Search results for: triply stochastic filtered marked Poisson point process.
7133 Computational Simulations on Stability of Model Predictive Control for Linear Discrete-time Stochastic Systems
Authors: Tomoaki Hashimoto
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Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the effectiveness of the obtained stability condition.Keywords: Computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18377132 Stochastic Impact Analysis of COVID-19 on Karachi Stock Exchange
Authors: Syeda Maria Ali Shah, Asif Mansoor, Talat Sharafat Rehmani, Safia Mirza
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The stock market of any country acts as a predictor of the economy. The spread of the COVID-19 pandemic has severely impacted the global financial markets. Besides, it has also critically affected the economy of Pakistan. In this study, we consider the role of the Karachi Stock Exchange (KSE) with regard to the Pakistan Stock Exchange and quantify the impact on macroeconomic variables in presence of COVID-19. The suitable macroeconomic variables are used to quantify the impact of COVID-19 by developing the stochastic model. The sufficiency of the computed model is attained by means of available techniques in the literature. The estimated equations are used to forecast the impact of pandemic on macroeconomic variables. The constructed model can help the policymakers take counteractive measures for restricting the influence of viruses on the Karachi Stock Market.
Keywords: COVID-19, Karachi Stock Market, macroeconomic variables, stochastic model, forecasting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7197131 Modeling and Simulating Reaction-Diffusion Systems with State-Dependent Diffusion Coefficients
Authors: Paola Lecca, Lorenzo Dematte, Corrado Priami
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The present models and simulation algorithms of intracellular stochastic kinetics are usually based on the premise that diffusion is so fast that the concentrations of all the involved species are homogeneous in space. However, recents experimental measurements of intracellular diffusion constants indicate that the assumption of a homogeneous well-stirred cytosol is not necessarily valid even for small prokaryotic cells. In this work a mathematical treatment of diffusion that can be incorporated in a stochastic algorithm simulating the dynamics of a reaction-diffusion system is presented. The movement of a molecule A from a region i to a region j of the space is represented as a first order reaction Ai k- ! Aj , where the rate constant k depends on the diffusion coefficient. The diffusion coefficients are modeled as function of the local concentration of the solutes, their intrinsic viscosities, their frictional coefficients and the temperature of the system. The stochastic time evolution of the system is given by the occurrence of diffusion events and chemical reaction events. At each time step an event (reaction or diffusion) is selected from a probability distribution of waiting times determined by the intrinsic reaction kinetics and diffusion dynamics. To demonstrate the method the simulation results of the reaction-diffusion system of chaperoneassisted protein folding in cytoplasm are shown.
Keywords: Reaction-diffusion systems, diffusion coefficient, stochastic simulation algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15147130 Stochastic Modeling for Parameters of Modified Car-Following Model in Area-Based Traffic Flow
Authors: N. C. Sarkar, A. Bhaskar, Z. Zheng
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The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver’s visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation.
Keywords: Area-based traffic, car-following model, micro-simulation, stochastic modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7607129 Stochastic Control of Decentralized Singularly Perturbed Systems
Authors: Walid S. Alfuhaid, Saud A. Alghamdi, John M. Watkins, M. Edwin Sawan
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Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.
