## On β γ Chebyshev functions and points of the interval

In this paper, we introduce the class of $(\beta,\gamma)$-Chebyshev functionsand corresponding points . We prove that they are orthogonal in certain subintervals of $[-1,1]$ withrespect to a weighted arc-cosine measure . We also study the behavior of the Lebesgue constants of the polynomialinterpolant at these points on varying the parameters $beta$ and $gamma$ .…

## Infinite GMRES for parameterized linear systems

Methods combine the well-established GMRES method for linear systems with algorithms for nonlineareigenvalue problems (NEPs) to generate a basis for the Krylov subspace . Weshow convergence factor bounds obtained similarly to those for the method GMRESfor linear systems. More specifically, a bound is obtained based on themagnitude of the parameter $mu$ and the spectrum of the linear companionmatrix, which corresponds to the reciprocal solutions to the corresponding NEP.…

## Minimum Principle on Specific Entropy and High Order Accurate Invariant Region Preserving Numerical Methods for Relativistic Hydrodynamics

This paper explores Tadmor’s minimum entropy principle for the relativistichydrodynamics (RHD) equations . It incorporates this principle into the design of robust high-order discontinuous Galerkin (DG) and finite volume schemes for RHD on general meshes . The schemes are proven to preserve numerical solutionsin a global invariant region constituted by all the known intrinsicconstraints .…

## Novel Deep neural networks for solving Bayesian statistical inverse

Markov chain Monte Carlo (MCMC) algorithms are standard techniques to solvesuch problems . MCMC techniques are computationally challenging as they require several thousands of forward PDE solves . The goal of this paper is to introduce a fractional deep neural network based approach for the forwardsolves within an MCMC routine .…

## A Bayesian Two part Hurdle Quantile Regression Model for Citation Analysis

Quantile regression presents a complete picture of the effects on the location, scale, and shape of the dependent variable at all points, not just atthe mean . Theirmodel allows zeros and non-zeros to be modeled independently butsimultaneously . The new modeldelivers more accurate quantile regression for moderately to highly citedarticles, and enables estimates of the extent to which factors influence the chances that an article will be low cited .…

## Tractable mechanisms for computing near optimal utility functions

Large scale multiagent systems must rely on distributed decision making, as centralized coordination is either impractical or impossible . We show that optimally designed local utilities achieve anapproximation ratio (price of anarchy) of 1-c/e, where c is the function’scurvature and e is Euler’s constant .…

## Diagnosis of COVID 19 and Non COVID 19 Patients by Classifying Only a Single Cough Sound

In this study, we proposed a machine learning-based system to distinguish patients with COVID-19 . The proposed system is excellent compared with similar studies in the literature . It can be easily used in smartphones and facilitate the diagnosis of patients .…

## A Tutorial on 5G NR V2X Communications

The Third Generation Partnership Project (3GPP) has recently published its release 16 that includes the first Vehicle to-Everything (V2X) standard based on the 5G New Radio (NR) air interface . 5G NR V2X introduces advancedfunctionalities on top of the NR air interface to support connected andautomated driving use cases with stringent requirements .…

## Timely Transmissions Using Optimized Variable Length Coding

A status updating system is considered in which a variable length code is used to transmit messages to a receiver over a noisy channel . The goal is tooptimize the codewords lengths such that successfully-decoded messages aretimely . A hybrid ARQ (HARQ) scheme is employed, in which variable-lengthincremental redundancy (IR) bits are added to the originally-transmittedcodeword until decoding is successful .…

## Semiquantitative Group Testing in at Most Two Rounds

Semiquantitative group testing (SQGT) is a pooling method in which the testoutcomes represent bounded intervals for the number of defectives . Alternatively, it may be viewed as an adder channel with quantized outputs . SQGT represents a natural choice for Covid-19 group testing as it allows for astraightforward interpretation of the cycle threshold values produced by polymerase chain reactions .…

## NELA GT 2020 A Large Multi Labelled News Dataset for The Study of Misinformation in News Articles

NELA-GT-2020 contains nearly 1.8M news articles from 519 sources collected between January 1st and December 31st, 2020 . Tweets embedded in the collected news articles add an extra layer ofinformation to the data . The NELa-GT 2020 dataset can be found athttps://doi.org/10.7910/DVN/CHMUYZ.…

## Regular Model Checking Approach to Knowledge Reasoning over Parameterized Systems technical report

We present a framework for modelling and verifying epistemicproperties over parameterized multi-agent systems that communicate by truthfulpublic announcements . In our framework, the number of agents or amount of resources are parameterized (i.e. not known a priori) and theresponding verification problem asks whether a given epistemic property istrue regardless of the instantiation of the parameters .…

## Optimal Priority Assignment for Real Time Systems A Coevolution Based Approach

In real-time systems, priorities assigned to tasks deter-mine the order of task executions, by relying on an underlying task scheduling policy . In practice, priorityassignments result from an interactive process between the development and testing teams . Our approach is based on a multi-objective, competitivecoevolutionary algorithm mimicking the interactive priority assignment process .…

## On Computation Complexity of True Proof Number Search

We point out that the computation of true proof number search in arbitrary directed acyclic graphs is NP-hard . The proof requires a reduction from SAT, which demonstrates that finding trueproof/disproof number for arbitrary DAG is at least as hard as deciding ifarbitrary SAT instance is satisfiable .…