A generator of cauchy-distributed time series with specific Hurst index

A generator of artificial Cauchy-distributed time series is presented. This generator transforms any random time series, e.g., standardized fractional Gaussian noise (FGN), into a Cauchy-distributed series with specific location and scale parameters and correlation structure, determined by the Hurst index. The proposed algorithm consists of an inverse cumulative distribution function (ICDF) transformation, a wavelet-analysis synthesis and, finally, a linear transformation. The resulting Cauchy-distributed series has approximately the desired location and scale parameters and exactly the desired Hurst index. The performance of the proposed generator is evaluated by estimating the location, scale and Hurst parameters from artificial time series and by calculating the mean squared error (MSE) of their cumulative distribution function (CDF). The input location, scale and Hurst index used in the simulations are taken from jitter samples of monitored Voice over Internet Protocol (VoIP) calls, which have been proved to be adequately modeled with these processes under some circumstances

Distinguishing Stationary/Nonstationary Scaling Processes Using Wavelet Tsallis q

Classification of processes as stationary or nonstationary has been recognized as an important and unresolved problem in the analysis of scaling signals. Stationarity or nonstationarity determines not only the form of autocorrelations and moments but also the selection of estimators. In this paper, a methodology for classifying scaling processes as stationary or nonstationary is proposed. The method is based on wavelet Tsallis q-entropies and particularly on the behaviour of these entropies for scaling signals. It is demonstrated that the observed wavelet Tsallis q-entropies of 1/f signals can be modeled by sum-cosh apodizing functions which allocates constant entropies to a set of scaling signals and varying entropies to the rest and that this allocation is controlled by q. The proposed methodology, therefore, differentiates stationary signals from non-stationary ones based on the observed wavelet Tsallis entropies for 1/f signals. Experimental studies using synthesized signals confirm that the proposed method not only achieves satisfactorily classifications but also outperforms current methods proposed in the literature

A Survey on Quality of Service in the Voice Over IP Technology

Voice services can be transmitted by circuit switched and packet switched networks (Internet). Voice over Internet Protocol (VoIP) is one of the most attractive and important service in telecommunication networks, current implementations of VoIP have two main types of architectures, which are based on H.323 and Session Initiation Protocol (SIP). However, when the voice traffic is transported over Internet, the packet based transmission may introduce impairments and it has influence on the Quality of Service (QoS) perceived by the end users. The voice quality of VoIP systems depends on many QoS parameters. Particularly, One Way Delay (OWD), jitter and Packet Loss Rate (PLR) have an important impact on voice quality. This survey presents the main concepts relating to the VoIP technology and quality of service issues

Generalized Wavelet Fisher’s Information of 1

This paper defines the generalized wavelet Fisher information of parameter q. This information measure is obtained by generalizing the time-domain definition of Fisher’s information of Furuichi to the wavelet domain and allows to quantify smoothness and correlation, among other signals characteristics. Closed-form expressions of generalized wavelet Fisher information for 1/fα signals are determined and a detailed discussion of their properties, characteristics and their relationship with wavelet q-Fisher information are given. Information planes of 1/f signals Fisher information are obtained and, based on these, potential applications are highlighted. Finally, generalized wavelet Fisher information is applied to the problem of detecting and locating weak structural breaks in stationary 1/f signals, particularly for fractional Gaussian noise series. It is shown that by using a joint Fisher/F-Statistic procedure, significant improvements in time and accuracy are achieved in comparison with the sole application of the F-statistic

CONTROL NUMÉRICO COMPUTARIZADO UTILIZANDO INTERPOLACIÓN LINEAL PARA AUTONIVELAR LA SUPERFICIE DE TRABAJO EN UNA CNC (COMPUTERIZED NUMERICAL CONTROL USING LINEAR INTERPOLATION TO SELF-LEVEL THE WORKING SURFACE IN A CNC)

