• Journal of the Korea institute for structural maintenance and inspection
• /
• v.10 no.6
• /
• pp.197-204
• /
• 2006

Recently, in order to realization of construction and economical saving, various studies are progressing. Also, the study on RCS system which is consisted of reinforced concrete column and steel beam is progressing actively. Actually, however, resisting mechanism of panel zone is influenced by transverse beams when the stress transfers inner panel to outer panel but existing literature didn't reflect the effect of transverse beams. This paper is to analyze the test result of five inner beam-column joints specimen with a variable such as web, flange thickness of transverse beam and face bearing plate(FBP) for RCS systems were tested under cyclic loadings conforming to NEHRP recommendation to investigate the effect of transverse beams and the structural performance of beam-column joints. From the test result, it was shown that transverse beams are effective to enhance the shear strength and structural performance of beam-column joints.

• KIISE Transactions on Computing Practices
• /
• v.21 no.11
• /
• pp.706-712
• /
• 2015

These days, much information is provided as a list of summaries through mobile services. In this regard, users consume information in which they are interested by observing the list and not by expressing their interest explicitly or implicitly through rating content or clicking links. Therefore, to appropriately model a user's interest, it is necessary to detect latent interest content. In this study, we propose a method for reasoning latent interest of a user by analyzing mobile content consumption logs of the user. Specifically, since erroneous reasoning will drastically degrade service quality, a unanimity ensemble method is adopted to maximize precision. In this method, an item is determined as the subject of latent interest only when multiple classifiers considering various aspects of the log unanimously agree. Accurate reasoning of latent interest will contribute to enhancing the quality of personalized services such as interest-based recommendation systems.

• KIISE Transactions on Computing Practices
• /
• v.21 no.11
• /
• pp.733-738
• /
• 2015

User demographic information is necessary in order to improve the quality of personalized services such as recommendation systems. Mobile data, especially text data, is known to be effective for prediction of user demographic information. However, mobile text data has privacy issues so that its utilization is limited. In this regard, we introduce an on-device gender prediction framework utilizing mobile text data while minimizing the privacy issue. Discriminative word and emoticon sets of each gender are constructed from web documents written by authors of each gender. After gender prediction is performed by comparing discriminative word and emoticon sets with a user's mobile text data, an ensemble method that combines two prediction results draws a final result. From experiments conducted on real-world mobile text data, the proposed on-device framework shows promising results for gender prediction.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.10
• /
• pp.2533-2543
• /
• 1997

It is necessary to understand and apply the concept of Quality of Service(QoS) for the objective selection among the computer network equipment. Because ITU-T E.800 recommendation covers the service quality of provider's viewpoint and the satisfaction of user, it can be used to evaluate and select the product of computer network systems. This paper is concerned with the development of an evaluation model using QoS and software tool for selection of the most suitable LAN switch. We apply the Analytic Hierarchy Process(AHP) method of Saaty which has been in a multiple criteria framework for an effective group decision process to the selection of LAN switch. The sample data are collected and processed from a questionnaire of professionals in the network field. And we implement a prototype tool for the selection of LAN switch according to the suggested selection model and analyse the result. The result of our research is expected to be a useful tool for decision making to evaluate and select the LAN switch and also can be applied to the decision making of evaluation and selection related to the product of computer network with QoS.

• The Journal of Industrial Distribution & Business
• /
• v.10 no.4
• /
• pp.43-56
• /
• 2019

Purpose - The purpose of this study is to classify the quality factors of chicken restaurant customers with the service quality based on the SERVQUAL, the quality factors based on the selection attributes and service qualities of chicken restaurants used in the previous studies. Research design, data, and methodology - This survey was carried out on the students of Kangwon University in Samchuk City, Kangwon Province from November 20 - November 30, 2017, and a total of 260 questionnaires were distributed, with 222 collected. Of them, effective questionnaires applied in the final study were a total of 193 except 29 that couldn't be used. Results - The findings of this study are as follows: Firstly, chicken restaurants' quality factors were divided into seven categories like cleanliness, service encounter quality, product quality, aesthetics, overall interior, purchase quality, and convenience. Secondly, it showed that service encounter quality, purchase quality, and cleanliness had a positive impact on customer satisfaction, respectively. Thirdly, it showed that service encounter quality, purchase quality, and cleanliness had a positive impact on trust, respectively. Fourthly, it showed that customer satisfaction had a positive impact on behavioral intention. Additionally, it suggested that customer satisfaction of chicken restaurant consumers had a positive impact on behavioral intention and thereby, higher customer satisfaction leads to higher levels of reuse and recommendation intention. Lastly, after checking the effect relations of trust between customer satisfaction about chicken restaurant and behavioral intention, it was analyzed that customer satisfaction has a positive impact on trust and trust has a positive impact on behavioral intention. On the other hand, it showed that trust have a partially mediating effect in the relations between customer satisfaction and behavioral intention. But, it showed that product quality, aesthetics, overall interior, purchase quality, and convenience did not have a positive impact on customer satisfaction. Conclusions - Chicken restaurant consumers put more priority on friendly and good services of chicken restaurant staff in service encounter and delivery order, rather than on reasonable price and discount systems. Thereby, chicken restaurant marketers need to take factors like service encounter quality, cleanliness into more consideration.

