Search results for: Discrete Radon Transform
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1188

Search results for: Discrete Radon Transform

1008 T-Wave Detection Based on an Adjusted Wavelet Transform Modulus Maxima

Authors: Samar Krimi, Kaïs Ouni, Noureddine Ellouze

Abstract:

The method described in this paper deals with the problems of T-wave detection in an ECG. Determining the position of a T-wave is complicated due to the low amplitude, the ambiguous and changing form of the complex. A wavelet transform approach handles these complications therefore a method based on this concept was developed. In this way we developed a detection method that is able to detect T-waves with a sensitivity of 93% and a correct-detection ratio of 93% even with a serious amount of baseline drift and noise.

Keywords: ECG, Modulus Maxima Wavelet Transform, Performance, T-wave detection

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1007 Continuous Plug Flow and Discrete Particle Phase Coupling Using Triangular Parcels

Authors: Anders Schou Simonsen, Thomas Condra, Kim Sørensen

Abstract:

Various processes are modelled using a discrete phase, where particles are seeded from a source. Such particles can represent liquid water droplets, which are affecting the continuous phase by exchanging thermal energy, momentum, species etc. Discrete phases are typically modelled using parcel, which represents a collection of particles, which share properties such as temperature, velocity etc. When coupling the phases, the exchange rates are integrated over the cell, in which the parcel is located. This can cause spikes and fluctuating exchange rates. This paper presents an alternative method of coupling a discrete and a continuous plug flow phase. This is done using triangular parcels, which span between nodes following the dynamics of single droplets. Thus, the triangular parcels are propagated using the corner nodes. At each time step, the exchange rates are spatially integrated over the surface of the triangular parcels, which yields a smooth continuous exchange rate to the continuous phase. The results shows that the method is more stable, converges slightly faster and yields smooth exchange rates compared with the steam tube approach. However, the computational requirements are about five times greater, so the applicability of the alternative method should be limited to processes, where the exchange rates are important. The overall balances of the exchanged properties did not change significantly using the new approach.

Keywords: CFD, coupling, discrete phase, parcel.

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1006 Investigation of Wave Atom Sub-Bands via Breast Cancer Classification

Authors: Nebi Gedik, Ayten Atasoy

Abstract:

This paper investigates successful sub-bands of wave atom transform via classification of mammograms, when the coefficients of sub-bands are used as features. A computer-aided diagnosis system is constructed by using wave atom transform, support vector machine and k-nearest neighbor classifiers. Two-class classification is studied in detail using two data sets, separately. The successful sub-bands are determined according to the accuracy rates, coefficient numbers, and sensitivity rates.

Keywords: Breast cancer, wave atom transform, SVM, k-NN.

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1005 Fingerprint Compression Using Contourlet Transform and Multistage Vector Quantization

Authors: S. Esakkirajan, T. Veerakumar, V. Senthil Murugan, R. Sudhakar

Abstract:

This paper presents a new fingerprint coding technique based on contourlet transform and multistage vector quantization. Wavelets have shown their ability in representing natural images that contain smooth areas separated with edges. However, wavelets cannot efficiently take advantage of the fact that the edges usually found in fingerprints are smooth curves. This issue is addressed by directional transforms, known as contourlets, which have the property of preserving edges. The contourlet transform is a new extension to the wavelet transform in two dimensions using nonseparable and directional filter banks. The computation and storage requirements are the major difficulty in implementing a vector quantizer. In the full-search algorithm, the computation and storage complexity is an exponential function of the number of bits used in quantizing each frame of spectral information. The storage requirement in multistage vector quantization is less when compared to full search vector quantization. The coefficients of contourlet transform are quantized by multistage vector quantization. The quantized coefficients are encoded by Huffman coding. The results obtained are tabulated and compared with the existing wavelet based ones.

