Search results for: filtering of stochastic signals.
1134 Stochastic Estimation of Cavity Flowfield
Authors: Yin Yin Pey, Leok Poh Chua, Wei Long Siauw
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Linear stochastic estimation and quadratic stochastic estimation techniques were applied to estimate the entire velocity flow-field of an open cavity with a length to depth ratio of 2. The estimations were done through the use of instantaneous velocity magnitude as estimators. These measurements were obtained by Particle Image Velocimetry. The predicted flow was compared against the original flow-field in terms of the Reynolds stresses and turbulent kinetic energy. Quadratic stochastic estimation proved to be more superior than linear stochastic estimation in resolving the shear layer flow. When the velocity fluctuations were scaled up in the quadratic estimate, both the time-averaged quantities and the instantaneous cavity flow can be predicted to a rather accurate extent.Keywords: Open cavity, Particle Image Velocimetry, Stochastic estimation, Turbulent kinetic energy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16621133 Culturally Enhanced Collaborative Filtering
Authors: Mahboobe Zardosht, Nasser Ghasem-Aghaee
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We propose an enhanced collaborative filtering method using Hofstede-s cultural dimensions, calculated for 111 countries. We employ 4 of these dimensions, which are correlated to the costumers- buying behavior, in order to detect users- preferences for items. In addition, several advantages of this method demonstrated for data sparseness and cold-start users, which are important challenges in collaborative filtering. We present experiments using a real dataset, Book Crossing Dataset. Experimental results shows that the proposed algorithm provide significant advantages in terms of improving recommendation quality.Keywords: Collaborative filtering, Cross-cultural, E-commerce, Recommender systems
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18071132 Stochastic Programming Model for Power Generation
Authors: Takayuki Shiina
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We consider power system expansion planning under uncertainty. In our approach, integer programming and stochastic programming provide a basic framework. We develop a multistage stochastic programming model in which some of the variables are restricted to integer values. By utilizing the special property of the problem, called block separable recourse, the problem is transformed into a two-stage stochastic program with recourse. The electric power capacity expansion problem is reformulated as the problem with first stage integer variables and continuous second stage variables. The L-shaped algorithm to solve the problem is proposed.Keywords: electric power capacity expansion problem, integerprogramming, L-shaped method, stochastic programming
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17781131 The Evaluation of the Performance of Different Filtering Approaches in Tracking Problem and the Effect of Noise Variance
Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri
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Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results.
Keywords: Gaussian approximation, KALMAN smoother, Parameter estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17201130 Microcontroller Based EOG Guided Wheelchair
Authors: Jobby K. Chacko, Deepu Oommen, Kevin K. Mathew, Noble Sunny, N. Babu
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A new cost effective, eye controlled method was introduced to guide and control a wheel chair for disable people, based on Electrooculography (EOG). The guidance and control is effected by eye ball movements within the socket. The system consists of a standard electric wheelchair with an on-board microcontroller system attached. EOG is a new technology to sense the eye signals for eye movements and these signals are captured using electrodes, signal processed such as amplification, noise filtering, and then given to microcontroller which drives the motors attached with wheel chair for propulsion. This technique could be very useful in applications such as mobility for handicapped and paralyzed persons.
