A determinação do tempo de vida útil dos alimentos é importante, pois garante que estes estejam adequados para o consumo se ingeridos dentro do período estipulado. Os alimentos que apresentam vida curta têm seu tempo de vida útil determinado por estudos não acelerados, os quais demandam métodos multivariados de análise para uma boa predição. Considerando isso, este estudo objetiva: propor um método estatístico multivariado capaz de predizer o tempo de vida útil de alimentos, em estudos não acerados; avaliar sua estabilidade e sensibilidade frente a perturbações provocadas nas variáveis de entrada, utilizando técnicas de simulação bootstrap; apresentar o método SheNon para dados experimentais por meio da construção de contrastes dos tempos preditos dos tratamentos de interesse e compará-los com uma diferença mínima significativa (DMS) obtida empiricamente por meio do método bootstrap. Com os resultados provenientes deste estudo constatou-se que o método proposto mostra-se promissor e estável para a predição do tempo de vida útil de alimentos em estudos não acelerados. O método mostrou-se sensível ao número de tempos (tamanho da amostra) em que o alimento foi observado. Verificou-se, também, bom desempenho na análise de dados experimentais, uma vez que após predição do tempo de vida útil para cada tratamento considerado, pode-se inferir sobre a igualdade dos tempos de vida de diferentes tratamentos. / Consumers are increasingly demanding about the quality of food and expectation that this quality is maintained at high level during the period between purchase and consumption. These expectations are a consequence not only of the requirement that the food should stay safe, but also the need to minimize the unwanted changes in their sensory qualities. Considering food safety and consumer demands this study aims to propose a multivariate statistical method to predict the shelf life of time not accelerated studies, the method SheNon. The development of multivariate method for predicting the shelf life of a food, considering all attributes and their natures describes a new concept of data analysis for estimating the degradation mechanisms that govern food and determines the time period in which these foods retain their characteristics within acceptable levels. The proposed method allows to include microbiological, physical, chemical and sensory attributes, which leads to a more accurate prediction of shelf life of food. The method SheNon features easy interpretation, its main advantages include the ability to combine information from different natures and can be generalized to data with experimental structure. The method SheNon was applied to eggplants minimally processed predicting a lifetime of around 9.6 days.

The main purpose of this degree project is to reveal the Airbnb customer’s preferences and quantify the impact of non-market factors on the market price of tourist accommodation in Berlin, Germany. The data retrieved from Airbnb listings, publicly available on Inside Airbnb (2017), was supplemented on indicator of sharing economy accommodation using machine learning method in order to distinguish between amateur and business-running professional hosts. The main aim is to examine the consumers’ preferences and quantify the marginal effect of "real sharing economy" accommodation and other key variables on market price. This is accomplished by model approach using hedonic pricing method, which is used to estimate the economic value of particular attribute. Surprisingly, our data indicates the negative impact of sharing economy indicator on price. The set of motivations of consumers, which determine their valuation of Airbnb listings, was identified. The trade-off between encompass and parsimony of the set was desired in order to build an effective model. Calculation of proportion of explained variance showed that the price is affected mainly by number of accommodated persons, degree of privacy, number of bedrooms, cancellation policy, distance from the city centre and sharing economy indicator in decreasing order.

