• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.275-284
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• 2007

Among the languages that allow long-distance reflexives, some languages have blocking effects, whereas others don't. The goal of this paper is to provide computational algorithms that can handle presence and absence of blocking effects of long-distance reflexives. We will examine the blocking effects in Chinese and Korea and develop computational algorithms for handling blocking effects in those two languages. The algorithms will be developed by incorporating Chierchia's Binding Theory into Steedman's Combinatory Categorial Grammar (CCG). Through the analyses and implementations, this paper illustrates how blocking effects can be implemented computationally.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.203-210
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• 2002

The great advantages on the Genetic Algorithms(GAs) are ease of implementation, and robustness in solving a wide variety of problems, several GAs based optimization models for solving complex structural problems were proposed. However, there are two major disadvantages in GAs. The first disadvantage, implementation of GAs-based optimization is computationally too expensive for practical use in the field of structural optimization, particularly for large-scale problems. The second problem is too difficult to find proper parameter for particular problem. Therefore, in this paper, a Distributed Hybrid Genetic Algorithms(DHGAs) is developed for structural optimization on a cluster of personal computers. The algorithm is applied to the minimum weight design of steel structures.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.295-298
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• 2002

This paper presents a fast block-matching algorithm to improve the conventional Three-Step Search (TSS) based method. The proposed Comparison Fast Block Matching Algorithm (CFBMA) begins with DAB for adaptive search range to choose searching method, and searches a part of search window that has high possibility of motion vector like other partial search algorithms. The CFBMA also considers the opposite direction to reduce local minimum, which is ignored in almost conventional based partial search algorithms. CFBMA uses the summation half-stop technique to reduce the computational load. Experimental results show that the proposed algorithm achieves the high computational complexity compression effect and very close or better image quality compared with TSS, SES, NTSS based partial search algorithms.

• Korean Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.68-85
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• 1998

Solid modeling refers to techniques for unambiguous representations of three-dimensional objects. Feature recognition is a sub-discipline focusing on the design and implementation of algorithms for detecting manufacturing information such as holes, slots, etc. in a solid model. Automated feature recognition has been an active research area in stolid modeling for many years, and is considered to be a critical component for CAD/CAM integration. This paper gives a technical overview of the state of the art in feature recognition research. Rather than giving an exhaustive survey, I focus on the three currently dominant feature recognition technologies: graph-based algorithms, volumetric decomposition techniques, and hint-based geometric reasoning. For each approach, I present a detailed description of the algorithms being employed along with some assessments of the technology. I conclude by outlining important open research and development issues.

• The Journal of Korean Association of Computer Education
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• v.18 no.6
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• pp.23-31
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• 2015

The main aim in software education is to improve problem-solving ability based on computational thinking with the healthy information ethics. For this purpose, many institutions have attempted various educational programs such as Educational Programming Language, Physical Computing, and Robot education. However, it is possible to obscure the essence of computer education for computational thinking if the computer education focuses on using certain special education programming language and products. Therefore, this paper suggests a method of algorithm education using RAPTOR which is a visual programming development environment and is based on flowcharts. In order to verify the effectiveness of the algorithms education using the RAPTOR, 16 high-school students were applied to an educational program for twelve hours on five steps and then we obtained positive results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1425-1440
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• 2017

In wireless communications, antenna selection (AS) is a widely used method for reducing comparable cost of multiple RF chains in MIMO systems. As is well known, most of literatures on combining AS with MIMO techniques concern linear modulations such as phase shift keying (PSK) and quadrature amplitude modulation (QAM). The combination of CPM and MIMO has been considered an optimal choice that can improve its capacity without loss of power and spectrum efficiency. The aim of this paper is to investigate joint transmit and receive antenna selection (JTRAS) in CPM MIMO systems. Specifically, modified incremental and decremental JTRAS algorithms are proposed to adapt to arbitrary number of selected transmit or receive antennas. The computational complexity of several JTRAS algorithms is analyzed from the perspective of channel capacity. As a comparison, the performances of bit error rate (BER) and spectral efficiency are evaluated via simulations. Moreover, computational complexity of the JTRAS algorithms is simulated in the end. It is inferred from discussions that both incremental JTRAS and decremental JTRAS perform close to optimal JTRAS in BER and spectral efficiency. In the sense of practical scenarios, adaptive JTRAS can be employed to well tradeoff performance and computational complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.232-248
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• 2014

