The Experts below are selected from a list of 32820 Experts worldwide ranked by ideXlab platform
A.j Mcarthur - One of the best experts on this subject based on the ideXlab platform.
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Thermal balance of livestock. 1. A Parsimonious Model
Agricultural and Forest Meteorology, 2000Co-Authors: John Turnpenny, A.j Mcarthur, J.a Clark, Christopher M. WathesAbstract:A mathematical Model based on the physics of heat transfer was developed to predict the components of heat loss from a homeothermic animal in relation to environmental conditions. The animal's trunk was treated as three concentric insulating cylinders around a heat-generating core, representing the body tissue, coat and surrounding environment. The Model also accounted for heat losses from appendages. The Model inputs were the hourly meteorological data, parameters and/or variables of animal physiology, and the thermoregulatory responses of different species to environmental conditions. The heat loss components were calculated by iteration of the heat balance equations, assuming steady heat flow. For illustration, the heat balance of a sheep outdoors is predicted from hourly weather data.
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Thermal balance of livestock. 2. Applications of a Parsimonious Model.
Agricultural and Forest Meteorology, 2000Co-Authors: John Turnpenny, J.a Clark, Christopher M. Wathes, A.j McarthurAbstract:Abstract A mathematical Model developed from heat transfer principles to predict the thermal status of a homeotherm was applied to sheep and cattle outdoors and pigs and broiler chickens indoors. The climatological variables considered in the Model include air temperature, wind speed, vapour pressure and solar radiation. For sheep, the fleece depth varied seasonally and thermal balance was achieved by a metabolic response, vasodilation and panting. For cattle, the thermal responses included sweating and piloerection of the coat. The insulation provided by the pig’s sparse hair coat was neglected, but the increase in its body insulation with age and environmental conditions was included as a major determinant of heat loss. For chickens, the insulation provided by the body tissue and feathers was described by a single thermal resistance. Their thermal responses included feather fluffing, vasomotor action in the combs and feet, and changes in respiration rate and body temperature. The Models were tested successfully for each species by simulating the experimental conditions used by previous workers and comparing the predictions with measured values of heat loss, skin and body temperature. The interception of solar radiation by animals outdoors was also tested successfully for solar elevations up to 45°. For sheep, the predicted heat loss agreed with measurements to within 10%. The onset of vasodilation for a shorn sheep on maintenance food intake was predicted successfully to occur at an air temperature of 25°C, and the variation of skin temperature on the legs with air temperature was predicted to within the uncertainty of the measurements. The Model predicted the heat loss from cattle in the cold with acceptable accuracy when the wind speed was low, but overestimated heat loss from calves by up to 30% in wind. In warm conditions, the evaporative heat loss from cattle as a consequence of sweating was predicted with acceptable accuracy. The errors incurred by ignoring solar radiation penetration into the coat were acceptably small, given the associated reduction in Model complexity. Sensitivity analysis showed that the predictions of heat loss from sheep and cattle were sensitive to wind speed and coat length, especially when the coat is short. For both species, the level of stress was sensitive to ambient vapour pressure at high air temperatures. For a single new-born pig, the Model underestimated heat loss at 30°C with an overall error of −9% over the range of wind speeds likely to be experienced indoors. The Model over-predicted heat loss by an average of 20% at 20°C, probably due to the absence in the Model of a temperature-dependent huddling response. However, for a 25 kg pig exposed to air temperatures from −5 to 35°C, the Model predicted the skin temperature on the trunk — a good indication of its thermal status — to within the limits of the experimental uncertainty. The total heat loss from chickens exposed to temperatures in the range 0–38°C was predicted with an overall error of 6%. In a separate test, the body core temperature of hens was predicted to within 0.3°C on average for the same range of air temperature, again within the limits of experimental uncertainty. Sensitivity analysis showed that the prediction of body temperature for chickens was most sensitive to ambient humidity at high air temperatures, and to body resistance. The paper discusses the limitations of the Models and the need for more measurements of heat losses from current breeds of livestock.
Christopher M. Wathes - One of the best experts on this subject based on the ideXlab platform.
