Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of continuous‐time nonlinear systems by using a gaussian process model

This paper deals with a nonparametric identification of continuous‐time nonlinear systems by using a Gaussian process model. Genetic algorithm is applied to train the Gaussian process prior model by minimizing the negative log marginal likelihood of the identification data. The nonlinear term of the objective system is estimated as the predictive mean function of the Gaussian process, and the confidence measure of the estimated nonlinear function is given by the predictive covariance function of the Gaussian process. Copyright © 2008 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
A new algorithm for signal reconstruction from the phase of bispectrum, and its applications in image enhancement

There are applications in signal processing where the bispectrum magnitude of the source signal is distorted while the phase remains clean or shifts linearly. Many different algorithms have been developed, to reconstruct a signal from both the magnitude and phase of its bispectrum. We introduce an iterative scheme, the bispectrum iterative reconstruction algorithm (BIRA), for reconstruction of FIR sequence from the phase of the bispectrum. Then we propose procedures to optimize BIRA algorithm and introduce a new algorithm named adaptive BIRA (ABIRA). Finally, we reconstruct an image which convolved with a linear phase channel and also an image that had been corrupted by additive white Gaussian noise.
A Propriety Multiplatform Game-Based Learning Game to Learn Object-Oriented Programming

In order to understand the important of object-oriented programming in tertiary level, a propriety game-based learning multiplatform game has been designed and develops as a learning tool to improve the student understanding toward object-oriented programming paradigm such as encapsulation, abstraction, inheritance and polymorphism. The proposed game is a 2D role-playing game in computer and mobile platform that allow players to learn Object-Oriented programming in an interaction way. Players will play along the flow of each game world and they will learn object-oriented programming paradigm subconsciously. Total of 214 undergraduate year one student had been participate to this research to determine the proposed game that design based on game-based learning approach is able to improve their understanding toward object-oriented programming paradigm compare to the traditional teaching and learning method. Thus, this paper is a research paper of an academic who worked with game designers, game developer to design and develop a propriety game-based learning game for learning object-oriented programming.
Experimental evaluations of RSS threshold-based optimised DV-HOP localisation for wireless ad-hoc networks

DV-HOP is a well-known connectivity-based range-free scheme which offers a cost-effective localisation solution for resource-constrained wireless ad-hoc and sensor networks. However, it generates a prominent amount of error with small-scale networks due to its multi-hop nature. To minimise the error and to make it applicable to both small- and large-scale networks, it is proposed to configure the connectivity of the network using available received signal strength (RSS) measurements and a predefined RSS threshold. An approximate formula for the optimal RSS threshold value that shows the minimum amount of error for a particular network to be localised is derived as a function of the total number of nodes and the network size. Experimental results confirm that utilising the proposed RSS threshold-based connectivity configuration significantly improves the localisation accuracy of DV-HOP in a practical environment without any extra hardware.
The ages of mutations in gene trees

Under the infinitely many sites mutation model, the mutational history of a sample of DNA sequences can be described by a unique gene tree. We show how to find the conditional distribution of the ages of the mutations and the time to the most recent common ancestor of the sample, given this gene tree. Explicit expressions for such distributions seem impossible to find for the sample sizes of interest in practice. We resort to a Monte Carlo method to approximate these distributions. We use this method to study the effects of variable population size and variable mutation rates, the distribution of the time to the most recent common ancestor of the population and the distribution of other functionals of the underlying coalescent process, conditional on the sample gene tree.
Triple‐pendulum vibration isolation system for a laser interferometer

We have developed a triple‐pendulum vibration isolation system for suspended mirrors used in a laser interferometer for gravitational wave detection. Owing to the passive damping method using high‐performance permanent magnets, the system has a very simple, compact structure. We measured the isolation ratio for vibration below 40 Hz and confirmed that the observed and calculated values are in good agreement. The stability of the system has been demonstrated by operating a Michelson laser interferometer incorporated with a mirror mounted on the vibration isolation system.
Optical microscope tomography. I. Support constraint

A new principle of tomographic optical microscope imaging has been developed that uses a computerized reconstruction algorithm and a transmission optical microscope. A conventional transmission microscope with a rotationally oblique illumination system provides projections of a thick specimen in various directions within the numerical aperture of the objective lens. The images obtained are combined to reconstruct a three-dimensional distribution of the sample by inverting the imaging system in a computer. The three-dimensional optical transfer function of this projection system is analyzed, and it is found that this system is strictly angularly band limited. For improving the spatial resolution we utilize a priori knowledge of the spatial extent of the object as the support constraint. Experimental results are presented to demonstrate the tomographic imaging capability of this principle.
Varstab: a procedure for determining homoscedastic transformations of multivariate normal populations

