• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.7C
• /
• pp.619-626
• /
• 2012

With the service suggesting additional extended or related query, search engines aim to provide their users more convenience. The extended or related query suggestion service based on popularity, or by how many people have searched on web using the query, has limitations to elevate users' satisfaction, because each user's preference and interests differ. This paper will demonstrate the design and realization of the system that suggests extended query appropriate for users' demands, and also an improvement in the computing process between entering the first search word and the subsequent extension to the related themes. According to the evaluation the proposed system suggested 41% more extended or related query than when searching on Google, and 48% more than on Yahoo. Also by improving the shortcomings of the extended or related query system based on general popularity rather than each user's preference, the new system enhanced users' convenience further.

• The Journal of the Korea Contents Association
• /
• v.18 no.1
• /
• pp.64-75
• /
• 2018

With the development of location-aware technologies and the activation of smart phones, location based social networks(LBSN) have been activated to allow people to easily share their location. In particular, studies on recommending the location of user interests by using the user check-in function in LBSN have been actively conducted. In this paper, we propose a location recommendation scheme considering time and user activities in LBSN. The proposed scheme considers user preference changes over time, local experts, and user interest in rare places. In other words, it uses the check-in history over time and distinguishes the user activity area to identify local experts. It also considers a rare place to give a weight to the user preferred place. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.1
• /
• pp.77-82
• /
• 2015

Recently, multi-user massive MIMO (MU-Massive MIMO) network has attracted a lot of attention as a technology to accommodate explosively increasing mobile data traffic. However, the MU-Massive MIMO network causes a tremendous hardware complexity in a base station and computational complexity to select optimal set of users. In this paper, we thus propose a simple algorithm for selecting antennas and users while reducing the hardware and computational complexities simultaneously. The proposed scheme has a computational complexity of $O((N-S_a+1){\times}min(S_a,K))$, which is significantly reduced compared to the complexity of optimal scheme based on Brute-Force searching, $$O\left({_N}C_S_a\sum_{i=1}^{min(S_a,K)}_KC_i\right)$$, where N, $S_a$, and K denote the number of total transmit antennas, the number of selected antennas, and the number of all users, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.316-318
• /
• 2019

Recently, healthy life has become an issue in an aging society, and the number of people who have been interested in continuous health care for better life is increasing. In this paper, we implemented a personalized recommendation systm to provide convenient healthcare management for user. The PHR (Personal Health Record) of user could be stored in the server along with health related information such as lifestyle, disease, and physical condition. The users could be classified into similar clusters according to the PHR profile in order to provide healthcare contents to the users who had similar PHR profile. K-Means clustering was applied to generate clusters based on PHR profile and ACDT(Ant Colony Decision Tree) algorithm was used to provide personalised recommendation of health information stored in knowledge base. The app system developed in this paper is useful for users to perform healthcare themselves by providing information on serious diseases and lifestyle habits to be improved according to the clusters classified by PHR profile.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.17 no.2
• /
• pp.139-144
• /
• 2007

Due to the increasing use of Internet and spread of ubiquitous environment the security of private information became an important issue. For this reason, many suggestions have been made in order to protect the privacy of users. In the study of authentication system using a smart card which is one of the methods for protecting private information, the main idea is to offer user anonymity. In 2004, Das et al. suggested an authentication system that guarantees anonymity by using a dynamic ID for the first time. However, this scheme couldn't guarantee complete anonymity as the identity of the user became revealed at log-in phase. In 2005, Chien at al. suggested a authentication system that guarantees anonymity, but this was only safe to the outsider(attacker). In this paper, we propose a scheme that enables the mutual authentication between the user and the sewer by using a smart card. For the protection of the user privacy, we suggest an efficient user authentication system that guarantees perfect anonymity to both the outsider and remote server.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.9
• /
• pp.113-127
• /
• 2012

Face detection methods using image processing have been proposed in many different ways. Generally, the most widely used method for face detection is an Adaboost that is proposed by Viola and Jones. This method uses Haar-like feature for image learning, and the detection performance depends on the learned images. It is well performed to detect face images within a certain distance range, but if the image is far away from the camera, face images become so small that may not detect them with the pre-learned Haar-like feature of the face image. In this paper, we propose the far distance face detection method that combine the Aadaboost of Viola-Jones with a saliency map and user's attention information. Saliency Map is used to select the candidate face images in the input image, face images are finally detected among the candidated regions using the Adaboost with Haar-like feature learned in advance. And the user's eye-tracking information is used to select the interest regions. When a subject is so far away from the camera that it is difficult to detect the face image, we expand the small eye gaze spot region using linear interpolation method and reuse that as input image and can increase the face image detection performance. We confirmed the proposed model has better results than the conventional Adaboost in terms of face image detection performance and computational time.

