• Title/Summary/Keyword: iterating

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Capacitively Coupled Plasma Simulation for Low-k Materials Etching Process Using $H_2/N_2$ gas (저 유전 재료의 에칭 공정을 위한 $H_2/N_2$ 가스를 이용한 Capacitively Coupled Plasma 시뮬레이션)

  • Shon, Chae-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.55 no.12
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    • pp.601-605
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    • 2006
  • The resistance-capacitance (RC) delay of signals through interconnection materials becomes a big hurdle for high speed operation of semiconductors which contain multi-layer interconnections in smaller scales with higher integration density. Low-k materials are applied to the inter-metal dielectric (IMD) materials in order to overcome the RC delay. Relaxation continuum (RCT) model that includes neutral-species transport model have developed to model the etching process in a capacitively coupled plasma (CCP) device. We present the parametric study of the modeling results of a two-frequency capacitively coupled plasma (2f-CCP) with $N_2/H_2$ gas mixture that is known as promising one for organic low-k materials etching. For the etching of low-k materials by $N_2/H_2$ plasma, N and H atoms have a big influence on the materials. Moreover the distributions of excited neutral species influence the plasma density and profile. We include the neutral transport model as well as plasma one in the calculation. The plasma and neutrals are calculated self-consistently by iterating the simulation of both species till a spatio-temporal steady state profile could be obtained.

Turn-on/off Angle for Maximum Torque of SRM by Using Self-tuning Control (SRM의 자기동조 방식에 의한 최대토크의 턴-온/오프각 제어)

  • Seo Jong-Yun;Cha Hyun-Rok;Seo Jung-Chul;Yang Hyong-Yeol;Kim Kwang-Heon;Lim Young-Cheol;Jang Do-Hyun
    • Proceedings of the KIPE Conference
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    • 2001.07a
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    • pp.243-246
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    • 2001
  • The control of the SRM(Switched Reluctance Motor) is usually based on the non-linear inductance profiles with positions. So determination of optimal switching angle is very different. This paper proposed that the determination method of turn-on/off angle in the SRM drives is to maintain the high torque, which is realized by using self-tuning control method. During the sampling time, a number of pulses from the encoder are checked by using micro-controller. And compared with pre-checked a number of pulses. After calculating difference between two data, turn-on/off angle moves forward or backward direction by using self-tuning method. The optimal turn-on/off angle is determined by iterating such a process and the maximum torque is maintained. Experimental results are provided to demonstrate the validity of the self-tuning controller.

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Optimization of hydraulic section of irrigation canals in cold regions based on a practical model for frost heave

  • Wang, Songhe;Wang, Qinze;An, Peng;Yang, Yugui;Qi, Jilin;Liu, Fengyin
    • Geomechanics and Engineering
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    • v.17 no.2
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    • pp.133-143
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    • 2019
  • An optimal hydraulic section is critical for irrigated water conservancy in seasonal frozen ground due to a large proportion of water leakage, as investigated by in-situ surveys. This is highly correlated with the frost heave of underlain soils in cold season. This paper firstly derived a practical model for frost heave of clayey soils, with temperature dependent thermal indexes incorporating phase change effect. A model test carried out on clay was used to verify the rationality of the model. A novel approach for optimizing the cross-section of irrigation canals in cold regions was suggested with live updated geometry characterized by three unique geometric constraints including slope of canal, ratio of practical flow section to the optimal and lining thickness. Allowable frost heave deformation and tensile stress in canal lining are utilized as standard in computation iterating with geometry updating while the construction cost per unit length is regarded as the eventual target in optimization. A typical section along the Jinghui irrigation canal was selected to be optimized with the above requirements satisfied. Results prove that the optimized hydraulic section exhibits smaller frost heave deformation, lower tensile stress and lower construction cost.

