Greenhouse gas budgets of crop production : current and likely future trends

Publisher PD

Semantic and pragmatic characterization of learning objects

Tese de doutoramento. Engenharia Informática. Universidade do Porto. Faculdade de Engenharia. 201

Distributed Computing and Monitoring Technologies for Older Patients

This book summarizes various approaches for the automatic detection of health threats to older patients at home living alone. The text begins by briefly describing those who would most benefit from healthcare supervision. The book then summarizes possible scenarios for monitoring an older patient at home, deriving the common functional requirements for monitoring technology. Next, the work identifies the state of the art of technological monitoring approaches that are practically applicable to geriatric patients. A survey is presented on a range of such interdisciplinary fields as smart homes, telemonitoring, ambient intelligence, ambient assisted living, gerontechnology, and aging-in-place technology. The book discusses relevant experimental studies, highlighting the application of sensor fusion, signal processing and machine learning techniques. Finally, the text discusses future challenges, offering a number of suggestions for further research directions

Filtragem Não Linear Adaptativa e Seguimento Radar Ótimo de Veículos Aeroespaciais

A filtragem não-linear é um dos tópicos mais importantes e complexos em engenharia, especialmente quando aplicada a situações de tempo-real em ambientes altamente não-lineares. Este é o cenário da maioria das aplicações aeroespaciais nomeadamente, aviso de colisão, seguimento radar, vigilância, orientação, navegação e controlo de veículos aeroespaciais, sendo que o principal objetivo é a estimação dos estados de um determinado alvo (seja este uma aeronave, satélite, míssil ou outro) a partir de medições ruidosas. A maior dificuldade está em desenvolver métodos que sejam capazes de lidar não só com a não-linearidade dos modelos, mas também com as incertezas associadas aos instrumentos de medições e às perturbações existentes no meio envolvente que afetam diretamente o sistema e, na sua maioria, são difíceis de prever e computar. Uma das estratégias mais utilizadas para garantir o ajuste dinâmico e ótimo dos métodos de filtragem face a todas estas adversidades é a implementação de algoritmos adaptativos. Assim sendo, a abordagem mais utilizada para lidar com esta problemática é a filtragem de Kalman. O seu sucesso, principalmente na área de engenharia, deve-se na sua maioria ao filtro de Kalman estendido (EKF – Extended Kalman Filter). Este assenta no pressuposto de que a linearização é suficiente para representar localmente a não-linearidade do sistema e, por conseguinte, o algoritmo utiliza o modelo linearizad0 em substituição ao modelo original não-linear. A linearização é um processo relativamente fácil de compreender e aplicar, o que justifica a popularidade do filtro. Contudo, ao lidar com sistemas altamente não-lineares, o EKF tende a apresentar algumas limitações, tais como, estimativas erráticas, comportamentos instáveis e por vezes até divergentes. De forma a colmatar algumas destas limitações, esta tese apresenta um filtro de Kalman estendido melhorado e adaptativo, denominado por improved Extended Kalman Filter (iEKF), onde para além da adaptabilidade clássica das matrizes de ruído, é proposto uso da norma de Frobenius como fator de correção da estimativa da covariância a priori e é também proposto um novo ponto de linearização. Desta forma, o iEKF adapta as matrizes de transição dos modelos através do novo ponto de linearização e adapta as informações estatísticas através da matriz de covariância proposta. A principal intenção é manter a simplicidade e estrutura pelo qual o EKF é conhecido, porém melhorar o seu desempenho e precisão com conceitos simples, eficazes e adaptativos. Um outro foco desta tese é analisar o desempenho da filtragem no seguimento radar. Assim sendo, tanto o EKF como o iEKF foram implementados e analisados em quatro aplicações deste âmbito, sendo estas: a estimação de uma órbita de um satélite artificial, a