• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.283-292
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• 2003

One-dimensional time-series data have been studied in various database applications such as data mining and data warehousing. However, in the current complex business environment, multidimensional data sequences (MDS') become increasingly important in addition to one-dimensional time-series data. For example, a video stream can be modeled as an MDS in the multidimensional space with respect to color and texture attributes. In this paper, we propose the effective similarity measures on which the similar pattern retrieval is based. An MDS is partitioned into segments, each of which is represented by various geometric and semantic features. The similarity measures are defined on the basis of these segments. Using the measures, irrelevant segments are pruned from a database with respect to a given query. Both data sequences and query sequences are partitioned into segments, and the query processing is based upon the comparison of the features between data and query segments, instead of scanning all data elements of entire sequences.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2298-2309
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• 2000

This paper proposes the multidimensioa! nested attribute indexing techniques (MD- NAI) in object-oriented databases using a multidimensional index structure. Since most conventional indexing techniques for object oriented databases use a one-dimensional index stnlcture such as the B-tree, they do not often handle complex qUlTies involving both nested attributes and class hierarchies. We extend a tunable two dimensional class hierachy indexing technique(2D-CHI) for nested attributes. The 2D-CHI is an indexing scheme that deals with the problem of clustering ohjects in a two dimensional domain space that consists of a kev attribute dOI11'lin and a class idmtifier domain for a simple attribute in a class hierachy. In our extended scheme, we construct indexes using multidimensional file organizations that include one class identifier domain per class hierarchy on a path expression that defines the indexed nested attribute. This scheme efficiently suppoI1s queries that involve search conditions on the nested attribute represcnted by an extcnded path expression. An extended path expression is a one in which a class hierarchy can be substituted by an indivisual class or a subclass hierarchy in the class hierarchy.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.254-262
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• 2005

This paper presents a new sequential indexing method called segment-page indexing (SP-indexing) for multidimensional range queries. The design objectives of SP-indexing are twofold:(1) improving the range query performance of multidimensional indexing methods (MIMs) and (2) providing a compromise between optimal index clustering and the full index reorganization overhead. Although more than ten years of database research has resulted in a great variety of MIMs, most efforts have focused on data-level clustering and there has been less attempt to cluster indexes. As a result, most relevant index nodes are widely scattered on a disk and many random disk accesses are required during the search. SP-indexing avoids such scattering by storing the relevant nodes contiguously in a segment that contains a sequence of contiguous disk pages and improves performance by offering sequential access within a segment. Experimental results demonstrate that SP-indexing improves query performance up to several times compared with traditional MIMs using small disk pages with respect to total elapsed time and it reduces waste of disk bandwidth due to the use of simple large pages.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.37-48
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• 2010

In this paper, we analyze the shortcomings of the previous declustering methods, which are based on grid-like partitioning and a mapping function from a cell to a disk number, for high-dimensional space and propose a solution. The problems arise from the fact that the number of splitting is small(for the most part, binary-partitioning is sufficient), and the side length of a range query whose selectivity is small is quite large. To solve this problem, we propose a mathematical model to estimate the performance of a grid-like partitioning method. With the proposed estimation model, we can choose a good grid-like partitioning method among the possible schemes and this results in overall improvement in declustering performance. Several experimental results show that we can improve the performance of a previous declustering method up to 2.7 times.

• 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.

• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.927-934
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• 2003

Database query optimates the selectivety of a query to find the most efficient access plan. Multi-dimensional selectivity estimation technique is required for a query with multiple attributes because the attributes are not independent each other. Histogram is practically used in most commercial database products because it approximates data distributions with small overhead and small error rates. However, histogram is inadequate for a query with multiple attributes because it incurs high storage overhead and high error rates. In this paper, we propose a novel method for multi-dimentional selectivity estimation. Compressed information from a large number of small-sized histogram buckets is maintained using the discrete cosine transform. This enables low error rates and low storage overheads even in high dimensions. Extensive experimental results show adventages of the proposed approach.

• Journal of Korea Water Resources Association
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• v.39 no.1 s.162
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• pp.11-22
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• 2006

This study is that MD-FDA and the existing method were applied together the outlet project under the construction in the Gulpo River basin. The results of both of them mot the economic feasibility of the Project. But, MD-FDA evaluated the suitable damage according to situations; 1) without project, 2) after 20m outlet construction, 3) after 80m outlet construction. That is, MD-FDA could exactly evaluate the Annual Expected Flood Damage by considering the characteristics to the inundated area. If M-FDA may use in the flood control projects, the projects will be able to be taken into account all characteristics of the total damage area and performed by reasonable criteria.

