• The KIPS Transactions:PartC
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• v.19C no.4
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• pp.247-252
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• 2012

Network coding has been shown to improve various performance metrics in network systems. However, if network coding is implemented as software a huge time delay may be incurred at encoding/decoding stage so it is imperative for network coding to be parallelized to reduce time delay when encoding/decoding. In this paper, we compare the performance of parallelized decoders for random linear network coding (RLC) and pipeline network coding (PNC), a recent development in order to alleviate problems of RLC. We also compare multi-threaded algorithms on multi-core CPUs and massively parallelized algorithms on GPGPU for PNC/RLC.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.73-79
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• 2021

Recently, in the field of computer animation, a method for generating motion using deep learning has been studied away from conventional finite-state machines or graph-based methods. The expressiveness of the network required for learning motions is more influenced by the diversity of motion contained in it than by the simple length of motion to be learned. This study aims to find an efficient network structure when the types of motions to be learned are diverse. In this paper, we train and compare three types of networks: basic fully-connected structure, mixture of experts structure that uses multiple fully-connected layers in parallel, recurrent neural network which is widely used to deal with seq2seq, and transformer structure used for sequence-type data processing in the natural language processing field.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.669-680
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• 2011

R-trees are widely used in various areas such as geographical information systems, CAD systems and spatial databases in order to efficiently index multi-dimensional data. As data sets used in these areas grow in size and complexity, however, range query operations on R-tree are needed to be further faster to meet the area-specific constraints. To address this problem, there have been various research efforts to develop strategies for acceleration query processing on R-tree by using the buffer mechanism or parallelizing the query processing on R-tree through multiple disks and processors. As a part of the strategies, approaches which parallelize query processing on R-tree through Graphics Processor Units(GPUs) have been explored. The use of GPUs may guarantee improved performances resulting from faster calculations and reduced disk accesses but may cause additional overhead costs caused by high memory access latencies and low data exchange rate between GPUs and the CPU. In this paper, to address the overhead problems and to adapt GPUs efficiently, we propose a novel approach which uses a GPU as a buffer to parallelize query processing on R-tree. The use of buffer algorithm can give improved performance by reducing the number of disk access and maximizing coalesced memory access resulting in minimizing GPU memory access latencies. Through the extensive performance studies, we observed that the proposed approach achieved up to 5 times higher query performance than the original CPU-based R-trees.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.726-734
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• 2015

Relational databases used by structuralizing data are the most widely used in data management at present. However, in relational databases, service becomes slower as the amount of data increases because of constraints in the reading and writing operations to save or query data. Furthermore, when a new task is added, the database grows and, consequently, requires additional infrastructure, such as parallel configuration of hardware, CPU, memory, and network, to support smooth operation. In this paper, in order to improve the web information services that are slowing down due to increase of data in the relational databases, we implemented a model to extract a large amount of data quickly and safely for users by processing Hadoop Distributed File System (HDFS) files after sending data to HDFSs and unifying and reconstructing the data. We implemented our model in a Web-based civil affairs system that stores image files, which is irregular data processing. Our proposed system's data processing was found to be 0.4 sec faster than that of a relational database system. Thus, we found that it is possible to support Web information services with a Hadoop-based big data processing technique in order to process a large amount of data, as in conventional relational databases. Furthermore, since Hadoop is open source, our model has the advantage of reducing software costs. The proposed system is expected to be used as a model for Web services that provide fast information processing for organizations that require efficient processing of big data because of the increase in the size of conventional relational databases.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.1
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• pp.1-8
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• 2017

Given a multi-dimensional dataset of tuples, a skyline query returns a subset of tuples which are not 'dominated' by any other tuples. Skyline query is very useful in Big data analysis since it filters out uninteresting items. Much interest was devoted to the MapReduce-based parallel processing of skyline queries in large-scale distributed environment. There are three requirements to improve parallelism in MapReduced-based algorithms: (1) workload should be well balanced (2) avoid redundant computations (3) Optimize network communication cost. In this paper, we introduce MR-SEAP (MapReduce sample Skyline object Equality Angular Partitioning), an efficient angular space partitioning based skyline query processing using sampling-based pruning, which satisfies requirements above. We conduct an extensive experiment to evaluate MR-SEAP.

