• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.56-57
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• 2014

As school facilities have been expanding quantity better than quality, efficient school facility management has been focused on from 2001 in domestic. Due to obsolescence of school facility, objective management and maintenance cost of school facility is very important. However LCC(Life cycle cost) analyst, owner, engineer, contractor and facility manager have a difficulty to obtain and facilitate the basic analyzed data required to analyze LCC of school facility and establish maintenance plan. Therefore this research presents muti-dimensional analysis method through data warehouse technique for supplying maintenance cost information of school facility that can trace and accumulate the scattered LCCing data in the perspective of life cycle of school facility.

• Nutrition Research and Practice
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• v.2 no.2
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• pp.85-92
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• 2008

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Gamer & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs.

• Journal of the Korean housing association
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• v.16 no.4
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• pp.121-129
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• 2005

The major goal of this study is drawing design plan factors considering residents' life cycle and life style when remodeling design is needed. By drawing such design factors, the study will propose an alternative remodeling design plan. Such design method was defined as Multi-Dimensional module design method. And constructing data-system based on Multi-Dimensional module was secondary goal in this study. The details are as follows: Based on analysis of Residents' demand for remodeling and features of emotion-design applied to remodeling, the system which is suitable for application in remodeling design method was conducted. Based on the type of construction materials, the level value was set up according to emotion-factor application. Also, by conducting coding operation according to the distinction of construction materials, this study seeks the unit drawing method of information for constructing emotion-information system.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.17-24
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• 2020

The traveling salesman problem is an algorithmic problem tasked with finding the shortest route that a salesman visits, visiting each city and returning to the started city. Due to the exponential time complexity of TSP, it's hard to implement on cases like amusement park or delivery. Also, TSP is hard to meet user's demand that is associated with multi-dimensional attributes like travel time, interests, waiting time because it uses only one attribute - distance between nodes. This paper proposed Top-n Skyline-Multi Dimension TSP to resolve formerly adverted problems. The proposed algorithm finds the shortest route faster than the existing method by decreasing the number of operations, selecting multi-dimensional nodes according to the dominance of skyline. In the simulation, we compared computation time of dynamic programming algorithm to the proposed a TS-MDT algorithm, and it showed that TS-MDT was faster than dynamic programming algorithm.

• Journal of the Korean Institute of Gas
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• v.4 no.4 s.12
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• pp.58-64
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• 2000

Data compression and retrieval method are investigated for the effective utilization of measured process data. In this paper, a new data compression method, Clustering Compression(CC), which is based on the k-means clustering algorithm and piecewise linear approximation method is suggested. Case studies on industrial data set showed the superior performance of clustering based techniques compared to other conventional methods and showed that CC could handle the compression of multi-dimensional data.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.939-947
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• 2016

As the number of legacy database systems and the size of data to manipulate have been vastly increased, it has become more difficult and complex to analyze characteristics of data. To improve the efficiency of data analysis and help administrators to make decisions in business life, BI(Business Intelligence) system is used. To construct data warehouse and cube from legacy database systems makes it easy and fast to transform raw data into integrated and categorized meaningful information. In this paper, we built a BI system for an University administration. Several source system databases were integrated to data warehouse to build data cubes. The implemented BI system shows much faster data analysis and reporting ability than the manipulation in legacy systems. It is especially efficient in multi dimensional data analysis, nonetheless in single dimensional analysis.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1259-1276
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• 2017

As technologies related to sensor network are currently emerging and the use of GeoSensor is increasing along with the development of Internet of Things (IoT) technology, spatial query processing systems to efficiently process spatial sensor data are being actively studied. However, existing spatial query processing systems do not support a spatial-temporal data type and a spatial-temporal operator for processing spatialtemporal sensor data. Therefore, they are inadequate for processing spatial-temporal sensor data like GeoSensor. Accordingly, this paper developed a spatial-temporal query processing system, for efficient spatial-temporal query processing of spatial-temporal sensor data in a sensor network. Lastly, this paper verified the utility of System through a scenario, and proved that this system's performance is better than existing systems through performance assessment of performance time and memory usage.

