• Proceedings of the International Microelectronics And Packaging Society Conference
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• 2002.11a
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• pp.91-95
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• 2002

A very small size BPF is realized using LTCC Multilayer technology. A λ/4 resonator with shunt-to-ground loaded capacitor is used to shorten resonator length and achieve higher qualityfactor. Also this resonator enable BPF to improve out-of-band rejection. Coupling coefficients between coupled stripline resonators and external qualityfactor of a resonator are derived and apply to the filter design. The measured results show a good agreement with the simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1187-1193
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• 2014

This paper presents an effective motion estimation to improve the performance of the motion compensated temporal filtering (MCTF) which is a core part of the wavelet-based scalable video coding. The proposed scheme makes the motion vector field uniform by the modified median operation and the search strategies using adjacent motion vectors, in order to enhance the pixel connectivity which is significantly relevant to the performance of the MCTF. Moreover, the motion estimation with variable block sizes that reflects the features of frames is introduced for further correlation improvement of the motion vector field. Experimental results illustrate that the proposed method reduces the decomposed energy on the temporal high frequency subband frame up to 30.33% in terms of variance compared to the case of the full search with fixed block sizes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.359-365
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• 2011

This study aims at filtering ALS points into ground and non-ground effectively through labeling and window based algorithm by utilizing 2D adjacency based on scan line. Firstly, points adjacency is constructed through minimal search based on scan line. Connected component labeling algorithm is applied to classify raw ALS points into ground and non-ground by utilizing the adjacency structure. Then, some small objects are removed by morphology filtering, and isolated ground points are restored by IDW estimation. The experimental results shows that the method provides good filtering performance( about 97% accuracy) for diverse sites, and the overall processing takes less time than converting raw data into TIN or raster grid.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.113-120
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• 2009

Currently the verbal abuse in text message over on-line game is so serious. However we do not have any effective policy or technical tools yet. Till now in order to cope with this problem, the online game service providers have accumulated a set of forbidden words and applied this list on the textual word used in on-line game, which is called 'Swear filter'. But young on-line game players easily avoid this filtering method by coining another words which is not kept in the list. Especially Korean is very easy to make new variations of a vulgar word. In this paper, we propose one smart filtering algorithm to identify newly coined profanities. Important features of our method include the canonical form transformation of coined profanities, semi-global alignment between in the level of consonant and vowel units. For experiment, we have collected more than 1000 newly coined vulgar words in on-line gaming sites and tested these word against our methods. where our system have successfully filtered more than 90% of those newly coined vulgar words.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.877-885
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• 2011

A collaborative filtering(CF) is the most widely used technique in recommender system. However, CF has sparsity and scalability problems. These problems reduce the accuracy of recommendation and extensive studies have been made to solve these problems, In this paper, we proposed a method that uses a weight so as to solve these problems. After creating a user-item matrix, the proposed method analyzes information about users who prefer the item only by using data with a rating over 4 for enhancing the accuracy in the recommendation. The proposed method uses information about the genre of the item as well as analyzed user information as a weight during the calculation of similarity, and it calculates prediction by using only data for which the similarity is over a threshold and uses the data as the rating value of unrated data. It is possible simultaneously to reduce sparsity and to improve accuracy by calculating prediction through an analysis of the characteristics of an item. Also, it is possible to conduct a quick classification based on the analyzed information once a new item and a user are registered. The experiment result indicated that the proposed method has been more enhanced the accuracy, compared to item based, genre based methods.

• Journal of Korea Multimedia Society
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• v.11 no.10
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• pp.1338-1346
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• 2008

In this paper, we propose a new P2P-based music recommendation system. In comparison with previous system in client-server environment, the proposed system shows higher quality of music recommendation through real-time sharing of music preference information between peers. A collaborative filtering is implemented as a recommendation algorithm. As a user preference profile, we use the inherit KID music genre index contained in all legitimate music file instead of music feature vectors as in previous research so that the proposed system can mitigate the performance degradation and high computational load caused by feature inaccuracy and feature extraction. The performance of the proposed system is evaluated in various ways with real 16-weeks transaction data provided by Korean music portal, 5 company and it shows comparative quality of recommendation with only small amount of computational load.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.18-24
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• 2010

Mobile devices wide spread among users after the release of Apple's iPhone, especially in Korea. Mobile device has their own advantages in terms of weight, size, mobility and so on. But, on the contrary, mobile device has to provide more accurate and personalized information because of a small screen and a limited function of information retrieval. This paper presents a user"s preference element changeable recommender system by employing extended collaborative filtering as a technique to provide useful information in a mobile environment. Proposed system reflects user's similar groups by simultaneously considering users' information with preferences and demographic characteristics. Then we construct list of recommenders by user's choice. Finally, we show the implementation of a prototype based on iPhone.

• Journal of KIISE
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• v.43 no.8
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• pp.883-892
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• 2016

Spectrum-based fault localization (SFL) method assigns a suspicious ratio. The statement is strongly affected by a failed test case compared to a passed test case. A failed test case assigns a suspicious ratio while a passed test case reduces some parts of assigned suspicious ratio. In the absence of a failed test case, it is impossible to localize the fault. Thus, a failed test case is very important for fault localization. However, spectrum-based fault localization has difficulty in reflecting the unique characteristics of a failed test because a failed test case and a passed test case are input at the same time to calculate a suspicious ratio. This paper supplements for this limitation and suggests a test case grouping method for more accurate fault localization. In addition, this paper suggested a filtering method considering test efficiency and verified the effectiveness by applying 65 algorithms. In 90 % of whole methods, the accuracy was improved by 13% and the effectiveness was improved by 72% based on EXAM score.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.79-86
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• 2011

Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.10-18
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• 2008

The most critical element in the real-time operation of RFID application programs that are suitable for the mobile environment is the RFID middleware, made exclusively for mobile handsets, which processes collected data on a real-time basis and sends only the useful information to the application client. In this paper, we intend to design and implement a mobile RFID middleware system that supports the mobile handset environment for real-time based processing of the necessary data in the mobile environment. The proposed mobile RFID middleware system includes a mobile reader interface that collects the tag data, a mobile filtering engine that processes the tag data into more meaningful data that is sent to the application interface, and finally the mobile application interface that supports the m-SOAP application access protocol for interfacing with existing mobile applications. The filtering speed of the newly-developed middleware engine was found to be suitable for the characteristics of mobile handsets.