Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-excited Vibration Control of the Flexible Planar Parallel 3-RRR Robot

A self-excited vibration active control approach for a 3-RRR flexible planar parallel robot is developed to improve accuracy and stability. The 3-RRR parallel flexible robot experimental setup is constructed. From the motion experiments, it is demonstrated that the residual vibration can be converted to self-excited vibration at a high-speed motion, which will affect the stability and positioning precision of the platform. To suppress the self-excited vibration owing to flexibility, friction, backlash, coupling, and other nonlinear factors, a nonlinear controller and a fuzzy control algorithm are designed to attenuate the self-excited vibration. Experiments are conducted in different positions of the 3-RRR flexible parallel robot. The experimental results demonstrate that the investigated control methods can suppress the self-excited vibration effectively.
Étude de la production de paires de bosons W de même charge au LHC avec les données proton-proton à 8 TeV dans l'expérience CMS

This Master's thesis studies the same sign W bosons scattering process and aims to measure its cross section at the LHC using the proton-proton data at 8TeV in the center of mass in the CMS experiment. This rare process is key in probing the nature of electroweak symmetry breaking and is sensitive to Beyond the Standard Model theories. In September 2013, both the ATLAS and the CMS experiments had yet to go further than preliminary studies with regards to the measurement of the cross section studied in this thesis. We hereby demonstrate that one can isolate the same sign W bosons scattering process from the other W boson pairs production processes. By comparing data and simulations we determine the kinematic cuts necessary to isolate the events from the studied process. Several backgrounds cannot be overlooked, namely the W+jets, WZ and Z+jets backgrounds. After highlighting the fact that our simulations failed to estimate properly the W+jets background and that a slight gap between data and simulations is therefore induced, we also undertake a more detailed analysis of the Z+jets by developing a method allowing us to measure the probability of leptons charge misidenti cation in our data, which we compare to the probability measured in our simulations. On a technical side and althought it did not interfere with our analysis, we noticed a minor failure of the MadGraph software, which we reported to the parties involved.
5G on the Roads: Latency-Optimized Federated Analytics in the Vehicular Edge

Coordination among vehicular actors becomes increasingly important at the dawn of autonomous driving. With communication serving as the basis for this process, latency emerges as a critical limiting factor in information gathering, processing, and redistribution. While these processes have further implications on data privacy, they are also fundamental in safety and efficiency aspects. In this work, we target exactly these areas: we propose a privacy-preserving system for collecting and sharing data in high-mobility automotive environments that aims to minimize the latency of these processes. Namely, we focus on keeping high definition maps (highly accurate environmental and road maps with dynamic information) up-to-date in a crowd-sourced fashion. We employ federated analytics for privacy-preserving, low-latency, scalable processing and data distribution running over a two-tiered infrastructural layout consisting of mobile vehicular nodes and static nodes leveraging the low latency, high throughput and broadcast capabilities of the 5G edge. We take advantage of this setup by proposing queuing theory based analytical models and optimizations to minimize information delivery latency. As our numerical simulations over wide parameter-ranges indicate, the latency of timely data distribution can be decreased only with careful system planning and 5G infrastructure. We obtain the optimal latency characteristics in densely populated central metropolitan scenarios when Gb/s uplink speeds are achievable and the coverage area (map segment size) can reach a diameter of 1km.
SiZer inference for generalized varying coefficient models

ABSTRACT SiZer (significant zero crossings of derivatives) is an effective tool for exploring significant features in curves from the viewpoint of the scale space theory. In this paper, a SiZer approach is developed for generalized varying coefficient models (GVCMs) in order to achieve the task of understanding dynamic characteristics of the regression relationship at multiscales. The proposed SiZer method is based on the local-linear maximum likelihood estimation of GVCMs and the one-step estimation procedure is employed to alleviate the computational cost of estimating the coefficients and their derivatives at different scales. Simulation studies are performed to assess the performance of the SiZer inference and two real-world examples are given to demonstrate its applications.
Ritz–Galerkin method for solving an inverse problem of parabolic equation with moving boundaries and integral condition

ABSTRACT In this paper, we consider an inverse problem for parabolic equation with moving boundaries and integral condition. Existence and uniqueness are proved using tool from double-layer heat potential and Volterra integral equations of the second kind. For computation part, the Ritz–Galerkin method is first implemented to get an approximate solution of intermediate function H(x, t), and then based on relationships between H(x, t) and , respectively, numerical solutions of and u(x, t) are obtained. Finally, numerical examples are presented to show the validity and applicability of our method.
Tidal Dissipation in Extrasolar Planets

