• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.49-54
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• 2011

In this paper, End-to-End VoIP(Voice over Internet Protocol) performance over large scale MANET(Mobile Ad-hoc Networks) is evaluated. VoIP implementation model, which can be used for large scale MANET, is suggested through this evaluation. VoIP simulator based on NS-2 network simulator is used for performance measurement. Call connection ratio as a connection performance, MOS and network delay as a transmission performance, packet loss rate as other performance is measured with this simulation. Finally, maximum $10{\sim}15km^2$ as a single MANET, 500 nodes and 100 call connections is suggested for VoIP implementation and operation conditions over large scale MANETs.

• Proceedings of the Korean Vacuum Society Conference
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• 2000.02a
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• pp.164-164
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• 2000

Since Au-Pt alloys have various atomic structures depending upon composition and annealing temperature, it is very interesting to investigate the electronic structures of alloys. We studied the changes of the electronic structure I the Au-Pt alloys by x-ray absorption near edge spectroscopy (XANES). Two kinds of Au-Pt alloy samples were prepared by arc melting methods and ion-beam-mixing technique. The Pt L2, 3-edge and Au L2, 3-edge X-ray absorption spectra (XPS) were measured with the electron yield mode detector at the 3C1 beam line of the Pohang Light Source (PLS). It was found that there was a substantial decrease in the area of the Pt L2, 3 white lines compared with that of pure Pt. The observed decrease in white line area was attributed to an increase in the number of pure Pt. The observed decrease in white line area was attributed to an increase in the number of 5d-electrons at the Pt site upon alloy formation. However, the Au L2, 3 edge spectra for Au-Pt alloys are all similar to that of pure Au. This implies that the 5d hole count of Au is not changed by alloy formation with Pt.

• Proceedings of the Korean Vacuum Society Conference
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• 2003.02a
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• pp.84-84
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• 2003

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.95-98
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• 1996

Universal Learning Network(U.L.N.), which can model and control the large scale complicated systems naturally, consists of nonlinearly operated nodes and multi-branches that may have arbitrary time delays including zero or minus ones. Therefore, U.L.N. can be applied to many kinds of systems which are difficult to be expressed by ordinary first order difference equations with one sampling time delay. It has been already reported that learning algorithm of parameter variables in U.L.N. by forward and backward propagation is useful for modeling, managing and controlling of the large scale complicated systems such as industrial plants, economic, social and life phenomena. But, in the previous learning algorithm of U.L.N., time delays between the nodes were fixed, in other words, criterion function of U.L.N. was improved by adjusting only parameter variables. In this paper, a new learning algorithm is proposed, where not only parameter variables but also time delays between the nodes can be adjusted. Because time delays are integral numbers, adjustment of time delays can be carried out by a kind of random search procedure which executes intensified and diversified search in a single framework.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.4
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• pp.478-485
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• 2013

This paper focuses on the design and control of a new concept for wind turbines with a planetary gearbox to realize a power split. This concept, where the generated wind power is split into two parts, is to increase the utilization of the wind power and may be particularly suitable for large scale off-shore wind turbines. In order to reduce the cost of the power electronic devices, a synchronous generator, which is driven by the planetary gear, is directly connected to the power grid without electronic converter. A servo drive, which functions as the control actuator, is connected to the power grid by a power electronic converter. With small scale power electronic device, the current harmonics can also be reduced. The speed of the main shaft is controlled to track the optimal tip speed ratio. Meanwhile the speed of the synchronous generator is controlled to stay at the synchronous speed. The minimum rated power of the servo motor and the converter, is studied and discussed in this paper. Different variants of the wind turbine with a planetary gear are also compared. The controller for optimal tip speed ratio and synchronous speed tracking is given.

