940 resultados para Distance-based techniques
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This research is funded by UK Medical Research Council grant number MR/L011115/1
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This research is funded by UK Medical Research Council grant number MR/L011115/1. We would like to thank the 105 experts in behaviour change who have committed their time and offered their expertise for study 2 of this research. We are also very grateful to all those who sent us peer-reviewed behaviour change intervention descriptions for study 1. Finally, we would like thank Dr. Emma Beard and Dr. Dan Dediu for their statistical input and to all the researchers, particularly Holly Walton, who have assisted in the coding of papers for study 1.
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The importance of non-destructive techniques (NDT) in structural health monitoring programmes is being critically felt in the recent times. The quality of the measured data, often affected by various environmental conditions can be a guiding factor in terms usefulness and prediction efficiencies of the various detection and monitoring methods used in this regard. Often, a preprocessing of the acquired data in relation to the affecting environmental parameters can improve the information quality and lead towards a significantly more efficient and correct prediction process. The improvement can be directly related to the final decision making policy about a structure or a network of structures and is compatible with general probabilistic frameworks of such assessment and decision making programmes. This paper considers a preprocessing technique employed for an image analysis based structural health monitoring methodology to identify sub-marine pitting corrosion in the presence of variable luminosity, contrast and noise affecting the quality of images. A preprocessing of the gray-level threshold of the various images is observed to bring about a significant improvement in terms of damage detection as compared to an automatically computed gray-level threshold. The case dependent adjustments of the threshold enable to obtain the best possible information from an existing image. The corresponding improvements are observed in a qualitative manner in the present study.
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The use of structural health monitoring of civil structures is ever expanding and by assessing the dynamical condition of structures, informed maintenance management can be conducted at both individual and network levels. With the continued growth of information age technology, the potential arises for smart monitoring systems to be integrated with civil infrastructure to provide efficient information on the condition of a structure. The focus of this thesis is the integration of smart technology with civil infrastructure for the purposes of structural health monitoring. The technology considered in this regard are devices based on energy harvesting materials. While there has been considerable focus on the development and optimisation of such devices using steady state loading conditions, their applications for civil infrastructure are less known. Although research is still in initial stages, studies into the uses associated with such applications are very promising. Through the use of the dynamical response of structures to a variety of loading conditions, the energy harvesting outputs from such devices is established and the potential power output determined. Through a power variance output approach, damage detection of deteriorating structures using the energy harvesting devices is investigated. Further applications of the integration of energy harvesting devices with civil infrastructure investigated by this research includes the use of the power output as a indicator for control. Four approaches are undertaken to determine the potential applications arising from integrating smart technology with civil infrastructure, namely • Theoretical analysis to determine the applications of energy harvesting devices for vibration based health monitoring of civil infrastructure. • Laboratory experimentation to verify the performance of different energy harvesting configurations for civil infrastructure applications. • Scaled model testing as a method to experimentally validate the integration of the energy harvesting devices with civil infrastructure. • Full scale deployment of energy harvesting device with a bridge structure. These four approaches validate the application of energy harvesting technology with civil infrastructure from a theoretical, experimental and practical perspective.
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Quantitative and qualitative analyses of planktonic foraminiferal assemblages from 134 core-top sediment samples collected along the western Iberian margin were used to assess the latitudinal and longitudinal changes in surface water conditions and to calibrate a Sea Surface Temperature (SST) transfer function for this seasonal coastal upwelling region. Q-mode factor analysis performed on relative abundances yielded three factors that explain 96% of the total variance: factor 1 (50%) is exclusively defined by Globigerina bulloides, the most abundant and widespread species, and reflects the modern seasonal (May to September) coastal upwelling areas; factor 2 (32%) is dominated by Neogloboquadrina pachyderma (dextral) and Globorotalia inflata and seems to be associated with the Portugal Current, the descending branch of the North Atlantic Drift; factor 3 (14%) is defined by the tropical-sub-tropical species Globigerinoides ruber (white), Globigerinoides trilobus trilobus, and G. inflata and mirrors the influence of the winter-time eastern branch of the Azores Current. In conjunction with satellite-derived SST for summer and winter seasons integrated over an 18 year period the regional foraminiferal data set is used to calibrate a SST transfer function using Imbrie & Kipp, MAT and SIMMAX(ndw) techniques. Similar predicted errors (RMSEP), correlation coefficients, and residuals' deviation from SST estimated for both techniques were observed for both seasons. All techniques appear to underestimate SST off the southern Iberia margin, an area mainly occupied by warm waters where upwelling occurs only occasionally, and overestimate SST on the northern part of the west coast of the Iberia margin, where cold waters are present nearly all year round. The comparison of these regional calibrations with former Atlantic and North Atlantic calibrations for two cores, one of which is influenced by upwelling, reveals that the regional one attests more robust paleo-SSTs than for the other approaches.