Submitted by (ana.araujo@ufrpe.br) on 2017-02-17T11:47:54Z No. of bitstreams: 1 Ismael Gaiao da Costa.pdf: 2381457 bytes, checksum: 1ddfca5789915a115c0404f1571561e5 (MD5) / Made available in DSpace on 2017-02-17T11:47:54Z (GMT). No. of bitstreams: 1 Ismael Gaiao da Costa.pdf: 2381457 bytes, checksum: 1ddfca5789915a115c0404f1571561e5 (MD5) Previous issue date: 2011-02-24 / Brazil is the world's largest producer of sugarcane (Saccharum spp.), whose culture interacts with the most varied environments. The replacement of varieties has contributed greatly to an effective increase in productivity. Thus it studies of genotype x environment (G x E) interaction, the analysis of phenotypic adaptability and stability, and the selection of parents for hybridization are essential for the indication of varieties suited to different soil and climatic conditions. The objective of this research was to evaluate the agribusiness behavior, adaptability and phenotypic stability of 11 RB sugarcane clones in the final phase of the trial, in sugarcane micro regions in the State of Pernambuco, Brazil Northeast, for three consecutives harvests, as well as assisting the selection of potential parents to be used in future crossings by conducted by Sugarcane Breeding Program (PMGCA) of Network for the Development of Alcohol and Sugar (RIDESA) of Experimental Station Sugarcane Carpina (EECAC) of Federal Rural University of Pernambuco (UFRPE). The experiments were carried out in five Pernambuco sugar mills, in the months of july and august 2006, using the experimental design of randomized blocks with four replications and plots with five eight-meter furrows and spacing of 1.0 m. The results were subjected to analysis of variance, comparison of averages by Scott & Knott test and studies of adaptability, stability and genetic divergence. In each section the variables were measured as ton of pol per hectare (TPH), ton of cane per hectare (TCH); fibre (FIB), Pol% corrected (PCC), purity (PZA), soluble solids (BRIX) and total recoverable sugar (TRS). Based on the results, the best RB genotypes of sugarcane were G1, G6 and G9 in environment I, G1 and G11 in environment II, G1 and G9 in environment III, G3 for environment IV and G1 the environment V. Among the best clones, those with wide adaptability are: G1 and G11, and those with adaptability to environments are: G6 and G9. The genotypes most indicated for use in hybridizations are G1 and G6, as they showed the greatest genetic dissimilarity. / O Brasil é o maior produtor mundial de cana-de-açúcar (Saccharum spp.), cuja cultura interage com os mais variados ambientes. A substituição de variedades tem contribuído bastante para um eficiente aumento na produtividade. Neste sentido, os estudos da interação genótipo x ambiente (G x A), as análises de adaptabilidade e estabilidade fenotípica, e a seleção de parentais para cruzamentos são imprescindíveis para a indicação de variedades adequadas às diversas condições edafoclimáticas. Objetivou-se com esta pesquisa avaliar o comportamento agroindustrial, a adaptabilidade e a estabilidade fenotípica de 11 clones RB de cana-de-açúcar, na fase final da experimentação, em microrregiões canavieiras do Estado de Pernambuco, por três colheitas consecutivas, bem como auxiliar a seleção de progenitores potenciais a serem utilizados em futuros cruzamentos pelo Programa de Melhoramento Genético da Cana-de-açúcar (PMGCA) da Rede Interuniversitária para o Desenvolvimento do Setor Sucroalcooleiro (RIDESA) conduzido pela Estação Experimental de Cana-de-açúcar (EECAC) da Universidade Federal Rural de Pernambuco (UFRPE). Os experimentos foram instalados em cinco usinas de Pernambuco, nos meses de julho e agosto de 2006, utilizando-se o delineamento experimental de blocos casualizados, com quatro repetições e parcelas com cinco sulcos de oito metros com espaçamento de 1,0 m. Os resultados foram submetidos à análise de variância, à comparação de médias pelo teste de Scott & Knott e a estudos de adaptabilidade, estabilidade e divergência genética. Em cada corte foram mensuradas as variáveis tonelada de pol por hectare (TPH), tonelada de cana por hectare (TCH); Pol% corrigido (PCC), fibra (FIB), pureza (PZA), teor de sólidos solúveis (BRIX) e açúcar total recuperável (ATR). Com base nos resultados, os genótipos RB de cana-de-açúcar mais produtivos foram G1, G6 e G9; para o ambiente I, G11 e G1 para o ambiente II, G9 e G1 para o ambiente III, G3 para o ambiente IV e G1 para o ambiente V. Dentre os melhores clones, aqueles com adaptabilidade ampla são: G1 e G11; e aqueles com adaptabilidade para ambientes favoráveis são: G6 e G9. Os genótipos mais indicados para utilização em hibridações são G1 e G6, pois estes apresentaram a maior dissimilaridade genética.

