The Experts below are selected from a list of 873750 Experts worldwide ranked by ideXlab platform
Elena Kokoliou - One of the best experts on this subject based on the ideXlab platform.
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Knowledge Base
internal, 2017Co-Authors: Elena KokoliouAbstract:following a source reduction model Packaging in-line printing processes: includes the investigation of integrating a printing process in-line with packaging
Michael Malisoff - One of the best experts on this subject based on the ideXlab platform.
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Reduction Model approach for linear time-varying systems with input delays based on extensions of Floquet theory
Systems & Control Letters, 2016Co-Authors: Frédéric Mazenc, Michael MalisoffAbstract:We solve stabilization problems for linear time-varying systems under input delays. We show how changes of coordinates lead to systems with time invariant drifts, which are covered by the Reduction Model method and which lead to the problem of stabilizing a time-varying system without delay. For continuous time periodic systems, we can use Floquet theory to find the changes of coordinates. We also prove an analogue for discrete time systems, through a discrete time extension of Floquet theory.
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Reduction Model Approach for Systems with a Time-Varying Delay
2015Co-Authors: Frédéric Mazenc, Michael MalisoffAbstract:We provide a Reduction Model approach for achieving global exponential stabilization of linear systems with a time-varying pointwise delay in the input. We allow the delay to be discontinuous and uncertain. We also provide a stability result based on a different dynamic extension that ensures input-to-state stability with respect to additive uncertainties on the dynamics. Instead of the usual Lyapunov-Krasovskii or Razumikhin methods, we use a trajectory based approach.
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CDC - Reduction Model approach for systems with a time-varying delay
2015 54th IEEE Conference on Decision and Control (CDC), 2015Co-Authors: Frédéric Mazenc, Michael MalisoffAbstract:We provide a Reduction Model approach for achieving global exponential stabilization of linear systems with a time-varying pointwise delay in the input. We allow the delay to be discontinuous and uncertain. We also provide a stability result based on a different dynamic extension that ensures input-to-state stability with respect to additive uncertainties on the dynamics. Instead of the usual Lyapunov-Krasovskii or Razumikhin methods, we use a trajectory based approach.
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Local Stabilization of Nonlinear Systems through the Reduction Model Approach
IEEE Transactions on Automatic Control, 2014Co-Authors: Frédéric Mazenc, Michael MalisoffAbstract:We study a general class of nonlinear systems with input delays of arbitrary size. We adapt the Reduction Model approach to prove local asymptotic stability of the closed loop input delayed systems, using feedbacks that may be nonlinear. Our Lyapunov-Krasovskii functionals make it possible to determine estimates of the basins of attraction for the closed loop systems.
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Reduction Model method for local stabilization of time-varying nonlinear systems with input delays, structured nonlinearities, and uncertainties
2014Co-Authors: Frédéric Mazenc, Michael MalisoffAbstract:The Reduction Model approach is useful for stabilizing linear systems with arbitrarily long input delays. Here we adapt the approach to time varying nonlinear systems whose nonlinear parts satisfy certain structural conditions. We use Lyapunov-Krasovskii functionals to prove local stability of the closed loop systems. We provide estimates of the basins of attraction, and cover uncertainties acting on the Model.
Frédéric Mazenc - One of the best experts on this subject based on the ideXlab platform.
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Reduction Model approach for linear time-varying systems with input delays based on extensions of Floquet theory
Systems & Control Letters, 2016Co-Authors: Frédéric Mazenc, Michael MalisoffAbstract:We solve stabilization problems for linear time-varying systems under input delays. We show how changes of coordinates lead to systems with time invariant drifts, which are covered by the Reduction Model method and which lead to the problem of stabilizing a time-varying system without delay. For continuous time periodic systems, we can use Floquet theory to find the changes of coordinates. We also prove an analogue for discrete time systems, through a discrete time extension of Floquet theory.
