• Annual Conference of KIPS
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• 2012.11a
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• pp.1321-1322
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• 2012

With the advance of Information Technology (IT) and dynamic requirements, diverse application services have been provided for end users. With huge volume of these services and information, users are required to acquire customized services that provide personalized information and decision at particular extent of time. The case is more appealing in healthcare, where patients wish to have access to their medical record where they have control and provided with recommendation on the medical information. PHR (Personal Health Record) is most prevailing initiative that gives secure access on patient record at anytime and anywhere. PHR should also incorporate decision support to help patients in self-management of their diseases. Available PHR system incorporates basic recommendations based on patient routine data. We have proposed decision support service called "Smart CDSS" that provides recommendations on PHR data for diabetic patients. Smart CDSS follows HL7 vMR (Virtual Medical Record) to help in integration with diverse application including PHR. PHR shares patient data with Smart CDSS through standard interfaces that pass through Adaptability Engine (AE). AE transforms the PHR CCR/CCD (Continuity of Care Record/Document) into standard HL7 vMR format. Smart CDSS produces recommendation on PHR datasets based on diabetic knowledge base represented in shareable HL7 Arden Syntax format. The Smart CDSS service is deployed on public cloud over MS Azure environment and PHR is maintaining on private cloud. The system has been evaluated for recommendation for 100 diabetic patients from Saint's Mary Hospital. The recommendations were compared with physicians' guidelines which complement the self-management of the patient.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.63-76
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• 2000

Research on group decisions and electroinc meeting systems have been increasing rapidly according to the widespread of Internet technology. Although various issues have been raised in empirical research, we will try to solve an issue on idea categorizing in the group decision making process of elecronic meeting systems. Idea categorizing used at existing group decision support systems was performed in a top-down procedure and mostly participants\` by manual work. This resulted in tacking as long in idea categorizing as it does for idea generating, clustering an idea in multiple categories, and identifying almost similar redundant categories. However such methods have critical limitation in the electronic meeting systems, we suggest an intelligent idea categorizing methodology which is a bottom-up approach. This method consists of steps to present idea using keywords, identifying keywords\` affinity, computing similarity among ideas, and clustering ideas. This methodology allows participants to interact iteratively for clear manifestation of ambiguous ideas. We also developed a prototype system, IIC (intelligent idea categorizer) and evaluated its performance using the comparision experimetn with other systems. IIC is not a general purposed system, but it produces a good result in a given specific domain.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.1-9
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• 2008

Fuzzy Cognitive Map, one of ways to model, describe and infer reasoning relations, is widely used in the field of reasoning knowledge engineering. Despite of the natural and easy understanding of decision and smooth explanation of relation between front and rear, reasoning relation is organized with mathematical haziness and complex algorithm and rarely has an interactive user interface. This paper suggests an interactive Fuzzy Cognitive Map(FCM) construction support system. It builds a FCM increasingly concerning multiple experts' knowledge. Futhermore, it supports user-supportive environment by dynamically displaying the structure of Fuzzy Cognitive Map which is constructed by the interaction between experts and the system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.171-177
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• 2011

The decision making process is based on accurate and timely available information. To obtain precise information from the internet is becoming more difficult due to the continuous increase in vagueness and uncertainty from online information resources. This also poses a problem for blind people who desire the full use from online resources available to other users for decision making in their daily life. Ontology is considered as one of the emerging technology of knowledge representation and information sharing today. Fuzzy logic is a very popular technique of artificial intelligence which deals with imprecision and uncertainty. The classical ontology can deal ideally with crisp data but cannot give sufficient support to handle the imprecise data or information. In this paper, we incorporate fuzzy logic with heavyweight ontology to solve the imprecise information extraction problem from heterogeneous misty sources. Fuzzy ontology consists of fuzzy rules, fuzzy classes and their properties with axioms. We use Fuzzy OWL plug-in of Protege to model the fuzzy ontology. A prototype is developed which is based on OWL-2 (Web Ontology Language-2), PAL (Protege Axiom Language), and fuzzy logic in order to examine the effectiveness of the proposed system.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1097-1098
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• 2006

This study investigated the needs and effectiveness of the application of Computer-Aided Systems Engineering Tool in order to enhance the chance of success of the large and complex system development projects like City Train System. Furthermore, it was shown that the merits of Systems Engineering and Project Management must be complementary to each other in their interaction in a project. Especially, for the project plans must be executed based on the fully understood system being developed, the technical and management data of the system development need be integrated and be able to support exact and rapid decision making of project planning. As an alternative solution approach, a model for development knowledge capture integrating both technical and management data of system development was proposed using Computer Aided Systems Engineering tool-Cradle.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.99-108
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• 2006

