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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Desenvolvimento e qualidade de frutos de banana em função da proteção física dos cachos / Banana development and quality according bunches physical protection

Sakai, Ronaldo Kazuo 17 April 2015 (has links)
No cultivo da bananeira, a proteção física dos cachos é uma das principais técnicas culturais utilizada com a finalidade de melhorar a qualidade dos frutos. O objetivo desse trabalho foi estudar a influência do uso de diferentes tipos de embalagens para proteção do cacho de banana, cultivar Nanicão, durante o seu desenvolvimento e na pós-colheita dos frutos. Foram realizados dois experimentos em um bananal irrigado, com 8 anos de idade, em clima Cwa. O primeiro experimento foi realizado em duas épocas do ano para verificar a influência dos tipos de embalagens no desenvolvimento dos frutos e na sua qualidade. Os tratamentos foram: 1) testemunha (sem uso de proteção do cacho); 2) saco de polipropileno - TNT; 3) saco de polietileno azul; 4) saco de polietileno transparente), 5) saco de polietileno tratado com inseticida); e 6) saco de polietileno branco. Avaliou-se o período de frutificação (intervalo entre a emissão da inflorescência até a colheita dos frutos), massa do cacho, massa do engaço+ráquis, número de pencas por cacho, massa da 2ª penca, número de frutos da 2ª penca, massa da casca e polpa, relação polpa/casca, densidade dos frutos, lesões causadas por tripes, defeitos ou injúrias nos frutos, coloração da casca, sólidos solúveis, firmeza da polpa, acidez titulável e pH da polpa. No segundo experimento verificou-se a conservação desses frutos após a colheita e amadurecimento em ambiente controlado dos frutos. Avaliou-se a coloração da casca, sólidos solúveis da polpa, acidez titulável da polpa, pH da polpa, firmeza da polpa, perda de massa e relação polpa/casca. O delineamento utilizado em ambos os experimentos foram o inteiramente causalizado. A análise de variância dos dados obtidos foi realizada e no caso de significâncias as médias foram comparadas pelo teste Tukey (5%). Conclui-se que o uso das embalagens para proteção do cacho reduz o período de frutificação, independentemente da época de desenvolvimento do fruto. A massa do cacho, a massa do engaço+ráquis, número de pencas, massa da 2ª penca, número de frutos da 2ª penca, densidade dos frutos e pH da polpa não são influenciados pelo uso de embalagens para proteção do cacho. O uso de embalagens no cacho protege contra o ataque de tripes da erupção. No inverno, todos os tipos de proteção física do cacho de banana tiveram desempenho semelhantes no controle dessa praga. No verão, o melhor controle foi obtido pela embalagem impregnada com inseticida. O uso de embalagens para proteção do cacho interfere nos atributos físico-químicos considerados importantes na maturação dos frutos, tais como coloração da casca, sólidos solúveis, firmeza e acidez titulável. As embalagens confeccionadas de material translúcido propiciam a produção de frutos com menor quantidade de injúrias e maior período de conservação, após o amadurecimento em ambiente controlado dos frutos. Cachos de banana que se desenvolveram no verão apresentaram maior massa e período de frutificação inferior aos frutos desenvolvidos no inverno. / In banana crop, the fruit physical protection is an important cultural technique performed in order to improve fruit quality. The aim of this work was to study the different types of bag influence for banana bunch protection, cv. Nanicão, during fruit development and post-harvest. Two experiments were developed under irrigated conditions in a banana filed with 8 years of cultive, in climate Cwa. The first experiment was conducted in two seasons aiming to verify the influence of different bags types in the fruits development and quality. The treatments were: 1) control (without bunch protection); 2) polypropylene bag - TNT; 3) Blue polythene bag; 4) Transparent polyethylene bag), 5) polyethylene bag Treated with insecticide); and 6) White polyethylene bag. Evaluated variables were: fruiting period (interval between the inflorescence emission until fruit harvest), bunch weight, mass of stems + rachis, number of hands per bunch, mass of the 2nd bunch, number of fruits of the 2nd bunch, mass of peel and pulp, pulp / peel ratio, fruit density, injuries caused by thrips, defects or injuries in fruits, peel color, soluble solids, firmness, titratable acidity and pH of the pulp. In the second experiment was evaluated the conservation of these fruits after harvest and acclimatization. Evaluated variables were: skin color, soluble solids of the pulp, titratable acidity of the pulp, pulp pH, firmness, weight loss and pulp / peel ratio. The experimental design, in both experiments, was completely randomized design. Data variance analyses were performed and in the case of significance means were compared by Tukey test (5%). The use of packaging bunch protection reduces the fruiting period, regardless of the fruit development time. The bunch weight, the mass of stems + rachis, number of hands, mass of the 2nd bunch, number of fruits of the 2nd bunch, fruit density and pH of the pulp are not influenced by the use of packaging bunch protection. The use of packaging in the bunch protects against attack by thrips eruption. During the winter conditions, all kinds of physical protection of the banana bunch had similar performance against this bug. Under summer conditions, the best control was through the use of impregnated with insecticide packaging. The use of packaging bunch protection interferes in physicalchemical attributes considered important in the maturation of the fruit, such as coloring hunting, soluble solids, firmness and titratable acidity. The packaging made by translucent material provides fruit production with less injuries and greater conservation period, after fruit acclimatization. Banana bunches developed in the summer were heavier and fruiting period was shorter than the fruit developed during the winter.
2

