• Journal of the Korean Statistical Society
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• 제21권2호
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• pp.167-177
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• 1992

In this paper, we investigate the limiting distribution of $M_n = max (X_1, X-2, \cdots, X_n)$ in the infinite moving average process ${X_t = \sum c_i Z_{t-i}}$ generated from i.i.d. negative binomial variables $Z_i$'s. While no limit result is possible, nonetheless asymptotic bounds are derived. We also present the tail behavior of $X_t$, i.e., weighted sum of i.i.d. random variables. This continues a study made by Rootzen (1986) for discrete innovation sequences.

• Communications for Statistical Applications and Methods
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• 제11권2호
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• pp.255-264
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• 2004

Due to a computerized data processing, there are many cases when we encounter a huge data set. On the other hand, advances in computing technologies make it possible to deal with a huge data set. One important area is the data mining. In this paper we consider data mining when the dependent variable is binary. The proposed method is to use the poly-class model when the independent variables consists of continuous and discrete variables. An example is provided.

• 제어로봇시스템학회논문지
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• 제6권6호
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• pp.433-440
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• 2000

To flexibly evaluate performance and reliability of a real-time system which is intrinsically characterized by stringent timing constraints to generate correct responses, we propose fuzzyrandom variables and build a discrete event model embedded with fuzzy-random variables. Also, we adapt fuzzy-variables to a path-space approach, which derives the upper and lower bounds of reliability by using a semi-Markov model that explicitly contains the deadline information. Consequently, we propose certain formulas of state automata properly transformed by fuzzy-random variables, and present numerical examples applying the formulas to RTP(Rapid Thermal Process) to show that a complex system can be properly evaluated based on this model by computer simulation.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권7호
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• pp.363-369
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• 2000

To flexibly evaluate performance and reliability of an electric power system in the aspect of the real-time system which is intrinsically characterized by stringent timing constraints fails catastrophically if its control input is not updated by its digital controller computer within a certain time limit called the hard deadline, we propose fuzzy-random variables and build a discrete event model embedded with fuzzy-random variables. Also, we adapt fuzzy-variables to a path-space approach, which derives the upper and lower bounds of reliability by using a semi-Markov model that explicitly contains the deadline information. Consequently, we propose certain formulas of state automata properly transformed by fuzzy-random variables, and present numerical examples applying the formulas as well.

• 한국시뮬레이션학회논문지
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• 제7권2호
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• pp.137-152
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• 1998

One of the components that constitute the simulation models is the state variables whose values are determined by the time related simulation process. Embedding rule-based expert systems into the simulation models should provide a systematic way of handling these time-dependent variables without distracting the essential problem solving capabilities of the expert systems which are well suited for expressing the decision making function of complex cases. The expert system, however, is inefficient in dealing with the time elapsing characteristics of target system compare to the simulation models. To solve the problem, this paper provides an interruptible inference engine whose inferencing process can be interrupted when the variables' value, which are used as the parameters of the rules, are not yet determined due to the time dependent nature of the state variables. The process is resumed when the variables are ready. The elapse of time is calculated by time-advance function of the simulation model to which the expert system has been embedded. The example modeling shown exploits the embedded interruptible inferencing capability for the controlling and monitoring of metal grating process.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.1053-1059
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• 2009

Construction system modeling can enhance work performance by following the behaviors of a system. System behaviors may originate from physical aspects of a system, namely operation level variables, or from non-physical aspects of a system known as context level variables. However, construction system modelers usually focus on only one type of system variable (i.e., operation level or context level) which can lead to less accurate results. Hybrid modeling with System Dynamics (SD) and Discrete Event Simulation (DES) is one of the approaches that has been utilized to address this issue. In this research, an SD-DES hybrid model of a steel fabrication shop is developed, and the benefits of capturing context level variables together with operation level variables in the model are discussed.

• 품질경영학회지
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• 제32권3호
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• pp.198-215
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• 2004

Technology competitiveness evaluates environmental and engineered technology and process at both the scientific and market levels. There are increasing concerns to measure the effects of the technology variables on the potential market feasibility levels. However, there are very little empirical analysis studies on that issue. This study investigates the impacts of technology variables on the levels of market feasibility based on 230 data obtained from Korea Technology Transfer Center. As various statistical analysis, the canonical discriminant model, logit discriminant model and classification model were used and their results were compared. This study results showed that major technology variables had very significant relations to discriminate high and low categories of market feasibility. Finally, this study will help building management strategies to level up the potential market performance and also help financial Institutions to decide funds needed for small-sized technology firms.

• Management Science and Financial Engineering
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• 제7권2호
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• pp.1-11
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• 2001

Gouveia and Pires (European Journal of Operations Research 112(1999) 134-146) have proposed four extended formulations having precedence variables as extra variables and characterized the projections of three of the four formulations into the natural variable space. In Gouveia and Pires (Discrete Applied Mathematics 112 (2001)), they also have introduced some other extended formulations with the same extra variables and conjectured that the projection of one of the proposed formulations is equivalent to the one proposed by Dantzig, Fulkerson, and Johnson (Operations Research 2(1954) 393-410). In this paper, we provide a unifying framework based on which we give alternative proofs on the projections of three extended formulations and new proofs on those of two formulations appeared in Gouveia and Pires(1999, 2001).

• 대한기계학회논문집
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• 제18권2호
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• pp.278-291
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• 1994

A computer-aided robust design (CARD) technique is developed to search for the design variables, optimal as well as robust in the sense of Taguchi method. The CARD technique can effectively handle inequality problems by employing the variable penalty method, and dynamic problems with many design variables and/or with mixed discrete and continuous variables. It is also capable of providing contributions of each design variables to the object funtion and information for future designs. As the illustrative examples, two dynamic systems, engine mounting system and in-line feeder, are treated.

• International Journal of Naval Architecture and Ocean Engineering
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• 제11권2호
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• pp.809-818
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• 2019

The current trend in shipyard industry is to reduce the weight of ships to support the reduction of CO₂ emissions. In this study, the stiffened plate was optimized that is used for building most of the ship-structure. Further, this study proposed the hybrid Genetic Algorithm (GA) technique, which combines a genetic algorithm and subsequent optimization methods. The design variables included the number and type of stiffeners, stiffener spacing, and plate thickness. The number and type of stiffeners are discrete design variables that were optimized using the genetic algorithm. The stiffener spacing and plate thickness are continuous design variables that were determined by subsequent optimization. The plate deformation was classified into global and local displacement, resulting in accurate estimations of the maximum displacement. The optimization result showed that the proposed hybrid GA is effective for obtaining optimal solutions, for all the design variables.