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BACKGROUND: Cardiac rehabilitation (CR) programmes offering secondary prevention for cardiovascular disease (CVD) advise healthy lifestyle behaviours, with the behaviour change techniques (BCTs) of goals and planning, feedback and monitoring, and social support recommended. More information is needed about BCT use in home-based CR to support these programmes in practice.
AIM: To identify and describe the use of BCTs in home-based CR programmes.
DESIGN AND SETTING: Randomised controlled trials of home-based CR between 2005 and 2015 were identified by searching MEDLINE(®), Embase, PsycINFO, Web of Science, and Cochrane Database.
METHOD: Reviewers independently screened titles and abstracts for eligibility. Relevant data, including BCTs, were extracted from included studies. A meta-analysis studied risk factor change in home-based and comparator programmes.
RESULTS: From 2448 studies identified, 11 of good methodological quality (10 on post-myocardial infarction, one on heart failure, 1907 patients) were included. These reported the use of 20 different BCTs. Social support (unspecified) was used in all studies and goal setting (behaviour) in 10. Of the 11 studies, 10 reported effectiveness in reducing CVD risk factors, but one study showed no improvement compared to usual care. This study differed from effective programmes in that it didn't include BCTs that had instructions on how to perform the behaviour and monitoring, or a credible source.
CONCLUSION: Social support and goal setting were frequently used BCTs in home-based CR programmes, with the BCTs related to monitoring, instruction on how to perform the behaviour, and credible source being included in effective programmes. Further robust trials are needed to determine the relative value of different BCTs within CR programmes.
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This papers examines the use of trajectory distance measures and clustering techniques to define normal
and abnormal trajectories in the context of pedestrian tracking in public spaces. In order to detect abnormal
trajectories, what is meant by a normal trajectory in a given scene is firstly defined. Then every trajectory
that deviates from this normality is classified as abnormal. By combining Dynamic Time Warping and a
modified K-Means algorithms for arbitrary-length data series, we have developed an algorithm for trajectory
clustering and abnormality detection. The final system performs with an overall accuracy of 83% and 75%
when tested in two different standard datasets.
