• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.521-530
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• 2019

With a view to respond to urban climate change issues and improve the urban environment in a qualitative manner, the strategy of multi-dimensional greening of the traditional markets in the City of Seoul to secure the multi-dimensional green spaces can result in a significant effect in terms of landscaping, environment, and spatial aspect. The purpose of this study is to examine the elements of multi-dimensional greening for the multi-dimensional greening of buildings in order to enhance the greening function within urban phenomena and, with this, establish the criteria for success introduction of multi-dimensional greening and its qualitative expansion. For this, a total of 569 consumers of traditional markets have been interviewed, and the data from their questionnaires were analyzed through SPSS and AMOS software. The result of the analysis showed that the elements of the multi-dimensional greening of traditional markets, such as the economical, physical, functional, visual, and facility aspects all affected the consumer expectation in a positive manner. Also, depending on the gender of the customers of traditional markets, the ecological aspect among the elements of multi-dimensional greening had a significant difference. And, by the age, the functional, physical, and visual aspects of the elements of multi-dimensional greening showed a significant different. And, the expectation on the multidimensional greening of traditional markets also showed a statistically significant difference. By the level of education, there were significant differences in terms of the physical and visual aspects of the multi-dimensional greening elements. And, the level of expectation on the multidimensional greening also differed significantly.

• Journal of The Korean Digital Architecture Interior Association
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• v.5 no.1
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• pp.1-8
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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.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.247-253
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• 2017

Feature selection or variable selection is a data mining scheme for selecting highly relevant features with target concept from high dimensional data. It decreases dimensionality of data, and makes it easy to analyze clusters or classification. A feature selection scheme requires an evaluation function. Most of current evaluation functions are based on statistics or information theory, and they can evaluate only for single feature (one-dimensional data). However, features have interactions between them, and require evaluation function for multi-dimensional data for efficient feature selection. In this study, we propose modification of FSDD evaluation function for utilizing evaluation of multiple features using extended distance function. Original FSDD is just possible for single feature evaluation. Proposed approach may be expected to be applied on other single feature evaluation method.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.85-92
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• 2005

Recently, query processing techniques for the multi-dimensional data like images have been widely used to perform content-based retrieval of the data . Range query and Nearest neighbor query are widely used multi dimensional queries . This paper Proposes the efficient pruning strategies for k-nearest neighbor query in R-tree variants indexing structures. Pruning strategy is important for the multi-dimensional indexing query processing so that search space can be reduced. We analyzed the Pruning strategies and perform experiments to show overhead and the profit of the strategies. Finally, we propose best use of the strategies.

• International Journal of Automotive Technology
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• v.5 no.3
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• pp.165-172
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• 2004

Phenomenological models for direct injection diesel engine emissions including NO, soot, and HC were implemented into a full engine cycle simulation and validated with experimental data obtained from representative heavy-duty DI diesel engines. The cycle simulation developed earlier by Jung and Assanis (2001) features a quasi-dimensional, multi-zone, spray combustion model to account for transient spray evolution, fuel-air mixing, ignition and combustion. In this study, additional models for HC emissions were newly implemented and the models for NO, soot, and HC emissions were validated against experimental data. It is shown that the models can predict the emissions with reasonable accuracy. However, additional effort may be required to enhance the fidelity of models across a wide range of operating conditions and engine types.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.395-399
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• 2003

본 논문에서는 인문 사회과학 분야의 방대한 설문 데이터를 처리하기 위해 기존의 설문 항목들간의 평면적 관계에만 국한 되었던 연구에 대해 설문데이터 다차원 연관규칙 마이닝 시스템을 설계하고 데이터 간의 연관규칙을 탐사한다. 즉, 직관적으로 분류될 수 있는 기준에 따라 클러스터링을 실행하여 데이터를 분류한 후 각 클러스터로부터 다차원 연관 규칙을 탐사하는 시스템을 제안함으로써 보다 강력한 연관규칙을 탐사한다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1737-1745
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• 2000

In the last decade, considerable research effort has been studied ot multi-dimensional GIS and many spatiotemporal operations and query languages have been proposed. Many of them have focused on designing of operation, which process with data that is valid at current point in time. But, research that studied to updata operation that updates or inserts the past data is very rare. This paper designs an update operation and an insertion operation for integrity of past data of multi-dimensional GIS, and propose a new data model for efficient processing of the operations.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.313-316
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• 2011

The skyline of a multi-dimensional data set is a subset that consists of the data that are not dominated by other members of the set. Skyline computation can be very useful for decision making for multi-dimensional data set. However, in case that the skyline is very large, it may not be much useful for decision making. In this paper, we propose an algorithm for computing a part of the skyline considering location restrictions that the user provides, such as origin movement, degree ranges and/or distances from the origin. The algorithm eliminates noncandidate data rapidly, and returns in order the skyline points that satisfy the user's requests. We show that the algorithm is efficient by experiments.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1182-1188
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• 2014

Recently, the research on database outsourcing has been actively done with the popularity of cloud computing. However, because users' data may contain sensitive personal information, such as health, financial and location information, the data encryption methods have attracted much interest. Existing data encryption schemes process a query without decrypting the encrypted databases in order to support user privacy protection. On the other hand, to efficiently handle the large amount of data in cloud computing, it is necessary to study the distributed index structure. However, existing index structure and query processing algorithms have a limitation that they only consider single-column query processing. In this paper, we propose a grid-based multi column indexing scheme and an encrypted query processing algorithm. In order to support multi-column query processing, the multi-dimensional index keys are generated by using a space decomposition method, i.e. grid index. To support encrypted query processing over encrypted data, we adopt the Hilbert curve when generating a index key. Finally, we prove that the proposed scheme is more efficient than existing scheme for processing the exact and range query.

• 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.