Keywords: Contourlet Transform, Directional Filter bank, Laplacian Pyramid, Multistage Vector Quantization

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1004 Efficient Hardware Architecture of the Direct 2- D Transform for the HEVC Standard

Authors: Fatma Belghith, Hassen Loukil, Nouri Masmoudi

Abstract:

This paper presents the hardware design of a unified architecture to compute the 4x4, 8x8 and 16x16 efficient twodimensional (2-D) transform for the HEVC standard. This architecture is based on fast integer transform algorithms. It is designed only with adders and shifts in order to reduce the hardware cost significantly. The goal is to ensure the maximum circuit reuse during the computing while saving 40% for the number of operations. The architecture is developed using FIFOs to compute the second dimension. The proposed hardware was implemented in VHDL. The VHDL RTL code works at 240 MHZ in an Altera Stratix III FPGA. The number of cycles in this architecture varies from 33 in 4-point- 2D-DCT to 172 when the 16-point-2D-DCT is computed. Results show frequency improvements reaching 96% when compared to an architecture described as the direct transcription of the algorithm.

Keywords: HEVC, Modified Integer Transform, FPGA.

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1003 Road Extraction Using Stationary Wavelet Transform

Authors: Somkait Udomhunsakul

Abstract:

In this paper, a novel road extraction method using Stationary Wavelet Transform is proposed. To detect road features from color aerial satellite imagery, Mexican hat Wavelet filters are used by applying the Stationary Wavelet Transform in a multiresolution, multi-scale, sense and forming the products of Wavelet coefficients at a different scales to locate and identify road features at a few scales. In addition, the shifting of road features locations is considered through multiple scales for robust road extraction in the asymmetry road feature profiles. From the experimental results, the proposed method leads to a useful technique to form the basis of road feature extraction. Also, the method is general and can be applied to other features in imagery.

Keywords: Road extraction, Multiresolution, Stationary Wavelet Transform, Multi-scale analysis

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1002 Detection of Sags, Swells, and Transients Using Windowing Technique Based On Continuous S-Transform (CST)

Authors: K. Daud, A. F. Abidin, N. Hamzah, H. S. Nagindar Singh

Abstract:

This paper produces a new approach for power quality analysis using a windowing technique based on Continuous S-transform (CST). This half-cycle window technique approach can detect almost correctly for initial detection of disturbances i.e. voltage sags, swells, and transients. Samples in half cycle window has been analyzed based continuous S-transform for entire disturbance waveform. The modified parameter has been produced by MATLAB programming m-file based on continuous s-transform. CST has better time frequency and localization property than traditional and also has ability to detect the disturbance under noisy condition correctly. The excellent time-frequency resolution characteristic of the CST makes it the most an attractive candidate for analysis of power system disturbances signals.

Keywords: Power quality disturbances, initial detection, half cycle windowing, continuous S-transform.

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1001 Discrete Time Optimal Solution for the Connection Admission Control Problem

Authors: C. Bruni, F. Delli Priscoli, G. Koch, I. Marchetti

Abstract:

The Connection Admission Control (CAC) problem is formulated in this paper as a discrete time optimal control problem. The control variables account for the acceptance/ rejection of new connections and forced dropping of in-progress connections. These variables are constrained to meet suitable conditions which account for the QoS requirements (Link Availability, Blocking Probability, Dropping Probability). The performance index evaluates the total throughput. At each discrete time, the problem is solved as an integer-valued linear programming one. The proposed procedure was successfully tested against suitably simulated data.

Keywords: Connection Admission Control, Optimal Control, Integer valued Linear Programming, Quality of Service Requirements, Robust Control.

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1000 A Novel Technique for Ferroresonance Identification in Distribution Networks

Authors: G. Mokryani, M. R. Haghifam, J. Esmaeilpoor

Abstract:

Happening of Ferroresonance phenomenon is one of the reasons of consuming and ruining transformers, so recognition of Ferroresonance phenomenon has a special importance. A novel method for classification of Ferroresonance presented in this paper. Using this method Ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Competitive Neural Network used for classification. Ferroresonance data and other transients was obtained by simulation using EMTP program. Using Daubechies wavelet transform signals has been decomposed till six levels. The energy of six detailed signals that obtained by wavelet transform are used for training and trailing Competitive Neural Network. Results show that the proposed procedure is efficient in identifying Ferroresonance from other events.

