940 resultados para Transform statistics


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FTIR spectra are reported of methanol adsorbed at 295 K on ZnO/SiO 2, on reduced Cu/ZnO/SiO2 and on Cu/ZnO/SiO2 which had been preoxidised by exposure to nitrous oxide. Methanol on ZnO/SiO2 gave methoxy species on ZnO and SiO, in addition to both strongly and weakly physisorbed methanol on SiO2. The corresponding adsorption of methanol on reduced Cu/ZnO/SiO2 also gave methoxy species on Cu and a small amount of bridging formate. Reaction of methanol with a reoxidised Cu/ZnO/SiO2 catalyst resulted in an enhanced quantity of methoxy species on Cu. Heating adsorbed species on Cu/ZnO/SiO2 at 393 K led to the loss of methoxy groups on Cu and the concomitant formation of formate species on both ZnO and Cu. The comparable reaction on a reoxidised Cu/ZnO/SiO2 catalyst gave an increased amount of formate species on ZnO and this correlated with an increased quantity of methoxy groups lost from Cu. An explanation is given in terms of adsorption of formate and formaldehyde species at special sites located at the copper/zinc oxide interface.

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Fourier-transform infrared (FTIR) spectra are reported of formic acid and formaldehyde on ZnO/SiO2, reduced Cu/ZnO/SiO2 and reoxidised Cu/ZnO/SiO2 catalyst. Formic acid adsorption on ZnO/SiO2 produced mainly bidentate zinc formate species with a lesser quantity of unidentate zinc formate. Formic acid on reduced Cu/ZnO/SiO2 catalyst resulted not only in the formation of bridging copper formate structures but also in an enhanced amount of formate relative to that for ZnO/SiO2 catalyst. Formic acid on reoxidised Cu/ZnO/SiO2 gave unidentate formate species on copper in addition to zinc formate moieties. The interaction of formaldehyde with ZnO/SiO2 catalyst resulted in the formation of zinc formate species. The same reaction on reduced Cu/ZnO/SiO2 catalyst gave bridging formate on copper and a remarkable increase in the quantity of formate species associated with the zinc oxide. Adsorption of formaldehyde on a reoxidised Cu/ZnO/SiO2 catalyst produced bridging copper formate and again an apparent increase in the concentration of zinc formate species. An explanation in terms of the adsorption of molecules at special sites located at the interface between copper and zinc oxide is given.

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The reaction of CO2 and H2 with ZnO/SiO2 catalyst at 295 K gave predominantly hydrogencarbonate on zinc oxide and a small quantity of formate was evolved after heating at 393 K. Elevation of the reaction temperature to 503 K enhanced the rate of formation of zinc formate species. Significantly these formate species decomposed at 573 K almost entirely to CO2 and H2. Even after exposure of CO2-H2 or CO-CO2-H2 mixtures to highly defected ZnO/SiO2 catalyst, the formate species produced still decomposed to give CO2 and H2. It was concluded that carboxylate species which were formed at oxygen anion vacancies on polar Zn planes were not significantly hydrogenated to formate. Consequently it was proposed that the non-polar planes on zinc oxide contained sites which were specific for the synthesis of methanol. The interaction of CO2 and H2 with reduced Cu/ZnO/SiO2 catalyst at 393 K gave copper formate species in addition to substantial quantities of formate created at interfacial sites between copper and zinc oxide. It was deduced that interfacial formate species were produced from the hydrogenation of interfacial bidentate carbonate structures. The relevance of interfacial formate species in the methanol synthesis reaction is discussed. Experiments concerning the reaction of CO2-H2 with physical mixtures of Cu/SiO2 and ZnO/SiO2 gave results which were simply characteristic of the individual components. By careful consideration of previous data a detailed proposal regarding the role of spillover hydrogen is outlined. Admission of CO to a gaseous CO2-H2 feedstock resulted in a considerably diminished amount of formate species on copper. This was ascribed to a combination of over-reduction of the surface and site-blockage.

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FTIR spectra are reported of methyl formate adsorbed at 295 K on ZnO/SiO2, reduced Cu/ZnO/SiO2 and on Cu/ZnO/SiO2 which had been preoxidised by exposure to nitrous oxide. Methyl formate on ZnO/SiO2 gave adsorbed zinc formate species and strongly physisorbed molecular methanol on silica. The comparable reaction of methyl formate with reduced Cu/ZnO/SiO2 catalyst produced bridging formate species on copper and a diminished quantity of zinc formate relative to that formed on ZnO/SiO2 catalyst. This effect is explained in terms of site blockage on the ZnO surface by small copper clusters. Addition of methyl formate to a reoxidised Cu/ZnO/SiO2 catalyst produced a considerably greater amount of formate species on zinc oxide and methoxy groups on copper were detected. The increase in concentration of zinc formate species was rationalised in terms of rearrangement of unidentate copper formate species to become bonded to copper and zinc oxide sites located at the interface between these two components.