estimação de uma transferência orbital (transferência de Hohmann), a estimação de uma reentrada na atmosfera, e por fim, a estimação da trajetória de uma aeronave comercial, em que objetivo é estimar a posição e velocidade do veículo. Tanto o EKF como o iEKF foram analisados e comparados com base no RMSE (Root Mean Square Error). Os resultados demonstram que o iEKF fornece estimativas superiores. O algoritmo é, em geral, mais preciso, estável e confiável, demonstrando ser uma alternativa conveniente ao clássico EKF. Em suma, esta tese propõe um novo método de filtragem não-linear adaptativo, denominado por iEKF. Os resultados indicam que este deve ser tido em consideração para a estimação de estados não-linear tanto para o seguimento radar, como para qualquer outra área que necessidade de um algoritmo de filtragem eficiente.Nonlinear filtering is an important and complex topic in engineering, especially when applied to real-time applications with a highly nonlinear environment. This scenario involves most aerospace applications, such as surveillance, guidance, navigation, attitude control, collision warning and target tracking, where the main objective consists of estimating the states of a moving target (aircraft, satellite, missile, spacecraft, etc.) based on noisy measurements. The challenge is to develop methods that are capable to cope, not only with the nonlinearities of the models but also with the instrumental inaccuracies related to the data acquisition system and the environmental perturbations that are unwanted and, in most cases, difficult to compute. One of the promising strategies to dynamically adjust and guarantee filter optimality is the computation of adaptative algorithms. A very well-known framework to deal with those problems is the Kalman filter algorithms, whose success in engineering applications is mostly due to the Extended Kalman Filter (EKF). The EKF is based on the assumption that a local linearization of the system may be a sufficient description of nonlinearities, therefore the linearized model is used instead of the original nonlinear function. Such approximations are easy to understand and apply, which explains the popularity of the filter. However, when dealing with highly nonlinear systems, the EKF estimates suffer serious problems, such as unstable and quickly divergent behaviours and/or erratic estimates. To address those limitations, this thesis proposes an improved Extended Kalman filter (iEKF) with an adaptative structure, where a new Jacobian matrix expansion point is proposed, and a Frobenius norm of the covariance matrix is suggested as a correction factor for the a priori estimates. Therefore, the iEKF does not only update the statistical information based on the proposed covariance matrix but also updates the state and measurements transitions matrices based on the new Jacobian expansion point. The core idea is to maintain the EKF structure and simplicity but improve the overall performance with simple yet effective concepts. Another objective of this thesis was to evaluate the performance of the filtering methods on radar tracking applications. Thus, the effectiveness of EKF and iEKF were analysed and compared in four radar tracking applications: an artificial satellite orbit estimation, a Hohmann orbit transfer, an atmospheric reentry estimation, and a commercial aircraft trajectory estimation, where the position and velocity of the aerospace vehicle were computed. The EKF and iEKF were compared based on the RMSE (Root Mean Square Error). Simulations results suggest that the iEKF provides a considerably higher accuracy on the overall results. The algorithm is more precise, stable, and reliable, which make it an attractive alternative to the classic EKF. In summary, this thesis proposed an improved Extended Kalman Filter with an adaptative structure. This algorithm is a promising method for nonlinear state estimation, not only for radar tracking applications but any applications that require an efficient nonlinear filter

Enhancing phosphorus availability in some phosphate fixing soils of the Transkei region, South Africa using goat manure

