The Experts below are selected from a list of 72 Experts worldwide ranked by ideXlab platform

Claudio Sighieri - One of the best experts on this subject based on the ideXlab platform.

  • early evidence of the anticipatory response of plasma catecholamine in Equine Exercise
    Journal of Equine Veterinary Science, 2011
    Co-Authors: Paolo Baragli, Lucia Casini, Michele Ducci, Micaela Sgorbini, Claudio Sighieri
    Abstract:

    Abstract Catecholamines seem to play a role in Equine Exercise Physiology that is somewhat different from their role in human beings. In sport horses, a greater increase in plasma adrenaline (ADR) levels occurs in response to strenuous Exercise as compared with human beings. However, it is not known whether this is true for breeds not specifically bred for sport. The aim of this study was to gather data on plasma catecholamine kinetics during Exercise in a nonracing breed. We also attempted to evaluate the influence of the phases preceding the start of the Exercise on the kinetics of these molecules. Four 2-year-old female Esperia ponies were made to perform a four-step Exercise test on a treadmill. Blood samples were collected in the box (basal 1), in the treadmill room (basal 2), and at the conclusion of each step, using an automatic system. ADR and noradrenaline (NOR) levels were determined by high-pressure liquid chromatography. Results were analyzed using analysis of variance and the Student–Newman–Keuls test. As compared with basal 1, basal 2 showed a significant 19.6-fold increase for ADR and a 6.7-fold increase for NOR. The highest concentration was observed for both molecules at the end of the fourth step, with a significant 1.2-fold increase as compared with blood samples collected at basal 2 for ADR and a 2.4-fold increase for NOR. Therefore, in Esperia ponies, catecholamine showed a trend similar to that of Standardbreds and Thoroughbreds. The results reported in this study also revealed a marked increase in ADR in the phases preceding the beginning of physical activity. Therefore, the greater adrenergic activity in horses in response to Exercise could be because of an anticipatory response.

  • application of a constant blood withdrawal method in Equine Exercise Physiology studies
    Equine Veterinary Journal, 2010
    Co-Authors: Paolo Baragli, D Tedeschi, Franco Martelli, Domenico Gatta, Claudio Sighieri
    Abstract:

    Summary The aim of the present study was to test a constant blood withdrawal method (CBWM) to collect blood samples from horses during treadmill Exercise. CBWM was performed in 4 Standardbreds and 5 Haflinger horses. A peristaltic pump was used to control blood aspiration from an i.v. catheter via an extension line. Blood was collected using an automatic fractions collector, with a constant delay time between the drawing of blood and sample collection. Blood withdrawal using CBWM was made during a treadmill standardised Exercise test (SET). A blood flow of 12 ml/min was used and samples collected every 60 s during the entire period of Exercise. The volume of blood collected in each sample tube was 12.1 ± 0.2 ml, with a delay time of mean ± s.d. 25.3 ± 0.8 s. Plasma lactate kinetics based on measurement of lactate in each fraction showed an exponential increase during the first 13 min of Exercise (10.5 min of SET and 2.5 min recovery). The peak plasma lactate concentration was observed between 2.5 and 5.5 min after the end of SET. CBWM permits the kinetics of lactate and other blood-borne variables to be studied over time. This method could be a valuable aid for use in studying Equine Exercise Physiology.

Paolo Baragli - One of the best experts on this subject based on the ideXlab platform.

  • early evidence of the anticipatory response of plasma catecholamine in Equine Exercise
    Journal of Equine Veterinary Science, 2011
    Co-Authors: Paolo Baragli, Lucia Casini, Michele Ducci, Micaela Sgorbini, Claudio Sighieri
    Abstract:

    Abstract Catecholamines seem to play a role in Equine Exercise Physiology that is somewhat different from their role in human beings. In sport horses, a greater increase in plasma adrenaline (ADR) levels occurs in response to strenuous Exercise as compared with human beings. However, it is not known whether this is true for breeds not specifically bred for sport. The aim of this study was to gather data on plasma catecholamine kinetics during Exercise in a nonracing breed. We also attempted to evaluate the influence of the phases preceding the start of the Exercise on the kinetics of these molecules. Four 2-year-old female Esperia ponies were made to perform a four-step Exercise test on a treadmill. Blood samples were collected in the box (basal 1), in the treadmill room (basal 2), and at the conclusion of each step, using an automatic system. ADR and noradrenaline (NOR) levels were determined by high-pressure liquid chromatography. Results were analyzed using analysis of variance and the Student–Newman–Keuls test. As compared with basal 1, basal 2 showed a significant 19.6-fold increase for ADR and a 6.7-fold increase for NOR. The highest concentration was observed for both molecules at the end of the fourth step, with a significant 1.2-fold increase as compared with blood samples collected at basal 2 for ADR and a 2.4-fold increase for NOR. Therefore, in Esperia ponies, catecholamine showed a trend similar to that of Standardbreds and Thoroughbreds. The results reported in this study also revealed a marked increase in ADR in the phases preceding the beginning of physical activity. Therefore, the greater adrenergic activity in horses in response to Exercise could be because of an anticipatory response.

  • application of a constant blood withdrawal method in Equine Exercise Physiology studies
    Equine Veterinary Journal, 2010
    Co-Authors: Paolo Baragli, D Tedeschi, Franco Martelli, Domenico Gatta, Claudio Sighieri
    Abstract:

    Summary The aim of the present study was to test a constant blood withdrawal method (CBWM) to collect blood samples from horses during treadmill Exercise. CBWM was performed in 4 Standardbreds and 5 Haflinger horses. A peristaltic pump was used to control blood aspiration from an i.v. catheter via an extension line. Blood was collected using an automatic fractions collector, with a constant delay time between the drawing of blood and sample collection. Blood withdrawal using CBWM was made during a treadmill standardised Exercise test (SET). A blood flow of 12 ml/min was used and samples collected every 60 s during the entire period of Exercise. The volume of blood collected in each sample tube was 12.1 ± 0.2 ml, with a delay time of mean ± s.d. 25.3 ± 0.8 s. Plasma lactate kinetics based on measurement of lactate in each fraction showed an exponential increase during the first 13 min of Exercise (10.5 min of SET and 2.5 min recovery). The peak plasma lactate concentration was observed between 2.5 and 5.5 min after the end of SET. CBWM permits the kinetics of lactate and other blood-borne variables to be studied over time. This method could be a valuable aid for use in studying Equine Exercise Physiology.

Moura D.j. - One of the best experts on this subject based on the ideXlab platform.