Keywords: Electrooculography, Microcontroller, Signal processing, Wheelchair.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 55441129 A Novel Impulse Detector for Filtering of Highly Corrupted Images
Authors: Umesh Ghanekar
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As the performance of the filtering system depends upon the accuracy of the noise detection scheme, in this paper, we present a new scheme for impulse noise detection based on two levels of decision. In this scheme in the first stage we coarsely identify the corrupted pixels and in the second stage we finally decide whether the pixel under consideration is really corrupt or not. The efficacy of the proposed filter has been confirmed by extensive simulations.Keywords: Impulse detection, noise removal, image filtering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13681128 Stochastic Scheduling to Minimize Expected Lateness in Multiple Identical Machines
Authors: Ghulam Zakria, Zailin Guan , Yasser Riaz Awan, Wan Lizhi
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There are many real world problems in which parameters like the arrival time of new jobs, failure of resources, and completion time of jobs change continuously. This paper tackles the problem of scheduling jobs with random due dates on multiple identical machines in a stochastic environment. First to assign jobs to different machine centers LPT scheduling methods have been used, after that the particular sequence of jobs to be processed on the machine have been found using simple stochastic techniques. The performance parameter under consideration has been the maximum lateness concerning the stochastic due dates which are independent and exponentially distributed. At the end a relevant problem has been solved using the techniques in the paper..Keywords: Quantity Production Flow Shop, LPT Scheduling, Stochastic Scheduling, Maximum Lateness, Random Due Dates
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13531127 Comparison of Reliability Systems Based Uncertainty
Authors: A. Aissani, H. Benaoudia
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Stochastic comparison has been an important direction of research in various area. This can be done by the use of the notion of stochastic ordering which gives qualitatitive rather than purely quantitative estimation of the system under study. In this paper we present applications of comparison based uncertainty related to entropy in Reliability analysis, for example to design better systems. These results can be used as a priori information in simulation studies.Keywords: Uncertainty, Stochastic comparison, Reliability, serie's system, imperfect repair.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12091126 On Diffusion Approximation of Discrete Markov Dynamical Systems
Authors: Jevgenijs Carkovs
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The paper is devoted to stochastic analysis of finite dimensional difference equation with dependent on ergodic Markov chain increments, which are proportional to small parameter ". A point-form solution of this difference equation may be represented as vertexes of a time-dependent continuous broken line given on the segment [0,1] with "-dependent scaling of intervals between vertexes. Tending " to zero one may apply stochastic averaging and diffusion approximation procedures and construct continuous approximation of the initial stochastic iterations as an ordinary or stochastic Ito differential equation. The paper proves that for sufficiently small " these equations may be successfully applied not only to approximate finite number of iterations but also for asymptotic analysis of iterations, when number of iterations tends to infinity.Keywords: Markov dynamical system, diffusion approximation, equilibrium stochastic stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15221125 The Strict Stability of Impulsive Stochastic Functional Differential Equations with Markovian Switching
Authors: Dezhi Liu Guiyuan Yang Wei Zhang
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Strict stability can present the rate of decay of the solution, so more and more investigators are beginning to study the topic and some results have been obtained. However, there are few results about strict stability of stochastic differential equations. In this paper, using Lyapunov functions and Razumikhin technique, we have gotten some criteria for the strict stability of impulsive stochastic functional differential equations with markovian switching.Keywords: Impulsive; Stochastic functional differential equation; Strict stability; Razumikhin technique.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12421124 A New Approaches for Seismic Signals Discrimination
Authors: M. Benbrahim, K. Benjelloun, A. Ibenbrahim, M. Kasmi, E. Ardil
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The automatic discrimination of seismic signals is an important practical goal for the earth-science observatories due to the large amount of information that they receive continuously. An essential discrimination task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present new techniques for seismic signals classification: local, regional and global discrimination. These techniques were tested on seismic signals from the data base of the National Geophysical Institute of the Centre National pour la Recherche Scientifique et Technique (Morocco) by using the Moroccan software for seismic signals analysis.
Keywords: Seismic signals, local discrimination, regionaldiscrimination, global discrimination, Moroccan software for seismicsignals analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15041123 Mean Square Stability of Impulsive Stochastic Delay Differential Equations with Markovian Switching and Poisson Jumps
Authors: Dezhi Liu
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In the paper, based on stochastic analysis theory and Lyapunov functional method, we discuss the mean square stability of impulsive stochastic delay differential equations with markovian switching and poisson jumps, and the sufficient conditions of mean square stability have been obtained. One example illustrates the main results. Furthermore, some well-known results are improved and generalized in the remarks.
