have designed the architecture of the nursing record management server and a system of agents that provides support to the doctors and nurses with regard to the framework and mechanisms proposed above. A formal protocol has also been developed to create and control the communication required for negotiations. We verified the realization of the system by developing a web-based prototype. The system was implemented using ASP and IIS5.1.

• Ecology and Resilient Infrastructure
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• v.8 no.2
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• pp.120-132
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• 2021

The ecosystem and landscape conservation areas of Seoul were designated according to the Natural Environment Conservation Act and the Natural Environment Conservation Ordinance. With the adoption of the "Rapid Assessment of Wetland Ecosystem Service (RAWES)" approach and the "wetland ecosystem service" for the Ramsar Wetland City Accreditation at the 13th Meeting of the Conference of the Contracting Parties to the Ramsar Convention on Wetlands in 2018, the need for data evaluating wetland ecosystem services has become a necessity. Therefore, in this study, we selected five wetlands from the ecosystem and landscape conservation areas in Seoul, having high ecological conservation values, and evaluated their carbon sequestration and economic value assessment using the InVEST model, which is an ecosystem service evaluation technique. The evaluation results for carbon storage in each wetland are as follows: Tancheon Wetland: 3,674.62 Mg; Bamseom Island in the Hangang River: 1,511.57 Mg; Godeok-dong Wetland: 5,007.21 Mg; Amsa-dong Wetland: 7,108.47 Mg; and Yeouido Wetland: 290.27 Mg. Particularly, the Tancheon Wetland showed the lowest carbon sequestration of 1,130.37 Mg, as compared to the results acquired in 2013, of 4,804.99 Mg. When the average effective carbon rate of $16.06 (US) was applied to the decreased carbon sequestration value, a loss of $15,910.58(US) was calculated. Furthermore, if the average social cost of carbon ($204 (US)) is considered, which includes the impact of climate change on productivity and ecosystems, the total loss is equivalent to $202,101.97 (US). This study aims to examine the natural resource value of urban wetlands by evaluating selected major wetlands in Seoul. This study can be utilized as basic data to plan for the protection and management of the ecosystem and landscape conservation areas. Additionally, because wetland value assessment is considered essential, the results of this study can be used in future research to provide measures for evaluating ecosystem services in the Ramsar Wetland City Certification System. Moreover, this study can be utilized for selecting important wetlands as Ramsar sites, and to raise awareness about the significance of conserving urban wetlands, and for expanding international exchange among the Ramsar Wetland sites.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.1-31
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• 2009

This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.

• Korean Journal of Social Welfare
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• v.61 no.3
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• pp.77-101
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• 2009

As a case study in the field of policy implementation research, this study focuses on how the logic of consumer choice and provider competition operates on the front line of policy processing. To find the implementation process of the program, 39 interview data were analyzed, including voucher users, care workers, social workers in 4 agencies and local public officers in one of the district in Seoul, and relevant officials from the Ministry for Health, Welfare and Family affairs and the Center for Social Service Management. The main results are as follows: In the level of policy implementation, user choice and competition, which was the main logic behind the implementation of the voucher program, did not occur as expected by policy makers. Instead of user choosing his/her provider, it was found that the providers were choosing its users. Secondly, the case study found that providers have formed a caucus which allocated the local users equally amongst the providers. In this process, local public officers have supported the meeting by providing them with a list of users. Such results may be interpreted as a habitual execution from the tradition of supply-side subsidy, rather than the way of implementation in the market system. Thirdly, although voucher users could not choose their preferred agency in the first stage of service, some other choices exists so that users may choose their preferred care-giver and time for service. Finally, the change of agency and care-giver in the way of delivering services were observed.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.63-70
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• 2015

The fierce competition of mobile messenger services (MMS) allows MMS providers to perform a variety of marketing campaigns and business activities to enhance user loyalty. The applied model in this study is based on Oliver's four-stage loyalty model for the formation processes of user loyalty about MMS. While social network formation and service quality are the key elements of cognitive loyalty, positive mood and negative mood are the key components of affective loyalty in the study. Conative loyalty is captured by commitment. The data of 249 KakaoTalk users at least five times for three months is empirically tested based on the research model using partial least squares. The analysis of test identifies that positive feeling and commitment significantly influences behavioral loyalty, whereas negative feeling plays a significant role in inhibiting behavioral loyalty. The findings of this study show that social network formation and service quality significantly affect only positive feeling. The analysis results reveal several insights that can help MMS managers understand the roles of cognitive, affective, conative, and behavioral loyalty in the MMS environment.