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Les systèmes de communication optique avec des formats de modulation avancés sont actuellement l’un des sujets de recherche les plus importants dans le domaine de communication optique. Cette recherche est stimulée par les exigences pour des débits de transmission de donnée plus élevés. Dans cette thèse, on examinera les techniques efficaces pour la modulation avancée avec une détection cohérente, et multiplexage par répartition en fréquence orthogonale (OFDM) et multiples tonalités discrètes (DMT) pour la détection directe et la détection cohérente afin d’améliorer la performance de réseaux optiques. Dans la première partie, nous examinons la rétropropagation avec filtre numérique (DFBP) comme une simple technique d’atténuation de nonlinéarité d’amplificateur optique semiconducteur (SOA) dans le système de détection cohérente. Pour la première fois, nous démontrons expérimentalement l’efficacité de DFBP pour compenser les nonlinéarités générées par SOA dans un système de détection cohérente porteur unique 16-QAM. Nous comparons la performance de DFBP avec la méthode de Runge-Kutta quatrième ordre. Nous examinons la sensibilité de performance de DFBP par rapport à ses paramètres. Par la suite, nous proposons une nouvelle méthode d’estimation de paramètre pour DFBP. Finalement, nous démontrons la transmission de signaux de 16-QAM aux taux de 22 Gbaud sur 80km de fibre optique avec la technique d’estimation de paramètre proposée pour DFBP. Dans la deuxième partie, nous nous concentrons sur les techniques afin d’améliorer la performance des systèmes OFDM optiques en examinent OFDM optiques cohérente (CO-OFDM) ainsi que OFDM optiques détection directe (DDO-OFDM). Premièrement, nous proposons une combinaison de coupure et prédistorsion pour compenser les distorsions nonlinéaires d’émetteur de CO-OFDM. Nous utilisons une interpolation linéaire par morceaux (PLI) pour charactériser la nonlinéarité d’émetteur. Dans l’émetteur nous utilisons l’inverse de l’estimation de PLI pour compenser les nonlinéarités induites à l’émetteur de CO-OFDM. Deuxièmement, nous concevons des constellations irrégulières optimisées pour les systèmes DDO-OFDM courte distance en considérant deux modèles de bruit de canal. Nous démontrons expérimentalement 100Gb/s+ OFDM/DMT avec la détection directe en utilisant les constellations QAM optimisées. Dans la troisième partie, nous proposons une architecture réseaux optiques passifs (PON) avec DDO-OFDM pour la liaison descendante et CO-OFDM pour la liaison montante. Nous examinons deux scénarios pour l’allocations de fréquence et le format de modulation des signaux. Nous identifions la détérioration limitante principale du PON bidirectionnelle et offrons des solutions pour minimiser ses effets.
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Research on the cognitive and decision-making processes of individuals who choose to engage in ideologically based violence is vital. Our research examines how abstract and concrete construal mindsets affect likelihood to engage in ideologically based violence. Construal Level Theory (CLT) states that an abstract mindset (high-level construal), as opposed to a concrete mindset (low-level construal), is associated with a greater likelihood of engaging in goal-oriented, value-motivated behaviors. Assuming that ideologically based violence is goal-oriented, we hypothesized that high-level construal should result in an increased likelihood of engaging in ideologically based violence. In the pilot study we developed and tested 24 vignettes covering controversial topics and assessed them on features such as relatability, emotional impact, and capacity to elicit a violent reaction. The ten most impactful vignettes were selected for use in the primary investigations. The two primary investigations examined the effect of high- and low-level construal manipulations on self-reported likelihood of engaging in ideologically based violence. Self-reported willingness was measured through an ideological violence assessment. Data trends implied that participants were engaged in the study, as they reported a higher willingness to engage in ideologically based violence when they had a higher passion for the vignette's social issue topic. Our results did not indicate a significant relationship between construal manipulations and level of passion for a topic.
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In order to optimize frontal detection in sea surface temperature fields at 4 km resolution, a combined statistical and expert-based approach is applied to test different spatial smoothing of the data prior to the detection process. Fronts are usually detected at 1 km resolution using the histogram-based, single image edge detection (SIED) algorithm developed by Cayula and Cornillon in 1992, with a standard preliminary smoothing using a median filter and a 3 × 3 pixel kernel. Here, detections are performed in three study regions (off Morocco, the Mozambique Channel, and north-western Australia) and across the Indian Ocean basin using the combination of multiple windows (CMW) method developed by Nieto, Demarcq and McClatchie in 2012 which improves on the original Cayula and Cornillon algorithm. Detections at 4 km and 1 km of resolution are compared. Fronts are divided in two intensity classes (“weak” and “strong”) according to their thermal gradient. A preliminary smoothing is applied prior to the detection using different convolutions: three type of filters (median, average and Gaussian) combined with four kernel sizes (3 × 3, 5 × 5, 7 × 7, and 9 × 9 pixels) and three detection window sizes (16 × 16, 24 × 24 and 32 × 32 pixels) to test the effect of these smoothing combinations on reducing the background noise of the data and therefore on improving the frontal detection. The performance of the combinations on 4 km data are evaluated using two criteria: detection efficiency and front length. We find that the optimal combination of