Keywords: Decentralized, optimal control, output, singular perturb.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15627128 Automatically Generated and Marked E-Learning Exercises for Logistics Cost Accounting
Authors: Markus Siepermann, Christoph Siepermann
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This paper presents the concept and realisation of an e-learning tool that provides predefined or automatically generated exercises concerning logistics cost accounting. Students may practise where and whenever they like to via the Internet. Their solutions are marked automatically by the tool while considering consecutive faults and without any intervention of lecturers.Keywords: Automatic marking, e-learning environment, onlinepracticing, randomly-generated exercises.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15577127 Supplier Selection in a Scenario Based Stochastic Model with Uncertain Defectiveness and Delivery Lateness Rates
Authors: Abeer Amayri, Akif A. Bulgak
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Due to today’s globalization as well as outsourcing practices of the companies, the Supply Chain (SC) performances have become more dependent on the efficient movement of material among places that are geographically dispersed, where there is more chance for disruptions. One such disruption is the quality and delivery uncertainties of outsourcing. These uncertainties could lead the products to be unsafe and, as is the case in a number of recent examples, companies may have to end up in recalling their products. As a result of these problems, there is a need to develop a methodology for selecting suppliers globally in view of risks associated with low quality and late delivery. Accordingly, we developed a two-stage stochastic model that captures the risks associated with uncertainty in quality and delivery as well as a solution procedure for the model. The stochastic model developed simultaneously optimizes supplier selection and purchase quantities under price discounts over a time horizon. In particular, our target is the study of global organizations with multiple sites and multiple overseas suppliers, where the pricing is offered in suppliers’ local currencies. Our proposed methodology is applied to a case study for a US automotive company having two assembly plants and four potential global suppliers to illustrate how the proposed model works in practice.Keywords: Global supply chains, quality, stochastic programming, supplier selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15587126 Sensitivity of Small Disturbance Angle Stability to the System Parameters of Future Power Networks
Authors: Nima Farkhondeh Jahromi, George Papaefthymiou, Lou van der Sluis
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The incorporation of renewable energy sources for the sustainable electricity production is undertaking a more prominent role in electric power systems. Thus, it will be an indispensable incident that the characteristics of future power networks, their prospective stability for instance, get influenced by the imposed features of sustainable energy sources. One of the distinctive attributes of the sustainable energy sources is exhibiting the stochastic behavior. This paper investigates the impacts of this stochastic behavior on the small disturbance rotor angle stability in the upcoming electric power networks. Considering the various types of renewable energy sources and the vast variety of system configurations, the sensitivity analysis can be an efficient breakthrough towards generalizing the effects of new energy sources on the concept of stability. In this paper, the definition of small disturbance angle stability for future power systems and the iterative-stochastic way of its analysis are presented. Also, the effects of system parameters on this type of stability are described by performing a sensitivity analysis for an electric power test system.
Keywords: Power systems stability, Renewable energy sources, Stochastic behavior, Small disturbance rotor angle stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20717125 On Four Models of a Three Server Queue with Optional Server Vacations
Authors: Kailash C. Madan
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We study four models of a three server queueing system with Bernoulli schedule optional server vacations. Customers arriving at the system one by one in a Poisson process are provided identical exponential service by three parallel servers according to a first-come, first served queue discipline. In model A, all three servers may be allowed a vacation at one time, in Model B at the most two of the three servers may be allowed a vacation at one time, in model C at the most one server is allowed a vacation, and in model D no server is allowed a vacation. We study steady the state behavior of the four models and obtain steady state probability generating functions for the queue size at a random point of time for all states of the system. In model D, a known result for a three server queueing system without server vacations is derived.Keywords: A three server queue, Bernoulli schedule server vacations, queue size distribution at a random epoch, steady state.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13707124 Error Propagation of the Hidden-Point Bar Method: Effect of Bar Geometry
Authors: Said M. Easa, Ahmed Shaker
