• Journal of Korea Trade
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• v.24 no.8
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• pp.81-100
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• 2020

Purpose - Based on complexity theory, this study develops a configurational model to predict the profitability of Halal cosmetics firms in the Indonesian and Malaysian markets. The proposed research model involves two level configurations-industry context and selling strategies-to predict high and low scores of a firm's profitability. The industry context configuration model comprises industry stability, product homogeneity, price sensitivity, and switching cost. Selling strategies include customer-focused, competitor-focused, and margin-focused approaches. Design/methodology - This is the first empirical study that calculates causal models using a combination of industry context and selling strategy factors to predict profitability. Data obtained from the marketing managers of cosmetics firms are used to test the proposed configurational model using fuzzy-set qualitative comparative analysis (fsQCA). It contributes to the current knowledge of business marketing by identifying the factors necessary to achieve profitability using analysis of condition (ANC). Findings - The results revealed that unique and distinct models explain the conditions for high and low profitability in the Indonesian and Malaysian halal cosmetic markets. While customer-focused selling strategy is necessary to attain a higher profit in both the markets, margin-focused selling strategy appears to be an essential factor only in Malaysia. Complexity of the interactions of selling strategies with industry factors and differences between across two study markets confirmed that complexity theory can support the research configurational model. The theoretical and practical implications are also illustrated. Originality/value - Despite the rapid growth of the global halal industry, there is little knowledge about the halal cosmetic market. This study contributes to the current literature of the halal market by performing a set of asymmetric analytical approaches using a complex theoretical model. It also deepens our understating of how the Korean firms can approach the Muslim consumer's needs to generate more beneficial turnover/revenue.

• Advances in environmental research
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• v.2 no.3
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• pp.203-227
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• 2013

Global demand for dwelling energy and implications of changing climatic conditions on buildings confront the built environment to build sustainable dwellings. This study investigates the variability of future climatic conditions on newly built detached dwellings in the UK. Series of energy modelling and simulations are performed on ten detached houses to evaluate and predict the impact of varying future climatic patterns on five building performance indicators. The study identifies and quantifies a consistent declining trend of building performance which is in consonance with current scientific knowledge of annual temperature change prediction in relations to long term climatic variation. The average percentage decrease for the annual energy consumption was predicted to be 2.80, 6.60 and 10.56 for 2020s, 2050s and 2080s time lines respectively. A similar declining trend in the case of annual natural gas consumption was 4.24, 9.98 and 16.1, and that for building emission rate and heating demand were 2.27, 5.49 and 8.72 and 7.82, 18.43 and 29.46 respectively. The study further analyse future heating and cooling demands of the three warmest months of the year and ascertain future variance in relative humidity and indoor temperature which might necessitate the use of room cooling systems to provide thermal comfort.

• Architectural research
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• v.18 no.4
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• pp.145-149
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• 2016

Recently, a goal was set globally to reduce the Carbon Dioxide ($CO_2$) emission at national levels by 30 % in comparison to the Business As Usual (BAU) pursuant to the United Nations Framework Convention on Climate Change. As construction industry accounts for as high as 40 % of the $CO_2$ emission by the entire industrial sector in Korea, efforts toward reducing emissions from the construction industry are essential. Buildings are mainly responsible for $CO_2$ emissions, and, to reduce the $CO_2$ emitted from the buildings, a fast and accurate calculation method is required to be introduced in the architectural design phase. If the standardized data based on Building Information Modelling (BIM) is utilized, $CO_2$ emissions can be calculated quickly and accurately during the design phase. However, it is difficult for the designers who lack the knowledge regarding $CO_2$ emissions to reduce and manage such emission during the planning and design phases of buildings by estimating the quantities of various materials and the corresponding $CO_2$ emissions. Accordingly, the objective of this study is to develop a BIM-based $CO_2$ emission estimation system for a rapid and objective analysis and verification of $CO_2$ emissions.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.249-256
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive learning mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control (FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, FLC and ANN controller.

• Structural Engineering and Mechanics
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• v.68 no.4
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• pp.423-442
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• 2018

In this paper, masonry infilled reinforced concrete (RC) frames are analyzed through a probabilistic approach. A macro-modeling technique, based on an equivalent diagonal pin-jointed strut, has been resorted to for modelling the stiffening contribution of the masonry panels. Since it is quite difficult to decide which mechanical characteristics to assume for the diagonal struts in such simplified model, the strut width is here considered as a random variable, whose stochastic characterization stems from a wide set of empirical expressions proposed in the literature. The stochastic analysis of the masonry infilled RC frame is conducted via the Probabilistic Transformation Method by employing a set of space transformation laws of random vectors to determine the probability density function (PDF) of the system response in a direct manner. The knowledge of the PDF of a set of response indicators, including displacements, bending moments, shear forces, interstory drifts, opens an interesting discussion about the influence of the uncertainty of the masonry infills and the resulting implications in a design process.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.754-759
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• 2007

