Miracle-dz/UniFAR-FTUs huggingface dataset:
A localized artificial diffusivity method to simulate compressible multiphase flows using the stiffened gas equation of state

The development of numerical approaches to perform direct numerical simulations of compressible multiphase flows has been an active field of research for several years. Proper treatment of fluid interfaces is crucial as important physics occur in this infinitesimally small region. Furthermore, the compressibility of the fluid requires proper treatment of discontinuities. Artificial diffusivity is among a number of methods widely used for compressible flows. This study develops a general form of consistent artificial diffusion fluxes and extends the localized artificial diffusivity method for high‐order central schemes to solve multiphase flows with an interface‐capturing method. These fluxes ensure an oscillation‐free interface for pressure, velocity, and temperature without employing a sharpening technique. Moreover, the high‐order representation of all scales in the flow helps capture the wide range of instabilities inherent in these flows. The goal is to develop an approach capable of performing high‐fidelity simulations supported by physics‐driven validation. This is achieved by solving the five‐equation model with the stiffened‐gas equation of state using the proposed method for multicomponent and multiphase flows on a variety of 1D and 2D problems.
Local wellposedness of Maxwell systems with scalar-type retarded material laws

We study the local wellposedness in H for the system of Maxwell equations in a bounded domain equipped with perfectly conducting boundary conditions. The medium is described by a retarded and nonlinear expression for the polarisation having the property that the polarisation is always parallel to the electric eld. An example is the Kerr e ect in a homogeneous, isotropic and inversion-symmetric medium. The results are obtained using semigroup theory.
Real-Time Teleoperation of a Robot Arm for Self-Contact Bc

The mechanisms by which humans localize touch on their bodies are not yet fully understood. Specific manipulations of tactile localization are needed to improve understanding. One possibility is to exploit self-contact when humans slide over their skin surface, but use a robotic arm in the middle [1, 2]. However, current state-of-the-art studies lack the ecological conditions of free movement to investigate the influence of proprioception versus touch during self-touch by changing forward kinematic parameters [3]. This gap can be bridged by using a motion capture system in conjunction with a teleoperated robotic manipulator equipped with an artificial finger. This thesis focuses on the technical part, a real-time teleoperation task with the additional transformation of a motor-totouch gain, with latency minimized to levels indistinguishable for participants of an experiment as timing is crucial in such studies. It further emphasizes safety and usability, with thorough risk mitigation and the creation of a simple to use graphical user interface. The effectiveness of the tool was verified through pilot experiments, validating its potential to advance research in human sensory perception, which has a potential impact on the fields of humanrobot interaction, prosthetic design, and rehabilitation interventions.
Enhancing ProMoEE and DyVProMo with Additional Features to Foster Empirical Studies in the Context of Process Models Comprehension

Business Process Management (BPM) has become an important factor on management level for enterprises, as it offers the opportunity to increase productivity and lower cost. This has led to a wide use of BPM techniques in the industry, offering the ability to describe processes, improve and automate them or respond to changes quickly. In order to visually represent processes, notations are used. One of the most common is Business Process Model and Notation (BPMN), which is capable of displaying interconnected activities along with resources and other information. A process model that does not accurately represent the real world may lead to a reduction in above benefits. Therefore, enterprises have an interest in skilled experts creating high quality process models. In reality a lot of untrained personnel is involved in the modeling process. Hence, there is interest in efficient ways of helping novices to understand modeling languages. That is why research on the comprehension of process models is being conducted. One area of research is the addition of constructs to the existing notation. In particular, the coloring of modeling elements can help to distinguish and recognize them more easily. In this thesis two pre-existing applications dealing with the assistance of conducting research on modeling comprehension are fostered. One is an application to dynamically change the displayed model elements to reduce complexity or providing help with model element names through the addition of annotations. It is fostered by expanding its functionality to dynamically add predefined colors to the model elements, providing another way of supporting understanding. The other is a survey platform with the ability to create questionnaires including the functionality to view and edit process models. Hence, it aims at the conduction of empirical research on model comprehension. It is improved in its Maintainability, usability and Applicability. Moreover, the first application is fully integrated into the second one, providing the ability to use it for surveys in questionnaires.
Domain Generalization in Image Retrieval through Training Data Synthesis

