• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.993-1003
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• 2012

The purpose of this study was to estimate the determinants of victory and defeat through analyzing records of Korean men pro-basketball. Statistical models of victory and defeat were established by collecting present basketball records (2010-2011, 2011-2012 season). Korea Basketball League (KBL) informs records of every pro-basketball game data. The six offence variables (2P%, 3P%, FT%, OR, AS, TO), and the four defense variables (DR, ST, GD, BS) were used in this study. PASW program was used for logistic regression and Answer Tree program was used for the decision tree. All significance levels were set at .05. Major results were as follows. In the logistic regression, 2P%, 3P%, and TO were three offense variables significantly affecting victory and defeat, and DR, ST, and BS were three significant defense variables. Offensive variables 2P%, 3P%, TO, and AS are used in constructing the decision tree. The highest percentage of victory was 80.85% when 2P% was in 51%-58%, 3P% was more than 31 percent, and TO was less than 11 times. In the decision tree of the defence variables, the highest percentage of victory was 94.12% when DR was more than 24, ST was more than six, and BS was more than two times.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.1141-1151
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• 1997

In this paper the Maximum Block Method is suggested for the Feature Extraction of stokes of off-line Chinese characters.The Maximum Block Method is a technique which enlarges the block from the first found pixel that wxtracts the skeleton and features of the input characters.The maximum Block mthod is an adequate technique for the correct extraction of the features since the exsting thining methods have shortcomings of making the feature extraction difficult from the distoritions generated from the effiects of the parial noises,inflection points and blemishes. The printed outputs and chinese books of the middle and high school students,and other materials are used for the test.It was found that the Maxthod is also an effective technique for the extraction of skeleton line and features,which is the preoprocessing of the pattern recognition,for the Korean chracters and English as well as chinese chracters.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.578-591
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• 2016

In this paper, the fast encoding algorithm in High Efficiency Video Coding (HEVC) encoder was studied. For the encoding efficiency, the current HEVC reference software is divided the input image into Coding Tree Unit (CTU). then, it should be re-divided into CU up to maximum depth in form of quad-tree for RDO (Rate-Distortion Optimization) in encoding precess. But, it is one of the reason why complexity is high in the encoding precess. In this paper, to reduce the high complexity in the encoding process, it proposed the method by determining the maximum depth of the CU using a hierarchical clustering at the pre-processing. The hierarchical clustering results represented an average combination of motion vectors (MV) on neighboring blocks. Experimental results showed that the proposed method could achieve an average of 16% time saving with minimal BD-rate loss at 1080p video resolution. When combined the previous fast algorithm, the proposed method could achieve an average 45.13% time saving with 1.84% BD-rate loss.

• Journal of Digital Convergence
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• v.18 no.3
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• pp.1-12
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• 2020

The purpose of this study is to explore the trend of blockchain technology through analysis of patents and news articles using text mining, and to suggest the blockchain policy agenda by grasping social interests. For this purpose, 327 blockchain-related patent abstracts in Korea and 5,941 full-text online news articles were collected and preprocessed. 12 patent topics and 19 news topics were extracted with latent dirichlet allocation topic modeling. Analysis of patents showed that topics related to authentication and transaction accounted were largely predominant. Analysis of news articles showed that social interests are mainly concerned with cryptocurrency. Policy agendas were then derived for blockchain development. This study demonstrates the efficient and objective use of an automated technique for the analysis of large text documents. Additionally, specific policy agendas are proposed in this study which can inform future policy-making processes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.801-814
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• 2004

In this paper, we propose a block adaptive binarization (BAB) using a modified quadratic filter (MQF) to binarize business card images acquired by personal digital assistant (PDA) cameras effectively. In the proposed method, a business card image is first partitioned into blocks of 8${\times}$8 and the blocks are then classified into character Hocks (CBs) and background blocks (BBs). Each classified CB is windowed with a 24${\times}$24 rectangular window centering around the CB and the windowed blocks are improved by the pre-processing filter MQF, in which the scheme of threshold selection in QF is modified. The 8${\times}$8 center block of the improved block is barbarized with the threshold selected in the MQF. A binary image is obtained tiling each binarized block in its original position. Experimental results show that the MQF and the BAB have much better effects on the performance of binarization compared to the QF and the global binarization (GB), respectively, for the test business card images acquired in a PDA. Also the proposed BAB using MQF gives binary images of much better quality, in which the characters appear much better clearly, over the conventional GB using QF. In addition, the binary images by the proposed BAB using MQF yields about 87.7% of character recognition rate so that about 32.0% performance improvement over those by the GB using QF yielding about 55.7% of character recognition rate using a commercial character recognition software.