• Journal of Korea Multimedia Society
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• v.10 no.9
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• pp.1093-1105
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• 2007

This paper presents a multidimensional type inheritance indexing technique (MD-TIX) for XML databases. We use a multidimensional file organization as the index structure. In conventional XML database indexing techniques using one-dimensional index structures, they do not efficiently handle complex queries involving both nested elements and type inheritance hierarchies. We extend a two-dimensional type hierarchy indexing technique(2D-THI) for indexing the nested elements of XML databases. 2D-THI is an indexing scheme that deals with the problem of clustering elements in a two-dimensional domain space consisting of the key value domain and the type identifier domain for indexing a simple element in a type hierarchy. In our extended scheme, we handle the clustering of the index entries in a multidimensional domain space consisting of a key value domain and multiple type identifier domains that include one type identifier domain per type hierarchy on a path expression. This scheme efficiently supports queries that involve search conditions on the nested element represented by an extended path expression. An extended path expression is a path expression in which every type hierarchy on a path can be substituted by an individual type or a subtype hierarchy.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.438-438
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• 2018

최근 여름철 강우로 인한 도시시설과 공공시설의 피해가 급증화되고 대형화 되면서 이에 대한 피해를 최소화하여 피해를 최대한 줄이는 객관적인 판단이 필요하다. 특히, 하천정비계획지구의 경우에는 치수사업의 타당성을 판단할 수 있는 경제성분석이 중요하다. 치수사업의 경제성분석 방법을 연구할 수 있는 방법으로는 다차원 홍수피해 산정방법((Multi-Dimension Flood Damage Assessment; MD-FDA)이 치수사업의 경제성 분석을 계량 평가하는 방법으로 주로 사용되고 있다. 다차원 홍수피해 산정방법은 홍수피해 유형과 토지이용을 고려한 침수피해액 산정이 가능한 경제성 분석 방법이다. 본 연구에서는 SG정비계획지구 13개소(축제 및 확폭지구 4개소, 보축 및 하도준설지구 9개소)에 대해 다차원 홍수피해 산정방법을 이용하여 치수경제성 분석을 실시하였다. 치수경제성 분석을 위해 해당지역의 주거지역, 농업지역, 산업지역의 대상자산을 분석하여 자산가치를 분석하고 빈도별 홍수량에 대응하는 침수심과 침수편입율을 추정하여 침수지역의 자산액을 조사하였다. 조사된 자료를 활용하여 사업 시행전후에 대한 직접피해액을 자산피해와 인명피해로 구분하여 치수경제성 대상지구의 홍수규모별 예상피해액을 산정하였다. 그리고 피해액을 근거로 하여 비용편익비(B/C)를 활용하여 최종적인 치수경제성 분석을 진행하였다. 분석결과, 대상지구 3개 지구에서 B/C가 1이상의 값을 가져 사업의 경제성이 높은 것으로 나타났다. 분석결과를 활용하여 B/C가 1이하인 계획지구에 대해서도 치수사업의 일관성 및 지역주민의 안정된 생활보장을 위해 지속적인 사업의 시행이 필요할 것으로 판단된다.

• Korean Journal of Social Welfare Studies
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• v.42 no.4
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• pp.5-34
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• 2011

There have been increasing incidents of natural and social disasters that claimed many lives and caused financial calamities worldwide, which call for an attention to mental health issues affecting disaster victims. This study reviewed the findings of the empirical research on the effects of disaster on the victims, the prevalence and determinants of the mental health problems. The disaster tends to disproportionately affect the socio-economically disadvantaged population and their mental health problems and recovery seemed to be heavily influenced by post-disaster experiences such as restoration of physical environment, prospect of economic recovery and resumption of normalcy in their lives, opportunities for participation in decision-making that affect their lives. Such findings suggest that the disaster mental health should shift from its traditional approach that focuses on short-term clinical interventions to alleviate acute mental distress for the victims to a public health approach that involve medical, social and economic interventions as well as community empowerment to prevent chronicity of the mental health problems and to improve the general quality of life of the individuals and the community adversely affected by the disaster. Implications for the social work research, policy making, education and practice were discussed.