Keywords: Impulsive, stochastic, delay, Markovian switching, Poisson jumps, mean square stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15121122 Numerical Analysis of All-Optical Microwave Mixing and Bandpass Filtering in an RoF Link
Authors: S. Khosroabadi, M. R. Salehi
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In this paper, all-optical signal processors that perform both microwave mixing and bandpass filtering in a radio-over-fiber (RoF) link are presented. The key device is a Mach-Zehnder modulator (MZM) which performs all-optical microwave mixing. An up-converted microwave signal is obtained and other unwanted frequency components are suppressed at the end of the fiber span.Keywords: Microwave mixing, bandpass filtering, all-optical, signal processing, MZM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16791121 Adaptive Filtering of Heart Rate Signals for an Improved Measure of Cardiac Autonomic Control
Authors: Desmond B. Keenan, Paul Grossman
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In order to provide accurate heart rate variability indices of sympathetic and parasympathetic activity, the low frequency and high frequency components of an RR heart rate signal must be adequately separated. This is not always possible by just applying spectral analysis, as power from the high and low frequency components often leak into their adjacent bands. Furthermore, without the respiratory spectra it is not obvious that the low frequency component is not another respiratory component, which can appear in the lower band. This paper describes an adaptive filter, which aids the separation of the low frequency sympathetic and high frequency parasympathetic components from an ECG R-R interval signal, enabling the attainment of more accurate heart rate variability measures. The algorithm is applied to simulated signals and heart rate and respiratory signals acquired from an ambulatory monitor incorporating single lead ECG and inductive plethysmography sensors embedded in a garment. The results show an improvement over standard heart rate variability spectral measurements.Keywords: Heart rate variability, vagal tone, sympathetic, parasympathetic, spectral analysis, adaptive filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17071120 Building and Tree Detection Using Multiscale Matched Filtering
Authors: Abdullah H. Özcan, Dilara Hisar, Yetkin Sayar, Cem Ünsalan
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In this study, an automated building and tree detection method is proposed using DSM data and true orthophoto image. A multiscale matched filtering is used on DSM data. Therefore, first watershed transform is applied. Then, Otsu’s thresholding method is used as an adaptive threshold to segment each watershed region. Detected objects are masked with NDVI to separate buildings and trees. The proposed method is able to detect buildings and trees without entering any elevation threshold. We tested our method on ISPRS semantic labeling dataset and obtained promising results.Keywords: Building detection, tree detection, matched filtering, multiscale, local maximum filtering, watershed segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4931119 A Robust and Adaptive Unscented Kalman Filter for the Air Fine Alignment of the Strapdown Inertial Navigation System/GPS
Authors: Jian Shi, Baoguo Yu, Haonan Jia, Meng Liu, Ping Huang
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Adapting to the flexibility of war, a large number of guided weapons launch from aircraft. Therefore, the inertial navigation system loaded in the weapon needs to undergo an alignment process in the air. This article proposes the following methods to the problem of inaccurate modeling of the system under large misalignment angles, the accuracy reduction of filtering caused by outliers, and the noise changes in GPS signals: first, considering the large misalignment errors of Strapdown Inertial Navigation System (SINS)/GPS, a more accurate model is made rather than to make a small-angle approximation, and the Unscented Kalman Filter (UKF) algorithms are used to estimate the state; then, taking into account the impact of GPS noise changes on the fine alignment algorithm, the innovation adaptive filtering algorithm is introduced to estimate the GPS’s noise in real-time; at the same time, in order to improve the anti-interference ability of the air fine alignment algorithm, a robust filtering algorithm based on outlier detection is combined with the air fine alignment algorithm to improve the robustness of the algorithm. The algorithm can improve the alignment accuracy and robustness under interference conditions, which is verified by simulation.
Keywords: Air alignment, fine alignment, inertial navigation system, integrated navigation system, UKF.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4681118 Segmentation of Noisy Digital Images with Stochastic Gradient Kernel
Authors: Abhishek Neogi, Jayesh Verma, Pinaki Pratim Acharjya
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Image segmentation and edge detection is a fundamental section in image processing. In case of noisy images Edge Detection is very less effective if we use conventional Spatial Filters like Sobel, Prewitt, LOG, Laplacian etc. To overcome this problem we have proposed the use of Stochastic Gradient Mask instead of Spatial Filters for generating gradient images. The present study has shown that the resultant images obtained by applying Stochastic Gradient Masks appear to be much clearer and sharper as per Edge detection is considered.Keywords: Image segmentation, edge Detection, noisy images, spatialfilters, stochastic gradient kernel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14741117 Noise Analysis of Single-Ended Input Differential Amplifier using Stochastic Differential Equation
Authors: Tarun Kumar Rawat, Abhirup Lahiri, Ashish Gupta
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In this paper, we analyze the effect of noise in a single- ended input differential amplifier working at high frequencies. Both extrinsic and intrinsic noise are analyzed using time domain method employing techniques from stochastic calculus. Stochastic differential equations are used to obtain autocorrelation functions of the output noise voltage and other solution statistics like mean and variance. The analysis leads to important design implications and suggests changes in the device parameters for improved noise characteristics of the differential amplifier.
Keywords: Single-ended input differential amplifier, Noise, stochastic differential equation, mean and variance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16511116 A Scenario-Based Approach for the Air Traffic Flow Management Problem with Stochastic Capacities
Authors: Soumia Ichoua
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In this paper, we investigate the strategic stochastic air traffic flow management problem which seeks to balance airspace capacity and demand under weather disruptions. The goal is to reduce the need for myopic tactical decisions that do not account for probabilistic knowledge about the NAS near-future states. We present and discuss a scenario-based modeling approach based on a time-space stochastic process to depict weather disruption occurrences in the NAS. A solution framework is also proposed along with a distributed implementation aimed at overcoming scalability problems. Issues related to this implementation are also discussed.
