Computed success rates of various carrier phase integer estimation solutions and their comparison with statistical success rates

The success rate of carrier phase ambiguity resolution (AR) is the probability that the ambiguities are successfully fixed to their correct integer values. In existing works, an exact success rate formula for integer bootstrapping estimator has been used as a sharp lower bound for the integer least squares (ILS) success rate. Rigorous computation of success rate for the more general ILS solutions has been considered difficult, because of complexity of the ILS ambiguity pull-in region and computational load of the integration of the multivariate probability density function. Contributions of this work are twofold. First, the pull-in region mathematically expressed as the vertices of a polyhedron is represented by a multi-dimensional grid, at which the cumulative probability can be integrated with the multivariate normal cumulative density function (mvncdf) available in Matlab. The bivariate case is studied where the pull-region is usually defined as a hexagon and the probability is easily obtained using mvncdf at all the grid points within the convex polygon. Second, the paper compares the computed integer rounding and integer bootstrapping success rates, lower and upper bounds of the ILS success rates to the actual ILS AR success rates obtained from a 24 h GPS data set for a 21 km baseline. The results demonstrate that the upper bound probability of the ILS AR probability given in the existing literatures agrees with the actual ILS success rate well, although the success rate computed with integer bootstrapping method is a quite sharp approximation to the actual ILS success rate. The results also show that variations or uncertainty of the unit–weight variance estimates from epoch to epoch will affect the computed success rates from different methods significantly, thus deserving more attentions in order to obtain useful success probability predictions.

Effects of different practice task constraints on fluctuations of player heart rate in small-sided football games

This paper analyzes effects of different practice task constraints on heart rate (HR) variability during 4v4 smallsided football games. Participants were sixteen football players divided into two age groups (U13, Mean age: 12.4±0.5 yrs; U15: 14.6±0.5). The task consisted of a 4v4 sub-phase without goalkeepers, on a 25x15 m field, of 15 minutes duration with an active recovery period of 6 minutes between each condition. We recorded players’ heart rates using heart rate monitors (Polar Team System, Polar Electro, Kempele, Finland) as scoring mode was manipulated (line goal: scoring by dribbling past an extended line; double goal: scoring in either of two lateral goals; and central goal: scoring only in one goal). Subsequently, %HR reserve was calculated with the Karvonen formula. We performed a time-series analysis of HR for each individual in each condition. Mean data for intra-participant variability showed that autocorrelation function was associated with more short-range dependence processes in the “line goal” condition, compared to other conditions, demonstrating that the “line goal” constraint induced more randomness in HR response. Relative to inter-individual variability, line goal constraints demonstrated lower %CV and %RMSD (U13: 9% and 19%; U15: 10% and 19%) compared with double goal (U13: 12% and 21%; U15: 12% and 21%) and central goal (U13: 14% and 24%; U15: 13% and 24%) task constraints, respectively. Results suggested that line goal constraints imposed more randomness on cardiovascular stimulation of each individual and lower inter-individual variability than double goal and central goal constraints.

Molecular structure of Mg-Al, Mn-Al and Zn-Al halotrichites : an infrared spectroscopic study

Near infrared (NIR), X-ray diffraction (XRD) and infrared (IR) spectroscopy have been applied to halotrichites of the formula MgAl2(SO4)4∙22H2O, MnAl2(SO4)4∙22H2O and ZnAl2(SO4)4∙22H2O. Comparison of the halotrichites in different spectral regions has shown that the incorporation of a divalent transition metal into the halotrichite structure causes a shift in OH stretching band positions to lower wavenumbers. Therefore, an increase in hydrogen bonded water is observed for divalent cations with a larger molecular mass. XRD has confirmed the formation of halotrichite for all three samples and characteristic peaks of halotrichite have been identified at 18.5 and 24.5° 2θ, along with a group of six peaks between 5 and 15° 2θ. It has been observed that Mg-Al and Mn-Al halotrichite are very similar in structure, while Zn-Al showed several differences particularly in the NIR spectra. This work has shown that halotrichite structures can be synthesised and characterised by infrared and NIR spectroscopy.

