• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3A
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• pp.311-318
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• 2008

We propose new pulse shapes for FCC-compliant ultra-wideband (UWB) radios. The projections onto convex sets (POCS) technique is used to optimize temporal and spectral shapes of UWB pulses under the constraints of all of the desired UWB signal properties: efficient spectral utilization under the FCC spectral mask, time-limitedness, and good autocorrelation. Simulation results show that for all values of the pulse duration, the new pulse shapes not only meet the FCC spectral mask most efficiently, but also have nearly the same autocorrelation functions. It is also observed that our truncated (i.e., strictly time-limited) pulse shapes outperform the truncated Gaussian monocycle in the BER performance of binary TH-PPM systems for the same pulse durations. The POCS technique provides an effective method for designing UWB pulse shapes in terms of its inherent design flexibility and joint optimization capability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.11
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• pp.625-636
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• 2014

In this paper, we propose a new embedded image compression scheme which uses rate-distortion optimized block coding of wavelet coefficients. Unlike to previous works in which set-partition or block-partition is performed according to the magnitude of wavelet coefficients, the proposed scheme achieves rate-distortion optimization by sorting wavelet coefficients or blocks according to their expected rate-distortion slope. At the same time, it performs the optimized block-partition coding using the expected rate-distortion slope of blocks. The proposed scheme also uses various relationship of wavelet coefficients for the entropy coding. Experimental results demonstrate that the proposed image compression scheme provides better overall performance than the existing embedded coding schemes such as SPIHT and EBCOT, in which the PSNR gains of the proposed scheme are about 0.11~1.16dB and -0.18~0.52dB, respectively.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.1
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• pp.64.1-64.1
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• 2011

MIRIS (Multipurpose Infra-Red Imaging System), is a small infrared space telescope which is being developed by KASI, as the main payload of Science and Technology Satellite 3 (STSAT-3). Two wideband filters (I and H) of the MIRIS enables us to study the cosmic infrared background by detecting the absolute background brightness. The narrow band filter for Paschen ${\alpha}$ emission line observation will be employed to survey the Galactic plane for the study of warm ionized medium and interstellar turbulence. The opto-mechanical design of the MIRIS is optimized to operate around 200K for the telescope, and the cryogenic temperature around 90K for the sensor in the orbit, by using passive and active cooling technique, respectively. The engineering and qualification model of the MIRIS has been fabricated and successfully passed various environmental tests, including thermal, vacuum, vibration and shock tests. The flight model was also assembled and is in the process of system optimization to be launched in 2012 by a Russian rocket. The mission operation scenario and the data reduction software is now being developed. After the successful mission of FIMS (the main payload of STSAT-1), MIRIS is the second Korean space telescope, and will be an important step towards the future of Korean space astronomy.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.483-488
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• 2016

In this paper, we propose a prototype-based classification learning by using the nearest-neighbor rule. The nearest-neighbor is applied to segment the class area of all the training data with hyperspheres, and a hypersphere must cover the data from the same class. The radius of a hypersphere is computed by the mid point of the two distances to the farthest same class point and the nearest other class point. And we transform the prototype selection problem into a set covering problem in order to determine the smallest set of prototypes that cover all the training data. The proposed prototype selection method is designed by a greedy algorithm and applicable to process a large-scale training set in parallel. The prediction rule is the nearest-neighbor rule and the new training data is the set of prototypes. In experiments, the generalization performance of the proposed method is superior to existing methods.

• Journal of Biosystems Engineering
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• v.9 no.2
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• pp.48-57
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• 1984

