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The ability to detect moisture in broiler feathers for five moisture-sensing devices using varying techniques, an infrared (IR) camera, and one type of moisture-sensitive paper was evaluated in two experiments; using artificial feather beds in laboratory settings and in field conditions using live birds. In the first experiment (lab testing-phase I), seven levels of moisture were applied once per day to the swatches with four different feather densities to account for moisture variation and feather density present in commercial barn conditions. True moisture of the feathers was determined gravimetrically on a daily basis. Using the five devices, 20 readings each were acquired from each of the swatches. The average temperatures of a selected area from images captured using an IR camera along with average device readings were compared with the true moisture content. Moisture-sensitive paper images were analyzed in Photoshop and Matlab prior to statistical analysis. Data from all devices, the IR camera, and moisture-sensitive paper were analyzed using SAS Procedure GLM to define relationships between the true moisture content and the readings. The devices were analyzed based on their accuracy, consistency and sensitivity using adjusted-R2, standard error, and regression slope, respectively. The data from all devices and techniques were significantly correlated with feather swatch moisture content (P<0.05). Results from the first experiment suggested potential to measure feather moisture by several of the tested devices. While feather density presented as a challenge during this experiment, it was not considered as a significant issue when evaluating the devices. The “Hay” and “Construction 1” sensors showed the most promise in detecting feather moisture and iv were selected for further testing using live birds. The two devices had relatively higher accuracy, consistency, and sensitivity compared to other devices and techniques. The second experiment (field testing – phase II) evaluated the two selected devices (Hay and Construction 1 sensors) in various commercial broiler settings. Device readings were acquired from the back, wing, and breast feathers. A sample of back feathers from each bird was collected to determine the true moisture. Statistical analyses of data were the same as in experiment 1. Although the initial study, conducted within a lab setting, denoted a significant relationship between true moisture content and device readings, testing within the field environments showed the devices to perform poorly. Readings from both devices and for all the locations tested demonstrated a lack of sensitivity, accuracy, and consistency for measuring moisture in feathers of live birds.

Made available in DSpace on 2014-06-11T19:31:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2006-12-11Bitstream added on 2014-06-13T20:42:01Z : No. of bitstreams: 1 mathias_im_dr_botfca.pdf: 1186171 bytes, checksum: a99a3192900af068caf82ad18c373cfa (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Universidade Estadual Paulista (UNESP) / O trabalho descrito nesta tese apresenta o desenvolvimento de um sistema computacional denominado PMNeural, baseado em Redes Neurais Artificiais (RNAs). A finalidade do sistema é o tratamento de dados climáticos e de molhamento foliar por orvalho, visando reconhecer padrões de comportamento de variáveis meteorológicas em relação ao molhamento foliar por orvalho. Para determinar as melhores arquiteturas e algoritmos de treinamento de RNAs, bem como, definir quais as variáveis climáticas que influenciam significativamente na ocorrência do molhamento foliar, foram utilizados dois simuladores: o simulador SNNS (Stuttgart Neural Network Simulator) versão 4.2, que utiliza plataforma operacional Linux e o simulador JavaNNS - Java Neural Network Simulator 1.1, com ambiente de execução Windows, o qual é baseado no SNNS. Foram utilizados dados climáticos de três estudos de caso, dois destes referentes à cultura do trigo, oriundos de locais e datas diferentes. Base de Dados 1 - Fazenda Capão do Cipó, em Castro - PR, safra de inverno de 2003. Base de Dados 2 - Campo Demonstrativo e Experimental da Fundação ABC - Fazenda Palmeirinha, em Piraí do Sul - PR., safra de inverno de 2005. Base de Dados 3 - Posto Agrometeorológico ESALQ/USP em Piracicaba - SP, período entre julho e setembro de 2005. Um quarto estudo de caso foi elaborado a partir dos arquivos dos estudos de casos 1, 2 e 3, utilizando-se as variáveis climáticas comuns, juntamente com seus respectivos índices de molhamento. Dentre os algoritmos de treinamento testados nos simuladores, o Resilient 2 Propagation (Rprop) foi o que apresentou as menores taxas de erro em relação aos outros... / The work described in this thesis presents the development of a computational system named PMNeural based on Artificial Neural Networks (ANNs). The system has for purpose the handle of climatic and leaf wetness data, aiming to recognize patterns of behavior of meteorological variables in relation to the wetness from dew. Two simulators were used in order to determine the best architecture and ANNs training algorithms, as