Keywords: Competitive Neural Network, Ferroresonance, EMTP program, Wavelet transform.

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999 Human Action Recognition Based on Ridgelet Transform and SVM

Authors: A. Ouanane, A. Serir

Abstract:

In this paper, a novel algorithm based on Ridgelet Transform and support vector machine is proposed for human action recognition. The Ridgelet transform is a directional multi-resolution transform and it is more suitable for describing the human action by performing its directional information to form spatial features vectors. The dynamic transition between the spatial features is carried out using both the Principal Component Analysis and clustering algorithm K-means. First, the Principal Component Analysis is used to reduce the dimensionality of the obtained vectors. Then, the kmeans algorithm is then used to perform the obtained vectors to form the spatio-temporal pattern, called set-of-labels, according to given periodicity of human action. Finally, a Support Machine classifier is used to discriminate between the different human actions. Different tests are conducted on popular Datasets, such as Weizmann and KTH. The obtained results show that the proposed method provides more significant accuracy rate and it drives more robustness in very challenging situations such as lighting changes, scaling and dynamic environment

Keywords: Human action, Ridgelet Transform, PCA, K-means, SVM.

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998 Image Segmentation by Mathematical Morphology: An Approach through Linear, Bilinear and Conformal Transformation

Authors: Dibyendu Ghoshal, Pinaki Pratim Acharjya

Abstract:

Image segmentation process based on mathematical morphology has been studied in the paper. It has been established from the first principles of the morphological process, the entire segmentation is although a nonlinear signal processing task, the constituent wise, the intermediate steps are linear, bilinear and conformal transformation and they give rise to a non linear affect in a cumulative manner.

Keywords: Image segmentation, linear transform, bilinear transform, conformal transform, mathematical morphology.

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997 Secure Proxy Signature Based on Factoring and Discrete Logarithm

Authors: H. El-Kamchouchi, Heba Gaber, Fatma Ahmed, Dalia H. El-Kamchouchi

Abstract:

A digital signature is an electronic signature form used by an original signer to sign a specific document. When the original signer is not in his office or when he/she travels outside, he/she delegates his signing capability to a proxy signer and then the proxy signer generates a signing message on behalf of the original signer. The two parties must be able to authenticate one another and agree on a secret encryption key, in order to communicate securely over an unreliable public network. Authenticated key agreement protocols have an important role in building a secure communications network between the two parties. In this paper, we present a secure proxy signature scheme over an efficient and secure authenticated key agreement protocol based on factoring and discrete logarithm problem.

Keywords: Discrete logarithm, factoring, proxy signature, key agreement.

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996 Dynamics of a Discrete Three Species Food Chain System

Authors: Kejun Zhuang, Zhaohui Wen

Abstract:

The main purpose of this paper is to investigate a discrete time three–species food chain system with ratio dependence. By employing coincidence degree theory and analysis techniques, sufficient conditions for existence of periodic solutions are established.

Keywords: Food chain, ratio–dependent, coincidence degree, periodic solutions.

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995 Motion Parameter Estimation via Dopplerlet-Transform-Based Matched Field Processing

Authors: Hongyan Dai

Abstract:

This work presents a matched field processing (MFP) algorithm based on Dopplerlet transform for estimating the motion parameters of a sound source moving along a straight line and with a constant speed by using a piecewise strategy, which can significantly reduce the computational burden. Monte Carlo simulation results and an experimental result are presented to verify the effectiveness of the algorithm advocated.

Keywords: matched field processing; Dopplerlet transform; motion parameter estimation; piecewise strategy

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994 Envelope-Wavelet Packet Transform for Machine Condition Monitoring

Authors: M. F. Yaqub, I. Gondal, J. Kamruzzaman

Abstract:

Wavelet transform has been extensively used in machine fault diagnosis and prognosis owing to its strength to deal with non-stationary signals. The existing Wavelet transform based schemes for fault diagnosis employ wavelet decomposition of the entire vibration frequency which not only involve huge computational overhead in extracting the features but also increases the dimensionality of the feature vector. This increase in the dimensionality has the tendency to 'over-fit' the training data and could mislead the fault diagnostic model. In this paper a novel technique, envelope wavelet packet transform (EWPT) is proposed in which features are extracted based on wavelet packet transform of the filtered envelope signal rather than the overall vibration signal. It not only reduces the computational overhead in terms of reduced number of wavelet decomposition levels and features but also improves the fault detection accuracy. Analytical expressions are provided for the optimal frequency resolution and decomposition level selection in EWPT. Experimental results with both actual and simulated machine fault data demonstrate significant gain in fault detection ability by EWPT at reduced complexity compared to existing techniques.

