• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.253-260
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• 2018

The acoustic communication channel in shallow underwater is typically shown as time-varying multipath fading channel characteristics. The received signal through channel transmission cause inter-symbol interference (ISI) owing to multiple components of different time delay and amplitude. To compensate for this, several techniques have been used, and one of them is acoustic equalizer. In this study, we used four equalizers - feed forward equalizer (FFE), decision directed equalizer (DDE), decision feedback equalizer (DFE) and combination DDE with DFE to compensate ISI. And we applied two adaptive algorithms to adjust coefficient of equalizers - normalized least mean square algorithm and recursive least square algorithm. As result, we found that it has a significant performance improvement over 6 dB on SNR in nonlinear equalizer. By combination of DFE and DDE has almost best performance in any case.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.11-17
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• 2009

This paper presents a new adaptive relay selection scheme for a regenerative orthogonal frequency division multiplexing access(OFDMA) relay network with fairness constrains. In the Proposed scheme, we select the best M relays out of a set of K potential relays to maximize system capacity. Among these selected relays, subcarriers are reallocated to satisfy fairness constraints as well as to minimize the degradation of the system performance. Afterwards, power allocation is performed for each subcarrier based on the water-filling method to enhance the performance improvement. By using the trade-off relationship between the system capacity and the fairness, the modified version of proposed scheme is also investigated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3166-3179
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• 2013

A pre-processing system for adaptive noise removal is proposed based on the principle of identifying and filtering object regions and background regions. Human perception of images depends on bright, well-focused object regions; these regions can be treated with the best filters, while simpler filters can be applied to other regions to reduce overall computational complexity. In the proposed method, bright region segmentation is performed, followed by segmentation of object and background regions. Noise in dark, background, and object regions is then removed by the median, fast bilateral, and bilateral filters, respectively. Simulations show that the proposed algorithm is much faster than and performs nearly as well as the bilateral filter (which is considered a powerful noise removal algorithm); it reduces computation time by 19.4 % while reducing PSNR by only 1.57 % relative to bilateral filtering. Thus, the proposed algorithm remarkably reduces computation while maintaining accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3286-3300
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• 2016

High Efficiency Video Coding (HEVC) Standard, as the latest coding standard, introduces satisfying compression structures with respect to its predecessor Advanced Video Coding (H.264/AVC). The new coding standard can offer improved encoding performance compared with H.264/AVC. However, it also leads to enormous computational complexity that makes it considerably difficult to be implemented in real time application. In this paper, based on machine learning, a fast partitioning method is proposed, which can search for the best splitting structures for Intra-Prediction. In view of the video texture characteristics, we choose the entropy of Gray-Scale Difference Statistics (GDS) and the minimum of Sum of Absolute Transformed Difference (SATD) as two important features, which can make a balance between the computation complexity and classification performance. According to the selected features, adaptive decision trees can be built for the Coding Units (CU) with different size by offline training. Furthermore, by this way, the partition of CUs can be resolved as a binary classification problem. Experimental results have shown that the proposed algorithm can save over 34% encoding time on average, with a negligible Bjontegaard Delta (BD)-rate increase.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3090-3102
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• 2015

The accuracy of an augmented reality (AR) application is highly dependent on the resolution of the object's image and the device's computational processing capability. Naturally, a mobile smart device equipped with a high-resolution camera becomes the best platform for portable AR services. AR applications require significant energy consumption and very fast response time, which are big burdens to the smart device. However, there are very few ways to overcome these burdens. Computation offloading via mobile cloud computing has the potential to provide energy savings and enhance the performance of applications executed on smart devices. Therefore, in this paper, adaptive mobile computation offloading of mobile AR applications is considered in order to determine optimal offloading points that satisfy the required quality of experience (QoE) while consuming minimum energy of the smart device. AR feature extraction based on SURF algorithm is partitioned into sub-stages in order to determine the optimal AR cloud computational offloading point based on conditions of the smart device, wireless and wired networks, and AR service cloud servers. Tradeoffs in energy savings and processing time are explored also taking network congestion and server load conditions into account.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.6
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• pp.730-740
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• 2018