Image retrieval based on deep neural networks relies on a large number of diverse training images. The challenge of severe visual appearance changes, specifically day–night and photo–sketch, is addressed using synthesized training images as a form of data augmentation. GANs are studied to learn image–to–image translation allowing to generate more training data of the scarce domain. For the day– night task, image representation is cast as metric learning and the GAN generator is used to generate diverse day–night pairs for the training. Various generator architectures are evaluated, including a novel lightweight GAN architecture that preserves the content between the original and synthesized images with edge consistency and simultaneously trains an edge detector to operate on both day and night images. For the photo–sketch task, no training sketches are available, which is tackled with an edge detector, that transforms photos into edge images, and then, the GAN generator is used to thin the edges that approximate sketch images. The proposed data augmentation approach outperforms prior work and improves over the current state–of– the–art Tokyo 24/7 day-night image retrieval benchmark while maintaining performance on the Oxford and Paris benchmarks. However, similar GAN–based augmentation does not surpass handcrafted augmentation used for sketch recognition.
Transverse to longitudinal phase space coupling in an electron beam for suppression of microbunching instability

The microbunching instability developed during the beam compression process in the linear accelerator (LINAC) of a free-electron laser (FEL) facility has always been a problem that degrades the lasing performance, and even no FEL is able to be produced if the beam quality is destroyed too much by the instability. A common way to suppress the microbunching instability is to introduce extra uncorrelated energy spread by the laser heater that heats the beam through the interaction between the electron and laser beam, as what has been successfully implemented in the Linac Coherent Light Source and Fermi@Elettra. In this paper, a simple and effective scheme is proposed to suppress the microbunching instability by adding two transverse gradient undulators (TGU) before and after the magnetic bunch compressor. The additional uncorrelated energy spread and the density mixing from the transverse spread brought up by the first TGU results in significant suppression of the instability. Meanwhile, the extra slice energy spread and the transverse emittance can also be effectively recovered by the second TGU. The magnitude of the suppression can be easily controlled by varying the strength of the magnetic fields of the TGUs. Theoretical analysis and numerical simulations demonstrate the capability of the proposed technique in the LINAC of an x-ray free-electron laser facility.
Model reduction by PCA and Kriging

Introduction In our approach a specific computationally-expensive CFD simulation or computer code, referred to as FullOrder Model (FOM) [1, 2], is treated as a black box that generates a certain output y (e.g. the temperature field) given a set of input parameters x (e.g. the equivalence ratio) and indicated by y = F (x). After enough observations of the FOM’s output are available, y(xi) ∀i = 1, . ,M, a Surrogate Model (SM) can be trained and the output y∗ for a particular set of unexplored inputs x∗ can be predicted without the need to evaluate F (x∗) and, thus, no simulation is run. This is very important in the context of optimization problems with expensive objective functions, e.g. design optimization in industrial applications. Principal Component Analysis (PCA) [3] can be used to find a new, smaller set of uncorrelated variables, often referred to as PCA scores, which is representative of the original variables of interest. Once these PCA scores are found, a SM can be built for each one of them, hence Reduced-Order (Surrogate) Models (ROMs). The Kriging interpolation method [4, 5] was chosen to find a response surface for these scores. The Kriging interpolation method was chosen over other regression techniques because of the encouraging results shown in [2, 6–8]. In the present work, the Kriging-PCA approach is extended to combustion applications. PCA For a data-set Y(M × N), containing M observations of N original variables, PCA finds a set of Principal Components (PCs), collected into a matrix A = {a1, a2, . } [3, 11–14]. The PCs are the eigenvectors of the data correlation matrix. Their eigenvalues represent the portion of the data variance that they account for. Thus, the PCs can be sorted in descent order of importance. Only the first few q < N PCs can be retained if
Elliptical instability of the Moore–Saffman model for a trailing wingtip vortex

In this paper, we investigate the elliptical instability exhibited by two counter-rotating trailing vortices. This type of instability can be viewed as a resonance between two normal modes of a vortex and an external strain field. Recent numerical investigations have extended earlier results that ignored axial flow to include models with a simple wake-like axial flow such as the similarity solution found by Batchelor (J. Fluid Mech., vol. 20, 1964, pp. 645–658). We present herein growth rates of elliptical instability for a family of velocity profiles found by Moore & Saffman (Proc. R. Soc. Lond. A, vol. 333, 1973, pp. 491–508). These profiles have a parameter $n$ that depends on the wing loading. As a result, unlike the Batchelor vortex, they are capable of modelling both the jet-like and the wake-like axial flow present in a trailing vortex at short and intermediate distances behind a wingtip. Direct numerical simulations of the linearized Navier–Stokes equations are performed using an efficient spectral method in cylindrical coordinates developed by Matsushima & Marcus (J. Comput. Phys., vol. 53, 1997, pp. 321–345). We compare our results with those for the Batchelor vortex, whose velocity profiles are closely approximated as the wing loading parameter $n$ approaches 1. An important conclusion of our investigation is that the stability characteristics vary considerably with $n$ and $W_{0}$ , a parameter measuring the strength of the mean axial velocity component. In the case of an elliptically loaded wing ( $n=0.50$ ), we find that the instability growth rates are up to 50 % greater than those for the Batchelor vortex. Our results demonstrate the significant effect of the distribution and intensity of the axial flow on the elliptical instability of a trailing vortex.
Diffraction grating strain gauge method: error analysis and its application for the residual stress measurement in thermal barrier coatings