well as, to define which the climatic variables that influence significantly in the leaf wetness occurrence: the SNNS (Stuttgart Neural Network Simulator) version 4.2 for Linux platform, and the JavaNNS - Java Neural Network Simulator 1.1, for Windows platform, which is based on the SNNS. Climatic data of three case studies were used, two related to wheat culture, obtained from different places and dates. Dataset 1 - Capão do Cipó Farm, in Castro - PR, 2003. Dataset 2 - Palmeirinha Farm in Piraí do Sul - PR, 2005 winter crop. Dataset 3 - Meteorological Station of ESALQ/USP in Piracicaba - SP, from July to September, 2005. A fourth case study was elaborated from datasets of the case studies 1, 2 and 3, using the common climatic variables together with their respective wetness indexes. After testing the training algorithms in the simulators, the Resilient Propagation (Rprop) presented lower training errors than the others evaluated methods: Backpropagation Standard, Backpropagation for batch training, Backpropagation with momentum term, Backpropagation with chunkwise update, Backpropagation with Weight Decay and Quickprop. It was verified 4 also that, among the climatic variables used for classification of leaf wetness from dew, the inclusion of the schedule had influenced in the obtaining better ANNs results... (Complete abstract, click electronic access below)

Resumo: O trabalho descrito nesta tese apresenta o desenvolvimento de um sistema computacional denominado PMNeural, baseado em Redes Neurais Artificiais (RNAs). A finalidade do sistema é o tratamento de dados climáticos e de molhamento foliar por orvalho, visando reconhecer padrões de comportamento de variáveis meteorológicas em relação ao molhamento foliar por orvalho. Para determinar as melhores arquiteturas e algoritmos de treinamento de RNAs, bem como, definir quais as variáveis climáticas que influenciam significativamente na ocorrência do molhamento foliar, foram utilizados dois simuladores: o simulador SNNS (Stuttgart Neural Network Simulator) versão 4.2, que utiliza plataforma operacional Linux e o simulador JavaNNS - Java Neural Network Simulator 1.1, com ambiente de execução Windows, o qual é baseado no SNNS. Foram utilizados dados climáticos de três estudos de caso, dois destes referentes à cultura do trigo, oriundos de locais e datas diferentes. Base de Dados 1 - Fazenda Capão do Cipó, em Castro - PR, safra de inverno de 2003. Base de Dados 2 - Campo Demonstrativo e Experimental da Fundação ABC - Fazenda Palmeirinha, em Piraí do Sul - PR., safra de inverno de 2005. Base de Dados 3 - Posto Agrometeorológico ESALQ/USP em Piracicaba - SP, período entre julho e setembro de 2005. Um quarto estudo de caso foi elaborado a partir dos arquivos dos estudos de casos 1, 2 e 3, utilizando-se as variáveis climáticas comuns, juntamente com seus respectivos índices de molhamento. Dentre os algoritmos de treinamento testados nos simuladores, o Resilient 2 Propagation (Rprop) foi o que apresentou as menores taxas de erro em relação aos outros... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The work described in this thesis presents the development of a computational system named PMNeural based on Artificial Neural Networks (ANNs). The system has for purpose the handle of climatic and leaf wetness data, aiming to recognize patterns of behavior of meteorological variables in relation to the wetness from dew. Two simulators were used in order to determine the best architecture and ANNs training algorithms, as well as, to define which the climatic variables that influence significantly in the leaf wetness occurrence: the SNNS (Stuttgart Neural Network Simulator) version 4.2 for Linux platform, and the JavaNNS - Java Neural Network Simulator 1.1, for Windows platform, which is based on the SNNS. Climatic data of three case studies were used, two related to wheat culture, obtained from different places and dates. Dataset 1 - Capão do Cipó Farm, in Castro - PR, 2003. Dataset 2 - Palmeirinha Farm in Piraí do Sul - PR, 2005 winter crop. Dataset 3 - Meteorological Station of ESALQ/USP in Piracicaba - SP, from July to September, 2005. A fourth case study was elaborated from datasets of the case studies 1, 2 and 3, using the common climatic variables together with their respective wetness indexes. After testing the training algorithms in the simulators, the Resilient Propagation (Rprop) presented lower training errors than the others evaluated methods: Backpropagation Standard, Backpropagation for batch training, Backpropagation with momentum term, Backpropagation with chunkwise update, Backpropagation with Weight Decay and Quickprop. It was verified 4 also that, among the climatic variables used for classification of leaf wetness from dew, the inclusion of the schedule had influenced in the obtaining better ANNs results... (Complete abstract, click electronic access below) / Orientador: Angelo Cataneo / Coorientador: Alaine Margarete Guimarães / Banca: Célia Regina Lopes Zimback / Banca: Marco Antonio Martim Biaggioni / Banca: Manoel Henrique Salgado / Banca: Marcelo Giovanetti Canteri / Doutor

