Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiplicative reasoning professional development programme : evaluation

The Multiplicative Reasoning Project (MRP) delivered by the National Centre for Excellence in the Teaching of Mathematics (NCETM) in 2013/14 focused on developing teachers' understanding and capacity to teach topics that involved multiplicative reasoning to Key Stage 3 (KS3) pupils. Multiplicative reasoning refers to the mathematical understanding and capability to solve problems arising from proportional situations often involving an understanding and application of fractions as well as decimals, percentages, ratios and proportions. The aspects of multiplicative reasoning addressed in the NCETM project were proportional and fractional relationships. The teaching approaches encouraged were the use of mathematical models, visual approaches and problem solving strategies. Approximately 60 teachers in 30 schools engaged in 3 regional professional development networks, led by professional development leaders, supported by university researchers. Specific project materials were created by a team of curriculum developers. The impact of MRP on pupil outcomes was evaluated using a 3-level Clustered Randomised Control Trial (CRT) research design. The trial ran between October 2013 and June 2014 and involved 8,777 year 7 (Y7), year 8 (Y8) and year 9 (Y9) pupils (level 1) clustered into 418 Y7, Y8 and Y9 mathematics classes (level 2) clustered into 60 secondary schools. Approximately half the schools, teachers and pupils participated in the intervention and half formed a control group. Progress was compared between the two groups of pupils using Key Stage 2 (KS2) data as a base line and GL Assessment Progress in Mathematics Test (PiM) tests as an outcome measure. This is a measure of general mathematical attainment that is correlated with national tests.
Gauge-invariant dynamical quantities of QED with decomposed gauge potentials

We discover an inner structure of the QED system; i.e., by decomposing the gauge potential into two orthogonal components, we obtain a new expansion of the Lagrangian for the electron-photon system, from which, we realize the orthogonal decomposition of the canonical momentum conjugate to the gauge potential with the canonical momentum's two components conjugate to the gauge potential's two components, respectively. Using the new expansion of Lagrangian and by the general method of field theory, we naturally derive the gauge invariant separation of the angular momentum of the electron-photon system from Noether theorem, which is the rational one and has the simplest form in mathematics, compared with the other four versions of the angular momentum separation available in literature. We show that it is only the longitudinal component of the gauge potential that is contained in the orbital angular momentum of the electron, as Chen et al. have said. A similar gauge invariant separation of the momentum is given. The decomposed canonical Hamiltonian is derived, from which we construct the gauge invariant energy operator of the electron moving in the external field generated by a proton [Phys. Rev. A 82, 012107 (2010)], where we show that the form of the kinetic energy containing the longitudinal part of the gauge potential is due to the intrinsic requirement of the gauge invariance. Our method provides a new perspective to look on the nucleon spin crisis and indicates that this problem can be solved strictly and systematically.
The use of the Schwarz-Christoffel transformation in finite element mesh generation.

This thesis describes a new conpute r-based method for the generation of finite element meshes. It relies upon the Schwarz-Christoffel transformation, a conformai mapping from conplex variable theory. This mapping is defined and some examples of its use in classical fluid dynamics are given. A practical method for evaluating the parameters defining this transformation is described and emphasis is placed on -the efficiency of the solution process in order that coirputer run times may be kept as short as possible. A theorem in Euclidean geometry is stated and proved which links the theory of the Schwarz-Christoffel mapping and the geometrical use to vdiich it is put here. Two such Schwarz-Christoffel transformations are used to construct a mapping between any two polygons. The desirable properties of a finite element mesh are stated and a method is described which atteirpts to generate such a mesh in any sinply-connected two-dimensional region. Numbering of the nodes is an inherent part of the generation scheme, thus ensuring that the optimum bandwidth of the resulting system of linear equations in the analysis phase is obtained. In order to be able to present example meshes, a particular element type, the three-noded triangle, is used and a section describing the enumeration of hexagons, all of whose internal angles are 2n/3, is included. The thesis includes a brief survey of existing methods of two-dimensional mesh generation as well as several example meshes.
Bearing fault-induced feature enhancement via adaptive multi-band denoising model

