• Management Science and Financial Engineering
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• v.8 no.1
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• pp.21-38
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• 2002

Rapid advances in information technology(IT) and telecommunication systems impact the number and quality of decision-making in organizations. Specifically, middle mangers must posses or develop the creativity necessary for survival in a constantly changing and volatile business environment. While tradition and conventional wisdom tell us that a middle managers role centers on control and monitoring, todays competitive arena has spun out a new managerial requirement developing and maintaining an innovative attitude. Problematically, most previous research has focused on the issue of changing decision authority (i. e. centralization/decentralization). Moreover, much previous research has also largely ignored environmental changes exposing new roles that middle managers have assumed. This study explores the means of identifying middle managerial roles, managerial possibilities involving the growing popularity of open systems through electronic brainstorming, and an adaptation and development of Diffusion Theory and attempt to counter criticism leveled at the theory's inability to provide an adequate explanation for diffusion of complex organizational technology. This paper develops three ideas: 1) Introducing the 'Chasing Curve' as a theoretical background. 2) Suggesting a new methodology using electronic brainstorming for analyzing the gap between Knowing (the perceived importance of middle managers' roles) and Doing (the degree of current status of middle managers' roles), which we term the 'Spiral Gap Analysis Model'. 3) Identifying a feedback system for minimizing the Knowing - Doing gap, aimed at development of IT strategic priority decision support, which we call this the 'Star Process'.

• IE interfaces
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• v.24 no.3
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• pp.267-273
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• 2011

In the shipbuilding industry, since production processes are so complicated that the data collection for decision making cannot be fully automated, most of production planning and controls are based on the information provided only by field workers. Therefore, without sufficient information it is very difficult to manage the whole production process efficiently. Job status is one of the most important information used for evaluating the remaining processing time in production control, specifically, in block assembly shop. Currently, it is checked by a production manager manually and production planning is modified based on that information, which might cause a delay in production control, resulting in performance degradation. Motivated by these remarks, in this paper we propose an efficient algorithm for identifying job status in block assembly shop for shipbuilding. The algorithm is based on the multi-layer perceptron neural network model using two key factors for input parameters. We showed the superiority of the algorithm by using a numerical experiment, based on real data collected from block assembly shop.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.124-130
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• 2004

Microarray expression datasets are incessantly cumulated with the aid of recent technological advances. One of the first steps for analyzing these data under various experimental conditions is determining differentially expressed genes (DEGs) in each condition. Reasonable choices of thresholds for determining differentially expressed genes are used for the next -step-analysis with suitable statistical significances. We present a model for identifying DEGs using pathway information based on the global connectivity structure. Pathway information can be regarded as a collection of biological knowledge, thus we are tying to determine the optimal threshold so that the consequential connectivity structure can be the most compatible with the existing pathway information. The significant feature of our model is that it uses established knowledge as a reference to determine the direction of analyzing microarray dataset. In the most of previous work, only intrinsic information in the miroarray is used for the identifying DEGs. We hope that our proposed method could contribute to construct biologically meaningful network structure from microarray datasets.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.272-279
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• 1997

In this paper, a fuzzy generalized predictive control (FGPC) for non-linear plants is proposed. In the proposed method, the receding horizon control is applied to the control part, while fuzzy systems are used for the predictor part. It is suggested that the fuzzy predictor is time-varying affine with respect to input variables for easy computation of control inputs. Since the receding horizon control can be obtained only with a predictor instead of a plant model, the fuzzy predictor is obtained directly from input-output data without identifying a plant model. A parameter estimation algorithm is used for identifying the fuzzy predictor. The control inputs of the FGPC are computed by minimizing a receding horizon cost function with predicted plant outputs. The proposed controller has a similar architecture to the generalized predictive control (GPC) except for the predictor synthesis method, and thus may possess inherent good properties of the GPC. Computer simulations show that the performance of the FGPC is satisfactory.

