909 resultados para Micro total analysis system
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Micro-mechanical analysis of polymeric composites provides a powerful means for the quantitative assessment of their bulk behavior. In this paper we describe a robust finite element model (FEM) for the micro-structural modeling of the behavior of particulate filled polymer composites under external loads. The developed model is applied to simulate stress distribution in polymer composites containing particulate fillers. Quantitative information about the magnitude and location of maximum stress concentrations obtained from these simulations is used to predict the dominant failure and crack growth mechanisms in these composites. The model predictions are compared with the available experimental data and also with the values found using other methods reported in the literature. These comparisons show the range of the validity of the developed model and its predictive potential.
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Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case.
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AIMS: To assess quantitatively variations in the extent of capillary basement membrane (BM) thickening between different retinal layers and within arterial and venous environments during diabetes.
METHODS: One year after induction of experimental (streptozotocin) diabetes in rats, six diabetic animals together with six age-matched control animals were sacrificed and the retinas fixed for transmission electron microscopy (TEM). Blocks of retina straddling the major arteries and veins in the central retinal were dissected out, embedded in resin, and sectioned. Capillaries in close proximity to arteries or veins were designated as residing in either an arterial (AE) or a venous (VE) environment respectively, and the retinal layer in which each capillary was located was also noted. The thickness of the BM was then measured on an image analyser based two dimensional morphometric analysis system.
RESULTS: In both diabetics and controls the AE capillaries had consistently thicker BMs than the VE capillaries. The BMs of both AE and VE capillaries from diabetics were thicker than those of capillaries in the corresponding retinal layer from the normal rats (p < or = 0.005). Also, in normal AE and VE capillaries and diabetic AE capillaries the BM in the nerve fibre layer (NFL) was thicker than that in either the inner (IPL) or outer (OPL) plexiform layers (p < or = 0.001). However, in diabetic VE capillaries the BMs of capillaries in the NFL were thicker than those of capillaries in the IPL (p < or = 0.05) which, in turn, had thicker BMs than capillaries in the OPL (p < or = 0.005).
CONCLUSIONS: The variation in the extent of capillary BM thickening between different retinal layers within AE and VE environments may be related to differences in levels of oxygen tension and oxidative stress in the retina around arteries compared with that around veins.
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Thesis (Ph.D.)--University of Washington, 2015
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Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes
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Hard real- time multiprocessor scheduling has seen, in recent years, the flourishing of semi-partitioned scheduling algorithms. This category of scheduling schemes combines elements of partitioned and global scheduling for the purposes of achieving efficient utilization of the system’s processing resources with strong schedulability guarantees and with low dispatching overheads. The sub-class of slot-based “task-splitting” scheduling algorithms, in particular, offers very good trade-offs between schedulability guarantees (in the form of high utilization bounds) and the number of preemptions/migrations involved. However, so far there did not exist unified scheduling theory for such algorithms; each one was formulated in its own accompanying analysis. This article changes this fragmented landscape by formulating a more unified schedulability theory covering the two state-of-the-art slot-based semi-partitioned algorithms, S-EKG and NPS-F (both fixed job-priority based). This new theory is based on exact schedulability tests, thus also overcoming many sources of pessimism in existing analysis. In turn, since schedulability testing guides the task assignment under the schemes in consideration, we also formulate an improved task assignment procedure. As the other main contribution of this article, and as a response to the fact that many unrealistic assumptions, present in the original theory, tend to undermine the theoretical potential of such scheduling schemes, we identified and modelled into the new analysis all overheads incurred by the algorithms in consideration. The outcome is a new overhead-aware schedulability analysis that permits increased efficiency and reliability. The merits of this new theory are evaluated by an extensive set of experiments.