As modificações impostas pela ação do homem desequilibram o complexo sistema natural, alterando os elementos e características do clima na escala local. A cidade é o exemplo mais significativo destas transformações e o campo térmico urbano é um dos elementos do sistema cidade-atmosfera mais afetados pela mudança do uso e da cobertura do solo. No Brasil, tem-se observado que a grande maioria dos estudos de clima urbano está focada nas grandes cidades, sobre as características do clima urbano para a região Centro-Oeste, especialmente nas cidades de pequeno porte, pouco se conhece. Dessa forma, o objetivo desta pesquisa foi de analisar as influências das características geourbanas na configuração do clima da cidade de Iporá e identificar a variabilidade temporal e espacial das ilhas de calor urbanas. Para tanto, instalou-se oito aparelhos termo-higrômetros para a coleta de dados de temperatura do ar e umidade e duas estação meteorológicas completas, uma na área urbana e a outra na área rural, também foram utilizadas imagens multiespectrais do satélite Landsat 5 e 8. Nas análises dos dados foram utilizadas regressões lineares simples e múltiplas, modelagem, simulações e foi proposto um índice (InGe) para quantificar a influência do homem no clima da cidade. Os resultados evidenciaram que: 1 - em algumas áreas da cidade de Iporá foram observadas tendências significativas de aumento na intensidade das anomalias térmicas; 2 - as variáveis mais influentes na regressão linear múltipla da temperatura de superfície (TS) foram o NDVI que explicou 35% da variabilidade e a densidade demográfica com 25%; 3 - a equação final, proposta como modelo preditor da intensidade máxima da ilha de calor urbana de superfície para a Região do Oeste Goiano obteve r2 de 0,6; 4 - quanto maior a distância da área verde maior a temperatura de superfície, além disso, na primavera ou próximo dela, a intensidade do efeito da área verde na TS foi muito superior ao efeito em outras datas; 5 - os padrões dos desvios da umidade absoluta permitiram afirmar que a área central, mais urbanizada, teve os maiores desvios negativos e áreas com maiores valores de NDVI e próximas aos cursos d\'água apresentaram os maiores desvios positivos de umidade; 6 - as ilhas de calor urbanas em Iporá foram mais frequentes na intensidade de 0,5°C e 1°C, a intensidade máxima observada foi de 3,5°C; 7 - as áreas localizadas nos fundos de vale apresentaram os menores valores térmicos, o que sugere uma drenagem de ar frio. Contudo, constatou-se que a cidade de Iporá, mesmo se tratando de uma cidade pequena, modifica seus parâmetros atmosféricos. / The changes imposed by man unbalance the complex natural system, changing the climate elements and features at local scale. The city is the most significant example of these transformations and the urban thermal field is the element of the city-atmosphere most affected by the use and land cover change system. In Brazil, it has been observed that the vast majority of urban climate research is focused on big cities, so that little is known on urban climate characteristics for the Midwest, especially in small towns. Thus, the objective of this research was to analyze the influence of Geourban characteristics in the climate setting of the city of Iporá and to identify the temporal and spatial variability of urban heat islands. Therefore, eight Thermo-Hygrometer devices for collecting air temperature and humidity data and two complete weather stations were settled, one in the urban area and the other in the rural area; Landsat 5 and 8 multi-spectral images of were also used. In data analysis simple and multiple linear regressions, modeling and simulations were used and an index (InGe) was proposed to quantify the man influence on the city climate. The results showed that: 1 - in some areas of Iporá city significant trends of increasing intensity of thermal anomalies were observed; 2 - the most influential variables in the multiple regression of surface temperature (TS) were explained by NDVI (35% of the variability) and population density (25%); 3 - the final equation, proposed as a maximum intensity predictive model of the urban surface heat island for the West Region of Goiás, we obtained an R2 0.6; 4 - the greater the distance from the green area, the higher surface temperature; moreover, in the spring, or close to it, the intensity of the green area effect on TS was by far superior to the effect at other periods; 5 - the patterns of the absolute humidity deviations allow us to affirm that the central area, urbanized, had the highest negative variances, while the areas with higher NDVI values and nearby watercourses showed the highest positive deviations moisture; 6 - urban heat islands on Iporá were more frequent at the intensity of 0.5°C to 1°C, while the maximum intensity was observed at 3.5°C; 7 - the areas located in the valley bottoms had the lowest thermal values, suggesting a cold air drainage. However, it was found that the city of Iporá, despite being a small town, modifies its atmospheric parameters.

