Supervisión multidistribuida para el control de procesos de conservación de productos agroalimentarios: optimización de calidad del producto

La presente Tesis está orientada al análisis de la supervisión multidistribuida de tres procesos agroalimentarios: el secado solar, el transporte refrigerado y la fermentación de café, a través de la información obtenida de diferentes dispositivos de adquisición de datos, que incorporan sensores, así como el desarrollo de metodologías de análisis de series temporales, modelos y herramientas de control de procesos para la ayuda a la toma de decisiones en las operaciones de estos entornos. En esta tesis se han utilizado: tarjetas RFID (TemTrip®) con sistema de comunicación por radiofrecuencia y sensor de temperatura; el registrador (i-Button®), con sensor integrado de temperatura y humedad relativa y un tercer prototipo empresarial, módulo de comunicación inalámbrico Nlaza, que integra un sensor de temperatura y humedad relativa Sensirion®. Estos dispositivos se han empleado en la conformación de redes multidistribuidas de sensores para la supervisión de: A) Transportes de producto hortofrutícola realizados en condiciones comerciales reales, que son: dos transportes terrestre de producto de IV gama desde Murcia a Madrid; transporte multimodal (barco-barco) de limones desde Montevideo (Uruguay) a Cartagena (España) y transporte multimodal (barco-camión) desde Montevideo (Uruguay) a Verona (Italia). B) dos fermentaciones de café realizadas en Popayán (Colombia) en un beneficiadero. Estas redes han permitido registrar la dinámica espacio-temporal de temperaturas y humedad relativa de los procesos estudiados. En estos procesos de transporte refrigerado y fermentación la aplicación de herramientas de visualización de datos y análisis de conglomerados, han permitido identificar grupos de sensores que presentan patrones análogos de sus series temporales, caracterizando así zonas con dinámicas similares y significativamente diferentes del resto y permitiendo definir redes de sensores de menor densidad cubriendo las diferentes zonas identificadas. Las metodologías de análisis complejo de las series espacio-temporales (modelos psicrométricos, espacio de fases bidimensional e interpolaciones espaciales) permitieron la cuantificación de la variabilidad del proceso supervisado tanto desde el punto de vista dinámico como espacial así como la identificación de eventos. Constituyendo así herramientas adicionales de ayuda a la toma de decisiones en el control de los procesos. Siendo especialmente novedosa la aplicación de la representación bidimensional de los espacios de fases en el estudio de las series espacio-temporales de variables ambientales en aplicaciones agroalimentarias, aproximación que no se había realizado hasta el momento. En esta tesis también se ha querido mostrar el potencial de un sistema de control basado en el conocimiento experto como es el sistema de lógica difusa. Se han desarrollado en primer lugar, los modelos de estimación del contenido en humedad y las reglas semánticas que dirigen el proceso de control, el mejor modelo se ha seleccionado mediante un ensayo de secado realizado sobre bolas de hidrogel como modelo alimentario y finalmente el modelo se ha validado mediante un ensayo en el que se deshidrataban láminas de zanahoria. Los resultados sugirieron que el sistema de control desarrollado, es capaz de hacer frente a dificultades como las variaciones de temperatura día y noche, consiguiendo un producto con buenas características de calidad comparables a las conseguidas sin aplicar ningún control sobre la operación y disminuyendo así el consumo energético en un 98% con respecto al mismo proceso sin control. La instrumentación y las metodologías de análisis de datos implementadas en esta Tesis se han mostrado suficientemente versátiles y transversales para ser aplicadas a diversos procesos agroalimentarios en los que la temperatura y la humedad relativa sean criterios de control en dichos procesos, teniendo una aplicabilidad directa en el sector industrial ABSTRACT This thesis is focused on the analysis of multi-distributed supervision of three agri-food processes: solar drying, refrigerated transport and coffee fermentation, through the information obtained from different data acquisition devices with incorporated sensors, as well as the development of methodologies for analyzing temporary series, models and tools to control processes in order to help in the decision making in the operations within these environments. For this thesis the following has been used: RFID tags (TemTrip®) with a Radiofrequency ID communication system and a temperature sensor; the recorder (i-Button®), with an integrated temperature and relative humidity and a third corporate prototype, a wireless communication module Nlaza, which has an integrated temperature and relative humidity sensor, Sensirion®. These devices have been used in creating three multi-distributed networks of sensors for monitoring: A) Transport of fruits and vegetables made in real commercial conditions, which are: two land trips of IV range products from Murcia to Madrid; multimodal transport (ship - ship) of lemons from Montevideo (Uruguay) to Cartagena (Spain) and multimodal transport (ship - truck) from Montevideo (Uruguay) to Verona (Italy). B) Two coffee fermentations made in Popayan (Colombia) in a coffee processing plant. These networks have allowed recording the time space dynamics of temperatures and relative humidity of the processed under study. Within these refrigerated transport and fermentation processes, the application of data display and cluster analysis tools have allowed identifying sensor groups showing analogical patterns of their temporary series; thus, featuring areas with similar and significantly different dynamics from the others and enabling the definition of lower density sensor networks covering the different identified areas. The complex analysis methodologies of the time space series (psychrometric models, bi-dimensional phase space and spatial interpolation) allowed quantifying the process variability of the supervised process both from the dynamic and spatial points of view; as well as the identification of events. Thus, building additional tools to aid decision-making on process control brought the innovative application of the bi-dimensional representation of phase spaces in the study of time-space series of environmental variables in agri-food applications, an approach that had not been taken before. This thesis also wanted to show the potential of a control system based on specialized knowledge such as the fuzzy logic system. Firstly, moisture content estimation models and semantic rules directing the control process have been developed, the best model has been selected by an drying assay performed on hydrogel beads as food model; and finally the model has been validated through an assay in which carrot sheets were dehydrated. The results suggested that the control system developed is able to cope with difficulties such as changes in temperature daytime and nighttime, getting a product with good quality features comparable to those features achieved without applying any control over the operation and thus decreasing consumption energy by 98% compared to the same uncontrolled process. Instrumentation and data analysis methodologies implemented in this thesis have proved sufficiently versatile and cross-cutting to apply to several agri-food processes in which the temperature and relative humidity are the control criteria in those processes, having a direct effect on the industry sector.