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Thermal balance of livestock. 1. A Parsimonious Model
Agricultural and Forest Meteorology, 2000Co-Authors: John Turnpenny, A.j Mcarthur, J.a Clark, Christopher M. WathesAbstract:A mathematical Model based on the physics of heat transfer was developed to predict the components of heat loss from a homeothermic animal in relation to environmental conditions. The animal's trunk was treated as three concentric insulating cylinders around a heat-generating core, representing the body tissue, coat and surrounding environment. The Model also accounted for heat losses from appendages. The Model inputs were the hourly meteorological data, parameters and/or variables of animal physiology, and the thermoregulatory responses of different species to environmental conditions. The heat loss components were calculated by iteration of the heat balance equations, assuming steady heat flow. For illustration, the heat balance of a sheep outdoors is predicted from hourly weather data.
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Thermal balance of livestock. 2. Applications of a Parsimonious Model.
Agricultural and Forest Meteorology, 2000Co-Authors: John Turnpenny, J.a Clark, Christopher M. Wathes, A.j McarthurAbstract:Abstract A mathematical Model developed from heat transfer principles to predict the thermal status of a homeotherm was applied to sheep and cattle outdoors and pigs and broiler chickens indoors. The climatological variables considered in the Model include air temperature, wind speed, vapour pressure and solar radiation. For sheep, the fleece depth varied seasonally and thermal balance was achieved by a metabolic response, vasodilation and panting. For cattle, the thermal responses included sweating and piloerection of the coat. The insulation provided by the pig’s sparse hair coat was neglected, but the increase in its body insulation with age and environmental conditions was included as a major determinant of heat loss. For chickens, the insulation provided by the body tissue and feathers was described by a single thermal resistance. Their thermal responses included feather fluffing, vasomotor action in the combs and feet, and changes in respiration rate and body temperature. The Models were tested successfully for each species by simulating the experimental conditions used by previous workers and comparing the predictions with measured values of heat loss, skin and body temperature. The interception of solar radiation by animals outdoors was also tested successfully for solar elevations up to 45°. For sheep, the predicted heat loss agreed with measurements to within 10%. The onset of vasodilation for a shorn sheep on maintenance food intake was predicted successfully to occur at an air temperature of 25°C, and the variation of skin temperature on the legs with air temperature was predicted to within the uncertainty of the measurements. The Model predicted the heat loss from cattle in the cold with acceptable accuracy when the wind speed was low, but overestimated heat loss from calves by up to 30% in wind. In warm conditions, the evaporative heat loss from cattle as a consequence of sweating was predicted with acceptable accuracy. The errors incurred by ignoring solar radiation penetration into the coat were acceptably small, given the associated reduction in Model complexity. Sensitivity analysis showed that the predictions of heat loss from sheep and cattle were sensitive to wind speed and coat length, especially when the coat is short. For both species, the level of stress was sensitive to ambient vapour pressure at high air temperatures. For a single new-born pig, the Model underestimated heat loss at 30°C with an overall error of −9% over the range of wind speeds likely to be experienced indoors. The Model over-predicted heat loss by an average of 20% at 20°C, probably due to the absence in the Model of a temperature-dependent huddling response. However, for a 25 kg pig exposed to air temperatures from −5 to 35°C, the Model predicted the skin temperature on the trunk — a good indication of its thermal status — to within the limits of the experimental uncertainty. The total heat loss from chickens exposed to temperatures in the range 0–38°C was predicted with an overall error of 6%. In a separate test, the body core temperature of hens was predicted to within 0.3°C on average for the same range of air temperature, again within the limits of experimental uncertainty. Sensitivity analysis showed that the prediction of body temperature for chickens was most sensitive to ambient humidity at high air temperatures, and to body resistance. The paper discusses the limitations of the Models and the need for more measurements of heat losses from current breeds of livestock.
John Turnpenny - One of the best experts on this subject based on the ideXlab platform.
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Thermal balance of livestock. 1. A Parsimonious Model
Agricultural and Forest Meteorology, 2000Co-Authors: John Turnpenny, A.j Mcarthur, J.a Clark, Christopher M. WathesAbstract:A mathematical Model based on the physics of heat transfer was developed to predict the components of heat loss from a homeothermic animal in relation to environmental conditions. The animal's trunk was treated as three concentric insulating cylinders around a heat-generating core, representing the body tissue, coat and surrounding environment. The Model also accounted for heat losses from appendages. The Model inputs were the hourly meteorological data, parameters and/or variables of animal physiology, and the thermoregulatory responses of different species to environmental conditions. The heat loss components were calculated by iteration of the heat balance equations, assuming steady heat flow. For illustration, the heat balance of a sheep outdoors is predicted from hourly weather data.