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A method using L-cysteine for the determination of arsenous acid (As(III)), arsenic acid (As(V)), monomethylarsonic acid (MMAA), and dimethylarsinic acid (DMAA) by hydride generation was demonstrated. The instrument used was a d.c. plasma atomic emission spectrometer (OCP-AES). Complete recovery was reported for As(III), As(V), and DMAA while 86% recovery was reported for MMAA. Detection limits were determined, as arsenic for the species listed previously, to be 1.2, 0.8, 1.1, and 1.0 ngemL-l, respectively. Precision values, at 50 ngemL-1 arsenic concentration, were f.80/0, 2.50/0, 2.6% and 2.6% relative standard deviation, respectively. The L-cysteine reagent was compared directly with the conventional hydride generation technique which uses a potassium iodide-hydrochloric acid medium. Recoveries using L-cysteine when compared with the conventional method provided the following results: similar recoveries were obtained for As(III), slightly better recoveries were obtained for As(V) and MMAA, and significantly better recoveries for DMAA. In addition, tall and sharp peak shapes were observed for all four species when using L-cysteine. The arsenic speciation method involved separation by ion exchange .. high perfonnance liquid chromatography (HPLC) with on-line hydride generation using the L.. cysteine reagent and measurement byOCP-AES. Total analysis time per sample was 12 min while the time between the start of subsequent runs was approximately 20 min. A binary . gradient elution program, which incorporated the following two eluents: 0.01 and 0.5 mM tri.. sodium citrate both containing 5% methanol (v/v) and both at a pH of approximately 9, was used during the separation by HPLC. Recoveries of the four species which were measured as peak area, and were normalized against As(III), were 880/0, 290/0, and 40% for DMAA, MMAA and As(V), respectively. Resolution factors between adjacent analyte peaks of As(III) and DMAA was 1.1; DMAA and MMAA was 1.3; and MMAA and As(V) was 8.6. During the arsenic speciation study, signals from the d.c. plasma optical system were measured using a new photon-signal integrating device. The_new photon integrator developed and built in this laboratory was based on a previously published design which was further modified to reflect current available hardware. This photon integrator was interfaced to a personal computer through an AID convertor. The .photon integrator has adjustable threshold settings and an adjustable post-gain device.
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Please consult the paper edition of this thesis to read. It is available on the 5th Floor of the Library at Call Number: Z 9999 E38 D56 1992
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Deux thématiques importantes des technologies de la santé: la pratique médicale fondée sur des preuves probantes et l’évaluation des interventions en médecine sont fondées sur une approche positiviste et une conception mécaniste des organisations en santé. Dans ce mémoire, nous soulevons l’hypothèse selon laquelle les théories de la complexité et la systémique permettent une conceptualisation différente de ces deux aspects de la gouvernance clinique d’une unité de Soins Intensifs Chirurgicaux (SIC), qui est considérée comme un système adaptatif dynamique non linéaire qui nécessite une approche systémique de la cognition. L’étude de cas d’une unité de SIC, permet de démontrer par de nombreux exemples et des analyses de micro-situations, toutes les caractéristiques de la complexité des patients critiques et instables et de la structure organisationnelle des SIC. Après une critique épistémologique de l’Evidence-Based Medicine nous proposons une pratique fondée sur des raisonnements cliniques alliant l’abduction, l’herméneutique et la systémique aux SIC. En nous inspirant des travaux de Karl Weick, nous suggérons aussi de repenser l’évaluation des modes d’interventions cliniques en s’inspirant de la notion d’organisation de haute fiabilité pour mettre en place les conditions nécessaires à l’amélioration des pratiques aux SIC.
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L’analyse de la marche a émergé comme l’un des domaines médicaux le plus im- portants récemment. Les systèmes à base de marqueurs sont les méthodes les plus fa- vorisées par l’évaluation du mouvement humain et l’analyse de la marche, cependant, ces systèmes nécessitent des équipements et de l’expertise spécifiques et sont lourds, coûteux et difficiles à utiliser. De nombreuses approches récentes basées sur la vision par ordinateur ont été développées pour réduire le coût des systèmes de capture de mou- vement tout en assurant un résultat de haute précision. Dans cette thèse, nous présentons notre nouveau système d’analyse de la démarche à faible coût, qui est composé de deux caméras vidéo monoculaire placées sur le côté gauche et droit d’un tapis roulant. Chaque modèle 2D de la moitié du squelette humain est reconstruit à partir de chaque vue sur la base de la segmentation dynamique de la couleur, l’analyse de la marche est alors effectuée sur ces deux modèles. La validation avec l’état de l’art basée sur la vision du système de capture de mouvement (en utilisant le Microsoft Kinect) et la réalité du ter- rain (avec des marqueurs) a été faite pour démontrer la robustesse et l’efficacité de notre système. L’erreur moyenne de l’estimation du modèle de squelette humain par rapport à la réalité du terrain entre notre méthode vs Kinect est très prometteur: les joints des angles de cuisses (6,29◦ contre 9,68◦), jambes (7,68◦ contre 11,47◦), pieds (6,14◦ contre 13,63◦), la longueur de la foulée (6.14cm rapport de 13.63cm) sont meilleurs et plus stables que ceux de la Kinect, alors que le système peut maintenir une précision assez proche de la Kinect pour les bras (7,29◦ contre 6,12◦), les bras inférieurs (8,33◦ contre 8,04◦), et le torse (8,69◦contre 6,47◦). Basé sur le modèle de squelette obtenu par chaque méthode, nous avons réalisé une étude de symétrie sur différentes articulations (coude, genou et cheville) en utilisant chaque méthode sur trois sujets différents pour voir quelle méthode permet de distinguer plus efficacement la caractéristique symétrie / asymétrie de la marche. Dans notre test, notre système a un angle de genou au maximum de 8,97◦ et 13,86◦ pour des promenades normale et asymétrique respectivement, tandis que la Kinect a donné 10,58◦et 11,94◦. Par rapport à la réalité de terrain, 7,64◦et 14,34◦, notre système a montré une plus grande précision et pouvoir discriminant entre les deux cas.
