• Title/Summary/Keyword: gradient algorithm

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Three Dimensional Layering Algorithm for 3-D Metal Printing Using 5-axis (3 차원 금속 프린팅을 위한 다중 3 차원 적층 알고리듬(3DL))

  • Ryu, Sua;Jee, Haeseong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.38 no.8
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    • pp.881-886
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    • 2014
  • The purpose of three-dimensional (3-D) metal printing using 5-axis is to deposit metal powder by changing the orientation of the deposited structure to be built for the overhang or undercut feature on part geometry. This requires a complicated preprocess functionality of providing three dimensionally sliced layers to cover the required part geometry. This study addresses the overhang/undercut problem in 3-D metal printing and discusses a possible solution of providing 3-D layers to be built using the DMT(R) machine.

Development of The Irregular Radial Pulse Detection Algorithm Based on Statistical Learning Model (통계적 학습 모형에 기반한 불규칙 맥파 검출 알고리즘 개발)

  • Bae, Jang-Han;Jang, Jun-Su;Ku, Boncho
    • Journal of Biomedical Engineering Research
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    • v.41 no.5
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    • pp.185-194
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    • 2020
  • Arrhythmia is basically diagnosed with the electrocardiogram (ECG) signal, however, ECG is difficult to measure and it requires expert help in analyzing the signal. On the other hand, the radial pulse can be measured with easy and uncomplicated way in daily life, and could be suitable bio-signal for the recent untact paradigm and extensible signal for diagnosis of Korean medicine based on pulse pattern. In this study, we developed an irregular radial pulse detection algorithm based on a learning model and considered its applicability as arrhythmia screening. A total of 1432 pulse waves including irregular pulse data were used in the experiment. Three data sets were prepared with minimal preprocessing to avoid the heuristic feature extraction. As classification algorithms, elastic net logistic regression, random forest, and extreme gradient boosting were applied to each data set and the irregular pulse detection performances were estimated using area under the receiver operating characteristic curve based on a 10-fold cross-validation. The extreme gradient boosting method showed the superior performance than others and found that the classification accuracy reached 99.7%. The results confirmed that the proposed algorithm could be used for arrhythmia screening. To make a fusion technology integrating western and Korean medicine, arrhythmia subtype classification from the perspective of Korean medicine will be needed for future research.

Transit Frequency Optimization with Variable Demand Considering Transfer Delay (환승지체 및 가변수요를 고려한 대중교통 운행빈도 모형 개발)

  • Yu, Gyeong-Sang;Kim, Dong-Gyu;Jeon, Gyeong-Su
    • Journal of Korean Society of Transportation
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    • v.27 no.6
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    • pp.147-156
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    • 2009
  • We present a methodology for modeling and solving the transit frequency design problem with variable demand. The problem is described as a bi-level model based on a non-cooperative Stackelberg game. The upper-level operator problem is formulated as a non-linear optimization model to minimize net cost, which includes operating cost, travel cost and revenue, with fleet size and frequency constraints. The lower-level user problem is formulated as a capacity-constrained stochastic user equilibrium assignment model with variable demand, considering transfer delay between transit lines. An efficient algorithm is also presented for solving the proposed model. The upper-level model is solved by a gradient projection method, and the lower-level model is solved by an existing iterative balancing method. An application of the proposed model and algorithm is presented using a small test network. The results of this application show that the proposed algorithm converges well to an optimal point. The methodology of this study is expected to contribute to form a theoretical basis for diagnosing the problems of current transit systems and for improving its operational efficiency to increase the demand as well as the level of service.

Tunnel Ventilation Controller Design Employing RLS-Based Natural Actor-Critic Algorithm (RLS 기반의 Natural Actor-Critic 알고리즘을 이용한 터널 환기제어기 설계)

  • Chu B.;Kim D.;Hong D.;Park J.;Chung J.T.;Kim T.H.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2006.05a
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    • pp.53-54
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    • 2006
  • The main purpose of tunnel ventilation system is to maintain CO pollutant and VI (visibility index) under an adequate level to provide drivers with safe driving condition. Moreover, it is necessary to minimize power consumption used to operate ventilation system. To achieve the objectives, the control algorithm used in this research is reinforcement teaming (RL) method. RL is a goal-directed teaming of a mapping from situations to actions. The goal of RL is to maximize a reward which is an evaluative feedback from the environment. Constructing the reward of the tunnel ventilation system, two objectives listed above are included. RL algorithm based on actor-critic architecture and natural gradient method is adopted to the system. Also, the recursive least-squares (RLS) is employed to the learning process to improve the efficiency of the use of data. The simulation results performed with real data collected from existing tunnel are provided in this paper. It is confirmed that with the suggested controller, the pollutant level inside the tunnel was well maintained under allowable limit and the performance of energy consumption was improved compared to conventional control scheme.

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Load Frequency Control of Multi-area Power System using Auto-tuning Neuro-Fuzzy Controller (자기조정 뉴로-퍼지제어기를 이용한 다지역 전력시스템의 부하주파수 제어)

