• Asia pacific journal of information systems
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• v.8 no.2
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• pp.53-67
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• 1998

The explosive growth of the Web is providing end-users access to ever-increasing volumes of information. The resources of legacy systems and relational databases have also been made available to the Web browser, which has become an essential business tool. Recently, model management on the Internet/Web is also proposed with its conceptual design or prototypical system like DecisionNet and DSS Web. However, they are also suffering from the same symptoms as the Web, Although we can identify the elements of a page with HTML tags and (declare) the relationships among the various document elements, they are semantically opaque to computer systems and have no domain-specific meaning. However, HTML is not extensible, so developers are forced to invent convoluted, non-standard solutions for embedding and parsing data. Extensible Markup Language (XML) is a simplified subset of SGML that has many benefits for folks who want to improve structure, maintainability, searchability, presentation, and other aspects of their document management. This paper proposes a structured markup language for model representation and management on the Web as an XML application. The language is based on a conceptual modeling framework, Object-Oriented Structured Modeling (OOSM), which is an extension of the structured modeling.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1496-1515
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• 2017

One of the most visible developments in Decision Support Systems (DSS) was the emergence of rule-based expert systems. Hence, despite their success in many sectors, developers of Medical Rule-Based Systems have met several critical problems. Firstly, the rules are related to a clearly stated subject. Secondly, a rule-based system can only learn by updating of its rule-base, since it requires explicit knowledge of the used domain. Solutions to these problems have been sought through improved techniques and tools, improved development paradigms, knowledge modeling languages and ontology, as well as advanced reasoning techniques such as case-based reasoning (CBR) which is well suited to provide decision support in the healthcare setting. However, using CBR reveals some drawbacks, mainly in its interrelated tasks: the retrieval and the adaptation. For the retrieval task, a major drawback raises when several similar cases are found and consequently several solutions. Hence, a choice for the best solution must be done. To overcome these limitations, numerous useful works related to the retrieval task were conducted with simple and convenient procedures or by combining CBR with other techniques. Through this paper, we provide a combining approach using the multi-criteria analysis (MCA) to help, the traditional retrieval task of CBR, in choosing the best solution. Afterwards, we integrate this approach in a decision model to support medical decision. We present, also, some preliminary results and suggestions to extend our approach.

• Korean Journal of Oriental Medicine
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• v.13 no.2 s.20
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• pp.75-81
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• 2007

The need for the study of the revealing Sasang constitution at scientific term is increasing as the application of this discipline to the patient produces more accurate result. To obtain scientific evidence of Sasang constitution, it is crucial to analyze accumulated clinical information and associate them to the biological indices that may classify Sasang constitution. Thus, the analysis of clinical information is the most important stepping stone to go toward to the stage of developing model and decision support system (DSS) for classifying Sasang constitution. This study is a preliminary analysis of 1,109 samples collected with 171 clinical indices. To find meaningful clinical indices for classifying Sasang constitutional medicine, we applied decision tree model for them. The skin of 66.5% within whole Taeeumin is thick and non feeble. In the case of 69.8% within whole Soyangin, the skin is non feeble and slippery. In the case of 64.4% within whole Soeumin. they have feeble skin. Therefore, the property of skin can be suggested to be more important than any other index for the classification of Sasang constitution.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.5
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• pp.96-105
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• 2002

As an useful water purification system for non-point source pollution in rural watersheds, interests in constructed wetlands are growing at home and abroad. It is well known that constructed wetlands are easily installed, no special managemental needs, and more flexible at fluctuating influent loads. They have a capacity for purification against nutrient materials such as phosphorus and nitrogen causing eutrophication of lentic water bodies. The Constructed Wetland Design Model (CWDM), developed through this study is consisted mainly of Database System, Runoff-discharge Prediction Submodel, Water Quality Prediction Submodel, and Area Assessment Submodel. The Database System includes data of watershed, discharge, water quality, pollution source, and design factors for the constructed wetland. It supplies data when predicting water quality and calculating the required areas of constructed wetlands. For the assessment of design flow, the GWLF (Generalized Watershed Loading Function) is used, and for water quality prediction in streams estimating influent pollutant load, Water Quality Prediction Submodel, that is a submodel of DSS-WQMRA model developed by previous works is amended. The calculation of the required areas of constructed wetlands is achieved using effluent target concentrations and area calculation equations that developed from the monitoring results in the United States. The CWDM is applied to Bokha watershed to appraise its application by assessing design flow and predicting water quality. Its application is performed through two calculations: one is to achieve each target effluent concentrations of BOD, SS, T-N and T-P, the other is to achieve overall target effluent concentrations. To prove the validity of the model, a comparison of unit removal rates between the calculated one from this study and the monitoring result from existing wetlands in Korea, Japan and United States was made. As a result, the CWDM could be very useful design tool for the constructed wetland in rural watersheds and for the non-point source pollution management.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.177-191
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• 2007

Supplier relationship management (SRM) is an important contributor to a company's efficiency and credibility. Although several ways are used to provide SRM functionality, these are often not easily integrated with existing procurement systems. We designed and implemented a practical SRM system called BestChoice SRM and present its design and architecture. It has the core functionality of SRM with the simple adaptability of BestChoice which is a decision support system for evaluating suppliers with the aid of visualized analysis It allows seamless integration with existing systems and permits flexible strategy changes as market conditions shift. The key to this flexibility is template-based segmentation. Ease of integration was demonstrated through the installation of BestChoice SRM at a major Korean commercial e-procurement agency.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1156-1166
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• 1999