Desenvolvimento e qualidade de frutos de banana em função da proteção física dos cachos / Banana development and quality according bunches physical protection

Ronaldo Kazuo Sakai 17 April 2015 (has links)
No cultivo da bananeira, a proteção física dos cachos é uma das principais técnicas culturais utilizada com a finalidade de melhorar a qualidade dos frutos. O objetivo desse trabalho foi estudar a influência do uso de diferentes tipos de embalagens para proteção do cacho de banana, cultivar Nanicão, durante o seu desenvolvimento e na pós-colheita dos frutos. Foram realizados dois experimentos em um bananal irrigado, com 8 anos de idade, em clima Cwa. O primeiro experimento foi realizado em duas épocas do ano para verificar a influência dos tipos de embalagens no desenvolvimento dos frutos e na sua qualidade. Os tratamentos foram: 1) testemunha (sem uso de proteção do cacho); 2) saco de polipropileno - TNT; 3) saco de polietileno azul; 4) saco de polietileno transparente), 5) saco de polietileno tratado com inseticida); e 6) saco de polietileno branco. Avaliou-se o período de frutificação (intervalo entre a emissão da inflorescência até a colheita dos frutos), massa do cacho, massa do engaço+ráquis, número de pencas por cacho, massa da 2ª penca, número de frutos da 2ª penca, massa da casca e polpa, relação polpa/casca, densidade dos frutos, lesões causadas por tripes, defeitos ou injúrias nos frutos, coloração da casca, sólidos solúveis, firmeza da polpa, acidez titulável e pH da polpa. No segundo experimento verificou-se a conservação desses frutos após a colheita e amadurecimento em ambiente controlado dos frutos. Avaliou-se a coloração da casca, sólidos solúveis da polpa, acidez titulável da polpa, pH da polpa, firmeza da polpa, perda de massa e relação polpa/casca. O delineamento utilizado em ambos os experimentos foram o inteiramente causalizado. A análise de variância dos dados obtidos foi realizada e no caso de significâncias as médias foram comparadas pelo teste Tukey (5%). Conclui-se que o uso das embalagens para proteção do cacho reduz o período de frutificação, independentemente da época de desenvolvimento do fruto. A massa do cacho, a massa do engaço+ráquis, número de pencas, massa da 2ª penca, número de frutos da 2ª penca, densidade dos frutos e pH da polpa não são influenciados pelo uso de embalagens para proteção do cacho. O uso de embalagens no cacho protege contra o ataque de tripes da erupção. No inverno, todos os tipos de proteção física do cacho de banana tiveram desempenho semelhantes no controle dessa praga. No verão, o melhor controle foi obtido pela embalagem impregnada com inseticida. O uso de embalagens para proteção do cacho interfere nos atributos físico-químicos considerados importantes na maturação dos frutos, tais como coloração da casca, sólidos solúveis, firmeza e acidez titulável. As embalagens confeccionadas de material translúcido propiciam a produção de frutos com menor quantidade de injúrias e maior período de conservação, após o amadurecimento em ambiente controlado dos frutos. Cachos de banana que se desenvolveram no verão apresentaram maior massa e período de frutificação inferior aos frutos desenvolvidos no inverno. / In banana crop, the fruit physical protection is an important cultural technique performed in order to improve fruit quality. The aim of this work was to study the different types of bag influence for banana bunch protection, cv. Nanicão, during fruit development and post-harvest. Two experiments were developed under irrigated conditions in a banana filed with 8 years of cultive, in climate Cwa. The first experiment was conducted in two seasons aiming to verify the influence of different bags types in the fruits development and quality. The treatments were: 1) control (without bunch protection); 2) polypropylene bag - TNT; 3) Blue polythene bag; 4) Transparent polyethylene bag), 5) polyethylene bag Treated with insecticide); and 6) White polyethylene bag. Evaluated variables were: fruiting period (interval between the inflorescence emission until fruit harvest), bunch weight, mass of stems + rachis, number of hands per