• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.2A
• /
• pp.139-148
• /
• 2011

This paper presents the minimum-cost network selection scheme which determines the transmission instance in the multi-band maritime communication system, so that the shipment-related real-time information can be transmitted within the maximum allowed period. The transmission instances and the corresponding network selection process are modeled by a Markov Decision Process (MDP), for the channel model in the 2-state Markov chain, which can be solved by stochastic dynamic programming. It derives the minimum-cost network selection rule, which can reduce the network cost significantly as compared with the straight-forward scheme with a periodic transmission.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2007.11a
• /
• pp.482-487
• /
• 2007

As the importance of logistics is increasing, Enterprises design the supply chain(SC) network to minimize the total costs considering inventory holding cost, transportation cost and apply the efficient strategies of supply chain based on SC network Calculating the logistics costs without reflecting the logistics components like the packaging cost, transportation related cost, storage cost, loading & unloading cost, and distribution costs, the companies should have many limitation to calculate the logistics cost of real enterprise and install the SC network reducing them. Therefore, this research is aimed at establishing SC strategies which can be an efficient alternative for a decision making on supply chain, based on existing reference and current logistics networks of 'L' company in Korea and analyzing interaction effects between strategies and influence on logistics cost by these strategies. As the method of analysis, we analyze the interaction effects between strategies as well as install the optimal SC network reflecting concrete logistics components from the viewpoint of total logistics costs. we expect that analysis method of this paper would be applied various industries and used the efficient tools for the decision mating by planing and execution of the logistics budget from enterprises.

• Korean Management Science Review
• /
• v.25 no.2
• /
• pp.89-109
• /
• 2008

As the importance of logistics is increasing, Enterprises try to design the supply chain(SC) network to minimize the total costs considering inventory holding cost, transportation cost and apply the efficient strategies of supply chain based on SC network. Despite of this efforts, Calculating the logistics costs without reflecting the real components of logistics like the packaging cost, transportation related cost, storage cost, loading & unloading cost, and distribution costs, the companies has many limitation to calculate the logistics cost of real enterprise. For overcoming such problem, this paper is aimed at establishing SC strategies which can be an efficient alternative for a decision making on supply chain, based on existing reference and current logistics networks of 'L' company in Korea. Also, we analyze the interaction effects between strategies as well as install the optimal SC network reflecting concrete logistics components from the viewpoint of total logistics costs using the simulation and statistic methods. we expect that analysis results of this paper would be applied various industries and be utilized to the efficient tools for the decision making by planing and execution of the logistics budget from enterprises.

• The Journal of Korean Physical Therapy
• /
• v.25 no.2
• /
• pp.43-48
• /
• 2013

Purpose: The aim of this study was to demonstrate that non-participation of physical therapists on the political decision-making committee results in invasion of their interests. Methods: To demonstrate the effects, we analyzed the change of medical insurance score decided by the Health Insurance Policy Deliberation Committee between 2001 and 2012 years, focusing on medical examination as the interest of the participation group and physical therapy cost as interest of the non-participation group. Results: Total medical insurance cost increased by 23.72%, on average. Medical examination cost increased by 23.90% and 37.66% in medical examination for new and established patients, respectively. However, physical therapy cost was reduced by 5.01%. The medical examination cost for physical therapy without medical checkup increased by 2.62%. Conclusion: This study shows that the physical therapy cost, related on the interest of the non-participative group in the Health Insurance Policy Deliberation Committee, rather decreased while the total medical insurance cost increased.These findings demonstrate the invasion of the non-participative group on the Health Insurance Policy Deliberation Committee. Thus, aggressive participation in political decision-making committee is necessary in order to protect and increase rights and interests of Korean physical therapists.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2023.05a
• /
• pp.389-390
• /
• 2023

To improve the cost performance of construction sites, various systems and standards are constantly being developed and implemented. Although legal requirements for these system and standard improvements have been increasing, the cost efficiency performance of construction sites remains stagnant. We have digitized documents generated through construction supervision work at 39 building construction sites and proposed a model that can support decision-making in cost efficiency evaluation. This model selects key keywords that are considered to be highly related to cost efficiency by identifying the patterns and relationships of keywords through associated rule analysis and social network analysis using keywords derived from documents. In addition, it is expected to be used as a decision-making aid to determine the cost efficiency of a specific building construction site by establishing a logistic regression model using core keywords. As a systematic database of construction supervision documents and an integrated system of massive data generated by digital technology are established in the future, the accuracy and reliability of the cost efficiency evaluation model are expected to be reinforced.