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Problématique. L'utilisation d'un chien d'assistance à la mobilité (CAM) représente une option novatrice pour préserver l’intégrité des membres supérieurs (MSs) chez les utilisateurs de fauteuil roulant manuel (FRM). Aucune étude biomécanique n’a quantifié les effets du CAM sur les efforts aux MSs lors de la montée d’un plan incliné. Objectif. Cette étude quasi-expérimentale vise à comparer les efforts aux MSs lors de la montée d’un plan incliné avec et sans l’assistance d’un CAM. Méthodologie. Dix participants avec une lésion de la moelle épinière (LME) qui utilisent un FRM et possèdent un CAM ont monté un plan incliné à trois reprises avec et sans l’assistance du CAM. Les forces appliquées sur les cerceaux, mesurées avec des roues instrumentées, et les mouvements du FRM et des MSs, enregistrés avec un système d'analyse du mouvement, ont permis de mesurer les efforts mécaniques aux MSs. Simultanément, l'activité électromyographique (EMG) des muscles grand pectoral, deltoïde antérieur, biceps et triceps a été enregistrée et normalisée avec sa valeur maximale pour mesurer les efforts musculaires aux MSs. Résultats. En général, le CAM réduit significativement les valeurs moyennes et maximales de la force totale appliquée aux cerceaux et de sa composante tangentielle, des moments nets de flexion, de rotation interne et d’adduction aux épaules et des taux d’utilisation musculaire du deltoïde antérieur, du biceps et du triceps. Conclusion. L’assistance d’un CAM réduit les efforts aux MSs lors de la montée d’un plan incliné chez les utilisateurs d’un FRM ayant une LME.
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In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.
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Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries
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Die laserinduzierte Plasmaspektroskopie (LIPS) ist eine spektrochemische Elementanalyse zur Bestimmung der atomaren Zusammensetzung einer beliebigen Probe. Für die Analyse ist keine spezielle Probenpräparation nötig und kann unter atmosphärischen Bedingungen an Proben in jedem Aggregatzustand durchgeführt werden. Femtosekunden Laserpulse bieten die Vorteile einer präzisen Ablation mit geringem thermischen Schaden sowie einer hohen Reproduzierbarkeit. Damit ist fs-LIPS ein vielversprechendes Werkzeug für die Mikroanalyse technischer Proben, insbesondere zur Untersuchung ihres Ermüdungsverhaltens. Dabei ist interessant, wie sich die initiierten Mikrorisse innerhalb der materialspezifschen Struktur ausbreiten. In der vorliegenden Arbeit sollte daher ein schnelles und einfach zu handhabendes 3D-Rasterabbildungsverfahren zur Untersuchung der Rissausbreitung in TiAl, einer neuen Legierungsklasse, entwickelt werden. Dazu wurde fs-LIPS (30 fs, 785 nm) mit einem modifizierten Mikroskopaufbau (Objektiv: 50x/NA 0.5) kombiniert, welcher eine präzise, automatisierte Probenpositionierung ermöglicht. Spektrochemische Sensitivität und räumliches Auflösungsvermögen wurden in energieabhängigen Einzel- und Multipulsexperimenten untersucht. 