• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.190-198
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• 1993

A multiple criteria model for the facility layout problem considers both of the quantitative, the cost of the work flow, and qualitative, the closeness rating score, aspect. Rosenblatt, Fortenberry & Cox and Urban have developed multiple criteria models that consider both of the quantitative and qualitative aspect. Fortenberry & Cox's multiplicity model penalizes facilities with undesirable closeness rating and high work flows more than those undesirable closeness rating and low work flow between them to contribute to the objective function regardless of the closeness rating between these facilities. In this paper, it is intended to develops a improved multiple-criteria facility layout model considering the function for maintaning the distance between facilities.

• Fashion & Textile Research Journal
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• v.17 no.5
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• pp.718-730
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• 2015

This study investigated the correlation between the level of consistency in fashion show models' appearance and design concept through a statistical and qualitative analysis of the S/S Paris Collection 2014. The following conclusions have been drawn in this study. First, the percentage of models of color was very low in regards to the physical appearance of models; in addition, there was a higher percentage of Caucasian models for collections with a high level of consistency in models' physical appearance. Collections with a high percentage of models of color indicate more casual design concepts and the promotion of diversity in racial background is considered more effective for street fashion. Second, collections with a high level of consistency in models' physical appearance tend to control various elements that constitute a physical appearance through more detailed planning and stage direction. Third, there is a tendency to reinforce design concepts by creating a consistency in the overall physical appearance of models. This affirms that their physical appearance is determined by brand (i.e. designer) and is used to maximize a design concept delivery. The results of this study suggests that the physical appearance of models must be determined in line with the design concept versus detailed planning that must consider audience perspectives as well as adjust the show's length and the interval between each model appearing on the stage.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.134-143
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• 2010

This paper proposes a framework for classifying metric-based software quality prediction models, especially case of software criticality, into four types. Models are classified along two vectors: input metric forms and the necessity of past project data. Each type has its own characteristics and its strength and weakness are compared with those of other types using newly defined criteria. Through this qualitative evaluation each organization can choose a proper model to suit its environment. My earlier studies of criticality prediction model implemented specific models in each type and evaluated their prediction performances. In this paper I analyze the experimental results and show that the characteristics of a model type is the another key of successful model selection.

• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.171-180
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• 2006

Change is inevitable and is a reality of construction projects. Most construction contracts include change clauses and allowing contractors an equitable adjustment to the contract price and duration caused by change. However, the actions of a contractor can cause a loss of productivity and furthermore can result in disruption of the whole project because of a cumulative or ripple effect. Because of its complicated nature, it becomes a complex issue to determine the cumulative impact (ripple effect) caused by single or multiple change orders. Furthermore, owners and contractors do not always agree on the adjusted contract price for the cumulative impact of the changes. A number of studies have attempted to quantify the impact of change orders on project costs and schedule. Many of these attempted to develop regression models to quantify the loss. However, regression analysis has shortcomings in dealing with many qualitative or noisy input data. This study develops ANN models to classify and quantify the labor productivity losses that are caused by the cumulative impact of change orders. The results show that ANN models give significantly improved performance compared to traditional statistical models.

• Journal of Construction Engineering and Project Management
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• v.5 no.1
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• pp.26-31
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• 2015

Success of the construction companies is based on the successful completion of projects within the agreed cost and time limits. Artificial neural networks (ANN) have recently attracted much attention because of their ability to solve the qualitative and quantitative problems faced in the construction industry. For the estimation of cost and duration different ANN models were developed. The database consists of data collected from completed projects. The same data is normalised and used as inputs and targets for developing ANN models. The models are trained, tested and validated using MATLAB R2013a Software. The results obtained are the ANN predicted outputs which are compared with the actual data, from which deviation is calculated. For this purpose, two successfully completed highway road projects are considered. The Nftool (Neural network fitting tool) and Nntool (Neural network/ Data Manager) approaches are used in this study. Using Nftool with trainlm as training function and Nntool with trainbr as the training function, both the Projects A and B have been carried out. Statistical analysis is carried out for the developed models. The application of neural networks when forming a preliminary estimate, would reduce the time and cost of data processing. It helps the contractor to take the decision much easier.