• Journal of Energy Engineering
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• v.15 no.1 s.45
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• pp.1-7
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• 2006

The multi-dimensional two-phase flow models were developed for analyze the multi-dimensional behaviors or nuclear systems. To verify the simple turbulence model, The single phase mixing problem in a rectangular slab was calculated and compared with the commercial CFD code results. That result shows a good agreement with the CFD result. And the RPI Air-water experiments were simulated to assess the two-phase turbulence model in the multi-dimensional component. The first calculated distribution or void-fraction is highly dispersed and diffusive. It was revealed that the main reason is undesirable stratification force in a horizontal stratified flow regimes. Therefore the horizontally stratified flow regime is deleted because the stratified flow regime is not expected in multi-dimensional flow. With the modification of the flow regime, the predicted flow patterns and void fraction profiles are in good agreement with the measured data.

• Journal of Distribution Science
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• v.13 no.4
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• pp.55-64
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• 2015

Purpose - Multi-dimensional prices comprise multiple components such as monthly payments and a number of payments rather than a single lump-sum amount. According to previous studies, an increase in the number of price dimensions leads to a massive amount of cognitive stress resulting in incorrect calculation, and deterioration in the consistency of the price judgment. However, an increase only in the level of complexity of calculating multi-dimensional prices does not always result in a corresponding decrease in the accuracy of price evaluation. Since diverse variables could affect consumers' purchase-decision-making process, the results of price evaluation would be different. In this study, an empirical analysis was performed to determine how the accuracy of price evaluation varies depending on the extent of the complexity of price dimensions using product involvement and brand preference as moderating variables. Research design, data, and methodology - A survey was conducted on 260 students, and 252 effective responses were used for analysis. The data was analyzed using t-test, one-way ANOVA, and two-way ANOVA. In this study, six hypotheses were developed to examine the effect of product involvement and brand preference on consumers' evaluation effort of multi-dimensional prices. Results - As the number of price dimensions increased, accuracy of price evaluation appeared to be low in high involvement, as expected. However, it showed no differences in price evaluation effort when the level of complexity of calculating multi-dimensional prices is low. When a small number of price dimensions are presented in both cases of high and low involvement, accuracy of price evaluation is much higher in a weak brand preference. On the contrary, a strong brand preference enhances an accuracy of price evaluation only in case of low involvement when the number of price dimensions is increased. An interaction effect of product involvement and brand preference on consumers' evaluation of multi-dimensional prices did not exist irrespective of the level of complexity of calculating prices being high or low. Conclusions - When the number of price dimensions is small, consumers' effort for price evaluation shows almost no difference without the moderating effect of involvement, and a weak brand preference leads to a higher accuracy of price evaluation in an effort to make the best selection. No interaction effect of product involvement and brand preference was found except for a main effect of brand preference. When a price is composed of multiple dimensions rendering it more difficult to calculate the final price, the effort for price evaluation was expected to decrease only slightly in case of combination of high involvement and strong brand preference. This is because people have a higher purchase intentions and trust for that particular brand. However, the accuracy of price evaluation was much lower in cases of high involvement, and there was no interaction effect between product involvement and brand preference except for a main effect of involvement and brand preference, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3348-3364
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• 2021

Magic matrix-based data hiding schemes are applied to transmit secret information through open communication channels safely. With the development of various magic matrices, some higher dimensional magic matrices are proposed for improving the security level. However, with the limitation of computing resource and the requirement of real time processing, these higher dimensional magic matrix-based methods are not advantageous. Hence, a kind of data hiding scheme based on a single or a group of multi-dimensional flexible magic matrices is proposed in this paper, whose magic matrix can be expanded to higher dimensional ones with less computing resource. Furthermore, an adaptive mechanism is proposed to reduce the embedding distortion. Adapting to the secret data, the magic matrix with least distortion is chosen to embed the data and a marker bit is exploited to record the choice. Experimental results confirm that the proposed scheme hides data with high security and a better visual quality.