Keywords: Envelope Detection, Wavelet Transform, Bearing Faults, Machine Health Monitoring.

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993 Analysis of Vibration Signal of DC Motor Based on Hilbert-Huang Transform

Authors: Chun-Yao Lee, Hung-Chi Lin

Abstract:

This paper presents a signal analysis process for improving energy completeness based on the Hilbert-Huang Transform (HHT). Firstly, the vibration signal of a DC Motor obtained by employing an accelerometer is the model used to analyze the signal. Secondly, the intrinsic mode functions (IMFs) and Hilbert spectrum of the decomposed signal are obtained by applying HHT. The results of the IMFs constituent and the original signal are compared and the process of energy loss is discussed. Finally, the differences between Wavelet Transform (WT) and HHT in analyzing the signal are compared. The simulated results reveal the analysis process based on HHT is advantageous for the enhancement of energy completeness.

Keywords: Hilbert-Huang transform, Hilbert spectrum, Wavelettransform, Wavelet spectrum, DC Motor.

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992 Adaptive Multiple Transforms Hardware Architecture for Versatile Video Coding

Authors: T. Damak, S. Houidi, M. A. Ben Ayed, N. Masmoudi

Abstract:

The Versatile Video Coding standard (VVC) is actually under development by the Joint Video Exploration Team (or JVET). An Adaptive Multiple Transforms (AMT) approach was announced. It is based on different transform modules that provided an efficient coding. However, the AMT solution raises several issues especially regarding the complexity of the selected set of transforms. This can be an important issue, particularly for a future industrial adoption. This paper proposed an efficient hardware implementation of the most used transform in AMT approach: the DCT II. The developed circuit is adapted to different block sizes and can reach a minimum frequency of 192 MHz allowing an optimized execution time.

Keywords: AMT, DCT II, hardware, transform, VVC.

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991 Using Discrete Event Simulation Approach to Reduce Waiting Times in Computed Tomography Radiology Department

Authors: Mwafak Shakoor

Abstract:

The purpose of this study was to reduce patient waiting times, improve system throughput and improve resources utilization in radiology department. A discrete event simulation model was developed using Arena simulation software to investigate different alternatives to improve the overall system delivery based on adding resource scenarios due to the linkage between patient waiting times and resource availability. The study revealed that there is no addition investment need to procure additional scanner but hospital management deploy managerial tactics to enhance machine utilization and reduce the long waiting time in the department.

Keywords: Arena, Computed Tomography (CT), Discrete event simulation, Healthcare modeling, Radiology department, Waiting time.

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990 Conventional and PSO Based Approaches for Model Reduction of SISO Discrete Systems

Authors: S. K. Tomar, R. Prasad, S. Panda, C. Ardil

Abstract:

Reduction of Single Input Single Output (SISO) discrete systems into lower order model, using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Modified Cauer Form (MCF) and differentiation are used. In this method the original discrete system is, first, converted into equivalent continuous system by applying bilinear transformation. The denominator of the equivalent continuous system and its reciprocal are differentiated successively, the reduced denominator of the desired order is obtained by combining the differentiated polynomials. The numerator is obtained by matching the quotients of MCF. The reduced continuous system is converted back into discrete system using inverse bilinear transformation. In the evolutionary technique method, Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.

Keywords: Discrete System, Single Input Single Output (SISO), Bilinear Transformation, Reduced Order Model, Modified CauerForm, Polynomial Differentiation, Particle Swarm Optimization, Integral Squared Error.

