• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.411-417
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• 2007

The rate control is an essential component in video coding to provide better quality under given coding constraints, such as channel capacity, frame rates, etc. In general, source data cannot be described as a single distribution in a video coding, hence it can cause an exhaustive approximation problem. It drops a coding efficiency under weak channel environments, such as mobile communications. In this paper, we design a new quantization parameter decision model that is based on a rate-distortion function of generalized Gaussian distribution. In order to adaptively express various source data distribution, we decide a shape parameter by observing a ratio of samples, which have a small value. For experiment, the proposed algorithm is implemented into H.264/AVC video codec, and its performance is compared with that of MPEG-2 TM5, H.263 TMN8 rate control algorithm. As shown in simulation results, the proposed algorithm provides an improved quality rather than previous algorithms and generates the number of bits closed to the target bits.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.67-75
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• 2013

The advantages of the orthogonal frequency division multiplexing (OFDM) are high spectral efficiency, resiliency to RF interference, and lower multi-path distortion. To further utilize vast channel capacity of the multiuser OFDM, one has to find the efficient adaptive subchannel and bit allocation among users. In this paper, we compare the performance of the linear programming dual of the 0-1 integer programming formulation with the existing convex optimization approach for the optimal subchannel and bit allocation problem of the multiuser OFDM. Utilizing tight lower bound provided by the LP dual formulation, we develop a primal heurisitc algorithm based on the LP dual solution. The performance of the primal heuristic is compared with MAO, ESA heuristic solutions, and integer programming solution on MATLAB simulation on a system employing M-ary quadrature amplitude modulation (MQAM) assuming a frequency-selective channel consisting of three independent Rayleigh multi-paths.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4819-4834
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• 2015

The spectral efficiency of cellular networks can be improved when proximate users engage in device-to-device (D2D) communications to communicate directly without going through a base station. However, D2D communications that are not properly designed may generate interference with existing cellular networks. In this paper, we study resource allocation and power control to minimize the probability of an outage and maximize the overall network throughput. We investigate three power control-based schemes: the Partial Co-channel based Overlap Resource Power Control (PC.OVER), Fractional Frequency Reuse based Overlap Resource Power Control (FFR.OVER) and Fractional Frequency Reuse based Adaptive Power Control (FFR.APC) and also compare their performance. In PC.OVER, a certain portion of the total bandwidth is dedicated to the D2D. The FFR.OVER and FFR.APC schemes combine the FFR techniques and the power control mechanism. In FFR, the entire frequency band is partitioned into two parts, including a central and edge sub-bands. Macrocell users (mUEs) transmit using uniform power in the inner and outer regions of the cell, and in all three schemes, the D2D receivers (D2DRs) transmit with low power when more than one D2DRs share a resource block (RB) with the macrocells. For PC.OVER and FFR.OVER, the power of the D2DRs is reduced to its minimum, and for the FFR.APC scheme, the transmission power of the D2DRs is iteratively adjusted to satisfy the signal to interference ratio (SIR) threshold. The three schemes exhibit a significant improvement in the overall system capacity as well as in the probability of a user outage when compared to a conventional scheme.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.677-693
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• 2013

IPCC showed that calculation of climate vulnerability index requires standardization process of various proxy variables for the estimation of climate exposure, sensitivity, and adaptive capacity. In this study, four different methodologies of standardization methods: Z-score, Rescaling, Ranking, and Distance to the reference country, are employed to evaluate climate vulnerability-VRI (Vulnerability-Resilience Indicator) over Korean peninsula, and the error ranges of VRI, arising from employing the different standardization are estimated. All of proxy variables are provided by CCGIS (Climate Change adaptation toolkit based on GIS) which hosts information on both past and current socio-economic data and climate and environmental IPCC SRES (A2, B1, A1B, A1T, A1FI, and A1 scenarios) climate data for the decades of 2000s, 2020s, 2050s, and 2100s. The results showed that Z-score and Rescaling methods showed statistically undistinguishable results with minor differences of spatial distribution, while Ranking and Distance to the reference country methods showed some possibility to lead the different ranking of VRI among South Korean provinces, depending on the local characteristics and reference province. The resultant VRIs calculated from different standardization methods showed Cronbach's alpha of more than 0.84, indicating that all of different methodologies were overall consistent. Similar horizontal distributions were shown with the same trends: VRI increases as province is close to the coastal region and/or it close toward lower latitude, and decreases as it is close to urbanization area. Other characteristics of the four different standardization are discussed in this study.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.76-84
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• 2007

The goal of this paper is to improve the watermarking performance using the following two methods; watermark estimation and low density parity check (LDPC) codes. For a blind watermark decoding, the power of a host image, which is hundreds times greater than the watermark power, is the main noise source. Therefore, a technique that can reduce the effect of the power of the host image to the detector is required. To this end, we need to estimate watermark from the watermarked image. In this paper, the watermark estimation is done by an adaptive estimation method with the generalized Gaussian distribution modeling of sub-band coefficients in the wavelet domain. Since the watermark capacity as well as the error rate can be improved by adopting optimum decoding principles and error correcting codes (ECC), we employ the LDPC codes for the decoding of the estimated watermark. Also, in LDPC codes, the knowledge about the noise power can improve the error correction capability. Simulation results demonstrate the superior performance of the proposed algorithm comparing to LDPC decoding with other estimation-based watermarking algorithms.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.80-91
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• 2010

