Imaging and Motion Prediction for an Automated Live-Bird Transfer Process

2000 ◽  
Author(s):  
Kok-Meng Lee ◽  
Jeffry Joni ◽  
Xuecheng Yin
Keyword(s):  
Real Time ◽  
Transfer Process ◽  
Imaging System ◽  
Motion Prediction ◽  
Design Evaluation ◽  
Transfer System ◽  
Structured Illumination ◽  
Prediction And Control ◽  
And Control ◽  
Live Bird

Abstract This paper presents the illumination design of a real-time live-bird imaging system for determining the size and initial presentation of a bird on a moving conveyor. A real-time live-bird imaging system presents a challenging design problem, for it must minimize the variability of the birds’ visual reflexes to mechanical processes, it must account for variations in bird size/shape/color, it must meet the cycle-time requirement, and yet provide an adequately illuminated environment to ease human supervision. In this paper, we first identify the variables needed for motion prediction. Second, by analyzing the bird visual perception we have developed a two-stage structured illumination that has the potential to minimize the demand on the control efforts of the transfer system, and to improve birds’ welfare and the ultimate product quality. Finally, we present the image algorithms and experimental results of the design evaluation using live birds. It is expected that the design principles presented in this paper provide essential bases for motion analysis, prediction, and control of an automated live-bird transfer process.

scholarly journals Real-Time In Vivo Bioluminescent Imaging for Evaluating the Efficacy of Antibiotics in a Rat Staphylococcus aureus Endocarditis Model

2005 ◽  
Vol 49 (1) ◽  
pp. 380-387 ◽  
Author(s):  
Yan Q. Xiong ◽  
Julie Willard ◽  
Jagath L. Kadurugamuwa ◽  
Jun Yu ◽  
Kevin P. Francis ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Real Time ◽  
Imaging System ◽  
Bioluminescent Imaging ◽  
Vancomycin Therapy ◽  
Treatment Groups ◽  
Highly Sensitive ◽  
Relevant Animal Model ◽  
And Control

ABSTRACT Therapeutic options for invasive Staphylococcus aureus infections have become limited due to rising antimicrobial resistance, making relevant animal model testing of new candidate agents more crucial than ever. In the present studies, a rat model of aortic infective endocarditis (IE) caused by a bioluminescently engineered, biofilm-positive S. aureus strain was used to evaluate real-time antibiotic efficacy directly. This strain was vancomycin and cefazolin susceptible but gentamicin resistant. Bioluminescence was detected and quantified daily in antibiotic-treated and control animals with IE, using a highly sensitive in vivo imaging system (IVIS). Persistent and increasing cardiac bioluminescent signals (BLS) were observed in untreated animals. Three days of vancomycin therapy caused significant reductions in both cardiac BLS (>10-fold versus control) and S. aureus densities in cardiac vegetations (P < 0.005 versus control). However, 3 days after discontinuation of vancomycin therapy, a greater than threefold increase in cardiac BLS was observed, indicating relapsing IE (which was confirmed by quantitative culture). Cefazolin resulted in modest decreases in cardiac BLS and bacterial densities. These microbiologic and cardiac BLS differences during therapy correlated with a longer time-above-MIC for vancomycin (>12 h) than for cefazolin (∼4 h). Gentamicin caused neither a reduction in cardiac S. aureus densities nor a reduction in BLS. There were significant correlations between cardiac BLS and S. aureus densities in vegetations in all treatment groups. These data suggest that bioluminescent imaging provides a substantial advance in the real-time monitoring of the efficacy of therapy of invasive S. aureus infections in live animals.

Transient Stability Prediction and Control in Real-Time by QUEP

1989 ◽  
Vol 9 (5) ◽  
pp. 62-62
Author(s):  
W. W. Lemmon ◽  
K. R. C. Mamandur ◽  
W. R. Barcelo
Keyword(s):  
Real Time ◽  
Transient Stability ◽  
Stability Prediction ◽  
Prediction And Control ◽  
And Control

scholarly journals Motion prediction and control for patient motion compensation in radiotherapy

2011 ◽  
Vol 44 (1) ◽  
pp. 5985-5990 ◽  
Author(s):  
Olivier C.L. Haas ◽  
Daniel Paluszczyszyn ◽  
Mariusz Ruta ◽  
Piotr Skworcow
Keyword(s):  
Motion Compensation ◽  
Motion Prediction ◽  
Patient Motion ◽  
Prediction And Control ◽  
And Control

Neural Network-Based Prediction and Control of Air Flow in a Data Center

2012 ◽  
Vol 4 (2) ◽  
Author(s):  
Flavio de Lorenzi ◽  
Christof Vömel
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Real Time ◽  
Data Center ◽  
Cooling System ◽  
Air Flow ◽  
Data Center Cooling ◽  
Prediction And Control ◽  
Reduce Energy Consumption ◽  
And Control

As modern data centers continue to grow in power, size, and numbers, there is an urgent need to reduce energy consumption by optimized cooling strategies. In this paper, we present a neural network-based prediction of air flow in a data center that is cooled through perforated floor tiles. With a significantly smaller execution time than computational fluid dynamics, it predicts in real-time server inlet temperatures and can detect whether prevalent air flow cools the servers sufficiently to guarantee safe operation. Combined with a cooling system model, we obtain a temperature and air flow control algorithm that is fast and accurate enough to find an optimal operating point of the data center cooling system in real-time. We also demonstrate the performance of our algorithm on a reference data center and show that energy consumption can be reduced by up to 30%.

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