Diffraction grating strain gauge (DGSG) is an optical strain measurement method. Based on this method, a six-spot diffraction grating strain gauge (S-DGSG) system has been developed with the advantages of high and adjustable sensitivity, compact structure, and non-contact measurement. In this study, this system is applied for the residual stress measurement in thermal barrier coatings (TBCs) combining the hole-drilling method. During the experiment, the specimen’s location is supposed to be reset accurately before and after the hole-drilling, however, it is found that the rigid body displacements from the resetting process could seriously influence the measurement accuracy. In order to understand and eliminate the effects from the rigid body displacements, such as the three-dimensional (3D) rotations and the out-of-plane displacement of the grating, the measurement error of this system is systematically analyzed, and an optimized method is proposed. Moreover, a numerical experiment and a verified tensile test are conducted, and the results verify the applicability of this optimized method successfully. Finally, combining this optimized method, a residual stress measurement experiment is conducted, and the results show that this method can be applied to measure the residual stress in TBCs.
Some Results on Weak KAM Theory for Time-periodic Tonelli Lagrangian Systems

Abstract This paper contributes several results on weak KAM theory for time-periodic Tonelli Lagrangian systems. Wang and Yan [Commun. Math. Phys. 309 (2012), 663-691] introduced a new kind of Lax-Oleinik type operator associated with any time-periodic Tonelli Lagrangian. Firstly, using the new operator we give an equivalent definition of the backward weak KAM solution. Then we prove a result on the asymptotic behavior of the new operators with an arbitrary continuous function as initial condition, by taking advantage of the definition mentioned above. Finally, for a specific class of time-periodic Tonelli Lagrangians, we discuss the rate of convergence of the new operators.
A Local Linear Regression Method Using a Discrete Kernel Function with Applications to Bond Curve Construction

Local linear regression is generally used to estimate the dependency of a random variable Y on another random variable X from a finite sample of data points. Except for the chosen kernel function, no model assumptions on the relationship between X and Y are taken into account in the estimation. In this paper, we show that discretizing the kernel function is consistent with a piecewise linear model assumption on the relationship between X and Y . Under certain boundary conditions, this relationship can be shown to be continuous. We apply the local linear regression with discretized kernel (LLRDK) to a problem from finance: the construction of a bond spread curve from a discrete set of observed bond market prices. The method we present comprises a valuation approach that combines a reference interest rate curve, survival probabilities from CDS markets and the statistical estimation of the bond CDS basis spreads using the LLRDK. This allows for the consistent combination of local linear regression as a statistical estimation method with model assumptions on the bond CDS spread such as a piecewise constant or piecewise linear dependency on time.
Multiple-instance ensemble learning for hyperspectral images

Abstract. An ensemble framework for multiple-instance (MI) learning (MIL) is introduced for use in hyperspectral images (HSIs) by inspiring the bagging (bootstrap aggregation) method in ensemble learning. Ensemble-based bagging is performed by a small percentage of training samples, and MI bags are formed by a local windowing process with variable window sizes on selected instances. In addition to bootstrap aggregation, random subspace is another method used to diversify base classifiers. The proposed method is implemented using four MIL classification algorithms. The classifier model learning phase is carried out with MI bags, and the estimation phase is performed over single-test instances. In the experimental part of the study, two different HSIs that have ground-truth information are used, and comparative results are demonstrated with state-of-the-art classification methods. In general, the MI ensemble approach produces more compact results in terms of both diversity and error compared to equipollent non-MIL algorithms.
Tunable multiband band-stop filter based on graphene metamaterial in THz frequency

ABSTRACT In this paper, a tunable multiband band-stop filter based on single-layer and few-layer doped periodically graphene rings is designed at THz wavelength. The performance of the proposed structure is calculated by using the finite-difference time-domain method. The metamaterial structure is comprised of the concentric graphene ring resonators printed on substrate layer of silica medium. The multiband band-stop filter can be achieved by adjusting the numbers of graphene ring resonator. More importantly, a dynamically tunable filter can be designed by adjusting the applied voltage or chemical potential doping to manipulate graphene’s Fermi energy. The z-component electric ﬁeld is investigated to explain the physical mechanism of the transmission. In addition, the proposed filter has the advantage of independence to polarization and insensitivity to the angles of the incident wave. Our design can have potential applications in various ﬁelds of tunable photonic devices, sensors and multi-band communication.
Research on relation model of optical camouflage similarity and identification probability of marine targets