Keywords: Air traffic management, sample average approximation, scenario-based approach, stochastic capacity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20341115 Application of Hardware Efficient CIC Compensation Filter in Narrow Band Filtering
Authors: Vishal Awasthi, Krishna Raj
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In many communication and signal processing systems, it is highly desirable to implement an efficient narrow-band filter that decimate or interpolate the incoming signals. This paper presents hardware efficient compensated CIC filter over a narrow band frequency that increases the speed of down sampling by using multiplierless decimation filters with polyphase FIR filter structure. The proposed work analyzed the performance of compensated CIC filter on the bases of the improvement of frequency response with reduced hardware complexity in terms of no. of adders and multipliers and produces the filtered results without any alterations. CIC compensator filter demonstrated that by using compensation with CIC filter improve the frequency response in passed of interest 26.57% with the reduction in hardware complexity 12.25% multiplications per input sample (MPIS) and 23.4% additions per input sample (APIS) w.r.t. FIR filter respectively.
Keywords: Multirate filtering, Narrow-band Signaling, Compensation Theory, CIC filter, Decimation, Compensation filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28981114 PTH Moment Exponential Stability of Stochastic Recurrent Neural Networks with Distributed Delays
Authors: Zixin Liu, Jianjun Jiao Wanping Bai
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In this paper, the issue of pth moment exponential stability of stochastic recurrent neural network with distributed time delays is investigated. By using the method of variation parameters, inequality techniques, and stochastic analysis, some sufficient conditions ensuring pth moment exponential stability are obtained. The method used in this paper does not resort to any Lyapunov function, and the results derived in this paper generalize some earlier criteria reported in the literature. One numerical example is given to illustrate the main results.
Keywords: Stochastic recurrent neural networks, pth moment exponential stability, distributed time delays.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12131113 A Computational Stochastic Modeling Formalism for Biological Networks
Authors: Werner Sandmann, Verena Wolf
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Stochastic models of biological networks are well established in systems biology, where the computational treatment of such models is often focused on the solution of the so-called chemical master equation via stochastic simulation algorithms. In contrast to this, the development of storage-efficient model representations that are directly suitable for computer implementation has received significantly less attention. Instead, a model is usually described in terms of a stochastic process or a "higher-level paradigm" with graphical representation such as e.g. a stochastic Petri net. A serious problem then arises due to the exponential growth of the model-s state space which is in fact a main reason for the popularity of stochastic simulation since simulation suffers less from the state space explosion than non-simulative numerical solution techniques. In this paper we present transition class models for the representation of biological network models, a compact mathematical formalism that circumvents state space explosion. Transition class models can also serve as an interface between different higher level modeling paradigms, stochastic processes and the implementation coded in a programming language. Besides, the compact model representation provides the opportunity to apply non-simulative solution techniques thereby preserving the possible use of stochastic simulation. Illustrative examples of transition class representations are given for an enzyme-catalyzed substrate conversion and a part of the bacteriophage λ lysis/lysogeny pathway.
Keywords: Computational Modeling, Biological Networks, Stochastic Models, Markov Chains, Transition Class Models.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15371112 Analysis 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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For optimal unbiased filter as mean-square and in the case of functioning anomalous noises in the observation memory channel, we have proved insensitivity of filter to inaccurate knowledge of the anomalous noise intensity matrix and its equivalence to truncated filter plotted only by non anomalous components of an observation vector.
Keywords: Mathematical expectation, filtration, anomalous noise, memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20071111 Passivity Analysis of Stochastic Neural Networks With Multiple Time Delays
Authors: Biao Qin, Jin Huang, Jiaojiao Ren, Wei Kang
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This paper deals with the problem of passivity analysis for stochastic neural networks with leakage, discrete and distributed delays. By using delay partitioning technique, free weighting matrix method and stochastic analysis technique, several sufficient conditions for the passivity of the addressed neural networks are established in terms of linear matrix inequalities (LMIs), in which both the time-delay and its time derivative can be fully considered. A numerical example is given to show the usefulness and effectiveness of the obtained results.
