Do Rendimento Mínimo Garantido ao Rendimento Social de Inserção

A presente dissertação de mestrado tem como finalidade primordial mapear a intervenção técnica com base processual, junto de uma família beneficiária de rendimento social de inserção. Mais especificamente aferir as problemáticas e vulnerabilidades da família ao longo do acompanhamento, confrontando com a avaliação diagnóstica e a elaboração de todo o acompanhamento. A investigação segue uma metodologia de estudo de caso com análise documental de um processo acompanhado há 18 anos, cruzando as evidências da intervenção aferindo avaliação diagnostica, a conceção do plano de intervenção e respetivo processo de monitorização, acompanhamento e avaliação. O presente estudo apresenta a necessidade de estruturação de instrumentos de monitorização de todo acompanhamento e uma reflexão sobre as implicações da medida relativamente ao comportamento das famílias beneficiária.

Development and use of risk adjusted statistical process control tools for the monitoring and improvement of clinical outcomes in interventional cardiology

This thesis explored the development of statistical methods to support the monitoring and improvement in quality of treatment delivered to patients undergoing coronary angioplasty procedures. To achieve this goal, a suite of outcome measures was identified to characterise performance of the service, statistical tools were developed to monitor the various indicators and measures to strengthen governance processes were implemented and validated. Although this work focused on pursuit of these aims in the context of a an angioplasty service located at a single clinical site, development of the tools and techniques was undertaken mindful of the potential application to other clinical specialties and a wider, potentially national, scope.

Autonomous vehicle path planning for persistence monitoring under uncertainty using Gaussian based Markov decision process

One of the main challenges facing online and offline path planners is the uncertainty in the magnitude and direction of the environmental energy because it is dynamic, changeable with time, and hard to forecast. This thesis develops an artificial intelligence for a mobile robot to learn from historical or forecasted data of environmental energy available in the area of interest which will help for a persistence monitoring under uncertainty using the developed algorithm.

Fiber Bragg Grating Sensors for Real Time Monitoring of Evacuation Process

Fiber bragg grating (FBG) sensors have been widely used for number of sensing applications like temperature, pressure, acousto-ultrasonic, static and dynamic strain, refractive index change measurements and so on. Present work demonstrates the use of FBG sensors in in-situ measurement of vacuum process with simultaneous leak detection capability. Experiments were conducted in a bell jar vacuum chamber facilitated with conventional Pirani gauge for vacuum measurement. Three different experiments have been conducted to validate the performance of FBG sensor in monitoring vacuum creating process and air bleeding. The preliminary results of FBG sensors in vacuum monitoring have been compared with that of commercial Pirani gauge sensor. This novel technique offers a simple alternative to conventional method for real time monitoring of evacuation process. Proposed FBG based vacuum sensor has potential applications in vacuum systems involving hazardous environment such as chemical and gas plants, automobile industries, aeronautical establishments and leak monitoring in process industries, where the electrical or MEMS based sensors are prone to explosion and corrosion.

Solid state electrochemical sensor for monitoring Mg in Al refining process

Novel solid-state electrochemical sensors have been designed using the Mg2+ cation conductors incorporating novel solid-state reference electrodes for in-line monitoring of Mg in molten Al during the refining process and also for in-line monitoring of Mg content in molten Al in the alloying process. In this paper we report the preparation of Mg2+ ion conductors, MgAl2O4 and MgZr4(PO4)6, by the solid state ceramic synthesis route, measurement of their electrical properties using ac-impedance spectroscopy and application of the above cation conductors for designing novel electrochemical sensors for monitoring Mg dissolved in molten Al. The activation energy for Mg2+ ion conduction in MgAl2O4 is 2.08 eV and in MgZr4(PO4)6 is 1.7 eV, respectively. The sensors have been found to respond rapidly to change in Mg content in molten aluminium around 1000 K.

