• Journal of KIISE:Databases
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• v.28 no.3
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• pp.344-356
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• 2001

This paper deals with the subsequence searching problem under time-warping in sequence databases. Our work is motivated by the observation that subsequence searches slow down quadratically as the average length of data sequences increases. To resolve this problem, the Segment-Based Approach for Subsequence Searches (SBSS) is proposed. The SBASS divides data and query sequences into a series of segments, and retrieves all data subsequences that satisfy the two conditions: (1) the number of segments is the same as the number of segments in a query sequence, and (2) the distance of every segment pair is less than or equal to a tolerance. Our segmentation scheme allows segments to have different lengths; thus we employ the time warping distance as a similarity measure for each segment pair. For efficient retrieval of similar subsequences, we extract feature vectors from all data segments exploiting their monotonically changing properties, and build a spatial index using feature vectors. Using this index, queries are processed with the four steps: (1) R-tree filtering, (2) feature filtering, (3) successor filtering, and (4) post-processing. The effectiveness of our approach is verified through extensive experiments.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.3-14
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• 2023

Recently, the effect of using social media on psychological well-being has been highlighted. However, studies exploring factors that may predict the quality of social media relationships are relatively rare. The present study investigated whether social media activity and psychological states, such as loneliness and depression, can predict the quality of social media relationships during the COVID-19 quarantine period using a machine learning technique. Ninety-five participants completed a self-report survey on loneliness, Instagram activity, quality of social media relationships, and depression at different time points (during the self-isolation and after the release of self-isolation). Similarity analyses, including multidimensional scaling (MDS), representational similarity analysis (RSA), and classification analyses, were conducted separately at each point in time. The results of MDS revealed that time spent on social media and depression were distinguished from others in the first dimension, and loneliness and passive use were distinguished from others in the second dimension. We divided the data into two groups based on the quality of social media relationships (high and low), and we conducted RSA on each group. Findings indicated an interaction between the quality of the social media relationships and the situation. Specifically, the effect of self-isolation on the high-quality social media relationship group is more pronounced than that on the low-quality group. The classification results also revealed that the predictors of social media relationships depend on whether or not they are isolated. Overall, the results of this study imply that social media relationship could be well predicted when people are not in isolated situations.

• The Journal of Information Technology
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• v.1 no.2
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• pp.55-63
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• 1998

본 논문은 웹 상에서 하이퍼텍스트 문서의 정보 검색에 있어서 검색에 요구되는 질의어에 따른 검색 결과가 주제에 따른 관련성을 측정하며, 하이퍼텍스트 문서가 링크되는 문서 상호간의 유사성에 대하여 정량화를 시도함으로써 검색 엔진의 성능분석을 제시한다.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.5
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• pp.419-433
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• 2004

As XML becomes a standard for data representation, integration, and exchange on the Web, several XML query languages have been proposed. World Wide Web Consortium(W3C) has proposed XQuery as a standard for the XML query language. Like SQL, XQuery allows nested queries. Thus, normalization rules have been proposed to transform nested XQuery queries to semantically equivalent ones that could be executed more efficiently. However, previous normalization rules are applicable only to restricted forms of nested XQuery queries. Specifically, they can not handle FLWR expressions having nested expressions in the where clause. In this paper, we propose normalization rules for XQuery queries by extending those for SQL queries. Our proposed rules can handle FLWR expressions haying nested expressions in every clause. The major contributions of this paper are as follows. First, we classily nesting types of XQuery queries according to the existence of correlation and aggregation. We then propose normalization rules for each nesting type. Second, we propose detailed algorithms that apply the normalization rules to nested XQuery queries.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.20-27
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• 2003

In this paper, we implemented a content-based image retrieval system that user can choose a wanted query region of object and retrieve similar object from image database. Query image is induced to wavelet transformation after divided into hue components and gray components that hue features is extracted through color autocorrelogram and dispersion in hue components. Texture feature is extracted through autocorrelogram and GLCM in gray components also. Using features of two components, retrieval is processed to compare each similarity with database image. In here, weight value is applied to each similarity value. We make up for each defect by deriving features from two components beside one that elevations of recall and precision are verified in experiment results. Moreover, retrieval efficiency is improved by weight value. And various features of database images are indexed automatically in feature library that make possible to rapid image retrieval.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.3
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• pp.171-180
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• 2003