To accurately extract the bearing fault-induced impulse features from the vibration signals corrupted by heavy noise and large-amplitude random impulses, an adaptive multi-band denoising model based on the Morlet wavelet filter and sparse representation is put forward. First, to locate the desired frequency band associated with fault components, the Morlet wavelet filter is employed to band-pass the signal from the perspective of the frequency-domain. Herein, an improved Protrugram-based index, termed as windowed envelope spectral kurtosis, is designed as the objective function to choose the optimal center frequency and the bandwidth of the Morlet wavelet filter. Furthermore, benefitting from the time-domain characteristics of the vibration signal, the in-band noise is eliminated by sparse representation. One of the critical parameters (resonance frequency) of the wavelet atom used in the sparse representation dictionary is directly taken as the center frequency of the Morlet wavelet filter, which makes full use of the information derived from the filter, and thus significantly improves the calculation efficiency. Finally, the recovery signal is demodulated by the Hilbert transform to extract the fault characteristic frequency. The effectiveness and superiority of the proposed method are demonstrated through a complete analysis of the simulated, experimental, and engineering signals, as well as a comparison with such prevalent methods as Kurtogram, individual sparse representation, and Morlet wavelet filter combined with the maximum correlation kurtosis deconvolution.
Model Calibration and Parameter Estimation: For Environmental and Water Resource Systems

Introduction. - The Classical Inverse Problem. - The Gauss-Newton Method. - Multiobjective Inversion and Regularization. - Statistical Methods for Parameter Estimation. - Model Differentiation. - Model Dimension Reduction. - Development of Data-Driven Models. - Data Assimilation for Inversion. - Model Uncertainty Quantification. - Optimal Experimental Design. - Goal-Oriented Modeling.
Improving statistical image reconstruction for cardiac X-ray computed tomography

Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography by Jang Hwan Cho Chair: Jeffrey A. Fessler X-ray computed tomography (CT) is one of the most widely used imaging modalities for medical diagnosis. Recent advancements in CT scanner technology have led to increased use of CT in various applications. Unfortunately, these technological advances in CT imaging pose new challenges such as increased X-ray radiation dose and complexity of image reconstruction. Statistical image reconstruction methods use realistic models that incorporate the physics of the measurements and the statistical properties of the measurement noise, and they have potential to provide better image quality and dose reduction compared to the conventional filtered back-projection (FBP) method. However, statistical methods face several challenges that should be addressed before they can replace the FBP method universally. Such challenges include substantial computation time, anisotropic and nonuniform spatial resolution and noise properties, and other artifacts. In this thesis, we develop various methods to overcome these challenges of statistical image reconstruction methods. Rigorous regularization design methods in Fourier domain were proposed to achieve more isotropic and uniform spatial resolution or noise properties. The design framework is general so that users can control the spatial resolution and the noise characteristics of the estimator. Experimental results show the proposed method can achieve its goal with modest computation cost. In addition, a regularization design method based on the hypothetical geometry concept was introduced to improve resolution or noise uniformity. Proposed designs using the new concept effectively improved the spatial resolution or noise uniformity in the reconstructed image. The hypothetical geometry idea is general enough to be applied to other scan geometries. We investigated various methods to reduce image artifacts in reconstructed images caused by the short-scan geometry. Statistical weighting modification, based on how much each detector
A measure-theoretic framework for constraints and bounds on measurements of data

We propose a mathematical framework for measures to study constraints and bounds on measurements of data used in the domains of databases and data mining. This framework is significant in that it facilitates the use of two tools for knowledge extraction, and paves the way for additional support of applications involving measurements in other computing areas such as the theory of reasoning about uncertainty in machine learning. The first tool permits the identification of structure present in data using measure constraints. This leads naturally to the consideration of implication problems for such constraints, which, in turn, leads to the introduction and consideration of inference rules systems and their associated soundness and completeness. We use this tool to study data dependencies in relational databases and to study disjunctive rules which are used in the determination of more compact representations of frequent itemsets in the frequent itemsets mining problem. We also make connections to propositional logic allowing us to prove completeness of a fragment of propositional logic and provide complexity results about the implication problem of measure constraints. The second tool consists of bounding rules that permit reasoning about bounds on measurements of data in terms of measures of related data. This leads to a general measure bounding theorem which is the fundamental tool for reasoning about these bounds. We apply this theorem to the frequent itemsets mining problem in data mining. In that context, we conduct a theoretical investigation of the bounding theorem assuming independence properties on the database and derive in the independent case the best bounds and show that these bounds can be computed efficiently. Then we report on an experimental evaluation to test the adequacy of these bounds on real world datasets. The key rule used in current frequent itemset mining algorithms, the anti-monotonicity rule, has been known to provide good bounds on the support of itemsets. We find that, for dense datasets, rules other than the anti-monotonicity rule provide tighter bounds on the support of itemsets. This leads to improved mining algorithms for this problem.
Two Aircraft TDOA/DD Passive Localization