• Management & Information Systems Review
• /
• v.31 no.4
• /
• pp.309-337
• /
• 2012

This study aims to suggest theoretical models and background for the analysis of antecedent factors such as customer satisfaction and repurchasing decision by use of Technology-Based Self-Service (TBSS) delivery service. Specifically, the study have focused on the analysis that after the values of customer satisfaction and repurchasing decision were transformed into the values of Cost-Benefit analysis and then compared with the values of result benefits, process benefits, financial costs and non-financial costs. After analysis, it was found that ordering and delivery service by use of TBSS has a positive influence on customer satisfaction in terms of result benefits, process benefits, time savings and financial cost savings. In addition, it was confirmed that sub-category of customer satisfaction such as overall satisfaction, satisfaction for expectations, satisfaction for ideals has also a positive impact on repurchasing decision. It is expected that the results of this study will help analyze the customer satisfaction and repurchasing decision and provide a practical help for a business.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.2
• /
• pp.129-136
• /
• 2017

Among the information technology and automation that have rapidly developed in the manufacturing industries recently, tens of thousands of quality variables are estimated and categorized in database every day. The former existing statistical methods, or variable selection and interpretation by experts, place limits on proper judgment. Accordingly, various data mining methods, including decision tree analysis, have been developed in recent years. Cart and C5.0 are representative algorithms for decision tree analysis, but these algorithms have limits in defining the tolerance of continuous explanatory variables. Also, target variables are restricted by the information that indicates only the quality of the products like the rate of defective products. Therefore it is essential to develop an algorithm that improves upon Cart and C5.0 and allows access to new quality information such as loss cost. In this study, a new algorithm was developed not only to find the major variables which minimize the target variable, loss cost, but also to overcome the limits of Cart and C5.0. The new algorithm is one that defines tolerance of variables systematically by adopting 3 categories of the continuous explanatory variables. The characteristics of larger-the-better was presumed in the environment of programming R to compare the performance among the new algorithm and existing ones, and 10 simulations were performed with 1,000 data sets for each variable. The performance of the new algorithm was verified through a mean test of loss cost. As a result of the verification show, the new algorithm found that the tolerance of continuous explanatory variables lowered loss cost more than existing ones in the larger is better characteristics. In a conclusion, the new algorithm could be used to find the tolerance of continuous explanatory variables to minimize the loss in the process taking into account the loss cost of the products.

• Journal of the Korean Institute of Educational Facilities
• /
• v.25 no.6
• /
• pp.35-44
• /
• 2018

The purpose of this study is to predict more accurate construction costs and to support efficient decision making in the planning and design stages of smart education facilities. The higher the error in the projected cost, the more risk a project manager takes. If the manager can predict a more accurate construction cost in the early stages of a project, he/she can secure a decision period and support a more rational decision. During the planning and design stages, there is a limited amount of variables that can be selected for the estimating model. Moreover, since the number of completed smart schools is limited, there is little data. In this study, various artificial intelligence models were used to accurately predict the construction cost in the planning and design phase with limited variables and lack of performance data. A theoretical study on an artificial neural network and deep learning was carried out. As the artificial neural network has frequent problems of overfitting, it is found that there is a problem in practical application. In order to overcome the problem, this study suggests that the improved models of Deep Neural Network and Deep Belief Network are more effective in making accurate predictions. Deep Neural Network (DNN) and Deep Belief Network (DBN) models were constructed for the prediction of construction cost. Average Error Rate and Root Mean Square Error (RMSE) were calculated to compare the error and accuracy of those models. This study proposes a cost prediction model that can be used practically in the planning and design stages.

• IE interfaces
• /
• v.13 no.2
• /
• pp.211-216
• /
• 2000

A methodology that determines the optimal shutdown time of a nuclear power plant is suggested. The shutdown time is decided considering the trade off between the cost of accident and the loss of profit due to the early shutdown. We adopt the bayesian approach in manipulating the model parameter that predicts the accidents. We build decision tree models and apply dynamic programming approach to decide whether to shutdown immediately or operate one more period. The branch parameters in decision trees are updated by bayesian approach. We apply real data to this model and provide the cost of accidents that guarantees the immediate shutdown.

• Journal of KIISE:Databases
• /
• v.34 no.1
• /
• pp.70-83
• /
• 2007

Most of works for skyline queries have focused on static data objects. With the advance in mobile applications, however, the need of continuous skyline queries for moving objects has been increasing. To process continuous skyline queries, the 4-phased decision method of skyline regions has been proposed recently. However, it is not feasible for a large number of data because of the high cost of computing skyline regions. To solve this problem, this paper first provides a theoretical analysis of the 4-phased decision method. Then we propose a progressive decision method of skyline regions for the 4-phased decision method, which consists of a distance-based pruning and an extent shrinking of region decision lines. The proposed method can efficiently reduce the cost of the decision of skyline region in the 4-phased decision method. This paper also presents the experimental results to show the effectiveness of the proposed method.