Made available in DSpace on 2015-04-22T22:10:29Z (GMT). No. of bitstreams: 1 Ronaldo.pdf: 1637363 bytes, checksum: 9790e5cd16e5dd126dae9d8524889ce1 (MD5) Previous issue date: 2011-06-03 / Performance evaluation of production processes or subsidiary to this is always something to be sought, due bring some differentiation as a competitor. Many processes use proprietary computer tools, as worksheets, and can meet the need of either demand, but there are cases where their use should be avoided, due may bring harm to the result, or cause increased costs to their practice. Companies, in general, should carry out inventories at various periods, as daily, weekly, quarterly or as needed. Inventory is a routine activity, some companies or industries stop their production process in order to start the inventory process. In theses cases, the completion time becomes critical, because depending on the date which may be close to delivering a big sale product, it is desired that the inventory may be as brief as possible, otherwise it may bring delays in delivery and other results not expected. An analysis of the process of periodic inventory counting of items of a specific sector of the electronics industry in Manus Industry Pole was conducted to better understand the problems from this. With the analysis it was possible to identify which problems exist and investigate better ways of their implementation, such as the use of wireless networks and a mobile device to collect real time data. Noted in conclusion that there was a reduction in costs due to the decrease of people like the counting process, the use of low-cost technology, and we observed a decrease in errors and increase accuracy. / O desempenho dos processos produtivos ou auxiliares a este é algo a ser buscado sempre, pois traz alguma diferenciação quanto ao concorrente. Muitos processos auxiliam-se por ferramentas computacionais comerciais, como planilhas eletrônicas, e podem atender a necessidade de uma ou outra demanda, contudo há processos em que seu uso deve ser evitado, pois podem trazer prejuízos ao resultado, ou causar aumento de custos com a sua prática. As empresas, em geral, devem realizar inventários, em vários períodos, seja diário, semanal, trimestral ou quando necessário. Inventariar é uma atividade rotineira, algumas empresas ou indústrias param seu processo de produção para que seja realizado o processo de inventário. Nestes casos, o tempo de realização se torna crítico, pois dependendo da data, que pode ser próximo a uma grande entrega de produto, deseja-se que o inventário seja o mais breve possível, caso contrário pode trazer atrasos na entrega e outros resultados não esperados. Uma análise do processo de contagens de itens do inventário periódico de um setor específico de uma indústria de eletroeletrônicos do pólo industrial de Manaus foi realizada para melhor entendimento dos problemas oriundos deste. Com a análise foi possível identificar quais problemas existiam e investigar melhores formas de sua execução, tais como o uso de redes sem fio e um dispositivo móvel para coleta em tempo real dos dados. Como conclusão observou-se que houve uma redução de custos devido à diminuição de pessoas envolvidas com o processo de contagem, pelo uso de tecnologia de baixo custo, e foi possível verificar uma diminuição nos erros e aumento de acuracidade.

