• Journal of Information Technology Services
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• v.10 no.4
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• pp.295-307
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• 2011

The purpose of this research is to find a better knowledge service R&D management process. There are four basic characteristics in service : intangibility, inseparability, inconsistency, and no inventory. These intrinsic characteristics require us to change the traditional manufacturing sector based R&D management process. It is necessary to develop an effective knowledge service R&D management model to improve the competitiveness of the service industry and Korean economy. A model case knowledge service R&D has been performed to find a better R&D management model. The whole cycle of R&D process, such as planning, selection, performing, and evaluation has been reviewed by real experience. Several important aspects of R&D process are compared between manufacturing R&D and service R&D. A knowledge service R&D management framework has been suggested. The results of this research can be used for building a better service R&D management process.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.4
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• pp.207-218
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• 2019

The purpose of this study is to develop a model that can systematically study the whole learning process of machine learning. Since the existing model describes the learning process with minimum coding, it can learn the progress of machine learning sequentially through the new model, and can visualize each process using the tensor flow. The new model used all of the existing model algorithms and confirmed the importance of the variables that affect the target variable, survival. The used to classification training data into training and verification, and to evaluate the performance of the model with test data. As a result of the final analysis, the ensemble techniques is the all tutorial model showed high performance, and the maximum performance of the model was improved by maximum 5.2% when compared with the existing model using. In future research, it is necessary to construct an environment in which machine learning can be learned regardless of the data preprocessing method and OS that can learn a model that is better than the existing performance.

• Journal of the Korean Society for information Management
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• v.40 no.1
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• pp.51-71
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• 2023

This study analyzed the government data quality management model, big data quality management model, and data lifecycle model for research data management, and analyzed the components common to each data quality management model. Those data quality management models are designed and proposed according to the lifecycle or based on the PDCA model according to the characteristics of target data, which is the object that performs quality management. And commonly, the components of planning, collection and construction, operation and utilization, and preservation and disposal are included. Based on this, the study proposed a process model for research data quality management, in particular, the research data quality management to be performed in a series of processes from collecting to servicing on a research data platform that provides services using research data as target data was discussed in the stages of planning, construction and operation, and utilization. This study has significance in providing knowledge based for research data quality management implementation methods.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.450-457
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• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.

• Journal of Information Technology Applications and Management
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• v.20 no.3
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• pp.143-167
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• 2013

The main propose of this research is to examine the performances in ERP introduced enterprises by utilizing BSC model proposed by Kaplan and Norton [1992], to realize this goals, a theoretical review on ERP, BSC, and other related issues is performed in advance, accordingly, research model was generated. In conceptual model analysis, we focused on casual relationships among four performance measurement indicators after introduction of ERP proposed by Kaplan and Norton [2000]. To test the model, structural equation modeling is employed to analyze data collected from 164 enterprises which have introduced ERP for more than 1 year. Survey respondents were confined within the representatives of each enterprise's ERP. Hypotheses proposed in our research are tested by covariance structure model, results are listed as follow : First, learning and growth performance is significant factors for improving both internal process performance and customer performance; second, process performance has a positive impact on customer performance third, despite that customer performance is positively related to financial performance, no direct relationship is found between internal process performance and financial performance, an indirect relationship is built through intermediate medium of customer performance. Based upon these results, we discuss implications at the latter part of paper. Meanwhile, we also provide research limitations, and future research in the final section.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• ETRI Journal
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• v.33 no.1
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• pp.110-120
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• 2011

As information technology rapidly develops and the period required to enter new technology shortens, there emerges a wide variety of alternatives for consumers. When there are many alternatives in the market, users choose after making comparisons. This process of making comparisons is our research key. We established a research model to find a mixed effect that comes from new attitudes to technology adoption and alternative's continuous usage intention. The effect is revealed through a relative attractiveness (RA) factor to explain a user's process of comparison. We empirically test our research model in the new media services, such as mobile TV, web TV, and mobile IPTV. According to our research results, a continuous usage intention of an existing technology is an important factor to explain the adoption of a new technology. So, the contribution of our research is in finding a role for the RA factor in research in new technology adoption.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.1065-1069
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• 2005

The construction failures can be decreased through continuous improvement of construction process based upon the information of construction failures. Herein, the information of construction failures can be utilized as the key factor for identifying and enhancing various ineffective construction processes that can prevent failures. This research proposes a process model for the continuous improvement of construction processes by using construction failure information. Extensive reviews and analyses of literatures related to construction failures are performed to investigate its definition, type, cause, and lessons learned. This research adapts process modeling methodology and case-based reasoning for the development of the proposed CIMCP(continuous improvement model of construction process), and then suggests its framework that contains modules of case retrieval, case index, and case adaptation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.737-740
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• 1996

This paper suggests a boltzman machine neural network model to determine model input sequences in line balancing process of mixed model assembly line. We first present a proper energy function, next determine the value of parameters using simulation process.

• Journal of the military operations research society of Korea
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• v.7 no.1
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• pp.53-80
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• 1981

This paper explores a rational investment decision model in sequential capital allocation process under capital rationing. A method is proposed for measuring the new investment decision factor which is the flexibility that describes the future availability of invested funds. This flexibility is important in sequential decision process. Also presented is a multiobjective (MO) decision model into which flexibility is incorporated with the profit and risk factors. The effectiveness of this criterion is compared with the expected present value and the mean-semivariance criteria through a simulation model.