Low availability of soil phosphorus (P) caused by strong sorption of P is a major constraint to agricultural production in most South African soils, particularly those from the high rainfall areas. The aim of this study was therefore to investigate whether combined addition of goat manure with inorganic P fertilizers could enhance P availability in some P fixing soils of the Transkei region, South Africa. The study addressed the following specific objectives (i) to assess P sorption capacities and requirements of selected soils and their relationship with selected soil properties and single point sorption test, (ii) to assess the effects of goat manure and lime addition on P sorption properties of selected P fixing soils (iii) to assess the temporal changes in concentration of inorganic and microbial biomass P fractions following application of inorganic fertilizer P with goat manure in a laboratory incubation experiment, and, (iv) to assess the effects of goat manure application with inorganic phosphate on inorganic and microbial biomass P fractions, P uptake and dry matter yield of maize. Sorption maxima (Smax) of seven soils examined ranged from 192.3 to 909.1 (mg P kg-1) and were highly and positively correlated with sorption affinity constant (r = 0.93, p = 0.01) and organic C (r = 0.71, p = 0.01). The amount of P required for maintaining a soil solution concentration of 0.2 mg P l-1 ranged from 2.1 to 123.5 mg P kg-1 soil. Soils collected from Qweqwe (a Cambisol), Qunu (an Acrisol), Ncihane (a Luvisol) and Bethania (a Ferralsol) had lower external P requirement values and were classified as lower sorbers, whereas soils from Ntlonyana (a Planosol), Chevy Chase (a Ferralsol) and Flagstaff (a Ferralsol) were classified as moderate sorbers. The results suggested that P availability could be compromised in 43 percent iii of the soils studied and that measures to mitigate the adverse effects of P sorption were needed to ensure that P is not a limiting factor to crop production, where such soils are found. Goat manure addition at varying rates (5, 10 and 20 tha-1 dry weight basis) to two of the moderately P fixing soils from Chevy Chase and Flagstaff, reduced P sorption maxima (Smax) compared to the control treatment. Phosphate sorption decreased with increasing amounts of goat manure in both soils but the extent of reduction was greater on Chevy Chase soil than on Flagstaff soil. The relative liming effects of the different rates of goat manure followed the order 20 t GM ha-1 > 10 t GM ha-1 > 5 t GM ha-1. In a separate experiment, addition of inorganic P at varying rates (0, 90, 180, and 360 kg P ha-1) to Flagstaff soil increased labile P fractions (resin P, biomass P and NaHCO3-Pi) and the increases were greater when goat manure was co-applied. The control treatments contained only 17.2 and 27.5 mg P kg-1 of resin extractable P in the un-amended and manure amended treatments, respectively which increased to 118.2 and 122.7 mg P kg-1 on day 28 of incubation. Biomass P concentration was increased from 16.8 to 43.9 mg P kg-1 in P alone treatments but the fraction was greatly enhanced with manure addition, increasing it from 32.6 to 97.7 mg P kg-1. NaOH-Pi was the largest extractable Pi fraction and ranged from 144.3 to 250.6 mg P kg-1 and 107.5 to 213.2 mg P kg-1 in the unamended and manure amended treatments, respectively. Dry matter yield and P uptake by maize grown in the glasshouse were highly and significantly (p = 0.05) correlated with the different P fractions in the soil. The correlations followed the order resin P (r = 0.85) > NaOH-Pi (r = 0.85) > NaHCO3-Pi (r = 0.84) >> biomass P (r = 0.56) for dry matter yield at 6 weeks after planting. At 12 weeks after planting, goat manure had iv highly significant effects on resin P and biomass P but had no effect on NaHCO3-Pi and NaOH–Pi. The combination of biomass P, resin P and NaHCO3-Pi explained 75.8 percent of the variation in dry matter yield of which 63.0 percent of the variation was explained by biomass P alone. The greatest increase in biomass P occurred when added P was co-applied with 5 or 10 tha-1 goat manure. The predictive equation for maize dry matter yield (DM) was: DM (g) = 1.897 biomass P + 0.645 resin P (r = 0.73). Resin P was the fraction that was most depleted due to plant uptake and decreased by 56 to 68 percent between the 6th week and the 12th week of sampling indicating that it played a greater role in supplying plant available P. The results therefore suggested that the use of goat manure may allow resource poor farmers to use lower levels of commercial phosphate fertilizers because of its effect to reduce soil P sorption. In addition, higher increases in biomass P due to manure addition observed at lower rates of added P indicated that goat manure has potential for enhancing bioavailability and fertilizer use efficiency of small inorganic P applications

The Economics of Desertification, Land Degradation, and Drought; Toward an Integrated Global Assessment