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The hidden-point bar method is useful in many surveying applications. The method involves determining the coordinates of a hidden point as a function of horizontal and vertical angles measured to three fixed points on the bar. Using these measurements, the procedure involves calculating the slant angles, the distances from the station to the fixed points, the coordinates of the fixed points, and then the coordinates of the hidden point. The propagation of the measurement errors in this complex process has not been fully investigated in the literature. This paper evaluates the effect of the bar geometry on the position accuracy of the hidden point which depends on the measurement errors of the horizontal and vertical angles. The results are used to establish some guidelines regarding the inclination angle of the bar and the location of the observed points that provide the best accuracy.Keywords: Hidden point, accuracy, error propagation, surveying, evaluation, simulation, geometry.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17087123 Modelling Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) Outbreak Using Poisson and Negative Binomial Model
Authors: W. Y. Wan Fairos, W. H. Wan Azaki, L. Mohamad Alias, Y. Bee Wah
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Dengue fever has become a major concern for health authorities all over the world particularly in the tropical countries. These countries, in particular are experiencing the most worrying outbreak of dengue fever (DF) and dengue haemorrhagic fever (DHF). The DF and DHF epidemics, thus, have become the main causes of hospital admissions and deaths in Malaysia. This paper, therefore, attempts to examine the environmental factors that may influence the recent dengue outbreak. The aim of this study is twofold, firstly is to establish a statistical model to describe the relationship between the number of dengue cases and a range of explanatory variables and secondly, to identify the lag operator for explanatory variables which affect the dengue incidence the most. The explanatory variables involved include the level of cloud cover, percentage of relative humidity, amount of rainfall, maximum temperature, minimum temperature and wind speed. The Poisson and Negative Binomial regression analyses were used in this study. The results of the analyses on the 915 observations (daily data taken from July 2006 to Dec 2008), reveal that the climatic factors comprising of daily temperature and wind speed were found to significantly influence the incidence of dengue fever after 2 and 3 weeks of their occurrences. The effect of humidity, on the other hand, appears to be significant only after 2 weeks.Keywords: Dengue Fever, Dengue Hemorrhagic Fever, Negative Binomial Regression model, Poisson Regression model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28037122 An Approach to Noise Variance Estimation in Very Low Signal-to-Noise Ratio Stochastic Signals
Authors: Miljan B. Petrović, Dušan B. Petrović, Goran S. Nikolić
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This paper describes a method for AWGN (Additive White Gaussian Noise) variance estimation in noisy stochastic signals, referred to as Multiplicative-Noising Variance Estimation (MNVE). The aim was to develop an estimation algorithm with minimal number of assumptions on the original signal structure. The provided MATLAB simulation and results analysis of the method applied on speech signals showed more accuracy than standardized AR (autoregressive) modeling noise estimation technique. In addition, great performance was observed on very low signal-to-noise ratios, which in general represents the worst case scenario for signal denoising methods. High execution time appears to be the only disadvantage of MNVE. After close examination of all the observed features of the proposed algorithm, it was concluded it is worth of exploring and that with some further adjustments and improvements can be enviably powerful.
Keywords: Noise, signal-to-noise ratio, stochastic signals, variance estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22467121 Stochastic Edge Based Anomaly Detection for Supervisory Control and Data Acquisitions Systems: Considering the Zambian Power Grid
Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni
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In Zambia, recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines, to upgrade power systems into smart grids, target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, they are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, and therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we present a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.
Keywords: Anomaly detection, SmartGrid, edge, maintainability, reliability, stochastic process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2987120 One scheme of Transition Probability Evaluation
Authors: Alexander B. Bichkov, Alla A. Mityureva, Valery V. Smirnov
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In present work are considered the scheme of evaluation the transition probability in quantum system. It is based on path integral representation of transition probability amplitude and its evaluation by means of a saddle point method, applied to the part of integration variables. The whole integration process is reduced to initial value problem solutions of Hamilton equations with a random initial phase point. The scheme is related to the semiclassical initial value representation approaches using great number of trajectories. In contrast to them from total set of generated phase paths only one path for each initial coordinate value is selected in Monte Karlo process.Keywords: Path integral, saddle point method, semiclassical approximation, transition probability
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15967119 Synthesis of Filtering in Stochastic Systems on Continuous-Time Memory Observations in the Presence of Anomalous Noises
Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov
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We have conducted the optimal synthesis of rootmean- squared objective filter to estimate the state vector in the case if within the observation channel with memory the anomalous noises with unknown mathematical expectation are complement in the function of the regular noises. The synthesis has been carried out for linear stochastic systems of continuous - time.
