998 resultados para near-rectangular slot


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Summary form only given. Geometric simplicity, efficiency and polarization purity make slot antenna arrays ideal solutions for many radar, communications and navigation applications, especially when high power, light weight and limited scan volume are priorities. Resonant arrays of longitudinal slots have a slot spacing of one-half guide wavelength at the design frequency, so that the slots are located at the standing wave peaks. Planar arrays are implemented using a number of rectangular waveguides (branch line guides), arranged side-by-side, while waveguides main lines located behind and at right angles to the branch lines excite the radiating waveguides via centered-inclined coupling slots. Planar slotted waveguide arrays radiate broadside beams and all radiators are designed to be in phase.

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Diagnosis of articular cartilage pathology in the early disease stages using current clinical diagnostic imaging modalities is challenging, particularly because there is often no visible change in the tissue surface and matrix content, such as proteoglycans (PG). In this study, we propose the use of near infrared (NIR) spectroscopy to spatially map PG content in articular cartilage. The relationship between NIR spectra and reference data (PG content) obtained from histology of normal and artificially induced PG-depleted cartilage samples was investigated using principal component (PC) and partial least squares (PLS) regression analyses. Significant correlation was obtained between both data (R2 = 91.40%, p<0.0001). The resulting correlation was used to predict PG content from spectra acquired from whole joint sample, this was then employed to spatially map this component of cartilage across the intact sample. We conclude that NIR spectroscopy is a feasible tool for evaluating cartilage contents and mapping their distribution across mammalian joint

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With the increasing need to adapt to new environments, data-driven approaches have been developed to estimate terrain traversability by learning the rover’s response on the terrain based on experience. Multiple learning inputs are often used to adequately describe the various aspects of terrain traversability. In a complex learning framework, it can be difficult to identify the relevance of each learning input to the resulting estimate. This paper addresses the suitability of each learning input by systematically analyzing the impact of each input on the estimate. Sensitivity Analysis (SA) methods provide a means to measure the contribution of each learning input to the estimate variability. Using a variance-based SA method, we characterize how the prediction changes as one or more of the input changes, and also quantify the prediction uncertainty as attributed from each of the inputs in the framework of dependent inputs. We propose an approach built on Analysis of Variance (ANOVA) decomposition to examine the prediction made in a near-to-far learning framework based on multi-task GP regression. We demonstrate the approach by analyzing the impact of driving speed and terrain geometry on the prediction of the rover’s attitude and chassis configuration in a Marsanalogue terrain using our prototype rover Mawson.

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The intercalation of an anionic surfactant, sodium dodecylsulfate (SDS), into hydrocalumite (CaAl-LDH-Cl) was investigated in this study. To understand the intercalation behavior, X-ray diffraction (XRD), mid-infrared spectroscopy (MIR), near-infrared spectroscopy (NIR) and scanning electron microscopy (SEM) were undertaken. The near-infrared spectra indicated a special spectral range from 6000 to 5600cm-1and prominent bands of CaAl-LDH-Cl intercalated with SDS around 8388cm-1. This band was assigned to the second overtone of the first fundamental of CH stretching vibrations of SDS, and it could be used to determinate the result of CaAl-LDH-Cl modified by SDS. Moreover, the results revealed that different adsorption behaviors were observed at different (high and low) concentrations of SDS. When the SDS concentration was around 0.2molL-1, anion exchange intercalation occurred and the interlayer distance expanded to about 3.25nm. When SDS concentration was 0.005molL-1, the surface adsorption of DS- was the major anion exchange event.

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Marble from the Chillagoe deposits was extensively used in the construction of Australia’s parliament house. Near infrared (NIR) spectroscopy has been applied to study the quality of marble from the Chillagoe marble deposits and to distinguish between different types of marble in the Chillagoe deposits. A comparison of the NIR spectra of marble with dolomite and monohydrocalcite is made. The spectrum of the marble closely resembles that of monohydrocalcite and is different from that of dolomite. The infrared spectra of the minerals are characterised by OH and water stretching vibrations. Both the first and second fundamental overtones of these bands are observed in the NIR spectra. Marble is characterised by NIR bands at 4005, 4268 and 4340 cm–1, attributed to carbonate combination bands and overtones. Marble also shows NIR bands at 5005, 5106, 5234 and 5334 cm–1 assigned to water combination bands. Finally the NIR spectrum of the marble displays broad low-intensity features centred upon 6905 cm–1 attributed to the water first overtones. It appears feasible to identify marble through the use of NIR spectroscopy.

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The mineral chloritoid collected from the argillite in the bottom of Yaopo Formation of Western Beijing was characterized by mid-infrared (MIR) and near-infrared (NIR) spectroscopy. The MIR spectra showed all fundamental vibrations including the hydroxyl units, basic aluminosilicate framework and the influence of iron on the chloritoid structure. The NIR spectrum of the chloritoid showed combination (ν + δ)OH bands with the fundamental stretching (ν) and bending (δ) vibrations. Based on the chemical component data and the analysis result from the MIR and NIR spectra, the crystal structure of chloritoid from western hills of Beijing, China, can be illustrated. Therefore, the application of the technique across the entire infrared region is expected to become more routine and extend its usefulness, and the reproducibility of measurement and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for the unit cell structural analysis.

