Miracle-dz/UniFAR-FTUs huggingface dataset:
A methodological analysis of the normalisation, calibration and linearity of continuous diversity measures

The concepts of concentration and diversity play an important role in several fields of research. The existing indices in use are plagued by three deficiencies. They lack normalisation; they lack calibration; and their nonlinearity causes insufficient discrimination among related but dissimilar situations. After appraising the most common measures in light of these concepts, the paper shows how extant indices could be normalised and calibrated. In addition, we outline the general criteria for future diversity measures, and construct an intrinsically normalised, calibrated and linear one. A theoretical derivation is provided and a number of arguments and illustrative examples are included. We also discuss the limitations of continuous indices, including ours, and proffer some useful caveats.
The radiation operator

The concept of the radiation operator is introduced to assist in the analysis of various problems involving sources and their radiation fields. It gives the field outside the source region as operating on the field of a point source. Because there is a simple connection between the radiation vector describing the far-field and the radiation operator, it can be used to define fields anywhere outside the source region from their values in the far-field zone. Another important properly of the radiation operator is its ability to express sources of fields given their radiation pattern and polarization in the far zone. The source of such a field can be written in the form of radiation operator operating on a current element, the delta function source. To interpret this in terms of computable functions, existing tables of operational rules for different classes of operators can be applied. Examples of radiation operators corresponding to different sources are given together with examples of sources corresponding to given radiation field patterns. Finally it is shown that the radiation operator allows a considerable simplification to the derivation of the multipole expansion theory when compared to the classical recursion-formula derivation through spherical harmonic eigenfunctions.
Machine Learning-based Intrusion Detection System Against Routing Attacks in the Internet of Things

Internet of things (IoT) applications are growing daily, as they are being used in many areas and systems, and as their uses and modes of employment increase, there are many gaps with them. Security is one of the most challenging problems in IoT. IoT is composed of a considerable number of connected devices. Therefore, mobile data traffic is significant, and routing protocols are needed. IoT has many routing protocols; the most widely used is the RPL protocol, which considers limited power and the device’s capabilities. Still, it suffers from several weaknesses. The most important one is routing-based attacks which target this protocol. In this work, we aim to solve the problem of Internet of Things exposure to RPL-based attacks as a routing protocol. We built an anomaly intrusion detection system based on Machine learning and an IoT attacks dataset. This dataset, which is generated through the Cooja simulator, contains the most critical attacks and implementation of different scenarios that allowed for the extraction of essential features, in addition to new sensitive features such as nodes' power and their geographical location. Furthermore, we fix minority classes (rare attacks) by balancing the dataset. The results were satisfying because they decreased the false alert rate percentage and maximised accuracy and precision.
Multi‐model multi‐analysis ensembles in quasi‐operational medium‐range forecasting

Ensemble prediction systems (EPS) for medium‐range forecasting attempt to account for uncertainty in numerical weather prediction (NWP) by sampling the distribution function of future atmospheric states. Forecast uncertainty derives from uncertainty in both the analysed initial conditions (analysis errors) and in the forecast evolution (model errors). Current operational systems are primarily based on sampling the analysis errors through initial‐condition perturbations with, at best, only limited sampling of model errors. One approach to sampling model errors and also to widening the sampling of analysis errors, is to include more than one NWP model, and more than one operational analysis to which perturbations are added, in the ensemble system. Previous work has demonstrated from a small number of case‐studies that this multi‐model multi‐analysis ensemble (MMAE) approach can perform significantly better than a single‐model system such as the Ensemble Prediction System (EPS) run by the ECMWF (European Centre for Medium‐Range Weather Forecasts). In this study a MMAE was created by combining the ECMWF ensemble with an ensemble using the Met Office model and analysis, and was run daily for a year to assess the benefits over a larger, quasi‐operational sample of forecasts. The results are compared with the operational ECMWF EPS which includes the latest upgrades, including stochastic physics which makes some allowance for uncertainty due to model errors. Results show that both for probabilistic forecasts (assessed by Brier skill scores and relative operating characteristics) and for deterministic forecasts based on the ensemble mean (assessed by root‐mean square errors) the MMAE has increased forecast skill relative to the EPS. These improvements are obtained with no overall increase in ensemble size. Ensemble spread is also greater in the MMAE, and the increased skill is believed to be due to the additional model producing solutions which are synoptically more different than those produced by a single model ensemble. Benefits of the MMAE vary both in time and with geographical region, depending on which individual ensemble system performs better in particular synoptic situations. It is found that the MMAE almost always performs as well as the best individual ensemble, and on occasions better than either of them. © Crown copyright, 2002.
The motion of a thin oil sheet under the steady boundary layer on a body

