• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.434-441
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• 2005

For LDPC decoding, received symbols are splitted bit by bit based using the received in-phase and quadrature components. The method of bit-splitting is affected on decoding performance because its method depend on distance over symbol constellation. Therefore this paper propose the bit split method using the sector information with sacrifice a little performance loss compared to Euclidean distance method. Futhermore DVB-S2 specification supports BC(Backward Compactible) mode which using the hierarchical modulation method, this paper also analyze the decoding performance according to deviation angle of 8PSK constellation for various LDPC coding rates.

• 한국전산유체공학회:학술대회논문집
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• 2002.05a
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• pp.8-15
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• 2002

For the large scale computation of turbulent flows around an arbitrarily shaped body, a parallel LES (large eddy simulation) code has been recently developed in which domain decomposition method is adopted. METIS and MPI (message Passing interface) libraries are used for domain partitioning and data communication between processors, respectively. For unsteady computation of the incompressible Wavier-Stokes equation, 4-step splitting finite element algorithm [1] is adopted and Smagorinsky or dynamic LES model can be chosen fur the modeling of small eddies in turbulent flows. For the validation and performance-estimation of the parallel code, a three-dimensional laminar flow generated by natural convection inside a cube has been solved. Then, we have solved the turbulent flow around MIRA (Motor Industry Research Association) model at $Re = 2.6\times10^6$, which is based on the model height and inlet free stream velocity, using 32 processors on IBM SMP cluster and compared with the existing experiment.

• Journal of Communications and Networks
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• v.18 no.2
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• pp.173-181
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• 2016

In this paper, we address a new robust optimization problem in a multiuser multiple-input single-output broadcasting system with simultaneous wireless information and power transmission, where a multi-antenna base station (BS) sends energy and information simultaneously to multiple users equipped with a single antenna. Assuming that perfect channel-state information (CSI) for all channels is not available at the BS, the uncertainty of the CSI is modeled by an Euclidean ball-shaped uncertainty set. To optimally design transmit beamforming weights and receive power splitting, an average total transmit power minimization problem is investigated subject to the individual harvested power constraint and the received signal-to-interference-plus-noise ratio constraint at each user. Due to the channel uncertainty, the original problem becomes a homogeneous quadratically constrained quadratic problem, which is NP-hard. The original design problem is reformulated to a relaxed semidefinite program, and then two different approaches based on convex programming are proposed, which can be solved efficiently by the interior point algorithm. Numerical results are provided to validate the robustness of the proposed algorithms.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.39-44
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• 2002

In this paper, in order to improve the performance of TCP short traffic application services in wireless Internet environments, the Split-ACKs (SPACK) scheme is proposed. In wireless networks, unlike wired networks, packet losses will occur more often due to high bit error rates. Therefore, each packet loss over wireless lints results in congestion control procedure of TCP being invoked at the source. This causes severe end-to-end Performance degradation of TCP. In this paper, to alleviate the TCP Performance, the SPACK method, split acknowledgement Packets in the base station, is proposed. Using computer simulation, the performance of TCP using SPACK is analysed and shows better performance than traditional TCP Protocol.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.1
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• pp.21-24
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• 2017

Passive millimeter wave (MMW) imaging penetrates clothing to detect concealed objects. The distances extraction to the concealed objects is critical for the security and defense. In this paper, we address a passive stereo 3 mm MMW imaging system to extract the longitudinal distance to the concealed object. The concealed object area is segmented and extracted by the k-means clustering algorithm with splitting initialization. The distance to the concealed object is estimated by the corresponding centers of the segmented objects. In the experimental two pairs (each pair for horizontal and vertical polarization) of stereo MMW images are obtained to estimate distances to concealed objects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3086-3101
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• 2021