Hydrological modeling, like runoff modelling for flood prevention, is based on digital elevation models (DEMs). The fact that the DEMs do not represent existing road culverts can lead to considerable hydrological misinterpretations. In order to overcome this limitation, a GIS method was developed to automatically adjust the elevation model, hydrologically enforcing the DEM, so that the results of hydrological modeling accounts for flow through culverts. The hydro-enforced DEM showed to better represent the drainage network than the former DEM when compared with the river map. The topographic wetness index is the most commonly applied topographic index and a good indicator of soil moisture distribution. It has been integrated into many hydrological models and pollution risk indices as well as into the prediction of wetland distribution. Using the hydro-DEM from the previous step and the soil map in conjunction with the TWI, an improved TWI was achieved, namely a soil-topographic wetness index (STI). The linkages between specific soil types and TWI or STI values were analyzed. They revealed a clear linkage between STI values and soil type based on the soil transmissivity (R2=0.77). However, the TWI values showed low correlations to the soil types (R2=0.02). As a specific application, both TWI and STI were tested for the detection of wetlands. Wetlands are important ecosystems which act as buffer zones by filtering pollutants and slowing floodwater. Being able to identify their distribution is important in landscape planning and ecology. A wetland threshold value was determined for each index and their results where compared with the wetland map from the property map (assumed as ground truth) and with the potential wetland area. Finally, a visual validation was performed with the use of an aerial photography. The results showed that the STI performed slightly better than the TWI for the detection of wetlands, detecting 3% more wetlands. The impact of the soil map on the topographic wetness index was therefore determined as positive.

The ability to sense humidity and wetness is an important sensory attribute for many species across the animal kingdom, including humans. Although this sensory ability plays an important role in many human physiological and behavioural functions, as humans largest sensory organ i.e. the skin seems not to be provided with specific receptors for the sensation of wetness (i.e. hygroreceptors), the neurophysiological mechanisms underlying this complex sensory experience are still poorly understood. The aim of this Thesis was to investigate the neurophysiological mechanisms underpinning humans remarkable ability to sense skin wetness despite the lack of specific skin hygroreceptors. It was hypothesised that humans could learn to perceive the wetness experienced when the skin is in contact with a wet surface or when sweat is produced through a complex multisensory integration of thermal (i.e. heat transfer) and tactile (i.e. mechanical pressure and friction) inputs generated by the interaction between skin, moisture and (if donned) clothing. Hence, as both thermal and tactile skin afferents could contribute significantly to drive the perception of skin wetness, their role in the peripheral and central sensory integration of skin wetness perception was investigated, both under conditions of skin s contact with an external (dry or wet) stimulus as well as during the active production of sweat. A series of experimental studies were performed, aiming to isolate the contribution of each sensory cue (i.e. thermal and tactile) to the perception of skin wetness during rest and exercise, as well as under different environmental conditions. It was found that it is not the contact of the skin with moisture per se, but rather the integration of particular sensory inputs which drives the perception of skin wetness during both the contact with an external (dry or wet) surface, as well as during the active production of sweat. The role of thermal (cold) afferents appears to be of a primary importance in driving the perception of skin wetness during the contact with an external stimulus. However, when thermal cues (e.g. evaporative cooling) are limited, individuals seem to rely more on tactile cues (i.e. stickiness and skin friction) to characterise their perception of skin wetness. The central integration of conscious coldness and mechanosensation, as sub-served by peripheral cutaneous A-nerve fibers, seems therefore the primary neural process underpinning humans ability to sense wetness. Interestingly, these mechanisms (i.e. integration of thermal and tactile sensory cues) appear to be remarkably consistent regardless of the modality for which skin wetness is experienced, i.e. whether due to passive contact with a wet stimulus or due to active production of sweat. The novelty of the findings included in this Thesis is that, for the first time, mechanistic evidence has been provided for the neurophysiological processes which underpin humans ability to sense wetness on their skin. Based on these findings, the first neurophysiological sensory model for human skin wetness perception has been developed. This model helps explain humans remarkable ability to sense warm, neutral and cold skin wetness.

