• ETRI Journal
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• v.37 no.2
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• pp.212-221
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• 2015

As the amount of re-sequencing genome data grows, minimizing the execution time of an analysis is required. For this purpose, recent computing systems have been adopting both high-performance coprocessors and host processors. However, there are few applications that efficiently utilize these heterogeneous computing resources. This problem equally refers to the work of single nucleotide polymorphism (SNP) detection, which is one of the bottlenecks in genome data processing. In this paper, we propose a method for speeding up an SNP detection by enhancing the utilization of heterogeneous computing resources often used in recent high-performance computing systems. Through the measurement of workload in the detection procedure, we divide the SNP detection into several task groups suitable for each computing resource. These task groups are scheduled using a window overlapping method. As a result, we improved upon the speedup achieved by previous open source applications by a magnitude of 10.

• ETRI Journal
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• v.30 no.5
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• pp.644-652
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• 2008

In this paper, a low-power CMOS interface circuit is designed and demonstrated for capacitive sensor applications, which is implemented using a standard 0.35-${\mu}m$ CMOS logic technology. To achieve low-power performance, the low-voltage capacitance-to-pulse-width converter based on a self-reset operation at a supply voltage of 1.5 V is designed and incorporated into a new interface circuit. Moreover, the external pulse signal for the reset operation is made unnecessary by the employment of the self-reset operation. At a low supply voltage of 1.5 V, the new circuit requires a total power consumption of 0.47 mW with ultra-low power dissipation of 157 ${\mu}W$ of the interface-circuit core. These results demonstrate that the new interface circuit with self-reset operation successfully reduces power consumption. In addition, a prototype wireless sensor-module with the proposed circuit is successfully implemented for practical applications. Consequently, the new CMOS interface circuit can be used for the sensor applications in ubiquitous sensor networks, where low-power performance is essential.

• Journal of Electrochemical Science and Technology
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• v.7 no.2
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• pp.97-114
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• 2016

Lithium batteries based on elemental sulfur as the cathode-active material capture great attraction due to the high theoretical capacity, easy availability, low cost and non-toxicity of sulfur. Although lithium/sulfur (Li/S) primary cells were known much earlier, the interest in developing Li/S secondary batteries that can deliver high energy and high power was actively pursued since early 1990’s. A lot of technical challenges including the low conductivity of sulfur, dissolution of sulfur-reduction products in the electrolyte leading to their migration away from the cathode, and deposition of solid reaction products on cathode matrix had to be tackled to realize a high and stable performance from rechargeable Li/S cells. This article presents briefly an overview of the studies pertaining to the different aspects of Li/S batteries including those that deal with the sulfur electrode, electrolytes, lithium anode and configuration of the batteries.

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1432-1438
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• 2015

We present a methodology to detect moving shadows in video sequences, which is considered as a challenging and critical problem in the most visual surveillance systems since 1980s. While most previous moving shadow detection methods used hand-crafted features such as chromaticity, physical properties, geometry, or combination thereof, our method can automatically learn features to classify whether image segments are shadow or foreground by using a deep learning architecture. Furthermore, applying Markov Random Field enables our system to refine our shadow detection results to improve its performance. Our algorithm is applied to five different challenging datasets of moving shadow detection, and its performance is comparable to that of state-of-the-art approaches.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2646-2651
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• 2021

A rectangular-shaped PET system with an adjustable gantry (AGPET) has been developed for imaging small animals. The AGPET system employs a new depth of interaction (DOI) method using a depth dependent reflector patterns and a new digital time pickoff method based on the pulse reconstruction method. To evaluate the performance of the AGPET, timing resolution, intrinsic spatial resolution and point source images were acquired. The timing resolution and intrinsic spatial resolution were measured using two detector modules and Na-22 gamma source. The PET images were acquired in two field of view (FOV) sizes, 30 mm and 90 mm, to demonstrate the characteristic of the AGPET. As a result of in the experiment results, the timing resolution was 0.9 ns using the pulse reconstruction method based on the bi-exponential model. The intrinsic spatial resolution was an average of 1.7 mm and the spatial resolution of PET images after DOI correction was 2.08 mm and 2.25 mm at the centers of 30 mm and 90 mm FOV, respectively. The results show that the proposed AGPET system provided higher sensitivity and resolution for small animal imaging.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3775-3784
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• 2024