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The approach to remove greenhouse gases by pumping liquid CO2 several kilometres below the ground implies that many carbonate containing minerals will be formed. Among these minerals, the formation of hydromagnesite, dypingite and nesquehonite are possible, thus necessitating a study of such minerals. These minerals with a hydrotalcite-related formulae have been characterised by a combination of infrared and near infrared spectroscopy. Layered double hydroxides (also known as anionic clays or hydrotalcites) are a group of layered clay minerals described by the general formula: [M1–x2+Mx3+(OH)2]x+[An–]x/n∙mH2O. The infrared spectra of the minerals are characterised by OH and water stretching vibrations. Both the first and second fundamental overtones of these bands are observed in the NIR spectra in the 7030–7235 cm–1 and 10,490–10,570 cm–1 spectral ranges. Intense (CO3)2– symmetrical and anti-symmetrical stretching vibrations confirm the distortion of the carbonate anion. The position of the water bending vibration indicates water is strongly hydrogen-bonded to the carbonate anion in the mineral structure. NIR spectroscopy offers a method for quickly analysing such materials.

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Overhead high-voltage power lines are known sources of corona ions. These ions rapidly attach to aerosols to form charged particles in the environment. Although the effect of ions and charged particles on human health is largely unknown, much attention has focused on the increasing exposure as a result of the expanding power network in urban residential areas. However, it is not widely known that a large number of charged particles in urban environments originate from motor vehicle emissions. In this study, for the first time, we compare the concentrations of charged nanoparticles near busy roads and overhead power lines. We show that large concentrations of both positive and negative charged nanoparticles are present near busy roadways and that these concentrations commonly exceed those under high-voltage power lines. We estimate that the concentration of charged nanoparticles found near two freeways carrying around 120 vehicles per minute exceeded the corresponding maximum concentrations under two corona-emitting overhead power lines by as much as a factor of 5. The difference was most pronounced when a significant fraction of traffic consisted of heavy-duty diesel vehicles which typically have high particle and charge emission rates.

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This thesis develops and applies an analytical method to treat the blast response of glass façades and studies the influence of controlling parameters such as all component materials and geometric properties, support conditions and energy absorption, and hence establishes a framework for their design for a credible blast event.

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This thesis is a cross-sectional study of a health insurance scheme for a representative sample of the near-poor in Cao Lanh district, Dong Thap province, Vietnam. It examines insurance coverage, health service utilisation, out-of-pocket expenditures and their associated factors. The research findings contribute evidence for policy makers who seek to improve the health insurance scheme for socioeconomically disadvantaged people in Vietnam, which is an important component of national efforts to implement universal health insurance. This community-level research adds to the evidence-base needed to improve the insurance system and thereby influence the quality of health care services.

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Recent research on hollow flange beams has led to the development of an innovative rectangular hollow flange channel beam (RHFCB) for use in floor systems. The new RHFCB is a mono-symmetric structural section made by intermittently rivet fastening two torsionally rigid closed rectangular hollow flanges to a web plate element, which allows section optimisation by selecting appropriate combinations of web and flange widths and thicknesses. However, the current design rules for cold-formed steel sections are not directly applicable to rivet fastened RHFCBs. To date, no investigation has been conducted on their web crippling behaviour and strengths. Hence an experimental study was conducted to investigate the web crippling behaviour and capacities of rivet fastened RHFCBs under End Two Flange (ETF) and Interior Two Flange (ITF) load cases. It showed that RHFCBs failed by web crippling, flange crushing and their combinations. Comparison of ultimate web crippling capacities with the predictions from the design equations in AS/NZS 4600 and AISI S100 showed that the current design equations are unconservative for rivet fastened RHFCB sections under ETF and ITF load cases. Hence new equations were proposed to determine the web crippling capacities of rivet fastened RHFCBs. These equations can also be used to predict the capacities of RHFCBs subject to combined web crippling and flange crushing conservatively. However, new capacity equations were proposed in the case of flange crushing failures that occurred in thinner flanges with smaller bearing lengths. This paper presents the details of this web crippling experimental study of RHFCB sections and the results.

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Even though crashes between trains and road users are rare events at railway level crossings, they are one of the major safety concerns for the Australian railway industry. Nearmiss events at level crossings occur more frequently, and can provide more information about factors leading to level crossing incidents. In this paper we introduce a video analytic approach for automatically detecting and localizing vehicles from cameras mounted on trains for detecting near-miss events. To detect and localize vehicles at level crossings we extract patches from an image and classify each patch for detecting vehicles. We developed a region proposals algorithm for generating patches, and we use a Convolutional Neural Network (CNN) for classifying each patch. To localize vehicles in images we combine the patches that are classified as vehicles according to their CNN scores and positions. We compared our system with the Deformable Part Models (DPM) and Regions with CNN features (R-CNN) object detectors. Experimental results on a railway dataset show that the recall rate of our proposed system is 29% higher than what can be achieved with DPM or R-CNN detectors.