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.22-30
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• 2009

Purpose : Patient motion during magnetic resonance (MR) imaging is one of the major problems due to its long scan time. Entropy based post-processing motion correction techniques have been shown to correct motion artifact effectively. One of main limitations of these techniques however is its long processing time. In this study, we propose several methods to reduce this long processing time effectively. Materials and Methods : To reduce the long processing time, we used the separability property of two dimensional Fourier transform (2-D FT). Also, a computationally light metric (sum of all image pixel intensity) was used instead of the entropy criterion. Finally, partial Fourier reconstruction, in particular the projection onto convex set (POCS) method, was combined thereby reducing the size of the data which should be processed and corrected. Results : Time savings of each proposed method are presented with different data size of brain images. In vivo data were processed using the proposed method and showed similar image quality. The total processing time was reduced to 15% in two dimensional images and 30% in the three dimensional images. Conclusion : The proposed methods can be useful in reducing image motion artifacts when only post-processing motion correction algorithms are available. The proposed methods can also be combined with parallel imaging technique to further reduce the processing times.

• Korea-Australia Rheology Journal
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• v.20 no.3
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• pp.117-125
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• 2008

Viscoelastic instabilities are of fundamental importance to understanding the physics of complex fluids and of practical importance to materials processing and fluid characterization. Significant progress has been made over the past 15 years in understanding instabilities in viscoelastic flows with curved streamlines and is reviewed here. Taylor-Couette flow, torsional flow between a cone and plate, and torsional flow between parallel plates have received special attention due to both the basic significance of these flows and their critical role in rheometry. First, we review the criteria for determining when these flows become unstable due to elasticity in the absence of inertia, and discuss the generalization of these criteria to more complex flows with curved streamlines. Then, focusing on experiments and simulations in the Taylor-Couette problem, we review how thermal sensitivity (i.e., the dependence of fluid viscosity and elasticity on temperature) and inertia affect the stability of viscoelastic flows. Finally, we conclude with some general thoughts on unresolved issues and remaining challenges related to viscoelastic instabilities.

• The Journal of the Acoustical Society of Korea
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• v.13 no.2
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• pp.38-49
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• 1994

This paper proposes Echo canceller used in simultaneous two-way ('full-duplex') transmission of data signals over two-wire circuits which can be achieved by using a hybrid coupler. This Echo canceller uses sequential processing instead of parallel processing with conventional adaptive digital filter. This structure reduces the number of multipliers. Thus, this structure is much more suitable for IC implementation. This Echo canceller operates according to the 'Stochastic Iteration Algorithm(SIA).' SIA algorithm has merit of good performance and small hardware requirement.

• The KIPS Transactions:PartA
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• v.17A no.2
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• pp.73-80
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• 2010

As the power of hardware has improved, there have been numerous researches in processing concurrently using multitasking method. The incremental evaluation is the evaluation method of reevaluating only affected parts instead of reevaluating overall program when the program has been changed. It is necessary to do more studies that improve the efficiency of concurrent incremental evaluation to do multitasking using multi-threading of Java not to do in parallel using multiprocessor. In this paper, the dependency in the dependency chart is based on the attribute that describes the real value of the variable that directly affects the semantics, thereby doing efficient evaluation. So using the dependency, this paper presents the concurrent incremental evaluation algorithm for Java Languages and proves its correctness, analyzing the efficiency of concurrent incremental evaluation by the simulation.

• The KIPS Transactions:PartA
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• v.12A no.4 s.94
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• pp.281-288
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• 2005

Efficient utilization of processing resources in a large multicomputer system with the possibility of fault occurrence depends on the reliable processor management scheme. This paper presents a dynamic and reliable processor allocation strategy to increase the performance of mesh-connected parallel systems with faulty processors The basic idea is to reconfigure a faulty mesh system into a maximum convex system using the fault-free upper or lower boundary nodes to compensate for the non-boundary faulty nodes. To utilize the non-rectangular shaped system parts, our strategy tries to allocate L-shaped submeshes instead of signaling the allocation failure. Extensive simulations show that the strategy performs more efficiently than other strategies in terms of the job response time md the system utilization.