Miracle-dz/UniFAR-FTUs huggingface dataset:
Finite volume and meshless algorithms for ideal magnetohydrodynamics

This thesis is devoted to the development of numerical frameworks for ideal magnetohydrodynamics (MHD) based on the finite volume and meshfree approaches. The principal contribution is a new flux splitting scheme based on wave-particle behaviour for solving compressible ideal MHD equations in one and two dimensions. This scheme referred to as Magneto-acoustic Wave Particle Splitting (MWPS) scheme exploits the idea that while ideal MHD equations are non-convex with non-homogeneous fluxes as opposed to their hydrodynamic counterparts, they exhibit an overall wave-like structure. The proposed approach therefore splits the flux vector into three distinct parts: the particle-like transport part and the wave-like pressure and magnetic parts. The pressure part of the fluxes satisfy homogeneity property and the split flux Jacobians are constructed with a provision to regulate the numerical dissipation. The magnetic part of the fluxes however is non-homogeneous and is treated using a central scheme with artificial viscosity. This tripartite treatment of the total flux vector results in a scheme with a central-upwind like character and in one-dimension has been extended to second-order spatial accuracy through the solution-dependent weighted least-squares approach for gradient calculations. The use of solution-dependent weights incorporates the effects of limiting and results in a bounded and higherorder accurate flux scheme. Unlike the one-dimensional (1D) finite volume flow solver, the development of two-dimensional (2D) MHD code is fraught with two challenges. These are consequence of the additional equation for the x-component of the magnetic field in two-dimensions where there are eight conserved variables as opposed to seven in 1D MHD flows. Firstly, the MWPS scheme does not extend “naturally” from one to two dimensions, requiring the use of a further splitting of the magnetic flux vector with the split magnetic fluxes treated using a central scheme with artificial dissipation. Secondly, the multi-dimensionality requires that the solenoidality condition on the magnetic field ∇ ·B = 0 be numerically enforced for physically consistent solutions. The latter issue has been dealt with using an approach analogous to the artificial compressibility method used to enforce the incompressibility constraint. Aptly known as Artificial Compressibility Analogy (ACA) approach, it employs an additional equation for a scalar potential whose solution allows the numerical divergence errors in the magnetic field to be radiated away. The equation for the scalar potential is clearly not a “physical” conservation law and is therefore solved using the Local Lax-Friedrichs scheme
Multi-Scale Spatial and Channel-wise Attention for Improving Object Detection in Remote Sensing Imagery

The spatial resolution of remote sensing images is continuously improved by the development of remote sensing satellite and sensor technology. Hence, background information in an image becomes increasingly complex and causes considerable interference to the object detection task. Can we pay as much attention to the object in an image as human vision does? This letter proposes a multi-scale spatial and channel-wise attention (MSCA) mechanism to answer this question. MSCA has two advantages that help improve object detection performance. First, attention is paid to the spatial area related to the foreground, and compared with other channels, more attention is given to the feature channel with a greater response to the foreground region. Second, for objects with different scales, MSCA can generate an attention distribution map that integrates multi-scale information and applies it to the feature map of the deep network. MSCA is a flexible module that can be easily embedded into any object detection model based on deep learning. With the attention exerted by MSCA, the deep neural network can efficiently focus on objects of different backgrounds and sizes in remote sensing images. Experiments show that the mean average precision of object detection is improved after the addition of MSCA to the current object detection model.
Adding Value to Value-Added: Theory and Applications to Teachers and Bureaucrats

Value-added estimators are extensively used to study teachers and other groups. In addition to estimating an individual’s causal impact on outcomes, value-added models describe the dispersion of individual effects: For example, variation in teacher quality contributes about 2% of the variance in their students’ same-year test scores. In this dissertation, I explore the use of value-added estimators in different contexts and discuss the statistical properties of these estimators. In the first chapter, I model teacher value-added as a vector encompassing teacher effects on many outcomes. The covariance matrix of teacher value-added reveals that teachers have large effects on high school graduation and future test scores, but that immediatelyobservable teacher effects are poor proxies for future effects. Teacher effects on attendance are about as persistent and as predictive of future achievement as teacher effects on test scores. In the second chapter, I discuss statistical issues that arise in finite samples. In the third chapter, joint with Jonas Hjort and Gautam Rao, I take an in-depth look at one context in which relatively small data induces finite-sample biases: the effects of bureaucrats on local economic outcomes in India. Although point estimates suggest that bureaucrat quality is an important determinant of variation in night light intensity and project completion, randomization inference shows that point estimates are biased upwards and insignificant.
Study of Satisfaction of Information System Users in Study Program (SIMPRODI) in Gorontalo State University

