• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.243-249
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• 2008

Based on a comprehensive framework that reflects lifecycle requirements of KMs and BPMs, we propose an PKMS(Process based KMS) for integrating KMs and BPMs in order to combine the advantages of the two paradigms. This paper first defines the priority order of knowledge according to knowledge type and classifies it into three groups which consist of Basic KM, Practical KM and Reference KM. Then, it suggests PKMS knowledge map composed of much core-knowledge each of which has information about a unit of the related business process. Using the PKMS Knowledge map, we can directly provide related core-knowledge related for the business process while a person is working a unit of business process. This paper designed the PKMS applied to employment insurance business part. Long term goal of the concepts is to concern a change management organization of knowledge on PKMS.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.2
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• pp.103-123
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• 2006

Assuming that the knowledge creation and retrieval functions could be the most important factors for a successful knowledge management(KM) especially during the promotion stage of KM, this study suggests an e-learning application as one of best methods for producing knowledge and also the integrated knowledge repository model in which learning, knowledge. and information objects can be semantically associated through topic map-based knowledge map. The traditional KM system provides a simple directory-based knowledge map. which can not provide the semantic links between topics or objects. The proposed model can be utilized as a solution to solve the above-mentioned disadvantages of the traditional models. In order to collect the basic data for the proposed model, first, case studies utilizing interviews and surveys were conducted targeting at three Korean insurance companies' knowledge managers(or e-learning managers) and librarians. Second, the related studies and other topic map-based pilot systems were investigated.

• Journal of Intelligence and Information Systems
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• v.5 no.2
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• pp.79-97
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• 1999

Knowledge management (KM) is emerging as a robust management mechanism with which an organization can remain highly intelligent and competitive in a turbulent market. Organization knowledge is at the heart of KM success. As a vehicle of acquiring organizational knowledge in a distributed decision-making environment, we applied a fuzzy cognitive map (FMM) technique and proved its effectiveness in a distributed knowledge management environment. Our approach was applied to the financial statement analysis problem, yielding a robust result.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.111-114
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• 2004

Management of human knowledge is an interesting concept that has attracted the attention of philosophers for thousands of years. Artificial intelligence and knowledge engineering has provided some degree of rigor to the study of knowledge systems and expert systems(ES) re able to use knowledge to solve the problems and answer questions. Therefore, the process of conceptualization and inference of knowledge are fundamental problem solving activities and hence, are essential activities for solving the problem of software ES construction Especially, the access to relevant, up-to-date and reliable knowledge is very important task in the daily work of physicians and nurses. In this study, we propose the conceptualization and inference mechanism for implicit knowledge management in medical diagnosis area. To this purpose, we combined the dynamic knowledge map(KM) and relational database(RDB) into a dynamic knowledge map(DKM). A graphical user-interface of DKM allows the conceptualization of the implicit knowledge of medical experts. After the conceptualization of implicit knowledge, we developed an RDB-based inference mechanism and prototype software ES to access and retrieve the implicit knowledge stored in RDB. Our proposed system allows the fast comfortable access to relevant knowledge fitting to the demands of the current task.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.9-12
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• 2004

Developing an efficient knowledge base construction mechanism as an input method for expert systems (ES) development is of extreme importance due to the fact that an input process takes a lot of time and cost in constructing an ES. Most ES require experts to explicit their tacit knowledge into a form of explicit knowledge base with a full sentence. In addition, the explicit knowledge bases were composed of strict grammar and keywords. To overcome these limitations, this paper proposes a knowledge conceptualization and construction mechanism for automated knowledge acquisition, allowing an efficient decision. To this purpose, we extended traditional knowledge map (KM) construction process to dynamic knowledge map (DKM) and combined this algorithm with relational database (RDB). In the experiment section, we used medical data to show the efficiency of our proposed mechanism. Each rule in the DKM was characterized by the name of disease, clinical attributes and their treatments. Experimental results with various disease show that the proposed system is superior in terms of understanding and convenience of use.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.101-107
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• 2006