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Thermal balance of livestock. 2. Applications of a Parsimonious Model.
Agricultural and Forest Meteorology, 2000Co-Authors: John Turnpenny, J.a Clark, Christopher M. Wathes, A.j McarthurAbstract:Abstract A mathematical Model developed from heat transfer principles to predict the thermal status of a homeotherm was applied to sheep and cattle outdoors and pigs and broiler chickens indoors. The climatological variables considered in the Model include air temperature, wind speed, vapour pressure and solar radiation. For sheep, the fleece depth varied seasonally and thermal balance was achieved by a metabolic response, vasodilation and panting. For cattle, the thermal responses included sweating and piloerection of the coat. The insulation provided by the pig’s sparse hair coat was neglected, but the increase in its body insulation with age and environmental conditions was included as a major determinant of heat loss. For chickens, the insulation provided by the body tissue and feathers was described by a single thermal resistance. Their thermal responses included feather fluffing, vasomotor action in the combs and feet, and changes in respiration rate and body temperature. The Models were tested successfully for each species by simulating the experimental conditions used by previous workers and comparing the predictions with measured values of heat loss, skin and body temperature. The interception of solar radiation by animals outdoors was also tested successfully for solar elevations up to 45°. For sheep, the predicted heat loss agreed with measurements to within 10%. The onset of vasodilation for a shorn sheep on maintenance food intake was predicted successfully to occur at an air temperature of 25°C, and the variation of skin temperature on the legs with air temperature was predicted to within the uncertainty of the measurements. The Model predicted the heat loss from cattle in the cold with acceptable accuracy when the wind speed was low, but overestimated heat loss from calves by up to 30% in wind. In warm conditions, the evaporative heat loss from cattle as a consequence of sweating was predicted with acceptable accuracy. The errors incurred by ignoring solar radiation penetration into the coat were acceptably small, given the associated reduction in Model complexity. Sensitivity analysis showed that the predictions of heat loss from sheep and cattle were sensitive to wind speed and coat length, especially when the coat is short. For both species, the level of stress was sensitive to ambient vapour pressure at high air temperatures. For a single new-born pig, the Model underestimated heat loss at 30°C with an overall error of −9% over the range of wind speeds likely to be experienced indoors. The Model over-predicted heat loss by an average of 20% at 20°C, probably due to the absence in the Model of a temperature-dependent huddling response. However, for a 25 kg pig exposed to air temperatures from −5 to 35°C, the Model predicted the skin temperature on the trunk — a good indication of its thermal status — to within the limits of the experimental uncertainty. The total heat loss from chickens exposed to temperatures in the range 0–38°C was predicted with an overall error of 6%. In a separate test, the body core temperature of hens was predicted to within 0.3°C on average for the same range of air temperature, again within the limits of experimental uncertainty. Sensitivity analysis showed that the prediction of body temperature for chickens was most sensitive to ambient humidity at high air temperatures, and to body resistance. The paper discusses the limitations of the Models and the need for more measurements of heat losses from current breeds of livestock.
Mario Sznaier - One of the best experts on this subject based on the ideXlab platform.
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a randomized algorithm for Parsimonious Model identification
IEEE Transactions on Automatic Control, 2018Co-Authors: Burak Yilmaz, Korkut Bekiroglu, Constantino Lagoa, Mario SznaierAbstract:Identifying Parsimonious Models is generically a “hard” nonconvex problem. Available approaches typically rely on relaxations such as Group Lasso or nuclear norm minimization. Moreover, incorporating stability and Model order constraints into the formalism in such methods entails a substantial increase in computational complexity. Motivated by these challenges, in this paper we present algorithms for Parsimonious linear time invariant system identification aimed at identifying low-complexity Models which i) incorporate a priori knowledge on the system (e.g., stability), ii) allow for data with missing/nonuniform measurements, and iii) are able to use data obtained from several runs of the system with different unknown initial conditions. The randomized algorithms proposed are based on the concept of atomic norm and provide a numerically efficient way to identify sparse Models from large amounts of noisy data.