bunch, mass of the 2nd bunch, number of fruits of the 2nd bunch, mass of peel and pulp, pulp / peel ratio, fruit density, injuries caused by thrips, defects or injuries in fruits, peel color, soluble solids, firmness, titratable acidity and pH of the pulp. In the second experiment was evaluated the conservation of these fruits after harvest and acclimatization. Evaluated variables were: skin color, soluble solids of the pulp, titratable acidity of the pulp, pulp pH, firmness, weight loss and pulp / peel ratio. The experimental design, in both experiments, was completely randomized design. Data variance analyses were performed and in the case of significance means were compared by Tukey test (5%). The use of packaging bunch protection reduces the fruiting period, regardless of the fruit development time. The bunch weight, the mass of stems + rachis, number of hands, mass of the 2nd bunch, number of fruits of the 2nd bunch, fruit density and pH of the pulp are not influenced by the use of packaging bunch protection. The use of packaging in the bunch protects against attack by thrips eruption. During the winter conditions, all kinds of physical protection of the banana bunch had similar performance against this bug. Under summer conditions, the best control was through the use of impregnated with insecticide packaging. The use of packaging bunch protection interferes in physicalchemical attributes considered important in the maturation of the fruit, such as coloring hunting, soluble solids, firmness and titratable acidity. The packaging made by translucent material provides fruit production with less injuries and greater conservation period, after fruit acclimatization. Banana bunches developed in the summer were heavier and fruiting period was shorter than the fruit developed during the winter.
3

Efficacy of advanced oxidation technology and lactic acid wash for controlling Escherichia coli O157:H7 in bagged baby spinach

McKay, Krista Marie January 1900 (has links)
Master of Science / Food Science / Kelly J.K. Getty / James L. Marsden / Escherichia coli O157:H7 outbreaks have been linked to leafy green produce and bagged spinach. The objective of this study was to evaluate a Photohydroionization (PHI) panel (novel advanced oxidation technology) and varying concentrations of lactic acid washes for controlling E. coli O157:H7 on baby spinach. Leaves were dip inoculated with a five-strain cocktail of E. coli O157:H7 inoculum having a concentration between 5-6 log CFU/ml. Leaves were submerged in inoculum for 30 s and dried for 1 h. Non-inoculated and inoculated leaves were washed for 30 s in food grade lactic acid diluted to concentrations of 0.5, 1.0, or 2.0% and allowed to dry for 10 min. For PHI treatment, leaves were placed under the PHI panel and treated for 1, 2, or 5 min on both sides for total treatment times of 2, 4 or 10 min. Following treatments, leaves were either sealed in low-density polyethylene bags or enumerated. Samples were enumerated at 0, 3, 7, 10, and 14 days following inoculation. Ten gram samples were diluted with sterile peptone and stomached for one min, and then 0.1 ml was plated onto sorbitol MacConkey agar with cefixime and tellurite plates that were incubated at 37°C for 24 h. For lactic acid treatments, E. coli O157:H7 populations were different (P < 0.05) compared to the control. There was no difference (P > 0.05) due to sampling time so sampling times where pooled together for each lactic acid concentration of 0.5, 1.0, and 2.0% and resulted in 2.01, 2.78, and 3.67 log CFU/g reductions, respectively. Leaves treated with 1.0% and 2.0% lactic acid had color degradation and were organoleptically unacceptable by day 14. When leaves were treated with PHI for 1, 2, or 5 min per side, E. coli O157:H7 populations were reduced 1.6, 1.49, or 1.95 log CFU/g, respectively. Leaves treated with PHI were not different from one another, but were different (P < 0.05) from the positive control. No color change occurred in leaves treated with PHI. The PHI panel and lactic acid washes of 0.5% or higher are effective in reducing E. coli O157:H7 in baby spinach.
4