Hydrofoil is the direct component to generate thrust for underwater glider. It is significant to improve propulsion efficiency of hydrofoil. This study optimizes the shape of a hydrofoil using Free-Form Deformation (FFD) parametric approach and Surrogate-based Optimization (SBO) algorithm. FFD approach performs a volume outside the hydrofoil and the position changes of control points in the volume parameterize hydrofoil's geometric shape. SBO with adaptive parallel sampling method is regarded as a promising approach for CFD-based optimization. Combination of existing sampling methods is being widely used recently. This paper chooses several well-known methods for combination. Investigations are implemented to figure out how many and which methods should be included and the best combination strategy is provided. As the hydrofoil can be stretched from airfoil, the optimizations are carried out on a 2D airfoil and a 3D hydrofoil, respectively. The lift-drag ratios are compared among optimized and original hydrofoils. Results show that both lift-drag-ratios of optimized hydrofoils improve more than 90%. Besides, this paper preliminarily explores the optimization of hydrofoil with root-tip-ratio. Results show that optimizing 3D hydrofoil directly achieves slightly better results than 2D airfoil.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.3
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• pp.312-319
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• 2011

In this paper, a new linearization algorithm for DPD(Digital PreDistorter) is suggested. This new algorithm uses DFP(Davidon-Fletcher-Powell) method. This algorithm is more accurate than that of the existing algorithms, and this method renew the best-fit value in every routine with out setting the initial value of step-size. In modeling power amplifier, the memory polynomial model which can model the memory effect of the power amplifier is used. And the overall structure of linearizer is based on an indirect learning architecture. In order to verify for performance of proposed algorithm, we compared with LMS(Least Mean-Squares), RLS(Recursive Least squares) algorithm.

• Journal of KIISE
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• v.41 no.12
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• pp.1090-1098
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• 2014

In this paper, an improved ACDE (Adaptive Cauchy Differential Evolution) algorithm with faster convergence speed, called ACDE2, is suggested. The baseline ACDE algorithm uses a "DE/rand/1" mutation strategy to provide good population diversity, and it is appropriate for solving multimodal optimization problems. However, the convergence speed of the mutation strategy is slow, and it is therefore not suitable for solving unimodal optimization problems. The ACDE2 algorithm uses a "DE/current-to-best/1" mutation strategy in order to provide a fast convergence speed, where a control parameter initialization operator is used to avoid converging to local optimization. The operator is executed after every predefined number of generations or when every individual fails to evolve, which assigns a value with a high level of exploration property to the control parameter of each individual, providing additional population diversity. Our experimental results show that the ACDE2 algorithm performs better than some state-of-the-art DE algorithms, particularly in unimodal optimization problems.

• Journal of Wetlands Research
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• v.21 no.4
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• pp.267-280
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• 2019

Adaptive Management (AM) is one of the best available approaches for managing natural resources in the presence of uncertainty. In spite of the limitations, AM has been widely applied in nature resource management policies and plans internationally, while application of AM in nature resource management in Korea is limitedly used. Accordingly, this study reviews application of AM in nature resource management research in Korea with respect to its definitions, procedures, impediments and considerations. The present study also reviews recent ecological modelling studies which is an essential component of AM approach. Finally, management of artificial sea forest, coastal wetlands and fisheries are suggested as the recommended fields to adopt AM.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1572-1582
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• 2011

The rapid growth of UnderWater Acoustic Sensor Networks (UW-ASNs) has led researchers to enhance underwater MAC protocols against limitations existing in underwater environment. We propose the customized robust real-time packet inspection mechanism with addressing the problem of the search for the data packet loss and network performance quality analysis in UW-ASNs, and describe our experiences using this approach. The goal of this work is to provide a framework to assess the network real-time performance quality. We propose a customized and adaptive mechanism to detect, monitor and analyze the data packets according to the MAC protocol standards in UW-ASNs. The packet analyzing method and software we propose is easy to implement, maintain, update and enhance. We take input stream as real data packets from sniffer node in capture mode and perform fully analysis. We were interested in developing software and hardware designed tool with the same capabilities which almost all terrestrial network packet sniffers have. Experimental results confirm that the best way to achieve maximum performance requires the most adaptive algorithm. In this paper, we present and offer the proposed packet analyzer, which can be effectively used for implementing underwater MAC protocols.