• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.71-79
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• 2007

Recent advances in the internet infrastructure have resulted in a large number of huge Web sites and portals worldwide. These Web sites are being visited by various types of users in many different ways. Among all the web page access sequences from different users, some of them occur so frequently that may need an attention from those who are interested. We call them frequent access patterns and access sequences that can be frequent the candidate patterns. Since these candidate patterns play an important role in the incremental Web mining, it is important to efficiently generate, add, delete, and search for them. This thesis presents a novel tree structure that can efficiently store the candidate patterns and a related set of algorithms for generating the tree structure, adding new patterns, deleting unnecessary patterns, and searching for the needed ones. The proposed tree structure has a kind of the 3 dimensional link structure and its nodes are layered.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.12
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• pp.1079-1088
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• 2015

Parallelism and performance enhancement of calculating view factors in KSDS developed by KARI is introduced in this paper. View factor is an essential parameters of radiation thermal analysis for a spacecraft, and the amount of computation of them is not negligible. Especially, independent integration of view factors at each position of the orbit because the relative displace between solar panel and main body of a satellite varies with the position on the orbit. This paper introduces a range of parallelism of computing view factor and their performance, detection of obstructions by spatial search algorithm based on KD-Tree, and the reduction of the calculation of view factors of a satellite with relative motion between solar panel and main body, called updating fractional view factor matrix, for satellite thermal analysis.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.859-872
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• 2004

With the rapid advance of computer and communication techonology, the recent trend of education environment is edveloping in the ubiquitous learning (u-learning) direction that learners select and organize the contents, time and order of learning by themselves. Since the amount of education information through the internet is increasing rapidly and it is managed in document in an effective way is necessary. The document clustering is integrated documents to subject by classifying a set of documents through their similarity among them. Accordingly, the document clustering can be used in exploring and searching a document and it can increased accuracy of search. This paper proposes an efficient incremental clustering method for a set of documents increase gradually. The incremental document clustering algorithm assigns a set of new documents to the legacy clusters which have been identified in advance. In addition, to improve the correctness of the clustering, removing the stop words can be proposed.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.58-71
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• 2002

Generally, multi-dimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amount of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel high-dimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-n$\times$mD(disk) architecture which is the hybrid type of nP-nD and lP-nD. Its node structure increases fan-out and reduces the height of a index tree. Also, A range search algorithm that maximizes I/O parallelism is devised, and it is applied to K-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.12
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• pp.665-682
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• 2007

Line drawing is a widely used style in non-photorealistic rendering because it generates expressive descriptions of object shapes with a set of strokes. Although various techniques for line drawing of 3D objects have been developed, line drawing of 2D images has attracted little attention despite interesting applications, such as image stylization. This paper presents a robust and effective technique for generating line drawings from 2D images. The algorithm consists of three parts; filtering, linking, and stylization. In the filtering process, it constructs a likelihood function that estimates possible positions of lines in an image. In the linking process, line strokes are extracted from the likelihood function using clustering and graph search algorithms. In the stylization process, it generates various kinds of line drawings by applying curve fitting and texture mapping to the extracted line strokes. Experimental results demonstrate that the proposed technique can be applied to the various kinds of line drawings from 2D images with detail control.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.306-319
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• 2009

A name is a key feature for distinguishing people, but we often fail to discriminate people because an author may have multiple names or multiple authors may share the same name. Such name ambiguity problems affect the performance of document retrieval, web search and database integration. Especially, in bibliography information, a number of errors may be included since there are different authors with the same name or an author name may be misspelled or represented with an abbreviation. For solving these problems, it is necessary to disambiguate the names inputted into the database. In this paper, we propose a method to solve the name ambiguity by using social networks constructed based on the relations between authors. We evaluated the effectiveness of the proposed system based on DBLP data that offer computer science bibliographic information.

• The Journal of the Acoustical Society of Korea
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• v.18 no.2
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• pp.3-10
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• 1999

This paper describes the development and evaluation of a Korean address input system employing automatic speech recognition technique as user interface for input Korean address. Address consists of cities, provinces and counties. The system works on a window 95 environment of personal computer with built-in soundcard. In the speech recognition part, the Continuous density Hidden Markov Model(CHMM) for making phoneme like units(PLUs) and One Pass Dynamic Programming(OPDP) algorithm is used for recognition. For address recognition, Finite State Automata(FSA) suitable for Korean address structure is constructed. To achieve an acceptable performance against the variation of speakers, microphones, and environmental noises, Maximum a posteriori(MAP) estimation is implemented in adaptation. And to improve the recognition speed, fast search method using variable pruning threshold is newly proposed. In the evaluation tests conducted for the 100 connected words uttered by 3 males the system showed above average 96.0% of recognition accuracy for connected words after adaption and recognition speed within 2 seconds, showing the effectiveness of the system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.175-183
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• 2004

In this paper, we propose a new accurate and robust image mosaic technique of the mural underdrawing taken from the infra-red camera, which is based on multiple image registration and adaptive blending technique. The image mosaicing methods which have been developed so far have the following deficits. It is hard to generate a high resolution image when there are regions that do not have features or intensity gradients, and there is a trade-off in overlapping region size in view of registration and blending. We consider these issues as follows. First, in order to mosaic images with neither noticeable features nor intensity gradients, we use a projected supplementary pattern and pseudo color image for features in the image pieces which are registered. Second, we search the overlapping region size with minimum blending error between two adjacent images and then apply blending technique to minimum error overlapping region. Finally, we could find our proposed method is more effective and efficient for image mosaicing than conventional mosaic techniques and also is more adequate for the application of infra-red mural underdrawing mosaicing. Experimental results show the accuracy and robustness of the algorithm

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.201-216
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• 2008

Nowadays various new items are available, but limitation of searching effort makes it difficult for customers to search new items which they want to purchase. Therefore new item providers and customers need recommendation systems which recommend right items for right customers. In this research, we focus on the new item recommendation issue, and suggest preference boundary- based procedures which extend traditional content-based algorithm. We introduce the concept of preference boundary in a feature space to recommend new items. To find the preference boundary of a target customer, we suggest heuristic algorithms to find the centroid and the radius of preference boundary. To evaluate the performance of suggested procedures, we have conducted several experiments using real mobile transaction data and analyzed their results. Some discussions about our experimental results are also given with a further research area.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6B
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• pp.585-594
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• 2009

Efficient filtering is an important factor in RFID system performance. Because of huge volume of tag data in future ubiquitous environment, if RFID readers transmit tag data without filtering to upper-layer applications, which results in a significant system performance degradation. In this paper, we provide an efficient filtering technique which operates on RFID air protocol. RFID air protocol filtering between tags and a reader has some advantages over filtering in readers and middleware, because air protocol filtering reduces the volume of filtering work before readers and middleware start filtering. Exploiting the air protocol filtering advantage, we introduce a geometrical algorithm for generating air protocol filters and verify their performance through simulation with analytical time models. Results of dense RFID reader environment show that air protocol filtering algorithms reduce almost a half of the total filtering time when compared to the results of linear search.