Adjoint modular Galois representations and their Selmer groups

In the last 15 years, many class number formulas and main conjectures have been proven. Here, we discuss such formulas on the Selmer groups of the three-dimensional adjoint representation ad(φ) of a two-dimensional modular Galois representation φ. We start with the p-adic Galois representation φ0 of a modular elliptic curve E and present a formula expressing in terms of L(1, ad(φ0)) the intersection number of the elliptic curve E and the complementary abelian variety inside the Jacobian of the modular curve. Then we explain how one can deduce a formula for the order of the Selmer group Sel(ad(φ0)) from the proof of Wiles of the Shimura–Taniyama conjecture. After that, we generalize the formula in an Iwasawa theoretic setting of one and two variables. Here the first variable, T, is the weight variable of the universal p-ordinary Hecke algebra, and the second variable is the cyclotomic variable S. In the one-variable case, we let φ denote the p-ordinary Galois representation with values in GL2(Zp[[T]]) lifting φ0, and the characteristic power series of the Selmer group Sel(ad(φ)) is given by a p-adic L-function interpolating L(1, ad(φk)) for weight k + 2 specialization φk of φ. In the two-variable case, we state a main conjecture on the characteristic power series in Zp[[T, S]] of Sel(ad(φ) ⊗ ν−1), where ν is the universal cyclotomic character with values in Zp[[S]]. Finally, we describe our recent results toward the proof of the conjecture and a possible strategy of proving the main conjecture using p-adic Siegel modular forms.

Numerical resolution of Emden's equation using Adomian polynomials

Purpose: In this paper the authors aim to show the advantages of using the decomposition method introduced by Adomian to solve Emden's equation, a classical non‐linear equation that appears in the study of the thermal behaviour of a spherical cloud and of the gravitational potential of a polytropic fluid at hydrostatic equilibrium. Design/methodology/approach: In their work, the authors first review Emden's equation and its possible solutions using the Frobenius and power series methods; then, Adomian polynomials are introduced. Afterwards, Emden's equation is solved using Adomian's decomposition method and, finally, they conclude with a comparison of the solution given by Adomian's method with the solution obtained by the other methods, for certain cases where the exact solution is known. Findings: Solving Emden's equation for n in the interval [0, 5] is very interesting for several scientific applications, such as astronomy. However, the exact solution is known only for n=0, n=1 and n=5. The experiments show that Adomian's method achieves an approximate solution which overlaps with the exact solution when n=0, and that coincides with the Taylor expansion of the exact solutions for n=1 and n=5. As a result, the authors obtained quite satisfactory results from their proposal. Originality/value: The main classical methods for obtaining approximate solutions of Emden's equation have serious computational drawbacks. The authors make a new, efficient numerical implementation for solving this equation, constructing iteratively the Adomian polynomials, which leads to a solution of Emden's equation that extends the range of variation of parameter n compared to the solutions given by both the Frobenius and the power series methods.