Gnanadesikan 1977 illustrates the utility of the power transformations considered by Moore and Tukey (1954) Box and Cox (1964), and Andrews, Gnanadesikan, and Warner (1971). These transformations have been used to obtain and assess both the marginal and joint normality of the underlying distributions. This paper investigates the utility of this procedure in defining homoscedastic transformations in multivariate populations.
Automatic registration method for multisensor datasets adopted for dimensional measurements on cutting tools

Multisensor systems with optical 3D sensors are frequently employed to capture complete surface information by measuring workpieces from different views. During coarse and fine registration the resulting datasets are afterward transformed into one common coordinate system. Automatic fine registration methods are well established in dimensional metrology, whereas there is a deficit in automatic coarse registration methods. The advantage of a fully automatic registration procedure is twofold: it enables a fast and contact-free alignment and further a flexible application to datasets of any kind of optical 3D sensor. In this paper, an algorithm adapted for a robust automatic coarse registration is presented. The method was originally developed for the field of object reconstruction or localization. It is based on a segmentation of planes in the datasets to calculate the transformation parameters. The rotation is defined by the normals of three corresponding segmented planes of two overlapping datasets, while the translation is calculated via the intersection point of the segmented planes. First results have shown that the translation is strongly shape dependent: 3D data of objects with non-orthogonal planar flanks cannot be registered with the current method. In the novel supplement for the algorithm, the translation is additionally calculated via the distance between centroids of corresponding segmented planes, which results in more than one option for the transformation. A newly introduced measure considering the distance between the datasets after coarse registration evaluates the best possible transformation. Results of the robust automatic registration method are presented on the example of datasets taken from a cutting tool with a fringe-projection system and a focus-variation system. The successful application in dimensional metrology is proven with evaluations of shape parameters based on the registered datasets of a calibrated workpiece.
The solar diameter and oblateness measured by the solar disk sextant on the 1992 September 30 balloon flight

This paper reports the results of a balloon flight of the Solar Disk Sextant (SDS) on 1992 September 30. This was the first flight in which the SDS used a wedge assembly fabricated by molecular contact in order to eliminate the wedge angle variations observed in previous flights. The instrument performed as designed. The main results obtained are values of the solar diameter for a number of discrete heliocentric latitudes, and the solar oblateness. The accuracy of the diameter values is better than 0.2 sec whereas the precision is approximately 1-2 mas. The equatorial solar diameter, at 1 AU, was 1919.06 sec +/- 0.12 sec, and the oblateness epsilon = 8.63 +/- 0.88 x 10(exp -6).
Thermal Stresses in an Infinite Elastic Pipe Weakened by a Finite Cylindrical Crack

Axially symmetric thermal stresses in the vicinity of a finite cylindrical crack in an elastic pipe are calculated. The surfaces of the crack are assumed to be insulated. The outer surface of the pipe is heated so as to maintain a constant temperature T d , and the inner surface of the pipe is cooled so as to maintain a constant temperature T b . Expressions developed by Sharma are used to solve the problem. Stress intensity factors are defined and calculated numerically for several configurations of the pipe.
A PREDICTED PEDESTAL EFFECT FOR PULSE PROPAGATION IN CONSTANT‐Q SOLIDS

Under the assumption of almost constant‐Q behavior of solids over a wide range of frequencies, together with some meaningful assumptions about the linear frequency behavior of the attenuation function, we have been able to obtain theoretical expressions describing the waveform distortion of an impulse‐excited plane wave as it decays and spreads on passing through large distances of the solid. When typical values for the parameters (as obtained from laboratory model or short range field experiments) for a solid having a mechanical Q of about 50 are used, the resulting waveforms at first glance appear to have a simple and not unexpected behavior. The peak amplitude of the waveform in the time domain varies roughly with the inverse of the square of the travel distance (this includes an inverse first power due to geometrical spreading). Also, a spreading of the waveform occurs that varies roughly linearly with the travel distance. This spreading is such that a positive impulse simply broadens as it travels wi.
Dark mass moments

Paczynski B. (1986, Astrophys. J., 304) has shown how to detect the dark constituents of the halo of our Galaxy, should their mass lie in the approximate domain 10 −6 < M/M ○. < 0.1. Massive Halo Objects, when crossing close to the line-of-sight of a more distant and fixed star, would gravitationally microlense its image, resulting in a time-dependent achromatic magnification with a predictable shape. Observations now in preparation will monitor ∼10 6 stars in the Large Magellanic Cloud during ∼1 yr. Barring unsuspected backgrounds, these observations will establish or exclude a halo dark mass constituency in the quoted mass ranges.
Asymptotic Properties of Estimators for the Parameters of Spatial Inhomogeneous Poisson Point Processes