Regional differences in sweat gland output, skin temperature and thermoreceptor distribution can account for variations in regional perceptions of temperature, thermal comfort and wetness sensation. Large cohorts of studies have assessed these perceptual responses during sedentary activity but the findings are typically applied to a multitude of conditions, including exercise. Increases in sweat gland output, redistribution of blood flow and changes in skin and core temperature are basic responses to exercise in most conditions and these ultimately influence our perceptual responses. The primary aim of this thesis is to determine factors that influence regional differences in thermal sensation, thermal comfort and wetness sensation during exercise in moderate to hot conditions. The secondary aim is to develop and understand an additional variable, galvanic skin conductance (GSC) that can be used to predict thermal comfort and wetness sensation. The aim of the first study (Chapter 4) was to determine the influence of exercise on thermal sensitivity and magnitude sensation of warmth to a hot-dry stimulus (thermal probe at 40°C) and assess if any gender-linked differences and/or regional differences exist. From the data, body maps indicating sensitivity were produced for both genders during rest and exercise. Females had more regional differences than males. Overall sensitivity was greatest at the head, then the torso and declined towards the extremities. The data showed that exercise did not cause a significant reduction in thermal sensitivity but magnitude estimation was significantly lower after exercise for males and selected locations in females. The cause of a reduced magnitude sensation is thought to be associated with exercise induced analgesia; a reduction in sensitivity due to exercise related increases in circulating hormones. As the literature suggests that thermal comfort in the heat is influenced by the presence of sweat, the next study and all proceeding studies were concerned with this concept. In Chapter 5, building on earlier studies performed in our laboratories, the influence of local skin wettedness (wlocal) on local thermal comfort and wetness sensation was investigated in a neutral dry condition (20.2 ± 0.5°C and 43.5 ± 4.5% RH) whilst walking (4.5 km∙hr-1). Regional differences in wlocal were manipulated using specialised clothing comprising permeable and impermeable material areas. Strong correlations existed between local thermal comfort and local wetness sensation with the various measured wlocal (r2>0.88, p<0.05 and r2>0.83, p<0.05, respectively). The thermal comfort limit was defined as the wlocal value at which the participants no longer felt comfortable. Regional comfort limits for wlocal were identified (in order of high-low sensitivity); lower back (0.40), upper legs (0.44), lower legs (0.45), abdomen (0.45), chest (0.55), upper back (0.56), upper arms (0.57) and lower arms (0.65). The maximum degree of discomfort and wetness sensation experienced during the investigation was kept deliberately low in an attempt to determine the threshold values. Therefore comfort scores and wetness scores rarely reached a state of uncomfortable or wet so the next step was to assess these relationships when sweat production is high and the sensations worsened. However, pilot testing indicated that a ceiling effect would occur for wlocal at high levels of sweat production whilst thermal discomfort increased indicating wlocal was not the determining parameter in that case. Thus an additional parameter was required. The chosen parameter was galvanic skin conductance (GSC) due to its alleged ability to monitor pre-secretory sweat gland activity, skin hydration and surface sweat. In Chapter 6, the reliability, reproducibility and validity of GSC were confirmed in a series of pilot tests. Moderate to strong correlations were found between GSC and regional sweat rate (RSR) (r2>0.60, p<0.05) and wlocal (r2>0.55, p<0.05). The literature suggests standardising GSC relative to a minimum and maximum GSC value; however uncertainties arise when attempting to achieve maximum GSC. Therefore a change from baseline (∆GSC) was chosen as the proposed method of standardisation for further use. Additional results (from Chapter 9) revealed that ∆GSC also reflects pre-secretory sweat gland activity as it increased prior to sweat being present on the skin surface and prior to an increase in RSR. In Chapter 9, also hydration of the stratum corneum was measured using a moisture meter and the results revealed that it has an upper limit; indicating maximal hydration. From this point of full skin saturation ∆GSC and RSR markedly increase though sensations did not. It was also found that ∆GSC is only influenced by surface sweat that is in direct contact with the electrode and is not influenced by sweat elsewhere