• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.441-447
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• 2000

Automatic word spacing is needed to solve the automatic indexing problem of the non-spaced documents and the space-insertion problem of the character recognition system at the end of a line. We propose a word spacing algorithm that automatically finds out word spacing positions. It is based on the recognition of Eojeol components by using the sentence partition and bidirectional longest-match algorithm. The sentence partition utilizes an extraction of Eojeol-block where the Eojeol boundary is relatively clear, and a Korean morphological analyzer is applied bidirectionally to the recognition of Eojeol components. We tested the algorithm on two sentence groups of about 4,500 Eojeols. The space-level recall ratio was 97.3% and the Eojeol-level recall ratio was 93.2%.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.5
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• pp.177-188
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• 2018

The scale of graph data has been increased rapidly because of the growth of mobile Internet applications and the proliferation of social network services. This brings upon the imminent necessity of efficient distributed and parallel graph processing approach since the size of these large-scale graphs are easily over a capacity of a single machine. Currently, there are two popular parallel graph processing approaches, vertex-centric graph processing and block centric processing. While a vertex-centric graph processing approach can easily be applied to the parallel processing system, a block-centric graph processing approach is proposed to compensate the drawbacks of the vertex-centric approach. In these systems, the initial quality of graph partition affects to the overall performance significantly. However, it is a very difficult problem to divide the graph into optimal states at the initial phase. Thus, several dynamic load balancing techniques have been studied that suggest the progressive partitioning during the graph processing time. In this paper, we present a load balancing algorithms for the block-centric graph processing approach where most of dynamic load balancing techniques are focused on vertex-centric systems. Our proposed algorithm focus on an improvement of the graph partition quality by dynamically reassigning blocks in runtime, and suggests block split strategy for escaping local optimum solution.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.332-340
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• 2022

Recently, with the development of deep learning and artificial neural network technologies, research on the application of neural network has been actively conducted in the field of video coding. In particular, deep learning-based intra prediction is being studied as a way to overcome the performance limitations of the existing intra prediction techniques. This paper presents a method of context-adaptive neural network-based intra prediction model training and its coding performance analysis. In other words, in this paper, we implement and train a known intra prediction model based on convolutional neural network (CNN) that predicts a current block using contextual information from reference blocks. Then, we integrate the trained model into HM16.19 as an additional intra prediction mode and evaluate the coding performance of the trained model. Experimental results show that the trained model gives 0.28% BD-rate bit saving over HEVC in All Intra (AI) coding mode. In addition, the coding performance change of training considering block partition is also presented.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.1
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• pp.1-12
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• 2019

This paper proposes a new motion vector smoothing and motion compensation method to increase the frame rate of videos. The proposed method reduces false motion vector smoothing by improving the weight with reflecting accuracy to overcome the limitation of the conventional motion vector smoothing using the adaptively weighted vector median. Also, to improve the interpolated image quality of the conventional OBMC(Overlapped Block Motion Compensation), a scheme that divides an original block into 4 sub-blocks and then generates the interpolated frame using the reestimated motion vector for each sub-block is proposed. The simulation results prove that the proposed method can provide much better objective and subjective image quality than the conventional method.

• Fire Science and Engineering
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• v.3 no.1
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• pp.3-9
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• 1989

This paper is study that the mathemetical model of water mebrane splinklikler capacity in fire prevention block. The methmetical investigation are performed about prediction of five temperature in room and water membrane splinkler capacity by use of experimental model. The good correlation between predicted and experimental results is indication the adequacy of the mothemetical model. However. further experimental and analytical worke are needed before a more general mathemetical model can be proposed.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.392-395
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• 1999

The state assignment for a finite state machine greatly affects the delay, area, and testabilities of the sequential circuits. In order to minimize the dependencies among state variables, therefore possibly to reduce the length and number of feedback cycles, a new state assignment technique based on m-block partition is introduced in this paper. After the completion of state assignment and logic synthesis, partial scan design is performed to choose minimal number of scan flip-flops. Experiment shows drastic improvement in testabilities while preserving low area and delay overhead.

