• 한국경영과학회지
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• 제42권1호
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• pp.65-77
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• 2017

The purpose of this paper is to develop a model of level evaluation for data governance that can diagnose and verify level of insufficient part of operating data governance. We expanded the previous study related on attribute indices of data governance and developed a level model of evaluation and items. The model of level evaluation for data governance is the level of evaluation and has items of 400 components. We used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a level evaluation model for data governance at the early phase. This paper will be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

• 한국대기환경학회지
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• 제30권3호
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• pp.270-280
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• 2014

The objective of this research is to quantitatively valuate the economic value of analysis model related to climate change mitigation and adaptation. Due to the fact that the subject of this research, which is the Korean climate change mitigation and adaptation model, has not been actualized, a conjoint analysis applying stated preference data has utilized. As results, among the many attributes considered in this research, the value of the attribute related to reflecting Korea's current situation is analyzed to be largest in both greenhouse gas (GHG) mitigation model and climate change adaptation model. Additionally, if all the considered functional aspects are assumed to be feasible, the economic value of the Korean GHG mitigation model is assumed to be 60.3 billion Korean won(KRW) and the Korean climate change adaptation model is assumed to be 51 billion KRW.

• Journal of Construction Engineering and Project Management
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• 제1권2호
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• pp.1-10
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• 2011

Bridges are critical and valuable components in any road and rail transportation network. Therefore bridge remediation has always been a top priority for asset managers and engineers, but identifying the nature of true defect deterioration and associated remediation treatments remains a complex task. Nowadays Decision Support Systems (DSS) are widely used to assist decision makers across an extensive spectrum of unstructured decision environments. The main objective of this research is to develop a requirements-driven methodology for bridge monitoring and maintenance which has the ability to assess the bridge condition and find the best remediation treatments using Simple Multi Attribute Rating Technique (SMART); with the aim of maintaining a bridge within acceptable limits of safety, serviceability and sustainability.

• 한국공작기계학회논문집
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• 제17권1호
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• pp.77-85
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• 2008

The objective of the study is to construct a sensor fusion system for tool-condition monitoring (TCM) that will lead to a more efficient and economical drill usage. Drill-wear monitoring has an important attribute in the automatic machining processes as it can help preventing the damage of tools and workpieces, and optimizing the drill usage. In this study, we present the architectures of a multi-layer feed-forward neural network with Levenberg-Marquardt training algorithm based on sensor fusion for the monitoring of drill-wear condition. The input features to the neural networks were extracted from AE, vibration and current signals using the wavelet packet transform (WPT) analysis. Training and testing were performed at a moderate range of cutting conditions in the dry drilling of steel plates. The results show good performance in drill- wear monitoring by the proposed method of sensor fusion and neural network analysis.

• 한국군사과학기술학회지
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• 제13권1호
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• pp.99-104
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• 2010

MDPREF(Multidimensional Preference Analysis) is a program for analysis of preferences. It is what is known as a vector model. This means that the objective of the MDPREF analysis is to identify a perceptual map displaying subject(attribute) vectors. To form the subject vectors visually, lines are drawn from the origin of the plot to each subject point. We analysis the defense industry infrastructure in fire power area by using MDPREF.

• 한국관광식음료학회지:관광식음료경영연구
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• 제16권1호
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• pp.1-20
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• 2005

The objective of this study is to examine how the factors influence each other by determining the appropriate measurement standard based on the fast food restaurant attribute evaluation, perceived pricing, value, satisfaction and intent for return patronage, and present an effective fast food restaurant marketing strategy based on the analytical results by patrons and market segmentations. The results showed that restaurant attribution evaluation had a positive effect on the perceived value, satisfaction and intent for return patronage of the fast food restaurant patrons; perceived pricing of the fast food restaurant patrons had a positive affect on the perceived value, satisfaction and intent for return patronage; perceived value had a positive affect on satisfaction and intent for return patronage; and satisfaction had a positive affect on intent for return patronage.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.144-147
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• 1993

The long-term electricity resource planning of electric utility has undergone significant change during the past decade. The current resource planning can be considered as multi-objective decision making procedure under the various uncertainties such as demand growth, construction cost, fuel price, environmental regulation, plant site, financial adequacy, new technology advent and so on. This paper presents a standardized electricity resource planning scheme using the strategic planning concept. EGEAS computer model was fully applied to indentify feasible alternative plans and simulate various attribute values corresponding each alternative plan and future. As a case study, a hypothetical long-ten capacity expansion planning problem is analyzed.

• 산업경영시스템학회지
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• 제8권11호
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• pp.85-95
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• 1985

This thesis is a study on the work sampling method which is one of the important parts in the fields of work measurement today. The primary objective of this study is to examine various methods of selecting observation times in work sampling studies, including simple random systematic, and stratified sampling and a new method called restricted random sampling. The attribute of these sampling methods are explained, particulary statistical efficiency, and the important advantages of stratification are analysed. A case study of work sampling was made in a manufacturing plant to show its practical application and the effectiveness of the stratified random sampling technique.

• Korean Journal of Mathematics
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• 제29권1호
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• pp.137-167
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• 2021

Spherical fuzzy set (SFS) is also one of the fundamental concepts for address more uncertainties in decision problems than the existing structures of fuzzy sets, and thus its implementation was more substantial. The well-known sine trigonometric function maintains the periodicity and symmetry of the origin in nature and thus satisfies the expectations of the experts over the multi parameters. Taking this feature and the significance of the SFSs into the consideration, the main objective of the article is to describe some reliable sine trigonometric laws (ST L) for SFSs. Associated with these laws, we develop new average and geometric aggregation operators to aggregate the Spherical fuzzy numbers (SFNs). Then, we presented a group decision- making (DM) strategy to address the multi-attribute group decision making (MAGDM) problem using the developed aggregation operators. In order to verify the value of the defined operators, a MAGDM strategy is provided along with an application for the selection of laptop. Moreover, a comparative study is also performed to present the effectiveness of the developed approach.

• Journal of Information Processing Systems
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• 제17권1호
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• pp.163-177
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• 2021

Many methods of discovering social networking communities or clustering of features are based on the network structure or the content network. This paper proposes a community discovery method based on topic models using a time factor and an unsupervised clustering method. Online community discovery enables organizations and businesses to thoroughly understand the trend in users' interests in their products and services. In addition, an insight into customer experience on social networks is a tremendous competitive advantage in this era of ecommerce and Internet development. The objective of this work is to find clusters (communities) such that each cluster's nodes contain topics and individuals having similarities in the attribute space. In terms of social media analytics, the method seeks communities whose members have similar features. The method is experimented with and evaluated using a Vietnamese corpus of comments and messages collected on social networks and ecommerce sites in various sectors from 2016 to 2019. The experimental results demonstrate the effectiveness of the proposed method over other methods.