Consider a spatial point pattern realized from an inhomogeneous Poisson process on a bounded Borel set , with intensity function λ (s; θ), where . In this article, we show that the maximum likelihood estimator and the Bayes estimator are consistent, asymptotically normal, and asymptotically efficient as the sample region . These results extend asymptotic results of Kutoyants (1984), proved for an inhomogeneous Poisson process on [0, T] , where T →∞. They also formalize (and extend to the multiparameter case) results announced by Krickeberg (1982), for the spatial domain . Furthermore, a Cramér–Rao lower bound is found for any estimator of θ. The asymptotic properties of and are considered for modulated (Cox (1972)), and linear Poisson processes.
Role of ionization fraction on the surface roughness, density, and interface mixing of the films deposited by thermal evaporation, dc magnetron sputtering, and HiPIMS: An atomistic simulation

We explore the effect of ionization fraction on the epitaxial growth of Cu film on Cu (111) substrate at room temperature. We compare thermal evaporation, dc magnetron sputtering (dcMS) and high power impulse magnetron sputtering (HiPIMS). Three deposition conditions i.e. fully neutral, 50% ionized and 100% ionized flux were considered as thermal evaporation, dcMS and HiPIMS, respectively, for ~20000 adatoms. It is shown that higher ionization fraction of the deposition flux leads to smoother surfaces by two major mechanisms i.e. decreasing clustering in the vapor phase and bi-collision of high energy ions at the film surface. The bi-collision event consists of local amorphization which fills the gaps between islands followed by crystallization due to secondary collisions. We found bi-collision events to be very important to prevent island growth to become dominant and increase the surface roughness. Regardless of the deposition method, epitaxial Cu thin films suffer from stacking fault areas (twin boundaries) in agreement with recent experimental results. In addition, HiPIMS deposition presents considerable interface mixing while it is negligible in thermal evaporation and dcMS deposition, those present less adhesion accordingly.
Microwave Tunable Components and Subsystems Based on Ferroelectrics: Physics and Principles of Design

The most promising microwave ferroelecric device is a ferroelectric phase shifter, aimed to be an element of a phased-array antenna. The following characteristics of the phase shifter are important: microwave insertion loss, range of operational temperatures, life time. Designing microwave tunable components is based on carefully developed models of ferroelectrics and appropriate software of the circuit design. The quality of a phase shifter is determined by the figure of merit ( F ) defined as a ratio phase shift/insertion loss and measured in deg/dB. For competitive applications one needs F = 200-300 deg/dB. An extended temperature range of operation is urgently required. There are the following ways of improvement of the ferroelectric phase shifters: i) utilizing an appropriate chemical compound of ferroelectric material, ii) developing the structure of the device, for example, the film with a variable composition factor, iii) application of the digital mode of operation.
Neural-Attention-Based Deep Learning Architectures for Modeling Traffic Dynamics on Lane Graphs

Deep neural networks can be powerful tools, but require careful application-specific design to ensure that the most informative relationships in the data are learnable. In this paper, we apply deep neural networks to the nonlinear spatiotemporal physics problem of vehicle traffic dynamics. We consider problems of estimating macroscopic quantities (e.g., the queue at an intersection) at a lane level. First-principles modeling at the lane scale has been a challenge due to complexities in modeling social behaviors like lane changes, and those behaviors’ resultant macro-scale effects. Following domain knowledge that upstream/downstream lanes and neighboring lanes affect each others’ traffic flows in distinct ways, we apply a form of neural attention that allows the neural network layers to aggregate information from different lanes in different manners. Using a microscopic traffic simulator as a testbed, we obtain results showing that an attentional neural network model can use information from nearby lanes to improve predictions, and, that explicitly encoding the lane-to-lane relationship types significantly improves performance. We also demonstrate the transfer of our learned neural network to a more complex road network, discuss how its performance degradation may be attributable to new traffic behaviors induced by increased topological complexity, and motivate learning dynamics models from many road network topologies.
Comment Generation System for Program Procedure Learning

We have constructed a learning system, by organizing procedures, for learning program creation. However, manually creating procedures used for learning systems requires a significant amount of time. In this study, in addition to the automatic generation of program procedures using natural language processing technology, we generate new program content and procedures by learning program lists and comments through deep learning LSTM.
Detection of O2 dayglow emission from Mars and the Martian ozone abundance

High-resolution spectroscopy of Mars in the vicinity of 1.27 microns has revealed the presence of emission lines of O2 which are interpreted as the result of production of O2(1 delta g) in the ultraviolet photolysis of Martian ozone. In the equatorial region of Mars, the dayglow intensity implies an ozone abundance near 0.2 microatm, which seems consistent with theoretical models which utilize the measured water-vapor abundance. A much larger ozone abundance exists in the atmosphere at high winter latitude, in agreement with direct measurement of ozone absorption performed by the Mariner spacecraft.
Experimental and simulation study of breakdown voltage enhancement of AlGaN/GaN heterostructures by Si substrate removal