A stationary electronic emitter can be located by two aircraft from Time Difference Of Arrival (TDOA) and Differential Doppler(DD) measurements. The algorithm and error analytic expression of localization are given. Several curves of constant TDOA and DD are shown. The comparison of localization based on TDOA and DD is presented. The result indicates the previous approach performance is better.
Decay of the lower-hybrid wave into an ion cyclotron mode and a whistler wave

The electrostatic lower-hybrid wave is shown to decay parametrically into a whistler wave and a resonant ion cyclotron mode or an ion cyclotron quasi-mode or a reactive quasi-mode. The convective threshold powers for these decay instabilities are found to be much larger than presently available pump powers. These decay instabilities, however, are expected to play an important role in the saturation of the parametrically excited short-wavelength lower-hybrid waves having frequency close to ωlh.
Speed and accuracy comparison of techniques to solve a binary quadratic programming problem with applications to synchronous CDMA

We compare methods for solving the NP-hard binary quadratic programming (BQP) problem. Various methods are discussed, including box-constrained quadratic programming, branch and bound, coordinate descent, group decision making and semi-definite relaxation. An algorithm from target-tracking, the probabilistic data association filter, is modified to the BQP application. Simulation results show that this and several other methods can significantly outperform the decision feedback detector (DFD) or its group counterpart, GDFD.
Variation of the sea surface drag coefficient with wind speed

Eddy correlation measurements of wind turbulence obtained at a sand spit on Sable Island, Nova Scotia, in winds ranging from gentle breeze to strong gale force agree with other recent measurements over water. There is a significant increase in the drag coefficient with wind speed which is well described by the equation of Charnock (1955). The heat transfer coefficient is slightly lower than the drag coefficient.
Mesh Parameterizations and Geometry Images

By using highly efficient image coding technique,geometry image becomes an important tool for compression and progressive representation of geometry data.The geometry images method was designed and implemented based on several classic mesh parameterizations:barycentric mapping parameterization,discrete conformal parameterization,discrete authalic parameterization,mean value coordinate parameterization and geometric-stretch parameterization.Experiments show that the geometric-stretch parameterization provides the best results on both PSNR values and reconstructive quality.
Ab initio modeling of surface structure for SrTiO 3 perovskite crystals

We present and discuss the results of calculations of ${\mathrm{SrTiO}}_{3}$ (100) surface relaxation and rumpling with two different terminations (SrO and ${\mathrm{TiO}}_{2}). $ These are based on ab initio Hartree-Fock method with electron correlation corrections and density functional theory calculations with different exchange-correlation functionals, including hybrid exchange techniques. Both approaches use the localized Gaussian-type basis set. All methods agree well on surface energies and on atomic displacements, as well as on considerable increase of covalency effects nearby the surface. More detailed experiments on surface rumpling and relaxation are necessary for further testing theoretical predictions.
Effect of Omitted Variable due to Misspecification Error inRegression Analysis

The practical problem is not why specification errors are made but how to detect them. There are number of tests for specification error in detecting the errors of omitted variables from a regression analysis. Using the observations on the dependent variables generated from Microsoft Excel according to the specification labeled true, a bootstrap simulation approach was used for the data generated for each of the models at different sample sizes 20, 30, 50, and 80 respectively each with 100 replications. Using bootstrapping experiment and some properties which estimators should possess if their estimates are to be accepted as good and satisfactory estimates of the parameters, namely, the bias, variance, mean square error, and root mean square error. The models investigated in the bootstrapping experiment consist of the problem of omitted variables. For the models considered, the experiment reveals that the estimated changes the effect of omitted variable as the coefficient varies in the different models. The effect of omitted variable becomes unstable which produces a bias and inconsistent
Estimating a Mixture of Efficiency Indices

In this paper we estimate parametric input and output distance functions as well as a mixture of input and output distance functions. The main advantage of the mixing model is that it lets the data determine the orientation of technical inefficiency, which is an open problem in efficiency analysis. Since estimates of technical inefficiency from the input and output distance functions are not directly comparable, we develop cross-indices that can be used to compute input (output) technical inefficiency from the estimates of output (input) distance function. These cross-indices are especially useful in the mixture model in which both the input and output distance functions are simultaneously estimated. The proposed technique is applied to a panel data on European Railways (1970-1994).
An autonomously recording inverted echo sounder: ARIES II