Keywords: Mathematical expectation, filtration, anomalous noise, memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19587118 Performance Analysis of 5G for Low Latency Transmission Based on Universal Filtered Multi-Carrier Technique and Interleave Division Multiple Access
Authors: A. Asgharzadeh, M. Maroufi
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5G mobile communication system has drawn more and more attention. The 5G system needs to provide three different types of services, including enhanced Mobile BroadBand (eMBB), massive machine-type communication (mMTC), and ultra-reliable and low-latency communication (URLLC). Universal Filtered Multi-Carrier (UFMC), Filter Bank Multicarrier (FBMC), and Filtered Orthogonal Frequency Division Multiplexing (f-OFDM) are suggested as a well-known candidate waveform for the coming 5G system. Themachine-to-machine (M2M) communications are one of the essential applications in 5G, and it involves exchanging of concise messages with a very short latency. However, in UFMC systems, the subcarriers are grouped into subbands but f-OFDM only one subband covers the entire band. Furthermore, in FBMC, a subband includes only one subcarrier, and the number of subbands is the same as the number of subcarriers. This paper mainly discusses the performance of UFMC with different parameters for the UFMC system. Also, paper shows that UFMC is the best choice outperforming OFDM in any case and FBMC in case of very short packets while performing similarly for long sequences with channel estimation techniques for Interleave Division Multiple Access (IDMA) systems.
Keywords: UFMC, IDMA, 5G, subband.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4607117 Multimode Dynamics of the Beijing Road Traffic System
Authors: Zundong Zhang, Limin Jia, Xiaoliang Sun
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The Beijing road traffic system, as a typical huge urban traffic system, provides a platform for analyzing the complex characteristics and the evolving mechanisms of urban traffic systems. Based on dynamic network theory, we construct the dynamic model of the Beijing road traffic system in which the dynamical properties are described completely. Furthermore, we come into the conclusion that urban traffic systems can be viewed as static networks, stochastic networks and complex networks at different system phases by analyzing the structural randomness. As well as, we demonstrate the evolving process of the Beijing road traffic network based on real traffic data, validate the stochastic characteristics and the scale-free property of the network at different phasesKeywords: Dynamic Network Models, Structural Randomness, Scale-free Property, Multi-mode character
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15227116 Forecasting Issues in Energy Markets within a Reg-ARIMA Framework
Authors: Ilaria Lucrezia Amerise
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Electricity markets throughout the world have undergone substantial changes. Accurate, reliable, clear and comprehensible modeling and forecasting of different variables (loads and prices in the first instance) have achieved increasing importance. In this paper, we describe the actual state of the art focusing on reg-SARMA methods, which have proven to be flexible enough to accommodate the electricity price/load behavior satisfactory. More specifically, we will discuss: 1) The dichotomy between point and interval forecasts; 2) The difficult choice between stochastic (e.g. climatic variation) and non-deterministic predictors (e.g. calendar variables); 3) The confrontation between modelling a single aggregate time series or creating separated and potentially different models of sub-series. The noteworthy point that we would like to make it emerge is that prices and loads require different approaches that appear irreconcilable even though must be made reconcilable for the interests and activities of energy companies.Keywords: Forecasting problem, interval forecasts, time series, electricity prices, reg-plus-SARMA methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8027115 Fish Locomotion for Innovative Marine Propulsion Systems
Authors: Omar B. Yaakob, Yasser M. Ahmed, Ahmad F. Said
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There is an essential need for obtaining the mathematical representation of fish body undulations, which can be used for designing and building new innovative types of marine propulsion systems with less environmental impact. This research work presents a case study to derive the mathematical model for fish body movement. Observation and capturing image methods were used in this study in order to obtain a mathematical representation of Clariasbatrachus fish (catfish). An experiment was conducted by using an aquarium with dimension 0.609 m x 0.304 m x 0.304 m, and a 0.5 m ruler was attached at the base of the aquarium. Progressive Scan Monochrome Camera was positioned at 1.8 m above the base of the aquarium to provide swimming sequences. Seven points were marked on the fish body using white marker to indicate the fish movement and measuring the amplitude of undulation. Images from video recordings (20 frames/s) were analyzed frame by frame using local coordinate system, with time interval 0.05 s. The amplitudes of undulations were obtained for image analysis from each point that has been marked on fish body. A graph of amplitude of undulations versus time was plotted by using computer to derive a mathematical fit. The function for the graph is polynomial with nine orders.
Keywords: Fish locomotion, body undulation, steady and unsteady swimming modes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21857114 Improving Spatiotemporal Change Detection: A High Level Fusion Approach for Discovering Uncertain Knowledge from Satellite Image Database
Authors: Wadii Boulila, Imed Riadh Farah, Karim Saheb Ettabaa, Basel Solaiman, Henda Ben Ghezala
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This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.