A solution is obtained for the motion of a thin oil sheet, of non-uniform thickness, under a boundary layer. The following points are deduced: (a) The oil flows in the direction of the boundary-layer skin-friction, except near separation, where the oil tends to indicate separation too early. These conclusions are independent of oil viscosity. (b) The effect of the oil flow on the boundary-layer motion is very small. The application of the results to the interpretation of oil-flow patterns is briefly considered.
Asymptotically Informative Prior for Bayesian Analysis

In classical Bayesian inference the prior is treated as fixed and its effects are ignored asymptotically, and useful information, if any, is wasted. However, in practice often an informative prior is summarized from previous similar or the same kind of studies, which contains useful cumulative information for the current study. We treat such prior to be non-fixed, i.e., we give the data sizes in the prior studies similar status as the that of the current dataset. Under this formulation, the prior is asymptotically non-negligible, and its original information is transferred to the new study. We explore some basic properties of Bayesian estimators under such prior formulation, and illustrate the method via simulation.
Evaluación de ocupación del espectro radioeléctrico en Bogotá-Colombia

Este articulo describe los detalles y resultados de una campana de medicion de espectro, que tuvo lugar en Bogota (Colombia) desde Marzo a Diciembre de 2012. El estudio incluye el analisis de ocupacion de las bandas de frecuencias que van desde 54 MHz a 6 GHz. Las mediciones se ordenan de acuerdo a las diferentes bandas y servicios, a fin de proveer una vision clara de los ciclos de trabajo tipicos asociados a diferentes tecnologias. Los resultados sugieren que la utilizacion actual del espectro es todavia muy baja, incluso en una densa area urbana. PACS: 84.40. Ua, 89.70. -a, 41.20. Jb
Using H$_2$ Emission to Study the Fast Wind in Proto-Planetary Nebulae

We present the results of a high-resolution H$_2$ imaging and spectroscopic study of four bipolar proto-planetary nebulae: IRAS 16594–4656, Hen 3-401, Rob 22, and IRAS 17150–3224. These reveal the locations and kinematics of the H$_2$ emission and the shaping of the nebulae by their collimated fast winds.
Dynamical Structure and Evolution of Stellar Systems

The main goal of the PhD research described is to gain insight in the dynamical structure and evolution of galaxies, globular clusters and other stellar systems. For nearby stellar systems, realistic axisymmetric and triaxial dynamical models are constructed that fit their photometric and (two-dimensional) spectroscopic observations in detail. For early-type galaxies at higher redshift, the Fundamental Plane is used to investigate the evolution of their mass-to-light ratios. The connection of the results from both approaches allows a better understanding of the formation history of these stellar systems.
Robust exponential smoothing

The paper is devoted to robust modifications of exponential smoothing for time series with outliers or long-tailed distributions. Classical exponential smoothing applied to such time series is sensitive to the presence of outliers or long-tailed distributions and may give inadequate smoothing and forecasting results. First, simple and double exponential smoothing in the L1 norm (i.e. based on the least absolute deviations) are discussed in detail. Then, general exponential smoothing is made robust, replacing the least squares approach by M-estimation in such a way that the recursive character of the final formulas is preserved. The paper gives simple algorithmic procedures which preserve advantageous features of classical exponential smoothing and, in addition, which are less sensitive to outliers. Robust versions are compared numerically with classical ones.
Maximum likelihood estimation of correlation between maximal oxygen consumption and the 6-min walk test in patients with chronic heart failure

