• Journal of the Korean Society for Library and Information Science
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• v.41 no.2
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• pp.335-357
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• 2007

There has been many studies representing intellectual structures with multidimensional scaling(MDS) However MDS configuration is limited in representing local details and explicit structures. In this paper, we identified two components of MDS mapping approach; one is MDS algorithm and the other is preparation of data matrix. Various combinations of the two components of MDS mapping are compared through some measures of fit. It is revealed that the conventional approach composed of ALSCAL algorithm and Euclidean distance matrix calculated from Pearson's correlation matrix is the worst of the compared MDS mapping approaches. Otherwise the best approach to make MDS map is composed of PROXSCAL algorithm and z-scored Euclidean distance matrix calculated from Pearson's correlation matrix. These results suggest that we could obtain more detailed and explicit map of a knowledge domain through careful considerations on the process of MDS mapping.

• Explosives and Blasting
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• v.42 no.1
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• pp.23-33
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• 2024

Recently, various techniques and patented methods on blasting operation are being newly developed. In this study, test construction of the MDS blasting method was performed, and the fragmentation size and the occurrence rate of rocks exceeding 300mm were measured and analyzed in comparing to normal blasting method. Test construction was performed three times each for normal and the MDS at the same bench for each round, and fragmentation size(P80) and occurrence rate of rocks exceeding 300mm(S30) were measured using digital image processing. A sieve bucket was also manufactured on-site to sort oversized rock particles from muck piles, and their weights and equivalents were measured to calculate actual values. As a result, the fragmentation size decreased of 21.0% with the MDS compared to normal, and 100-S30 decreased of 10.1%, with actual values decreasing of 7.6%. Although there were variations in blasting effects for each round due to differences in rock quality at site, overall, the MDS proved to be more effective compared to normal blasting method under equivalent conditions.

• Journal of the Korean housing association
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• v.1 no.2
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• pp.1-11
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• 1990

A study of domestic furniture arrangements may reveal the living style relevant to the room as conceived and coded by occupants and the effects of the physical environment on the structure of behavior settings. The purpose of this study was to investigate, through analizing the furniture usage and behavior as a non-reactive and activity oriented behavioral measures, the occupants` domestic habits as a living style using MDS. MDS(multidimensional scaling technique) is a statistical technique for creating a spatial representation of data. It Is a particularly appropriate technique for analizing qualitative data such as the furniture usage and behavior because it takes into account all of the relationships between items. For the MDS analysis, the furniture usage and behavior examined by housing types based on 114 households in Seoul. The result of spatial configuration by MDS has three dimensions : recogn;lion of room function, pattern of room organization, understanding of room meaning. The effect of housing types for dimensions is identical but configuration of furniture items is different.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.19-24
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• 2005

Radio Frequency Identification (RFID) is a technology used to identify the physical objects and get information about the object on which the tag attaches from network. It is expected that RFID will lead IT market from human-oriented to object-oriented. Therefore, RFID technology and services will become wide-spread. But the system of RFID naming service is quite similar to the existing DNS facilities. So it has many weak points against to DDos attack. Furthermore if the MDS server Is under attack, there might be trouble of total RFID networks.In this paper, we propose a new detecting model to find attack traffic at local routers by using Management Information Base (MIB) which is optimized for RFID MDS server.

• Explosives and Blasting
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• v.41 no.3
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• pp.13-25
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• 2023

The conventional bench blasting method uses the bottom initiation in all blast holes in a round, whereas the MDS (mixture detonation system) method applies the bottom and top initiations alternately according to the spatial position or temporal sequence of each blast hole. The former and latter are respectively called the SMDS (spatial MDS) and TMDS (temporal MDS) methods. Another variant called MMDS (modified MDS) is designed for the specific use in the site having a fly-rock problem. This study compares the MDS method to the conventional method in the aspect of rock fracturing effect. The comparison is made by numerical simulations for a two-row bench blasting model in the LS-DYNA. The SPH-FEM coupling method is utilized for constructing the blasting model. The SPH elements are used for the rock in the near-field region of the blast holes, and the FEM elements for that in the far-field region. The RHT material model is used for the rock. As a result of the simulations, it was found that up to 0.4 m deeper damaged zone was appeared in the SMDS method than in the conventional method for the case of the burden 1.6 m and bench height 3.0 m. In addition, the fly-rock velocity to the normal direction of the bench slope was appeared about 2.0 m/s lower in the MMDS method compared to the other methods.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.301-309
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• 2009