  • Data Mining As A Tool To Evaluate Thermal Comfort Of Horses
    Katholieke Universiteit Leuven, 2015
    Co-Authors: Maia A.p.a., Medeiros B.b.l., Vercellino R.a., Sarubbi J., Oliveira S.r.m., Griska P.r., Moura D.j.
    Abstract:

    Thermal comfort is of great importance to preserve body temperature homeostasis during thermal stress conditions. Although thermal comfort of horses has been widely studied, research has not reported its relationship to surface temperature (TS). The aim of this study was to investigate the potential of data mining techniques as a tool to associate surface temperature with thermal comfort of horses. TS was measured using infrared thermographic image processing. Physiological and environmental variables were used to define the predicted class, which classified thermal comfort as "comfort" and "discomfort". The TS variables for the armpit, croup, breast and groin of horses and the predicted class were then submitted to a machine learning process. All dataset variables were considered relevant to the classification problem and the decision-tree model yielded an accuracy rate of 74.0%. The feature selection methods used to reduce computational cost and simplify predictive learning reduced the model accuracy to 70.1%; however the model became simpler with representative rules. For these selection methods and for the classification using all attributes, TS of armpit and breast had a higher rating power for predicting thermal comfort. The data mining techniques had discovered new variables relating to the thermal comfort of horses.281290FancomAutio, E., Neste, R., Airaksinen, S., Heiskanen, M., Measuring the heat loss in horses in different seasons by infrared thermography (2006) Journal of Applied Animal Welfare Science, 9, pp. 211-221Batista, G.H.A.P.A., Prati, R.C., Monard, M.C., A study of the behavior of several methods for balancing machine learning training data (2004) SIGK DD Explorations, 6, pp. 20-29Castanheira, M., Paiva, S.R., Louvandini, H., Landim, A., Fiorvanti, M.C.S., Paludo, G.R., Dallago, B.S., McManus, C., Multivariate analysis for characteristics of heat tolerance in horses in Brazil (2010) Tropical Animal Health and Production, 42, pp. 185-191Chapman, P., Clinton, J., Kerber, R., Khabaz, T., Reinartz, T., Shearer, C., Wirth, R., CRIS P-DM 1.0: Step-by-step data mining guide (2000) The CRIS P-DM Consortium, , http://www.spss.ch/upload/1107356429_CrispDM1.0.pdf, Available atChawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P., SMOTE : Synthetic minority over-sampling technique (2002) Journal of Artificial Intelligence Research, 16, pp. 321-357Crivelenti, R.C., Coelho, R.M., Adami, S.F., Oliveira, S.R.M., Data mining to infer soil-landscape relationships in digital soil mapping (2009) Pesquisa Agropecuária Brasileira, 44, pp. 1707-1715. , Portuguese, with abstract in EnglishCunningham, J.G., (2002) Textbook F Veterinary Physiology, , Saunders/Elsevier, Philadelphia, PA, USAHan, J., Kamber, M., Pei, J., (2011) Data Mining: Concepts and Techniques, , Morgan Kaufmann Publishers, San Francisco, CA, USAHuang, C.-J., Yang, D.-X., Chuang, Y.-T., Application of wrapper approach and composite classifier to the stock trend prediction (2008) Expert Systems with Applications, 34, pp. 2870-2878Japkowicz, N., (2003) Class Imbalances: Are We Focusing on the Right Issue?, , http://www.site.uottawa.ca/~nat/Papers/papers.html, Accessed Oct. 16, 2012Jodkowska, E., Dudek, K., Przewozny, M., The maximum temperatures (Tmax) distribution on the body surface of sport horses (2011) Journal of Life Sciences, 5, pp. 291-297Jones, S., Horseback riding in the dog days (2009) Animal Science E-news University of Arkansas, 2 (3-4), p. 7. , http://www.aragriculture.org/news/animal_science_enews/2009/july2009.htm, The Cooperative Extension DivisonKohn, C.W., Hinchcliff, K.W., Physiological responses to the endurance test of a 3-dayevent during hot and cool weather (1995) Equine Veterinary Journal, 20, pp. 31-36Kohn, C.W., Hinchcliff, K.W., McKeever, K.H., Evaluation of washing with cold water to facilitate heat dissipation in horses Exercised in hot, humid conditions (1999) American Journal of Veterinary Research, 60, pp. 299-305Lin, S.-W., Chen, S.-C., Parameter determination and feature selection for C4.5 algorithm using scatter search approach (2012) Software Computer, 16, pp. 63-75Lutu, P.E.N., Engelbrecht, A.P., A decision rule-based method for feature selection in predictive data mining (2010) Expert Systems with Applications, 37, pp. 602-609Marlin, D.J., Scott, C.M., Roberts, C.A., Casas, I., Holah, G., Schroter, R., Post Exercise changes in compartmental body temperature accompanying intermittent cold water cooling in the hyperthermic horse (1998) Equine Veterinary Journal, 30, pp. 28-34McConaghy, F.F., Hodgson, D.R., Rose, R.J., Hales, J.R., Redistribution of cardiac output in response to heat exposure in the pony (1996) Equine Veterinary Journal Supplement, 22, pp. 42-46McCutcheon, L.J., Geor, R.J., Thermoregulation and Exercise-associated heat stress (2008) Equine Exercise Physiology: The Science of Exercise in the Athletic Horse, pp. 382-396. , Hinchcliff, K.W. Geor, R.J. Kaneps, A.J. eds. Elsevier Health Sciences, Philadelphia, PA, USAMcKeever, K.H., Eaton, T.L., Geiser, S., Kearns, C.F., Lehnhard, R.A., Age related decreases I thermoregulation and cardiovascular function in horses (2010) Equine Veterinary Journal, 42, pp. 449-454Quinlan, J.R., (1993) C4.5: Programs for Machine Learning, , Morgan Kaufmann, San Francisco, CA, USASikora, M., Induction and pruning of classification rules for prediction of microseismic hazards in coal mines (2011) Expert Systems with Applications, 38, pp. 6748-6758Tattersall, G.J., Cadena, V., Insights into animal temperature adaptations revealed through thermal imaging (2010) The Imaging Science Journal, 58, pp. 261-268Tsang, S., Kao, B., Yip, K.Y., Ho, W., Lee, S.D., Decision tree for uncertain data (2011) IEEE Transactions on Knowledge and Data Engineering, 23, pp. 64-78Wang, T., Qin, Z., Jin, Z., Zhang, S., Handling over-fitting in test cost-sensitive decision tree learning by feature selection, smoothing and pruning (2010) The Journal of Systems and Software, 83, pp. 1137-114

  • Data Mining Applied To Horse Thermal Comfort
    2015
    Co-Authors: Maia A.p.a., Medeiros B.b.l., Vercellino R.a., Sarubbi J., Oliveira S.r.m., Griska P.r., Moura D.j.
    Abstract:

    Thermal comfort plays a critical role in body temperature regulation. Heat-regulation mechanisms, such as changes in peripheral blood flow, are activated by thermal stress to maintain body homeostasis and it can results in a fluctuation of skin temperature. Although thermal comfort of horse has been studied, its relation with surface temperature is rarely seen in the literature. Therefore, the aim of this study was to verify the potential of data mining techniques in knowledge discovery by associating surface temperature with thermal comfort of horses. The decision tree model presented 74.0% of accuracy and all attributes of dataset were considered relevant for the classification problem. The results revealed the potential of data mining techniques to Equine thermal comfort classification problems.422428Autio, E., Neste, R., Airaksinen, S., Heiskanen, M.-L., Measuring the heat loss in horses in different seasons by infrared thermography (2006) Journal of Applied Animal Welfare Science, 9 (3), pp. 211-221. , DOI 10.1207/s15327604jaws0903-3Batista, G.E.A.P.A., Prati, R.C., Monard, M.C., A study of the behavior of several methods for balancing machine learning training set (2003) SIGKDD Exploration, 6 (1), pp. 20-29Chapman, P., Clinton, J., Kerber, R., Khabaz, T., Reinartz, T., Shearer, C., Wirth, R., (2000) CRISP-DM 1.0: Step-by-step Data Mining Guide, , http://www.spss.ch/upload/1107356429_CrispDM1.0.pdf, Available at: Accessed 22 November 2011Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P., SMOTE: Synthetic minority over-sampling technique (2002) Journal of Artificial Intelligence Research, 16, pp. 321-357. , http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume16/chawla02a.pdfCunningham, J.G., Termorregulação (2002) Tratado de Fisiologia Veterinária, , 3rd ed. São Paulo: Guanabara KooganFayyad, U., Stolorz, P., Data mining and KDD: Promise and challenges (1997) Future Generation Computer Systems, 13 (2-3), pp. 99-115. , PII S0167739X97000150Ferreira, V.M.O.S., Francisco, N.S., Belloni, M., Aguirre, G.M.Z., Caldara, F.R., Nääs, I.A., Garcia, R.G., Polycarpo, G.V., Infrared thermography applied to the evaluation of metabolic heat loss of chicks fed with different energy densities Brazilian J. of Poult. Sci., 13 (2), pp. 113-118Hodgson, D.R., Davies, R.E., McConaghy, F.F., Thermoregulation in the horse in response to Exercise (1994) British Veterinary Journal, 150 (3), pp. 219-234Huang, P., Lin, P., Shangwei, Y., Xiao, M., Data Mining for seasonal influences in broiler breeding based on observational study (2011) Information Computing and Applic., 7030, pp. 25-32Japkowicz, N., Class imbalances: Are we focusing on the right issue? (2003) 2nd Workshop on Learning from Imbalanced Data Sets, pp. 17-23Jones, S., Horsback Riding in the Dog Days (2009) (S.L.): Animal Science e-news University of Arkansas, 2 (3), pp. 3-4. , The Cooperative Extension Divison, 7pKnížková, I., Kinc, P., Gürdil, G.A.K., Pinar, Y., Selvi, K.Ç., Applications of infrared thermography in animal production (2007) J. of Fac. of Agric., 22 (3), pp. 329-336Laurikkala, J., (2001) Improving Identification of Difficult Small Classes by Balancing Class Distribution, , http://sci2s.ugr.es/keel/pdf/algorithm/congreso/2001-Laurikkala-LNCS.pdf, Available at: Accessed 01 November 2011Marlin, D.J., Scott, C.M., Roberts, C.A., Casas, I., Holah, G., Schroter, R., Post Exercise changes in compartmental body temperature accompanying intermittent cold water cooling in the hyperthermic horse (1998) Equine Vet. J., 30, pp. 28-34McCutcheon, L.J., Geor, R.J., Thermoregulation and Exercise-associated heat stress (2008) Equine Exercise Physiology: The Science of Exercise in the Athletic Horse, pp. 382-386. , Hinchcliff, K.W.R. J. Geor, A. J. Kaneps. Philadelphia: ElsevierMutaf, S., Şeber Kahraman, N., Frat, M.Z., Surface wetting and its effect on body and surface temperatures of domestic laying hens at different thermal conditions (2008) Poult. Sci., 87, pp. 2441-2450Paludo, G.R., McManus, C., De Melo, R.Q., Cardoso, A.G., Da, S.M.F.P., Moreira, M., Fuck, B.H., Effect of Heat Stress and Exercise on Physiological Parameters of Horses of the Brazilian Army (2002) Revista Brasileira de Zootecnia, 31 (3), pp. 1130-1142Oliveira, L.A., Campei, J.E.G., Azevedo, D.M.M.R., Costa, A.P.R., Turco, S.H.N., Moura, J.W.S., Estudo de respostas fisiológicas de equinos sem raça definida e da raça quarto de milha às condições climáticas de Teresina, Piauí (2008) Ciencia Animal Brasileira, 9 (4), pp. 827-838Vale, M.M., Moura, D.J., Nääs, I.A., Pereira, D.F., Characterization of heat waves affecting mortality of broilers between 29 days and market age (2010) Brazilian J.of Poult.Sci., 12 (4), pp. 279-28

Griska P.r. - One of the best experts on this subject based on the ideXlab platform.

  • Data Mining As A Tool To Evaluate Thermal Comfort Of Horses
    Katholieke Universiteit Leuven, 2015
    Co-Authors: Maia A.p.a., Medeiros B.b.l., Vercellino R.a., Sarubbi J., Oliveira S.r.m., Griska P.r., Moura D.j.
    Abstract:

    Thermal comfort is of great importance to preserve body temperature homeostasis during thermal stress conditions. Although thermal comfort of horses has been widely studied, research has not reported its relationship to surface temperature (TS). The aim of this study was to investigate the potential of data mining techniques as a tool to associate surface temperature with thermal comfort of horses. TS was measured using infrared thermographic image processing. Physiological and environmental variables were used to define the predicted class, which classified thermal comfort as "comfort" and "discomfort". The TS variables for the armpit, croup, breast and groin of horses and the predicted class were then submitted to a machine learning process. All dataset variables were considered relevant to the classification problem and the decision-tree model yielded an accuracy rate of 74.0%. The feature selection methods used to reduce computational cost and simplify predictive learning reduced the model accuracy to 70.1%; however the model became simpler with representative rules. For these selection methods and for the classification using all attributes, TS of armpit and breast had a higher rating power for predicting thermal comfort. The data mining techniques had discovered new variables relating to the thermal comfort of horses.281290FancomAutio, E., Neste, R., Airaksinen, S., Heiskanen, M., Measuring the heat loss in horses in different seasons by infrared thermography (2006) Journal of Applied Animal Welfare Science, 9, pp. 211-221Batista, G.H.A.P.A., Prati, R.C., Monard, M.C., A study of the behavior of several methods for balancing machine learning training data (2004) SIGK DD Explorations, 6, pp. 20-29Castanheira, M., Paiva, S.R., Louvandini, H., Landim, A., Fiorvanti, M.C.S., Paludo, G.R., Dallago, B.S., McManus, C., Multivariate analysis for characteristics of heat tolerance in horses in Brazil (2010) Tropical Animal Health and Production, 42, pp. 185-191Chapman, P., Clinton, J., Kerber, R., Khabaz, T., Reinartz, T., Shearer, C., Wirth, R., CRIS P-DM 1.0: Step-by-step data mining guide (2000) The CRIS P-DM Consortium, , http://www.spss.ch/upload/1107356429_CrispDM1.0.pdf, Available atChawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P., SMOTE : Synthetic minority over-sampling technique (2002) Journal of Artificial Intelligence Research, 16, pp. 321-357Crivelenti, R.C., Coelho, R.M., Adami, S.F., Oliveira, S.R.M., Data mining to infer soil-landscape relationships in digital soil mapping (2009) Pesquisa Agropecuária Brasileira, 44, pp. 1707-1715. , Portuguese, with abstract in EnglishCunningham, J.G., (2002) Textbook F Veterinary Physiology, , Saunders/Elsevier, Philadelphia, PA, USAHan, J., Kamber, M., Pei, J., (2011) Data Mining: Concepts and Techniques, , Morgan Kaufmann Publishers, San Francisco, CA, USAHuang, C.-J., Yang, D.-X., Chuang, Y.-T., Application of wrapper approach and composite classifier to the stock trend prediction (2008) Expert Systems with Applications, 34, pp. 2870-2878Japkowicz, N., (2003) Class Imbalances: Are We Focusing on the Right Issue?, , http://www.site.uottawa.ca/~nat/Papers/papers.html, Accessed Oct. 16, 2012Jodkowska, E., Dudek, K., Przewozny, M., The maximum temperatures (Tmax) distribution on the body surface of sport horses (2011) Journal of Life Sciences, 5, pp. 291-297Jones, S., Horseback riding in the dog days (2009) Animal Science E-news University of Arkansas, 2 (3-4), p. 7. , http://www.aragriculture.org/news/animal_science_enews/2009/july2009.htm, The Cooperative Extension DivisonKohn, C.W., Hinchcliff, K.W., Physiological responses to the endurance test of a 3-dayevent during hot and cool weather (1995) Equine Veterinary Journal, 20, pp. 31-36Kohn, C.W., Hinchcliff, K.W., McKeever, K.H., Evaluation of washing with cold water to facilitate heat dissipation in horses Exercised in hot, humid conditions (1999) American Journal of Veterinary Research, 60, pp. 299-305Lin, S.-W., Chen, S.-C., Parameter determination and feature selection for C4.5 algorithm using scatter search approach (2012) Software Computer, 16, pp. 63-75Lutu, P.E.N., Engelbrecht, A.P., A decision rule-based method for feature selection in predictive data mining (2010) Expert Systems with Applications, 37, pp. 602-609Marlin, D.J., Scott, C.M., Roberts, C.A., Casas, I., Holah, G., Schroter, R., Post Exercise changes in compartmental body temperature accompanying intermittent cold water cooling in the hyperthermic horse (1998) Equine Veterinary Journal, 30, pp. 28-34McConaghy, F.F., Hodgson, D.R., Rose, R.J., Hales, J.R., Redistribution of cardiac output in response to heat exposure in the pony (1996) Equine Veterinary Journal Supplement, 22, pp. 42-46McCutcheon, L.J., Geor, R.J., Thermoregulation and Exercise-associated heat stress (2008) Equine Exercise Physiology: The Science of Exercise in the Athletic Horse, pp. 382-396. , Hinchcliff, K.W. Geor, R.J. Kaneps, A.J. eds. Elsevier Health Sciences, Philadelphia, PA, USAMcKeever, K.H., Eaton, T.L., Geiser, S., Kearns, C.F., Lehnhard, R.A., Age related decreases I thermoregulation and cardiovascular function in horses (2010) Equine Veterinary Journal, 42, pp. 449-454Quinlan, J.R., (1993) C4.5: Programs for Machine Learning, , Morgan Kaufmann, San Francisco, CA, USASikora, M., Induction and pruning of classification rules for prediction of microseismic hazards in coal mines (2011) Expert Systems with Applications, 38, pp. 6748-6758Tattersall, G.J., Cadena, V., Insights into animal temperature adaptations revealed through thermal imaging (2010) The Imaging Science Journal, 58, pp. 261-268Tsang, S., Kao, B., Yip, K.Y., Ho, W., Lee, S.D., Decision tree for uncertain data (2011) IEEE Transactions on Knowledge and Data Engineering, 23, pp. 64-78Wang, T., Qin, Z., Jin, Z., Zhang, S., Handling over-fitting in test cost-sensitive decision tree learning by feature selection, smoothing and pruning (2010) The Journal of Systems and Software, 83, pp. 1137-114