• Korea Journal of Hospital Management
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• v.25 no.1
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• pp.32-45
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• 2020

Purpose: The purpose of this research is to develop two medical tourism system models which explain medical tourism phenomenon with a systemic approach. Methodology/Approach: This research was conducted using a qualitative data analysis which mainly refer previous references in relation to medical tourism in the areas of tourism and medicine. Leiper's tourism system model was utilized as a conceptual framework. In-depth interviews with experts in the area were attempted in order to pretest the models. Findings: This research suggests a medical tourism system framework and a medical service provision framework. The first model presents medical tourism components and their relationships within a framework presented in a diagram. The second model shows the relationships among medical services required by medical tourists, the service providers, and service human resources along with movements of medical tourists. Practical Implications: The first model presents a spatial composition of medical tourism components and their relationships, whereas the second model shows the linkage among medical services, the service providers, and relevant service human resources along with time sequential steps of medical tourists. These two models are complementary and may be used as useful tools to observe medical tourism phenomenon with a systemic and holistic approach. These two models may enable stake holders avoid unnecessary confusions and conflicts that result in duplication of government policies and a waste of budget and human resources.

• Journal of Korea Trade
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• v.25 no.2
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• pp.1-21
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• 2021

Purpose - The purpose of this research is to develop two medical tourism system models which explain medical tourism phenomenon with a systemic approach. Design/methodology - This research was conducted by using a qualitative data analysis which mainly refers to previous references of medical tourism in the areas of tourism and medicine. Leiper's tourism system model was utilized as a conceptual framework. In-depth interviews with experts in the field were conducted in order to pretest the models. Findings - This research suggests a medical tourism system framework and a medical service provision framework. The first model presents medical tourism components and their relationships within a framework presented in a diagram. The second model shows the relationships among medical services required by medical tourists, the service providers, and service human resources along with movements of medical tourists. Originality/value - The first model presents a spatial composition of medical tourism components and their relationships, whereas the second model shows the linkage among medical services, the service providers, and relevant service human resources along with time sequential steps of medical tourists. These two models are complementary and may be used as useful tools to observe medical tourism phenomenon with a systemic and holistic approach. These two models may enable stake holders avoid unnecessary confusions and conflicts that result in duplication of government policies and a waste of budget and human resources.

• Journal of the Korean Society of Visualization
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• v.22 no.1
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• pp.49-60
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• 2024

The purpose of this study establishes the deep neural network (DNN) and Decoder models to predict the flow and thermal fields of three-dimensional wavy wings as a passive flow control. The wide ranges of the wavy geometric parameters of wave amplitude and wave number are considered for the various the angles of attack and the aspect ratios of a wing. The huge dataset for training and test of the deep learning models are generated using computational fluid dynamics (CFD). The DNN and Decoder models exhibit quantitatively accurate predictions for aerodynamic coefficients and Nusselt numbers, also qualitative pressure, limiting streamlines, and Nusselt number distributions on the surface. Particularly, Decoder model regenerates the important flow features of tiny vortices in the valleys, which makes a delay of the stall. Also, the spiral vortical formation is realized by the Decoder model, which enhances the lift.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.239-246
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• 2008

The supplier selection has a direct effect on the organization's efficiency, effectiveness and competitiveness, so the right supplier selection is the most important decision of a company. In order to select the best suppliers, both qualitative and quantitative factors should be considered. To decide which suppliers are the best and how much should be purchased from each selected supplier, many models which considered a single objective and multiple objectives have been proposed. But they have problems in considering qualitative factors which are very important in supplier selection. So in this article an integration model of an analytical hierarchy process and linear programming is proposed to consider both qualitative and quantitative factors in choosing the best suppliers and placing the optimum order quantities among them. This integrated model can be applied effectively and easily any organization and management circumstances.