• Journal of The Korean Association of Information Education
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• v.26 no.3
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• pp.197-207
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• 2022

In this paper, we develop a machine learning based block code generation and recommendation model for the purpose of reducing cognitive load of learners during coding education that learns the learner's block that has been made in the block programming environment using natural processing model and fine-tuning and then generates and recommends the selectable blocks for the next step. To develop the model, the training dataset was produced by pre-processing 50 block codes that were on the popular block programming language web site 'Entry'. Also, after dividing the pre-processed blocks into training dataset, verification dataset and test dataset, we developed a model that generates block codes based on LSTM, Seq2Seq, and GPT-2 model. In the results of the performance evaluation of the developed model, GPT-2 showed a higher performance than the LSTM and Seq2Seq model in the BLEU and ROUGE scores which measure sentence similarity. The data results generated through the GPT-2 model, show that the performance was relatively similar in the BLEU and ROUGE scores except for the case where the number of blocks was 1 or 17.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.771-779
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• 2009

Digital topographical maps used for GIS DB are mainly produced by the traditional way of analogue aerial photogrammetry. Therefore, analogue photos are only available for digital mapping after preprocessing such as film developing, printing and scanning. However, digital aerial camera is able to get digital image directly without preprocessing and thus the performance and efficiency of photogrammetry are extremely increased. This study aims to investigate geometric stability of digital aerial frame camera DMC (Digital Modular Camera). In order to verify the geometric stability of digital aerial camera DMC, some different block conditions with and without cross strips, GPS/INS data and variation of GCPs are introduced in the block adjustment. The accuracy results of every block condition were compared each other by computation of residuals of exterior orientation (EO) parameters. Results of study shows that the geometric stability of the block adjustment with cross strips is increased about 30% against without cross strips. The accuracy of EO parameters of block adjustment with cross strips is also increased about 2cm for X-coordinate, 3cm for Y-coordinate, 3cm for Z-coordinate, and 6" for omega, 4" for phi and 3" for kappa.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9A
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• pp.772-780
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• 2005

In this paper, an efficient pre-processing in space tine block coded-spatial multiplexing systems is presented. The pre-processing scheme is designed empirically with extending the diagonally weighted orthogonal space time-block coded diversity system to spatial multiplexing system. Simulation results show the proposed scheme outperforms both the precoder using the predefued codebooks and typical antenna selection scheme over moderate doppler frequency in limited feedback channel.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.4
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• pp.206-213
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• 2003

In this paper, we propose a design method of automatic thickness measurement and defect inspection system, which measures the thickness of the autoclaved lightweight concrete block and inspects the defect on a real-time basis. The image processing system was established with a CCD camera, an image grabber, and a personal computer without using assembled measurement equipment. For the realization of proposed algorithm, the preprocessing method that can be applied to overcome uneven lighting environment, threshold decision method, unit length decision method in uneven condition with rocking objects, and the curvature calibration method of camera using a constructed grid are developed. From the experimental results, we have found that the required measurement accuracy specification is sufficiently satisfied using our proposed method.

• Journal of Broadcast Engineering
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• v.7 no.4
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• pp.310-316
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• 2002

In this paper, we propose an adaptive search range decision algorithm for fast motion estimation of video coding. Block matching algorithm for motion vector estimation that improves coding efficiency by reduction of temporal redundancy has trade-off problem between the motion vector accuracy and the complexity. The proposed algorithm playing as a pre-processing of fast motion estimation adaptively determines the motion search range by the local statistics of neighboring motion vectors. resulting in dramatic reduction of the computational cost without the loss of coding efficiency. Experimental results show the capability of the proposed algorithm.