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Reduction Model Approach for Systems with a Time-Varying Delay
2015Co-Authors: Frédéric Mazenc, Michael MalisoffAbstract:We provide a Reduction Model approach for achieving global exponential stabilization of linear systems with a time-varying pointwise delay in the input. We allow the delay to be discontinuous and uncertain. We also provide a stability result based on a different dynamic extension that ensures input-to-state stability with respect to additive uncertainties on the dynamics. Instead of the usual Lyapunov-Krasovskii or Razumikhin methods, we use a trajectory based approach.
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CDC - Reduction Model approach for systems with a time-varying delay
2015 54th IEEE Conference on Decision and Control (CDC), 2015Co-Authors: Frédéric Mazenc, Michael MalisoffAbstract:We provide a Reduction Model approach for achieving global exponential stabilization of linear systems with a time-varying pointwise delay in the input. We allow the delay to be discontinuous and uncertain. We also provide a stability result based on a different dynamic extension that ensures input-to-state stability with respect to additive uncertainties on the dynamics. Instead of the usual Lyapunov-Krasovskii or Razumikhin methods, we use a trajectory based approach.
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Local Stabilization of Nonlinear Systems through the Reduction Model Approach
IEEE Transactions on Automatic Control, 2014Co-Authors: Frédéric Mazenc, Michael MalisoffAbstract:We study a general class of nonlinear systems with input delays of arbitrary size. We adapt the Reduction Model approach to prove local asymptotic stability of the closed loop input delayed systems, using feedbacks that may be nonlinear. Our Lyapunov-Krasovskii functionals make it possible to determine estimates of the basins of attraction for the closed loop systems.
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Reduction Model method for local stabilization of time-varying nonlinear systems with input delays, structured nonlinearities, and uncertainties
2014Co-Authors: Frédéric Mazenc, Michael MalisoffAbstract:The Reduction Model approach is useful for stabilizing linear systems with arbitrarily long input delays. Here we adapt the approach to time varying nonlinear systems whose nonlinear parts satisfy certain structural conditions. We use Lyapunov-Krasovskii functionals to prove local stability of the closed loop systems. We provide estimates of the basins of attraction, and cover uncertainties acting on the Model.
Alexander Rodriguezpalacios - One of the best experts on this subject based on the ideXlab platform.
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textile masks and surface covers a spray simulation method and a universal droplet Reduction Model against respiratory pandemics
Frontiers in Medicine, 2020Co-Authors: Alexander Rodriguezpalacios, Fabio Cominelli, Abigail R Basson, Theresa T Pizarro, Sanja IlicAbstract:The main form of COVID-19 transmission is via "oral-respiratory droplet contamination" (droplet: very small drop of liquid) produced when individuals talk, sneeze, or cough. In hospitals, health-care workers wear facemasks as a minimum medical "droplet precaution" to protect themselves. Due to the shortage of masks during the pandemic, priority is given to hospitals for their distribution. As a result, the availability/use of medical masks is discouraged for the public. However, for asymptomatic individuals, not wearing masks in public could easily cause the spread of COVID-19. The prevention of "environmental droplet contamination" (EnvDC) from coughing/sneezing/speech is fundamental to reducing transmission. As an immediate solution to promote "public droplet safety," we assessed household textiles to quantify their potential as effective environmental droplet barriers (EDBs). The synchronized implementation of a universal "community droplet Reduction solution" is discussed as a Model against COVID-19. Using a bacterial-suspension spray simulation Model of droplet ejection (mimicking a sneeze), we quantified the extent by which widely available clothing fabrics reduce the dispersion of droplets onto surfaces within 1.8 m, the minimum distance recommended for COVID-19 "social distancing." All textiles reduced the number of droplets reaching surfaces, restricting their dispersion to <30 cm, when used as single layers. When used as double-layers, textiles were as effective as medical mask/surgical-cloth materials, reducing droplet dispersion to <10 cm, and the area of circumferential contamination to ~0.3%. The synchronized implementation of EDBs as a "community droplet Reduction solution" (i.e., face covers/scarfs/masks and surface covers) will reduce COVID-19 EnvDC and thus the risk of transmitting/acquiring COVID-19.