Tidal Dissipation in Extrasolar Planets Fernando Gabriel Peña Doctor of Philosophy Graduate Department of Astronomy & Astrophysics University of Toronto 2010 Many known extra-solar giant planets lie close to their host stars. Around 60 have their semi-major axes smaller than 0.05 AU. In contrast to planets further out, the vast majority of these close-in planets have low eccentricity orbits. This suggests that their orbits have been circularized likely due to tidal dissipation inside the planets. These exoplanets share with our own Jupiter at least one trait in common: when they are subject to periodic tidal forcing, they behave like a lossy spring, with a tidal “quality factor”, Q, of order 10. This parameter is the ratio between the energy in the tide and the energy dissipated per period. To explain this, a possible solution is resonantly forced internal oscillation. If the frequency of the tidal forcing happens to land on that of an internal eigenmode, this mode can be resonantly excited to a very large amplitude. The damping of such a mode inside the planet may explain the observed Q value. The only normal modes that fall in the frequency range of the tidal forcing (∼ few days) are inertial modes, modes restored by the Coriolis force. We present a new numerical technique to solve for inertial modes in a convective, rotating sphere. This technique combines the use of an ellipsoidal coordinate system with a pseudo-spectral method to solve the partial differential equation that governs the inertial oscillations. We show that, this technique produces highly accurate solutions when the density profile is smooth. In particular, the lines of nodes are roughly parallel to the ellipsoidal coordinate axes. In particular, using these accurate solutions, we estimate
Error boundedness of Correction Procedure via Reconstruction / Flux Reconstruction

We study the long time error behaviour of correction procedure via reconstruction / flux reconstruction methods to hyperbolic conservation laws. We show that not only the choice of the numerical flux (upwind or central) affects the growth rate and asymptotic value of the error, but also that the selection of bases (Gau{\ss}-Lobatto or Gau{\ss}-Legendre) is even more important. Using Gau{\ss}-Legendre basis, the error reaches the asymptotic value faster and to a lower value than by using Gau{\ss}-Lobatto basis. Also the differences in the error caused by the numerical flux is not essential for low resolution computations in the Gau{\ss}-Legendre case. This behaviour is best seen if a particular FR scheme is investigated which has a strong connection to the Discontinious Galerkin framework, but holds also for other flux reconstruction schemes with low order resolution computations.
A computational study of the effects of DC electric fields on non-premixed counterflow methane-air flames

Two-dimensional axisymmetric simulations for counterflow non-premixed methane-air flames were undertaken as an attempt to reproduce the experimentally observed electro-hydrodynamic effect, also known as the ionic wind effect, on flames. Incompressible fluid dynamic solver was implemented with a skeletal chemical kinetic mechanism and transport property evaluations. The simulation successfully reproduced the key characteristics of the flames subjected to DC bias voltages at different intensity and polarity. Most notably, the simulation predicted the flame positions and showed good qualitative agreement with experimental data for the current–voltage curve. The flame response to the electric field with positive and negative polarity exhibited qualitatively different characteristics. In the negative polarity of the configuration considered, a non-monotonic variation of the current with the voltage was observed, along with the existence of an unstable regime at an intermediate voltage level. With positive polarity, a typical monotonic current–voltage curve was obtained. This behavior was attributed to the asymmetry in the distribution of the positive and negative ions resulting from ionization processes. The present study demonstrated that the mathematical and computational models for the ion chemistry, transport, and fluid dynamics were able to describe the key processes responsible for the flame-electric field interaction.
Prediction and Impact Analysis of Passenger Flow in Urban Rail Transit in the Postpandemic Era

In the postpandemic era, exploring the relationship between the daily new COVID-19 cases and passenger flow in urban rail transit can help effectively predict the impact of future pandemic situations on rail transit. In this study, based on a gated recurrent unit (GRU) neural network model, the daily passenger flow in urban rail transit in the postpandemic era was predicted, and the results were compared with those obtained using the long short-term memory (LSTM) neural network and other conventional time series analysis models such as SARIMA (seasonal autoregressive integrated moving average). Based on the trained GRU model, a partial dependence plot (PDP) was adopted to explore the quantitative relationship between the daily passenger flow and the daily new cases or weather attribute. The results showed that (1) the prediction accuracy of the GRU neural network model was 95.25%, which was the highest among the prediction models studied, indicating that the GRU could achieve the best performance. (2) The GRU model did not fluctuate significantly in the initial training stage, and its convergence rate was higher than that of the LSTM. (3) The number of daily new cases was negatively correlated with the daily passenger flow. For every new case on the previous day, the daily passenger flow fell by an average of 54,600 person-times. (4) Compared with no rain condition, the daily passenger flow decreased by 207,600 person-times on an average on rainy days. In summary, the neural network could achieve accurate prediction, while the PDP could compensate for the “black box” disadvantage of nonparametric models, owing to which the quantitative relationship between the number of new cases and daily passenger flow could be successfully explored. Our study can serve as a basis for demand prediction, operational organization, and policy implementation related to urban rail transit.
An Introduction to Expressionism Analysis Based on Meaningful Deformation

