• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.4
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• pp.63-71
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• 1989

Four series of reinforced concrete beams were tested to determine their shear cracking strengths and ultimate shear capacities. All beams were singly reinforced without shear reinforcement. The concrete strength was the prime variable which was varied from 247 to $708kg/cm^2$(8500 to 10000 psi). Within each series the shear span-to-depth ratio was varied from 2 to 5, while concrete strength was held constant. Test results indicate that the effect of concrete strength on shear capacities is varied as the shear span-to-depth ratio is changed. Furthermore, the current shear design provisions do not provide a consistency with respect to estimating shear capacities of reinforced concrete beams. By introducing the shear failure mode index, a new equation is proposed to predict ultimate shear strengths of reinforced concrete beams without web reinforcement.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.15-28
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• 2016

As the industry of Mobile Internet has been gradually developed, the major device for accessing the web is predicted to shift from PC to Mobile devices in the near future. This drastic increase of demand in Mobile devices has drawn a more convenient standard of living by transcending time and space in our lives, however, it triggered various side effects such as a digital divide. This study was conducted to analyze how people utilize the contents via Mobile devices and their active attitude toward Mobile Internet by dividing individual characteristics into generations, education level and income level, and also identify whether Mobile contents utilization has an effect on the active attitude. The research results could be used for establishing a policy to narrow the gap in Mobile contents use and active attitude by individual characteristics.

• Journal of the Korean Society for Library and Information Science
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• v.35 no.4
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• pp.97-122
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• 2001

This empirical study investigated the effect of choice of record field(s) upon which to search on retrieval performance for a large operational bibliographic database. The query terms used in the study were identified algorithmically from each target set in four different ways: (1) controlled terms derived from index term frequency weights, (2) uncontrolled terms derived from index term frequency weights. (3) controlled terms derived from inverse document frequency weights, and (4) uncontrolled terms based on universe document frequency weights. Su potable choices of record field were recognised. Using INSPEC terminology, these were the fields: (1) Abstract. (2) 'Anywhere'(i.e., ail fields). (3) Descriptors. (4) Identifiers, (5) 'Subject'(i.e., 'Descriptors' plus Identifiers'). and (6) Title. The study was undertaken in an operational web-based IR environment using the INSPEC bibliographic database. The retrieval performances were evaluated using D measure (bivariate in Recall and Precision). The main findings were that: (1) there exist significant differences in search performance arising from choice of field, using 'mean performance measure' as the criterion statistic; (2) the rankings of field-choices for each of these performance measures is sensitive to the choice of query : and (3) the optimal choice of field for the D-measure is Title.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.157-164
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• 2006

Since XML is emerging as the de facto standard for exchanging and representation of data on the web, the amount of XML data has rapidly increased. Thus, the need for effective store and retrieval of U data has arisen. Since the existing techniques such as XRel which is an XML storage and management technique using RDBMS simply record the existing all label paths, diverse classes of label path expressions could not be efficiently supported. In this paper, we present a technique which supports storage and retrieval for XML data using RDBMS efficiently compared with the existing approaches. Since the proposed technique keeps the XML path index on the relational database and replace label paths with path identifiers, diverse XML queries can be evaluated compared with existing approaches. Also, the proposed technique does not require the modification of the relational database engine and consumes the disk space less. Our experimental result demonstrates the better query performance compared with existing techniques.

• Journal of Digital Contents Society
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• v.10 no.1
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• pp.1-10
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• 2009

One important issue to generalize the ubiquitous paradigm is the development of user-centralized and intelligent ubiquitous computing systems. Sharing knowledge and correct communication between users and devices are needed to be aware of continuous changed context information and infer services for which users are suited. The goal of this paper is to describe and manage effectively the meaning of services or data which each device offers for interaction between users and devices based on semantic relationships and reasoning. In this paper, we represent semantic data using OWL and design a ubiquitous based intelligent system. We propose some index structures and strategies to process queries classified by each subsystem and adopt labeling schemes to identify classes and resources in the semantic data. We can find devices which satisfies various user's requests exactly and quickly using the proposed strategies.