• Journal of Intelligence and Information Systems
• /
• v.13 no.4
• /
• pp.65-78
• /
• 2007

This paper proposes a new method of weighted template matching for machine-printed numeral recognition. The proposed weighted template matching, which emphasizes the feature of a pattern using adaptive Hamming distance on local feature areas, improves the recognition rate while template matching processes an input image as one global feature. Template matching is vulnerable to random noises that generate ragged outlines of a pattern when it is binarized. This paper offers a method of chain code trimming in order to remove ragged outlines. The method corrects specific chain codes within the chain codes of the inner and the outer contour of a pattern. The experiment compares confusion matrices of both the template matching and the proposed weighted template matching with chain code trimming. The result shows that the proposed method improves fairly the recognition rate of the machine-printed numerals.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.10
• /
• pp.1010-1014
• /
• 2010

Article-related product recommender system is an emerging e-commerce service which recommends items based on association in contexts between items and articles. Current services recommend based on the similarity between tags of articles and items, which is deficient not only due to the high cost in manual tagging but also low accuracies in recommendation. As a component of novel article-related item recommender system, we propose a new method for tagging item images based on pre-defined categories. We suggest a hypernetwork-based algorithm for learning association between images, which is represented by visual words, and categories of products. Learned hypernetwork are used to assign multiple tags to unlabeled item images. We show the ability of our method with a product set of real-world online shopping-mall including 1,251 product images with 10 categories. Experimental results not only show that the proposed method has competitive tagging performance compared with other classifiers but also present that the proposed multi-tagging method based on hypernetworks improves the accuracy of tagging.

• Publications of The Korean Astronomical Society
• /
• v.18 no.1
• /
• pp.97-110
• /
• 2003

WRC-03 was held between 9 June and 4 July 2003 in Geneva, Switzerland. Over 2,200 delegates from 138 ITU Member States attended the Conference. The delegates considered some 2,500 proposals, and over 900 numbered documents related to 50 agenda items. The final output of the Conference consists of 527 pages of new and revised text of the Radio Regulations. This paper provides some details about the outcome of the radio astronomy related issues at the WRC-03 Conference. It is divided into two part: a) Agenda item1.8.2 and b) Agenda item 1.32, related to radio astronomy. Relevant extracts from the Final Acts of WRC-03 are given in the Appendix. Agenda item 1.8.2 was one of the most controversial Agenda Items at WRC-03. Studies were carried out within ITU-R TG 1/7 for the last three years; the results of these studies are summarized in Recommendation ITU-R SM.1633. The Conference adopted a new footnote (5.347A), that calls for the application of Resolution 739 (WRC-03) in the 1452-1492 MHz, 1525-1559 MHz, 1613.8-1626.5 MHz, 2655-2670 MHz, 2670-2690 MHz and 21.4-22.0 GHz bands. Agenda item 1.32 is to consider technical and reglatory provisions concerning the band 37.5-43.5 GHz, in accordance with Resolutions 128 (Rev.WRC-2000) and 84 (WRC-2000). WRC-03 reviewed and adjusted the New footnotes 5.551H and 5.551I cover the protection of radio astronomy observations in the 42.5-43.5 GHz band from unwanted emissions by non-geostationary (5.551H) and geostationary (5.551I) FSS and BSS systems, respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.5
• /
• pp.221-226
• /
• 2021

Collaborative filtering based recommender systems recommend user-preferrable items based on rating history and are essential function for the current various commercial purposes. In order to determine items to recommend, prediction of preference score for unrated items is estimated based on similar rating history. Previous studies usually employ two methods individually, i.e., similar user based or similar item based ones. These methods have drawbacks of degrading prediction accuracy in case of sparse user ratings data or when having difficulty with finding similar users or items. This study suggests a new rating prediction method by integrating the two previous methods. The proposed method has the advantage of consulting more similar ratings, thus improving the recommendation quality. The experimental results reveal that our method significantly improve the performance of previous methods, in terms of prediction accuracy, relevance level of recommended items, and that of recommended item ranks with a sparse dataset. With a rather dense dataset, it outperforms the previous methods in terms of prediction accuracy and shows comparable results in other metrics.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.5
• /
• pp.47-53
• /
• 2021

Sparse ratings data hinder reliable similarity computation between users, which degrades the performance of memory-based collaborative filtering techniques for recommender systems. Many works in the literature have been developed for solving this data sparsity problem, where the most simple and representative ones are the methods of utilizing Jaccard index. This index reflects the number of commonly rated items between two users and is mostly integrated into traditional similarity measures to compute similarity more accurately between the users. However, such integration is very straightforward with no consideration of the degree of data sparsity. This study suggests a novel idea of applying different similarity measures depending on the numeric value of Jaccard index between two users. Performance experiments are conducted to obtain optimal values of the parameters used by the proposed method and evaluate it in comparison with other relevant methods. As a result, the proposed demonstrates the best and comparable performance in prediction and recommendation accuracies.