• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.237-242
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• 2002

The sales activity of most of small manufacturing companies is based on orders of buyers. The process of promotion, receipt and selection of orders of the manufacturers is closely coupled with the load status of the production lines. The decision on whether to accept an order or not, or the selection of optimal order set among excessive orders is entirely dependent on the schedule of production lines. However, in the real world, since the production scheduling activity is mainly performed by human experts, most of small manufacturers are suffer from being unable to meet due dates, lack of rapid decision on the acceptance of new order. To cope with this problem, this paper deals with the development of an agent for selecting an optimal order set automatically. The main engine of selection agent is based on the typical job-shop scheduling model since our target domain is the injection molding company. To solve the problem, we have formulated it as IP (Integer Program) model, and it has been successfully implemented by ILOG and selection agent. And we have suggested an architecture of an agent for tackling web based order selection problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.5
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• pp.1-8
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• 2002

The sales activity of most of small manufacturing companies is based on orders of buyers. The process of promotion, receipt and selection of orders of the manufacturers is closely coupled with the load status of the production lines. The decision on whether to accept an order or not, or the selection of optimal order set among excessive orders is entirely dependent on the schedule of production lines. However, in the real world, since the production scheduling activity is mainly performed by human experts, most of small manufacturers are suffer from being unable to meet due dates, lack of rapid decision on the acceptance of new order. To cope with this problem, this paper deals with the development of an agent for selecting an optimal order set automatically. The main engine of selection agent is based on the typical job-shop scheduling model since our target domain is the injection molding company. To solve the problem, we have formulated it as IP (Integer Program) model, and it has been successfully implemented by ILOG and selection agent. And we have suggested an architecture of an agent for tackling web based order selection problems.

• The Journal of Information Systems
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• v.17 no.2
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• pp.137-154
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• 2008

Customer Relationship Management (CRM) is indispensable for companies in recent business environment, in which the customers are recognized as more valuable asset to increase the earning power of enterprise. For gaining competitive advantage, most companies want to maintain existing customer relationships and generate more profits with customers through long-term relationships. In this study, we developed the models which are designed to select CRM systems in financial institution, which is one of competitive sectors and undergoes rapid changes due to M&A(Merger and acquisition), innovation and reengineering in Korea. The selection model of CRM systems for financial institution was developed utilizing the Analytic Hierarchy Process (AHP) and the expert's knowledge were built up of three groups; researcher group, developer group, and user group. We found that there are significant deferences for the weights of criteria in our selection model according to the kind of experts. This study provides helpful guidance on how to assign appropriate weights to each criteria in selection models when financial institution introduce the CRM systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.7
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• pp.1252-1273
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• 2011

In Web Service Composition (WSC) area, services selection aims at selecting an appropriate candidate from a set of functionally-equivalent services to execute the function of each task in an abstract WSC according to their different QoS values. In despite of many related works, few of previous studies consider transactional constraints in QoS-aware WSC, which guarantee reliable execution of Composite Web Service (CWS) that is composed by a number of unpredictable web services. In this paper, we propose a novel global selection-optimal approach in WSC by considering both transactional constraints and end-to-end QoS constraints. With this approach, we firstly identify building rules and the reduction method to build layer-based Directed Acyclic Graph (DAG) model which can model transactional relationships among candidate services. As such, the problem of solving global optimal QoS utility with transactional constraints in WSC can be regarded as a problem of solving single-source shortest path in DAG. After that, we present Graph-building algorithms and an optimal selection algorithm to explain the specific execution procedures. Finally, comprehensive experiments are conducted based on a real-world web service QoS dataset. The experimental results show that our approach has better performance over other competing selection approaches on success ratio and efficiency.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.439-449
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• 2020

Meta-analysis provides a way of integrating several independent studies of interest. Since small studies with statistically significant results are more likely to be published, publication bias, which is a special case of selection bias, often occurs in meta analysis. Conditional likelihood and weighted estimating equation have been proposed to deal with publication bias, but they require to specify a correct selection probability model. In contrast, the pairwise pseudolikelihood approach can correct publication bias without fully specifying the correct selection probability model, but its performance in meta-analysis was not investigated. In this paper, we perform a numerical study about whether the pairwise pseudolikelihood approach is effective for solving publication bias arising from typical meta-analysis settings.