Formal group laws and hypergraph colorings

Thesis (Ph.D.)--University of Washington, 2016-06

Adult mental health needs and expenditure in Australia

Background Relatively little international work has examined whether mental health resource allocation matches need. This study aimed to determine whether adult mental health resources in Australia are being distributed equitably. Method Individual measures of need were extrapolated to Australian Areas, and Area-based proxies of need were considered. Particular attention was paid to the prevalence of mental health problems, since this is arguably the most objective measure of need. The extent to which these measures predicted public sector, private sector and total adult mental health expenditure at an Area level was examined. Results In the public sector, 41.6% of expenditure variation was explained by the prevalence of affective disorders, personality disorders, cognitive impairment and psychosis, as well as the Area's level of economic resources and State/Territory effects. In the private sector, 72.4% of expenditure variation was explained by service use and State/Territory effects (with an alternative model incorporating service use and State/Territory supply of private psychiatrists explaining 69.4% of expenditure variation). A relatively high proportion (58.7%) of total expenditure variation could be explained by service utilisation and State/Territory effects. Conclusions For services to be delivered equitably, the majority of variation in expenditure would have to be accounted for by appropriate measures of need. The best model for public sector expenditure included an appropriate measure of need but had relatively poor explanatory power. The models for private sector and total expenditure had greater explanatory power, but relied on less appropriate measures of need. It is concluded that mental health services in Australia are not yet being delivered equitably.

Statistical modeling and projections of lung cancer mortality in 4 industrialized countries

The purpose of this work was to model lung cancer mortality as a function of past exposure to tobacco and to forecast age-sex-specific lung cancer mortality rates. A 3-factor age-period-cohort (APC) model, in which the period variable is replaced by the product of average tar content and adult tobacco consumption per capita, was estimated for the US, UK, Canada and Australia by the maximum likelihood method. Age- and sex-specific tobacco consumption was estimated from historical data on smoking prevalence and total tobacco consumption. Lung cancer mortality was derived from vital registration records. Future tobacco consumption, tar content and the cohort parameter were projected by autoregressive moving average (ARIMA) estimation. The optimal exposure variable was found to be the product of average tar content and adult cigarette consumption per capita, lagged for 2530 years for both males and females in all 4 countries. The coefficient of the product of average tar content and tobacco consumption per capita differs by age and sex. In all models, there was a statistically significant difference in the coefficient of the period variable by sex. In all countries, male age-standardized lung cancer mortality rates peaked in the 1980s and declined thereafter. Female mortality rates are projected to peak in the first decade of this century. The multiplicative models of age, tobacco exposure and cohort fit the observed data between 1950 and 1999 reasonably well, and time-series models yield plausible past trends of relevant variables. Despite a significant reduction in tobacco consumption and average tar content of cigarettes sold over the past few decades, the effect on lung cancer mortality is affected by the time lag between exposure and established disease. As a result, the burden of lung cancer among females is only just reaching, or soon will reach, its peak but has been declining for I to 2 decades in men. Future sex differences in lung cancer mortality are likely to be greater in North America than Australia and the UK due to differences in exposure patterns between the sexes. (c) 2005 Wiley-Liss, Inc.

The performance of the maximum ratio combining method in correlated Rician-fading channels for antenna-diversity signal combining

The performance of the maximum ratio combining method for the combining of antenna-diversity signals in correlated Rician-fading channels is rigorously studied. The distribution function of the normalized signal-to-noise ratio (SNR) is expanded in terms of a power series and calculated numerically. This power series can easily take into account the signal correlations and antenna gains and can be applied to any number of receiving antennas. An application of the method to dual-antenna diversity systems produces useful distribution curves for the normalized SNR which can be used to find the diversity gain. It is revealed that signal correlation in Rician-fading channels helps to increase the diversity gain rather than to decrease it as in the Rayleigh fading channels. It is also shown that with a relative strong direct signal component, the diversity gain can be much higher than that without a direct signal component.