A cadeia produtiva da cana-de-açúcar vem sofrendo problemas de diversas naturezas, sendo a mais comum a estiagem, agravada pelas mudanças climáticas que reduzem a disponibilidade de água no solo, afetando diretamente a produtividade da cultura. Uma grande proporção da cultura da cana-de-açúcar não é irrigada, sendo sujeita a alterações entre estações úmidas e secas em condições tropicais e subtropicais, mas quando é irrigada, tem-se observado um incremento significativo na produtividade da cultura. As necessidades hídricas da cultura devem ser atendidas, tanto, na quantidade requerida, quanto no momento oportuno. Para isto, devem ser quantificados parâmetros relacionados com o seu estado hídrico. No entanto, os métodos empregados convencionalmente são demorados, custosos e invasivos. Como alternativa que ajuda a reduzir tempo e custos, o sensoriamento remoto hiperespectral vem sendo utilizado para estimar o estado hídrico em diferentes escalas, uma vez que permite a captura de grande quantidade de informação rapidamente. Para o presente trabalho, o comportamento espectral da vegetação de 400 a 2500 nm, foi utilizado na quantificação de alguns parâmetros que estabelecem o seu estado hídrico. As avaliações tanto em casa de vegetação quanto em laboratório foram feitas em folhas de cana-de-açúcar submetidas a déficit hídrico programado. Para os dados de laboratório foram obtidos R2 > 0,8 na região do visível e R2 < 0,55, na região do infravermelho próximo para CRA (conteúdo relativo de água). Para EEA (espessura equivalente da água) foi obtido um R2 < 0,6 na região do infravermelho próximo. / The sugarcane agribusiness has been suffering several kinds of problems. The most common is the drought caused by the weather changes, which reduce the water availability in the soil, affecting directly the crop yield. A large proportion of the sugarcane crop is not irrigated undergoing changes between wet and dry seasons in tropical and subtropical conditions, but when it is irrigated, it has been possible to observe an increase in the crop yield. The crop water requirements must be provided, both at the required amount and at the right time. To do this, parameters related to its moisture status have to be quantized. However, conventional methods are slow, invasive and expensive. As an alternative to reduce time and costs, the hyperspectral remote sensing has been being used to estimate the water status at different scales, because it allows capturing big amounts of information quickly. In the present study, the spectral behavior of vegetation between 400 and 2500 nm was used to quantify some parameters that establish its water status. The evaluations were conducted both in the greenhouse and the laboratory on sugarcane leaves under programmed water deficit. The laboratory data obtained were R2> 0.8 in the visible region and R2 <0.55 in the near infrared region for the RWC (relative water content). For the EWT (equivalent water thickness) was obtained a R2 <0.6 in the near infrared region.

This study is an investigation if a recurrent long short-term memory (LSTM) based neural network can be used to estimate the battery capacity in electrical cars. There is an enormous interest in finding the underlying reasons why and how Lithium-ion batteries ages and this study is a part of this broader question. The research questions that have been answered are how well a LSTM model estimates the battery capacity, how the LSTM model is performing compared to a linear model and what parameters that are important when estimating the capacity. There have been other studies covering similar topics but only a few that has been performed on a real data set from real cars driving. With a data science approach, it was discovered that the LSTM model indeed is a powerful model to use for estimation the capacity. It had better accuracy than a linear regression model, but the linear regression model still gave good results. The parameters that implied to be important when estimating the capacity were logically related to the properties of a Lithium-ion battery.En studie över hur väl ett återkommande neuralt nätverk kan estimera kapaciteten hos Litium-ion batteri hos elektroniska fordon, när en en datavetenskaplig strategi har använts.

The primary objective of this study is to evaluate the operational effects of U-turn movement at signalized intersections. More specifically, the research objectives include the following parts: To identify the factors affecting the operational performance of U-turning vehicles. In this case, we are particularly interested in the U-turn speeds of U-turning vehicles. To evaluate the impacts of U-turns on capacity of signalized intersections, and To simulate U-turn movement at signalized intersections using Synchro and validate the simulation results. To achieve the research objectives, extensive field data collection work was conducted at sixteen selected sites at Tampa Bay area of Florida. The data collected in the field include: U-turning speed Left turning speed Turning radius Queue discharge time Control delay Hourly traffic volume, and Percentage of U- turning vehicles in left turn lane. Based on the collected field data, a linear regression model was developed to identify the factors affecting the turning speeds of U-turning vehicles at signalized intersections. The model shows the turning speed is significantly impacted by the turning radius and the speed of U-turning vehicles increases with the increase of turning radius. On the basis of field data field data collection, a regression model was developed to estimate the relationship between the average queue discharge time for each turning vehicle and the various percentages of U-turning vehicles in the left turn traffic stream. Adjustment factors for various percentages of U-turning vehicles were also developed by using the regression model. The adjustment factors developed in this study can be directly used to estimate the capacity reduction due to the presence of various percentages of U-turning vehicles at a signalized intersection. The developed adjustment factors were used to improve the simulation of U-turn movement at signalized intersection by using Synchro. The simulation model was calibrated and validated by field data. It was found that using the developed adjustment factors will greatly improve the accuracy of the simulation results for U-turn movement.