To supply precise marketing and differentiated service for the electric power service department, it is very important to predict the customers with high sensitivity of electric power failure. To solve this problem, we propose a novel grouped 𝑙_1/2 sparsity constrained logistic regression method for sensitivity assessment of electric power failure. Different from the 𝑙₁ norm and k-support norm, the proposed grouped 𝑙_1/2 sparsity constrained logistic regression method simultaneously imposes the inter-class information and tighter approximation to the nonconvex 𝑙₀ sparsity to exploit multiple correlated attributions for prediction. Firstly, the attributes or factors for predicting the customer sensitivity of power failure are selected from customer sheets, such as customer information, electric consuming information, electrical bill, 95598 work sheet, power failure events, etc. Secondly, all these samples with attributes are clustered into several categories, and samples in the same category are assumed to be sharing similar properties. Then, 𝑙_1/2 norm constrained logistic regression model is built to predict the customer's sensitivity of power failure. Alternating direction of multipliers (ADMM) algorithm is finally employed to solve the problem by splitting it into several sub-problems effectively. Experimental results on power electrical dataset with about one million customer data from a province validate that the proposed method has a good prediction accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1975-1988
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• 2019

Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.2047-2066
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• 2024

In order to improve the coverage and achieve massive spectrum access, non-orthogonal multiple access (NOMA) technology is applied in millimeter wave massive multiple-input multiple-output (mMIMO) communication network. However, the power assumption of active sensors greatly limits its wide applications. Recently, Intelligent Reconfigurable Surface (IRS) technology has received wide attention due to its ability to reduce power consumption and achieve passive transmission. In this paper, spectral efficiency maximum problem in the millimeter wave mMIMO-NOMA system with IRS is considered. The sparse RF chain antenna structure is designed at the base station based on continuous phase modulation. Furthermore, a joint optimization problem for power allocation, power splitting, analog precoding and IRS reconfigurable matrices are constructed, which aim to achieve the maximum spectral efficiency of the system under the constraints of user's quality of service, minimum energy harvesting and total transmit power. A three-stage iterative algorithm is proposed to solve the above mentioned non-convex optimization problems. We obtain the local optimal solution by fixing some optimization parameters firstly, then introduce the relaxation variables to realize the global optimal solution. Simulation results show that the spectral efficiency of the proposed scheme is superior compared to the conventional system with phase shifter modulation. It is also demonstrated that IRS can effectively assist mmWave communication and improve the system spectral efficiency.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.627-630
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• 2014

The latest video coding standard, high efficiency video coding (HEVC) achieves high coding efficiency by employing a quadtree-based coding unit (CU) block partitioning structure which allows recursive splitting into four equally sized blocks. At each depth level, each CU is partitioned into variable sized blocks of prediction units (PUs). However, the determination of the best CU partition for each coding tree unit (CTU) and the best PU mode for each CU causes a dramatic increase in computational complexity. To reduce such computational complexity, we propose a fast PU decision algorithm that early terminates PU search. The proposed method skips the computation of R-D cost for certain PU modes in the current CU based on the best mode and the rate-distortion (RD) cost of the upper depth CU. Experimental results show that the proposed method reduces the computational complexity of HM12.0 to 18.1% with only 0.2% increases in BD-rate.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.354-362
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• 2012

Recently, High Efficiency Video Coding (HEVC) is under development jointly by MPEG and ITU-T for the next international video coding standard. Compared to the previous standards, HEVC supports variety of splitting units, such as coding unit (CU), prediction unit (PU), and transform unit (TU). Among them, it has been known that the recursive quadtree structure of CU can improve the coding efficiency while the encoding complexity is increased significantly. In this paper, a simple conditional probability to predict the early termination condition of recursive unit structure is introduced. The proposed conditional probability is estimated based on Bayes' formula from local statistics of rate-distortion costs in encoder. Experimental results show that the proposed method can reduce the total encoding time by about 32% according to the test configuration while the coding efficiency loss is 0.4%-0.5%. In addition, the encoding time can be reduced by 50% with 0.9% coding efficiency loss when the proposed method was used jointly with HM4.0 early CU termination algorithm.