• 제목/요약/키워드: ControlNet

검색결과 1,526건 처리시간 0.034초

인위적인 토양산성화에 대한 사방오리나무와 물오리나무 묘목의 생리반응 및 생장특성 (Physiological Responses and Growth Performance of Alnus firma and Alnus hirsuta Seedlings to Artificial Soil Acidification)

  • 최동수;토다 히로토
    • 한국환경복원기술학회지
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    • 제15권5호
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    • pp.145-153
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    • 2012
  • To obtain basic information for evaluating resistance of soil acidification for growth, net photosynthesis, $N_2$ fixation rate and nutrient status of Alnus firma and Alnus hirsuta seedlings grown in brown forest soil acidified with $H_2SO_4$ or $HNO_3$ solution were investigated (control (pH=5.9), LN (pH=5.0; Low levels of Nitric acid), HN (pH=4.0; High levels of Nitric acid), LS (pH=5.0; Low levels of Sulfuric acid), and HS (pH=4.0; High levels of Sulfuric acid)). The shoot dry weight of Alnus firma and Alnus hirsuta and the root dry weight of Alnus hirsuta seedlings grown in the HN, LS and HS were significantly less than that of the seedlings grown in the control. The Chlorophyll a/b ratio in leaves of Alnus firma at LN, LS and HS was significantly lower than that of control. The concentration of N in leaves of Alnus hirsuta at HS was significantly higher than that of control. The net photosynthetic rate of Alnus firma and Alnus hirsuta seedlings at LN and HN was higher than that of control. Based on the results, we concluded that the negative effects of soil acidification due to sulfate deposition are greater than those of soil acidification due to nitrate deposition on growth, net photosynthesis and $N_2$ fixation rate of Alnus firma more than Alnus hirsuta.

통합생산환경에서의 가상공장 시물레이터 개발을 위한 제어모형 (A Control Model for Prototyping Virtual Factory Simulator in Computer Integrated Manufacturing Environment)

  • Namkyu Park;Hyun Jung Lee
    • 한국전자거래학회지
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    • 제1권1호
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    • pp.227-247
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    • 1996
  • Presented in this paper is a control model for developing virtual factory simulator, which is being operated under the distributed environment. The control model consists of production activity plan and information flows. To incorporate elements of the characteristics of the distributed control system, we suggested a collaboration model. This model is working under the client/server architecture, and also designed for cooperative-distributed shop control(CDSC) system in order to exploit several advantages of client/server architecture. Collaboration among each agent(or client) is done through negotiation and task sharing. Based on a contract net model, the CDSC system has three kinds of agents-order agent, resource agent, and communication forwarding agent. Each agent performs shop scheduling and control through negotiation on contract net. No node in CDSC system can have authority over other node. A bidding scheme is employed far negotiation between order agent and resource agents. The CDSC system can support re-negotiation among resource agents and an algorithm for re-negotiation is also developed. Experimental results are shown to advocate the effectiveness of the CDSC system for CIM environments.

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실시간 운영체제를 이용한 로봇제어기 소프트웨어의 구현 및 성능 분석 (An implementation and performance analysis for robot control software under real-time operating systems)

  • 손승우;이기동
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.375-378
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    • 1996
  • Robot control software is a hard real-time system that must output the planned trajectory points within an explicit short time period. In this paper, we present a design and implementation method for robot control software using commercial real-time operating systems, RTKemel 4.5. Therefore, various robot motions, efficient user interface, and system failure check are easily implemented by using multitasking function, intertask communication mechanism, and real-time runtime libraries of RTKernel. The performance analysis of commercial real-time operating system for robot control is presented based on Timed Petri net(TPN) and we can use these results to design an optimal system.

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ER댐퍼를 이용한 차량의 진동제어 (Vibration Control of a Vehicle using ER Damper)

  • 주동우;이육형;박명관
    • 한국정밀공학회지
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    • 제16권5호통권98호
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    • pp.104-111
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    • 1999
  • A semi-active suspension system for a vehicle using an Electrorheological Fluid damper has been studied. Apparent viscosity of ERF(Electrorheological Fluid) can be changed rapidly by applying electric field. The damping force of ER damper can be selectively controlled by employing electric field to the ER fluid domain. This paper deals with a two-degree-of-freedom suspension using the ER damper for a quarter car model. An intelligent control method using fuzzy control with genetic algorithm has been employed to control the damping force of the ER damper. The GA designs the optimal structure and performance of Fuzzy Net Controller having hybrid structure. The designed fuzzy net controller has been compared with the skyhook type controller for a quarter car model. The computer simulation results show that the semi-active suspension with ER damper has a good performance in the sense of ride quality with less vibration for ground vehicle.