Automated Gravel Road Condition Assessment : A Case Study of Assessing Loose Gravel using Audio Data

Saeed, Nausheen January 2021 (has links)
Gravel roads connect sparse populations and provide highways for agriculture and the transport of forest goods. Gravel roads are an economical choice where traffic volume is low. In Sweden, 21% of all public roads are state-owned gravel roads, covering over 20,200 km. In addition, there are some 74,000 km of gravel roads and 210,000 km of forest roads that are owned by the private sector. The Swedish Transport Administration (Trafikverket) rates the condition of gravel roads according to the severity of irregularities (e.g. corrugations and potholes), dust, loose gravel, and gravel cross-sections. This assessment is carried out during the summertime when roads are free of snow. One of the essential parameters for gravel road assessment is loose gravel. Loose gravel can cause a tire to slip, leading to a loss of driver control.  Assessment of gravel roads is carried out subjectively by taking images of road sections and adding some textual notes. A cost-effective, intelligent, and objective method for road assessment is lacking. Expensive methods, such as laser profiler trucks, are available and can offer road profiling with high accuracy. These methods are not applied to gravel roads, however, because of the need to maintain cost-efficiency.  In this thesis, we explored the idea that, in addition to machine vision, we could also use machine hearing to classify the condition of gravel roads in relation to loose gravel. Several suitable classical supervised learning and convolutional neural networks (CNN) were tested. When people drive on gravel roads, they can make sense of the road condition by listening to the gravel hitting the bottom of the car. The more we hear gravel hitting the bottom of the car, the more we can sense that there is a lot of loose gravel and, therefore, the road might be in a bad condition. Based on this idea, we hypothesized that machines could also undertake such a classification when trained with labeled sound data. Machines can identify gravel and non-gravel sounds. In this thesis, we used traditional machine learning algorithms, such as support vector machines (SVM), decision trees, and ensemble classification methods. We also explored CNN for classifying spectrograms of audio sounds and images in gravel roads. Both supervised learning and CNN were used, and results were compared for this study. In classical algorithms, when compared with other classifiers, ensemble bagged tree (EBT)-based classifiers performed best for classifying gravel and non-gravel sounds. EBT performance is also useful in reducing the misclassification of non-gravel sounds. The use of CNN also showed a 97.91% accuracy rate. Using CNN makes the classification process more intuitive because the network architecture takes responsibility for selecting the relevant training features. Furthermore, the classification results can be visualized on road maps, which can help road monitoring agencies assess road conditions and schedule maintenance activities for a particular road. / <p>Due to unforeseen circumstances the seminar was postponed from May 7 to 28, as duly stated in the new posting page.</p>
5