• Broadcasting and Media Magazine
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• v.15 no.4
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• pp.45-54
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• 2010

최근 ISO/IEC와 ITU는 공동협력팀(Joint Collaborative Team on Video Coding-JCT-VC)을 구성하여 HEVC(High Efficiency Video Coding)라 불리는 새로운 비디오 압축 표준 기술을 개발하고 있다. JCT-VC의 목표 중 하나는 H.264/AVC 압축률의 2배를 향상하는 것으로 최근 HEVC 테스트 모델(HEVC Test Model - HM)을 확정했다. HM의 여러 기술 중에서 확장 블록 구조 (large block structure) 기술은 CTB(Coded Tree Block)와 TU(Transform Unit), PU(Partition Unit)로 구성된다. CTB와 TU는 압축 단위와 변환 기술을 확장한 반복적인 문법구조(recursive syntax structure)이며, PU는 H.264/AVC과 동일한형태를 띈다. 확장 블록 구조는CTB, PU, TU의 여러 조합에 의해 다양한 모드를 지원하여 압축 성능은 높아졌지만 HM 부호화기의 복잡도는 증가한다. 본 논문에서는 HM에 채택된 확장블록구조 및 변환 기술에 대해 설명한 후, TMuC 및 HM의 테스트 영상을 이용하여 다양한 최대 CTB 및 TU 크기의 압축성능 및 선택비율을 분석한다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.11
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• pp.1288-1293
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• 2009

This paper discusses about modeling method to simulate a nonlinear behavior like sliding or rocking of two stacked body system under earthquake condition. A double body system design can be an option to reduce seismic response of a component in comparison to a single body system for free standing structures. Therefore, according to the priority of components, the structure is to be designed by proper ratio of partition in their height for improvement of seismic capability and structural integrity. Nonlinear modeling and analysis using simple rigid body and dynamic system has been performed to check the trend in such cases. As a result, one of the two bodies can be chosen to reduce the seismic response from energy absorption of the other one by appropriate application of friction ratios not only in slip-slip condition but in slip-rock condition.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.4
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• pp.235-241
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• 2016

Compared to the former H.264 standard, the number of the prediction modes has highly increased in HEVC intra prediction. Compression efficiency and accurate prediction are significantly improved. However, the computational complexity increases as well. To solve this problem, this paper proposes the new scheme where not only prediction modes but also block partition candidate are early chosen. Compared to the original intra prediction in HEVC, the proposed scheme achieves about 38% reduction in processing cycles with a marginal loss in compression efficiency.

• Macromolecular Research
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• v.15 no.7
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• pp.623-632
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• 2007

Thermosensitive nanoparticles were prepared via the self-assembly of two different $poly({\varepsilon}-caprolactone)$-based block copolymers of poly(N-isopropylacrylamide)-b-$poly({\varepsilon}-caprolactone)$ (PNPCL) and poly(ethylene glycol)-b-$poly({\varepsilon}-caprolactone)$ (PEGCL). The self-aggregation and thermosensitive behaviors of the mixed nanoparticles were investigated using $^1H-NMR$, turbidimetry, differential scanning microcalorimetry (micro-DSC), dynamic light scattering (DLS), and fluorescence spectroscopy. The copolymer mixtures (mixed nanoparticles, M1-M5, with different PNPCL content) formed nano-sized self-aggregates in an aqueous environment via the intra- and/or intermolecular association of hydrophobic PCL chains. The microscopic investigation of the mixed nanoparticles showed that the critical aggregation concentration (cac), the partition equilibrium constants $(K_v)$ of pyrene, and the aggregation number of PCL chains per one hydrophobic microdomain varied in accordance with the compositions of the mixed nanoparticles. Furthermore, the PNPCL harboring mixed nanoparticles evidenced phase transition behavior, originated by coil to the globule transition of PNiPAAm block upon heating, thereby resulting in the turbidity change, endothermic heat exchange, and particle size reduction upon heating. The drug release tests showed that the formation of the thermosensitive hydrogel layer enhanced the sustained drug release patterns by functioning as an additional diffusion barrier.