  • Infrared Thermography To Evaluate The Training Horse Thermoregulation [uso Da Termografia Infravermelha Na Análise Da Termorregulação De Cavalo Em Treinamento]
    2015
    Co-Authors: De Moura D.j., Maia A.p.a., Medeiros B.b.l., Vercellino R.a., Sarubbi J., Griska P.r.
    Abstract:

    Heat-regulation mechanisms, such as changes in peripheral blood flow, are activated by thermal stress to maintain body homeostasis. The infrared thermography enables to identify changes in blood flow and it has been valuable for recognizing stress in animals. This research aimed to evaluate the use of infrared thermography in the training horse thermoregulation. An Anglo-Arab horse was studied and Exercised once a day. Infrared thermography images of horsés armpit, croup, breast and groin and physiological parameters were taken before and after Exercise and 0, 5 and 10 minutes after shower for eight days. The air temperature, relative humidity and air velocity were also registered. There were no differences between the surface temperature of croup and breast and the treatments, implying low participation in thermoregulation. However, the armpit and groin temperature increased after the Exercise and decreased after shower, suggesting that vasomotor mechanisms were activated to heat exchange. Similar results were found for physiological parameters which show organism thermal responses for heat loss. It was concluded that infrared thermography allowed accuracy in determining the horse body surface temperature and it was possible to infer on thermoregulation.3112332Autio, E., Neste, R., Airaksinen, S., Heiskanen, M., Measuring the heat loss in horses in different seasons by infrared thermography (2006) Journal of Applied Animal Welfare Science, 9 (3), pp. 211-221. , MahwahBouzida, N., Bendada, A., Maldague, X.P., Visualization of body thermoregulation by infrared imaging (2009) Journal of Thermal Biology, 34 (3), pp. 120-126. , OxfordBrandi, R.A., Furtado, C.E., Martins, E.N., Freitas, E.V.V., Lacerda Neto, J.C., Queiroz Neto, A., Ribeiro, L.B., Desempenho de equinos submetidos a enduro alimentados com níveis de óleo de soja na dieta (2009) Revista Brasileira de Saúde e Produção Animal, 10 (2), pp. 311-321. , SalvadorCarvalho, T., Mara, L.S., Hidratação e nutrição no esporte (2010) Revista Brasileira de Medicina do Esporte, 16 (2), pp. 33-40. , Rio de JaneiroCunningham, J.G., Termorregulação (2002) Tratado de fisiologia veterinária, pp. 550-561. , 3.ed. São Paulo: Guanabara KooganEtchichury, M., (2008) Termorregulação em cavalos submetidos a diferentes métodos de resfriamento pós-exercício. 2008, , 103 f. Tese (Doutorado em Zootecnia) - Universidade de São Paulo, Faculdade de Zootecnia e Engenharia de Alimentos, PirassunungaJones, S., Horsback riding in the dog days (2009) Animal Science e-News, 2 (3), pp. 3-4. , http://www.aragriculture.org/News/animal_science_enews/2009/pdf/july2009.pdf, Disponível em. Acesso em: 5 maio 2010Knížková, I., Kunc, P., Gürdíl, G.A.K., Pinar, Y., Selví, K.Ç., Applications of infrared thermography in animal production (2007) Journal of the Faculty of Agriculture, 22 (3), pp. 329-336. , KyushuKohn, C.W., Hinchcliff, K.W., Mckeever, K.H., Evaluation of washing with cold water to facilitate heat dissipation in horses Exercised in hot, humid conditions (1999) American Journal of Veterinary Research, 60 (3), pp. 299-305. , SchaumburgOliveira, L.A., Campel, J.E.G., Azevedo, D.M.M.R., Costa, A.P.R., Turco, S.H.N., Moura, J.W.S., Estudo de respostas fisiológicas de equinos sem raça definida e da raça quarto de milha às condições climáticas de Teresina, Piauí. (2008) Ciência Animal Brasileira, 9 (4), pp. 827-838. , GoiâniaMarlin, D.J., Scott, C.M., Roberts, C.A., Casas, I., Holah, G., Schroter, R., Post Exercise changes in compartmental body temperature accompanying intermittent cold water cooling in the hyperthermic horse (1998) Equine Veterinary Journal, 222 (30), pp. 28-34. , Borough GreenMcconaghy, F.F., Hodgson, D.R., Rose, R.J., Hales, J.R.S., Redistribution of cardiac output in response to heat exposure in the pony (1996) Equine Veterinary Journal Supplement, 22, pp. 42-46. , july,NewmarketMccutcheon, L.J., Geor, R.J., Thermoregulation and Exercise-associated heat stress (2008) Equine Exercise Physiology: the science of Exercise in the athletic horse, pp. 382-386. , HINCHCLIFF, K.W.GEOR, R.J.KANEPS, A.J. Philadelphia: ElsevierMorgan, K., Ehrlemark, A., Sällvik, K., Dissipation of heat from standing horses exposed to ambient temperatures between -3 °C and 37 °C (1997) Journal of Thermal Biology, 22 (3), pp. 177-186. , Great BritainPaludo, G.R., Mcmanus, C., Melo, R.Q., Cardoso, A.G., Mello, F.P.S., Moreira, M., Fuck, B.H., Efeito do estresse térmico e do exercício sobre os parâmetros fisiológicos de cavalos do exército brasileiro (2002) Revista Brasileira de Zootecnia, 31 (3), pp. 1.130-1.142. , Viçosa-MGPerissonoto, M., Moura, D.J., Matarazzo, S.V., Silva, I.J.O., Lima, K.A.O., Efeito da utilização de sistemas de climatização nos parâmetros fisiológicos do gado leiteiro (2006) Engenharia Agrícola, 26 (3), pp. 663-671. , JaboticabalPerrone, G.M., Caviglia, J.F., Pérez, A., Fidanza, M., Marquez, A., Catelli, J.L., González, G., Cambios em las variables fisiológicas en equinos compitiendo en una prueba combinada (2006) Anales de Veterinaria, 22, pp. 35-42. , MurciaPirrone, F., Albertini, M., Clement, M.G., Lafortuna, C.L., Respiratory mechanics in Standardbred horses with sub-clinical inflammatory airway disease and poor athletic performance (2007) The Veterinary Journal, 173, pp. 144-150. , LondonPuoli Filho, J.N.P., Barros Neto, T.L., Rodrigues, H.M., Garcia, H.P.L., Parâmetros fisiológicos do desempenho de cavalos de alta performance hidratados voluntariamente com água ou solução isotônica contendo carboidrato (2007) Brazilian Journal of Veterinary Research and Animal Science, 44 (2), pp. 122-131. , São PauloRibeiro, N.L., Furtado, D.A., Medeiros, A.N., Ribeiro, M.N., Silva, R.C.B., Souza, C.M.S., Avaliação dos índices de conforto térmico, parâmetros fisiológicos e gradiente térmico de ovinos nativos (2008) Revista de Engenharia Agrícola, 28 (4), pp. 614-623. , JaboticabalSilva, L.A.C., Santos, S.A., Silva, R.A.S., Mcmanus, C., Petzold, H., Adaptação do cavalo pantaneiro ao estresse da lida diária de gado no Pantanal, Brasil. (2005) Archivos de Zootecnia, 54, pp. 509-513. , CórdobaStewart, M., Webster, J.R., Schaefer, A.L., Cook, J., Scott, S.L., Infrared thermography as a non-invasive tool to study animal welfare (2005) Animal Welfare, 14, pp. 319-325. , South MimmsTitto, E.A.L., Pereira, A.M.F., Toledo, L.R.A., Passini, R., Nogueira Filho, J.C.M., Gobesso, A.A.O., Etchichury, M., Titto, C.G., Concentração de eletrólitos em equinos submetidos a diferentes temperaturas (2009) Revista Brasileira de Saúde e Produção Animal, 10 (1), pp. 236-244. , Salvador(2007) SAEG - Sistemas para análises estatísticas e genéticas, p. 150. , Universidade Federal De Viçosa. Versão 9.1. Viçosa-MG. (Manual do usuário

