• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.1
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• pp.21-28
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• 2011

In the existing digital map of the Ver.1.0, it is impossible to make a small scale digital map, which is under the 1/5000 scale map, by using the 1/1000 digital map which is the most large scale one. Because of this reason, the existing digital maps are produced into a 1/1000 and a 1/5000 map by means of two different scale aerial photos. The next generation digital map should be successively related to a small scale digital map based on the most large scale digital one. This is so important from the aspects of data share and the consecutive renewal. Ever since the development of the digital map of the Ver. 2.0, the possibility of making a multi-scale consecutive digital map has been presented and the related research has been done again. The most basic thing in the multi-scale digital maps is to decide the criteria of the generalization between the two scales. In this study, I try to formulate the criteria of the generalization required to make the 1/5000 digital map by using the 111000 digital one. In addition, I by to explore the application possibility of the consecutive renewal by carrying out auto-generalization.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.1-8
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• 2008

It is essential to maintain constant QoS despite of cell overload or erroneous wireless link during transmission because QoS of a multimedia service may be severely degraded by small delay or packet loss. This paper deals with a cell selection method for supporting the QoS of multimedia services over heterogeneous networks. The proposed scheme is based on Fuzzy Multi-Criteria Decision Making (FMCDM), in which uncertain parameters such as user system preference, the communication cost and cell load, and the transmission delay are used in the decision process using the aggregation function in fuzzy set theory. In this scheme, errors in the evaluation parameters impose milder changes on the total evaluation value than in binary logics. Simulation is focused on the average delay and packet loss rate, and the simulation results show that our proposed method provides mobile terminals the optimal performance.

• Spatial Information Research
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• v.9 no.2
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• pp.227-238
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• 2001

As society progresses and becomes more complicated, improvements and demanded in the quality of life according to various interest groups. In relation to environment concerns, waste landfill sites in particular have been of concern. Conflicts involving treatment of such sites and decision making policies have been a point of contention between local governments, residents, and concerned organizations. To resolve these conflicts, this study developed the Multi-Criteria Spatial Decision Support System (MC-SDSS). The results of the case study revealed several conclusions; first, the approach used in this study can help to yield a better consensus for deciding upon waste landfill sites; next, by conducing sensitivity analysis, technical errors which can occur during the decision making process can be minimized; and finally, resistance from specific opposition groups can be effectively dealt with by using MC-SDSS.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.49-56
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• 2011

This paper deals with a methodology for searching optimal route of hazard material (hazmat) vehicles. When we make a decision of hazmat optimal paths, there is a conflict between the public aspect which wants to minimize risk and the private aspect which has a goal of minimizing travel time. This paper presents Efficient Vector Labeling algorithm as a methodology for searching optimal path of hazmat transportation, which is intrinsically one of the multi-criteria decision making problems. The output of the presented algorithm is a set of Pareto optimal paths considering both risk and travel time at a time. Also, the proposed algorithm is able to identify non-dominated paths which are significantly different from each other in terms of links used. The proposed Efficient Vector Labeling algorithm are applied to test bed network and compared with the existing k-shortest path algorithm. Analysis of result shows that the proposed algorithm is more efficient and advantageous in searching reasonable alternative routes than the existing one.

• Steel and Composite Structures
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• v.27 no.1
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• pp.27-33
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• 2018

In this study, a mixed-interpolated tensorial component 4 nodes method (MITC4) is treated as a numerical analysis model for topology optimization using multiple materials assigned within Reissner-Mindlin plates. Multi-material optimal topology and shape are produced as alternative plate retrofit designs to provide reasonable material assignments based on stress distributions. Element density distribution contours of mixing multiple material densities are linked to Solid Isotropic Material with Penalization (SIMP) as a design model. Mathematical formulation of multi-material topology optimization problem solving minimum compliance is an alternating active-phase algorithm with the Gauss-Seidel version as an optimization model of optimality criteria. Numerical examples illustrate the reliability and accuracy of the present design method for multi-material topology optimization with Reissner-Mindlin plates using MITC4 elements and steel materials.

• Journal of the Korean Solar Energy Society
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• v.25 no.2
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• pp.53-62
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• 2005

In this study, the thermal performance of multi-story double-skin facade(DSF) with variation of cavity height is evaluated to offer useful data in determining cavity height of multi-story DSF. For this, thermal criteria for multi-story DSF is adopted and a DSF model for evaluation of the thermal performance is established. Through the evaluation of CFD simulation, the recommended height of multi-story DSF is 5 stories or less to improve the thermal performance during the intermediate season.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.255-262
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• 2002

In this paper, an improved multi-objective optimmum design method is proposed. And it is applied to steel frames under seismic loads. The multi-objective optimization problem is formulated with three optimality criteria, namely, minimum structural weight and maximum strain energy and stability. The Pareto curve can be obtained by performing the multi-objective optimization for multistory shear buildings. In order to efficiently solve the multi-objective optimization problem the decomposition method that separates both system-level and element-level is used. In addition, various techniques such as effective reanalysis technique with respect to intermediate variables and sensitivity analysis using an automatic differentiation (AD) we incorporated. Moreover, the relationship function among section properties induced from the profile is used in order to link system-level and element level. From the results of numerical investigation, it may be stated that the proposed method will lead to the more rational design compared with the conventional one.

• Fashion & Textile Research Journal
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• v.12 no.3
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• pp.318-326
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• 2010

The advantages of the multi-channel retailing have been widely discussed but empirical research on fashion multi-channel retailing has been limited. In this study, multi-channel concept was discussed and then, channel choosing condition of apparel shopper and channel choosing criteria for information search and buying were investigated as a empirical study. Drawing on a sample of 298 customers of apparel products in Korea, the result demonstrated that some differences in the perception of experience goods and search goods among apparel products. And, according to buying channel, consumers were different from each other in information search time and clothing expenses. Some suggestion for the future research of multi-channel retailing was given.

• Land and Housing Review
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• v.13 no.3
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• pp.107-113
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• 2022

With increasing airtight building construction aimed at reducing energy consumption, indoor relative humidity is increasing which can lead to condensation and moisture damage in multi-family residential buildings. This has led to increased implementation of mechanical ventilation to control indoor moisture. However mechanical ventilation systems consume additional energy and generate noise. As this leads to occupant discomfort, it is necessary to select a ventilation system that addresses the energy and noise issues. This research measured the ventilation performance, energy consumption, and noise level of mechanical ventilation devices in multi-family residential buildings. TOPSIS, a multi-criteria decision making technique was used to determine appropriate ventilation strategies in addition to occupant ventilation system operation preference.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.