EFEITO DA IDADE DA MATRIZ NO TEMPO DE ECLOSÃO, TEMPO DE PERMANÊNCIA DO NEONATO NO NASCEDOURO E O PESO DO PINTAINHO

Six hundred eggs from 32, 43 and 60 week-old Cobb-500®  broiler breeder were incubated at 37,8°C  and 60% of humidity. It was used a completely randomized design with three treatments (broiler breeder ages) and 200 repetitions (each embryo/chick was considered a repetition). Eggs were weighted at 1st and 19 th days, weight losses during the incubation were estimated, chicks were weighted at birth and when they were removed from hatchery and weight losses during this period were measured. Eggs and chicks from older broiler breeder were heavier. There were no differences in relation to egg weight losses, on chick weight percentages (chick weight/egg weight ratio), of incubation time (h) and on the weight losses during their hatchery remaining. Considering 32, 43 and 60 week-old broiler breeder, respectively, initial egg weight was highly and positively correlated with egg weight at 19 th day of incubation (0.75; 0.86 and 0.79), with birth chick weight (0.57, 0.72, 0.72) and with chick weight at hatchery removing (0.38, 0.41, 0.51); positive correlations (0.61,0.41 and 0.63) were observed between incubation time and chick weight. Negative correlations (-0.79, -0.96 and -0.76) were found between incubation time and chick weight losses during hatchery remaining. In conclusion, broiler breeder age affected egg and chick weight. Eggs from different broiler breeder ages might be incubated during the same period without affecting the quality of newborn in function of the time spends in hatchery.Utilizaram-se 600 ovos embrionados, provenientes de matrizes de 32, 43 e 60 semanas de idade, da linhagem Cobb – 500, incubados a 37,8°C e 60% de umidade. Foram analisados peso do ovo, peso dos ovos aos 19 dias de incubação, tempo de incubação, perda de peso do ovo durante a incubação, peso dos pintainhos no momento do nascimento e na retirada do nascedouro e perda de peso do pintainho no nascedouro. Foi utilizado um delineamento inteiramente ao acaso com 3 tratamentos (idade da matriz) e 200 repetições (cada ovo foi considerado uma repetição). Os resultados foram submetidos à análise de variância e Teste de Tukey (5%). Matrizes mais velhas produziram ovos mais pesados. Não houve diferença na perda de peso de ovos, no percentual de peso dos pintainhos, no tempo de incubação (h) e também na perda de peso do pintainho no nascedouro. Houve uma correlação positiva (0,75; 0,86; 0,79 respectivamente para matrizes de 32, 43 e 60 semanas) entre o peso inicial dos ovos e o peso dos ovos aos 19 dias de incubação, com o peso do pintainho, no momento do nascimento (0,57; 0,72; 0,72) e no momento da retirada do nascedouro (0,38; 0,41; 0,51). Também houve correlação (0,61; 0,41 e 0,63) entre o tempo de incubação e o peso do pintainho e com a perda de peso do pintainho no nascedouro (-0,79; -0,96; -0,76). Conclui-se que a idade da reprodutora afeta o peso do ovo e do pintainho. Ovos de matrizes de diferentes idades necessitam o mesmo tempo para incubação

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system