The ecological dynamics of 1v1 sub-phases in association football

This paper analyzes effects of different practice task constraints on heart rate (HR) variability during 4v4 smallsided football games. Participants were sixteen football players divided into two age groups (U13, Mean age: 12.4±0.5 yrs; U15: 14.6±0.5). The task consisted of a 4v4 sub-phase without goalkeepers, on a 25x15 m field, of 15 minutes duration with an active recovery period of 6 minutes between each condition. We recorded players’ heart rates using heart rate monitors (Polar Team System, Polar Electro, Kempele, Finland) as scoring mode was manipulated (line goal: scoring by dribbling past an extended line; double goal: scoring in either of two lateral goals; and central goal: scoring only in one goal). Subsequently, %HR reserve was calculated with the Karvonen formula. We performed a time-series analysis of HR for each individual in each condition. Mean data for intra-participant variability showed that autocorrelation function was associated with more short-range dependence processes in the “line goal” condition, compared to other conditions, demonstrating that the “line goal” constraint induced more randomness in HR response. Relative to inter-individual variability, line goal constraints demonstrated lower %CV and %RMSD (U13: 9% and 19%; U15: 10% and 19%) compared with double goal (U13: 12% and 21%; U15: 12% and 21%) and central goal (U13: 14% and 24%; U15: 13% and 24%) task constraints, respectively. Results suggested that line goal constraints imposed more randomness on cardiovascular stimulation of each individual and lower inter-individual variability than double goal and central goal constraints.

Development of a software model of a heavy vehicle suspension for research

A Simulink Matlab control system of a heavy vehicle suspension has been developed. The aim of the exercise presented in this paper was to develop a Simulink Matlab control system of a heavy vehicle suspension. The objective facilitated by this outcome was the use of a working model of a heavy vehicle (HV) suspension that could be used for future research. A working computer model is easier and cheaper to re-configure than a HV axle group installed on a truck; it presents less risk should something go wrong and allows more scope for variation and sensitivity analysis before embarking on further "real-world" testing. Empirical data recorded as the input and output signals of a heavy vehicle (HV) suspension were used to develop the parameters for computer simulation of a linear time invariant system described by a second-order differential equation of the form: (i.e. a "2nd-order" system). Using the empirical data as an input to the computer model allowed validation of its output compared with the empirical data. The errors ranged from less than 1% to approximately 3% for any parameter, when comparing like-for-like inputs and outputs. The model is presented along with the results of the validation. This model will be used in future research in the QUT/Main Roads project Heavy vehicle suspensions – testing and analysis, particularly so for a theoretical model of a multi-axle HV suspension with varying values of dynamic load sharing. Allowance will need to be made for the errors noted when using the computer models in this future work.

A biologically inspired object spectral-texture descriptor and its application to vegetation classification in power-line corridors

The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.

The synthesis and spectroscopic characterisation of hydrotalcite formed from aluminate solutions

Raman spectroscopy has been used to characterise nine hydrotalcites prepared from aluminate and magnesium solutions (magnesium chloride and seawater). The aluminate hydrotalcites are proposed to have the following formula Mg6Al2(OH)16(CO32-).xH2O, Mg6Al2(OH)16(CO32-,SO42-).xH2O, and Mg6Al2(OH)16(SO42-).xH2O. The synthesis of these hydrotalcites using seawater results in the intercalation of sulfate anions into the hydrotalcite interlayer. The spectra have been used to assess the molecular assembly of the cations and anions in the hydrotalcite structures. The spectra have been conveniently subdivided into spectral features based upon the carbonate anion, the hydroxyl units and water units. This investigation has shown the ideal conditions to form hydrotalcite from aluminate solutions is at pH 14 using magnesium chloride. Changes in synthesis conditions resulted in the formation of impurity products aragonite, thenardite, and gypsum.

