997 resultados para Adaptive Protection
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The increasing use of ionizing radiation for medical purposes emphasizes the concern about safety and justification of using ionizing radiation. This is linked with the use of new and high-dose X-ray technology (particularly CT). According to the UNSCEAR 2010 Report the total number of diagnostic medical examinations (both medical and dental) is estimated to have risen from 2.4 billion (period 1991–1996) to 3.6 billion (period 1997– 2008) - a marked increase in collective doses. An appropriate use of technology aiming diagnostic or therapy and respecting the ALARA principle is a mandatory requisite to safely perform any radiological procedure. Radiation protection is thus, a concern of all specialists in the radiology field ( radiologists, radiographers, medical physicists, among other professional groups). The importance of education and training of these professionals in reducing patients’ doses while maintaining the desired level of quality in medical exposures, as well as precise therapeutic treatments is well recognized. Education, training and continuing professional development (CPD) constitute a triad pointing towards the radiographers’ development of competences in the radiation protection field. This presentation excludes the radiographer role and competences in the fields of ultrasonography and MRI.
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A method to control the speed or the torque of a permanent-magnet direct current motor is presented. The rotor speed and the external torque estimation are simultaneously provided by appropriate observers. The sensorless control scheme is based on current measurement and switching states of power devices. The observer’s performances are dependent on the accurate machine parameters knowledge. Sliding mode control approach was adopted for drive control, providing the suitable switching states to the chopper power devices. Despite the predictable chattering, a convenient first order switching function was considered enough to define the sliding surface and to correspond with the desired control specifications and drive performance. The experimental implementation was supported on a single dsPIC and the controller includes a logic overcurrent protection.
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In this paper, we present the results of mammography quality control tests related to the work with Portuguese mammography equipment, either in conventional or in digital mammography computed radiography, showing the main differences in the tested equipments. Quality control in mammography is a very special area of quality control in radiology, which demands relatively high knowledge on physics. Digital imaging is changing the standards of the radiographic imaging. Regarding mammography, this is yet a controversial issue owing to some limitations of the digital detectors, like the resolution for instance. A complete set of results regarding radiation protection of the patients submitted to mammography diagnosis is presented. A discussion of the quality image parameters and its interpretation in conventional and digital mammography is presented. In conclusion, we present a sample of results that can be considered as characteristics of mammography equipment in Portugal.
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Tese de Doutoramento, Ciências do Mar (Biologia Marinha)
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Evolution by natural selection is driven by the continuous generation of adaptive mutations. We measured the genomic mutation rate that generates beneficial mutations and their effects on fitness in Escherichia coli under conditions in which the effect of competition between lineages carrying different beneficial mutations is minimized. We found a rate on the order of 10–5 per genome per generation, which is 1000 times as high as previous estimates, and a mean selective advantage of 1%. Such a high rate of adaptive evolution has implications for the evolution of antibiotic resistance and pathogenicity.
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The general transcription factor TFIIB, encoded by SUA7 in Saccharomyces cerevisiae, is required for transcription activation but apparently of a specific subset of genes, for example, linked with mitochondrial activity and hence with oxidative environments. Therefore, studying SUA7/TFIIB as a potential target of oxidative stress is fundamental. We found that controlled SUA7 expression under oxidative conditions occurs at transcriptional and mRNA stability levels. Both regulatory events are associated with the transcription activator Yap1 in distinct ways: Yap1 affects SUA7 transcription up regulation in exponentially growing cells facing oxidative signals; the absence of this activator per se contributes to increase SUA7 mRNA stability. However, unlike SUA7 mRNA, TFIIB abundance is not altered on oxidative signals. The biological impact of this preferential regulation of SUA7 mRNA pool is revealed by the partial suppression of cellular oxidative sensitivity by SUA7 overexpression, and supported by the insights on the existence of a novel RNA-binding factor, acting as an oxidative sensor, which regulates mRNA stability. Taken together the results point out a primarily cellular commitment to guarantee SUA7 mRNA levels under oxidative environments.
