• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.2
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• pp.37-43
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• 2009

In this study, multi-channel digital hearing aid algorithm for low power system is proposed. First, MDCT(Modified Discrete Cosine Transform) method converts time domain of input speech signal into frequency domain of it. Output signal from MDCT makes a group about each channel, and then each channel signal adjusts a gain using LCF(Loudness Compensation Function) table depending on hearing loss of an auditory person. Finally, compensation signal is composed by TDAC and IMDCT. Its all of process make progress 16-bit fixed-point operation. We use fast-MDCT instead of MDCT for reducing system complexity and previously computed tables instead of log computation for estimating a gain. This algorithm evaluate through computer simulation.

• Nuclear Engineering and Technology
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• v.48 no.2
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• pp.368-375
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• 2016

A sodiume-water reaction takes place when high-pressured water vapor leaks into sodium through a tiny defect on the surface of the heat transfer tube in a steam generator of the sodium-cooled fast reactor. The sodiume-water reaction brings deterioration of the mechanical strength of the heat transfer tube at the initial leakage site. As a result, it damages the crack itself, which may eventually enlarge into a larger opening. This self-enlargement is called "self-wastage phenomenon." In this study, a simulant experiment was proposed to reproduce the self-enlargement of a crack and to evaluate the mechanism of the self-wastage. The damage on the surface of the crack was simulated by making the neutralization reaction with hydrochloric acid solution and sodium hydroxide solution. A numerical investigation was carried out to validate the feasibility of the approach and to determine experimental conditions. From the computation results, it is observed that when 5M HCl is injected into 5M of NaOH with 0.05 m/s inlet velocity, the temperature at the surface near the crack increased over 319.26 K. The computational results show that the self-wastage phenomenon is capable of being reproduced by the simulant experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2240-2254
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• 2021

We investigate the channel allocation problem in an ultra-dense device-to-device (D2D) enabled cellular network in underlaying mode where multiple D2D users are forced to share the same channel. Two kinds of low complexity solutions, which just require partial channel state information (CSI) exchange, are devised to resolve the combinatorial optimization problem with the quality of service (QoS) guaranteeing. We begin by sorting the cellular users equipment (CUEs) links in sequence in a matric of interference tolerance for ensuring the SINR requirement. Moreover, the interference quota of CUEs is regarded as one kind of communication resource. Multiple D2D candidates compete for the interference quota to establish spectrum sharing links. Then base station calculates the occupation of interference quota by D2D users with partial CSI such as the interference channel gain of D2D users and the channel gain of D2D themselves, and carries out the channel allocation by setting different access priorities distribution. In this paper, we proposed two novel fast matching algorithms utilize partial information rather than global CSI exchanging, which reduce the computation complexity. Numerical results reveal that, our proposed algorithms achieve outstanding performance than the contrast algorithms including Hungarian algorithm in terms of throughput, fairness and access rate. Specifically, the performance of our proposed channel allocation algorithm is more superior in ultra-dense D2D scenarios.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1552-1559
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• 2021

Convolution neural networks (CNNs) show notable performance in image processing and are used as representative core models. CNNs extract and learn features from large amounts of train dataset. In general, it has a structure in which a convolution layer and a fully connected layer are stacked. The core of CNN is the convolution layer. The size of the kernel used for feature extraction and the number that affect the depth of the feature map determine the amount of weight parameters of the CNN that can be learned. These parameters are the main causes of increasing the computational complexity and memory usage of the entire neural network. The most computationally expensive components in CNNs are fully connected and spatial convolution computations. In this paper, we propose a Fourier Convolution Neural Network that performs the operation of the convolution layer in the Fourier domain. We work on modifying and improving the amount of computation by applying the fast fourier transform method. Using the MNIST dataset, the performance was similar to that of the general CNN in terms of accuracy. In terms of operation speed, 7.2% faster operation speed was achieved. An average of 19% faster speed was achieved in experiments using 1024x1024 images and various sizes of kernels.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2047-2052
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• 2023