La presente tesis de investigación busca hallar los factores que explican las exportaciones de la quinua de Perú hacia Estados Unidos durante los años 2007 al 2017; ésta se ha desarrollado en 5 capítulos: El primer capítulo incluye información sobre el producto elegido, un acercamiento al mercado mundial de la quinua, así como el destino específico de Estados Unidos; investigaciones anteriores, bases teóricas y definición de las variables del modelo econométrico a seguir. El segundo capítulo plantea la situación problemática, problemas específicos, hipótesis y objetivos, los cuales serán satisfechos a través de una investigación cuantitativa. El tercer capítulo desarrolla el tipo, alcance y diseño de la investigación, la operacionalización de las variables y los instrumentos metodológicos para el recojo de la investigación. El cuarto capítulo comprende el desarrollo y la aplicación del modelo de regresión lineal planteada en la tesis de Mamani (2015). El quinto capítulo muestra el análisis de los resultados obtenidos, conclusiones y recomendaciones. Según el análisis estadístico realizado, se puede concluir que las exportaciones de la quinua de Perú hacia Estados Unidos durante los años 2007 al 2017, son significativamente afectadas por los factores externos de Producto Bruto Interno de Estados Unidos, el precio internacional y la tarifa arancelaria. / This research thesis seeks to find the factors that explain the exports of quinoa from Peru to the United States during the years from 2007 to 2017; This has been developed in 5 chapters: The first chapter includes information about the chosen product, an approach to the world market of quinoa, as well as the specific destination of the United States; previous investigations, theoretical bases and definition of the variables of the followed econometric model. The second chapter presents the problematic situation, specific problems, hypotheses and objectives, which will be satisfied through a quantitative research. The third chapter develops the type, scope and design of the research, the operationalization of the variables and the methodological instruments for the collection of information. The fourth chapter includes the development and application of the linear regression model proposed in the thesis of Mamani (2015). The fifth chapter shows the analysis of the results obtained, conclusions and recommendations. According to the statistical analysis carried out, it can be concluded that the exports of quinoa from Peru to the United States during the years from 2007 to 2017 are significantly affected by the external factors of the United States Gross Domestic Product, the international price and the tariff rate. / Tesis

Traffic fatalities accounted for 1.24 million lives lost in 2013 worldwide, and almost 33 thousand of those fatalities were in the U.S. in 2013. The southeastern region of the nation stands out for continuously having higher fatality rates per mile driven than the national average. If one can establish compelling relationships between various factors and fatality rates, then policies and investments can be targeted to increase the safety on the network by focusing on policies that mitigate those factors. In this research effort risk-taking characteristics are explored. These factors have not been as comprehensively reviewed as conventional factors such as vehicle and facility conditions associated with safety. The hypothesis assumes if a person exhibits risk-taking behavior, that risk-taking behavior is not limited to only one aspect of risk, but is likely to occur in multiple facets of the person's life. Some of the risk-taking characteristics explored include credit score, safety belt use, smoking and tobacco use, drug use, mental health, educational attainment, obesity, and overall general health characteristics. All risk-taking characteristics with the exception of mental health were found to have statistically significant correlations with fatality rates alone. However, when a regression model was formed to estimate fatality rates by risk-taking characteristics, only four risk-taking characteristics - credit score, educational attainment, overall poor health, and seat belt use were found to be statistically significant at an integrated level with other demographic characteristics such as unemployment levels and population born is state of residency. By identifying at-risk population segments, education, counseling, enforcement, or other strategies may be deployed to help improve travel safety.