In this paper, we present an application of meaningful contours in visual arts. Here, after defining the meaningful circular and polygonal contour and presenting functional definitions of meaningful contour based on fuzzy thinking, we examine the grounds for deformation in the style of Expressionism, and provide a method for its understanding and learning. This view can help the method for criticizing the works of Expressionism as well as the educational methods of this style from a different perspective. It is definitely important to us that the proposed methods can maintain the individuality and individual independence of the person in the creation of the artwork based on a meaningful geometry, without involving the audience in educational stereotypes. Given the wide scope of the discussion of this style, our work is definitely describing the theoretical preliminaries in the area of fuzzy thinking and deformation, and we will provide the extensive analysis of the outstanding works of this style in the future papers and other definitions. But at the end of this paper, we will have some examples of deformation in the history of art.
Journal of Information Technology Education Barriers for Students' Learning of Holistic Systems Development

Executive Summary Based on action research of the Information Processing (IP) course at the bachelor programme HA/DØK at Copenhagen Business School, we investigate which barriers students experience when learning holistic systems development and why. HA/DØK has been developed to educate students who can facilitate between users and programmers and navigate within and between the application (i.e. the users') and the problem (i.e. the IT system's) domain. However, a summative evaluation suggests a gap between the study programme's intention and the students' learning and performance at the IP exam. Our investigation of this gap reveals that while the students readily think and act in accordance with the problem domain they all struggle to achieve the learning objectives that concern the application domain. We propose that the students' difficulties arise as a consequence of how the study programme is designed and outline alternatives for helping them overcome the barriers and/or reach the learning objectives.
PPG Signals-Based Blood-Pressure Estimation Using Grid Search in Hyperparameter Optimization of CNN–LSTM

Researchers commonly use continuous noninvasive blood-pressure measurement (cNIBP) based on photoplethysmography (PPG) signals to monitor blood pressure conveniently. However, the performance of the system still needs to be improved. Accuracy and precision in blood-pressure measurements are critical factors in diagnosing and managing patients’ health conditions. Therefore, we propose a convolutional long short-term memory neural network (CNN–LSTM) with grid search ability, which provides a robust blood-pressure estimation system by extracting meaningful information from PPG signals and reducing the complexity of hyperparameter optimization in the proposed model. The multiparameter intelligent monitoring for intensive care III (MIMIC III) dataset obtained PPG and arterial-blood-pressure (ABP) signals. We obtained 75,226 signal segments, with 60,180 signals allocated for training data, 12,030 signals allocated for the validation set, and 15,045 signals allocated for the test data. During training, we applied five-fold cross-validation with a grid-search method to select the best model and determine the optimal hyperparameter settings. The optimized configuration of the CNN–LSTM layers consisted of five convolutional layers, one long short-term memory (LSTM) layer, and two fully connected layers for blood-pressure estimation. This study successfully achieved good accuracy in assessing both systolic blood pressure (SBP) and diastolic blood pressure (DBP) by calculating the standard deviation (SD) and the mean absolute error (MAE), resulting in values of 7.89 ± 3.79 and 5.34 ± 2.89 mmHg, respectively. The optimal configuration of the CNN–LSTM provided satisfactory performance according to the standards set by the British Hypertension Society (BHS), the Association for the Advancement of Medical Instrumentation (AAMI), and the Institute of Electrical and Electronics Engineers (IEEE) for blood-pressure monitoring devices.
An autocorrelation-based copula model for producing realistic clear-sky index and photovoltaic power generation time-series

This study presents a method for using copulas to model the temporal variability of the clear-sky index. The method utilizes the autocorrelation function and correlated outputs for $N$ time-steps are obtained. Results from the copula model are, in terms of distribution, autocorrelation, step changes and mean daily distribution, compared with the original data set and with an uncorrelated model based on random clear-sky index data. The copula model is shown to be superior to the uncorrelated model in all these aspects.
An implementation of Soft Set Theory in the Variables Selection Process for Corporate Failure Prediction Models. Evidence from NASDAQ Listed Firms