Risk-informed approach has been widely applied in the safety design, regulation, and operation of nuclear reactors. It has been commonly accepted that risk-informed design optimization should be used in the innovative reactor designs to make nuclear system highly safe and reliable. In spite of the risk-informed approach has been used in some advanced nuclear reactors designs, such as Westinghouse IRIS, Gen-IV sodium fast reactors and lead-based fast reactors, the process of risk-informed design of nuclear reactors is hardly to carry out when passive system reliability should be integrated in the framework. A practical method for new passive safety reactors based on probabilistic safety assessment (PSA) and passive system reliability analyze linking is proposed in this paper. New three-dimension frequency-consequence curve based on risk concept with three variables is used in this method. The proposed method has been applied to the determination optimization of design options selection in a 10 MWth lead-based research reactor(LR) to obtain one optimized system design in conceptual design stage, using the integrated reliability and probabilistic safety assessment program RiskA, and the computation resources and time consumption in this process was demonstrated reasonable and acceptable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.881-902
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• 2024

Fast decision support systems and accurate diagnosis have become significant in the rapidly growing healthcare sector. As the number of disparate medical IoT devices connected to the human body rises, fast and interrelated healthcare data retrieval gets harder and harder. One of the most important requirements for the Healthcare Internet of Things (HIoT) is semantic interoperability. The state-of-the-art HIoT systems have problems with bandwidth and latency. An extension of cloud computing called fog computing not only solves the latency problem but also provides other benefits including resource mobility and on-demand scalability. The recommended approach helps to lower latency and network bandwidth consumption in a system that provides semantic interoperability in healthcare organizations. To evaluate the system's language processing performance, we simulated it in three different contexts. 1. Polysemy resolution system 2. System for hyponymy-hypernymy resolution with polysemy 3. System for resolving polysemy, hypernymy, hyponymy, meronymy, and holonymy. In comparison to the other two systems, the third system has lower latency and network usage. The proposed framework can reduce the computation overhead of heterogeneous healthcare data. The simulation results show that fog computing can reduce delay, network usage, and energy consumption.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.36 no.6
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• pp.413-418
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• 2017

When measuring the radiated noise of an underwater vehicle, range information between acoustic source and receiver is an important evaluating factor, but it cannot use GPS. There is a method of using the cross correlation for finding the range of the acoustic source instead of the GPS. However, this method has heavy computational loads. This paper proposes a fast Fourier transform based method with a relatively small amount of computation to estimate the range of a source. The proposed method estimates Doppler frequencies of CW signals received at multiple receivers by fast Fourier transform and estimates the source range by comparing theoretical Doppler frequencies map previously calculated by a receiver position and source depth information. Simulation and lake trial were performed to verify the performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.4
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• pp.372-378
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• 2010

This paper propose the fast motion estimation algorithm with adaptive search range adjustment using motion activities of temporal and spatial neighbor blocks. The existing fast motion estimation algorithms with adaptive search range adjustment use the maximum motion vector of all blocks in the reference frame. So these algorithms may not control a optimum search range for slow moving block in current frame. The proposed algorithm use the maximum motion vector of neighbor blocks in the reference frame to control a optimum search range for slow moving block. So the proposed algorithm can reduce computation time for motion estimation. The experiment results show that the proposed algorithm can reduce the number of search points about 15% more than Simple Dynamic Search Range(SDSR) algorithm while maintaining almost the same bit-rate and motion estimation error.

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.140-146
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• 2011

In this paper, we propose a fast object classification method based on texture and color information for video surveillance. We take the advantage of local patches by extracting SURF and color histogram from images. SURF gives intensity content information and color information strengthens distinctiveness by providing links to patch content. We achieve the advantages of fast computation of SURF as well as color cues of objects. We use Bag of Word models to generate global descriptors of a region of interest (ROI) or an image using the local features, and Na$\ddot{i}$ve Bayes model for classifying the global descriptor. In this paper, we also investigate discriminative descriptor named Scale Invariant Feature Transform (SIFT). Our experiment result for 4 classes of the objects shows 95.75% of classification rate.