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989 An Automatic Sleep Spindle Detector based on WT, STFT and WMSD

Authors: J. Costa, M. Ortigueira, A. Batista, T. Paiva

Abstract:

Sleep spindles are the most interesting hallmark of stage 2 sleep EEG. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Sleep Spindles are also promising objective indicators for neurodegenerative disorders. Visual spindle scoring however is a tedious workload. In this paper three different approaches are used for the automatic detection of sleep spindles: Short Time Fourier Transform, Wavelet Transform and Wave Morphology for Spindle Detection. In order to improve the results, a combination of the three detectors is presented and comparison with human expert scorers is performed. The best performance is obtained with a combination of the three algorithms which resulted in a sensitivity and specificity of 94% when compared to human expert scorers.

Keywords: EEG, Short Time Fourier Transform, Sleep Spindles, Wave Morphology for Spindle Detection, Wavelet Transform.

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988 Computational Simulations on Stability of Model Predictive Control for Linear Discrete-time Stochastic Systems

Authors: Tomoaki Hashimoto

Abstract:

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.

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987 Electrocardiogram Signal Denoising Using a Hybrid Technique

Authors: R. Latif, W. Jenkal, A. Toumanari, A. Hatim

Abstract:

This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.

Keywords: Hybrid technique, ADTF, DWT, tresholding, ECG signal.

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986 Discrete Breeding Swarm for Cost Minimization of Parallel Job Shop Scheduling Problem

Authors: Tarek Aboueldah, Hanan Farag

Abstract:

Parallel Job Shop Scheduling Problem (JSSP) is a multi-objective and multi constrains NP-optimization problem. Traditional Artificial Intelligence techniques have been widely used; however, they could be trapped into the local minimum without reaching the optimum solution. Thus, we propose a hybrid Artificial Intelligence (AI) model with Discrete Breeding Swarm (DBS) added to traditional AI to avoid this trapping. This model is applied in the cost minimization of the Car Sequencing and Operator Allocation (CSOA) problem. The practical experiment shows that our model outperforms other techniques in cost minimization.

Keywords: Parallel Job Shop Scheduling Problem, Artificial Intelligence, Discrete Breeding Swarm, Car Sequencing and Operator Allocation, cost minimization.

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985 Modeling and Visualizing Seismic Wave Propagation in Elastic Medium Using Multi-Dimension Wave Digital Filtering Approach

Authors: Jason Chien-Hsun Tseng, Nguyen Dong-Thai Dao, Chong-Ching Chang

Abstract:

A novel PDE solver using the multidimensional wave digital filtering (MDWDF) technique to achieve the solution of a 2D seismic wave system is presented. In essence, the continuous physical system served by a linear Kirchhoff circuit is transformed to an equivalent discrete dynamic system implemented by a MD wave digital filtering (MDWDF) circuit. This amounts to numerically approximating the differential equations used to describe elements of a MD passive electronic circuit by a grid-based difference equations implemented by the so-called state quantities within the passive MDWDF circuit. So the digital model can track the wave field on a dense 3D grid of points. Details about how to transform the continuous system into a desired discrete passive system are addressed. In addition, initial and boundary conditions are properly embedded into the MDWDF circuit in terms of state quantities. Graphic results have clearly demonstrated some physical effects of seismic wave (P-wave and S–wave) propagation including radiation, reflection, and refraction from and across the hard boundaries. Comparison between the MDWDF technique and the finite difference time domain (FDTD) approach is also made in terms of the computational efficiency.

Keywords: Seismic Wave Propagation, Multi-dimension WaveDigital Filters, Partial Differential Equations.

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984 Exponential State Estimation for Neural Networks with Leakage, Discrete and Distributed Delays

Authors: Liyuan Wang, Shouming Zhong

Abstract:

In this paper, the design problem of state estimator for neural networks with the mixed time-varying delays are investigated by constructing appropriate Lyapunov-Krasovskii functionals and using some effective mathematical techniques. In order to derive several conditions to guarantee the estimation error systems to be globally exponential stable, we transform the considered systems into the neural-type time-delay systems. Then with a set of linear inequalities(LMIs), we can obtain the stable criteria. Finally, three numerical examples are given to show the effectiveness and less conservatism of the proposed criterion.