preliminary smoothing parameters in enhancing detection efficiency and preserving front length includes a median filter, a 16 × 16 pixel window size, and a 5 × 5 pixel kernel for strong fronts and a 7 × 7 pixel kernel for weak fronts. Results show an improvement in detection performance (from largest to smallest window size) of 71% for strong fronts and 120% for weak fronts. Despite the small window used (16 × 16 pixels), the length of the fronts has been preserved relative to that found with 1 km data. This optimal preliminary smoothing and the CMW detection algorithm on 4 km sea surface temperature data are then used to describe the spatial distribution of the monthly frequencies of occurrence for both strong and weak fronts across the Indian Ocean basin. In general strong fronts are observed in coastal areas whereas weak fronts, with some seasonal exceptions, are mainly located in the open ocean. This study shows that adequate noise reduction done by a preliminary smoothing of the data considerably improves the frontal detection efficiency as well as the global quality of the results. Consequently, the use of 4 km data enables frontal detections similar to 1 km data (using a standard median 3 × 3 convolution) in terms of detectability, length and location. This method, using 4 km data is easily applicable to large regions or at the global scale with far less constraints of data manipulation and processing time relative to 1 km data.
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Dissertação de Mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016
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The purpose of this study was to explore the relationship between faculty perceptions, selected demographics, implementation of elements of transactional distance theory and online web-based course completion rates. This theory posits that the high transactional distance of online courses makes it difficult for students to complete these courses successfully; too often this is associated with low completion rates. Faculty members play an indispensable role in course design, whether online or face-to-face. They also influence course delivery format from design through implementation and ultimately to how students will experience the course. This study used transactional distance theory as the conceptual framework to examine the relationship between teaching and learning strategies used by faculty members to help students complete online courses. Faculty members’ sex, number of years teaching online at the college, and their online course completion rates were considered. A researcher-developed survey was used to collect data from 348 faculty members who teach online at two prominent colleges in the southeastern part of United States. An exploratory factor analysis resulted in six factors related to transactional distance theory. The factors accounted for slightly over 65% of the variance of transactional distance scores as measured by the survey instrument. Results provided support for Moore’s (1993) theory of transactional distance. Female faculty members scored higher in all the factors of transactional distance theory when compared to men. Faculty number of years teaching online at the college level correlated significantly with all the elements of transactional distance theory. Regression analysis was used to determine that two of the factors, instructor interface and instructor-learner interaction, accounted for 12% of the variance in student online course completion rates. In conclusion, of the six factors found, the two with the highest percentage scores were instructor interface and instructor-learner interaction. This finding, while in alignment with the literature concerning the dialogue element of transactional distance theory, brings a special interest to the importance of instructor interface as a factor. Surprisingly, based on the reviewed literature on transactional distance theory, faculty perceptions concerning learner-learner interaction was not an important factor and there was no learner-content interaction factor.
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This work describes the synthesis of a propargylcarbamate-functionalized isophthalate ligand and its use in the solvothermal preparation of a new copper(II)-based metal organic framework named [Cu(1,3-YBDC)]ˑxH2O (also abbreviated as Cu-MOF. The characterization of this compound was performed using several complementary techniques such as infrared (ATR-FTIR) and Raman spectroscopy, X-ray powder diffraction spectroscopy (PXRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), atomic absorption spectroscopy (AAS) as well as thermal and surface area measurements. Synchrotron X-ray diffraction analysis revealed that this MOF contains a complex network of 5-substituted isophthalate anions bound to Cu(II) centers, arranged in pairs within paddlewheel (or “Chinese lantern”) structure with a short Cu…Cu distance of 2.633 Å. Quite unexpectedly, the apical atom in the paddlewheel structure belongs to the carbamate carbonyl oxygen atom. Such extra coordination by the propargylcarbamate groups drastically reduces the MOF porosity, a feature that was also confirmed by BET measurements. Indeed, its surface area was determined to be low (14.5 ± 0.8 m2/g) as its total pore volume (46 mm3/g). Successively the Cu-MOF was treated with HAuCl4 with the aim of studying the ability of the propargylcarbamate functionality to capture the Au(III) ion and reduce it to Au(0) to give gold nanoparticles (AuNPs). The overall amount of gold retained by the Cu-MOF/Au was determined by AAS while the amount of gold and its oxidation state on the surface of the MOF was studied by XPS. A glassy carbon (GC) electrode was drop-casted with a Cu-MOF suspension to electrochemically characterize the material through cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The performance of the modified electrodes towards nitrite oxidation was tested by CV and chronoamperometry.