• The Journal of Korean Association of Computer Education
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• v.15 no.2
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• pp.75-81
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• 2012

As the number of web users is increasing, the leakage of personal information is increasing. If some personal information is leaked, the victim can suffer from material damage or mental damage at the same time. Most of the leakages are result from the people who works for the personal information by accident or design. Hence, the Ministry of Public Administration and Security proposeed the measuring index and enumerates the details. The index is used in a system to check protection of a personal information. However, because this system is used to evaluate after the leakage, it cannot be used to construct some security system or programming a security system. To solve this problem, it needs to express the diversity of items and be able to count what assessors want to count. Thus, a summary sheet which displays the result of the tool will be presented in a radial form graph. Details will be presented as a bar graph. Therefore, it will be proposed that the tool can grasp the weak point and propose the direction of security.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.2
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• pp.109-132
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• 2012

This study examines the social network of scholars in the field of communication by using author cocitation data. A matrix containing the number of cocited documents between pairs of authors is created for social network analysis of scholars who are on the editorial board of Journal of Communication, and the networked map of the scholars is used to visualize the knowledge structure of the field by identifying groups of authors who are more central than others. In addition, the study compares the previous analysis performed in 2008 and the current analysis on the editorial board of the journal, which increased from 146 to 254 scholars in numbers. Author cocitation data was collected using Social Science Citation Index (SSCI) through the Web of Science database, and UCInet was used to create and visualize the author cocitation network and to analyze the correlation between the cocitation network and the factors that may have affected the structure of the cocitation network.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.845-850
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• 2009

Use of XML data has been increased with growth of Web 2.0 environment. XML is recognized its advantages by using based technology of RSS or ATOM for transferring information from blogs and news feed. Bitmap clustering is a method to keep index in main memory based on Relational DBMS, and which performed better than the other XML indexing methods during the evaluation. Existing method generates too many clusters, and it causes deterioration of result of searching quality. This paper proposes k-Bitmap clustering method that can generate user defined k clusters to solve above-mentioned problem. The proposed method also keeps additional inverted index for searching excluded terms from representative bits of k-Bitmap. We performed evaluation and the result shows that the users can control the number of clusters. Also our method has high recall value in single term search, and it guarantees the searching result includes all related documents for its query with keeping two indices.

• Journal of Digital Convergence
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• v.12 no.10
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• pp.243-252
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• 2014

Many researches about the effect on politics, economics and Sociocultural phenomenon using the social media are in progress. Authors utilized NAVER Trend most famous web browsing service in korea, NAVER Blog social media, NAVER Cafe service and Open Data(API) and also used temperature, humidity index data of Korea Meteorological Administration. This study analyzed a change of the public's emotion in korea using Cluster analysis of vocabulary of taste among its of feelings and senses. K-means clustering was followed by decision of the number of groups which was used Chi-square goodness of fit test and ward analysis. Eight groups was made and it represented sensitive vocabulary. By Discriminant analysis, eight groups decided by Cluster analysis has 98.9% accuracy. The change of the public's emotion has capability to predict people's activity so they can share sensibility and a bond of sympathy developed between them.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.351-361
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• 2003

The previous studies to extract features for document through word association have the problems of updating profiles periodically, dealing with noun phrases, and calculating the probability for indices. We propose more effective feature extraction method which is using association word mining. The association word mining method, by using Apriori algorithm, represents a feature for document as not single words but association-word-vectors. Association words extracted from document by Apriori algorithm depend on confidence, support, and the number of composed words. This paper proposes an effective method to determine confidence, support, and the number of words composing association words. Since the feature extraction method using association word mining does not use the profile, it need not update the profile, and automatically generates noun phrase by using confidence and support at Apriori algorithm without calculating the probability for index. We apply the proposed method to document classification using Naive Bayes classifier, and compare it with methods of information gain and TFㆍIDF. Besides, we compare the method proposed in this paper with document classification methods using index association and word association based on the model of probability, respectively.