Keywords: Knowledge discovery in satellite databases, knowledge fusion, data imperfection, data mining, spatiotemporal change detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15377113 Ground Motion Modelling in Bangladesh Using Stochastic Method
Authors: Mizan Ahmed, Srikanth Venkatesan
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Geological and tectonic framework indicates that Bangladesh is one of the most seismically active regions in the world. The Bengal Basin is at the junction of three major interacting plates: the Indian, Eurasian, and Burma Plates. Besides there are many active faults within the region, e.g. the large Dauki fault in the north. The country has experienced a number of destructive earthquakes due to the movement of these active faults. Current seismic provisions of Bangladesh are mostly based on earthquake data prior to the 1990. Given the record of earthquakes post 1990, there is a need to revisit the design provisions of the code. This paper compares the base shear demand of three major cities in Bangladesh: Dhaka (the capital city), Sylhet, and Chittagong for earthquake scenarios of magnitudes 7.0MW, 7.5MW, 8.0MW, and 8.5MW using a stochastic model. In particular, the stochastic model allows the flexibility to input region specific parameters such as shear wave velocity profile (that were developed from Global Crustal Model CRUST2.0) and include the effects of attenuation as individual components. Effects of soil amplification were analysed using the Extended Component Attenuation Model (ECAM). Results show that the estimated base shear demand is higher in comparison with code provisions leading to the suggestion of additional seismic design consideration in the study regions.Keywords: Attenuation, earthquake, ground motion, stochastic, seismic hazard.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20287112 A Study on Exclusive Breastfeeding using Over-dispersed Statistical Models
Authors: Naushad Mamode Khan, Cheika Jahangeer, Maleika Heenaye-Mamode Khan
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Breastfeeding is an important concept in the maternal life of a woman. In this paper, we focus on exclusive breastfeeding. Exclusive breastfeeding is the feeding of a baby on no other milk apart from breast milk. This type of breastfeeding is very important during the first six months because it supports optimal growth and development during infancy and reduces the risk of obliterating diseases and problems. Moreover, in Mauritius, exclusive breastfeeding has decreased the incidence and/or severity of diarrhea, lower respiratory infection and urinary tract infection. In this paper, we give an overview of exclusive breastfeeding in Mauritius and the factors influencing it. We further analyze the local practices of exclusive breastfeeding using the Generalized Poisson regression model and the negative-binomial model since the data are over-dispersed.
Keywords: Exclusive breast feeding, regression model, generalized poisson, negative binomial.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15877111 A New Approach to Feedback Shift Registers
Authors: Myat Su Mon Win
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The pseudorandom number generators based on linear feedback shift registers (LFSRs), are very quick, easy and secure in the implementation of hardware and software. Thus they are very popular and widely used. But LFSRs lead to fairly easy cryptanalysis due to their completely linearity properties. In this paper, we propose a stochastic generator, which is called Random Feedback Shift Register (RFSR), using stochastic transformation (Random block) with one-way and non-linearity properties.Keywords: Linear Feedback Shift Register, Non Linearity, R_Block, Random Feedback Shift Register
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18007110 Diagnosing the Cause and its Timing of Changes in Multivariate Process Mean Vector from Quality Control Charts using Artificial Neural Network
Authors: Farzaneh Ahmadzadeh
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Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.Keywords: Artificial neural network, change point estimation, monte carlo simulation, multivariate exponentially weighted movingaverage
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13667109 Non-equilibrium Statistical Mechanics of a Driven Lattice Gas Model: Probability Function, FDT-violation, and Monte Carlo Simulations
Authors: K. Sudprasert, M. Precharattana, N. Nuttavut, D. Triampo, B. Pattanasiri, Y. Lenbury, W. Triampo
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The study of non-equilibrium systems has attracted increasing interest in recent years, mainly due to the lack of theoretical frameworks, unlike their equilibrium counterparts. Studying the steady state and/or simple systems is thus one of the main interests. Hence in this work we have focused our attention on the driven lattice gas model (DLG model) consisting of interacting particles subject to an external field E. The dynamics of the system are given by hopping of particles to nearby empty sites with rates biased for jumps in the direction of E. Having used small two dimensional systems of DLG model, the stochastic properties at nonequilibrium steady state were analytically studied. To understand the non-equilibrium phenomena, we have applied the analytic approach via master equation to calculate probability function and analyze violation of detailed balance in term of the fluctuation-dissipation theorem. Monte Carlo simulations have been performed to validate the analytic results.Keywords: Non-equilibrium, lattice gas, stochastic process