Optical camouflage painting, as a basic measure against optical reconnaissance and optical sighting weapon attack, is a general method of optical camouflage of small vessels. By utilizing this method, we can design the camouflage pattern according to basic features of vessel background, paint the camouflage pattern to equipment target surface with camouflage coating, and imitate the natural background or the outline of segmentation targets in color and texture, thus reducing the exposure signs of equipment targets. Due to the fact that most of existing qualitative evaluations on camouflage effectiveness are quantitative evaluation or evaluation based on experts' judgment, this paper put forward a new evaluation method of optical camouflage effectiveness of marine target based on target identification probability and similarity between the target and the background, carried out practical measurement test on optical camouflage effectiveness of marine targets, and calculated quantitative camouflage evaluation results of 50 collected images according to actual contribution of feature indexes. A mathematic relation model of optical identification probability and similarity of marine targets was built after comparison with manual interpretation results of identification probability. The results indicate that: the higher the similarity, the lower the identification probability. If the target and background are totally different, the corresponding target identification probability is 1, which indicates that the lower the similarity, the more the exposure features of the target, and the easier the target to be detected; if the target and background are similar, the corresponding target identification probability is 0, which indicates that the higher the similarity, the less the exposure features of the target, and the more difficult the target to be detected.
Toward Education Quality Improvement in China: A Brief Overview of the National Assessment of Education Quality

This article is an overview of the National Assessment of Education Quality (NAEQ) of China in reading, mathematics, sciences, arts, physical education, and moral education at Grades 4 and 8. After a review of the background and history of NAEQ, we present the assessment framework with students’ holistic development at the core and the design for each subject used in the 2015–2017 assessment cycle. Technical details including item response modeling and the standard setting procedure are presented. We conclude with a discussion of the social impact, current issues, and future directions of national educational assessment.
Marching-on-in-Degree Time-Domain Integral Equation Solver for Transient Electromagnetic Analysis of Graphene

The marching-on-in-degree (MOD) time-domain integral equation (TDIE) solver for the transient electromagnetic scattering of the graphene is presented in this paper. Graphene’s dispersive surface impedance is approximated using rational function expressions of complex conjugate pole-residue pairs with the vector fitting (VF) method. Enforcing the surface impedance boundary condition, TDIE is established and solved in the MOD scheme, where the temporal surface impedance is carefully convoluted with the current. Unconditionally stable transient solution in time domain can be ensured. Wide frequency band information is obtained after the Fourier transform of the time domain solution. Numerical results validate the proposed method.
Symmetries in physics

The concept of symmetries in physics is briefly reviewed. In the first part of these lecture notes, some of the basic mathematical tools needed for the understanding of symmetries in nature are presented, namely group theory, Lie groups and Lie algebras, and Noether's theorem. In the second part, some applications of symmetries in physics are discussed, ranging from isospin and flavor symmetry to more recent developments involving the interacting boson model and its extension to supersymmetries in nuclear physics.
Credibility Theory and Geometry

: Vol. 11,2004 We present a geometric approach to studying greatest accuracy credibility theory. Our main tool is the concept of orthogonal projections. We show, for example, that to determine the Biihlmann credibility premium is to find the coefficients of the minimum-norm vector in an affine space spanned by certain orthogonal random variables. Our approach is illustrated by deriving various common credibility formulas. Several equivalent forms of the credibility factor Z are derived by means of similar triangles.
Non-thermal electron populations in microwave heated plasmas investigated with X-ray detectors

An investigation of the generation and dynamics of superthermal electrons in fusion plasma is carried out. A SDD+CsI(Tl) based X-ray diagnostic is constructed, characterized and installed at ASDEX Upgrade. In various plasma heating power and densities, the fraction and the energy distribution of the superthermal electrons is obtained by a bi-Maxwellian model and compared with Fokker-Planck simulations.
Region Based Image Retrieval Using Ratio of Proportional Overlapping Object

In Region Based Image Retrieval (RBIR), determination of the relevant block in query region is based on the percentage of image objects that overlap with each sub-blocks. But in some images, the size of relevant objects are small. It may cause the object to be ignored in determining the relevant sub-blocks. Therefore, in this study we proposed a system of RBIR based on the percentage of proportional objects that overlap with sub-blocks. Each sub-blocks is selected as a query region. The color and texture features of the query region will be extracted by using HSV histogram and Local Binary Pattern (LBP), respectively. We also used shape as global feature by applying invariant moment as descriptor. Experimental results show that the proposed method has average precision with 74%.