The rapid development of Information Technology (IT) today provides many conveniences in various forms of business, including the service business. System User Satisfaction (User satisfaction) is the response and feedback that the user raises after using the information system. This study aims to obtain empirical evidence regarding the use of SIMPRODI application products and how SIMPRODI can provide good services for students. The survey research method was carried out and the data collected was 252 data. The data was then analyzed by PLS-SEM. The results showed that the quality of the system did not have a significant effect on the SIMPRODI intention to use, but the quality of information and quality of service was significant on the intention to use, then when the intention to use was higher the user satisfaction was better and vice versa when the SIMPRODI user satisfaction was high then intention to use is also getting higher.
Local Appearance based Novel Facial Feature Extraction Method for Human Expression Recognition

A novel approach to extract the light invariant local feature for facial expression recognition is presented in this paper. It is robust in monotonic gray-scale changes caused by illumination variations. Proposed method is easy to perform and time effective. The local strength for a pixel is calculated by finding the decimal value of the neighboring of that pixel with the particular rank in term of its gray-scale value among all the nearest pixels. When eight neighboring pixels are considered, the gradient direction of the neighboring pixel with the mix of second minima and maxima of the gray scale intensity can capture more local details and yield the best performance for the facial expression recognition in our experiment. CK+ dataset is used in this experiment to find out the facial expression classification. The classification accuracy rate achieved is 92.1 ± 3.2%, which is not the best but easier to compute. The results show that the experimented feature extraction technique is fast, accurate and efficient for facial expression recognition.
EFFECTS OF UNFOLDING TECHNIQUES AS DESIGN STIMULI IN BUILDING DESIGN

Through paper folding techniques, i.e. origami, people can make fascinating 3D forms from 2D sheets. Many architects utilise folding techniques in their design process as design stimuli. However, the reverse process, unfolding 3D forms, presents computational geometry problems, and there is limited research that clarifies how designers can use theses unfolding techniques. In this study, we begin by introducing a computational geometry method for generating common developments by unfolding 3D plural cuboids. Next, this paper presents the results of an experiment where extended protocol analysis methods were used to examine the effects of using the unfolding techniques as design stimuli during concept generation. The results show that the unfolding techniques promote creativity in building design and enhance participants’ extension of idea space from the microscopic perspective.
Voronoi-Visibility Roadmap-based Path Planning Algorithm for Unmanned Surface Vehicles

In this paper, a novel Voronoi-Visibility (VV) path planning algorithm, which integrates the merits of a Voronoi diagram and a Visibility graph, is proposed for solving the Unmanned Surface Vehicle (USV) path planning problem. The VM (Voronoi shortest path refined by Minimising the number of waypoints) algorithm was applied for performance comparison. The VV and VM algorithms were compared in ten Singapore Strait missions and five Croatian missions. To test the computational time, a high-resolution, large spatial dataset was used. It was demonstrated that the proposed algorithm not only improved the quality of the Voronoi shortest path but also maintained the computational efficiency of the Voronoi diagram in dealing with different geographical scenarios, while also keeping the USV at a configurable clearance distance c from coastlines. Quantitative results were generated by comparing the Voronoi, VM and VV algorithms in 2,000 randomly generated missions using the Singapore dataset.
Using the Prognostic Score to Reduce Heterogeneity in Observational Studies

In large sample observational studies, the control population often greatly outnumbers the treatment population. Typical practice is to match several control observations to a single treated observation, with the goal of reducing variability of the resulting treatment effect estimate. However, increasing the control to treated ratio yields diminishing returns in terms of variance reduction and in practice leads to poorer quality matches. In line with Rosenbaum's argument on the importance of reducing heterogeneity to strengthen causal inference against unobserved bias, we suggest first expending some of the controls to fit a prognostic model, then matching with the resulting prognostic score to produce matched sets with lower heterogeneity. We propose methodological alternatives for fitting the prognostic model that help avoid concerns of overfitting and extrapolation, then we demonstrate in a simulation setting how this alternative use of the control observations can lead to gains in terms of both treatment effect estimation and design sensitivity.
Adaptive Nonlinear Hierarchical Control for a Rotorcraft Transporting a Cable-Suspended Payload