on the skin surface between electrodes. Higher levels of thermal discomfort have rarely been explored and neither has its relationship with wlocal. The ability of ∆GSC and wlocal to predict local thermal comfort and wetness sensation were compared in two different conditions to elicit low and high sweat production. Unlike Chapter 5, the body sites were not manipulated to control wlocal but allowed to vary naturally over time. The test was carried out on males (Chapter 7) and females (Chapter 8) to compare any gender linked differences and the results suggest that females are more sensitive than males to the initial presence of sweat. For both genders, wlocal and ∆GSC are strong predictors of thermal comfort and wetness sensation. More importantly, wlocal can only be used to predict local thermal comfort in conditions of low sweat production or low levels of thermal discomfort. However, once sweat production increases and thermal discomfort worsens ΔGSC (and not wlocal) can predict thermal comfort. Due to low sweat production observed in females indicates that this is only relevant for females. It appears that epidermal hydration has an important role on influencing thermal comfort. Receptors influencing our perceptual responses are located in the epidermis and when sweat is produced and released onto the skin surface, this epidermis swells and the sensitivity of receptors are said to increase. wlocal indicates the amount of moisture present on the skin surface, yet ∆GSC indicates presecretory sweat gland activity and epidermal hydration where the receptors are located. This may explain why on numerous occasions thermal comfort had a stronger relationship with ∆GSC than wlocal. Where Chapter 5 indicated the true local comfort limits for each respective zone, Chapter 7 and 8 provided a global picture of how local regions interact and influence local thermal comfort across the body. When wlocal varies naturally, the torso areas naturally produce more sweat than the extremities and it seemed that these areas produce so much more sweat than the extremities that they dominate local thermal comfort across the whole body. This is referred to in this thesis as a model of segmental interaction. As with thermal comfort, wetness sensation had strong relationships with wlocal and ∆GSC. The results also revealed a strong relationship between wetness sensation and thermal comfort. In contrast to the widely supported claim, a drop in skin temperature is not required to stimulate a wetness sensation. The point at which we detect sweat and when it becomes uncomfortable occurs at different wlocal values across the body. Thermal comfort is shown to be influenced by sweat during exercise in moderate-to-hot conditions. As w has an upper limit the findings suggest that it cannot predict thermal comfort during high sweat rates. Galvanic skin conductance monitors the process of sweat production more closely and thus is a better predictor of thermal comfort during all conditions and particularly during high sweat production. The strong relationship between thermal comfort and wetness sensation confirm the role of sweat production on thermal comfort. Gender differences to perceptual responses were observed, with females generally being more sensitive to sweat and a warm thermal stimulus than males. Regional differences to sweat and a warm stimulus generally suggest that the torso area is more sensitive than the extremities. This is important not only for sports clothing design but also protective clothing at the work place.

Title: Parameterization of body discomfort of driver and front passanger in a monotone load during driving by car Objectives: The aim of this work based on the implemented case study is determination utilization of selected subjective and objective methods to assess discomfort sitting position of driver and front passanger in the monotone load during driving by car. Methods: This thesis is type of descriptive - association qualitative research. In practical part the objective discomfort parameters were monitored using Mobile system for scanning and evaluation of occupational safety and hygiene and the subjective parameters using Questionnaire physical map in combination with modified Borg scale, the mental state was monitored using modified questionnaire POMS. Results: Detailed link was not proved in context of subjective and objective methods or roles, the measurements were too influenced by entering factors and variability of observed objective parameters. The skin temperature, wetness and heart rate appear to be unsuitable for monitoring the sitting discomfort in realistic conditions, subjective methods are usable in research. Their results showed that the subjective discomfort and fatigue grew more during ride back. Pause resulted in reduced subjective discomfort. Keywords: skin temperature,...