En este trabajo se presenta la implementación de una máquina CNC (Control Numérico Computarizado, por sus siglas en español) de bajo costo que utiliza un algoritmo de autonivelación para mejorar el desempeño del maquinado. Mediante el algoritmo se puede corregir por software el desnivel de la cama de fresado independientemente de las imperfecciones del material que se va a maquinar. Básicamente lo que hace el software es deformar el dibujo que se imprimirá de tal manera que este compense la deformación del material. Se utiliza una tarjeta de desarrollo “Arduino UNO” para capturar los datos de una sonda de contacto, posteriormente la información obtenida será procesada por una computadora, que a su vez enviará los datos procesados al Arduino para que este accione los motores. Se utilizó NetBeans para el desarrollo de la plataforma del usuario y el firmware GRBL (para Arduino) como lenguaje de programación, ambos de código libre, además el software Matlab es utilizado para realizar las simulaciones del código. Los resultados muestran que el uso del algoritmo de autonivelación efectivamente mejora el proceso de maquinado.This paper presents the implementation of a CNC machine (Computerized Numerical Control, for its acronym in Spanish) of low cost that uses a self-leveling algorithm to improve the machining performance. By means of the algorithm, the unevenness of the milling bed can be corrected, by software, independently of the imperfections of the material to be machined. Basically, what the software does is to deform the drawing that will be printed in such a way that it compensates for the deformation of the material. An "Arduino UNO" board is used to capture the data from a contact probe, then the information obtained will be processed by a computer, which in turn will send the processed data to the Arduino, so that it drives the motors. NetBeans was used for the development of the user platform and the GRBL firmware (for Arduino) as programming language, both of them are free code, in addition the Matlab software is used to perform the code simulations. The results show that the use of the self-leveling algorithm improves the machining process

A Study of Wavelet Analysis and Data Extraction from Second-Order Self-Similar Time Series

Statistical analysis and synthesis of self-similar discrete time signals are presented. The analysis equation is formally defined through a special family of basis functions of which the simplest case matches the Haar wavelet. The original discrete time series is synthesized without loss by a linear combination of the basis functions after some scaling, displacement, and phase shift. The decomposition is then used to synthesize a new second-order self-similar signal with a different Hurst index than the original. The components are also used to describe the behavior of the estimated mean and variance of self-similar discrete time series. It is shown that the sample mean, although it is unbiased, provides less information about the process mean as its Hurst index is higher. It is also demonstrated that the classical variance estimator is biased and that the widely accepted aggregated variance-based estimator of the Hurst index results biased not due to its nature (which is being unbiased and has minimal variance) but to flaws in its implementation. Using the proposed decomposition, the correct estimation of the Variance Plot is described, as well as its close association with the popular Logscale Diagram

An Outline of Data Aggregation Security in Heterogeneous Wireless Sensor Networks

Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes’ resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach

A Novel Method for Polar Form of Any Degree of Multivariate Polynomials with Applications in IoT

Identification schemes based on multivariate polynomials have been receiving attraction in different areas due to the quantum secure property. Identification is one of the most important elements for the IoT to achieve communication between objects, gather and share information with each other. Thus, identification schemes which are post-quantum secure are significant for Internet-of-Things (IoT) devices. Various polar forms of multivariate quadratic and cubic polynomial systems have been proposed for these identification schemes. There is a need to define polar form for multivariate dth degree polynomials, where d ≥ 4 . In this paper, we propose a solution to this need by defining constructions for multivariate polynomials of degree d ≥ 4 . We give a generic framework to construct the identification scheme for IoT and RFID applications. In addition, we compare identification schemes and curve-based cryptoGPS which is currently used in RFID applications

Modeling QoS parameters of VoIP traffic with multifractal and Markov models

In this paper, we analyze the jitter and packet loss behavior of voice over Internet protocol (VoIP) traffic by means of networks measurements and simulations results. As result of these analyses, we provide a detailed characterization and accurate modeling of these Quality of Service (QoS) parameters. Our studies have revealed that VoIP jitter can be modeled by self-similar and multifractal models. We present a methodology for simulating packet loss. Besides, we found relationships between Hurst parameter (H) with packet loss rate (PLR)