• Journal of the Korean Society of Marine Environment & Safety
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• v.16 no.1
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• pp.11-20
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• 2010

Oyster production is playing an important role in domestic aquaculture, but facing some problems such as exports decrease, a slowdown in domestic demand and marine environmental deterioration. In order to obtain the suitable and sustainable oyster production, suitable sites selection is an important step in oyster aquaculture. This study was conducted to identify the suitable sites for lunging culture of oyster using Geographic Information System(GIS)-based multi-criteria evaluation methods. Most of the parameters were extracted by Inverse Distance Weighted(IDW) methods in GIS and eight parameters were grouped into two basic sub-models for oyster aquaculture, namely oyster growth sub-model(Sea Temperature, Salinity, Hydrodynamics, Chlorophyll-a) and environment sub-model(Bottom DO, TOC, Sediment AVS, Benthic Diversity). Suitability scores were ranked on a scale from 1(leased suitable) and 8(most suitable), and about 80.1% of the total potential area had the highest scores 5 and 6. These areas were shown to have the optimum condition for oyster culture in GeojeHansan Bay. This method to identify suitable sites for oyster culture may be used to develop bivalve culture management system for supporting a decision making.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.403-409
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• 2024

In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.10
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• pp.239-246
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• 2020

In the medical field where artificial intelligence technology is introduced, research related to clinical decision support system(CDSS) in relation to diagnosis and prediction is actively being conducted. In particular, medical imaging-based disease diagnosis area applied AI technologies at various products. However, medical imaging data consists of inconsistent data, and it is a reality that it takes considerable time to prepare and use it for research. This paper describes a one-stop AI learning platform for converting to medical image standard R_CDM(Radiology Common Data Model) and supporting AI algorithm development research based on the dataset. To this, the focus is on linking with the existing CDM(common data model) and model the system, including the schema of the medical imaging standard model and report information for multi-center research based on DICOM(Digital Imaging and Communications in Medicine) tag information. And also, we show the execution results based on generated datasets through the AI learning platform. As a proposed platform, it is expected to be used for various image-based artificial intelligence researches.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.80-91
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• 2008

The Purpose of this study is the applicaion of social network analysis for expanding the use of spatial data in local government. Spatial data generated from UIS projects play very important roles as a means of supporting decision making and solving complicated urban problems, but the utilization of the spatial data has not reach the expected level, considering to the huge amount of investment. Accordingly, there should be efforts in efficient management of spatial data, establishment of a sharing system, and expanded utilization of spatial data. Social network analysis applied to this research is a theory that explains the behaviors and patterns of units forming the system and measures distances between nodes, strength, etc. based on relations among nodes forming the network and the structural characteristics of the network. According to the results of surveying civil servants who were using spatial data on Busan Metropolitan City, obstacles to the sharing of spatial data were mostly non technical factors related to data users' attitude and their relations with circumstances. In order to expand the use of spatial data, this study performed social network analysis that applied the theory of planned behavior and examined the flow of spatial data, and by doing so, we analyzed related personnel's perception, identified obstacles to data sharing, and suggested a framework for promoting the expanded utilization of spatial data.

• Journal of Distribution Science
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• v.4 no.2
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• pp.21-40
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• 2006

Small and middle sized Franchise system channels experience conflicts because of constant interaction between franchiser and franchisee. However, it is rarely that attempt has been made to identify causes of conflicts in distribution of franchise industry. The purpose of this study was to explore cause of conflicts from the franchisee. For the study, data were collected from the owner or the shop-manager with a contractor in franchise systems. By means of in-depth interviews with multiple informants, their statement was analyzed qualitatively. From analysis of the resulting data, the causes of conflicts were associated with two broad sets, attitudinal and structural differences between franchisers and franchisees. First, attitudinal sources of conflict were identified as perception of subordinated relationships between channel members, delayed announcement on order changes, difficulties in communication by doing irresponsible behavior, different expectations between channel members in market territory and lack of consistent-supporting. Second, structural sources of conflict involved unilateral decision on interior, payment method, unreasonable delivery issue, treat franchisee with discrimination by the sales, in controlling against free management. There are limitations on generalization due to the results based on interview, but this study will be a useful exploratory step before designing a large scale survey.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.183-194
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• 2004