To analyze the grain transport velocity, which is valuable for optimizing the separation losses, an oscillating appratus for sieve was designed. The grain transport velocity was measured in each combination of three amplitude levels, three rpm levels and four projection angle levels. To analyze the grain transport velocity theortically, two computer programs were developed. And the results from experiment and theoretical analysis were compared. 1. The grain transport velocity was increased with the projection angle of oscillating sieve. Especially when the projection angle is higher than $45^{\circ}$ the grain transport velocity on the flat-plate was not increased but on the racked surface was increased persistently. 2. The grain transport velocity was increased linearly with the frequency of oscillating motion. The speed of driving link must be higher than 350 rpm at 24mm amplitude, 250 rpm at 36 mm amplitude to transport the grain efficiently. 3. The grain transport velocity was increased with the amplitude of oscillating motion. But if the amplitude was smaller than interval of racks, the grain on the racked surface was not transported, even though the projection angle or the speed of revolutionary link was increased. 4. The transport characteristics of a grain varied with the amplitude and projection angle. Especially in the range of 1.5 < K < 2.3 at $45^{\circ}$ projection angle the transportation of grain was successful and the grain motion consisted of sliding movement (forward, backward) and jumping movement, which is considered recommendable for separating process of a combine sieve. 5. The results from theoretical analysis were approximately in accord with that from experiment.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.137-151
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• 2008

H.264/AVC is showed high coding efficiency more than previous video coding standard by using new coding tools. Specially, Variable block-based motion estimation and Rate-Distortion Optimization are very important coding tools in H.264/AVC. These coding tools have high coding efficiency, however the encoder complexity greatly increase due to these coding tools. In this paper, we propose early SKIP mode decision and selective inter/intra mode decision to reduce the computational complexity. Simulation results show that the proposed method could reduce encoding time of the overall sequences by 30% on average than JM 10.2 without noticeable degradation of coding efficiency. Besides, the proposed method runs over twice as fast as the previous proposed Fast Coding Mode Selection method (FCMS)[5].

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.433-440
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• 2014

In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and $CO_2$ emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1686-1693
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• 2014

In this paper, oil-paper samples composed of transformer windings were used to investigate the insulation degradation process subjected to partial discharge (PD), with artificial defects inside to simulate the PD induced insulation degradation. To determine appropriate test voltages, the breakdown time obtained through a group of accelerated electrical degradation tests under high voltages was firstly fitted by two-parameter Weibull model to acquire the average breakdown time, which was then applied to establish the inverse power law life model to choose advisable test voltages. During the electrical degradation process, PD signals were synchronously detected by an ultra-high frequency (UHF) sensor from inception to breakdown. For PD analysis, the whole degradation process was divided into ten stages, and chaos theory was introduced to analyze the variation of three chaotic parameters with the development of electrical degradation, namely the largest Lyapunov exponent, correlation dimension and Komogorov entropy of PD amplitude time series. It is shown that deterministic chaos of PD is confirmed during the oil-paper degradation process, and the obtained results provide a new effective tool for the diagnosis of degradation of oil-paper insulation subjected to PD.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.115-119
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• 2006

The channel is one of the precious and limited resources in wireless networks. There are many researches on the channel management. Recently, the optimization problem of guard channels has been an important issue. In this paper, we propose an intelligent channel management technique based on the neural networks. An SRN channel alteration model is developed to generate the learning data for the neural networks and the performance analysis of system. In the proposed technique, the neural network is trained to generate optimal guard channel number g, using backpropagation supervised learning algorithm. The optimal g is computed using the neural network and compared to the g computed by the SRN model. The numerical results show that the difference between the value of g by backpropagation and that value by SRN model is ignorable.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1151-1160
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• 2016

In recent years, the energy storage systems such as LiB, NaS, RFB(Redox-Flow Battery), Super- capacitor, pumped hydro storage, flywheel, CAES(Compressed Air Energy Storage) and so on have received great attention as practical solutions for the power supply problems. They can be used for various purpose of peak shaving, load leveling and frequency regulation, according to the characteristics of each ESS(energy storage system). This paper will focus at 1 MWh RFB system, which is being developed through the original technology project of energy material. The output of ESS is mainly characterized by C-rate, which means that the total rated capacity of battery will be delivered in 1 hour. And it is a very important factor in the ESS operation scheduling. There can be several options according to the operation intervals 15, 30 and 60minutes. The operation scheduling is based on the optimization to minimize the daily electricity cost. This paper analyzes the cost-saving effects by the each operating time-interval in case that the RFB ESS is optimally scheduled for peak shaving and load leveling.