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FTIR spectra are reported of CO2 and COi/Hi on a silica-supported caesium-doped copper catalyst. Adsorption of COj on a "caesium"/silica surface resulted in the formation of COj and complexed CO species. Exposure of CO2 to' a caesium-doped reduced copper catalyst produced not only these species but also two forms of adsorbed carboxylate giving bands at 1550, 1510, 1365 and 1345 cm"1. Reaction of carboxylate species with hydrogen at 388 K gave formate species on copper and caesium oxide in addition to methoxy groups associated with caesium oxide. Methoxy species were not detected on undoped copper catalyst suggesting that caesium may be a promoter for the methanol synthesis reaction. Methanol decomposition on a caesium-doped copper catalyst produced a small number of formate species on copper and caesium oxide. Methoxy groups on caesium oxide decomposed to CO and U.2, and subsequent reaction between CO and adsorbed oxygen resulted in carboxylate formation. Methoxy species located at interfacial sites appeared to exhibit unusual adsorption properties.

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This thesis analyses the performance bounds of amplify-and-forward relay channels which are becoming increasingly popular in wireless communication applications. The statistics of cascaded Nakagami-m fading model which is a major obstacle in evaluating the outage of wireless networks is analysed using Mellin transform. Furthermore, the upper and the lower bounds for the ergodic capacity of the slotted amplify-and-forward relay channel, for finite and infinite number of relays are derived using random matrix theory. The results obtained will enable wireless network designers to optimize the network resources, benefiting the consumers.

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According to social constructivists, learners are active participants in constructing new knowledge in a social process where they interact with others. In these social settings teachers or more knowledgeable peers provide support. This research study investigated the contribution that an online synchronous tutorial makes to support teaching and learning of undergraduate introductory statistics offered by an Australian regional university at a distance. The introductory statistics course which served as a research setting in this study was a requirement of a variety of programs at the University, including psychology, business and science. Often students in these programs perceive this course to be difficult and irrelevant to their programs of study. Negative attitudes and associated anxiety mean that students often struggle with the content. While asynchronous discussion forums have been shown to provide a level of interaction and support, it was anticipated that online synchronous tutorials would offer immediate feedback to move students forward through ―stuck places.‖ At the beginning of the semester the researcher offered distance students in this course the opportunity to participate in a weekly online synchronous tutorial which was an addition to the usual support offered by the teaching team. This tutorial was restricted to 12 volunteers to allow sufficient interaction to occur for each of the participants. The researcher, as participant-observer, conducted the weekly tutorials using the University's interactive online learning platform, Wimba Classroom, whereby participants interacted using audio, text chat and a virtual whiteboard. Prior to the start of semester, participants were surveyed about their previous mathematical experiences, their perceptions of the introductory statistics course and why they wanted to participate in the online tutorial. During the semester, they were regularly asked pertinent research questions related to their personal outcomes from the tutorial sessions. These sessions were recorded using screen capture software and the participants were interviewed about their experiences at the end of the semester. Analysis of these data indicated that the perceived value of online synchronous tutorial lies in the interaction with fellow students and a content expert and with the immediacy of feedback given. The collaborative learning environment offered the support required to maintain motivation, enhance confidence and develop problemsolving skills in these distance students of introductory statistics. Based on these findings a model of online synchronous learning is proposed.

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Diagnostics of rotating machinery has developed significantly in the last decades, and industrial applications are spreading in different sectors. Most applications are characterized by varying velocities of the shaft and in many cases transients are the most critical to monitor. In these variable speed conditions, fault symptoms are clearer in the angular/order domains than in the common time/frequency ones. In the past, this issue was often solved by synchronously sampling data by means of phase locked circuits governing the acquisition; however, thanks to the spread of cheap and powerful microprocessors, this procedure is nowadays rarer; sampling is usually performed at constant time intervals, and the conversion to the order domain is made by means of digital signal processing techniques. In the last decades different algorithms have been proposed for the extraction of an order spectrum from a signal sampled asynchronously with respect to the shaft rotational velocity; many of them (the so called computed order tracking family) use interpolation techniques to resample the signal at constant angular increments, followed by a common discrete Fourier transform to shift from the angular domain to the order domain. A less exploited family of techniques shifts directly from the time domain to the order spectrum, by means of modified Fourier transforms. This paper proposes a new transform, named velocity synchronous discrete Fourier transform, which takes advantage of the instantaneous velocity to improve the quality of its result, reaching performances that can challenge the computed order tracking.