Rotorcrafts, with satisfactory maneuver performance and ability under complex terrains unreachable for ground robots, are playing important roles for goods transportation. In this article, we focus on the control of the cable-suspended transportation way due to its lower costs and more agility of the rotorcraft’s rotational motion. Compared with traditional crane systems and single rotorcrafts without loads, the aerial transportation system presents “double” underactuated property, stronger system nonlinearity, and more complex dynamic coupling, which are huge challenges for control schemes design. Meanwhile, aerial transportation usually suffers from external disturbances and uncertainties presented with aerodynamic damping coefficients and rope length. Additionally, overshoots of the rotorcraft’s position are potential threats for flight safety, especially in confined and complex environments. To address these problems, a novel adaptive control scheme is designed, which ensures effective rotorcraft positioning and payload swing suppression with restricted overshoot amplitudes. Asymptotic results are obtained with rigorous theoretical derivations provided by the Lyapunov-based stability analysis and LaSalle’s invariance theorem. Real-time experiments are performed to validate the effectiveness of the proposed control scheme even in the presence of external disturbances. To the best of our knowledge, this is the first method designed for aerial transportation systems which achieves simultaneous rotorcraft positioning and swing suppression, together with insurance for overshoot restriction even in the presence of parametric uncertainties.
Wavelength Scaling of Laser Wakefield Acceleration for the EuPRAXIA Design Point

Scaling the particle beam luminosity from laser wakefield accelerators to meet the needs of the physics community requires a significant, thousand-fold increase in the average power of the driving lasers. Multipulse extraction is a promising technique capable of scaling high peak power lasers by that thousand-fold increase in average power. However, several of the best candidate materials for use in multipulse extraction amplifiers lase at wavelengths far from the 0.8–1.0 μm region which currently dominates laser wakefield research. In particular, we have identified Tm:YLF, which lases near 1.9 µm, as the most promising candidate for high average power multipulse extraction amplifiers. Current schemes to scale the laser, plasma, and electron beam parameters to alternative wavelengths are unnecessarily restrictive in that they stress laser performance gains to keep plasma conditions constant. In this paper, we present a new and more general scheme for wavelength scaling a laser wakefield acceleration (LWFA) design point that provides greater flexibility in trading laser, plasma, and electron beam parameters within a particular design point. Finally, a multipulse extraction 1.9 µm Tm:YLF laser design meeting the EuPRAXIA project’s laser goals is discussed.
Optimisation of wind turbine blade structures using a genetic algorithm

The current diminution of fossil-fuel reserves, stricter environmental guidelines and the world’s ever-growing energy needs have directed to the deployment of alternative renewable energy sources. Among the many renewable energies, wind energy is one of the most promising and the fastest growing installed alternative-energy production technology. In order to meet the production goals in the next few decades, both significant increases in wind turbine installations and operability are required, while maintaining a profitable and competitive energy cost. As the size of the wind turbine rotor increases, the structural performance and durability requirements tend to become more challenging. In this sense, solving the wind turbine design problem is an optimization problem where an optimal solution is to be found under a set of design constraints and a specific target. Seen the world evolution towards the renewable energies and the beginning of an implementation of a local wind industry in Quebec, it becomes imperative to follow the international trends in this industry. Therefore, it is necessary to supply the designers a suitable decision tool for the study and design of optimal wind turbine blades. The developed design tool is an open source code named winDesign which is capable to perform structural analysis and design of composite blades for wind turbines under various configurations in order to accelerate the preliminary design phase. The proposed tool is capable to perform a Pareto optimization where optimal decisions need to be taken in the presence of trade-offs between two conflicting objectives: the annual energy production and the weight of the blade. For a given external blade shape, winDesign is able to determine an optimal composite layup, chord and twist distributions which either minimizes blade mass or maximizes the annual energy production while simultaneously satisfying design constraints. The newly proposed graphical tool incorporates two novel VCH and KGA techniques and is validated with numerical simulation on both mono-objective and multi-objective optimization problems.
Analysis of Compressed CSI Feedback in MISO Systems

Compressed sensing based channel state information (CSI) feedback schemes have been investigated as a feasible solution for massive antenna systems. Most of research works have focused on the measurement matrix design based on the sparsity obtained from spatially correlated channels. In this letter, we analyze the feasibility of a compressed CSI feedback based on the sparsity obtained from temporally correlated channels. The compressed feedback distortion and its rate loss in temporally correlated channels are analyzed as a function of the sparsity level and the number of transmit antennas, which are compared to those in uncorrelated channels. Based on the numerical analysis and simulation results, it is demonstrated that utilizing the sparsity obtained from temporally correlated channels is feasible for the compressed CSI feedback.
Multi-Matrices Low-Rank Decomposition With Structural Smoothness for Image Denoising