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17227108 Reliability Analysis for Cyclic Fatigue Life Prediction in Railroad Bolt Hole
Authors: Hasan Keshavarzian, Tayebeh Nesari
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Bolted rail joint is one of the most vulnerable areas in railway track. A comprehensive approach was developed for studying the reliability of fatigue crack initiation of railroad bolt hole under random axle loads and random material properties. The operation condition was also considered as stochastic variables. In order to obtain the comprehensive probability model of fatigue crack initiation life prediction in railroad bolt hole, we used FEM, response surface method (RSM), and reliability analysis. Combined energy-density based and critical plane based fatigue concept is used for the fatigue crack prediction. The dynamic loads were calculated according to the axle load, speed, and track properties. The results show that axle load is most sensitive parameter compared to Poisson’s ratio in fatigue crack initiation life. Also, the reliability index decreases slowly due to high cycle fatigue regime in this area.Keywords: Rail-wheel tribology, rolling contact mechanic, finite element modeling, reliability analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10987107 An Evaluation of Algorithms for Single-Echo Biosonar Target Classification
Authors: Turgay Temel, John Hallam
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A recent neurospiking coding scheme for feature extraction from biosonar echoes of various plants is examined with avariety of stochastic classifiers. Feature vectors derived are employedin well-known stochastic classifiers, including nearest-neighborhood,single Gaussian and a Gaussian mixture with EM optimization.Classifiers' performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifers perform equivalently and that the modified preprocessing configuration yields considerably improved results.
Keywords: Classification, neuro-spike coding, non-parametricmodel, parametric model, Gaussian mixture, EM algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16567106 Stochastic Modeling and Combined Spatial Pattern Analysis of Epidemic Spreading
Authors: S. Chadsuthi, W. Triampo, C. Modchang, P. Kanthang, D. Triampo, N. Nuttavut
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We present analysis of spatial patterns of generic disease spread simulated by a stochastic long-range correlation SIR model, where individuals can be infected at long distance in a power law distribution. We integrated various tools, namely perimeter, circularity, fractal dimension, and aggregation index to characterize and investigate spatial pattern formations. Our primary goal was to understand for a given model of interest which tool has an advantage over the other and to what extent. We found that perimeter and circularity give information only for a case of strong correlation– while the fractal dimension and aggregation index exhibit the growth rule of pattern formation, depending on the degree of the correlation exponent (β). The aggregation index method used as an alternative method to describe the degree of pathogenic ratio (α). This study may provide a useful approach to characterize and analyze the pattern formation of epidemic spreadingKeywords: spatial pattern epidemics, aggregation index, fractaldimension, stochastic, long-rang epidemics
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16697105 Statistical Characteristics of Distribution of Radiation-Induced Defects under Random Generation
Authors: Pavlo Selyshchev
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We consider fluctuations of defects density taking into account their interaction. Stochastic field of displacement generation rate gives random defect distribution. We determinate statistical characteristics (mean and dispersion) of random field of point defect distribution as function of defect generation parameters, temperature and properties of irradiated crystal.
Keywords: Irradiation, Primary Defects, Interaction, Fluctuations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18297104 Damage Localization of Deterministic-Stochastic Systems
Authors: Yen-Po Wang, Ming-Chih Huang, Ming-Lian Chang
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A scheme integrated with deterministic–stochastic subspace system identification and the method of damage localization vector is proposed in this study for damage detection of structures based on seismic response data. A series of shaking table tests using a five-storey steel frame has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom. Both single and combinations of multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged (ill-conditioned) counterpart has also been studied. The proposed scheme proves to be effective.
Keywords: Damage locating vectors, deterministic-stochastic subspace system, shaking table tests, system identification.
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