Synthesis and vibrational spectroscopy of halotrichite and bilinite

Near infrared (NIR), infrared (IR) spectroscopy and X-ray diffraction (XRD) have been applied to halotrichites of the formula FeAl2(SO4)4∙22H2O and Fe2+Fe23+(SO4)4∙22H2O. Comparison of the halotrichites and their starting materials has been used to give a better understanding of the bonding involved in these types of minerals. The vibrational spectroscopy data has shown that Fe2+ oxidises during the formation of halotrichite, no preventative measures were implemented to prevent oxidation, and this has been clearly shown by the position and broadness of electronic bands of transition metals in the NIR spectra (12500 to 7500 cm-1). It is apparent from this region that Fe3+ substitutes for Al3+ in the synthesis of halotrichite. Due to the oxidation of Fe2+ to Fe3+ the halotrichite sample contains a small portion of bilinite. This has been confirmed by XRD, peaks at 9 and 14° 2θ were observed in the halotrichite sample and are identical to the XRD pattern obtained for bilinite. Substitution of aluminium for Fe3+ has resulted in significant changes in the overall infrared and NIR spectral profiles. However, the lower wavenumber regions of the NIR spectra have very similar spectral profiles, which indicate a similar structure to halotrichite has formed for bilinite. This work has shown that iron halotrichites can be synthesised and characterised by infrared and NIR spectroscopy.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

Similarity metrics within a point of view

In vector space based approaches to natural language processing, similarity is commonly measured by taking the angle between two vectors representing words or documents in a semantic space. This is natural from a mathematical point of view, as the angle between unit vectors is, up to constant scaling, the only unitarily invariant metric on the unit sphere. However, similarity judgement tasks reveal that human subjects fail to produce data which satisfies the symmetry and triangle inequality requirements for a metric space. A possible conclusion, reached in particular by Tversky et al., is that some of the most basic assumptions of geometric models are unwarranted in the case of psychological similarity, a result which would impose strong limits on the validity and applicability vector space based (and hence also quantum inspired) approaches to the modelling of cognitive processes. This paper proposes a resolution to this fundamental criticism of of the applicability of vector space models of cognition. We argue that pairs of words imply a context which in turn induces a point of view, allowing a subject to estimate semantic similarity. Context is here introduced as a point of view vector (POVV) and the expected similarity is derived as a measure over the POVV's. Different pairs of words will invoke different contexts and different POVV's. Hence the triangle inequality ceases to be a valid constraint on the angles. We test the proposal on a few triples of words and outline further research.

Raman spectroscopy of gallium- and zinc-based hydrotalcites

Insight into the unique structure of hydrotalcites (HTs) has been obtained using Raman spectroscopy. Gallium-contg. HTs of formula Zn4 Ga2(CO3)(OH)12 · xH2O (2:1 ZnGa-HT), Zn6 Ga2(CO3)(OH)16 · xH2O (3:1 ZnGa-HT) and Zn8 Ga2(CO3)(OH)18 · xH2O (4:1 ZnGa-HT) have been successfully synthesized and characterised by X-ray diffraction (XRD) and Raman spectroscopy. The d(003) spacing varies from 7.62 Å for the 2:1 ZnGa-HT to 7.64 Å for the 3:1 ZnGa-HT. The 4:1 ZnGa-HT showed a decrease in the d(003) spacing, compared to the 2:1 and 3:1 compds. Raman spectroscopy complemented with selected IR data has been used to characterize the synthesized gallium-contg. HTs. Raman bands obsd. at around 1050, 1060 and 1067 cm-1 are attributed to the sym. stretching modes of the (CO32-) units. Multiple ν3 (CO32-) antisym. stretching modes are found between 1350 and 1520 cm-1, confirming multiple carbonate species in the HT structure. The splitting of this mode indicates that the carbonate anion is in a perturbed state. Raman bands obsd. at 710 and 717 cm-1 and assigned to the ν4 (CO32-) modes support the concept of multiple carbonate species in the interlayer.

A Raman spectroscopic study of copiapites Fe2+Fe3+(SO4)6(OH)2 · 20H2O: environmental implications

Raman spectroscopy has been used to study selected mineral samples of the copiapite group. Copiapite (Fe2+Fe3+(SO4)6(OH)2 · 20H2O) is a secondary mineral formed through the oxidn. of pyrite. Minerals of the copiapite group have the general formula AFe4(SO4)6(OH)2 · 20H2O, where A has a + 2 charge and can be either magnesium, iron, copper, calcium and/or zinc. The formula can also be B2/3Fe4(SO4)6(OH)2 · 20H2O, where B has a + 3 charge and may be either aluminum or iron. For each mineral, two Raman bands are obsd. at around 992 and 1029 cm-1, assigned to the (SO4)2-ν1 sym. stretching mode. The observation of two bands provides evidence for the existence of two non-equiv. sulfate anions in the mineral structure. Three Raman bands at 1112, 1142 and 1161 cm-1 are obsd. in the Raman spectrum of copiapites, indicating a redn. of symmetry of the sulfate anion in the copiapite structure. This redn. in symmetry is supported by multiple bands in the ν2 and ν4(SO4)2- spectral regions.