The existing management job of research expenses has been divided into three parts： budget planning, budget draw-up, and exact settlement of budget. However, it caused some problems. Under this current circumstance it is required to obtain research expenses steadily, to operate efficiently and to use them clearly to solve such problems. As a result of a study on data warehouse development process of existing system integration company (Inmon, IBM) to reflect current trend described above, data warehouse development process of Inmon uses systematic and gradual access as a classical development cycle method. It causes overlap and feedback to the previous step in the process of each step Is requested. And another problem that it is difficult to toil what function refers and corrects data because functions and data are separated during performing development process at data warehouse development process of IBM is caused. Integrated management data warehouse development process of research expenses in the enterprise environment which applies UML at planning and analysis step, design step and implement and test step is suggested in this paper. Information retrieval agent uses existing budget plan DB, budget draw-up DB and budget settlement DB to find out information that a user wants to know. Information retrieval agent collects and saves information at integration database and information integration agent extracts, transports, transforms and loads the data. Information integration agent reduces a user's efforts to access to a number of information sources and check each of them. It also screens out data that a user may not need. As a result, integrated management data warehouse development process of research expenses in the enterprise environment reflects a user's requirements as much as possible and provides various types of information to make a decision which is needed to establish the policy of research expense management. It helps an end user approach his/her desired analysis information quickly and get various data from the comprehensive viewpoint rather than the fragmentary viewpoint. Furthermore, as it integrated three systems into one, it is possible to share data, to integrate the system, to reduce operating expenses and to simplify supporting environment for the decision making.

• Journal of Physiology & Pathology in Korean Medicine
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• v.25 no.5
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• pp.765-772
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• 2011

Knowledge which is represented by formal logic are widely used in many domains such like artificial intelligence, information retrieval, e-commerce and so on. And for medical field, medical documentary records retrieval, information systems in hospitals, medical data sharing, remote treatment and expert systems need knowledge representation technology. To retrieve information intellectually and provide advanced information services, systematically controlled mechanism is needed to represent and share knowledge. Importantly, medical expert's knowledge should be represented in a form that is understandable to computers and also to humans to be applied to the medical information system supporting decision making. And it should have a suitable and efficient structure for its own purposes including reasoning, extendability of knowledge, management of data, accuracy of expressions, diversity, and so on. we call it ontology which can be processed with machines. We can use the ontology to represent traditional medicine knowledge in structured and systematic way with visualization, then also it can also be used education materials. Hence, the authors developed an Shanghanlun ontology by way of showing an example, so that we suggested a methodology for ontology development and also a model to structure the traditional medical knowledge. And this result can be used for student to learn Shanghanlun by graphical representation of it's knowledge. We analyzed the text of Shanghanlun to construct relational database including it's original text, symptoms and herb formulars. And then we classified the terms following some criterion, confirmed the structure of the ontology to describe semantic relations between the terms, especially we developed the ontology considering visual representation. The ontology developed in this study provides database showing fomulas, herbs, symptoms, the name of diseases and the text written in Shanghanlun. It's easy to retrieve contents by their semantic relations so that it is convenient to search knowledge of Shanghanlun and to learn it. It can display the related concepts by searching terms and provides expanded information with a simple click. It has some limitations such as standardization problems, short coverage of pattern(證), and error in chinese characters input. But we believe this research can be used for basic foundation to make traditional medicine more structural and systematic, to develop application softwares, and also to applied it in Shanghanlun educations.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.159-169
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• 2012

The purpose of this study was to assess the vulnerability of forest ecosystem to climate change in South Korea using socio-environmental indicators and the results of two vegetation models named as Hydrological and Thermal Analogy Group(HyTAG), and MAPSS-Century 1(MC1). The changing frequency and direction of biome types estimated by HyTAG model was used for quantifying sensitivity and adaptive capacity of forest distribution. Similarly, the variation and changing tendency of net primary production and soil carbon storage estimated by MC1 model was used for quantifying sensitivity and adaptive capacity of forest function. As socio-environmental indicators, many statistical data such as financial autonomy rate and the number of forestry officer was prepared. All indicators were standardized, and then calculated using the vulnerability assessment equation. The period of vulnerability assessment was divided into the past(1971-2000) and the future(2021-2050). To understand what policy has a priority to climate change, distribution maps of each indicators was depicted and the vulnerability results were compared among administrative districts. Evident differences could be found in entire study area. These differences were mostly derived from regionalspecific adaptive capacity. The result and methodology of this study would be helpful for the development of decision-making supporting system and policy making in forest management with respect to climate change.

• Korean Journal of Construction Engineering and Management
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• v.11 no.6
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• pp.35-44
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• 2010

For efficient maintenance management of bridges, an establishment of asset management system is necessary which helps prediction of maintenance cost and strategic allocation of budget in consideration of top priority. The main purpose of this study is to suggest asset valuation method, which is practical in conformity with domestic situations, through researches on asset valuation method of bridges. This study has researched asset valuation method of bridge, which is appropriate for domestic situations by finding out advantages and disadvantages through investigating domestic and foreign application examples of asset valuation method for bridge facilities. In this study, asset valuation method by historical cost and replacement cost were suggested and a valuation model for bridges was established. In addition, two suggested valuation methods were applied to actual bridges which is used in Korea. As the result, it was analyzed that bridge asset valuation method in consideration of historical cost is desirable for the accounting purpose. And, it was analyzed that valuation method utilizing depreciated replacement cost(DRC), which could consider various factors, is desirable for the maintenance decision supporting purpose.