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Biomarkers are biological indicators of human health conditions. Their ultra-sensitive quantification is of paramount importance in clinical monitoring and early disease diagnosis. Biosensors are simple and easy-to-use analytical devices and, in their world, electrochemiluminescence (ECL) is one of the most promising analytical techniques that needs an ever-increasing sensitivity for improving its clinical effectiveness. Scope of this project was the investigation of the ECL generation mechanisms for enhancing the ECL intensity also through the identification of suitable nanostructures. The combination of nanotechnologies, microscopy and ECL has proved to be a very successful strategy to improve the analytical efficiency of ECL in one of its most promising bioanalytical approaches, the bead-based immunoassay. Nanosystems, such as [Ru(bpy)3]2+-dye-doped nanoparticles (DDSNPs) and Bodipy Carbon Nanodots, have been used to improve the sensitivity of ECL techniques thanks to their advantageous and tuneable properties, reaching a signal increase of 750% in DDSNPs-bead-based immunoassay system. In this thesis, an investigation of size and distance effects on the ECL mechanisms was carried out through the innovative combination of ECL microscopy and electrochemical mapping of radicals. It allowed the discovery of an unexpected and highly efficient mechanistic path for ECL generation at small distances from the electrode surface. It was exploited and enhanced through the addition of a branched amine DPIBA to the usual coreactant TPrA solution for enhancing the ECL efficiency until a maximum of 128%. Finally, a beads-based immunoassay and an immunosensor specific for cardiac Troponin I were built exploiting previous results and carbon nanotubes features. They created a conductive layer around beads enhancing the signal by 70% and activating an ECL mechanism unobserved before in such systems. In conclusion, the combination of ECL microscopy and nanotechnology and the deep understanding of the mechanisms responsible for the ECL emission led to a great enhancement in the signal.
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The study of the user scheduling problem in a Low Earth Orbit (LEO) Multi-User MIMO system is the objective of this thesis. With the application of cutting-edge digital beamforming algorithms, a LEO satellite with an antenna array and a large number of antenna elements can provide service to many user terminals (UTs) in full frequency reuse (FFR) schemes. Since the number of UTs on-ground are many more than the transmit antennas on the satellite, user scheduling is necessary. Scheduling can be accomplished by grouping users into different clusters: users within the same cluster are multiplexed and served together via Space Division Multiple Access (SDMA), i.e., digital beamforming or Multi-User MIMO techniques; the different clusters of users are then served on different time slots via Time Division Multiple Access (TDMA). The design of an optimal user grouping strategy is known to be an NP-complete problem which can be solved only through exhaustive search. In this thesis, we provide a graph-based user scheduling and feed space beamforming architecture for the downlink with the aim of reducing user inter-beam interference. The main idea is based on clustering users whose pairwise great-circle distance is as large as possible. First, we create a graph where the users represent the vertices, whereas an edge in the graph between 2 users exists if their great-circle distance is above a certain threshold. In the second step, we develop a low complex greedy user clustering technique and we iteratively search for the maximum clique in the graph, i.e., the largest fully connected subgraph in the graph. Finally, by using the 3 aforementioned power normalization techniques, a Minimum Mean Square Error (MMSE) beamforming matrix is deployed on a cluster basis. The suggested scheduling system is compared with a position-based scheduler, which generates a beam lattice on the ground and randomly selects one user per beam to form a cluster.