Land degradation has not been comprehensively addressed at the global level or in developing countries. A suitable economic framework that could guide investments and institutional action is lacking. This study aims to overcome this deficiency and to provide a framework for a global assessment based on a consideration of the costs of action versus inaction regarding desertification, land degradation, and drought (DLDD). Most of the studies on the costs of land degradation (mainly limited to soil erosion) give cost estimates of less than 1 percent up to about 10 percent of the agricultural gross domestic product (GDP) for various countries worldwide. But the indirect costs of DLDD on the economy (national income), as well as their socioeconomic consequences (particularly poverty impacts), must be accounted for, too. Despite the numerous challenges, a global assessment of the costs of action and inaction against DLDD is possible, urgent, and necessary. This study provides a framework for such a global assessment and provides insights from some related country studies.Agricultural Finance, Crop Production/Industries, Environmental Economics and Policy, Land Economics/Use, Resource /Energy Economics and Policy,

The economics of desertification, land degradation, and drought: Toward an integrated global assessment

cost of inaction, desertification, drought, Economics, Land degradation, prevention of land degradation,

Re-examining and re-conceptualising enterprise search and discovery capability: towards a model for the factors and generative mechanisms for search task outcomes.

Many organizations are trying to re-create the Google experience, to find and exploit their own corporate information. However, there is evidence that finding information in the workplace using search engine technology has remained difficult, with socio-technical elements largely neglected in the literature. Explication of the factors and generative mechanisms (ultimate causes) to effective search task outcomes (user satisfaction, search task performance and serendipitous encountering) may provide a first step in making improvements. A transdisciplinary (holistic) lens was applied to Enterprise Search and Discovery capability, combining critical realism and activity theory with complexity theories to one of the worlds largest corporations. Data collection included an in-situ exploratory search experiment with 26 participants, focus groups with 53 participants and interviews with 87 business professionals. Thousands of user feedback comments and search transactions were analysed. Transferability of findings was assessed through interviews with eight industry informants and ten organizations from a range of industries. A wide range of informational needs were identified for search filters, including a need to be intrigued. Search term word co-occurrence algorithms facilitated serendipity to a greater extent than existing methods deployed in the organization surveyed. No association was found between user satisfaction (or self assessed search expertise) with search task performance and overall performance was poor, although most participants had been satisfied with their performance. Eighteen factors were identified that influence search task outcomes ranging from user and task factors, informational and technological artefacts, through to a wide range of organizational norms. Modality Theory (Cybersearch culture, Simplicity and Loss Aversion bias) was developed to explain the study observations. This proposes that at all organizational levels there are tendencies for reductionist (unimodal) mind-sets towards search capability leading to fixes that fail. The factors and mechanisms were identified in other industry organizations suggesting some theory generalizability. This is the first socio-technical analysis of Enterprise Search and Discovery capability. The findings challenge existing orthodoxy, such as the criticality of search literacy (agency) which has been neglected in the practitioner literature in favour of structure. The resulting multifactorial causal model and strategic framework for improvement present opportunities to update existing academic models in the IR, LIS and IS literature, such as the DeLone and McLean model for information system success. There are encouraging signs that Modality Theory may enable a reconfiguration of organizational mind-sets that could transform search task outcomes and ultimately business performance

Discrete Event Simulations

Considered by many authors as a technique for modelling stochastic, dynamic and discretely evolving systems, this technique has gained widespread acceptance among the practitioners who want to represent and improve complex systems. Since DES is a technique applied in incredibly different areas, this book reflects many different points of view about DES, thus, all authors describe how it is understood and applied within their context of work, providing an extensive understanding of what DES is. It can be said that the name of the book itself reflects the plurality that these points of view represent. The book embraces a number of topics covering theory, methods and applications to a wide range of sectors and problem areas that have been categorised into five groups. As well as the previously explained variety of points of view concerning DES, there is one additional thing to remark about this book: its richness when talking about actual data or actual data based analysis. When most academic areas are lacking application cases, roughly the half part of the chapters included in this book deal with actual problems or at least are based on actual data. Thus, the editor firmly believes that this book will be interesting for both beginners and practitioners in the area of DES