10 Laserpulse pro Position mit einer Pulsenergie von je 100 nJ führten in TiAl zum bestmöglichen Kompromiss aus hohem S/N-Verhältnis von 10:1 und kleinen Lochstrukturen mit inneren Durchmessern von 1.4 µm. Die für das Verfahren entscheidende laterale Auflösung, dem minimalen Lochabstand bei konstantem LIPS-Signal, beträgt mit den obigen Parametern 2 µm und ist die bislang höchste bekannte Auflösung einer auf fs-LIPS basierenden Mikro-/Mapping-Analyse im Fernfeld. Fs-LIPS Scans von Teststrukturen sowie Mikrorissen in TiAl demonstrieren eine spektrochemische Sensitivität von 3 %. Scans in Tiefenrichtung erzielen mit denselben Parametern eine axiale Auflösung von 1 µm. Um die spektrochemische Sensitivität von fs-LIPS zu erhöhen und ein besseres Verständnis für die physikalischen Prozesse während der Laserablation zu erhalten, wurde in Pump-Probe-Experimenten untersucht, in wieweit fs-Doppelpulse den laserinduzierten Abtrag sowie die Plasmaemission beeinflussen. Dazu wurden in einem Mach-Zehnder-Interferometer Pulsabstände von 100 fs bis 2 ns realisiert, Gesamtenergie und Intensitätsverhältnis beider Pulse variiert sowie der Einfluss der Materialparameter untersucht. Sowohl das LIPS-Signal als auch die Lochstrukturen zeigen eine Abhängigkeit von der Verzögerungszeit. Diese wurden in vier verschiedene Regimes eingeteilt und den physikalischen Prozessen während der Laserablation zugeordnet: Die Thermalisierung des Elektronensystems für Pulsabstände unter 1 ps, Schmelzprozesse zwischen 1 und 10 ps, der Beginn des Abtrags nach mehreren 10 ps und die Expansion der Plasmawolke nach über 100 ps. Dabei wird das LIPS-Signal effizient verstärkt und bei 800 ps maximal. Die Lochdurchmesser ändern sich als Funktion des Pulsabstands wenig im Vergleich zur Tiefe. Die gesamte Abtragsrate variiert um maximal 50 %, während sich das LIPS-Signal vervielfacht: Für Ti und TiAl typischerweise um das Dreifache, für Al um das 10-fache. Die gemessenen Transienten zeigen eine hohe Reproduzierbarkeit, jedoch kaum eine Energie- bzw. materialspezifische Abhängigkeit. Mit diesen Ergebnissen wurde eine gezielte Optimierung der DP-LIPS-Parameter an Al durchgeführt: Bei einem Pulsabstand von 800 ps und einer Gesamtenergie von 65 nJ (vierfach über der Ablationsschwelle) wurde eine 40-fache Signalerhöhung bei geringerem Rauschen erzielt. Die Lochdurchmesser vergrößerten sich dabei um 44 % auf (650±150) nm, die Lochtiefe um das Doppelte auf (100±15) nm. Damit war es möglich, die spektrochemische Sensitivität von fs-LIPS zu erhöhen und gleichzeitig die hohe räumliche Auflösung aufrecht zu erhalten.
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Under the framework of the European Union Funded SAFEE project(1), this paper gives an overview of a novel monitoring and scene analysis system developed for use onboard aircraft in spatially constrained environments. The techniques discussed herein aim to warn on-board crew about pre-determined indicators of threat intent (such as running or shouting in the cabin), as elicited from industry and security experts. The subject matter experts believe that activities such as these are strong indicators of the beginnings of undesirable chains of events or scenarios, which should not be allowed to develop aboard aircraft. This project aimes to detect these scenarios and provide advice to the crew. These events may involve unruly passengers or be indicative of the precursors to terrorist threats. With a state of the art tracking system using homography intersections of motion images, and probability based Petri nets for scene understanding, the SAFEE behavioural analysis system automatically assesses the output from multiple intelligent sensors, and creates. recommendations that are presented to the crew using an integrated airborn user interface. Evaluation of the system is conducted within a full size aircraft mockup, and experimental results are presented, showing that the SAFEE system is well suited to monitoring people in confined environments, and that meaningful and instructive output regarding human actions can be derived from the sensor network within the cabin.