The breakdown mechanism in GaN-based heterostructures (HFETs) grown on silicon substrate is investigated in detail by TCAD simulations and silicon substrate removal technique. High-voltage electrical measurements show that the breakdown voltage saturates for larger gate-drain distances. This failure mechanism is dominated by the avalanche breakdown in the Si substrate. High-voltage TCAD simulations of AlGaN/GaN/Si substrate structures show higher impact ionization factor and electron density at the Si interface indicating a leakage current path where avalanche breakdown occurs. Experimentally, by etching off the Si substrate the breakdown voltage no longer saturates and linearly increases for all gate-drain gaps. We propose the silicon removal technique as a viable way to enhance the breakdown voltage of AlGaN/GaN devices grown on Si substrate.
PARABOLIC POINTS AND ZETA-FUNCTIONS OF MODULAR CURVES

In this paper we obtain explicit formulas for the values at the center of the critical strip of Dirichlet series connected with weight 2 parabolic forms of the group Γ0(N). In particular, these formulas allow us to verify the Birch-Swinnerton-Dyer conjecture on the order of a zero for uniformizable elliptic curves over certain Γ-extensions. We also give applications to noncommutative reciprocity laws.
Statistical pattern recognition using Gaussian copula

Statistical pattern recognition has attracted great interest due to its applicability and to the advances in technology and computing. Significant research has been done in areas such as automatic character recognition, medical diagnostics, and data mining. The classical discrimination rule for pattern recognition assumes normality. However, in real life this assumption is often questionable. In some situations, the pattern vector is a mixture of discrete and continuous random variables. In this article, we use copula densities to model class conditional distribution for pattern recognition with Bayes’ decision rule. These types of densities are useful when the marginal densities of a pattern vector are not normally distributed. Those models are also useful for mixed pattern vectors. We also did simulations to compare the performance of the copula-based classifier with classical normal distribution based model and the independent-assumption-based model.
THE DUST SURROUNDING W HYDRAE

Dust shells surrounding the star W Hydrae have been resolved and measured at a wavelength of 11.15 μm, using the Infrared Spatial Interferometer. Two different models for the star and dust shells are used to fit the data, one for recent data taken over short time spans and another for the combined data of 15 years. Modeling of the data shows the presence of two dust shells with diameters of approximately 100 mas and 250 mas. The inner dust shell is seen to expand over the year 2008. The observations are consistent with a stellar diameter of 50 mas.
Deep subsurface waveguides with circular cross section produced by femtosecond laser writing

A combination of low numerical aperture focusing optics, in order to minimize spherical aberration, and beam shaping with a slit has been used to produce waveguides in fused silica by femtosecond laser writing. Waveguides with circular cross section and low losses are produced over a large depth window (>7mm) without changing any experimental parameter. Diffraction induces beam divergence along the axis perpendicular to the slit, leading to a shift of the focal plane. The focal intensity distribution can be predicted by a hybrid model combining Gaussian beam propagation with imaging of the slit into the material.
Blur Kernel Optimization: A New Approach to Patch Selection with Adaptive Kernel Estimation

Recently, many effective approaches appeared in the field of blind image deconvolution to reduce the computational cost. Using multiple smaller regions instead of whole image not only make the restoration efficient but also improves the results by discarding the ineffectual regions. It is observed that a study is needed to compare different methods for the selection of useful image patches and different schemes to utilize their blur kernels, which is aimed in the present work. A new patch selection method using Contrast based blur invariant features (CBIF) is proposed to find the useful regions which gives better results compared with others e.g., speed-up robust features (SURF), local binary patterns (LBP), local phase quantization (LPQ), maximally stable extremal regions (MSER), Canny and Sobel. In addition, gradually increasing contrast stretched levels shown to give better results compared with commonly used multiscale framework to avoid false local minima. It is also proposed that blur metric by Crete applied on latent image can be used for the selection of better kernel. It is observed that an effective strategy can give good results even when the patches are not selected carefully. The best results are obtained when our proposed patch selection is used with our “selective kernels averaging” scheme.
Simulation of the Au(111)-(22 ×√3) surface reconstruction

The (22׶3) reconstruction of the Au(111) surface is modeled using a priori density-functional theory simulations involving use of Born-Oppenheimer molecular dynamics and simulated annealing procedures. The reconstruction is exothermic by 0.43 eV per surface cell. Domains with surface atoms locating above fcc, hcp, and bridge sites of the second layer are produced, in quantitative agreement with experimental observations. While the reconstruction occurs to reduce the surface stresses created by cleavage of the bulk metal by minimizing the surface gold-gold interatomic separations, excess contraction appears associated with the bridge domains, causing them to stand out and form ridges above the surface. However, the chemical activity of the surface is reduced as the local surface density increases, making the fcc domain the most active part while the hcp domain and bridge ridges are less active.