Maximal oxygen consumption (VO2max) is the standard measurement used to quantify cardiovascular functional capacity and aerobic fitness. Unfortunately, it is a costly, impractical and labour-intensive measure to obtain. The 6-min walk test (6MWT) also assesses cardiopulmonary function, but in contrast to the VO2max test, it is inexpensive and can be performed almost anywhere. Various medical studies have addressed the correlation between VO2max and 6MWT in patients with chronic heart failure. Of particular interest, from a medical point of view, is the conditional correlation between the two measures given the individual's height, weight, age and gender. In this paper, we have calculated the maximum likelihood estimate of the conditional correlation in patients with chronic heart failure under the assumption of skew normality. Data were recorded from 98 patients in the Operative Unit of Thoracic Surgery in Bari, Italy. The estimated conditional correlation was found to be much smaller than estimated marginal correlations reported in the medical literature.
Berth Allocation Problem with Quay Crane Assignment for Container Terminals Based on Rolling-Horizon Strategy

In order to solve the large-scale integral dynamic scheduling of continuous berths and quay cranes problem, a method based on rolling-horizon strategy is proposed. A multiobjective optimization model that is established minimizes the total penalty costs considering vessels’ deviations to their preferred berthing positions, delayed times for berthing comparing to their estimated arrival times, and delayed times for departure comparing to their estimated departure times. Then, the scheduling process was divided into a set of continual scheduling interval according to the dynamic arrival sequences. Meanwhile, rolling-horizon strategies for setting rolling and frozen windows and the parameter updating strategy are designed. The input parameters of the model in the next rolling window are updated according to the optimal results of each time window which have been obtained. The model is solved by choosing appropriate rolling and freezing window lengths that represents the numbers of adjacent vessels in the sequence of calling vessels. The holistic optimal solution is obtained by gradually rolling and combining the results of each window. Finally, a case study indicated that the rolling schedule can solve large-scale scheduling problems, and the efficiency of the proposed approach relates to the size of rolling window, freeze ship quantity, and rolling frequency.
A new pulsar atmospheric model. I. Aligned magnetic and rotational axes

A model is proposed for the plasma atmosphere about a rotating magnetized neutron star with aligned magnetic and rotational axes. The model is generated with the aid of a gedanken experiment in which the rotational velocity . cap omega. of the star is adiabatically increased. By this device it is established that the star will acquire a charge sufficient to stop the charge loss to the nebula, but not the local surface emission. The resulting monopole electric field causes plasma to flow across magnetic surfaces at large distances from the star, where it dominates the dipole magnetic field, thereby forming a current loop from the polar caps to polar annuli. This same electric flow region can also establilsh current loops to the nebula, provided electron-positron pairs are produced. The vacuum electric field has a surface where ExB=0, which is a dome over the polar cap. For larger . cap omega. , radiation losses cause beam particles to be trapped around this surface, forming a relatively stationary, possibly turbulent component of the atmosphere. It is shown that this plasma dome is more stable than the force-free atmosphere, and is therefore presumably maintained by a balance between the radiative capture and diffusion of particles backmore » to the star. A small toroidal, nearly force-free region consisting of opposite charges also exists near the equator and is attached to an equatorial disk, maintained by diffusion. The limited atmospheric extent and toroidal drift velocity suggest that all the magnetic surfaces are closed (near-dipolar). (AIP)« less
Recent developments in shell stability analysis

W pracy omowiono kierunki rozwoju teorii powlok w ramach badan prowadzonych obecnie w Instytucie Inzynierii Lotniczej w Delft. Dotyczą one formulowania nowych ulepszonych kryteriow projektowania. Kryteria te uwzgledniają najnowsze wyniki prac teoretycznych przy wykorzystaniu wspolczesnej techniki obliczeniowej.
A split explicit integration scheme for numerical weather prediction

