• International conference on construction engineering and project management
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• 2015.10a
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• pp.627-628
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• 2015

Construction defect which can causes economic damage such as schedule delay, cost overrun is a considerably important factor in construction industry. In general, a construction defect features a difficulty to find out causes precisely because it occurs when several interrelated causes combine. Yet, studies have tried to understand the interrelationships between factors are limited. In addition, despite of a tremendous amount of construction data, it's not still enough to analyze them, but tends to depend on experience or know-how of practitioners. Thus, it is necessary to identify underlying causes in influential factors by utilizing related data. This paper analyses Interrelationships between causal factors using Association Rule Mining to discover root causes of construction defects. Confidence and Lift that can be used for presenting the interrelationships of the causes were extracted from 1241 cases in 30 projects in Korea. It is expected that this paper allows the construction managers to discover key factors and make right decisions to reduce occurrence of construction defects. Furthermore, analysis of interrelationships can improve understanding of structural patterns of construction defects.

• Korean Journal of Social Welfare
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• v.32
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• pp.235-266
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• 1997

• The Journal of the Korean dental association
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• v.25 no.6 s.217
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• pp.516-517
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• 1987

• The Journal of the Korean dental association
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• v.25 no.5 s.216
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• pp.402-403
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• 1987

• Asia pacific journal of information systems
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• v.20 no.2
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• pp.1-21
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• 2010

e-Government is an innovative phenomenon around the globe for refurbishing public administration. Research to date, however, has been deficient in empirical studies of the factors that emerge out of the interplay of structure and human interactions responsible for successful implementation of e-Government projects. From the perspective of structuration theory, this study examines and explains the impact of this interplay in the implementation of an e-Government system, eSeva for local administration at one of the Indian state, The results suggest that the success of implementation of e-Government projects can be conceptualized as the outcome of persisting constructive interrelationships among the human, programmatic and institutional elements of e-Government and the critical learning and adaptation as a result of efforts at the structuration level.

• Korea-Australia Rheology Journal
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• v.18 no.1
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• pp.31-38
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• 2006

A systematic approach is employed to elucidate the interrelationships among macroeconomic entities such as science, engineering, technology, industry and national economy. Specifically, a conceptual, sequential method has been developed to clearly identify the essential ingredients needed for each macroeconomic entity starting from science to transform to the next one, and all the way to the national economy where the production of added-value is of overriding importance. The results thus obtained can then be utilized for macroeconomists to readily apply the engineering theory and knowledge to various macroeconomics situations, while engineers can likewise utilize the results on top of the microeconomic knowledge already prevalent in many engineering fields in getting better grasp of the seemingly difficult nation's macroeconomic picture. Other peripheral concepts and issues such as the evolutionary development of industry, the perspectives of the $21^{st}$ century civilization, an analogy between macroeconomics and chemical engineering, and national policies for each macroeconomic entity are also presented in this study.

• Journal of the Korean Society of Safety
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• v.17 no.4
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• pp.126-132
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• 2002

By using the reference data, the empirical equations which describe the interrelationships of explosion properties and physical properties of n-chlorinated hydrocarbons have been derived. The properties which have been correlated are the lower and upper explosive limits, the stoichiometric coefficients, the heats of combustion, the carbon numbers. Also, the new equations using the mathematical and statistical methods for predicting the temperature dependence of lower explosive limits(LEL) of chlorinated hydrocarbons on the basis of the literature data are proposed. The fire and explosion properties calculated by the proposed equations in this research were a good agrement with literature data within a few A.A.P.E.(Average Absolute Percent Error) and A.A.D.(Average Absolute Deviation.) From a given explosive properties, by using the proposed equations, it is possible to predict to the fire and explosion characteristics for the other chlorinated hydrocarbons.

• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.317-333
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• 2022

Purpose - The purpose of this study is to investigate the interrelationships between visitor motivations, attitude, and behavioral intention toward the Harbin International Ice and Snow Festival, China. It is also to test moderating roles of gender and past travel experience between these factors. Design/methodology/approach - Data was collected from potential Chinese visitors, after which 420 usable surveys were processed. Findings - To investigate our hypotheses, we used descriptive, confirmatory factor analysis, and structural equation modeling. We found that aesthetic attractiveness, purchase of local products, and involvement had positive effects on attitude toward the festival. Attitude toward the festival had a significant effect on behavioral intention to visit. Finally, it was also found that gender and past travel experience significantly moderated the interrelationships between these factors. Research implications or Originality - Theoretical and managerial implications, as well as, suggestions for future research are discussed.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.1
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• pp.1-16
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• 2013

This study investigates the spatial distribution characteristics of Korean fashion industries during the last decade, in which the economic geography of fashion industries has changed dynamically with economic globalization and "thus resulted in increased" demand "of" diversification. In particular, this study examines the spatial distribution patterns of fashion industries in the Seoul metropolitan area where fashion industries are highly agglomerated. For the purpose, this study applies Moran's I Index of spatial autocorrelation analysis for seven functional sectors of fashion industries related to fashion production. The global and local agglomeration patterns are examined for each functional sector. The results clarify the distinction in the spatial agglomeration patterns among the seven functional sectors of fashion industries in the Seoul Metropolitan area. Logit models are developed to examine the interrelationships among functional sectors in their spatial agglomeration distribution patterns. By conducting binary logistic regression analysis, we find out how the spatial agglomeration of each functional sector is related to the others.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.755-762
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• 2022

This paper propose a clustered algorithm that possible more efficient COVID-19 disease learning prediction within clustering using context-aware attribute information. In typically, clustering of COVID-19 diseases provides to classify interrelationships within disease cluster information in the clustering process. The clustering data will be as a degrade factor if new or newly processing information during treated as contaminated factors in comparative interrelationships information. In this paper, we have shown the solving the problems and developed a clustering algorithm that can extracting disease correlation information in using K-means algorithm. According to their attributes from disease clusters using accumulated information and interrelationships clustering, the proposed algorithm analyzes the disease correlation clustering possible and centering points. The proposed algorithm showed improved adaptability to prediction accuracy of the classification management system in terms of learning as a group of multiple disease attribute information of COVID-19 through the applied simulation results.