Single crystal Raman spectroscopy of brandholzite Mg[Sb(OH)6]2•6H2O and bottinoite Ni[Sb(OH)6]2•6H2O and the polycrystalline Raman spectrum of mopungite Na[Sb(OH)6]

The single crystal Raman spectra of minerals brandholzite and bottinoite, formula M[Sb(OH)6]2•6H2O, where M is Mg+2 and Ni+2 respectively, and the non-aligned Raman spectrum of mopungite, formula Na[Sb(OH)6], are presented for the first time. The mixed metal minerals comprise of alternating layers of [Sb(OH)6]-1 octahedra and mixed [M(H2O)6]+2 / [Sb(OH)6]-1 octahedra. Mopungite comprises hydrogen bonded layers of [Sb(OH)6]-1 octahedra linked within the layer by Na+ ions. The spectra of the three minerals were dominated by the Sb-O symmetric stretch of the [Sb(OH)6]-1 octahedron, which occurs at approximately 620 cm-1. The Raman spectrum of mopungite showed many similarities to spectra of the di-octahedral minerals informing the view that the Sb octahedra gave rise to most of the Raman bands observed, particularly below 1200 cm-1. Assignments have been proposed based on the spectral comparison between the minerals, prior literature and density field theory calculations of the vibrational spectra of the free [Sb(OH)6]-1 and [M(H2O)6]+2 octahedra by a model chemistry of B3LYP/6-31G(d) and lanl2dz for the Sb atom. The single crystal data spectra showed good mode separation, allowing the majority of the bands to be assigned a symmetry species of A or E.

Vibrational spectroscopic study of the antimonate mineral bindheimite Pb2Sb2O6(O,OH)

Raman spectroscopy complimented with infrared spectroscopy has been used to characterise the antimonate mineral bindheimite Pb2Sb2O6(O,OH). The mineral is characterised by an intense Raman band at 656 cm-1 assigned to SbO stretching vibrations. Other lower intensity bands at 664, 749 and 814 cm-1 are also assigned to stretching vibrations. This observation suggests the non-equivalence of SbO units in the structure. Low intensity Raman bands at 293, 312 and 328 cm-1 are assigned to the OSbO bending vibrations. Infrared bands at 979, 1008, 1037 and 1058 cm-1 may be assigned to δ OH deformation modes of SbOH units. Infrared bands at 1603 and 1640 cm-1 are assigned to water bending vibrations, suggesting that water is involved in the bindheimite structure. Broad infrared bands centred upon 3250 cm-1 supports this concept. Thus the true formula of bindheimite is questioned and probably should be written as Pb2Sb2O6(O,OH,H2O)

Thermal decomposition of hydrotalcite with hexacyanoferrite(II) and hexacyanoferrate(III) anions in the interlayer : a controlled rate thermal analysis study

The mechanism for the decomposition of hydrotalcite remains unsolved. Controlled rate thermal analysis enables this decomposition pathway to be explored. The thermal decomposition of hydrotalcites with hexacyanoferrite(II) and hexacyanoferrate(III) in the interlayer has been studied using controlled rate thermal analysis technology. X-ray diffraction shows the hydrotalcites studied have a d(003) spacing of 11.1 and 10.9 Å which compares with a d-spacing of 7.9 and 7.98 Å for the hydrotalcite with carbonate or sulphate in the interlayer. Calculations based upon CRTA measurements show that 7 moles of water is lost, proving the formula of hexacyanoferrite(II) intercalated hydrotalcite is Mg6Al2(OH)16[Fe(CN)6]0.5 .7 H2O and for the hexacyanoferrate(III) intercalated hydrotalcite is Mg6Al2(OH)16[Fe(CN)6]0.66 * 9 H2O. Dehydroxylation combined with CN unit loss occurs in three steps between a) 310 and 367°C b) 367 and 390°C and c) between 390 and 428°C for both the hexacyanoferrite(II) and hexacyanoferrate(III) intercalated hydrotalcite.