Since mold industries are regarded as belonging to three types of bad business, capable young people are reluctant to work in this field. The industries are hard to employ skilled workers who have much experience and knowledge On the mold manufacturing. Thus, effective CAM systems are required for unskilled workers to create process plans and NC data for the manufacturing, and process plans play important roles in the downstream manufacturing processes, such as NC machining, polishing, and final assembly. This study proposes a decision support system that facilitates unskilled workers to easily select high quality NC-data, as well as to increase productivity. The proposed system is assumed to follow a CAM operation scenario that consists of next three steps: 1) identifying several process plans and enumerating feasible unit machining operations (UMOs) from material and part surface information, 2) creating all feasible NC-data based on UMOs using a commercial CAM system, 3) selecting the best NC data among the feasible NC data using four screening criteria, such as machining accuracy, machining allowance, cutting load, and processing time. A case study on the machining of a camera core mold is provided to demonstrate the proposed system.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.135-149
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• 2011

In this paper, we propose the high-risk group detection model for patients with high blood pressure using case-based reasoning. The proposed model can be applied for public health maintenance organizations to effectively manage knowledge related to high blood pressure and efficiently allocate limited health care resources. Especially, the focus is on the development of the model that can handle constraints such as managing large volume of data, enabling the automatic learning to adapt to external environmental changes and operating the system on a real-time basis. Using real data collected from local public health centers, the optimal high-risk group detection model was derived incorporating optimal parameter sets. The results of the performance test for the model using test data show that the prediction accuracy of the proposed model is two times better than the natural risk of high blood pressure.

• Journal of Information Technology Services
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• v.17 no.4
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• pp.119-137
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• 2018

Recently, the start-up firms have been under the spotlight because they can create many jobs and are regarded as the growth engine of a country in the fourth industrial revolution. Moreover, after the global financial debacle, many countries emphasize on an entrepreneurial spirit and venture firms. they also pay attention to the importance of educations to promote the start-up firms. In this work, based on technology acceptance model, we try to identify the main factors of accepting online start-up education system. We first defined this system as the online start-up education system which refers to a system to support learning for knowledge, experiences and overall process of start-up firms' tasks. This system also simulates tasks related with prep-entrepreneur so that can be regarded as a kind of decision support systems. As this system has some characteristics, we confirmed some factors of extended technology acceptance model. In our experiments, we find that the perceived ease of use and trust are main factors of acceptance for the online start-up education systems. These results mean that the system should be made to be easy and trustful for their users. Therefore, we expect that this work will be helpful to researchers and developers who consider start-up education systems and provide a way to activate founding start-up firms.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.47-67
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• 2013

With the emergence of indirect procurement, it has become a global trend for companies to outsource their maintenance, repair, and operating (MRO) supplies to procurement service providers (PSPs). Due to the variety of MRO items, evaluation of numerous suppliers in various industries is a particularly complex task for PSPs. Due to this complexity, many PSPs still evaluate and select suppliers based on the sourcing managers' subjective knowledge. Through the case of adopting a supplier evaluation system, this research is to find the managerial issues organizations should consider when they transform sourcing managers' knowledge into the system. We interpret the issues based on the Technology-Organization-Environment (TOE) framework. This case conclusively shows the importance of positive feedback loop between the users and the information system for the performance improvement of the system.

• Advances in Computational Design
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• v.3 no.4
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• pp.367-384
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• 2018

The consideration of constructability issues at the design stage can lead to improved construction performance with smooth project delivery and savings in time and money. Empirical studies demonstrate the value obtained by integrating construction knowledge with the building design process, and its benefits for owners, contractors and designers. However, it is still a challenge to implement the concept into current design practice. There is a need for a decision support tool to aid designers in reviewing their design constructability, deploying current technological tools, such as BIM. Such tools are beneficial at the conceptual design stage when there is a room to improve the design significantly with less incurred cost. This research investigates how current process- and object-oriented models can be used to assess design constructability. It proposes a BIM-based model using embedded information within the design environment to conduct the assessment. The modelling framework is demonstrated in four key parts; namely, the conceptual design model, the constructability assessment model, the assessment process model and the decision-making phase. Each is associated with a set of components and functions that contribute towards the targeted constructability assessment outcomes. The proposed framework is the first to combine a numerical assessment system and a rule-based system, allowing for both quantitative and qualitative approaches. The modelling framework and its implementation through a prototype are described in this paper. It is believed that this framework is the first to enable users to transfer their construction knowledge and experience directly into a design platform linked to BIM models. The assessment criteria can be customised by the users who can reflect their own constructability preferences into various specialised profiles that can be added to the constructability assessment model. It also allows for the integration of the assessment process with the design phase, facilitating the optimisation of constructability performance from the early design stage.