  • Jeong, Hyeong-Hwan;Kim, Sang-Hyo;Ju, Seok-Min;Heo, Dong-Ryeol;Lee, Gwon-Sun
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.49 no.3
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    • pp.95-106
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    • 2000
  • The load frequency control of power system is one of important subjects in view of system operation and control. That is even though the rapid load disturbances were applied to the given power system, the stable and reliable power should be supplied to the users, converging unconditionally and rapidly the frequency deviations and the tie-line power flow one on each area into allowable boundary limits. Nonetheless of such needs, if the internal parameter perturbation and the sudden load variation were given, the unstable phenomenal of power system can be often brought out because of the large frequency deviation and the unsuppressible power line one. Therefore, it is desirable to design the robust neuro-fuzzy controller which can stabilize effectively the given power system as soon as possible. In this paper the robust neuro-fuzzy controller was proposed and applied to control of load frequency over multi-area power system. The architecture and algorithm of a designed NFC(Neuro-Fuzzy Controller) were consist of fuzzy controller and neural network for auto tuning of fuzzy controller. The adaptively learned antecedent and consequent parameters of membership functions in fuzzy controller were acquired from the steepest gradient method for error-back propagation algorithm. The performances of the resultant NFC, that is, the steady-state deviations of frequency and tie-line power flow and the related dynamics, were investigated and analyzed in detail by being applied to the load frequency control of multi-area power system, when the perturbations of predetermined internal parameters. Through the simulation results tried variously in this paper for disturbances of internal parameters and external stepwise load stepwise load changes, the superiorities of the proposed NFC in robustness and adaptive rapidity to the conventional controllers were proved.

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2D LiDAR based 3D Pothole Detection System (2차원 라이다 기반 3차원 포트홀 검출 시스템)

  • Kim, Jeong-joo;Kang, Byung-ho;Choi, Su-il
    • Journal of Digital Contents Society
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    • v.18 no.5
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    • pp.989-994
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    • 2017
  • In this paper, we propose a pothole detection system using 2D LiDAR and a pothole detection algorithm. Conventional pothole detection methods can be divided into vibration-based method, 3D reconstruction method, and vision-based method. Proposed pothole detection system uses two inexpensive 2D LiDARs and improves pothole detection performance. Pothole detection algorithm is divided into preprocessing for noise reduction, clustering and line extraction for visualization, and gradient function for pothole decision. By using gradient of distance data function, we check the existence of a pothole and measure the depth and width of the pothole. The pothole detection system is developed using two LiDARs, and the 3D pothole detection performance is shown by detecting a pothole with moving LiDAR system.

Nanoaperture Design in Visible Frequency Range Using Genetic Algorithm and ON/OFF Method Based Topology Optimization Scheme (유전알고리즘 및 ON/OFF 방법을 이용한 가시광선 영역의 나노개구 형상의 위상최적설계)

  • Shin, Hyun Do;Yoo, Jeonghoon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.37 no.12
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    • pp.1513-1519
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    • 2013
  • A genetic algorithm (GA) is an optimization technique based on natural evolution theory to find the global optimal solution. Unlike the gradient-based method, it can design nanoscale structures in the electric field because it does not require sensitivity calculation. This research intends to design a nanoaperture with an unprecedented shape by the topology optimization scheme based on the GA and ON/OFF method in the visible frequency range. This research mainly aims to maximize the transmission rate at a measuring area located 10nm under the exit plane and to minimize the electric distribution at other locations. The finite element analysis (FEA) and optimization process are performed by using the commercial package COMSOL combined with the Matlab programming. The final results of the optimized model are analyzed by a comparison of the electric field intensity and the spot size of near field with those of the initial model.

An Implementation of Real-Time Numeral Recognizer Based on Hand Gesture Using Both Gradient and Positional Information (기울기와 위치 정보를 이용한 손동작기반 실시간 숫자 인식기 구현)

  • Kim, Ji-Ho;Park, Yang-Woo;Han, Kyu-Phil
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.3
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    • pp.199-204
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    • 2013
  • An implementation method of real-time numeral recognizer based on gesture is presented in this paper for various information devices. The proposed algorithm steadily captures the motion of a hand on 3D open space with the Kinect sensor. The captured hand motion is simplified with PCA, in order to preserve the trace consistency and to minimize the trace variations due to noises and size changes. In addition, we also propose a new HMM using both the gradient and the positional features of the simplified hand stroke. As the result, the proposed algorithm has robust characteristics to the variations of the size and speed of hand motion. The recognition rate is increased up to 30%, because of this combined model. Experimental results showed that the proposed algorithm gives a high recognition rate about 98%.

Wavelet-based Fusion of Optical and Radar Image using Gradient and Variance (그레디언트 및 분산을 이용한 웨이블릿 기반의 광학 및 레이더 영상 융합)

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.26 no.5
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    • pp.581-591
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    • 2010
  • In this paper, we proposed a new wavelet-based image fusion algorithm, which has advantages in both frequency and spatial domains for signal analysis. The developed algorithm compares the ratio of SAR image signal to optical image signal and assigns the SAR image signal to the fused image if the ratio is larger than a predefined threshold value. If the ratio is smaller than the threshold value, the fused image signal is determined by a weighted sum of optical and SAR image signal. The fusion rules consider the ratio of SAR image signal to optical image signal, image gradient and local variance of each image signal. We evaluated the proposed algorithm using Ikonos and TerraSAR-X satellite images. The proposed method showed better performance than the conventional methods which take only relatively strong SAR image signals in the fused image, in terms of entropy, image clarity, spatial frequency and speckle index.

Localization and a Distributed Local Optimal Solution Algorithm for a Class of Multi-Agent Markov Decision Processes

  • Chang, Hyeong-Soo
    • International Journal of Control, Automation, and Systems
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    • v.1 no.3
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    • pp.358-367
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    • 2003
  • We consider discrete-time factorial Markov Decision Processes (MDPs) in multiple decision-makers environment for infinite horizon average reward criterion with a general joint reward structure but a factorial joint state transition structure. We introduce the "localization" concept that a global MDP is localized for each agent such that each agent needs to consider a local MDP defined only with its own state and action spaces. Based on that, we present a gradient-ascent like iterative distributed algorithm that converges to a local optimal solution of the global MDP. The solution is an autonomous joint policy in that each agent's decision is based on only its local state.cal state.