An economical explicit integration scheme for numerical weather prediction models is described. A splitting technique is used, in which the horizontal advection terms in the governing equations are integrated with a timestep limited by the wind speed, whilst the terms which describe gravity-inertia oscillations are integrated in a succession of shorter steps. A two-level numerical scheme with small phase speed errors is used for the advection stage and a forward-backward method for the gravity-inertia terms. The split explicit scheme has been applied to the Meteorological Office operational 10-level model, and to a similar sigma coordinate model, to compute forecasts for periods up to six days ahead. The quality of the numerical forecasts obtained is not reduced when the timesteps used are close to the limits set by linear computational stability criteria. The use of such timesteps leads to a substantial computational economy relative to previously available integration schemes. For the northern hemisphere version of the 10-level model the computing time required is one-third of that for a split semi-implicit scheme and one-sixth of that for the original explicit Lax-Wendroff scheme. Verification statistics for split explicit forecasts indicate improved accuracy when compared with those for earlier operational models.
Sinkhorn ratings, and new strongly polynomial time algorithms for Sinkhorn balancing, Perron eigenvectors, and Markov chains

This paper simultaneously makes new con- tributions to political science, probability and statistics, and linear algebra. We describe a new method, "Sinkhorn ratings," for pairwise-comparison based ranking of chessplayers, web pages, or football teams; it also may be used to rank the candidates in an election in which each vote is a partial ordering of the candidates. We also describe the first "strongly polynomial time" al- gorithm for finding the Perron-Frobenius eigenvector of a matrix with non-negative entries, and the second strongly polynomial time algorithm (and the first practical one) for Sinkhorn balancing a matrix with non-negative entries. The former also may be regarded as the first strongly polynomial algorithm for finding the stationary distribu- tion of an N-state Markov chain with known transition matrix. Along the way we also present a new formula- tion of the Perron-Frobenius eigenvector and Markov sta- tionary distribution problems as concave-( minimization problems, and present a powerful new technique for prov- ing monotonicity statements e.g. about Markov chains.
Parameterizing Grid-Averaged Longwave Fluxes for Inhomogeneous Marine Boundary Layer Clouds

Abstract This paper examines the relative impacts on grid-averaged longwave flux transmittance (emittance) for marine boundary layer (MBL) cloud fields arising from horizontal variability of optical depth τ and cloud sides. First, using fields of Landsat-inferred τ and a Monte Carlo photon transport algorithm, it is demonstrated that mean all-sky transmittances for 3D variable MBL clouds can be computed accurately by the conventional method of linearly weighting clear and cloudy transmittances by their respective sky fractions. Then, the approximations of decoupling cloud and radiative properties and assuming independent columns are shown to be adequate for computation of mean flux transmittance. Since real clouds have nonzero geometric thicknesses, cloud fractions Âc presented to isotropic beams usually exceed the more familiar vertically projected cloud fractions Ac. It is shown, however, that when Ac ≲ 0.9, biases for all-sky transmittance stemming from use of Ac as opposed to Âc are roughly 2–5 times .
Motion planning and control of gantry cranes in cluttered work environment

Manipulating payloads with gantry cranes is challenging due to possible undesirable load pendulations induced by the crane motion and external perturbations. When the work environment is cluttered with obstacles, the problem gets increasingly difficult, which must be avoided, resulting in the need for appropriate load trajectory planning and more cautious craning strategy. The trajectory is first sketched by a series of points in the work space, and then approximated by spline functions. A rest-to-rest load motion along the specified trajectory is then imposed, resulting in one coordinated manoeuvre that omits the obstacles. The control of crane executing the load motion is viewed as an inverse dynamics problem, strongly influenced by the underactuated nature of the system. The arising governing differential-algebraic equations enable one for the analysis of crane dynamics and synthesis of its control in the specified motion. The open-loop control obtained this way is enhanced by a closed-loop control with feedback of the actual errors in load position to provide stable tracking of the reference trajectory in presence of perturbations and modelling inconsistencies. Some results of numerical simulations are reported.
Heteroskedasticity-consistent interval estimators