Keywords: State estimator, Neural networks, Globally exponential stability.

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983 Fuzzy Rules Emulated Network Adaptive Controller with Unfixed Learning Rate for a Class of Unknown Discrete-time Nonlinear Systems

Authors: Chidentree Treesatayapun

Abstract:

A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.

Keywords: Neuro-Fuzzy, learning algorithm, nonlinear discrete time.

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982 Image Dehazing Using Dark Channel Prior and Fast Guided Filter in Daubechies Lifting Wavelet Transform Domain

Authors: Harpreet Kaur, Sudipta Majumdar

Abstract:

In this paper a method for image dehazing is proposed in lifting wavelet transform domain. Lifting Daubechies (D4) wavelet has been used to obtain the approximate image and detail images.  As the haze is contained in low frequency part, only the approximate image is used for further processing. This region is processed by dehazing algorithm based on dark channel prior (DCP). The dehazed approximate image is then recombined with the detail images using inverse lifting wavelet transform. Implementation of lifting wavelet transform has the advantage of auxiliary memory saving, fast implementation and simplicity. Also, the proposed method deals with near white scene problem, blue horizon issue and localized light sources in a way to enhance image quality and makes the algorithm robust. Simulation results present improvement in terms of visual quality, parameters such as root mean square (RMS) contrast, structural similarity index (SSIM), entropy and execution time.

Keywords: Dark channel prior, image dehazing, lifting wavelet transform.

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981 Analytical Solution for the Zakharov-Kuznetsov Equations by Differential Transform Method

Authors: Saeideh Hesam, Alireza Nazemi, Ahmad Haghbin

Abstract:

This paper presents the approximate analytical solution of a Zakharov-Kuznetsov ZK(m, n, k) equation with the help of the differential transform method (DTM). The DTM method is a powerful and efficient technique for finding solutions of nonlinear equations without the need of a linearization process. In this approach the solution is found in the form of a rapidly convergent series with easily computed components. The two special cases, ZK(2,2,2) and ZK(3,3,3), are chosen to illustrate the concrete scheme of the DTM method in ZK(m, n, k) equations. The results demonstrate reliability and efficiency of the proposed method.

Keywords: Zakharov-Kuznetsov equation, differential transform method, closed form solution.

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980 A Discrete-Event-Simulation Approach for Logistic Systems with Real Time Resource Routing and VR Integration

Authors: Gerrit Alves, Jürgen Roßmann, Roland Wischnewski

Abstract:

Today, transport and logistic systems are often tightly integrated in the production. Lean production and just-in-time delivering create multiple constraints that have to be fulfilled. As transport networks often have evolved over time they are very expensive to change. This paper describes a discrete-event-simulation system which simulates transportation models using real time resource routing and collision avoidance. It allows for the specification of own control algorithms and validation of new strategies. The simulation is integrated into a virtual reality (VR) environment and can be displayed in 3-D to show the progress. Simulation elements can be selected through VR metaphors. All data gathered during the simulation can be presented as a detailed summary afterwards. The included cost-benefit calculation can help to optimize the financial outcome. The operation of this approach is shown by the example of a timber harvest simulation.

Keywords: Discrete-Event-Simulation, Logistic, Simulation, Virtual Reality.

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979 Comparative Study of QRS Complex Detection in ECG

Authors: Ibtihel Nouira, Asma Ben Abdallah, Ibtissem Kouaja, Mohamed Hèdi Bedoui

Abstract:

The processing of the electrocardiogram (ECG) signal consists essentially in the detection of the characteristic points of signal which are an important tool in the diagnosis of heart diseases. The most suitable are the detection of R waves. In this paper, we present various mathematical tools used for filtering ECG using digital filtering and Discreet Wavelet Transform (DWT) filtering. In addition, this paper will include two main R peak detection methods by applying a windowing process: The first method is based on calculations derived, the second is a time-frequency method based on Dyadic Wavelet Transform DyWT.

Keywords: Derived calculation methods, Electrocardiogram, R peaks, Wavelet Transform.

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