Monitoring A Micromechanical Process In Macroscale Carbon Nanotube Films And Fibers

The evaluation of mechanical properties of carbon nanotube (CNT) fibers is inherently difficult. Here, Raman scattering-a generic methodology independent of mechanical measurements-is used to determine the interbundle strength and microscopic failure process for various CNT macroarchitectures. Raman data are used to predict the moduli of CNT films and fibers, and to illustrate the influences of the twisting geometries on the fibers' mechanical performances.

Wind-driven desertification: process modeling, remote monitoring, and forecasting

Arid and semiarid landscapes comprise nearly a third of the Earth's total land surface. These areas are coming under increasing land use pressures. Despite their low productivity these lands are not barren. Rather, they consist of fragile ecosystems vulnerable to anthropogenic disturbance.

The purpose of this thesis is threefold: (I) to develop and test a process model of wind-driven desertification, (II) to evaluate next-generation process-relevant remote monitoring strategies for use in arid and semiarid regions, and (III) to identify elements for effective management of the world's drylands.

In developing the process model of wind-driven desertification in arid and semiarid lands, field, remote sensing, and modeling observations from a degraded Mojave Desert shrubland are used. This model focuses on aeolian removal and transport of dust, sand, and litter as the primary mechanisms of degradation: killing plants by burial and abrasion, interrupting natural processes of nutrient accumulation, and allowing the loss of soil resources by abiotic transport. This model is tested in field sampling experiments at two sites and is extended by Fourier Transform and geostatistical analysis of high-resolution imagery from one site.

Next, the use of hyperspectral remote sensing data is evaluated as a substantive input to dryland remote monitoring strategies. In particular, the efficacy of spectral mixture analysis (SMA) in discriminating vegetation and soil types and detennining vegetation cover is investigated. The results indicate that hyperspectral data may be less useful than often thought in determining vegetation parameters. Its usefulness in determining soil parameters, however, may be leveraged by developing simple multispectral classification tools that can be used to monitor desertification.

Finally, the elements required for effective monitoring and management of arid and semiarid lands are discussed. Several large-scale multi-site field experiments are proposed to clarify the role of wind as a landscape and degradation process in dry lands. The role of remote sensing in monitoring the world's drylands is discussed in terms of optimal remote sensing platform characteristics and surface phenomena which may be monitored in order to identify areas at risk of desertification. A desertification indicator is proposed that unifies consideration of environmental and human variables.

Rapid automated in-situ monitoring of total dissolved iron and total dissolved manganese in underground water by reverse-flow injection with chemiluminescence detection during the process of water treatment

Measurement of iron and manganese is very important in evaluating the quality of natural waters. We have constructed an automated Fe(II), total dissolved iron(TDI), Mn(II), and total dissolved manganese(TDM) analysis system for the quality control of underground drinking water by reverse flow injection analysis and chemiluminescence detection(rFIA-CL), The method is based on the measurement of the metal-catalyzed light emission from luminol oxidation by potassium periodate. The typical signal is a narrow peak, in which the height is proportional to light emitted and hence to the concentration of metal ions. The detection limits were 3 x 10(-6) mu g ml(-1) for Fe(II) and the linear range extents up to 1.0 x 10(-4) and 5 x 10(-6) mu g ml(-1) for Mn(II) cover a linear range to 1.0 x 10(-4) mu g ml(-1). This method was used for automated in-situ monitoring of total dissolved iron and total dissolved in underground water during water treatment. (C) 1997 Elsevier Science B.V.

Plug Force Monitoring for the Control and Optimisation of the Thermoforming Process

Thermoforming processes generally employ sheet temperature monitoring as the primary means of process control. In this paper the development of an alternative system that monitors plug force is described. Tests using a prototype device have shown that the force record over a forming cycle creates a unique map of the process operation. Key process features such as the sheet modulus, sheet sag and the timing of the process stages may be readily observed, and the effects of changes in all of the major processing parameters are easily distinguished. Continuous, cycle-to-cycle tests show that the output is consistent and repeatable over a longer time frame, providing the opportunity for development of an on-line process control system. Further testing of the system is proposed.