The linear regression model is commonly used in applications. One of the assumptions made is that the error variances are constant across all observations. This assumption, known as homoskedasticity, is frequently violated in practice. A commonly used strategy is to estimate the regression parameters by ordinary least squares and to compute standard errors that deliver asymptotically valid inference under both homoskedasticity and heteroskedasticity of an unknown form. Several consistent standard errors have been proposed in the literature, and evaluated in numerical experiments based on their point estimation performance and on the finite sample behaviour of associated hypothesis tests. We build upon the existing literature by constructing heteroskedasticity-consistent interval estimators and numerically evaluating their finite sample performance. Different bootstrap interval estimators are also considered. The numerical results favour the HC4 interval estimator.
Static and Dynamic Finite-Size Scaling Theory Based on the Renormalization Group Approach

Fisher's static finite-size scaling law is derived on the basis of the renormalization group theory and it is extended to dynamic critical phenomena in a finite system. This dynamic finite-size scaling law yields a cross-over effect with respect to the size and time-region. This effect is useful in analyzing computer simulations and also in studying the scaling property of the Kondo effect near the absolute zero temperature.
Chemical Composition of the Galactic Bulge in Baade's Window

Abstract 1. McWilliam and Zoccali (2009) show the existence of two Red Clump populations towards the Galactic bulge, based on 2MASS data. 2.Measured [Mg/Fe], [Al/Fe], and [La/Eu] ratios in the bulge are consistent with a rapid formation timescale (<1Gyr), which also requires a slightly top-heavy IMF to reproduce the mean bulge metallicity. The [C/O] and [O/Fe] ratios are consistent if their predicted metal-dependent yields from massive stars with winds are considered. The decline in explosive [α/Fe] (Si, Ca, and Ti) can only be understood if their yields also decline with metallicity above [Fe/H]~−1.
An extension of the IEM/IEMM surface scattering model

Abstract The integral equation model (IEM) has been developed over the last decade and, since its first presentation by Fung and Pan (1986 Proc. Int. Symp. on Multiple Scattering of Waves in Random Media and Random Surface (PA: Pennsylvania State University Press) pp 701–14), it has become one of the theoretical models most widely used for rough surface scattering in microwave remote sensing. The aim of this model was the study of the scattering by random rough surfaces under more general conditions than the Kirchhoff or the small-perturbation approximations. Furthermore, the IEM was meant to include multiple-scattering effects at second order. The IEM has been gradually corrected in two later releases by its original authors (Hsieh C-Y et al 1997 IEEE Trans. Geosci. Remote Sensing 35 901–9, Chen et al 2000 IEEE Trans. Geosci. Remote Sensing 38 249–56). However, the model still presents several theoretical hiatuses in its current formulation which call for a new revision. Most importantly, the IEM in its current form does not reduce in the general bistatic context to the small-perturbation method (SPM) when the scattering surface is slightly rough. A good description of multiple-scattering mechanisms implies that the single scattering is correctly described. This condition is not met by IEM as given hitherto. In the work presented here, a corrected version of IEM reproducing SPM for small roughness is proposed. Since it is also compliant with the physical and geometrical optics results, this new integral equation model is an appropriate candidate to bridge the gap between the Kirchhoff approximation and the SPM.
Improved Data Structure for the Orthogonal Packing Problem

In paper is considered the actual in industry and engineering orthogonal multidimensional packing problem. This problem is NP-hard in strong sense therefore an important role is played effectiveness of the used packing representation model. To increase the speed of placement of a given set of orthogonal objects into containers is offered a new data structure – multilevel linked data structure. The carried out computational experiments demonstrate high time efficiency of the proposed data structure compared to the ordered simple linked list.