• Title/Summary/Keyword: Convergence Performance

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Lithium/Sulfur Secondary Batteries: A Review

  • Zhao, Xiaohui;Cheruvally, Gouri;Kim, Changhyeon;Cho, Kwon-Koo;Ahn, Hyo-Jun;Kim, Ki-Won;Ahn, Jou-Hyeon
    • 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.

Moving Shadow Detection using Deep Learning and Markov Random Field (딥 러닝과 마르코프 랜덤필드를 이용한 동영상 내 그림자 검출)

  • Lee, Jong Taek;Kang, Hyunwoo;Lim, Kil-Taek
    • 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.

Performance evaluation of an adjustable gantry PET (AGPET) for small animal PET imaging

  • Song, Hankyeol;Kang, In Soo;Kim, Kyu Bom;Park, Chanwoo;Baek, Min Kyu;Lee, Seongyeon;Chung, Yong Hyun
    • 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.

Investigating the Tensile-Shear of Dissimilar Materials Joined Using the Hybrid SPR Technique (Hybrid SPR 접합을 적용한 이종소재 인장전단에 관한 연구)

  • Yu, Kwan-jong;Choi, Du-bok;Kim, Jae-yeol
    • 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.

Implementation of an Adaptive Genetic Algorithm Processor for Evolvable Hardware (진화 시스템을 위한 유전자 알고리즘 프로세서의 구현)

  • 정석우;김현식;김동순;정덕진
    • 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.

Parameter Estimation of Recurrent Neural Equalizers Using the Derivative-Free Kalman Filter

  • Kwon, Oh-Shin
    • 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.

Experimental Study on Bi-directional Filtered-x Least Mean Square Algorithm (양방향 Filtered-x 최소 평균 제곱 알고리듬에 대한 실험적인 연구)

  • Kwon, Oh Sang
    • 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.

Performance Experiment of Electron Beam Convergence Instrument (Finishing 용 전자빔 집속 장치의 성능 실험)

  • Lim, Sun Jong
    • Laser Solutions
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    • v.18 no.3
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    • pp.6-8
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    • 2015
  • Finishing process includes deburring, polishing and edge radiusing. It improves the surface profile of specimen and eliminates the alien substance on surface. Deburring is the elimination process for debris of edges. Polishing lubricates surfaces by rubbing or chemical treatment. There are two types for electron finishing. The one is using pulse beam. The other is using the convergent and scanning electron beam. Pulse type device appropriates the large area process. But it does not control the beam dosage. Scanning type device has advantages for dosage control and edge deburring. We design the convergence and scan type. It has magnetic lenses for convergence and scan device for scanning beam. Magnetic lenses consist of convergent and objective lens. The lenses are designed by the specification(beam size and working distance). In this paper, we evaluate the convergence performance by pattern process. Also, we analysis the results and important factors for process. The important factors for process are beam size, pressure, stage speed and vacuum. These results will be utilized into systematizing pattern shape and the factors.

Performance Improvement of the Fractionally-Spaced Equalizer with Modified-Multiplication Free Adaptive Filter Algorithm (변형 비분적응필터 알고리즘을 적용한 분할등화기 성능개선)

  • 윤달환;김건호;김명수;임채탁
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.6
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    • pp.28-34
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    • 1993
  • An algorithm for MMADF(modified multiplication-free adaptive filter) which need not to multiplication arithmatic operation is proposed to improve the performance of FSE (fractionally spaced equalizer) which reduce the ISI(intersymbol interference) in signal transfer channel. The input signals are quantized using DPCM and the reference signals is processed using a first-order linear prediction filter. The convergence properties of Sign. MADF and M-MADF algorithm for updating of the coefficients of a FIR digital filter of the fractionally spaced equalizer (FSE) are investigated and compared with one another. The convergence properties are characterized by the steady state error and the convergence speed. It is shown that the convergence speed of M-MADF is almost same as Sign algorithm and is faster than MADF in the condition of same steady state error. Especially it is very useful for high correlated signals.

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Interference Management with Block Diagonalization for Macro/Femto Coexisting Networks

  • Jang, Uk;Cho, Kee-Seong;Ryu, Won;Lee, Ho-Jin
    • ETRI Journal
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    • v.34 no.3
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    • pp.297-307
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    • 2012
  • A femtocell is a small cellular base station, typically designed for use in a home or small business. The random deployment of a femtocell has a critical effect on the performance of a macrocell network due to co-channel interference. Utilizing the advantage of a multiple-input multiple-output system, each femto base station (FBS) is able to form a cluster and generates a precoding matrix, which is a modified version of conventional single-cell block diagonalization, in a cooperative manner. Since interference from clustered-FBSs located at the nearby macro user equipment (MUE) is the dominant interference contributor to the coexisting networks, each cluster generates a precoding matrix considering the effects of interference on nearby MUEs. Through simulation, we verify that the proposed algorithm shows better performance respective to both MUE and femto user equipment, in terms of capacity.