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| Curi,Thayla Morandi Ridolfi de Carvalho; Conti,Dante; Vercellino,Rimena do Amaral; Massari,Juliana Maria; Moura,Daniella Jorge de; Souza,Zigomar Menezes de; Montanari,Rafael. |
| ABSTRACT Ventilation systems are incorporated at intensive poultry farms to control environment conditions and thermal comfort of broilers. The ventilation system operates based on environmental data, particularly measured by sensors of temperature and relative humidity. Sensors are placed at different positions of the facility. Quality, number and positioning of the sensors are critical factors to achieve an efficient performance of the system. For this reason, a strategic positioning of the sensors associated to controllers could support the maintenance and management of the microclimate inside the facility. This research aims to identify the three most representative points for the positioning of sensors in order to support the ventilation system during... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Broiler farms; Environmental control; Geostatistics; Ordinary kriging; Welfare. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162017000200101 |
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| Maia,Ana Paula de Assis; Oliveira,Stanley Robson de Medeiros; Moura,Daniella Jorge de; Sarubbi,Juliana; Vercellino,Rimena do Amaral; Medeiros,Brenda Batista Lemos; Griska,Paulo Roberto. |
| Thermal comfort is of great importance in preserving body temperature homeostasis during thermal stress conditions. Although the thermal comfort of horses has been widely studied, there is no report of its relationship with surface temperature (T S). This study aimed to assess the potential of data mining techniques as a tool to associate surface temperature with thermal comfort of horses. T S was obtained using infrared thermography image processing. Physiological and environmental variables were used to define the predicted class, which classified thermal comfort as "comfort" and "discomfort". The variables of armpit, croup, breast and groin T S of horses and the predicted classes were then subjected to a machine learning process. All variables in the... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Feature selection methods; Data mining; Surface temperature; Infrared thermography; Thermoregulation. |
| Ano: 2013 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162013000600001 |
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