Due to the convergence of broadcasting and communications, IPTV services are spotlighted as the that next-generation multimedia services. IPTV services should have functionality such as unlimited channel capacity, extension of media, QoS awareness and are required increasing traffic and quality control technology to adapt the attributes of IPTV service. Consequently, flow based quality control techniques are needed. Therefore, many studies for providing Internet QoS are performed at IETF (Internet Engineering Task Force). As the buffer management mechanism among IP QoS methods, active queue management method such as RED(Random Early Detection) and modified RED algorithms have proposed. However, these algorithms have difficulties to satisfy the requirements of various Internet user QoS. Therefore, in this paper we propose the Flow based AQM(Active Queue Management) algorithm for the multimedia services that request various QoS requirements. The proposed algorithm can converge the packet loss ratio to the target packet loss ratio of required QoS requirements. And we present a performance evaluation by the simulations using the ns-2.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.360-370
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• 2009

Using solar power in wireless sensor networks requires a different approach to energy optimization from networks with battery-based nodes. Solar energy is an inexhaustible supply which can potentially allow a system to run forever, but there are several issues to be considered such as the uncertainty of energy supply and the constraint of rechargeable battery capacity. In this paper, we present SolarSS: a reliable storage system for solar-powered sensor networks, which provides a set of functions, in separate layers, such as sensory data collection, replication to prevent failure-induced data loss, and storage balancing to prevent depletion-induced data loss. SolarSS adapts the level of layers activated dynamically depending on solar energy availability, and provides an efficient resource allocation and data distribution scheme to minimize data loss.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.149-154
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• 2004

In this research, we selected the speech recognition to implement the electric wheelchair system as a method to control it by only using the speech and used DTW (Dynamic Time Warping), which is speaker-dependent and has a relatively high recognition rate among the speech recognitions. However, it has to have small memory and fast process speed performance under consideration of real-time. Thus, we introduced VQ (Vector Quantization) which is widely used as a compression algorithm of speaker-independent recognition, to secure fast recognition and small memory. However, we found that the recognition rate decreased after using VQ. To improve the recognition rate, we applied ART2 (Adaptive Reason Theory 2) algorithm as a post-process algorithm to obtain about 5% recognition rate improvement. To utilize ART2, we have to apply an error range. In case that the subtraction of the first distance from the second distance for each distance obtained to apply DTW is 20 or more, the error range is applied. Likewise, ART2 was applied and we could obtain fast process and high recognition rate. Moreover, since this system is a moving object, the system should be implemented as an embedded one. Thus, we selected TMS320C32 chip, which can process significantly many calculations relatively fast, to implement the embedded system. Considering that the memory is speech, we used 128kbyte-RAM and 64kbyte ROM to save large amount of data. In case of speech input, we used 16-bit stereo audio codec, securing relatively accurate data through high resolution capacity.

• Biomolecules & Therapeutics
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• v.26 no.2
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• pp.175-181
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• 2018

Carbon monoxide (CO) is well-known as toxic gas and intrinsic signaling molecule such as neurotransmitter and blood vessel relaxant. Recently, it has been reported that low concentration of CO exerts therapeutic actions under various pathological conditions including liver failure, heart failure, gastric cancer, and cardiac arrest. However, little has been known about the effect of CO in neurodegenerative diseases like Parkinson's disease (PD). To test whether CO could exert a beneficial action during oxidative cell death in PD, we examined the effects of CO on 6-hydroxydopamine (6-OHDA)-induced cell death in C6 glioma cells. Treatment of CO-releasing molecule-2 (CORM-2) significantly attenuated 6-OHDA-induced apoptotic cell death in a dose-dependent manner. CORM-2 treatment decreased Bax/Bcl2 ratio and caspase-3 activity, which had been increased by 6-OHDA. CORM-2 increased phosphorylation of NF-E2-related factor 2 (Nrf2) which is a transcription factor regulating antioxidant proteins. Subsequently, CORM-2 also increased the expression of heme oxygenase-1 and superoxide dismutases (CuZnSOD and MnSOD), which were antioxidant enzymes regulated by Nrf2. These results suggest that CO released by CORM-2 treatment may have protective effects against oxidative cell death in PD through the potentiation of cellular adaptive survival responses via activation of Nrf2 and upregulation of heme oxygenase-1, leading to increasing antioxidant defense capacity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.709-730
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• 2017

To address the challenge of unprecedented growth in mobile data traffic, ultra-dense network deployment is a cost efficient solution to offload the traffic over some small cells. The overlapped coverage areas of small cells create more than one candidate access points for one mobile user. Signal strength based user association in IEEE 802.11 results in a significantly unbalanced load distribution among access points. However, the effective bandwidth demand of each user actually differs vastly due to their different preferences for mobile applications. In this paper, we formulate a set of non-linear integer programming models for joint user association control and user demand guarantee problem. In this model, we are trying to maximize the system capacity and guarantee the effective bandwidth demand for each user by soft-association control with a software defined network controller. With the fact of NP-hard complexity of non-linear integer programming solver, we propose a Kernighan Lin Algorithm based graph-partitioning method for a large-scale network. Finally, we evaluated the performance of the proposed algorithm for the edge users with heterogeneous bandwidth demands and mobility scenarios. Simulation results show that the proposed adaptive soft-association control can achieve a better performance than the other two and improves the individual quality of user experience with a little price on system throughput.