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The main objective of an Adaptive System is to adequate its relation with the user (content presentation, navigation, interface, etc.) according to a predefined but updatable model of the user that reflects his objectives, preferences, knowledge and competences [Brusilovsky, 2001], [De Bra, 2004]. For Educational Adaptive Systems, the emphasis is placed on the student knowledge in the domain application and learning style, to allow him to reach the learning objectives proposed for his training [Chepegin, 2004]. In Educational AHS, the User Model (UM), or Student Model, has increased relevance: when the student reaches the objectives of the course, the system must be able to readapt, for example, to his knowledge [Brusilovsky, 2001]. Learning Styles are understood as something that intent to define models of how given person learns. Generally it is understood that each person has a Learning Style different and preferred with the objective of achieving better results. Some case studies have proposed that teachers should assess the learning styles of their students and adapt their classroom and methods to best fit each student's learning style [Kolb, 2005], [Martins, 2008]. The learning process must take into consideration the individual cognitive and emotional parts of the student. In summary each Student is unique so the Student personal progress must be monitored and teaching shoul not be not generalized and repetitive [Jonassen, 1991], [Martins, 2008]. The aim of this paper is to present an Educational Adaptive Hypermedia Tool based on Progressive Assessment.
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This document is a survey in the research area of User Modeling (UM) for the specific field of Adaptive Learning. The aims of this document are: To define what it is a User Model; To present existing and well known User Models; To analyze the existent standards related with UM; To compare existing systems. In the scientific area of User Modeling (UM), numerous research and developed systems already seem to promise good results, but some experimentation and implementation are still necessary to conclude about the utility of the UM. That is, the experimentation and implementation of these systems are still very scarce to determine the utility of some of the referred applications. At present, the Student Modeling research goes in the direction to make possible reuse a student model in different systems. The standards are more and more relevant for this effect, allowing systems communicate and to share data, components and structures, at syntax and semantic level, even if most of them still only allow syntax integration.
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Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.
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An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.
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Real-time embedded applications require to process large amounts of data within small time windows. Parallelize and distribute workloads adaptively is suitable solution for computational demanding applications. The purpose of the Parallel Real-Time Framework for distributed adaptive embedded systems is to guarantee local and distributed processing of real-time applications. This work identifies some promising research directions for parallel/distributed real-time embedded applications.
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Smartphones and other internet enabled devices are now common on our everyday life, thus unsurprisingly a current trend is to adapt desktop PC applications to execute on them. However, since most of these applications have quality of service (QoS) requirements, their execution on resource-constrained mobile devices presents several challenges. One solution to support more stringent applications is to offload some of the applications’ services to surrogate devices nearby. Therefore, in this paper, we propose an adaptable offloading mechanism which takes into account the QoS requirements of the application being executed (particularly its real-time requirements), whilst allowing offloading services to several surrogate nodes. We also present how the proposed computing model can be implemented in an Android environment
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Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive (HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive (DA) method in terms of faster and improved tracking and parameter convergence.
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OBJECTIVE To analyze the effectiveness of the Chilean System of Childhood Welfare in transferring benefits to socially vulnerable families. METHODS A cross-sectional study with a sample of 132 families from the Metropolitan Region, Chile, stratified according to degree of social vulnerability, between September 2011 and January 2012. Semi-structured interviews were conducted with mothers of the studied families in public health facilities or their households. The variables studied were family structure, psychosocial risk in the family context and integrated benefits from the welfare system in families that fulfill the necessary requirements for transfer of benefits. Descriptive statistics to measure location and dispersion were calculated. A binary logistic regression, which accounts for the sample size of the study, was carried out. RESULTS The groups were homogenous regarding family size, the presence of biological father in the household, the number of relatives living in the same dwelling, income generation capacity and the rate of dependency and psychosocial risk (p ≥ 0.05). The transfer of benefits was low in all three groups of the sample (≤ 23.0%). The benefit with the best coverage in the system was the Single Family Subsidy, whose transfer was associated with the size of the family, the presence of relatives in the dwelling, the absence of the father in the household, a high rate of dependency and a high income generation capacity (p ≤ 0.10). CONCLUSIONS The effectiveness of benefit transfer was poor, especially in families that were extremely socially vulnerable. Further explanatory studies of benefit transfers to the vulnerable population, of differing intensity and duration, are required in order to reduce health disparities and inequalities.