  • Data Mining Applied To Horse Thermal Comfort
    2015
    Co-Authors: Maia A.p.a., Medeiros B.b.l., Vercellino R.a., Sarubbi J., Oliveira S.r.m., Griska P.r., Moura D.j.
    Abstract:

    Thermal comfort plays a critical role in body temperature regulation. Heat-regulation mechanisms, such as changes in peripheral blood flow, are activated by thermal stress to maintain body homeostasis and it can results in a fluctuation of skin temperature. Although thermal comfort of horse has been studied, its relation with surface temperature is rarely seen in the literature. Therefore, the aim of this study was to verify the potential of data mining techniques in knowledge discovery by associating surface temperature with thermal comfort of horses. The decision tree model presented 74.0% of accuracy and all attributes of dataset were considered relevant for the classification problem. The results revealed the potential of data mining techniques to Equine thermal comfort classification problems.422428Autio, E., Neste, R., Airaksinen, S., Heiskanen, M.-L., Measuring the heat loss in horses in different seasons by infrared thermography (2006) Journal of Applied Animal Welfare Science, 9 (3), pp. 211-221. , DOI 10.1207/s15327604jaws0903-3Batista, G.E.A.P.A., Prati, R.C., Monard, M.C., A study of the behavior of several methods for balancing machine learning training set (2003) SIGKDD Exploration, 6 (1), pp. 20-29Chapman, P., Clinton, J., Kerber, R., Khabaz, T., Reinartz, T., Shearer, C., Wirth, R., (2000) CRISP-DM 1.0: Step-by-step Data Mining Guide, , http://www.spss.ch/upload/1107356429_CrispDM1.0.pdf, Available at: Accessed 22 November 2011Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P., SMOTE: Synthetic minority over-sampling technique (2002) Journal of Artificial Intelligence Research, 16, pp. 321-357. , http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume16/chawla02a.pdfCunningham, J.G., Termorregulação (2002) Tratado de Fisiologia Veterinária, , 3rd ed. São Paulo: Guanabara KooganFayyad, U., Stolorz, P., Data mining and KDD: Promise and challenges (1997) Future Generation Computer Systems, 13 (2-3), pp. 99-115. , PII S0167739X97000150Ferreira, V.M.O.S., Francisco, N.S., Belloni, M., Aguirre, G.M.Z., Caldara, F.R., Nääs, I.A., Garcia, R.G., Polycarpo, G.V., Infrared thermography applied to the evaluation of metabolic heat loss of chicks fed with different energy densities Brazilian J. of Poult. Sci., 13 (2), pp. 113-118Hodgson, D.R., Davies, R.E., McConaghy, F.F., Thermoregulation in the horse in response to Exercise (1994) British Veterinary Journal, 150 (3), pp. 219-234Huang, P., Lin, P., Shangwei, Y., Xiao, M., Data Mining for seasonal influences in broiler breeding based on observational study (2011) Information Computing and Applic., 7030, pp. 25-32Japkowicz, N., Class imbalances: Are we focusing on the right issue? (2003) 2nd Workshop on Learning from Imbalanced Data Sets, pp. 17-23Jones, S., Horsback Riding in the Dog Days (2009) (S.L.): Animal Science e-news University of Arkansas, 2 (3), pp. 3-4. , The Cooperative Extension Divison, 7pKnížková, I., Kinc, P., Gürdil, G.A.K., Pinar, Y., Selvi, K.Ç., Applications of infrared thermography in animal production (2007) J. of Fac. of Agric., 22 (3), pp. 329-336Laurikkala, J., (2001) Improving Identification of Difficult Small Classes by Balancing Class Distribution, , http://sci2s.ugr.es/keel/pdf/algorithm/congreso/2001-Laurikkala-LNCS.pdf, Available at: Accessed 01 November 2011Marlin, D.J., Scott, C.M., Roberts, C.A., Casas, I., Holah, G., Schroter, R., Post Exercise changes in compartmental body temperature accompanying intermittent cold water cooling in the hyperthermic horse (1998) Equine Vet. J., 30, pp. 28-34McCutcheon, L.J., Geor, R.J., Thermoregulation and Exercise-associated heat stress (2008) Equine Exercise Physiology: The Science of Exercise in the Athletic Horse, pp. 382-386. , Hinchcliff, K.W.R. J. Geor, A. J. Kaneps. Philadelphia: ElsevierMutaf, S., Şeber Kahraman, N., Frat, M.Z., Surface wetting and its effect on body and surface temperatures of domestic laying hens at different thermal conditions (2008) Poult. Sci., 87, pp. 2441-2450Paludo, G.R., McManus, C., De Melo, R.Q., Cardoso, A.G., Da, S.M.F.P., Moreira, M., Fuck, B.H., Effect of Heat Stress and Exercise on Physiological Parameters of Horses of the Brazilian Army (2002) Revista Brasileira de Zootecnia, 31 (3), pp. 1130-1142Oliveira, L.A., Campei, J.E.G., Azevedo, D.M.M.R., Costa, A.P.R., Turco, S.H.N., Moura, J.W.S., Estudo de respostas fisiológicas de equinos sem raça definida e da raça quarto de milha às condições climáticas de Teresina, Piauí (2008) Ciencia Animal Brasileira, 9 (4), pp. 827-838Vale, M.M., Moura, D.J., Nääs, I.A., Pereira, D.F., Characterization of heat waves affecting mortality of broilers between 29 days and market age (2010) Brazilian J.of Poult.Sci., 12 (4), pp. 279-28