Size frequency distribution of the β-amyloid (aβ) deposits in dementia with Lewy bodies with associated Alzheimer’s disease pathology

The objective is to study beta-amyloid (Abeta) deposition in dementia with Lewy bodies (DLB) with Alzheimer's disease (AD) pathology (DLB/AD). The size frequency distributions of the Abeta deposits were studied and fitted by log-normal and power-law models. Patients were ten clinically and pathologically diagnosed DLB/AD cases. Size distributions had a single peak and were positively skewed and similar to those described in AD and Down's syndrome. Size distributions had smaller means in DLB/AD than in AD. Log-normal and power-law models were fitted to the size distributions of the classic and diffuse deposits, respectively. Size distributions of Abeta deposits were similar in DLB/AD and AD. Size distributions of the diffuse deposits were fitted by a power-law model suggesting that aggregation/disaggregation of Abeta was the predominant factor, whereas the classic deposits were fitted by a log-normal distribution suggesting that surface diffusion was important in the pathogenesis of the classic deposits.

Size frequency distributions of β-amyloid (Aβ) deposits:a comparative study of four neurodegenerative disorders

Deposition of ß-amyloid (Aß ), a 'signature' pathological lesion of Alzheimer's disease (AD), is also characteristic of Down's syndrome (DS), and has been observed in dementia with Lewy bodies (DLB) and corticobasal degeneration (CBD). To determine whether the growth of Aß deposits was similar in these disorders, the size frequency distributions of the diffuse ('pre-amyloid'), primitive ('neuritic'), and classic ('dense-cored') A ß deposits were compared in AD, DS, DLB, and CBD. All size distributions had essentially the same shape, i.e., they were unimodal and positively skewed. Mean size of Aß deposits, however, varied between disorders. Mean diameters of the diffuse, primitive, and classic deposits were greatest in DS, DS and CBD, and DS, respectively, while the smallest deposits, on average, were recorded in DLB. Although the shape of the frequency distributions was approximately log-normal, the model underestimated the frequency of smaller deposits and overestimated the frequency of larger deposits in all disorders. A 'power-law' model fitted the size distributions of the primitive deposits in AD, DS, and DLB, and the diffuse deposits in AD. The data suggest: (1) similarities in size distributions of Aß deposits among disorders, (2) growth of deposits varies with subtype and disorder, (3) different factors are involved in the growth of the diffuse/primitive and classic deposits, and (4) log-normal and power-law models do not completely account for the size frequency distributions.

Robust Parametric Estimation of Branching Processes with a Random Number of Ancestors

2000 Mathematics Subject Classification: 60J80.

Parametric Estimation in Branching Processes with an Increasing Random Number of Ancestors

2000 Mathematics Subject Classification: 60J80, 62M05

Zeros of Sequences of Partial Sums and Overconvergence

2000 Mathematics Subject Classification: 30B40, 30B10, 30C15, 31A15.

Temporal analysis of land use and transportation investments with geographic information system

Land use and transportation interaction has been a research topic for several decades. There have been efforts to identify impacts of transportation on land use from several different perspectives. One focus has been the role of transportation improvements in encouraging new land developments or relocation of activities due to improved accessibility. The impacts studied have included property values and increased development. Another focus has been on the changes in travel behavior due to better mobility and accessibility. Most studies to date have been conducted in metropolitan level, thus unable to account for interactions spatially and temporally at smaller geographic scales. ^ In this study, a framework for studying the temporal interactions between transportation and land use was proposed and applied to three selected corridor areas in Miami-Dade County, Florida. The framework consists of two parts: one is developing of temporal data and the other is applying time series analysis to this temporal data to identify their dynamic interactions. Temporal GIS databases were constructed and used to compile building permit data and transportation improvement projects. Two types of time series analysis approaches were utilized: univariate models and multivariate models. Time series analysis is designed to describe the dynamic consequences of time series by developing models and forecasting the future of the system based on historical trends. Model estimation results from the selected corridors were then compared. ^ It was found that the time series models predicted residential development better than commercial development. It was also found that results from three study corridors varied in terms of the magnitude of impacts, length of lags, significance of the variables, and the model structure. Long-run effect or cumulated impact of transportation improvement on land developments was also measured with time series techniques. The study offered evidence that congestion negatively impacted development and transportation investments encouraged land development. ^

Application of intervention analysis to evaluate the impacts of special events on freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.

Application of Intervention Analysis to Evaluate the Impacts of Special Events on Freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.