A series of kernel regression (KR) algorithms, such as the classic kernel regression (CKR), the 2- and 3-D steering kernel regression (SKR), have been proposed for image and video super-resolution. In existing KR frameworks, a single algorithm is usually adopted and applied for a whole image/video, regardless of region characteristics. However, their performances and computational efficiencies can differ in regions of different characteristics. To take full advantage of the KR algorithms and avoid their disadvantage, this paper proposes a kernel regression framework for video super-resolution. In this framework, each video frame is first analyzed and divided into three types of regions: flat, non-flat-stationary, and non-flat-moving regions. Then different KR algorithm is selected according to the region type. The CKR and 2-D SKR algorithms are applied to flat and non-flat-stationary regions, respectively. For non-flat-moving regions, this paper proposes a similarity-assisted steering kernel regression (SASKR) algorithm, which can give better performance and higher computational efficiency than the 3-D SKR algorithm. Experimental results demonstrate that the computational efficiency of the proposed framework is greatly improved without apparent degradation in performance.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.43-46
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• 2000

In this paper, we propose a fast adaptive diamond search algorithm(FADS) for block matching motion estimation. Fast motion estimation algorithms reduce the computational complexity by using the UESA (Unimodal Error Search Assumption) that the matching error monotonically increases as the search moves away from the global minimum error. Recently many fast BMAs(Block Matching Algorithms) make use of the fact that the global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the adjacent blocks. We change the origin of search window according to the spatially adjacent motion vectors and their MAE(Mean Absolute Error). The computer simulation shows that the proposed algorithm has almost the same computational complexity with UCBDS(Unrestricted Center-Biased Diamond Search)〔1〕, but enhance PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS(Full Search), even for the large motion case, with half the computational load.

• Journal of Computing Science and Engineering
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• v.6 no.4
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• pp.310-319
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• 2012

Next generation wireless receivers demand low computational complexity algorithms with high computing power in order to perform fast signal detections and error estimations. Several signal detection and estimation algorithms have been proposed for next generation wireless receivers which are primarily designed to provide reasonable performance in terms of signal to noise ratio (SNR) and bit error rate (BER). However, none of them have been chosen for direct implementation as they offer high computational complexity with relatively lower computing power. This paper presents a low-complexity power-efficient algorithm that improves the computing power and provides relatively faster signal detection for next generation wireless multiuser receivers. Measurement results of the proposed algorithm are provided and the overall system performance is indicated by BER and the computational complexity. Finally, in order to verify the low-complexity of the proposed algorithm we also present a formal mathematical proof.

• 한국전산유체공학회:학술대회논문집
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• 1999.11a
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• pp.17-22
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• 1999

Convergence characteristics and efficiency of three implicit approximate factorization schemes(ADI, DDADI and MAF) are examined using 2-Dimensional compressible upwind Navier-Stokes code. Second-order CSCM(Conservative Supra Characteristic Method) upwind flux difference splitting method with Fromm scheme is used for the right-hand side residual evaluation, while generally first-order upwind differencing is used for the implicit operator on the left-hand side. Convergence studies are performed using an example of the flow past a NACA0012 airfoil at steady transonic flow condition, i. e. Mach number 0.8 at $1.25^{\circ}$ angle of attack. The results were compared with other computational results in order to validate the current numerical analysis. The results from the implicit AF algorithms were compared well in low surface with the other computational results; however, not well in upper surface. It might be due to lack of the grid around the shock position. Because the algorithm minimizes the errors of the approximate decomposition, the improved convergence rate with MAF were observed.