Maia A.p.a. - One of the best experts on this subject based on the ideXlab platform.

  • Data Mining As A Tool To Evaluate Thermal Comfort Of Horses
    Katholieke Universiteit Leuven, 2015
    Co-Authors: Maia A.p.a., Medeiros B.b.l., Vercellino R.a., Sarubbi J., Oliveira S.r.m., Griska P.r., Moura D.j.
    Abstract:

    Thermal comfort is of great importance to preserve body temperature homeostasis during thermal stress conditions. Although thermal comfort of horses has been widely studied, research has not reported its relationship to surface temperature (TS). The aim of this study was to investigate the potential of data mining techniques as a tool to associate surface temperature with thermal comfort of horses. TS was measured using infrared thermographic image processing. Physiological and environmental variables were used to define the predicted class, which classified thermal comfort as "comfort" and "discomfort". The TS variables for the armpit, croup, breast and groin of horses and the predicted class were then submitted to a machine learning process. All dataset variables were considered relevant to the classification problem and the decision-tree model yielded an accuracy rate of 74.0%. The feature selection methods used to reduce computational cost and simplify predictive learning reduced the model accuracy to 70.1%; however the model became simpler with representative rules. For these selection methods and for the classification using all attributes, TS of armpit and breast had a higher rating power for predicting thermal comfort. The data mining techniques had discovered new variables relating to the thermal comfort of horses.281290FancomAutio, E., Neste, R., Airaksinen, S., Heiskanen, M., Measuring the heat loss in horses in different seasons by infrared thermography (2006) Journal of Applied Animal Welfare Science, 9, pp. 211-221Batista, G.H.A.P.A., Prati, R.C., Monard, M.C., A study of the behavior of several methods for balancing machine learning training data (2004) SIGK DD Explorations, 6, pp. 20-29Castanheira, M., Paiva, S.R., Louvandini, H., Landim, A., Fiorvanti, M.C.S., Paludo, G.R., Dallago, B.S., McManus, C., Multivariate analysis for characteristics of heat tolerance in horses in Brazil (2010) Tropical Animal Health and Production, 42, pp. 185-191Chapman, P., Clinton, J., Kerber, R., Khabaz, T., Reinartz, T., Shearer, C., Wirth, R., CRIS P-DM 1.0: Step-by-step data mining guide (2000) The CRIS P-DM Consortium, , http://www.spss.ch/upload/1107356429_CrispDM1.0.pdf, Available atChawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P., SMOTE : Synthetic minority over-sampling technique (2002) Journal of Artificial Intelligence Research, 16, pp. 321-357Crivelenti, R.C., Coelho, R.M., Adami, S.F., Oliveira, S.R.M., Data mining to infer soil-landscape relationships in digital soil mapping (2009) Pesquisa Agropecuária Brasileira, 44, pp. 1707-1715. , Portuguese, with abstract in EnglishCunningham, J.G., (2002) Textbook F Veterinary Physiology, , Saunders/Elsevier, Philadelphia, PA, USAHan, J., Kamber, M., Pei, J., (2011) Data Mining: Concepts and Techniques, , Morgan Kaufmann Publishers, San Francisco, CA, USAHuang, C.-J., Yang, D.-X., Chuang, Y.-T., Application of wrapper approach and composite classifier to the stock trend prediction (2008) Expert Systems with Applications, 34, pp. 2870-2878Japkowicz, N., (2003) Class Imbalances: Are We Focusing on the Right Issue?, , http://www.site.uottawa.ca/~nat/Papers/papers.html, Accessed Oct. 16, 2012Jodkowska, E., Dudek, K., Przewozny, M., The maximum temperatures (Tmax) distribution on the body surface of sport horses (2011) Journal of Life Sciences, 5, pp. 291-297Jones, S., Horseback riding in the dog days (2009) Animal Science E-news University of Arkansas, 2 (3-4), p. 7. , http://www.aragriculture.org/news/animal_science_enews/2009/july2009.htm, The Cooperative Extension DivisonKohn, C.W., Hinchcliff, K.W., Physiological responses to the endurance test of a 3-dayevent during hot and cool weather (1995) Equine Veterinary Journal, 20, pp. 31-36Kohn, C.W., Hinchcliff, K.W., McKeever, K.H., Evaluation of washing with cold water to facilitate heat dissipation in horses Exercised in hot, humid conditions (1999) American Journal of Veterinary Research, 60, pp. 299-305Lin, S.-W., Chen, S.-C., Parameter determination and feature selection for C4.5 algorithm using scatter search approach (2012) Software Computer, 16, pp. 63-75Lutu, P.E.N., Engelbrecht, A.P., A decision rule-based method for feature selection in predictive data mining (2010) Expert Systems with Applications, 37, pp. 602-609Marlin, D.J., Scott, C.M., Roberts, C.A., Casas, I., Holah, G., Schroter, R., Post Exercise changes in compartmental body temperature accompanying intermittent cold water cooling in the hyperthermic horse (1998) Equine Veterinary Journal, 30, pp. 28-34McConaghy, F.F., Hodgson, D.R., Rose, R.J., Hales, J.R., Redistribution of cardiac output in response to heat exposure in the pony (1996) Equine Veterinary Journal Supplement, 22, pp. 42-46McCutcheon, L.J., Geor, R.J., Thermoregulation and Exercise-associated heat stress (2008) Equine Exercise Physiology: The Science of Exercise in the Athletic Horse, pp. 382-396. , Hinchcliff, K.W. Geor, R.J. Kaneps, A.J. eds. Elsevier Health Sciences, Philadelphia, PA, USAMcKeever, K.H., Eaton, T.L., Geiser, S., Kearns, C.F., Lehnhard, R.A., Age related decreases I thermoregulation and cardiovascular function in horses (2010) Equine Veterinary Journal, 42, pp. 449-454Quinlan, J.R., (1993) C4.5: Programs for Machine Learning, , Morgan Kaufmann, San Francisco, CA, USASikora, M., Induction and pruning of classification rules for prediction of microseismic hazards in coal mines (2011) Expert Systems with Applications, 38, pp. 6748-6758Tattersall, G.J., Cadena, V., Insights into animal temperature adaptations revealed through thermal imaging (2010) The Imaging Science Journal, 58, pp. 261-268Tsang, S., Kao, B., Yip, K.Y., Ho, W., Lee, S.D., Decision tree for uncertain data (2011) IEEE Transactions on Knowledge and Data Engineering, 23, pp. 64-78Wang, T., Qin, Z., Jin, Z., Zhang, S., Handling over-fitting in test cost-sensitive decision tree learning by feature selection, smoothing and pruning (2010) The Journal of Systems and Software, 83, pp. 1137-114

