• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.82-87
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• 2015

There are many current researches that are looking to improve the quality of HTTP adaptive streaming services. However, the existing schemes have a serious problem of QoE (Quality of Experience) degradation because few consider VBR video transmission. To cope with this problem, in this paper, we proposed a novel media quality adaptation scheme called CB-DASH (Content and Buffer-aware DASH). The proposed scheme controlled the video quality considering the VBR characteristics of video and the client's buffer state. Through the simulation, we proved that our scheme accomplished a more accurate estimated bandwidth than the conventional DASH and improved the QoE of streaming service.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.413-421
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• 2015

Regularized Blind Deconvolution is a problem applicable in degraded images in order to bring the original image out of blur. Multichannel blind Deconvolution considered as an optimization problem. Each step in the optimization is considered as variable splitting problem using an algorithm called Alternating Minimization Algorithm. Each Step in the Variable splitting undergoes Augmented Lagrangian method (ALM) / Bregman Iterative method. Regularization is used where an ill posed problem converted into a well posed problem. Two well known regularizers are Tikhonov class and Total Variation (TV) / L2 model. TV can be isotropic and anisotropic, where isotropic for L2 norm and anisotropic for L1 norm. Based on many probabilistic model and Fourier Transforms Image deblurring can be solved. Here in this paper to improve the performance, we have used an adaptive regularization filtering and isotropic TV model Lp norm. Image deblurring is applicable in the areas such as medical image sensing, astrophotography, traffic signal monitoring, remote sensors, case investigation and even images that are taken using a digital camera / mobile cameras.

• Journal of IKEEE
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• v.24 no.1
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• pp.186-193
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• 2020

In this paper, we propose a multi-threading system to support reconfigurable hardware accelerators on Zynq SoC. We implement high-performance JPEG decoder with reconfigurable 2D IDCT hardware accelerators to achieve maximum performance available on the platform. In this system, up to four reconfigurable hardware accelerators synchronized with SW threads can be dynamically reconfigured to provide adaptive computing capabilities according to the given image resolution and the compression ratio. JPEG decoding is operated using images with resolutions 480p, 720p, 1080p at the compression ratio of 7:1-109:1. We show that significant performance improvements are achieved as the image resolution or the compression ratio increase. For 1080p resolution, the performance improvement is up to 79.11 times with throughput speed of 99 fps at the compression ratio 17:1.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.469-475
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• 2010

The objective of this study is to integrate reliability analysis into shape optimization problem using the evolutionary structural optimization (ESO) in the application example. Reliability-based shape optimization is formulated as volume minimization problem with probabilistic stress constraint under minimization max. von Mises stress and allow stress. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., reliability index approach (RIA), performance measure approach (PMA), single-loop singlevector (SLSV) and adaptive-loop (ADL), are used. Reliability-based shape optimization design process is conducted to obtain optimal shape satisfying max. von Mises stress and reliability index constraints with the above four methods, and then each result is compared with respect to numerical stability and computing time.

• Journal of the Optical Society of Korea
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• v.20 no.6
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• pp.745-751
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• 2016

A detection algorithm, based on the combined local-global (CLG) optical-flow model and Gaussian pyramid for a moving target appearing against a dynamic background, can compensate for the inadaptability of the classic Horn-Schunck algorithm to illumination changes and reduce the number of needed calculations. Incorporating the hypothesis of gradient conservation into the traditional CLG optical-flow model and combining structure and texture decomposition enable this algorithm to minimize the impact of illumination changes on optical-flow estimates. Further, calculating optical-flow with the Gaussian pyramid by layers and computing optical-flow at other points using an optical-flow iterative with higher gray-level points together reduce the number of calculations required to improve detection efficiency. Finally, this proposed method achieves the detection of a moving target against a dynamic background, according to the background motion vector determined by the displacement and magnitude of the optical-flow. Simulation results indicate that this algorithm, in comparison to the traditional Horn-Schunck optical-flow algorithm, accurately detects a moving target undergoing illumination changes against a dynamic background and simultaneously demonstrates a significant reduction in the number of computations needed to improve detection efficiency.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.6-8
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• 2009