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A new approach for recognizing the iris of the human eye is presented. Zero-crossings of the wavelet transform at various resolution levels are calculated over concentric circles on the iris, and the resulting one-dimensional (1-D) signals are compared with model features using different dissimilarity functions.

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A security system based on the recognition of the iris of human eyes using the wavelet transform is presented. The zero-crossings of the wavelet transform are used to extract the unique features obtained from the grey-level profiles of the iris. The recognition process is performed in two stages. The first stage consists of building a one-dimensional representation of the grey-level profiles of the iris, followed by obtaining the wavelet transform zerocrossings of the resulting representation. The second stage is the matching procedure for iris recognition. The proposed approach uses only a few selected intermediate resolution levels for matching, thus making it computationally efficient as well as less sensitive to noise and quantisation errors. A normalisation process is implemented to compensate for size variations due to the possible changes in the camera-to-face distance. The technique has been tested on real images in both noise-free and noisy conditions. The technique is being investigated for real-time implementation, as a stand-alone system, for access control to high-security areas.

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Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.

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A cell classification algorithm that uses first, second and third order statistics of pixel intensity distributions over pre-defined regions is implemented and evaluated. A cell image is segmented into 6 regions extending from a boundary layer to an inner circle. First, second and third order statistical features are extracted from histograms of pixel intensities in these regions. Third order statistical features used are one-dimensional bispectral invariants. 108 features were considered as candidates for Adaboost based fusion. The best 10 stage fused classifier was selected for each class and a decision tree constructed for the 6-class problem. The classifier is robust, accurate and fast by design.

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This is a discussion of the journal article: "Construcing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation". The article and discussion have appeared in the Journal of the Royal Statistical Society: Series B (Statistical Methodology).

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Loop detectors are widely used on the motorway networks where they provide point speed and traffic volumes. Models have been proposed for temporal and spatial generalization of speed for average travel time estimation. Advancement in technology provides complementary data sources such as Bluetooth MAC Scanner (BMS), detecting the MAC ID of the Bluetooth devices transported by the traveller. Matching the data from two BMS stations provides individual vehicle travel time. Generally, on the motorways loops are closely spaced, whereas BMS are placed few kilometres apart. In this research, we fuse BMSs and loops data to define the trajectories of the Bluetooth vehicles. The trajectories are utilised to estimate the travel time statistics between any two points along the motorway. The proposed model is tested using simulation and validated with real data from Pacific motorway, Brisbane. Comparing the model with the linear interpolation based trajectory provides significant improvements.

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Background Heatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under ‘normal’ conditions from the historical daily mortality records. The calculation of the excess mortality is a scientific challenge because of the stochastic temporal pattern of the daily mortality data which is characterised by (a) the long-term changing mean levels (i.e., non-stationarity); (b) the non-linear temperature-mortality association. The Hilbert-Huang Transform (HHT) algorithm is a novel method originally developed for analysing the non-linear and non-stationary time series data in the field of signal processing, however, it has not been applied in public health research. This paper aimed to demonstrate the applicability and strength of the HHT algorithm in analysing health data. Methods Special R functions were developed to implement the HHT algorithm to decompose the daily mortality time series into trend and non-trend components in terms of the underlying physical mechanism. The excess mortality is calculated directly from the resulting non-trend component series. Results The Brisbane (Queensland, Australia) and the Chicago (United States) daily mortality time series data were utilized for calculating the excess mortality associated with heatwaves. The HHT algorithm estimated 62 excess deaths related to the February 2004 Brisbane heatwave. To calculate the excess mortality associated with the July 1995 Chicago heatwave, the HHT algorithm needed to handle the mode mixing issue. The HHT algorithm estimated 510 excess deaths for the 1995 Chicago heatwave event. To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors. Conclusions The HHT algorithm is a novel and powerful analytical tool in time series data analysis. It has a real potential to have a wide range of applications in public health research because of its ability to decompose a nonlinear and non-stationary time series into trend and non-trend components consistently and efficiently.