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In this chapter we provide a generalization of jump-diffusion precesses (12.1) in two dimensions by considering a class of coupled systems that are described by a bivariate state vector x(t) contained in a two-dimensional state space {x}. The evolution of the state vector x(t) is assumed to be governed by a deterministic part to which diffusion parts and jump contributions are added. Generalization of the results to higher dimensions is straightforward. We note that for N multivariate time series, by assuming the presence of two-body type of interactions between time series, the analysis will reduce to analysing N(N − 1)/2 pairwise bivariate time series. © 2019, Springer Nature Switzerland... 

In this chapter we provide a generalization of jump-diffusion precesses (12.1) in two dimensions by considering a class of coupled systems that are described by a bivariate state vector x(t) contained in a two-dimensional state space {x}. The evolution of the state vector x(t) is assumed to be governed by a deterministic part to which diffusion parts and jump contributions are added. Generalization of the results to higher dimensions is straightforward. We note that for N multivariate time series, by assuming the presence of two-body type of interactions between time series, the analysis will reduce to analysing N(N − 1)/2 pairwise bivariate time series. © 2019, Springer Nature Switzerland... 

In this chapter we present the steps of reconstruction procedure for writing down the Langevin and jump diffusion stochastic dynamical equations for uni- and bivariate time series, sampled with time intervals τ. © 2019, Springer Nature Switzerland AG  

In this chapter we present the steps of reconstruction procedure for writing down the Langevin and jump diffusion stochastic dynamical equations for uni- and bivariate time series, sampled with time intervals τ. © 2019, Springer Nature Switzerland AG  

In the reliability analysis of systems, all system components are often assumed independent and failure of any component does not depend on any other component. One of the reasons for doing so is that considerations of calculation and elegance typically pull in simplicity. But in real-world applications, there are very complex systems with lots of subsystems and a choice of multiple components that may interact with each other. Therefore, components of the system can be affected by the occurrence of a failure in any of the components. The purpose of this paper is to give an explicit formula for the computation of the reliability of a system with two parallel active components and one spare... 

This paper aims to examine the key factors influencing driving risk perception in Iran. We conducted separate surveys for two groups of Iranian drivers, namely passenger car drivers and truck drivers. In order to assess driving risk perception, respondents were asked what they think about their Probability of Having a Road Accident (PHRA) and if they eventually have an accident as a driver, what they think about the Probability of it being Fatal or causing Severe Injury (PFSI). A Bivariate Ordered Probit model, which considers the possible correlation between PHRA and PFSI, was developed to explain the observed driving risk perception using type of vehicle, driving experience,... 

In this paper we report the results of classical molecular dynamics (MD) simulation of hexanoic acid adsorption on calcite (101-4) surface plane using Pavese and AMBER force fields for calcite and hexanoic acid, respectively. Pair correlation function, strictly suggests a well-structured adsorption. Density profile indicates the adsorption occurs through double-bonded O atom of the acid head group by direct interaction with Ca atom at calcite surface. Adsorption orientation of H and double-bonded O atoms was found to be as lock and key with respect to calcite surface Ca and O atoms, facilitating an effective adsorption. Adsorption time evolution indicates that O atom adsorption is... 

Iran is a country with numerous traffic accidents, offenses, and disruptions. According to the deterrence theory, increased detection of traffic offenses would decrease violations. Detection of traffic offenses is insufficient in Iran due to the limited operational capacity of the police. Reducing traffic violations would reduce accidents, disorders, and socio-economic costs. In this paper, a scheme for detecting and reporting speeding and parking violations to infringement processing through a crowdsourcing platform is proposed as a solution considering Iran's economic and social context. Two scenarios for detecting and reporting speeding and parking violations were considered: public... 

In this paper we present a sampling result about continuous-domain black and white images that form a convex shape. In particular, we will study shapes whose boundaries belong to the zero-level sets (roots) of bivariate polynomials. In [1] it was shown that generalized 2D moments of the image can lead to annihilation equations for the coefficients of the bivariate polynomial that determine the boundary of the shape. More precisely, when the bivariate polynomial is of degree n (which has n(n+3)/2 non-trivial coefficients), the results in [1] indicate that for invertibility of the linear annihilation equations, 2D moments of up to degree 3n-1 (overall equation moments) are required. In this... 

We introduce the bivariate jump-diffusion process, consisting of two-dimensional diffusion and two-dimensional jumps, that can be coupled to one another. We present a data-driven, nonparametric estimation procedure of higher-order (up to 8) Kramers-Moyal coefficients that allows one to reconstruct relevant aspects of the underlying jump-diffusion processes and to recover the underlying parameters. The procedure is validated with numerically integrated data using synthetic bivariate time series from continuous and discontinuous processes. We further evaluate the possibility of estimating the parameters of the jump-diffusion model via data-driven analyses of the higher-order Kramers-Moyal... 

Synchronization behavior of electroencephalographic (EEG) signals is important for decoding information processing in the human brain. Modern multichannel EEG allows a transition from traditional measurements of synchronization in pairs of EEG signals to whole-brain synchronization maps. The latter can be based on bivariate measures (BM) via averaging over pair-wise values or, alternatively, on multivariate measures (MM), which directly ascribe a single value to the synchronization in a group. In order to compare BM versus MM, we applied nine different estimators to simulated multivariate time series with known parameters and to real EEGs. We found widespread correlations between BM and MM,... 

In this study, the authors study lossy communication of correlated sources over a multiple-access wiretap channel (MAC-WT). Consider a system with two transmitters, a receiver and an eavesdropper. There are two correlated sources where each of them is observed by the corresponding transmitter, separately. Each transmitter wishes to describe its source sequence to the receiver with a desired distortion. The sources need to be kept secret from the eavesdropper. They find an achievable region for the MAC-WT with correlated sources by separation. A joint source-channel coding scheme for the MAC-WT is also proposed. They consider lossy communication of a bivariate Gaussian source over Gaussian... 

In this letter, we consider two problems of sending a bivariate Gaussian source through a two-user Gaussian non-orthogonal multiple-access channel. We provide a new distortion outer bound for the considered joint source-channel coding problems, which significantly reduces the gap between inner and outer bounds of the distortion for correlation coefficients below a threshold. Furthermore, numerical results show, that under some conditions, our proposed outer bound matches with the inner bound obtained via the separate source-channel coding scheme, which proves the optimality of this scheme. © 1997-2012 IEEE  

Geostatistical methods are grouped in two main divisions: univariate and multivariate. When there is adequate amount of primary data, univariate methods such as kriging and SGS give a good representation of property distribution in the reservoir, but practical difficulties appear when there is no sufficient data. In such a case it is necessary to choose multivariate geostatistical methods in which some covariables are contributed to model the primary variable. Multivariate geostatistics is a broad term that encompasses all geostatistical methods that utilize more than one variable to predict some physical property of the earth. Bivariate geostatistics is obviously the simplest subset of the... 

Meteorological droughts due to the concurrent occurrence of low-precipitation and high-temperature events can lead to severe negative impacts on agriculture, economy, ecosystem, and society. This study proposes a novel framework to characterize such drought conditions based on the joint variability of precipitation–temperature, particularly under climate change. Generalized hierarchical linear model is used to downscale precipitation and temperature at multiple stations from the outputs of nine General Circulation Models (GCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5. A bivariate drought index called Precipitation–Temperature Deciles Index (PTDI) is developed using...