• Journal of Microbiology and Biotechnology
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• v.15 no.5
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• pp.1022-1027
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• 2005

Based on plasmid display technology by the complexes of fusion protein and the encoding plasmid DNA, an in vitro selection method for high affinity DNA-binding protein was developed and experimentally demonstrated. The GAL4 DNA-binding domain (GAL4 DBD) was selected as a model DNA-binding protein, and enhanced green fluorescent protein (EGFP) was used as an expression reporter for the selection of target proteins. Error prone PCR was conducted to construct a mutant library of the model. Based on the affinity decrease with increased salt concentration, mutants of GAL4 DBD having high affinity were selected from the mutant protein library of protein-encoding plasmid complex by this method. Two mutants of (Lys33Glu, Arg123Lys, Ile127Lys) and (Ser47Pro, Ser85Pro) having high affinity were obtained from the first generation mutants. This method can be used for rapid in vitro selection of high affinity DNA-binding proteins, and has high potential for the screening of high affinity DNA-binding proteins in a sequence-specific manner.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.411-422
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• 2014

This study analyzed how average GPA (grade point average) changes as the number of completed semesters increases based on the estimates of intercept, slope, and quadratic term. The students included in this study are those who was admitted in 2011 and took 6 consecutive semesters. More precisely, it was analyzed if intercept, slope and quadratic term of average GPA were different between gender and selection method. The results showed that the intercept was different between selection method, the slope was different between gender, but the quadratic term was different between neither selection method nor gender.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.64
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• pp.187-210
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• 2014

As port functions change to act as an economic catalyst and take on a central position in industries engaged in international trade, port hinterland has become a significant component in international shipping. The success of port hinterland as a strategic base of logistic activities critically depends on location selection factor for international distribution center that links elements of global supply chain management. By examining multi-measurement items empirically, this paper analyzed location selection factor for international logistics distribution center in port hinterland, and evaluated Busan new port hinterland from the user's perspective. Employing exploratory factor analysis, the results revealed that the model structured around five factors incorporating geo-location and accessibility, availability, political supports, cost factors, and quality of business environment is valid and reliable in the context of the location selection factors for logistics distribution center in the context of port hinterland operations. The evaluation of Busan new port hinterland provides useful insights for strategic improvement to accommodate the users' expectation. Further, the model offers both a descriptive and diagnostic strategic management tool for port hinterland development and operations, to guide future improvement.

• Economic Analysis
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• v.26 no.1
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• pp.84-132
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• 2020

A central bank infers market expectations of future yields based on yield curves. The central bank needs to precisely understand the changes in market expectations of future yields in order to have a more effective monetary policy. This need explains why a range of models have attempted to produce yield curves and market expectations that are as accurate as possible. Alongside the development of bond markets, the interconnectedness between them and macroeconomic factors has deepened, and this has rendered understanding of what macroeconomic variables affect yield curves even more important. However, the existence of various theories about determinants of yields inevitably means that previous studies have applied different macroeconomics variables when estimating yield curves. This indicates model uncertainties and naturally poses a question: Which model better estimates yield curves? Put differently, which variables should be applied to better estimate yield curves? This study employs the Dynamic Nelson-Siegel Model and takes the Bayesian approach to variable selection in order to ensure precision in estimating yield curves and market expectations of future yields. Bayesian variable selection may be an effective estimation method because it is expected to alleviate problems arising from a priori selection of the key variables comprising a model, and because it is a comprehensive approach that efficiently reflects model uncertainties in estimations. A comparison of Bayesian variable selection with the models of previous studies finds that the question of which macroeconomic variables are applied to a model has considerable impact on market expectations of future yields. This shows that model uncertainties exert great influence on the resultant estimates, and that it is reasonable to reflect model uncertainties in the estimation. Those implications are underscored by the superior forecasting performance of Bayesian variable selection models over those models used in previous studies. Therefore, the use of a Bayesian variable selection model is advisable in estimating yield curves and market expectations of yield curves with greater exactitude in consideration of the impact of model uncertainties on the estimation.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.1
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• pp.118-125
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• 2003

As consumer's desire becomes various, agility of mold manufacturing is the most important factor for competitive mold manufacturer. Decision making process is required to produce optimal result of CAM systems in using commercial CAM system to generate tool path. The paper proposes a methodology fur computer-assisted tool selection procedures for various cutting type of rough, semi-rough and finish cuts. The procedure provides assistance for machining tool selection by analyzing sliced CAD model section of die cavity and core. Information about machining time for the generated NC-code is used to aid the tool selection. The module is developed with commercial CAM API. This module will be used fur the optimization of tool selection and planning process.