• Korean Journal of Clinical Pharmacy
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• v.21 no.2
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• pp.122-130
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• 2011

Objective: Although recombinant human erythropoietin (rhEPO) has revolutionized the treatment of anemia in chronic kidney disease (CKD) receiving hemodialysis (HD) with no need of blood transfusion, some patients have a blunted or appear to be resistant to rhEPO. There is a controversy in the causes of rhEPO resistance in maintenance HD patients with anemia. This study is to examine current anemia treatment outcomes and the factors influencing the rhEPO responsiveness in HD patient with CKD. Methods: The clinical parameters or factors relating to erythrompoietin treatment outcomes and erythropoietin responsiveness were collected from the HD patients in two large dialysis centers for three months. The collected paramenters included serum iron, total iron biding capacity (TIBC), transferrin saturation rate, ferritin, albumin, intact PTH, C-reactive protein (CRP), nPCR and medications such as an angiotensin converting enzyme inhbitor, an angiotension II receptor blocker and an HMG-CoA reductase inhibitor (HMG-CoA RI). The data were analyzed to examine the degree of acheiveing the anemia treatment goal and factors relating to ERI. Results: Among total 111 patients, 42 (42.3%) and 47 (37.8%) patients achieved the target Hct and Hb based on the Health Insurance Review and Assessment Services (HIRA) reimbursement criteria. In the higher ERI group (upper quartile), the patients had higher CRP levels (0.5 mg/dl) (p=0.0096), and lower TIBC score (<$240{\mu}g/dl$) (p=0.0027), and less patients were taking HMG-CoA RI (p=0.0019). Male patients (p=0.0204), patients with high TIBC score ($R^2$=0.084, p=0.0021) and patients taking HMG-CoA RI (p=0.0052) required to administer less dose of rhEPO meaning higher erythropoietin responsiveness. Conclusion: Less than 50% of CKD patients were achieving the goals of anemia by erythropoietin administration in large hospitals in Korea even though the goals were lower than those of NKF-K/DOQI practice guideline. The factors influencing ERI were sex, TIBC and HMG-CoA RI administration status, and neither an ACEI nor an ARB did not influence ERI.

• Journal of Distribution Science
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• v.11 no.6
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• pp.67-80
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• 2013

Purpose - This study aims to establish the relationships among brand equity, brand attitudes, and Visual Merchandising (VMD) in bakery stores. The results will help bakery franchisees and franchisers in devising appropriate strategies for successfully managing their bakery shops. Research design, data, and methodology - The VMD model for bakery shops comprises harmony, attractiveness, suitability, pandemic, functionality, and reliability. Further, brand equity encompasses brand awareness, perceived quality, and brand image. In this study, the VMD factors of bakery shops are used as independent variables, while brand equity and brand attitude are used as dependent variables. This study aims to ascertain the extent of the influence VMD components of bakery shops have on brand equity and brand attitude. Regression analysis was used to verify those effects. The measurement items, deemed reliable and valid in a previous study, were modified for this study. Questionnaires were distributed to 500 consumers nationwide, of whom 340 were used for the sample. The SPSS 19.0 statistical program was used for the analysis. Results - First, among the VMD bakery shop components, harmony, attractiveness, and pandemic have a positive impact on brand equity (brand awareness and brand image). Second, amongst the VMD components of bakery shops, attractiveness, pandemic, and reliability have a positive impact on brand equity (perceived quality). Third, amongst the VMD components of bakery shops, harmony, attractiveness, and reliability have a positive impact on brand attitude. Fourth, brand equity (brand awareness, brand image, and perceived quality) have a positive effect on brand attitude. Conclusions - This study identifies the relationships between the VMD components of a bakery shop and brand equity and attitude in order to propose a new model. The study has several practical implications. First, the development of brand equity and management can be important components in bakery shops' determination of whether their VMD components have an impact on brand equity. Second, among VMD components, harmony and attractiveness have a positive influence on the choice of bakery shop, while reliability and pandemic have a partly positive influence on the choice of bakery shop. Therefore, store atmospheres should be attractively designed, and store menus and interiors should be reviewed periodically to conform to the latest trends. This study suggests marketing strategies for brand equity formation. First, providing collateral product quality, hygiene, and safety benefits as well as product offerings to complement the season and employees' services should be considered. Second, display methods, illumination designs, and new product ideas should be periodically reviewed. Third, these should complement the overall harmony of the interior and exterior and of the store atmosphere in order to be attractive. Funds should thus be dedicated specifically for the facilities and their interiors. Fourth, it is necessary to build a friendly and relaxed image that can be easily called to mind by the customers.

• Weed & Turfgrass Science
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• v.3 no.2
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• pp.102-109
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• 2014

This study was conducted in order to utilize the basic data for weed control by surveying the occurrence of weed species and the degree of damages caused by those weeds occurred in cultivated Coix lacryma-jobi var. mayuen fields. Survey was carried out three times, from June to September in 2013. The weed flora was composed of a total of 98 weeds, 33 family, of which 58 species were annual, 21 species were biennial, and 19 were perennial plants. Thirty-one exotic species were included as well. Dominance was the highest with Digitaria ciliaris followed by Acalypha australis, Echinochloa crus-galli, Portulaca oleracea, Bidens frondosa etc. in order. In the PCA plot analysis, weeds occurred in C. lacryma-jobi var. mayuen fields were divided into three groups, Panicum dichotomitlorum community, Echinochloa crus-galli-Sigesbeckia pubescens community and Acalypha australis community. Yield of C. lacryma-jobi var. mayuen was reduced 60% in no weeding plots comparing to that in weed management plots.