  • Infrared Thermography To Evaluate The Training Horse Thermoregulation [uso Da Termografia Infravermelha Na Análise Da Termorregulação De Cavalo Em Treinamento]
    2015
    Co-Authors: De Moura D.j., Maia A.p.a., Medeiros B.b.l., Vercellino R.a., Sarubbi J., Griska P.r.
    Abstract:

    Heat-regulation mechanisms, such as changes in peripheral blood flow, are activated by thermal stress to maintain body homeostasis. The infrared thermography enables to identify changes in blood flow and it has been valuable for recognizing stress in animals. This research aimed to evaluate the use of infrared thermography in the training horse thermoregulation. An Anglo-Arab horse was studied and Exercised once a day. Infrared thermography images of horsés armpit, croup, breast and groin and physiological parameters were taken before and after Exercise and 0, 5 and 10 minutes after shower for eight days. The air temperature, relative humidity and air velocity were also registered. There were no differences between the surface temperature of croup and breast and the treatments, implying low participation in thermoregulation. However, the armpit and groin temperature increased after the Exercise and decreased after shower, suggesting that vasomotor mechanisms were activated to heat exchange. Similar results were found for physiological parameters which show organism thermal responses for heat loss. It was concluded that infrared thermography allowed accuracy in determining the horse body surface temperature and it was possible to infer on thermoregulation.3112332Autio, E., Neste, R., Airaksinen, S., Heiskanen, M., Measuring the heat loss in horses in different seasons by infrared thermography (2006) Journal of Applied Animal Welfare Science, 9 (3), pp. 211-221. , MahwahBouzida, N., Bendada, A., Maldague, X.P., Visualization of body thermoregulation by infrared imaging (2009) Journal of Thermal Biology, 34 (3), pp. 120-126. , OxfordBrandi, R.A., Furtado, C.E., Martins, E.N., Freitas, E.V.V., Lacerda Neto, J.C., Queiroz Neto, A., Ribeiro, L.B., Desempenho de equinos submetidos a enduro alimentados com níveis de óleo de soja na dieta (2009) Revista Brasileira de Saúde e Produção Animal, 10 (2), pp. 311-321. , SalvadorCarvalho, T., Mara, L.S., Hidratação e nutrição no esporte (2010) Revista Brasileira de Medicina do Esporte, 16 (2), pp. 33-40. , Rio de JaneiroCunningham, J.G., Termorregulação (2002) Tratado de fisiologia veterinária, pp. 550-561. , 3.ed. São Paulo: Guanabara KooganEtchichury, M., (2008) Termorregulação em cavalos submetidos a diferentes métodos de resfriamento pós-exercício. 2008, , 103 f. Tese (Doutorado em Zootecnia) - Universidade de São Paulo, Faculdade de Zootecnia e Engenharia de Alimentos, PirassunungaJones, S., Horsback riding in the dog days (2009) Animal Science e-News, 2 (3), pp. 3-4. , http://www.aragriculture.org/News/animal_science_enews/2009/pdf/july2009.pdf, Disponível em. Acesso em: 5 maio 2010Knížková, I., Kunc, P., Gürdíl, G.A.K., Pinar, Y., Selví, K.Ç., Applications of infrared thermography in animal production (2007) Journal of the Faculty of Agriculture, 22 (3), pp. 329-336. , KyushuKohn, C.W., Hinchcliff, K.W., Mckeever, K.H., Evaluation of washing with cold water to facilitate heat dissipation in horses Exercised in hot, humid conditions (1999) American Journal of Veterinary Research, 60 (3), pp. 299-305. , SchaumburgOliveira, L.A., Campel, J.E.G., Azevedo, D.M.M.R., Costa, A.P.R., Turco, S.H.N., Moura, J.W.S., Estudo de respostas fisiológicas de equinos sem raça definida e da raça quarto de milha às condições climáticas de Teresina, Piauí. (2008) Ciência Animal Brasileira, 9 (4), pp. 827-838. , GoiâniaMarlin, D.J., Scott, C.M., Roberts, C.A., Casas, I., Holah, G., Schroter, R., Post Exercise changes in compartmental body temperature accompanying intermittent cold water cooling in the hyperthermic horse (1998) Equine Veterinary Journal, 222 (30), pp. 28-34. , Borough GreenMcconaghy, F.F., Hodgson, D.R., Rose, R.J., Hales, J.R.S., Redistribution of cardiac output in response to heat exposure in the pony (1996) Equine Veterinary Journal Supplement, 22, pp. 42-46. , july,NewmarketMccutcheon, L.J., Geor, R.J., Thermoregulation and Exercise-associated heat stress (2008) Equine Exercise Physiology: the science of Exercise in the athletic horse, pp. 382-386. , HINCHCLIFF, K.W.GEOR, R.J.KANEPS, A.J. Philadelphia: ElsevierMorgan, K., Ehrlemark, A., Sällvik, K., Dissipation of heat from standing horses exposed to ambient temperatures between -3 °C and 37 °C (1997) Journal of Thermal Biology, 22 (3), pp. 177-186. , Great BritainPaludo, G.R., Mcmanus, C., Melo, R.Q., Cardoso, A.G., Mello, F.P.S., Moreira, M., Fuck, B.H., Efeito do estresse térmico e do exercício sobre os parâmetros fisiológicos de cavalos do exército brasileiro (2002) Revista Brasileira de Zootecnia, 31 (3), pp. 1.130-1.142. , Viçosa-MGPerissonoto, M., Moura, D.J., Matarazzo, S.V., Silva, I.J.O., Lima, K.A.O., Efeito da utilização de sistemas de climatização nos parâmetros fisiológicos do gado leiteiro (2006) Engenharia Agrícola, 26 (3), pp. 663-671. , JaboticabalPerrone, G.M., Caviglia, J.F., Pérez, A., Fidanza, M., Marquez, A., Catelli, J.L., González, G., Cambios em las variables fisiológicas en equinos compitiendo en una prueba combinada (2006) Anales de Veterinaria, 22, pp. 35-42. , MurciaPirrone, F., Albertini, M., Clement, M.G., Lafortuna, C.L., Respiratory mechanics in Standardbred horses with sub-clinical inflammatory airway disease and poor athletic performance (2007) The Veterinary Journal, 173, pp. 144-150. , LondonPuoli Filho, J.N.P., Barros Neto, T.L., Rodrigues, H.M., Garcia, H.P.L., Parâmetros fisiológicos do desempenho de cavalos de alta performance hidratados voluntariamente com água ou solução isotônica contendo carboidrato (2007) Brazilian Journal of Veterinary Research and Animal Science, 44 (2), pp. 122-131. , São PauloRibeiro, N.L., Furtado, D.A., Medeiros, A.N., Ribeiro, M.N., Silva, R.C.B., Souza, C.M.S., Avaliação dos índices de conforto térmico, parâmetros fisiológicos e gradiente térmico de ovinos nativos (2008) Revista de Engenharia Agrícola, 28 (4), pp. 614-623. , JaboticabalSilva, L.A.C., Santos, S.A., Silva, R.A.S., Mcmanus, C., Petzold, H., Adaptação do cavalo pantaneiro ao estresse da lida diária de gado no Pantanal, Brasil. (2005) Archivos de Zootecnia, 54, pp. 509-513. , CórdobaStewart, M., Webster, J.R., Schaefer, A.L., Cook, J., Scott, S.L., Infrared thermography as a non-invasive tool to study animal welfare (2005) Animal Welfare, 14, pp. 319-325. , South MimmsTitto, E.A.L., Pereira, A.M.F., Toledo, L.R.A., Passini, R., Nogueira Filho, J.C.M., Gobesso, A.A.O., Etchichury, M., Titto, C.G., Concentração de eletrólitos em equinos submetidos a diferentes temperaturas (2009) Revista Brasileira de Saúde e Produção Animal, 10 (1), pp. 236-244. , Salvador(2007) SAEG - Sistemas para análises estatísticas e genéticas, p. 150. , Universidade Federal De Viçosa. Versão 9.1. Viçosa-MG. (Manual do usuário