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갑상선 초음파 영상의 평활화 알고리즘에 따른 U-Net 기반 학습 모델 평가 (Evaluation of U-Net Based Learning Models according to Equalization Algorithm in Thyroid Ultrasound Imaging)

  • 정무진;오주영;박훈희;이주영
    • 대한방사선기술학회지:방사선기술과학
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    • 제47권1호
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    • pp.29-37
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    • 2024
  • This study aims to evaluate the performance of the U-Net based learning model that may vary depending on the histogram equalization algorithm. The subject of the experiment were 17 radiology students of this college, and 1,727 data sets in which the region of interest was set in the thyroid after acquiring ultrasound image data were used. The training set consisted of 1,383 images, the validation set consisted of 172 and the test data set consisted of 172. The equalization algorithm was divided into Histogram Equalization(HE) and Contrast Limited Adaptive Histogram Equalization(CLAHE), and according to the clip limit, it was divided into CLAHE8-1, CLAHE8-2. CLAHE8-3. Deep Learning was learned through size control, histogram equalization, Z-score normalization, and data augmentation. As a result of the experiment, the Attention U-Net showed the highest performance from CLAHE8-2 to 0.8355, and the U-Net and BSU-Net showed the highest performance from CLAHE8-3 to 0.8303 and 0.8277. In the case of mIoU, the Attention U-Net was 0.7175 in CLAHE8-2, the U-Net was 0.7098 and the BSU-Net was 0.7060 in CLAHE8-3. This study attempted to confirm the effects of U-Net, Attention U-Net, and BSU-Net models when histogram equalization is performed on ultrasound images. The increase in Clip Limit can be expected to increase the ROI match with the prediction mask by clarifying the boundaries, which affects the improvement of the contrast of the thyroid area in deep learning model learning, and consequently affects the performance improvement.

다층 신경회로망을 이용한 GMA 용접 공정에서의 용융지 크기의 예측 (Estimation of weld pool sizes in GMA welding processes using a multi-layer neural net)

  • 임태균;조형석
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.1028-1033
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    • 1991
  • This paper describes the design of a neural network estimator to estimate weld pool sizes for on-line use of quality monitoring and control in GMA welding processes. The estimator utilizes surface temperatures measured at various points on the top surface of the weldment as its input. The main task of the neural net is to realize the mapping characteristics from the point temperatures to the weld pool sizes through training, A series of bead-on plate welding experiments were performed to assess the performance of the neural estimator.

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Using Net Power Control for AMOLED TV

  • Arkhipov, Alexander;Lee, Baek-Woon;Park, Kyong-Tae;Sung, Si-Duk;Shin, Sung-Tae;Chung, Kyu-Ha
    • 한국정보디스플레이학회:학술대회논문집
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    • 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권1호
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    • pp.47-50
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    • 2007
  • The maximum current level in organic light emitting diodes (OLED) panel influences the maximum pixel luminance, the width of $V_{DD}$ lines, the maximum power consumption and the lifetime. We propose an algorithm that limits the overall current without any palpable image artifacts, and therefore, improve panel parameters by program.

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SOFM과 LAM을 이용한 영상 보간에 관한 연구 (A Study on Image Interpolation Using SOFM and LAM)

  • 장동언;정태상
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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    • pp.640-642
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    • 1998
  • When resampling an image to a new set of coordinates, there is often a noticeable loss in image quality. The interpolation kernel determines the quality of interpolation. In this paper, We think two interpolation methods: cubic-spline method, neural net method, at first study given interpolation method using spline and then present new interpolation methon using SOFM and LAM(neural net method), finally compare the performance of several interpolation methods including replication, bilinear, spline and new methods.

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Multi-robot control using Petri-net

  • Park, Se-Woong;Kuc, Tae-Yong
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.59.5-59
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    • 2001
  • Multi-agent robot system is the system which executes by cooperating with each robots and controlling several robots. Capability and function of each robot must be considered for cooperation behavior. Furthermore, it is necessary to analyze the given environment and to replace complex task with some simple tasks. Analysis of the given environment and role assignment for the given tasks are composed of discret event. In this paper, the hierarchical controller for multi-agent robot system using the petri-net state diagram is proposed. The proposed modeling method is implemented for soccer robot system. The effectiveness of proposed modeling method is shown through experiment.

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Multi-Dimensional Reinforcement Learning Using a Vector Q-Net - Application to Mobile Robots

  • Kiguchi, Kazuo;Nanayakkara, Thrishantha;Watanabe, Keigo;Fukuda, Toshio
    • International Journal of Control, Automation, and Systems
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    • 제1권1호
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    • pp.142-148
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    • 2003
  • Reinforcement learning is considered as an important tool for robotic learning in unknown/uncertain environments. In this paper, we propose an evaluation function expressed in a vector form to realize multi-dimensional reinforcement learning. The novel feature of the proposed method is that learning one behavior induces parallel learning of other behaviors though the objectives of each behavior are different. In brief, all behaviors watch other behaviors from a critical point of view. Therefore, in the proposed method, there is cross-criticism and parallel learning that make the multi-dimensional learning process more efficient. By ap-plying the proposed learning method, we carried out multi-dimensional evaluation (reward) and multi-dimensional learning simultaneously in one trial. A special neural network (Q-net), in which the weights and the output are represented by vectors, is proposed to realize a critic net-work for Q-learning. The proposed learning method is applied for behavior planning of mobile robots.