의사결정 시스템은 전사적인 의사결정과 전략적 정보수집을 위해 거대한 량의 정보를 빠른 시간내에 제공할 것을 요구한다. 데이타 웨어하우스는 이러한 정보를 신속히 제공하기 위해 여러 지역 데이타베이스로부터 필요한 정보를 사전에 추출하고 가공 및 통합하여 별도의 저장공간에 저장한다. 일반적으로, 웨어하우스 내의 정보는 지역 데이타베이스에 저장된 정보에 대한 실체화된 뷰로서 간주하며 지역 데이타의 변경에 따라 일관성을 유지하도록 반영해야 한다. 본 논문에서는 일관성을 유지하기 위해 정보 공유가 가능한 데이타 웨어하우스 시스템의 구조와 비-보상 실체 뷰 관리 기법을 제안한다. 본 논문에서 제안한 데이타 웨어하우스 시스템의 구조는 지역 데이타베이스에서 추출된 정보를 관리하는 별도의 지역 정보 관리자를 두어 뷰 관리자들 간의 정보 공유가 가능하게 한다. 비-보상 실체 뷰 관리 기법은 지역 데이타 변경 사건에 따른 뷰 관리 시 다른 사건에 의해 영향을 받지 않도록 하기 때문에 기본의 사전 보상이나 나중 보상 기법과는 달리 추가적인 질의 처리를 요구하지 않는 기법이다.Abstract A decision support system(DSS) commonly requires fast access to tremendous volume of information. A data warehouse is a database storing the information that is extracted, filtered and integrated from several relevant local databases to reply upon aggregated queries. The information stored in the data warehouse can be regarded as materialized views. The materialized view has to be modified according to the change of the corresponding local databases to preserve the data consistency. In this paper, we propose a data warehousing system architecture allowing information sharing (DAWINS), and a non-compensating materialized view maintenance algorithm(NCA). DAWINS architecture allows relevant information to be shared by individual view managers with local data manager for each local database. Unlikely to the pre- or post-compensating algorithms, which are required to remove the effects of some events to other view in the process of view maintenance, NCA does not require any additional query processing, since a local data manager in DAWINS already maintains the effects of update events occurring in local systems.

• Journal of Satellite, Information and Communications
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• v.8 no.1
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• pp.8-13
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• 2013

It is necessary to develop the next generation FTS which is suitable for our environment and effectively operates many launch vehicles. Standard tone, Secure tone, MHA, EFTS and DSSS are studied for the next generation FTS. FTS requires a high quality of performance and reliability because of their specific mission. And few FTSs are needed but the price is very expensive. Therefore we must investigate a part of the FTS whether the part can be reused for a part of the next FTS. In this paper, we use CCDF of the transmitted signal from FTS as the method to study a possibility of reusing HPA used in the present system. The simulation results show that PEP of Standard tone is 0.21dB and Secure tone and MHA has the same PEP. CPFSK's PEP is 1.81dB and PEP of DSSS using BPSK modulation is 2.6dB.

• Journal of Korean Academy of Nursing
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• v.45 no.5
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• pp.723-732
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• 2015

Purpose: The purpose of this study was to develop a system dynamics model for adolescent obesity in Korea that could be used for obesity policy analysis. Methods: On the basis of the casual loop diagram, a model was developed by converting to stock and flow diagram. The Vensim DSS 5.0 program was used in the model development. We simulated method of moments to the calibration of this model with data from The Korea Youth Risk Behavior Web-based Survey 2005 to 2013. We ran the scenario simulation. Results: This model can be used to understand the current adolescent obesity rate, predict the future obesity rate, and be utilized as a tool for controlling the risk factors. The results of the model simulation match well with the data. It was identified that a proper model, able to predict obesity probability, was established. Conclusion: These results of stock and flow diagram modeling in adolescent obesity can be helpful in development of obesity by policy planners and other stakeholders to better anticipate the multiple effects of interventions in both the short and the long term. In the future we suggest the development of an expanded model based on this adolescent obesity model.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.1-12
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• 2016

The current economic crisis is making new demands on manufacturing industry, in particular, in terms of the flexibility and efficiency of production processes. This requires production and administrative processes to be meshed with each other by means of IT systems to optimise the use and capacity utilisation of machines and lines but also to be able to respond rapidly to wrong developments in production and thus to minimise adverse impacts on the business. The future scenario of the "smart factory" represents the zenith of this development. The factory can be modified and expanded at will, combines all components from different manufacturers and enables them to take on context-related tasks autonomously. Integrated user interfaces will still be required at most for basic functionalities. The complex control operations will run wirelessly and ad hoc via mobile terminals such as PDAs or smartphones. The comnination of IoT, and Big Data optimisation is bringing about huge opportunities. these processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to big data to inform their decision support. Building a smart factory with smart assets at its core means reaching those desired new levels of productivity and efficiency. It means smart products that leverage advanced traceability, connectivity and intelligence. For businesses, it means being able to address the talent crunch through more autonomous. In a Smart Factory, machinery and equipment will have the ability to improve processes through self-optimization and autonomous decision-making.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.700-706
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• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.