In this paper, we propose a multi-matrices low-rank decomposition method for image denoising. In this new method, the total variation (TV) norm is incorporated into low-rank approximation analysis to achieve structural smoothness and to improve quality of the recovered images. Our proposed mathematical framework for multi-matrices low-rank decomposition combines the nuclear norm, TV norm, and $\mathcal {L}_{1}$ norm, which allows us to exploit the low-rank property of natural images, enhance the structural smoothness, and detect and remove large sparse noise. Based on the iterative alternating direction method, we develop an algorithm to solve the proposed challenging optimization problem. We conduct extensive experiments and perform evaluations on multi-images denoising and multi-frames video prediction. Our experimental results demonstrate that the proposed method outperforms the state-of-the-art low-rank matrix recovery methods, particularly for images with large sparse noise.
Development of maximally reusable grammars: Parallel development of Hebrew and Arabic grammars

We show how linguistic grammars of two different yet related languages can be developed and implemented in parallel, with language-independent fragments serving as shared resources, and language-specific ones defined separately for each language. The two grammars in the focus of this paper are of Modern Hebrew and Modern Standard Arabic, and the basic infrastructure, or core, of the grammars is based on "standard" HPSG. We identify four types of relations that exist between the grammars of two languages and demonstrate how the different types of relations can be implemented in parallel grammars with maximally shared resources. The examples pertain to the grammars of Modern Hebrew and Modern Standard Arabic, yet similar issues and considerations are applicable to other pairs of languages that have some degree of similarity.
Price-Based Bandwidth Allocation for Backscatter Communication With Bandwidth Constraints

Recently proposed Bluetooth low energy (BLE)-backscatter allows interference-free transmission by locally generating a sub-carrier for frequency shifting (FS). Motivated by the BLE backscatter, in this paper, we investigate the price-based bandwidth allocation for multi-user backscatter communication (BackCom), where multiple BackCom users are allocated to different non-overlapping sub-channels and all users share the whole spectrum in a frequency division multiple access (FDMA) manner. Each BackCom user is charged by the primary user (PU) in the same sub-channel for a price, which is proportional to the allocated bandwidth and can be viewed as the cost for bandwidth sharing. A Stackelberg game is formulated to study joint maximization of the revenue of PUs and the utility function of each BackCom user subject to the total bandwidth constraint on the PUs and the individual bandwidth constraints on each BackCom user. Stackelberg Equilibriums (SEs) for two proposed schemes are investigated in closed-form expressions. Simulation results confirm the effectiveness of proposed schemes in improving the revenue performance of PUs and the sum capacity performance of BackCom users.
Adiabatic circuits for power-constrained cryptographic computations

This thesis tackles the need for ultra-low power operation in power-constrained cryptographic computations. An example of such an application could be smartcards. One of the techniques which has proven to have the potential of rendering ultra-low power operation is ‘Adiabatic Logic Technique’. However, the adiabatic circuits has associated challenges due to high energy dissipation of the Power-Clock Generator (PCG) and complexity of the multi-phase power-clocking scheme. Energy efficiency of the adiabatic system is often degraded due to the high energy dissipation of the PCG. In this thesis, nstep charging strategy using tank capacitors is considered for the power-clock generation and several design rules and trade-offs between the circuit complexity and energy efficiency of the PCG using n-step charging circuits have been proposed. Since pipelining is inherent in adiabatic logic design, careful selection of architecture is essential, as otherwise overhead in terms of area and energy due to synchronization buffers is induced specifically, in the case of adiabatic designs using 4-phase power-clocking scheme. Several architectures for the Montgomery multiplier using adiabatic logic technique are implemented and compared. An architecture which constitutes an appropriate trade-off between energy efficiency and throughput is proposed along with its methodology. Also, a strategy to reduce the overhead due to synchronization buffers is proposed. A modification in the Montgomery multiplication algorithm is proposed. Furthermore, a problem due to the application of power-clock gating in cascade stages of adiabatic logic is identified. The problem degrades the energy savings that would otherwise be obtained by the application of power-clock gating. A solution to this problem is proposed. Cryptographic implementations also present an obvious target for Power Analysis Attacks (PAA). There are several existing secure adiabatic logic designs which are proposed as a countermeasure against PAA. Shortcomings of the existing logic designs are identified, and two novel secure adiabatic logic designs are proposed as the countermeasures against PAA and improvement over the existing logic designs.