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Parsimonious Model identification via atomic norm minimization
European Control Conference, 2014Co-Authors: Korkut Bekiroglu, Constantino Lagoa, Burak Yilmaz, Mario SznaierAbstract:During the past few years a considerably research effort has been devoted to the problem of identifying Parsimonious Models from experimental data. Since this problem is generically non-convex, these approaches typically rely on relaxations such as Group Lasso or nuclear norm minimization. However, while these approaches usually work well in practice, there is no guarantee that using these surrogates will lead to the simplest Model explaining the experimental data. In addition, incorporating stability constraints into the formalism entails a substantial increase in the computational complexity. Alternatively stability and Model order constraints can be handled directly using a moments based approach. However, presently this approach is limited to relatively small sized problems, due to its computational complexity. Motivated by these difficulties, recently a new approach has been proposed based on the idea of representing the response of an LTI system as a linear combination of suitably chosen objects (atoms) and the observation that minimizing the atomic norm leads to sparse representations. In this paper we cover the fundamentals of this new approach and show that it leads to a very efficient algorithm, that avoids the need for using regularization steps and automatically incorporates stability constraints. In addition, this approach can be extended to accommodate non-uniform sampling and (unknown) initial conditions. These results are illustrated with several examples, including identification of a very lightly damped structure from time and frequency domain measurements.
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ECC - Parsimonious Model identification via atomic norm minimization
2014 European Control Conference (ECC), 2014Co-Authors: Korkut Bekiroglu, Constantino Lagoa, Burak Yilmaz, Mario SznaierAbstract:During the past few years a considerably research effort has been devoted to the problem of identifying Parsimonious Models from experimental data. Since this problem is generically non-convex, these approaches typically rely on relaxations such as Group Lasso or nuclear norm minimization. However, while these approaches usually work well in practice, there is no guarantee that using these surrogates will lead to the simplest Model explaining the experimental data. In addition, incorporating stability constraints into the formalism entails a substantial increase in the computational complexity. Alternatively stability and Model order constraints can be handled directly using a moments based approach. However, presently this approach is limited to relatively small sized problems, due to its computational complexity. Motivated by these difficulties, recently a new approach has been proposed based on the idea of representing the response of an LTI system as a linear combination of suitably chosen objects (atoms) and the observation that minimizing the atomic norm leads to sparse representations. In this paper we cover the fundamentals of this new approach and show that it leads to a very efficient algorithm, that avoids the need for using regularization steps and automatically incorporates stability constraints. In addition, this approach can be extended to accommodate non-uniform sampling and (unknown) initial conditions. These results are illustrated with several examples, including identification of a very lightly damped structure from time and frequency domain measurements.
Ivan Leguerinel - One of the best experts on this subject based on the ideXlab platform.
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on calculating sterility in thermal preservation methods application of the weibull frequency distribution Model
International Journal of Food Microbiology, 2002Co-Authors: Pierre Mafart, Olivier Couvert, S Gaillard, Ivan LeguerinelAbstract:A simple and Parsimonious Model which originated from the Weibull frequency distribution was proposed to describe nonlinear survival curves of spores. This Model was suitable for downward concavity curves (Bacillus cereus and Bacillus pumilus), as well as for upward concavity curves (Clostridium botulinum). It was shown that traditional F values calculated from this new Model were no longer additive, to such an extent that a heat treatment should be better characterized by the obtained decimal reduction of spores. A modified Bigelow method was then proposed to assess this decade reduction or to optimize the heat treatment for a target reduction ratio.
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On calculating sterility in thermal preservation methods : application of the Weibull frequency distribution Model
International Journal of Food Microbiology, 2002Co-Authors: Pierre Mafart, Olivier Couvert, S Gaillard, Ivan LeguerinelAbstract:A simple and Parsimonious Model originated from the Weibull frequency distribution was proposed to describe non linear survival curves of spores. This Model was suitable for downward concavity curves (Bacillus cereus and Bacillus pumilus) as well as for upward concavity curves (Clostridium botulinum). It was shown that traditional F-values calculated from this new Model were no more additive, to such an extend that a heat treatment should be better characterized by the obtained decade reduction of spores. A modified Bigelow method was then proposed to assess this decade reduction or to optimize the heat treatment for a target reduction ratio.