In this research, we propose a hybrid inference architecture for medical diagnosis based on dynamic knowledge map (DKM) and relational database (RDB). Conventional expert systems (ES) and developing tools of ES has some limitations such as, 1) time consumption to extend the knowledge base (KB), 2) difficulty to change the inference path, 3) inflexible use of inference functions and operators. To overcome these Limitations, we use DKM in extracting the complex relationships and causal rules from human expert and other knowledge resources. The DKM also can help the knowledge engineers to change the inference path rapidly and easily. Then, RDB and its management systems help us to transform the relationships from diagram to relational table.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.400-405
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• 2013

The purpose of this study is to develop a composite platform for knowledge extractions, visualizations, and inference. Generally, the big data sets were frequently used in the healthcare and medical area. To help the knowledge managers/users working in the field, this study is focused on knowledge management (KM) based on Data Mining (DM), Knowledge Distribution Map (KDM), Decision Tree (DT), RDBMS, and SQL-inference. The proposed mechanism is composed of five key processes. Firstly, in Knowledge Parsing, it extracts logical rules from a big data set by using DM technology. Then it transforms the rules into RDB tables. Secondly, through Knowledge Maintenance, it refines and manages the knowledge to be ready for the computing of knowledge distributions. Thirdly, in Knowledge Distribution process, we can see the knowledge distributions by using the DT mechanism.Fourthly, in Knowledge Hierarchy, the platform shows the hierarchy of the knowledge. Finally, in Inference, it deduce the conclusions by using the given facts and data.This approach presents the advantages of diversity in knowledge representations and inference to improve the quality of computer-based medical diagnosis.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.2
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• pp.79-85
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• 2023

The Tibetan Plateau is home to the only alpine crane species, the black-necked crane (Grus nigricollis). Conservation efforts are severely hampered by a lack of knowledge on the spatial distribution and breeding habitats of this species. The ecological niche modeling framework used to predict the spatial distribution of this species, based on the maximum entropy and occurrence record data, allowed us to generate a species-specific spatial distribution map in Ladakh, Trans-Himalaya, India. The model was created by assimilating species occurrence data from 486 geographical sites with 24 topographic and bioclimatic variables. Fourteen variables helped forecast the distribution of black-necked cranes by 96.2%. The area under the curve score for the model training data was high (0.98), indicating the accuracy and predictive performance of the model. Of the total study area, the areas with high and moderate habitat suitability for black-necked cranes were anticipated to be 8,156 km² and 6,759 km², respectively. The area with high habitat suitability within the protected areas was 5,335 km². The spatial distribution predicted using our model showed that the majority of speculated conservation areas bordered the existing protected areas of the Changthang Wildlife Sanctuary. Hence, we believe, that by increasing the current study area, we can account for these gaps in conservation areas, more effectively.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.57.3-57.3
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• 2021

99942 Apophis is an Sq-type Potentially Hazardous Asteroid (PHA) with an estimated diameter of 370 m. It will approach the Earth down to 31,000 km from the surface during the encounter on April 13, 2029 UT, which is closer than geostationary satellites. This once-in-a-20,000 year opportunity would further expand our knowledge on the physical and dynamical processes which are expected to occur due to the gravitational tidal forces when an asteroid encounter with a planet. It will also provide an opportunity to promote great knowledge of the science of planetary defense. The science goal of the Apophis mission is to global-map the asteroid before and after the Earth's approach. In this talk, we will present scientific objectives, and briefly introduce instruments and operation scenarios of the mission.

• Korean Journal of Plant Taxonomy
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• v.43 no.2
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• pp.128-138
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• 2013

The conservation status of an endemic perennial herb, Hanabusaya asiatica (Nakai) Nakai (Campanulaceae) was determined by applying the IUCN risk assessment criteria from our field study and available specimen data. Also, the GIS technology was used to develop a species distribution map to calculate the extent of occurrence (EOO) and area of occupancy (AOO) for the taxon. After two years of continuous field studies, 269 mature individuals were found in four localities in 2011, while 216 mature individuals were confirmed in three localities in 2012. Based on the following data, such as EOO (2,742 $km^2$), AOO (76 $km^2$) and estimated population size of mature individuals, the taxon, which is known as 20 localities in Korean peninsula, is evaluated as the category of Endangered (EN). A major difficulty in application of IUCN criteria to Korean rare plants were the lack of essential biological information and understanding the correct knowledge of the IUCN criteria in previous Korean studies. Sound conclusions regarding the conservation status of individual species require more intensive population studies, observations, and applying IUCN assessment procedures correctly.