• Asian-Australasian Journal of Animal Sciences
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• v.5 no.2
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• pp.229-235
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• 1992

The usefulness of a portable linear electronic scanner. B-mode ultrasonic machine, was evaluated for estimating the longissimus muscle area from ultrasonic measurement of the muscle depth in 22 live pigs. The electronic scanner was easy to operate for muscle measurements in live pigs, which did not have to be held but were caged. The cross-sectional images of longissimus muscle and covering muscles and fat appeared on the monitor with grey scale in real time. It was easy to identify the ultrasonograms of fat and muscular tissues because the images differed in the degree of the grey scale. The longissimus muscle had less echogenic image than the other muscles. The boundary lines between first, second or third layers of backfat and the longissimus muscle were distinct on the ultrasonogram. The ultrasonic measurement at the shoulder was not acceptable because of the unstable measurements and the complex tissue structure. The repeatabilities for the measurements of longissimus muscle depth at one-half body length and last rib were acceptable. The simple correlation coefficients between ultrasonic estimates of the muscle depth in live pigs and the actual areas in the carcass, were 0.50 and 0.55 at the last rib and the one-half body length, respectively. Therefore, those positions were similarly suitable to measure. The method of electronic scanner for determining longissimus muscle area from the muscle depth was suitable for practical use in the field because of the simple and inexpensive technique.

• Proceedings of the KIEE Conference
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• 2002.04a
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• pp.133-138
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• 2002

The developments of the solar and the wind power energy are necessary since the future alternative energies that have no pollution and no limitation are restricted. Currently power generation system of MW scale has been developed, but it still has a few faults with the weather condition. In order to solve these existing problems, combined generation system of photovoltaic(400W) and wind power generation system(400W) was suggested. It combines wind power and solar energy to have the supporting effect from each other. However, since even combined generation system cannot always generate stable output with ever-changing weather condition, power compensation device that uses elastic energy of spiral spring to combined generation system was also added for the present study. In an experiment, when output of system gets lower than 12V(charging voltage), power was continuously supplied to load through the inverter by charging energy obtained from generating rotary energy of spiral spring operates in small scale generator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4648-4663
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• 2020

This paper proposes the Lempel-Ziv 4(LZ4) compression accelerator optimized for scale-out servers in data centers. In order to reduce CPU loads caused by compression, we propose an accelerator solution and implement the accelerator on an Field Programmable Gate Array(FPGA) as heterogeneous computing. The LZ4 compression hardware accelerator is a fully pipelined architecture and applies 16 dictionaries to enhance the parallelism for high throughput compressor. Our hardware accelerator is based on the 20-stage pipeline and dictionary architecture, highly customized to LZ4 compression algorithm and parallel hardware implementation. Proposing dictionary architecture allows achieving high throughput by comparing input sequences in multiple dictionaries simultaneously compared to a single dictionary. The experimental results provide the high throughput with intensively optimized in the FPGA. Additionally, we compare our implementation to CPU implementation results of LZ4 to provide insights on FPGA-based data centers. The proposed accelerator achieves the compression throughput of 639MB/s with fine parallelism to be deployed into scale-out servers. This approach enables the low power Intel Atom processor to realize the Hadoop storage along with the compression accelerator.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.474-483
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• 2018

In this paper, we propose a multi-scale high dynamic range (HDR) tone mapping algorithm using guided image filter (GIF). The GIF is used to divide an image into a base layer and a detail layer, then the range of the detail layer is reduced with a compression function to enhance the detail information of the image. However, in most cases, an image includes the detail and edge information in different scales. That is to say, it is difficult to represent all detail features under a certain scale, and a single-scale image decomposition method is not free from artifacts around edges. To solve the problems, the multi-scale image decomposition method is proposed. It utilizes the detail layers of several scale to determine how much edge is preserved. Experiment results show that the proposed algorithm has better image performance in preserving edge compared to conventional algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.301-307
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• 2024

This study introduces a novel cascade fusion architecture aimed at enhancing thermal images across various scale conditions. The processing of thermal images at multiple scales has been challenging due to the limitations of existing methods that are designed for specific scales. To overcome these limitations, this paper proposes a unified framework that utilizes cascade feature fusion to effectively learn multi-scale representations. Confidence maps from different image scales are fused in a cascaded manner, enabling scale-invariant learning. The architecture comprises end-to-end trained convolutional neural networks to enhance image quality by reinforcing mutual scale dependencies. Experimental results indicate that the proposed technique outperforms existing methods in multi-scale thermal image enhancement. Performance evaluation results are provided, demonstrating consistent improvements in image quality metrics. The cascade fusion design facilitates robust generalization across scales and efficient learning of cross-scale representations.