Keywords: Passivity, Stochastic neural networks, Multiple time delays, Linear matrix inequalities (LMIs).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16641110 Existence of Solution of Nonlinear Second Order Neutral Stochastic Differential Inclusions with Infinite Delay
Authors: Yong Li
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The paper is concerned with the existence of solution of nonlinear second order neutral stochastic differential inclusions with infinite delay in a Hilbert Space. Sufficient conditions for the existence are obtained by using a fixed point theorem for condensing maps.
Keywords: Mild solution, Convex multivalued map, Neutral stochastic differential inclusions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15591109 Formulating the Stochastic Finite Elements for Free Vibration Analysis of Plates with Variable Elastic Modulus
Authors: Mojtaba Aghamiri Esfahani, Mohammad Karkon, Seyed Majid Hosseini Nezhad, Reza Hosseini-Ara
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In this study, the effect of uncertainty in elastic modulus of a plate on free vibration response is investigated. For this purpose, the elastic modulus of the plate is modeled as stochastic variable with normal distribution. Moreover, the distance autocorrelation function is used for stochastic field. Then, by applying the finite element method and Monte Carlo simulation, stochastic finite element relations are extracted. Finally, with a numerical test, the effect of uncertainty in the elastic modulus on free vibration response of a plate is studied. The results show that the effect of uncertainty in elastic modulus of the plate cannot play an important role on the free vibration response.
Keywords: Stochastic finite elements, plate bending, free vibration, Monte Carlo, Neumann expansion method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16451108 Layout Based Spam Filtering
Authors: Claudiu N.Musat
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Due to the constant increase in the volume of information available to applications in fields varying from medical diagnosis to web search engines, accurate support of similarity becomes an important task. This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision. We present a novel approach to filtering based solely on layout, whose goal is not only to correctly identify spam, but also warn about major emerging threats. We propose a mathematical formulation of the email message layout and based on it we elaborate an algorithm to separate different types of emails and find the new, numerically relevant spam types.
Keywords: Clustering, layout, k-means, spam.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16071107 A Multi-Feature Deep Learning Algorithm for Urban Traffic Classification with Limited Labeled Data
Authors: Rohan Putatunda, Aryya Gangopadhyay
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Acoustic sensors, if embedded in smart street lights, can help in capturing the activities (car honking, sirens, events, traffic, etc.) in cities. Needless to say, the acoustic data from such scenarios are complex due to multiple audio streams originating from different events, and when decomposed to independent signals, the amount of retrieved data volume is small in quantity which is inadequate to train deep neural networks. So, in this paper, we address the two challenges: a) separating the mixed signals, and b) developing an efficient acoustic classifier under data paucity. So, to address these challenges, we propose an architecture with supervised deep learning, where the initial captured mixed acoustics data are analyzed with Fast Fourier Transformation (FFT), followed by filtering the noise from the signal, and then decomposed to independent signals by fast independent component analysis (Fast ICA). To address the challenge of data paucity, we propose a multi feature-based deep neural network with high performance that is reflected in our experiments when compared to the conventional convolutional neural network (CNN) and multi-layer perceptron (MLP).
Keywords: FFT, ICA, vehicle classification, multi-feature DNN, CNN, MLP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3611106 Stochastic Comparisons of Heterogeneous Samples with Homogeneous Exponential Samples
Authors: Nitin Gupta, Rakesh Kumar Bajaj
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In the present communication, stochastic comparison of a series (parallel) system having heterogeneous components with random lifetimes and series (parallel) system having homogeneous exponential components with random lifetimes has been studied. Further, conditions under which such a comparison is possible has been established.Keywords: Exponential distribution, Order statistics, Star ordering, Stochastic ordering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15291105 Dempster-Shafer Information Filtering in Multi-Modality Wireless Sensor Networks
Authors: D.M. Weeraddana, K.S. Walgama, E.C. Kulasekere
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A framework to estimate the state of dynamically varying environment where data are generated from heterogeneous sources possessing partial knowledge about the environment is presented. This is entirely derived within Dempster-Shafer and Evidence Filtering frameworks. The belief about the current state is expressed as belief and plausibility functions. An addition to Single Input Single Output Evidence Filter, Multiple Input Single Output Evidence Filtering approach is introduced. Variety of applications such as situational estimation of an emergency environment can be developed within the framework successfully. Fire propagation scenario is used to justify the proposed framework, simulation results are presented.
Keywords: Dempster-Shafer Belief theory, Evidence Filtering, Evidence Fusion, Sensor Modalities, Wireless Sensor Networks
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