Methodology of ontology building based on Web resources will not only reduce significantly the ontology construction period, but also enhance the quality of the ontology. Remarkable progress has been achieved in this regard, but they encounter similar difficulties, such as the Web data extraction and knowledge acquisition. This paper researches on the characteristics of ontology construction data, including dynamics, largeness, variation and openness and other features, and the fundamental issue of ontology construction - formalized representation method. Then, the key technologies used in and the difficulties with ontology construction are summarized. A software Model-OntoMaker (Ontology Maker) is designed. The model is innovative in two regards: (1) the improvement of generality: the meta learning machine will dynamically pick appropriate ontology learning methodologies for data of different domains, thus optimizing the results; (2) the merged processing of (semi-) structural and non-structural data. In addition, as known to all wetland researchers, information sharing is vital to wetland exploitation and protection, while wetland ontology construction is the basic task for information sharing. OntoMaker constructs the wetland ontologies, and the model in this work can also be referred to other environmental domains.

• Proceedings of the KSRS Conference
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• v.2
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• pp.586-589
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• 2006

High resolution satellite imagery is regarded as one of the important data sets to engineering application, as well as conventional scientific application. However, despite this general view, there are a few target applications using this information. In this study, the possibility for the future wide uses in associated with smart graphics of this information is investigated. The concept of smart graphics can be termed intelligent graphics with XML-based structure and knowledge related to semantic web, which is a useful component for the data dissemination framework model in a multi-layered web-based application. In the first step in this study, high resolution imagery is transformed to GML (Geographic Markup Language)-based structure with attribute schema and geo-references. In the second, this information is linked with GIS data sets, and this fused data set is represented in the X3D (eXtensible 3D), ISO-based web 3D graphic standard, with styling attributes, in the next stop. The main advantages of this approach using GML and X3D are the flourished representations of a source data according to user/clients’ needs and structured 3D visualization linked with other XML-based application. As for the demonstration of this scheme, 3D urban modelling case with actual data sets is presented.

• The Journal of Information Systems
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• v.20 no.2
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• pp.1-20
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• 2011

In this study, we verify the relationship, which is presented by ISO/IEC 15504, between the assessor's competence and the efficiency of assessment. The ISO standard has been developed by many formal trial experiences for the software process assessment. The software process assessment determines the process capability, and makes the software process improvement possible in the development cycle. In the field assessment, third-party and team-based assessments are generally recommended. Therefore assessors' competences are essential to achieve the effectiveness and the efficiency of assessment. Survey data are collected from the third-party process assessment of a real IT industry, and the analysis is done by a causal modelling technique - PLS. Some findings are as follows. Depending on assessors' SE experiences, effects of the assessor's competence are existed, and their standard knowledge and assessment skill are effected each other. And the efficiency of assessment depends on the assessor's competence. In addition, the power analysis is presented and future research is suggested, because of many limitations of this study.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.205-211
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• 2020

The study aims to assess factors affecting intention to purchase green products in Vietnam. The study employs samples from customers who have actually experienced green consumption in Vietnam. The samples were collected by convenient sampling methods. The survey obtained 206 responses with full information. The survey was conducted from October 2019 to January 2020. The measurement scale was a 5-point scale with 1- completely disagree and 5- strongly agree. This study employs factor analysis and structural equation modelling analysis. The results showed that the social and environment sustainability awareness have positive effects on altruism of customers who are interested in green consumption. Altruism also has the same direction on green purchase intention. Besides, the attitude toward buying green and health consciousness affects green purchase intention. At the same time, the altruism and attitude towards buying green products also influence positively on green purchase intention. Besides, the health consciousness positively affects attitude towards buying green products. The results show that the health consciousness has a negative impact on intention to purchase green products. The findings suggest that it is necessary to raise customers' health consciousness, customers' altruism from disseminating knowledge about environmental protection as well as society to enhance the green consumption in Vietnam.

• 한국전산유체공학회:학술대회논문집
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• 2007.04a
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• pp.120-124
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• 2007

Helicopters and rotary-wing vehicles encounter a wide variety of complex aerodynamic phenomena and these phenomena present substantial challenges for computational fluid dynamics(CFD) models. This investigation presents the rotor aerodynamic analysis items for the helicopter development and variety aerodynamic analysis methods to provide the better solution to researchers and helicopter developers between aerodynamic problems and numerical aerodynamic analysis methods. The numerical methods to make an analysis of helicopter rotor are as below - CFD Modelling : actuator disk model, BET model, fully rotor model,... - Grid : sliding mesh, chimera mesh / structure mesh, unstructure mesh,... - etc. : panel method periodic boundary, quasi-steady simulation, incompressible,... The choice of CFD methodology and the numerical resolution for the overall problem have been driven mostly by available computer speed and memory at any point in time. The combination of the knowledge of aerodynamic analysis items, available computing power and choice of CFD methods now allows the solution of a number of important rotorcraft aerodynamics design problems.