  • Data Mining Applied To Horse Thermal Comfort
    2015
    Co-Authors: Maia A.p.a., Medeiros B.b.l., Vercellino R.a., Sarubbi J., Oliveira S.r.m., Griska P.r., Moura D.j.
    Abstract:

    Thermal comfort plays a critical role in body temperature regulation. Heat-regulation mechanisms, such as changes in peripheral blood flow, are activated by thermal stress to maintain body homeostasis and it can results in a fluctuation of skin temperature. Although thermal comfort of horse has been studied, its relation with surface temperature is rarely seen in the literature. Therefore, the aim of this study was to verify the potential of data mining techniques in knowledge discovery by associating surface temperature with thermal comfort of horses. The decision tree model presented 74.0% of accuracy and all attributes of dataset were considered relevant for the classification problem. The results revealed the potential of data mining techniques to Equine thermal comfort classification problems.422428Autio, E., Neste, R., Airaksinen, S., Heiskanen, M.-L., Measuring the heat loss in horses in different seasons by infrared thermography (2006) Journal of Applied Animal Welfare Science, 9 (3), pp. 211-221. , DOI 10.1207/s15327604jaws0903-3Batista, G.E.A.P.A., Prati, R.C., Monard, M.C., A study of the behavior of several methods for balancing machine learning training set (2003) SIGKDD Exploration, 6 (1), pp. 20-29Chapman, P., Clinton, J., Kerber, R., Khabaz, T., Reinartz, T., Shearer, C., Wirth, R., (2000) CRISP-DM 1.0: Step-by-step Data Mining Guide, , http://www.spss.ch/upload/1107356429_CrispDM1.0.pdf, Available at: Accessed 22 November 2011Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P., SMOTE: Synthetic minority over-sampling technique (2002) Journal of Artificial Intelligence Research, 16, pp. 321-357. , http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume16/chawla02a.pdfCunningham, J.G., Termorregulação (2002) Tratado de Fisiologia Veterinária, , 3rd ed. São Paulo: Guanabara KooganFayyad, U., Stolorz, P., Data mining and KDD: Promise and challenges (1997) Future Generation Computer Systems, 13 (2-3), pp. 99-115. , PII S0167739X97000150Ferreira, V.M.O.S., Francisco, N.S., Belloni, M., Aguirre, G.M.Z., Caldara, F.R., Nääs, I.A., Garcia, R.G., Polycarpo, G.V., Infrared thermography applied to the evaluation of metabolic heat loss of chicks fed with different energy densities Brazilian J. of Poult. Sci., 13 (2), pp. 113-118Hodgson, D.R., Davies, R.E., McConaghy, F.F., Thermoregulation in the horse in response to Exercise (1994) British Veterinary Journal, 150 (3), pp. 219-234Huang, P., Lin, P., Shangwei, Y., Xiao, M., Data Mining for seasonal influences in broiler breeding based on observational study (2011) Information Computing and Applic., 7030, pp. 25-32Japkowicz, N., Class imbalances: Are we focusing on the right issue? (2003) 2nd Workshop on Learning from Imbalanced Data Sets, pp. 17-23Jones, S., Horsback Riding in the Dog Days (2009) (S.L.): Animal Science e-news University of Arkansas, 2 (3), pp. 3-4. , The Cooperative Extension Divison, 7pKnížková, I., Kinc, P., Gürdil, G.A.K., Pinar, Y., Selvi, K.Ç., Applications of infrared thermography in animal production (2007) J. of Fac. of Agric., 22 (3), pp. 329-336Laurikkala, J., (2001) Improving Identification of Difficult Small Classes by Balancing Class Distribution, , http://sci2s.ugr.es/keel/pdf/algorithm/congreso/2001-Laurikkala-LNCS.pdf, Available at: Accessed 01 November 2011Marlin, D.J., Scott, C.M., Roberts, C.A., Casas, I., Holah, G., Schroter, R., Post Exercise changes in compartmental body temperature accompanying intermittent cold water cooling in the hyperthermic horse (1998) Equine Vet. J., 30, pp. 28-34McCutcheon, L.J., Geor, R.J., Thermoregulation and Exercise-associated heat stress (2008) Equine Exercise Physiology: The Science of Exercise in the Athletic Horse, pp. 382-386. , Hinchcliff, K.W.R. J. Geor, A. J. Kaneps. Philadelphia: ElsevierMutaf, S., Şeber Kahraman, N., Frat, M.Z., Surface wetting and its effect on body and surface temperatures of domestic laying hens at different thermal conditions (2008) Poult. Sci., 87, pp. 2441-2450Paludo, G.R., McManus, C., De Melo, R.Q., Cardoso, A.G., Da, S.M.F.P., Moreira, M., Fuck, B.H., Effect of Heat Stress and Exercise on Physiological Parameters of Horses of the Brazilian Army (2002) Revista Brasileira de Zootecnia, 31 (3), pp. 1130-1142Oliveira, L.A., Campei, J.E.G., Azevedo, D.M.M.R., Costa, A.P.R., Turco, S.H.N., Moura, J.W.S., Estudo de respostas fisiológicas de equinos sem raça definida e da raça quarto de milha às condições climáticas de Teresina, Piauí (2008) Ciencia Animal Brasileira, 9 (4), pp. 827-838Vale, M.M., Moura, D.J., Nääs, I.A., Pereira, D.F., Characterization of heat waves affecting mortality of broilers between 29 days and market age (2010) Brazilian J.of Poult.Sci., 12 (4), pp. 279-28