• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.669-680
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• 2012

Noise removal of document images is a necessary step during preprocessing to recognize characters effectively because it has influences greatly on processing speed and performance for character recognition. We have considered using the spatial filters such as traditional mean filters and Gaussian filters, and wavelet transformed based methods for noise deduction in natural images. However, these methods are not effective for the noise removal of document images. In this paper, we present noise removal of document images using support vector regression. The proposed approach consists of two steps which are SVR training step and SVR test step. We construct an optimal prediction model using grid search with cross-validation in SVR training step, and then apply it to noisy images to remove noises in test step. We evaluate our SVR based method both quantitatively and qualitatively for noise removal in Korean, English and Chinese character documents, and compare it to some existing methods. Experimental results indicate that the proposed method is more effective and can get satisfactory removal results.

• Land and Housing Review
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• v.1 no.1
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• pp.1-7
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• 2010

Case-based reasoning (CBR) method can make estimators understand the estimation process more clearly. Thus, CBR is widely used as a methodology for cost estimation. In CBR, the quality of case retrieval affects the relevance of retrieved cases and hence the overall quality of the reminding capability of CBR system. Thus, it is essential to retrieve relevant past cases for establishing a robust CBR system. Case retrieval needs the following tasks to obtain appropriate case(s); indexing, search, and matching (Aamodt and Plaza 1994). However, the previous CBR researches mostly deal with matching process that has limits such as accuracy and efficiency of case retrieval. In order to address this issue, this research presents a CBR cost model for building projects that has two-step retrieval process: decision tree and nearest neighbor methods. Specifically, the proposed cost model has indexing, search and matching modules. Features in the model are divided into shape-based and scale-based attributes. Based on these, decision tree is established for facilitating the search task and nearest neighbor method was utilized for matching task. In regard to applying nearest neighbor method, attribute weights are assigned using GA optimization and similarity is calculated using the principle of distance measuring. Thereafter, the proposed CBR cost model is developed using 174 cases and validated using 12 test cases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.139-149
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• 2007

Asynchronous OFCDM(Orthogonal Frequency and Code Division Multiplexing) systems must have a cell search process necessarily unlike synch개nous systems. this process is hewn initial synchronization and a three-step cell search algorithm is performed for the initial synchronization in the following three steps: OFCDM symbol timing, i.e., Fast Fourier Transform(FFT) window timing is estimated employing guard interval (GI) correlation in the first step, then the frame timing and CSSC(Cell Specific Scrambling Code) group is detected by taking the correlation of the CPICH(Common Pilot Channel) based on the property yielded by shifting the CSSC phase in the frequency domain. Finally, the CSSC phase within the group is identified in the third step. This paper proposes a modification group code with two or three block of the conventional CPICH based cell search algorithm in the second step which offers MS(Mobile Station) complexity reductions. however, the effect of the reduction complexity leads to degradation of the performance therefore, look for combination to have the most minimum degradation. the proposed block type group code with suitable combinations is the nearly sane performance as conventional group code and has a complexity reduction that is to be compared and verified through the computer simulation.

• Journal of the military operations research society of Korea
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• v.26 no.1
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• pp.47-55
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• 2000

The purpose of this paper is to develop a new heuristic algorithm for vehicle routing problem. The algorithm is composed of two steps. First step is to make a initial solution using sweeping algorithm. Second step is to improve initial solution for optimal solution using node exchange algorithm and tabu search algorithm. We have proven that our algorithm has produced better results than solutions obtained by saving algorithm and genetic in ten example problems with different unit size.

• Korean Journal of Computational Design and Engineering
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• v.11 no.4
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• pp.315-325
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• 2006

It is very often necessary to search for similar parts during designing a new product because its parts are often easily designed by modifying existing similar parts. In this way, the design time and cost can be reduced. Thus it would be nice to have an efficient similarity comparison algorithm that can be used anytime in the design process. There have been many approaches to compare shape similarity between two solids. In this paper, two parts represented in B-Rep is compared in two steps: one for overall appearances and the other for detail features. In the first step, geometric information is used in low level of detail for easy and fast pre-classification by the overall appearance. In the second step, feature information is used to compare the detail shape in high level of detail to find more similar design. To realize the idea above, a multi resolution algorithm is proposed so that a given solid is described by an overall appearance in a low resolution and by detail features in high resolution. Using this multi-resolution representation, parts can be compared based on the overall appearance first so that the number of parts to be compared in high resolution is reduced, and then detail features are investigated to retrieve the most similar part. In this way, computational time can be reduced by the fast classification in the first step while reliability can be preserved by detail comparison in the second step.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.4
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• pp.5-23
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• 2014