This paper presents the novel implementation of memetic algorithm with GA (Genetic Algorithm) and MADS (Mesh Adaptive Direct Search), which is applied for optimal design methodology of electric machine. This hybrid algorithm has been developed for obtaining the global optimum rapidly, which is effective for optimal design of electric machine with many local optima and much longer computation time. In particular, the proposed memetic algorithm has been forwarded to optimal design of direct-driven PM wind generator for maximizing the Annual Energy Production (AEP), of which design objective should be obtained by FEA (Finite Element Analysis). After all, it is shown that GA combined with MADS has contributed to reducing the computation time effectively for optimal design of PM wind generator when compared with purposely developed GA implemented with the parallel computing method.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.601-605
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• 2010

In this paper, we propose a GBL(Game Based Learning) content of intelligent tutoring capability. The objective of our GBL content is to learn the Karnaugh Map which is generally used to simplify boolean functions. Our GBL content well-motivates learners with interesting game-based scenarios and also, through an intelligent tutoring module, gives learners adaptive feedbacks such as hints and explanations while maintaining learners' contextual immersion. Additionally, we identified significant improvement in terms of learning effectiveness by analyzing the test results of two (experimental and controlled) student groups learning the Karnaugh Map.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.552-556
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• 2004

This paper surveys the design of the adaptive information filtering agents to retrieve the useful information within a large scale database. As the information retrieval through the Internet is generalized, it is necessary to extract the useful information satisfied the user's request condition to reduce the seeking time. For the first, this module is designed by the Rough reduct to generate the reduced minimal knowledge database considered the users natural query language in a large scale knowledge database, and also it is executed the soft computing by the fuzzy composite processing to operate the uncertain value of the reduced schema domain.

• Journal of Internet Computing and Services
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• v.5 no.6
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• pp.11-20
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• 2004

Proportional Fair (PF) share policy has been adopted as a downlink scheduling scheme in CDMA2000 l×EV-DO standard. Although It offers optimal performance in aggregate throughput conditioned on equal time share among users, it cannot provide a bandwidth guarantee and a strict delay bound. which is essential requirements of real-time (RT) applications. In this study, we propose a new scheduling policy that provides quality-of-service (QoS) guarantees to a variety of traffic types demanding diverse service requirements. In our policy data traffic is categorized Into three classes, depending on sensitivity of Its performance to delay or throughput. And the primary components of our policy, namely, Proportional Fair (PF), Weighted Fair Queuing (WFQ), and delay-based prioritized scheme are intelligently combined to satisfy QoS requirements of each traffic type. In our policy all the traffic categories run on the PF policy as a basis. However the level of emphasis on each of those ingredient policies is changed in an adaptive manner by taking into account the channel conditions and QoS requirements. Such flexibility of our proposed policy leads to offering QoS guarantees effectively and. at the same time, maximizing the throughput. Simulations are used to verify the performance of the proposed scheduling policy. Experimental results show that our proposal can provide guaranteed throughput and maximum delay bound more efficiently compared to other policies.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.161-169
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• 2009

The development of Wireless Multimedia Sensor Networks(WMSNs) is getting realized in accordance with the increased demands to provide multimedia data transmission service such as CCTV movie, image chapter information, audio information based on wireless sensor network. It is very important to provide the differentiated quality assurance of service. In this paper, we propose a sensor medium access control protocol based on DSMAC, which provides differentiated Quality of Service(QoS) for delay. A proposed protocol is able to reduce the delay without increasing the energy consumption by adaptively changing the duty cycle according to the buffer occupancy. Simulation results show that the new MAC protocol performs better in terms of latency than S-MAC and DSMAC.