• Korean Journal of Construction Engineering and Management
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• v.13 no.1
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• pp.129-139
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• 2012

It is one of the most important decision making problems to select the adequate foundation practice for the downtown construction project. However the foundation practice has not been selected systematically yet by considering various construction field conditions in many projects. The foundation practice is often informally selected on the basis of only past experiences and skilled engineer's opinion. For making the selection process systematically, in this study, we propose a decision support system (DSS) for selecting foundation practices based on the Analytic Hierarchy Process (AHP) and the Preference Function (PF). In the proposed DSS, the AHP is used for making the selection process more reasonable and the PF is used for considering the decision maker's preference. To validate the proposed DSS, we apply the proposed DSS to the pre-performed construction projects. The application results show that the proposed DSS gives the same foundation practices with the implemented foundation practices that the skilled foundation engineers select after carefully analyzing construction field conditions. The proposed DSS can be used as a useful tool for making decisions to select the foundation practice in the construction fields.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.1
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• pp.11-16
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• 2023

Accurate hospital case modeling and prediction are crucial for efficient healthcare. In this study, we demonstrate the implementation of regression analysis methods in machine learning systems utilizing mathematical statics and machine learning techniques. The developed machine learning model includes Bayesian linear, artificial neural network, decision tree, decision forest, and linear regression analysis models. Through the application of these algorithms, corresponding regression models were constructed and analyzed. The results suggest the potential of leveraging machine learning systems for medical research. The experiment aimed to create an Azure Machine Learning Studio tool for the speedy evaluation of multiple regression models. The tool faciliates the comparision of 5 types of regression models in a unified experiment and presents assessment results with performance metrics. Evaluation of regression machine learning models highlighted the advantages of boosted decision tree regression, and decision forest regression in hospital case prediction. These findings could lay the groundwork for the deliberate development of new directions in medical data processing and decision making. Furthermore, potential avenues for future research may include exploring methods such as clustering, classification, and anomaly detection in healthcare systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.569-574
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• 2002

As consumer's desire becomes various, agility of mold manufacturing is most important factor for competence of manufacturer. In common works to use commercial CAM system to generate tool path, some decision making process is required to produce optimal result of CAM systems, The paper proposes a methodology for computer-assisted tool selection procedures for various cutting type, such as rough, semi-rough and finish cuts. The system provides assist-tool-items for machining of design model part of injection meld die by analyzing sliced CAD model of die cavity and core. Also, the generating NC-code of the tool size is used to calculate machining time. The system is developed with commercial CAM using API. This module will be used for optimization of tool selection and planning process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.8
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• pp.5591-5599
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• 2015

For the effective energy management, this study proposed BIM(Building Information Modeling)-based Data Mining Model(B-DMM). To conduct this, BIM-based data mining researches were surveyed then the use-cases and scenarios related to the energy management were analyzed. By using this results, B-DMM for supporting the decision making related the energy management was proposed. The output will be used as a decision making tool for managing a building energy.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.2
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• pp.81-90
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• 2013

A study on the flow-structure characteristics of marine 3/2WAY pneumatic valve is essential for optimizing the performance of ship engines. It is important that the valve has desirable safety factor and reduced weight from safety and economic point of view. In this paper, flow-structure characteristics of pneumatic valve is obtained by being optimized based on the proper design criteria. The air with the pressure of 30 bar is the working fluid which is made to fill in the tack in short time. This time is defined as the filling time. On optimum design by considering the flow-structure characteristics, the approach is based on (1) the mathematical formulation of design decisions using the compromise decision-making method, and (2) the approximation technique of response surfaces. The methodology is demonstrated as the multi-objective optimization tool to improve the performance of marine 3/2WAY pneumatic valve.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.260-270
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• 2013

This paper proposes a strategic portfolio model for managing performance of online games. The portfolio matrix is composed of two dimensions: financial performance and non-financial performance. Financial performance is measured by the conventional measure, average revenue per user (ARPU). In terms of non-financial performance, five non-financial key performance indicators (KPIs) that have been widely used in the online game industry are utilized: RU (Register User), VU (Visiting User), TS (Time Spent), ACU (Average Current User), MCU (Maximum Current User). Data envelopment analysis (DEA) is then employed to produce a single performance measure aggregating the five KPIs. DEA is a linear programming model for measuring the relative efficiency of decision making unit (DMUs) with multiple inputs and outputs. This study employs DEA as a tool for multiple criteria decision making (MCDM), in particular, the pure output model without inputs. Combining the two types of performance produces the online game portfolio matrix with four quadrants: Dark Horse, Stop Loss, Jack Pot, Luxury Goods. A case study of 39 online games provided by company 'N' is provided. The proposed portfolio model is expected to be fruitfully used for strategic decision making of online game companies.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.448-452
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• 2006

Remodeling is deemedto be very important from the perspective of the recycling of resources, instead of scrapping the existing structure, and the creation of 'value added' which is equivalent to the 'value added' from the new construction. In addition, the selection of the appropriate construction method assures the saving of construction cost, the shortening of construction period, and the improvement of quality. Moreover, the selection of the construction method for the remodeling construction is far more important than the current new construction work, considering that the characteristicsof construction site and the structure have a great effect on the construction in case of the remodelingconstruction. Current selection of the construction method, however, does not reflect the construction information, but just adheres to the construction method which was commonly applied previously. Therefore, this study proposes the measure to embody the tool that assists the decision making in selecting the construction method.

• Korean Journal of Construction Engineering and Management
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• v.2 no.1 s.5
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• pp.88-97
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• 2001

The Internet, the main issue of a new millennium, is being researched vitally for the progress of the construction industry, and the construction industry is considered to be led into a high-value added state-of-arts technology industry through CALS. Even if many construction companies gradually widen the use of the Internet for various purposes such as an electronic bidding system and an e-commerce system, the companies are still demanded to use the Internet more broadly and practically. Hence, the need for a tool for fast decision making and an effective construction management has risen. The PRIMA system has been developed specifically focused on meeting with those recent changes of the construction industry. This system is composed of three parts. Those are Just In Time(JIT) management, integrated application of man power${\cdot}$safety${\cdot}$work management and decision making process based on real-time information in the Internet. The usefulness of the PRIMA system has already been proved in a super-scale construction project. As the Internet environment get improved the use of the tool will be spread out gradually for many construction projects, regardless their size and location.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.37-53
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• 2023

The AI based intelligent command and control system can automatically analyzes the properties of intricate battlefield information and tactical data. In addition, commanders can receive situation analysis results and battlefield awareness through the system to support decision-making. It is necessary to build a battlefield situation analysis dataset similar to the actual battlefield situation for learning AI in order to provide decision-making support to commanders. In this paper, we explain the next step of the dataset construction method of the existing previous research, 'A Virtual Battlefield Situation Dataset Generation for Battlefield Analysis based on Artificial Intelligence'. We proposed a method to build the dataset required for the final battlefield situation analysis results to support the commander's decision-making and recognize the future battlefield. We developed 'Dataset Generator SW', a software tool to build a learning dataset for battlefield situation analysis, and used the SW tool to perform data labeling. The constructed dataset was input into the Siamese Network model. Then, the output results were inferred to verify the dataset construction method using a post-processing ranking algorithm.

• 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.