A content-based image retrieval(CBIR) system builds the image database using low-level features such as color, shape and texture and provides similar images that user wants to retrieve when the retrieval request occurs. What the user is interest in is a response time in consideration of the building time to build the index database and the response time to obtain the retrieval results from the query image. In a content-based image retrieval system, the similarity computing time comparing a query with images in database takes the most time in whole response time. In this paper, we propose the two-phase search method with the clustering technique of feature vector in order to minimize the similarity computing time. Experimental results show that this two-phase search method is 2-times faster than the conventional full-search method using original features of ail images in image database, while maintaining the same retrieval relevance as the conventional full-search method. And the proposed method is more effective as the number of images increases.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.636-646
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• 2015

In information society, the need to detect document duplication and plagiarism is increasing. Many studies have progressed to meet such need, but there are limitations in increasing document duplication detection quality due to technological problem of natural language processing. Recently, some studies tried to increase the quality by applying syntatic-semantic analysis technique. But, the studies have the problem comparing syntactic-semantic trees. This paper develops a syntactic-semantic tree comparator, designs and implements a discriminator of similar documents using the comparator. To evaluate the system, we analyze the correlation between human discrimination and system discrimination with the comparator. This analysis shows that the proposed discrimination has good performance. We need to define the document type and improve the processing technique appropriate for each type.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1599-1607
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• 2015

Recently, researches have been developing efficient techniques for accessing, querying, and managing XML documents which are frequently used in the Internet. In this paper, we propose a parent-child matrix to cluster XML documents efficiently. A parent-child matrix analyzes both the content and structural features of an XML document. Each cell of a parent-child matrix has either the value of a node in an XML tree or the value of a child node, where a parent-child relationship exists in the XML tree. Then, the similarity between two XML documents can be measured by the similarity between two corresponding parent-child matrices. The experiment shows that our proposed method has good performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.348-351
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• 2009

유비쿼터스 사회를 실현하는 핵심기술인 u-GIS 공간정보 기술은 데이터 스트림 처리 시스템(Data Stream Management System)과 지리정보 시스템(Geography Information System)이 결합된 플랫폼인 u-GIS DSMS를 요구한다. u-GIS DSMS는 GeoSeonsor에서 수집되는 센서 테이터와 GIS의 공간정보 데이터를 결합하여 처리하는 공간영역질의가 다수 요구된다. 이런 공간영역질의들은 특정 지역에 밀집하게 등록되는 경향이 있으며, 유사한 프리디킷을 가질 가능성이 높다. 이러한 특징은 공간영역질의가 특정 지역에 밀집되면 다수의 비슷한 연산들이 반복적으로 처리하기 때문에 시스템 성능이 저하 될 것이다. 이를 해결하기 위해 영역질의 색인기법 연구가 활발히 진행되고 있다. 그러나 기존의 VCR-Index와 CQI-Index 기법은 질의영역을 셀 구조나 가상구조로 분할하여 처리하기 때문에 자원 및 연산을 공유 할 수 없어 질의 처리 속도가 현저히 저하되기 때문에 대량의 공간영역질의 처리에는 부적합하다. 그래서 본 논문에서는 공간영역질의의 효율적인 연산 공유를 위한 질의영역 밀집도 기반의 그룹화 기법을 제안한다. 이 기법은 질의영역의 밀집도를 이용하여 공간영역질의들을 그룹화 후 색인을 구성한다. 색인된 영역들의 데이터는 단일 큐로 구성 후 질의들의 프리디킷을 분석하여 자원 및 연산 공유기법을 통해 기존의 기법보다 처리 속도 향상 및 메모리 사용을 감소시켰다.

• Journal of Aquaculture
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• v.13 no.3
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• pp.187-191
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• 2000

The effects of osmolality on the sperm motility in black seabream (Acanthopagrus schlegeli) were studied. Sperm motility of black seabream was suppressed when the osmolality was equal to the seminal fluid. But sperm became motile when the osmolality increased in electrolyte solution (NaCl, KCl, $CaCl_2$, $MgCl_2$) and non-electrolyte solution (mannitol, glucose, fructose, sucrose). The changes of sperm motility index (SMI) by osmolality of diluents described a parabola. In all of the diluents, SMI was the highest at ca. 1,000 mOsm/kg, which is similar to the osmolality of seawater. Sperm motility was induced by osmolality of diluents, but exposure to hypotonic or hypertonic diluents was harmful to the sperm.