This study reports the first step in the Classification-based Search and Knowledge Discovery (CSKD) project, which aims to combine information organization and retrieval approaches for building digital library applications. In this study, we explored the generation and application of a faceted vocabulary as a potential mechanism to enhance knowledge discovery. The faceted vocabulary construction process revealed some heuristics that can be refined in follow-up studies to further automate the creation of faceted classification structure, while our concept search application demonstrated the utility and potential of integrating classification-based approach with retrieval-based approach. Integration of text- and classification-based methods as outlined in this paper combines the strengths of two vastly different approaches to information discovery by constructing and utilizing a flexible information organization scheme from an existing classification structure.

• Journal of the Korea Computer Industry Society
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• v.4 no.4
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• pp.613-624
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• 2003

This paper proposes a design for efficient and accurate retrieval of similar image subsequences using the multi-dimensional time warping distance as similarity evaluation tool in image sequence database after building of two indexing structures implemented with priority queue and suffix tree respectively. Receiving query image sequence, at first step, the proposed method searches the candidate set of similar image subsequences in priory queue index structure. If it can not get satisfied results, it retrieves another candidate set in suffix tree index structure at second step. The using of the low-bound distance function can remove the dissimilar subsequence without false dismissals during similarity evaluating process between query image sequence and stored sequences in two index structures.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.181-197
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• 2001

A heuristic method TABU-CSP using Tabu Search (TS) is described for solving Constraint Satisfaction Problems (CSPs). The method is started with a complete but inconsistent solution of a binary CSP and obtained in prespecified number of iterations either a consistent solution or a near optimal solution with an acceptable number of conflicts. The repair in the solution at each iterative step is done by using two heuristics alternatively. The first heuristic is a min-conflicts heuristic that chooses a variable with the maximum number of conflicts and reassigns it the value which leads to the minimum number of conflicts. If the acceptable solution is not reached after the search continued for a certain number of iterations, the min-conflict heuristic is changed and the variable selected least number of times is chosen for repair. If an acceptable solution is not reached, the method switches back to the min-conflict heuristic and proceeds further. This allowed the method to explore a different region of search space space for the solution as well as to prevent cycling. The demonstration of the method is shown on a toy problem [9]which has no solution. The method is then tested on various randomly generated CSPs with different starting solutions. The performance of the proposed method in terms of the average number of consistency is checked and the average number of conflicts is conflicts is compared with that of the Branch and Bound(BB) method used to obtain the same solution. In almost all cases, the proposed method moves faster to the acceptable solution than BB.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.184-187
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• 2011

영상 압축은 멀티미디어 전송에 있어 핵심적인 기술이다. 동영상 압축 기술 중 움직임 예측은 H.264, MPEG-4 등의 압축 표준에서 시간적 중복성을 줄이기 위해 이용되고 있다. 따라서 영상의 압축 효율을 높이는 다양한 움직임 예측 알고리듬이 제안되었다. 이에 본 논문은 계산량을 줄이기 위해서 EPDS(Edge-Based Partial Distortion Search)를 기반으로 한 개선된 이단 탐색 움직임 예측 알고리듬을 제안한다. 이를 위하여 이단 탐색에서의 적응적 탐색 구간 적용 기술을 사용하였다. 제안한 알고리듬은 FS보다 98.11배 빠르다. 뿐만 아니라, PSNR을 통해 화질이 비슷하게 유지됨을 알 수 있다. 따라서 제안한 알고리듬은 고화질 디지털 영상 실시간 구현에 적합하다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.6
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• pp.35-48
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• 1993

In this paper, a hierarchical motion vector estimation algorithm using pyramidal structure is proposed. Using a smaller measurement window at each level of a pyramid than that of the conventional scheme, the proposed algorithm, based on the TSS(three step search), reduces the computational complexity greatly with its performance comparable to that of the TSS. By increasing the number of cnadidate motion vectors which are to be used as the initial search points for motion vector estimation at the next level, the performance improves further. Then the computational complexity of the proposed hierarchical algorithm depends on the number of candidate motion vectors, with its PSNR (peak signal to noise ratio) ranging between those of the TSS and the full search method. The simulation results with two different block sizes and various test sequences are given and its hardware implementation is also sketched.