A umidade é um dos principais agentes causadores de manifestações patológicas no ambiente construído, e, a chuva dirigida, é uma das principais fontes de umidade que afetam a durabilidade das fachadas das edificações. Desta forma, métodos vêm sendo desenvolvidos como forma de avaliação, entre eles se encontram os experimentais que buscam avaliar este fenômeno a partir da realização de ensaios. A pesquisa é motivada pela constatação da quase inexistência de estudos experimentais de quantificação de chuva dirigida, bem como pela identificação da problemática relacionada ao manchamento e infiltração de água na área próxima às janelas. Sendo assim, o objetivo principal desta pesquisa é identificar, com base em testes de chuva dirigida, a influência das características de projeção, com variações de 50 mm e 120 mm, de inclinação, com valores de 6% e 20%, e engaste lateral do peitoril, sem engaste e com engates de 100 mm, no molhamento da área de fachada localizada próxima às janelas. Este trabalho foi desenvolvido a partir da avaliação de nove modelos com dimensões 1,20m x 2,40m, sendo um modelo de referência sem peitoril, e outros oito englobando as diferentes configurações de projeção, inclinação e engastes laterais dos peitoris, em granito. As técnicas empregadas nas avaliações dos modelos foram a coleta de água da chuva nos paramentos dos modelos, registros de imagens termográficas por infravermelho, chuva colorida para identificação dos fluxos e registros fotográficos digitais A chuva simulada apresentava vazão total de 6 l/m, com diâmetros de gota que variavam de 0,86 mm – 1,45 mm com interceptação de velocidade de vento de 3,2 m/s, e, os testes foram desenvolvidos em quatro ciclos de 15 minutos de duração cada. Os resultados demonstraram que a utilização de prolongamentos laterais nos peitoris promoveram melhor desempenho dos modelos com relação ao descolamento da água da chuva das paredes, quando em comparação àqueles que não possuem esta configuração. Considerando a inclinação dos peitoris identificou-se que o valor de 6% permite, mesmo com a existência de um lacrimal na face inferior do peitoril, a percolação da água da chuva pela porção inferior deste elemento, com um gotejamento vertical. Nas configurações com 20% de inclinação do peitoril não se verifica este comportamento, contudo, o gotejamento ocorre no sentido da parede do modelo, direcionando parte do fluxo da chuva para a área localizada abaixo do peitoril, condicionando valores mais elevados de coleta de chuva. A projeção de 50 mm protege de forma menos eficiente as paredes dos modelos do molhamento pela chuva dirigida, gerando áreas protegidas menores e maiores valores de água coletada quando comparadas à projeção de 120 mm. / Moisture is one of the leading causes of pathological manifestations in buildings. Wind driven rain, is one of the main sources that affect the buildings facades durability. Thus, with the mean to evaluate this phenomenon, some experimental methods has been evaluated. The inexistence of experimental studies for wind driven rain quantification, motivated this research. Besides, this research aims to identify the staining and water seepage in the windows area problems. Thus, the main objective of this research is to identify, based on wind driven rain tests, the influence of geometrical characteristics of sills, in the wetness area located near windows. For this, there were developed sills with projection variations of 50 mm and 120 mm, inclinations of 6 % and 20 %, and sill without side extensions of window and 100 mm extensions. The experimental program contemplate the evaluation of nine wall models, with dimensions 1.20 m x 2.40 m, where a window were fixed and granite sills were installed, with the geometrical variations proposed. Simulated driving rain had total flow 6 l/m, with drop diameters ranging from 0.86 mm - 1.45 mm, with wind speed intercept of 3.2 m /s, and the tests were carried out in four cycles of 15 minutes each. There were collected rainwater on some controlled points of the walls models, besides infrared thermography images, colorful rain for identification of flows and digital photography. With the final results it was possible to conclude that the use of lateral extensions in windows sills promote better performance in the models, in relation to detachment of rainwater to the walls, when compared to sills without lateral extension. About sills inclination, it was found that the 6 % value results in a better behavior compared with 20% inclination. Finally, the windows sills with 120 mm protects more efficiently the models walls.