• Journal of the Korea Society for Simulation
• /
• v.11 no.2
• /
• pp.55-66
• /
• 2002

VHDL has been. widely used in modeling and simulation of hardware designs. However, complex relationship between components of the designs makes the VHDL modeling problem very difficult. Furthermore, after the initial creation of VHDL models, they evolve into many versions over their lifetime. To cope with such difficulties, this paper proposes a new methodology for the management of VHDL models supporting versions. Its conceptual bases are system entity structure and relational database. Within the methodology, a family of hierarchical structures of a design is organized in the form of VHDL model structure. It is, in turn, represented in the form of relational tables. Once the model structure is built in such a way, a specific simulation model which meets design objective is pruned from the model structure. The details of VHDL codes are systematically synthesized by combining it with the primitive models in a model base. These algorithms are also defined in terms of relational algebraic operations.

• Journal of Korean Society for Quality Management
• /
• v.23 no.1
• /
• pp.95-105
• /
• 1995

The error structure of nonlinearized technological growth models, such as, the Pearl curve, the Gompertz curve and the Wei bull growth curve, has zero mean and a constant variance over time. Transformed models, however, like the linearized Fisher-Pry model. the linearized Gompertz growth curve, and the linearized Weibull growth curve have increasing variance from t = 0 to the inflection point.

• Korean Management Science Review
• /
• v.11 no.3
• /
• pp.153-167
• /
• 1994

Credibility theory has provided with a useful tool the assignment of weighting factor that reflects the credibility of the observed individual and collective experience to secure fair experience rate-,making. We review credibility models which can effectively estimate risk premiums using credibility theory, and suggest an empirical Bayed model based on the collective statistics to estimate the structural parameters. To illustrate the use of evolutionary models, the models are applied to the actual data, such as loss ratio, claim frequencies and severity, in the Korean automobile insurance. Also the possibilities of generalizations and applications of empirical models are discussed.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.10 no.2
• /
• pp.75-82
• /
• 1985

Reorganization is essential part of data base maintenanc work and the reasonable reorganization points can be determined from the trade-off between reorganization cost and performance degradation. There has been many reorganization models so far, but none of these models have assumed nonlinear search cost function. This paper presents the existensions of two existing linear reorganization models for the case where the search cost function is quadratic. The higher performance of these extended models was shown in quadratic search cost function case.

• The KIPS Transactions:PartB
• /
• v.8B no.5
• /
• pp.441-446
• /
• 2001

On global interconnectivity, the activation of real-time and worldwide contents will permeate and impact all aspects of day-to-day life well throughout this century. In managing contents and models, we too will see the impact of this rapidly changing environment. The real time availability of contents pertaining to a companys supply chain through means of the Internet and mobile networks(e.g., the IMT-2000) will necessitate a change in decision-making processes for effective management of contents and models. To increase the availability of many contents and models, a management system should have adaptive function in proving adequate content and model for companies. In the respect of management of contents and models, this paper discusses a production mechanism of meta-knowledge for effectively managing contents and models. Through two experimental analyses with the production mechanism, it is proven that the system enabling adaptive contents and models provision goes beyond existing ones in view of efficiency of management of contents and models in the wire and wireless networks.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.20 no.1
• /
• pp.85-99
• /
• 1995

Increasingly, risk analysis is becoming important ingredients in achieving the successful implementation and application in the area of the project management. The project management system is designed to manage or control the project resources on a given activity within time, cost and performance so called TPPM (Total Productive Project Management). In this research, a risk analysis model misproposed to identify potential problem areas, quantify the risks, and generated the chice of the action that can be taken to reduce the risk. In addition two analysis models are proposed : 1) risk factor model and 2) network simulation model using VERT (Venture Evaluation and Review Technique ). The objective of the remodels is to estimate the schedule, cost performance risks. These proposed quantitative models for project risk analysis are proving its value for the project managers who need to assess the risk of changes in cost, schedule, or performance. The proposed models will be used in the area of project selection, evaluation and the allocation of project resources.

• Management Science and Financial Engineering
• /
• v.5 no.1
• /
• pp.27-49
• /
• 1999

WebME is an Web-based integrated modeling environment that implements a multi-facetted modeling approach to mathematical model representation and management. Key features of WebME include the following: (i) sharing of modeling knowledge on the Web, (ii) a user-friendly interface for creating, maintaining, and solving models, (iii) independent management of mathematical models from conceptual models, (iv) object-oriented conceptual blackboard concept, (v) multi-facetted mathematical modeling modeling, and (vi) declarative representation of mathematical knowledge. This paper presents details of design and implementation issues that were encountered in the development of WebME.

• Asia-Pacific Journal of Business
• /
• v.13 no.2
• /
• pp.107-122
• /
• 2022

Purpose - This study aims to develop machine learning models to predict administrative issue designation in KOSDAQ Market using financial data. Design/methodology/approach - Employing four classification techniques including logistic regression, support vector machine, random forest, and gradient boosting to a matched sample of five hundred and thirty-six firms over an eight-year period, the authors develop prediction models and explore the practicality of the models. Findings - The resulting four binary selection models reveal overall satisfactory classification performance in terms of various measures including AUC (area under the receiver operating characteristic curve), accuracy, F1-score, and top quartile lift, while the ensemble models (random forest and gradienct boosting) outperform the others in terms of most measures. Research implications or Originality - Although the assessment of administrative issue potential of firms is critical information to investors and financial institutions, detailed empirical investigation has lagged behind. The current research fills this gap in the literature by proposing parsimonious prediction models based on a few financial variables and validating the applicability of the models.

• Korean Management Science Review
• /
• v.28 no.2
• /
• pp.1-16
• /
• 2011

In this study we suggested two optimization models to answer a question from an investor standpoint : how many convertible bonds should one convert, and how many keep? One model minimizes certain risk to the minimum required expected return, the other maximizes the expected return subject to the maximum acceptable risk. In comparison with Markowitz portfolio models, which use the variance of return, our models used Conditional Value-at-Risk(CVaR) for risk measurement. As a coherent measurement, CVaR overcomes the shortcomings of Value-at-Risk(VaR). But there are still difficulties in solving CVaR including optimization models. For this reason, we adopted Rockafellar and Uryasev's[18, 19] approach. Then we could approximate the models as linear programming problems with scenarios. We also suggested to extend the models with credit risk, and applied examples of our models to Hynix 207CB, a convertible bond issued by the global semiconductor company Hynix.

• Korean Management Science Review
• /
• v.30 no.3
• /
• pp.55-70
• /
• 2013

In this study we suggested two optimization models to determine conversion weight of convertible bonds. The problem of this study is same as that of Park and Shim [1]. But this study used Value-at-Risk (VaR) for risk measurement instead of CVaR, Conditional-Value-at-Risk. In comparison with conventional Markowitz portfolio models, which use the variance of return, our models used VaR. In 1996, Basel Committee on Banking Supervision recommended VaR for portfolio risk measurement. But there are difficulties in solving optimization models including VaR. Benati and Rizzi [5] proved NP-hardness of general portfolio optimization problems including VaR. We adopted their approach. But we developed efficient algorithms with time complexity O(nlogn) or less for our models. We applied examples of our models to the convertible bond issued by a semiconductor company Hynix.