Multidimensional scaling(MDS) is a statistical multivariate analysis technique that is often used in information visualization for exploring similarities or dissimilarities in data. In order to analyse and visualize data, MDS measures the dissimilarities between objects and uses them or their mean if they are repeatedly measured. When there exist outliers or when the variation of data is too large, we can hardly get reliable results on the research using MDS. In this paper, we consider the MDS based on bootstrap method when the variation of data is large. Standardized residual sum of squares is considered as measuring goodness-of-fit of the model. A real data analysis is include to examine our approach.

• Information Systems Review
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• v.12 no.1
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• pp.209-227
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• 2010

One type of innovative multimedia platform environments is mobile data services (MDS), exemplified by Nate, Show, and OZ. In the context of MDS, enhancing user's continuance intention is a significant challenge to the continuing growth and long-term viability of MDS. Because the cost of using MDS is borne mainly by users, they are likely to evaluate it based on perceptions of what is received and what is given. This study identifies perceived usefulness and perceived enjoyment as the 'get'components, and perceived fee and perceived anxiety as the 'give' components. To understand the role of get and give components in the MDS post-adoption environment, this study incorporates these components into expectation confirmation model. We collected data from 204 users who had direct experiences with MDS within recent 3 months. The data was analyzed by employing PLS (partial least squares). Theoretical and practical implications of our findings are discussed.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.567-578
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• 2017

Grouped multivariate data can be tested for differences between two or more groups using multivariate analysis of variance (MANOVA). However, this method cannot be used if several assumptions of MANOVA are violated. In this case, multidimensional scaling (MDS) and analysis of distance (AOD) can be applied to grouped dissimilarities based on the various distances. A permutation test is a non-parametric method that can also be used to test differences between groups. MDS is used to calculate the coordinates of observations from dissimilarities and AOD is useful for finding group structure using the coordinates. In particular, AOD is mathematically associated with MANOVA if using the Euclidean distance when computing dissimilarities. In this paper, we study the between and within group structure by applying MDS and AOD to the grouped dissimilarities. In addition, we propose a new test statistic using the group structure for the permutation test. Finally, we investigate the relationship between AOD and MANOVA from dissimilarities based on the Euclidean distance.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.648-653
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• 2010

The non-metric multidimensional scaling (nMDS) is a method for analyzing the relation among objects by mapping them onto the Euclidean space. The nMDS is useful when it is difficult to use the concept of distance between pairs of objects due to non-metric dissimilarities between objects. The nMDS can be regarded as an optimization problem in which there are many local optima. Since the conventional nMDS algorithm utilizes the steepest descent method, it has a drawback in that the method can hardly find a better solution once it falls into a local optimum. To remedy this problem, in this paper, we applied the simulated annealing to the nMDS and proposed a new optimization algorithm which could search for a global optimum more effectively. We examined the algorithm using benchmarking problems and found that improvement rate of the proposed algorithm against the conventional algorithm ranged from 0.7% to 3.2%. In addition, the statistical hypothesis test also showed that the proposed algorithm outperformed the conventional one.

• Journal of the Korean Institute of Landscape Architecture
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• v.32 no.1
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• pp.47-56
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• 2004

Rapid economic development in Korea caused functions of city functions such as concentration of population, deterioration of the quality of living environment and traffic congestion. Korean cities have lost their identity becausr they are merged functionally and physically with neighboring cities, forming one mesa-city. Unified shape and disorganized streets of cities often cause confusion among foreigners and visitors. It is very difficult for them to find their image in strange cities. It is, however, important to correctly analyze the image and meaning of cities for understanding its identity. The purpose of this study is to develop a method to analyze the city image by focusing on some of the main cities in Korea. For this purpose, the adjective questionnaire and multi-dimension scaling (MDS) are applied to the analysis of city image. Image analysis graph by MDS can visually present the general and integrate images. The results of this study are summarized as follows: The important factors for interpretation of city image are historical and industrial character. Seoul, Taegu and Pusan have industrial and complex city images. Kongju has historical city image, while Changwon has a modern image. Chuncheon belongs to a soft and small image. Each city has an alternative solution against a negative image, according to the image analysis graph.