In this study, a skewness estimation method (SEM) and kurtosis estimation method (KEM) are introduced to determine the number of inactive cycles in Monte Carlo eigenvalue calculations. The SEM and KEM can determine the number of inactive cycles on the basis that fully converged fission source distributions may follow normal distributions without asymmetry or outliers. Two convergence criteria values and a minimum cycle length for the SEM and KEM were determined from skewness and kurtosis analyses of the AGN-201K benchmark and 1D slab problems. The SEM and KEM were then applied to two OECD/NEA slow convergence benchmark problems to evaluate the performance and reliability of the developed methods. Results confirmed that the SEM and KEM provide appropriate and effective convergence cycles when compared to other methods and fission source density fraction trends. Also, the determined criterion value of 0.5 for both ε₁ and ε₂ was concluded to be reasonable. The SEM and KEM can be utilized as a new approach for determining the number of inactive cycles and judging whether Monte Carlo tally values are fully converged. In the near future, the methods will be applied to various practical problems to further examine their performance and reliability, and optimization will be performed for the convergence criteria and other parameters as well as for improvement of the methodology for practical usage.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.9
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• pp.33-39
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• 2020

Self-piercing rivets are often used in the automotive industry, among other industries, as mechanical components to join multiple materials such as aluminum alloys. Self-piercing rivets have a strong sealing property, although there is considerable scope for their performance improvement. In this study, to enhance the performance of self-piercing rivets, the hybrid self-piercing riveting (SPR) technique, using the existing SPR and structural adhesive, was proposed. Moreover, heterogeneous material specimens subjected to the hybrid SPR technique were manufactured and tested. The joint strength of the test pieces of different materials was evaluated through finite element analyses.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.265-276
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• 2004

Genetic Algorithm(GA), that is shown stable performance to find an optimal solution, has been used as a method of solving large-scaled optimization problems with complex constraints in various applications. Since it takes so much time to execute a long computation process for iterative evolution and adaptation. In this paper, a hardware-based adaptive GA was proposed to reduce the serious computation time of the evolutionary process and to improve the accuracy of convergence to optimal solution. The proposed GA, based on steady-state model among continuos generation model, performs an adaptive mutation process with consideration of the evolution flow and the population diversity. The drawback of the GA, premature convergence, was solved by the proposed adaptation. The Performance improvement of convergence accuracy for some kinds of problem and condition reached to 5-100% with equivalent convergence speed to high-speed algorithm. The proposed adaptive GAP(Genetic Algorithm Processor) was implemented on FPGA device Xilinx XCV2000E of EHW board for face recognition.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.267-272
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• 2010

For the last decade, recurrent neural networks (RNNs) have been commonly applied to communications channel equalization. The major problems of gradient-based learning techniques, employed to train recurrent neural networks are slow convergence rates and long training sequences. In high-speed communications system, short training symbols and fast convergence speed are essentially required. In this paper, the derivative-free Kalman filter, so called the unscented Kalman filter (UKF), for training a fully connected RNN is presented in a state-space formulation of the system. The main features of the proposed recurrent neural equalizer are fast convergence speed and good performance using relatively short training symbols without the derivative computation. Through experiments of nonlinear channel equalization, the performance of the RNN with a derivative-free Kalman filter is evaluated.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.197-205
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• 2014

In applications of adaptive noise control or active noise control, the presence of a transfer function in the secondary path following the adaptive controller and the error path, been shown to generally degrade the performance of the Least Mean Square (LMS) algorithm. Thus, the convergence rate is lowered, the residual power is increased, and the algorithm can become unstable. In general, in order to solve these problems, the filtered-x LMS (FX-LMS) type algorithms can be used. But these algorithms have slow convergence speed and weakness in the environment that the secondary path and error path are varied. Therefore, I present the new algorithm called the "Bi-directional Filtered-x (BFX) LMS" algorithm with nearly equal computation complexity. Through experimental study, the proposed BFX-LMS algorithm has better convergence speed and better performance than the conventional FX-LMS algorithm, especially when the secondary path or error path is varied and the impulsive disturbance is flow in.