Automation in Site Planning of Apartment Complex - Through Rhino Grasshopper's Parametric Modeling and Optimization - (아파트 최적 배치 자동화 - Rhino Grasshopper를 활용한 parametric model의 최적화를 중심으로 -)

  • Sung, Woo-Jae;Jeong, Yo-Han
    • Journal of KIBIM
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    • v.10 no.3
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    • pp.22-32
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    • 2020
  • Apartment building site planning is one of time consuming and labor-intensive tasks in architectural design field, due to its complexity in zoning regulations, building codes, local restrictions, and site-specific conditions. In other words, the process can be seen as a very complicated mathematical function with layers of variables and parameters, which ironically can be automated using computational methods on parametric tools. In this paper, a practical method of automating site planning of an apartment complex has been proposed by utilizing parametric approaches in Rhino 3D and Grasshopper. Two primary parameters, building heights and positions, determine the efficacy of building layouts under all regulatory standards, thus testing out numerous combinations of the two will produce some successful layout alternatives. For this, equation solver has been used for iterating the parametric model to sort out meaningful results among others. It also has been proven that the proposed process significantly reduced the time in site planning down to less than an hour on most cases, and many successful alternatives could be obtained by using multiple computers. Post evaluation processes such as day light and view shed analysis helped sort out the best performing ones out of functioning alternatives.

Descriptive Assessment Tool for Computational Thinking Competencies (Computational Thinking 역량 평가를 위한 서술형 수행평가 도구)

  • Jeon, Soojin;Han, Seonkwan
    • Journal of The Korean Association of Information Education
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    • v.20 no.3
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    • pp.255-262
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    • 2016
  • In this paper, we proposes a method to effectively evaluate learner competencies of computational thinking. Developed descriptive performance assessment tool is the use of assessment items presented in a creative computing MIT. This tool is selected and modified items through expert delphi technique. The performance assessment tool is composed of four areas that are an experimenting and iterating, testing and debugging, reusing and remixing and abstracting and modularizing. We apply to software classes for the pre-service teachers and conducted this descriptive performance assessment. Applying result of the assessment, the developed assessment tool shows the reliability $Cronbach-{\alpha}$ values higher than 0.6. In addition, the validity of the test results is higher in experts delphi test. Descriptive assessment tool suggested in this study are identified as a useful assessment tool to effectively measure student CT competencies.

PAPR Reduction and BER Analysis of the OFDM System Using the TR and DCT Transform (톤 예약 기법과 DCT 변환을 이용한 OFDM 시스템의 PAPR 저감과 BER 분석)

  • Byeon, Heui-Seop;Shinn, Byung-Cheol;Ahn, Do-Seob
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.17 no.10 s.113
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    • pp.976-984
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    • 2006
  • OFDM system is very useful for the high speed communication system. However, OFDM system has a serious problem of high PAPR that results from the so many subcarriers in the same phase. This OFDM signal is distorted through the nonlinear HPA(High Power Amplifier). Tone reservation method is to insert tone signal in several types to reduce the PAPR after iterating this process by changing the tone signal. Also discrete cosine transform(DCT) can reduces the PAPR as multiplying the cosine value to change the angle and mix up with the data. In the paper, the combination of the TR method and DCT method is newly proposed for more effective reduction of the PAPR. Simulation results show that the proposed method outperforms the conventional simple TR method and DCT method with respect to the PAPR reduction and BER performance.

Feature Points Tracking of Digital Image By One-Directional Iterating Layer Snake Model (일방향 순차층위 스네이크 모델에 의한 디지털영상의 특징점 추적)

  • Hwang, Jung-Won;Hwang, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.4 s.316
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    • pp.86-92
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    • 2007
  • A discrete dynamic model for tracking feature points in 2D images is developed. Conventional snake approaches deform a contour to lock onto features of interest within an image by finding a minimum of its energy functional, composed of internal and external forces. The neighborhood around center snaxel is a space matrix, typically rectangular. The structure of the model proposed in this paper is a set of connected vertices. Energy model is designed for its local minima to comprise the set of alternative solutions available to active process. Block on tracking is one dimension, line type. Initial starting points are defined to the satisfaction of indent states, which is then automatically modified by an energy minimizing process. The track is influenced by curvature constraints, ascent/descent or upper/lower points. The advantages and effectiveness of this layer approach may also be applied to feature points tracking of digital image whose pixels have one directional properties with high autocorrelation between adjacent data lines, vertically or horizontally. The test image is the ultrasonic carotid artery image of human body, and we have verified its effect on intima/adventitia starting points tracking.