• The Journal of the Korea Contents Association
• /
• v.9 no.10
• /
• pp.110-121
• /
• 2009

In this paper, we propose the new method that offer detailed-information through relax the system memory limitation about 3D model to user. That method based on making LOD(Level of Detail) model from huge 3D data of structure cultural assets. In our method as transformed AOSP algorithm, first of all it create the hierarchical structure space about 3D data, and create the LOD model by surface simplification. Then it extract the ROI(Region of Interest) of user in simplified LOD model, and then do rendering by original model and same surface detailed-information after process the local detailed in extracted region. To evaluate the proposed method, we have some experiment by using the precise 3D scan data of structure cultural assets. Our method can offer the detailed-information same as exist method, and moreover 45% reduced consumption of memory experimentally by forming mesh structure same as ROI of simplified LOD model. So we can check the huge structure cultural assets particularly in general computer environment.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.6
• /
• pp.25-31
• /
• 2008

The web has been evolving as an indispensable part of our lives since Berners Lee introduced the first web sever and browser in 1990. From the web end user's point of view, the response time is a matter of concern. Moreover the throughput is an important factor to consider for the system manager's point as well. It's not easy to estimate the performance of a web application because it depends on various elements comprising the whole operational environment of the Internet from networking, client and server computing powers, DBMS and OS capabilities, to application itself. This paper suggests a coarse grained simulation model for web application performance estimation based on the data measured by Buch and Pentkowski [1] and the analytical model proposed by Gunther [2]. The result of the simulation model almost coincides with the measured data and estimates the performance of a new environment.

• Journal of KIISE:Databases
• /
• v.33 no.4
• /
• pp.423-436
• /
• 2006

In recent years, publish-subscribe (pub-sub) systems based on XML document filtering have received much attention. In a typical pub-sub system, subscribing users specify their interest in profiles expressed in the XPath language, and each new content is matched against the user profiles so that the content is delivered only to the interested subscribers. As the number of subscribed users and their profiles can grow very large, the scalability of the system is critical to the success of pub-sub services. In this paper, we propose a novel scalable filtering system called FiST(Filtering by Sequencing Twigs) that transforms twig patterns expressed in XPath and XML documents into sequences using Prufer's method. As a consequence, instead of matching linear paths of twig patterns individually and merging the matches during post-processing, FiST performs holistic matching of twig patterns with incoming documents. FiST organizes the sequences into a dynamic hash based index for efficient filtering. We demonstrate that our holistic matching approach yields lower filtering cost and good scalability under various situations.

• Proceedings of the Korea Society of Information Technology Applications Conference
• /
• 2006.06a
• /
• pp.159-181
• /
• 2006

본 연구에서는 청주와 그 인근 지역에서 정보시스템을 개발하거나 운영하고 있는 업체의 IS 실무자들에게 (1) IS 실무자의 업무 수행 성과, (2) 소프트웨서 및 IT 전문기술수준, (3) IS 지식 및 능력 수준, 그리고 (5) 재교육 수요에 대해서 설문 조사하였다. 본 연구의 조사 대상자들은 주로 Sl(system integration) 업체에 종사하는 IT(information technology) 실무자들과 e-Business를 수행하는 일반 기업에서 전산 업무를 담당하고 있는 실무자들이며, 구체적으로는 전산시스템 운영자, 시스템/데이터베이스 분석/설계자, 어플리케이션/웹 프로그래머, 최종사용자 지원 담당자, e-Business를 위한 IT 지원 인력 등이다. 조사 결과는 다음과 같다. 충북 지역에서 IS 실무자들은 자신들의 업무를 성공적으로 수행하기 위한 지식 및 기술의 다양한 영역에서 광범위하게 지식 및 기술의 결핍을 느끼고 있으며, 자신의 업무 성과가 전반적으로 좋지 않다고 판단하고 있고, 업무 관련 지식 및 기술에 대한 재교육의 필요성을 강하게 느끼고 있다. 또한, 충북 지역의 IS 실무자들은 주된 활동이나 업무가 시스템 개발과 유지보수, 최종 사용자 지원 등의 활동이며, 이에 대한 최신의 기술과 고객 중심의 시각화된 도구(GUI)를 제공하는데 많은 시간을 투자하며, 기존의 반복적인 개발 업무에서 점차 경력이 쌓임에 따라 고객 중심적인 새로운 시스템 개발을 위한 기획과 관리에 많은 관심을 기울이고 있으나, 조직 운영 및 의사결정 등과 같은 기술/지식들에는 낮은 관심을 보였다. IT전문 기술들 중 IS 실무자들이 필요로 하고 보유해야 한다고 응답한 기술들은 대다수가 웹 개발에 관련된 기술이며, IS 실무자들은 대규모 프로젝트의 수행에 필요한 공동 작업 수행 능력의 제고와 그를 위한 재교육에 높은 관심을 나타내었다. 본 조사는 충북의 IS 실무자들을 위한 대학 교육과 재교육을 포함하는 최적의 평생 교육계획 수립을 위한 기초적이고 필수적인 정보를 제공할 것으로 기대된다.