Automatic loose gravel condition detection using acoustic observations

Kyros, Gionian, Myrén, Elias January 2022 (has links)
Evaluation of the road's condition and state is essential for its upkeep, especially when discussing gravel roads, for the following reasons, among other. When loose gravel is not adequately maintained, it can pose a hazard to drivers, who can lose control of their vehicle and cause accidents. Current maintenance procedures are either laborious or time-consuming. Road agencies and institutions are on the lookout for more effective techniques. This study seeks to establish an automatic method for estimating loose gravel using acoustic observation. On gravelroads, recordings from a car's interior were evaluated and matched to the road's state. The first strategy examined road sections with a four-tier (multiclass) manual classification, based on their perceived condition of loose gravel, in accordance with the Swedish road administration authority’s guidelines. The second, examined two tier (binary) manual classification, distinguishing between roads with low and high maintenance needs. Sound features were extracted and processed for subsequentanalysis. Several supervised machine learning methods and algorithms, combined with selected data preprocessing strategies, were deployed. The performance of each strategy and model is determined by assessing and evaluating their classification accuracy along with other performance metrics. The SVM classifier had the best performance in classifying both multiclass as well as binary gravel road conditions. SVM achieved an accuracy of 57.8% when classifying on a four-tier scale and an accuracy of 82% when classifying on a two-tier scale. These results indicate some merits of using audio features as predictive features in the automatic classification of loose gravel conditions on gravel roads.
6

Improving XRD Analysis with Machine Learning

Drapeau, Rachel E. 14 August 2023 (has links) (PDF)
X-ray diffraction analysis (XRD) is an inexpensive method to quantify the relative proportions of mineral phases in a rock or soil sample. However, the analytical software available for XRD requires extensive user input to choose phases to include in the analysis. Consequently, analysis accuracy depends greatly on the experience of the analyst, especially as the number of phases in a sample increases (Raven & Self, 2017; Omotoso, 2006). The purpose of this project is to test whether incorporating machine learning methods into XRD software can improve the accuracy of analyses by assisting in the phase-picking process. In order to provide a large enough sample of X-ray diffraction (XRD) patterns and their known compositions to train the machine learning models, I created a dataset of 1.5 million calculated XRD patterns of realistic mineral mixtures. These synthetic XRD patterns were calculated using crystal structure files from the American Mineralogist Crystal Structure Database (AMCSD) with mineral occurrence data from the Mineral Evolution Database (MED) to mimic geologic knowledge used by expert analysts. Using this dataset, I trained and refined a variety of machine learning models to determine which model is most accurate in identifying the correct mineral phases.
7

A Comparison of Classification Methods in Predicting the Presence of DNA Profiles in Sexual Assault Kits

Heckman, Derek J. 11 January 2018 (has links)
No description available.
8

REAL-TIME PREDICTION OF SHIMS DIMENSIONS IN POWER TRANSFER UNITS USING MACHINE LEARNING

Jansson, Daniel, Blomstrand, Rasmus January 2019 (has links)
No description available.
9

Radar based tank level measurement using machine learning : Agricultural machines / Nivåmätning av tank med radar sensorer och maskininlärning

Thorén, Daniel January 2021 (has links)
Agriculture is becoming more dependent on computerized solutions to make thefarmer’s job easier. The big step that many companies are working towards is fullyautonomous vehicles that work the fields. To that end, the equipment fitted to saidvehicles must also adapt and become autonomous. Making this equipment autonomoustakes many incremental steps, one of which is developing an accurate and reliable tanklevel measurement system. In this thesis, a system for tank level measurement in a seedplanting machine is evaluated. Traditional systems use load cells to measure the weightof the tank however, these types of systems are expensive to build and cumbersome torepair. They also add a lot of weight to the equipment which increases the fuel consump-tion of the tractor. Thus, this thesis investigates the use of radar sensors together witha number of Machine Learning algorithms. Fourteen radar sensors are fitted to a tankat different positions, data is collected, and a preprocessing method is developed. Then,the data is used to test the following Machine Learning algorithms: Bagged RegressionTrees (BG), Random Forest Regression (RF), Boosted Regression Trees (BRT), LinearRegression (LR), Linear Support Vector Machine (L-SVM), Multi-Layer Perceptron Re-gressor (MLPR). The model with the best 5-fold crossvalidation scores was Random For-est, closely followed by Boosted Regression Trees. A robustness test, using 5 previouslyunseen scenarios, revealed that the Boosted Regression Trees model was the most robust.The radar position analysis showed that 6 sensors together with the MLPR model gavethe best RMSE scores.In conclusion, the models performed well on this type of system which shows thatthey might be a competitive alternative to load cell based systems.

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