An Optimization Method of Neural Networks using Adaptive Regulraization, Pruning, and BIC (적응적 정규화, 프루닝 및 BIC를 이용한 신경망 최적화 방법)

  • 이현진;박혜영
    • Journal of Korea Multimedia Society
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    • v.6 no.1
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    • pp.136-147
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    • 2003
  • To achieve an optimal performance for a given problem, we need an integrative process of the parameter optimization via learning and the structure optimization via model selection. In this paper, we propose an efficient optimization method for improving generalization performance by considering the property of each sub-method and by combining them with common theoretical properties. First, weight parameters are optimized by natural gradient teaming with adaptive regularization, which uses a diverse error function. Second, the network structure is optimized by eliminating unnecessary parameters with natural pruning. Through iterating these processes, candidate models are constructed and evaluated based on the Bayesian Information Criterion so that an optimal one is finally selected. Through computational experiments on benchmark problems, we confirm the weight parameter and structure optimization performance of the proposed method.

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Developing a Text Categorization System Based on Unsupervised Learning Using an Information Retrieval Technique (정보검색 기술을 이용한 비지도 학습 기반 문서 분류 시스템 개발)

  • Noh, Dae-Wook;Lee, Soo-Yong;Ra, Dong-Yul
    • Journal of KIISE:Software and Applications
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    • v.34 no.2
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    • pp.160-168
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    • 2007
  • For developing a text classifier using supervised learning, a manually labeled corpus of large size is required. However, it takes a lot of time and human effort. Recently a research paradigm was proposed to use a raw corpus and a small amount of seed information instead of manually labeled corpus. In this paper we introduce an unsupervised learning method that makes it possible to achieve better performance than other related works. The characteristics of our approach is that average mutual information is used to learn representative words and their weights and then update of the weights is done using a technique inspired by the works in information retrieval. By iterating this teaming process it was shown that a high performance system can be developed.

Improvement of Online Motion Planning based on RRT* by Modification of the Sampling Method (샘플링 기법의 보완을 통한 RRT* 기반 온라인 이동 계획의 성능 개선)

  • Lee, Hee Beom;Kwak, HwyKuen;Kim, JoonWon;Lee, ChoonWoo;Kim, H.Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.3
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    • pp.192-198
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    • 2016
  • Motion planning problem is still one of the important issues in robotic applications. In many real-time motion planning problems, it is advisable to find a feasible solution quickly and improve the found solution toward the optimal one before the previously-arranged motion plan ends. For such reasons, sampling-based approaches are becoming popular for real-time application. Especially the use of a rapidly exploring random $tree^*$ ($RRT^*$) algorithm is attractive in real-time application, because it is possible to approach an optimal solution by iterating itself. This paper presents a modified version of informed $RRT^*$ which is an extended version of $RRT^*$ to increase the rate of convergence to optimal solution by improving the sampling method of $RRT^*$. In online motion planning, the robot plans a path while simultaneously moving along the planned path. Therefore, the part of the path near the robot is less likely to be sampled extensively. For a better solution in online motion planning, we modified the sampling method of informed $RRT^*$ by combining with the sampling method to improve the path nearby robot. With comparison among basic $RRT^*$, informed $RRT^*$ and the proposed $RRT^*$ in online motion planning, the proposed $RRT^*$ showed the best result by representing the closest solution to optimum.