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textile masks and surface covers a universal droplet Reduction Model against respiratory pandemics
medRxiv, 2020Co-Authors: Alexander Rodriguezpalacios, Fabio Cominelli, Abigail R Basson, Theresa T Pizarro, Sanja IlicAbstract:The main form of COVID-19 transmission is via oral-respiratory droplet contamination (droplet; very small drop of liquid) produced when individuals talk, sneeze or cough. In hospitals, health-care workers wear facemasks as a minimum medical droplet precaution to protect themselves. Due to the shortage of masks during the pandemic, priority is given to hospitals for their distribution. As a result, the availability/use of medical masks is discouraged for the public. However, given that asymptomatic individuals, not wearing masks within the public, can be highly contagious for COVID-19, prevention of environmental droplet contamination (EnDC) from coughing/sneezing/speech is fundamental to reducing transmission. As an immediate solution to promote public droplet safety, we assessed household textiles to quantify their potential as effective environmental droplet barriers (EDBs). The synchronized implementation of a universal community droplet Reduction solution is discussed as a Model against COVID-19. Using a bacterial-suspension spray simulation Model of droplet ejection (mimicking a sneeze), we quantified the extent by which widely available clothing fabrics reduce the dispersion of droplets onto surfaces within 1.8m, the minimum distance recommended for COVID-19 social distancing. All textiles reduced the number of droplets reaching surfaces, restricting their dispersion to <30cm, when used as single layers. When used as double-layers, textiles were as effective as medical mask/surgical-cloth materials, reducing droplet dispersion to <10cm, and the area of circumferential contamination to ~0.3%. The synchronized implementation of EDBs as a community droplet Reduction solution (i.e., face covers/scarfs/masks & surface covers) could reduce EnDC and the risk of transmitting or acquiring infectious respiratory pathogens, including COVID-19.
Jennifer S. Perone - One of the best experts on this subject based on the ideXlab platform.
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Work Site Trip Reduction Model and Manual
Transportation Research Record: Journal of the Transportation Research Board, 2005Co-Authors: Philip L Winters, Ajay D Joshi, Rafael A. Perez, Jennifer S. PeroneAbstract:Today's transportation professionals often use the ITE Trip Generation Manual and the Parking Generation Manual for estimating future traffic volumes to base off-site transportation improvements and identify parking requirements. But these manuals are inadequate for assessing the claims made by specific transportation demand management (TDM) programs in reducing vehicle trips by a certain amount at particular work sites. This paper presents a work site trip Reduction Model (WTRM) that can help transportation professionals in assessing those claims. WTRM was built on data from three urban areas in the United States: Los Angeles, California; Tucson, Arizona; and nine counties in Washington State. The data consist of work sites’ employee modal characteristics aggregated at the employer level and a listing of incentives and amenities offered by employers. The dependent variable chosen was the change in vehicle trip rate that correlated with the goals of TDM programs. Two different approaches were used in the Model-building process: linear statistical regression and nonlinear neural networks. For performance evaluation the data sets were divided into two disjoint sets: a training set, which was used to build the Models, and a validation set, which was used as unseen data to evaluate the Models. Because the number of data samples varied from the three areas, two training data sets were formed: one consisted of all training data samples from three areas and the other contained equally sampled training data from the three areas. The best Model was the neural net Model built on equally sampled training data.
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Work Site Trip Reduction Model and Manual
Transportation Research Record, 2004Co-Authors: Philip L Winters, Rafael Perez, Ajay D Joshi, Jennifer S. PeroneAbstract:Today's transportation professionals often use the ITE Trip Generation Manual and the Parking Generation Manual for estimating future traffic volumes to base off-site transportation improvements and identify parking requirements. But these manuals are inadequate for assessing the claims made by specific transportation demand management (TDM) programs in reducing vehicle trips by a certain amount at particular work sites. This paper presents a work site trip Reduction Model (WTRM) that can help transportation professionals in assessing those claims. WTRM was built on data from three urban areas in the United States: Los Angeles, California; Tucson, Arizona; and nine counties in Washington State. The data consist of work sites' employee modal characteristics aggregated at the employer level and a listing of incentives and amenities offered by employers. The dependent variable chosen was the change in vehicle trip rate that correlated with the goals of TDM programs. Two different approaches were used in the ...