The foremost aim of this paper is to propose a reliable methodology regarding the selection process of financial ratios as input variables in the construction of corporate failure prediction models. In this paper soft set theory is introduced. In the first stage, emphasis is given on the state of liquidity as a measure for the classification of a group of NASDAQ listed firms in two a priori groups (failed and non-failed) using four liquidity criteria as follows: current ratio 1, current liabilities to total liabilities 70%, Equity to Liabilities 0 and Total Debt to Total Assets 70%. In the second stage, a parameter reduction algorithm is applied in order to determine, from a group of ratios, those which provide significant predictive power and optimize the classification accuracy of the model. A tabular representation of a soft set is constructed in order to select the input variables in the model based on the importance degree of each financial ratio. The findings show that the primary assumptions relevant to the definition of failure based on the soft set theory approach are confirmed, though the majority of the significant ratios in the applied sample of listed firms are related to the analysis of profitability.
FITTING AN ELLIPSE TO THE SET OF INTENSITY DATA POINTS OF VRANCEA EARTHQUAKES

Fitting an ellipse to the set of intensity data points of earthquakes occurred on 11.10. 1940, 07.04. 1977, 31.08. 1986, 30.05. 1990 and 31.05. 1990 is performed. Test criteria indicate that the ellipse smoothes the observed line of macroseismic field. For all earthquakes, focal axes of 5, 6 and 7 EMS-98 intensity zones are directed along the y-axis. For other zones are oriented along the parallels. This fact is one more acknowledgement of the anisotropy of a geophysical medium. Approximation of the set of points with an ellipse is performed using the method proposed by Fitzgibbon.
Analisis Sentimen Menggunakan Metode Naïve Bayes Untuk Mengetahui Respon Masyarakat Terhadap Vaksinasi

Media sosial merupakan suatu media yang sulit untuk lepas dari kehidupan sehari-hari saat ini, dimana setiap orang dapat dengan bebas berekspresi dan mengeluarkan isi pikirannya secara meluas di internet, dalam menghadapi pandemi COVID-19, Vaksinasi merupakan hal yang wajib dilakukan sebagai salah satu untuk memutuskan rantai penyebaran virus COVID-19, oleh karena itu informasi yang tersebar di media sosial mengenai vaksinasi juga perlu terjaga untuk mengurangi kekhawatiran masyarakat terhadap pandemi serta menjaga kelancaran vaksinasi yang sedang berjalan. Untuk mengetahui hal tersebut, diperlukan suatu studi analisis sentimen mengenai tanggapan masyarakat mengenai “vaksinasi”, dengan penelitian yang dilakukan ini untuk mengetahui bagaimana tanggapan masyarakat terhadap vaksinasi didapatkan bahwa banyak masyarakat yang mendukung serta menerima dengan baik vaksinasi dan hanya sedikit masyarakat yang menolak vaksinasi, pengukuran confusion matrix pada hasil klasifikasi juga dilakukan dengan hasil accuracy 84%, precision 95%, recall 85%, dan specificity 80%.
Equivariant Vector Bundles and Rigid Cohomology on Drinfeld's Upper Half Space over a Finite Field

Fix a finite field k and let X be Drinfeld's Upper Half Space over k of dimension n. Let S be the polynomial ring over k in n+1 variables, let G be the algebraic k-group scheme associated with the general linear group of degree n+1 and let Y=Proj S. Fix an algebraic action of G on Y. In the first part of this thesis, the global sections F(X) on X of a G-equivariant vector bundle F on Y are considered as a G(k)-representation. Due to a theorem of Orlik (2008), the computation of F(X) essentially reduces to the computation of the local cohomologies of F on Y with support in a k-rational closed subvariety Z. This local cohomology is considered as a representation of a certain parabolic subgroup P of G which stabilizes Z resp. of its Levi subgroup L. Three types of descriptions of these local cohomology modules are given: In the case where F arises from a representation of the stabilizer of a chosen base point of Y, a very general result on the structure of the local cohomology of F on Y with support in Z as an L-module is translated from Orlik's results. For general F, an even coarser strucutre result is proved by using an affine projection of Y onto Y-Z. In particular, when F equals the structure sheaf or a sheaf of differential forms on Y (resp. a Serre twist of either sheaf), this result is made very precise. In the case where the graded S-module associated with F is generated in degrees <2, a higher divided power version of the distribution algebra of G is used to for a more conceptual approach to the description of the local cohomologies mentioned in terms of the unipotent radical of P. In the second part of this thesis, the rigid cohomology of X is computed in two ways. The first method proceeds by computation of the rigid cohomology of the complement of X in Y (which is projective itself, thus its rigid cohomology is simply the de Rham cohomology of an associated rigid-analytic tube). Then application of the associated long exact sequence for rigid cohomology with proper supports yields the rigid cohomology of X. The second method proceeds by direct computation of the direct limit of the de Rham cohomologies of a certain cofinal family of strict open neighborhoods of the tube of X in the ambient rigid-analytic projective space. The resulting cohomology formula has been known since 2007, when Grose-Klonne proved that it is the same as the one obtained from l-adic cohomology using different methods.