• International Journal of Contents
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• v.16 no.4
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• pp.1-15
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• 2020

This study examined the impact of chatbot service quality (process quality, outcome quality, and servicescape quality) on user satisfaction and reliability by identifying the relationships between user satisfaction, reliability, immersion, and the paths of three variables influencing reuse intention. The survey was conducted of Korean users in their teens and 70s who had experience using chatbot services. A total of 218 convenience samples were extracted and the data analyzed. By the IS success and SERVQUAL model, the results of structural equation modeling revealed that the chatbot service quality did not affect user satisfaction and reliability. However, user satisfaction and reliability of the chatbot services were shown to lead to reuse intention, and user satisfaction was shown to affect immersion and immersion in reliability. The results showed that satisfaction, reliability, and immersion in the chatbot services were important factors in the chatbot reuse intention. Through the satisfaction and reliability gained through the service, the users wanted to reuse the chatbot services, especially the chatbot services that gained reliability, which will have a greater impact on reuse intention. We can use these results as marketing information to attract loyal customers by identifying the reuse intention of the chatbot service users.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.47-59
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• 1995

The main purpose of this study is identifying the factors which affect the mode choice behavior of work trips. Disaggregate behavioral approach is used for the analysis . The data were collected using the questionnaire survey method in Taegu. Two models were developed in this study which are multinomial logit model(MODEL-1) for auto, taxi and bus and multinomial logit model (MODEL-2) for auto, taxi, bus and subway. The stated preference (SP) data were used for the analysis of the subway mode choice behavior. MODEL-1 provide reasonable results for the future application. A multinomial model (MODEL-2) developed using the stated preference(SP) data was tested for the use of future transportation mode. It is four that the those models provides reasonable results in terms of behavioral and statistical consideration.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.548-552
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• 1994

The robust compensation controller, which has been proposed by one of the authors and is based on the fundamental principle of making the plant follow the reference model, consists of the reference model and the robust compensator. The reference model is constructed by using the nominal model of the plant and determines the input-output properties of the resultant system. The robust compensator is obtained as a solution of the mixed sensitivity problem in H infinity control theory. Therefore the resultant system is of low sensitivity and robust stability. In the case where uncertainty does not occur in the plant, the plant follows perfectly the reference model. Therefore, in the case where uncertainty occurs in the plant, we propose the system configuration which improves the following accuracy without replacing the 개bust compensator but by identifying, the plant and reconstructing the reference model.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.8
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• pp.462-470
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• 2003

This paper presents an algorithm of identifying parametric uncertainty by way of an interval model. For a given set of frequency response data from an uncertain linear SISO system of which the upper and the lower bounds of both magnitude and phase responses are represented, the proposed algorithm consists of two main parts: first, the nominal model is identified by using Least Square Estimation (LSE), and then an interval model is constructed by expanding the extremal properties of interval systems, so that tightly enclose the given envelopes within those of interval model. Two numerical examples are given to demonstrate and verify the developed algorithm. The identified interval model can be used for evaluating the worst case performance and stability margins against parametric uncertainty by using some extremal properties on interval systems.

• Korean System Dynamics Review
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• v.6 no.2
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• pp.5-23
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• 2005

This paper investigates a dynamic mechanism underlying the process of knowledge creation and evolution with a focus on the SECI model(standing for Socialization, Externalization, Combination, Internalization) as proposed by Nonaka and Takeuchi(1991) and broadly accepted especially among the practitioners in knowledge management field. The SECI model provides with intuitive logic and clear delineation of knowledge types between the tacit and the explicit, and embodies an interaction dynamic. However explanations of the propelling forces for the knowledge transfer over the four quadrants of the model is yet to be made. And the transmission mechanisms are not prescribed though the model mentions knowledge is created and evolved in a spiral process. This paper, therefore attempts first to extend and elaborate it into a dynamic SECI model by identifying those propelling factors and their relationships(linkages) based on the systems thinking.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1806-1811
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• 2006

A surgical patient is identified by an operating surgeon or a nurse manually. There always exists a chance that he/she misses the necessary identification process. It can bring about serious and critical demage to the surgical patient. Thus, it is necessary to prevent this kind of mistake automatically. This study proposes a business model identifying surgical patients using RFID system. The paper presents a design of the system identifying patients at the entrance of a operating room. It gives also some user interfaces of the system.