Abstract A self-contained instrument, the Autonomously Recording Inverted Echo Sounder (ARIES II), carrying two 250-kHz beam side-scan sonars and with the capacity to record sonar data sampled at 3.2 kHz for 168 h with the sonars operating with a pulse repetition rate of 2 Hz, has been constructed and tested in a mooring deployment that lasted for 25 days near the edge of the continental shelf west of Scotland. The mean water depth was 146 m. ARIES II was positioned at a mean transducer depth of 34.6 m with sonars directed upward at 20° to the horizontal to obtain acoustic returns from targets at or near the sea surface. The instrument was preprogrammed to record continuously over periods of 2, 4, and 13 h, the last to cover the M2 tidal cycle dominant in the area. Sonographs are presented to illustrate observations of surface waves and wave groups, internal solitons, rain showers, and Langmuir circulation. An analysis is made of the effects of surface waves, currents, and internal waves on the instrument.
Varying index varying bits substitution algorithm for the implementation of VLSB steganography

Variable least significant bits (VLSB) steganography is a pretty powerful and secure technique for data hiding in cover images, having variable data hiding capacity, signal-to-noise ratio, peak signal-to-noise ratio, and mean square error (MSE). This study presents a new algorithm for the implementation of VLSB steganography named varying index varying bits substitution (VIVBS). The VIVBS algorithm is a very secure, high capacity, flexible, and statistically unpredictable mechanism to conceal information in cover images. The method uses a secret stego-key comprising a reference point, and variation of the number of bits to be hidden with varying indices of pixels in the cover image. The secret key adds an extra feature of security to steganography, making it much immune to steganalysis. The VIVBS algorithm is capable of providing variable data hiding capacity and variable key size which can be changed by changing the range of least significant bits used. A data hiding capacity of 43.75% with a negligible MSE 14.67 dB has been achieved using the VIVBS algorithm. For larger data hiding capacity, the MSE and distortion increases significantly which make the existence of information predictable but the key size also increases significantly, making the retrieval of hidden information difficult for the unauthorized person.
User-Oriented Two-Dimensional Measure of Effectiveness for the Evaluation of Transport and Dispersion Models

Abstract A two-dimensional measure of effectiveness for comparing hazardous material transport and dispersion model predictions and field observations has been developed. This measure is used for comparing predictions and observations paired in space and time, and the components of this measure—overprediction, or false-positive fraction, and underprediction, or false-negative fraction—can illuminate strengths and weaknesses of a model in ways that many one-dimensional measures cannot. Comparisons of predictions of short-range field observations are used to illustrate features of this measure of effectiveness, including its computation based on dosages or based on a dosage threshold of interest. With this user-oriented measure of effectiveness, statistically significant resolution of transport and dispersion model performance differences as a function of downwind range and meteorological stability category grouping, as well as between different models, is described. Evaluation of probabilistic prediction o.
Seismic velocity model building by NIP-wave tomography — a case study in Iran

The Common-Reflection-Surface (CRS) stack accounts for local dip and curvature of reflectors in depth. Thus its stacking parameters carry far more information about the subsurface than conventional stacking velocity. This information allow us to provide a superior basis for subsequent applications. NIP-wave tomography inversion is one of these applications which uses NIP-wave curvature, emergence, angle and coherence for velocity inversion. In this paper we applied the CRS method on a complex structure in North East of Iran and then we performed the NIP-wave tomography inversion on this data set. The result clearly shows the usefulness of CRS attributes and the ability of this method for velocity model inversion.
A finite element-boundary element method for advection-diffusion problems with variable advective fields and infinite domains

In this paper a hybrid, finite element--boundary element method which can be used to solve for particle advection-diffusion in infinite domains with variable advective fields is presented. In previous work either boundary element, finite element, or difference methods have been used to solve for particle motion in advective-diffusive domains. These methods have a number of limitations. Due to the complexity of computing spatially dependent Green`s functions, the boundary element method is limited to domains containing only constant advective fields, and due to their inherent formulation, finite element and finite difference methods are limited to only domains of finite spatial extent. Thus, finite element and finite difference methods are limited to finite space problems for which the boundary element method is not, and the boundary element method is limited to constant advection field problems for which finite element and finite difference methods are not. In this paper it is proposed to split a domain into two sub-domains, and for each of these sub domains, apply the appropriate solution method; thereby, producing a method for the total infinite space, variable advective field domain.