Search results for: LFM Signal: Linear FM Signal
2161 An Optimized Method for Calculating the Linear and Nonlinear Response of SDOF System Subjected to an Arbitrary Base Excitation
Authors: Hossein Kabir, Mojtaba Sadeghi
Abstract:
Finding the linear and nonlinear responses of a typical single-degree-of-freedom system (SDOF) is always being regarded as a time-consuming process. This study attempts to provide modifications in the renowned Newmark method in order to make it more time efficient than it used to be and make it more accurate by modifying the system in its own non-linear state. The efficacy of the presented method is demonstrated by assigning three base excitations such as Tabas 1978, El Centro 1940, and MEXICO CITY/SCT 1985 earthquakes to a SDOF system, that is, SDOF, to compute the strength reduction factor, yield pseudo acceleration, and ductility factor.
Keywords: Single-degree-of-freedom system, linear acceleration method, nonlinear excited system, equivalent displacement method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11112160 Signal Reconstruction Using Cepstrum of Higher Order Statistics
Authors: Adnan Al-Smadi, Mahmoud Smadi
Abstract:
This paper presents an algorithm for reconstructing phase and magnitude responses of the impulse response when only the output data are available. The system is driven by a zero-mean independent identically distributed (i.i.d) non-Gaussian sequence that is not observed. The additive noise is assumed to be Gaussian. This is an important and essential problem in many practical applications of various science and engineering areas such as biomedical, seismic, and speech processing signals. The method is based on evaluating the bicepstrum of the third-order statistics of the observed output data. Simulations results are presented that demonstrate the performance of this method.
Keywords: Cepstrum, bicepstrum, third order statistics
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20392159 Preconditioned Jacobi Method for Fuzzy Linear Systems
Authors: Lina Yan, Shiheng Wang, Ke Wang
Abstract:
A preconditioned Jacobi (PJ) method is provided for solving fuzzy linear systems whose coefficient matrices are crisp Mmatrices and the right-hand side columns are arbitrary fuzzy number vectors. The iterative algorithm is given for the preconditioned Jacobi method. The convergence is analyzed with convergence theorems. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of the method.
Keywords: preconditioning, M-matrix, Jacobi method, fuzzy linear system (FLS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19072158 Research on the Problems of Housing Prices in Qingdao from a Macro Perspective
Authors: Liu Zhiyuan, Sun Zongdi, Liu Zhiyuan, Sun Zongdi
Abstract:
Qingdao is a seaside city. Taking into account the characteristics of Qingdao, this article established a multiple linear regression model to analyze the impact of macroeconomic factors on housing prices. We used stepwise regression method to make multiple linear regression analysis, and made statistical analysis of F test values and T test values. According to the analysis results, the model is continuously optimized. Finally, this article obtained the multiple linear regression equation and the influencing factors, and the reliability of the model was verified by F test and T test.
Keywords: Housing prices, multiple linear regression model, macroeconomic factors, Qingdao City.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11842157 Discrete Wavelet Transform Decomposition Level Determination Exploiting Sparseness Measurement
Authors: Lei Lei, Chao Wang, Xin Liu
Abstract:
Discrete wavelet transform (DWT) has been widely adopted in biomedical signal processing for denoising, compression and so on. Choosing a suitable decomposition level (DL) in DWT is of paramount importance to its performance. In this paper, we propose to exploit sparseness of the transformed signals to determine the appropriate DL. Simulation results have shown that the sparseness of transformed signals after DWT increases with the increasing DLs. Additional Monte-Carlo simulation results have verified the effectiveness of sparseness measure in determining the DL.
Keywords: Sparseness, DWT, decomposition level, ECG.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 58772156 Receive and Transmit Array Antenna Spacingand Their Effect on the Performance of SIMO and MIMO Systems by using an RCS Channel Model
Authors: N. Ebrahimi-Tofighi, M. ArdebiliPour, M. Shahabadi
Abstract:
In this paper, the effect of receive and/or transmit antenna spacing on the performance (BER vs. SNR) of multipleantenna systems is determined by using an RCS (Radar Cross Section) channel model. In this physical model, the scatterers existing in the propagation environment are modeled by their RCS so that the correlation of the receive signal complex amplitudes, i.e., both magnitude and phase, can be estimated. The proposed RCS channel model is then compared with classical models.Keywords: MIMO system, Performance of system, Signalcorrelation, SIMO system, Wireless channel model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19392155 Hardware Centric Machine Vision for High Precision Center of Gravity Calculation
Authors: Xin Cheng, Benny Thörnberg, Abdul Waheed Malik, Najeem Lawal
Abstract:
We present a hardware oriented method for real-time measurements of object-s position in video. The targeted application area is light spots used as references for robotic navigation. Different algorithms for dynamic thresholding are explored in combination with component labeling and Center Of Gravity (COG) for highest possible precision versus Signal-to-Noise Ratio (SNR). This method was developed with a low hardware cost in focus having only one convolution operation required for preprocessing of data.Keywords: Dynamic thresholding, segmentation, position measurement, sub-pixel precision, center of gravity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23572154 A Contractor for the Symmetric Solution Set
Authors: Milan Hladik
Abstract:
The symmetric solution set Σ sym is the set of all solutions to the linear systems Ax = b, where A is symmetric and lies between some given bounds A and A, and b lies between b and b. We present a contractor for Σ sym, which is an iterative method that starts with some initial enclosure of Σ sym (by means of a cartesian product of intervals) and sequentially makes the enclosure tighter. Our contractor is based on polyhedral approximation and solving a series of linear programs. Even though it does not converge to the optimal bounds in general, it may significantly reduce the overestimation. The efficiency is discussed by a number of numerical experiments.
Keywords: Linear interval systems, solution set, interval matrix, symmetric matrix.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12922153 Speaker Identification by Atomic Decomposition of Learned Features Using Computational Auditory Scene Analysis Principals in Noisy Environments
Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic
Abstract:
Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.
Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15732152 Pattern Recognition of Biological Signals
Authors: Paulo S. Caparelli, Eduardo Costa, Alexsandro S. Soares, Hipolito Barbosa
Abstract:
This paper presents an evolutionary method for designing electronic circuits and numerical methods associated with monitoring systems. The instruments described here have been used in studies of weather and climate changes due to global warming, and also in medical patient supervision. Genetic Programming systems have been used both for designing circuits and sensors, and also for determining sensor parameters. The authors advance the thesis that the software side of such a system should be written in computer languages with a strong mathematical and logic background in order to prevent software obsolescence, and achieve program correctness.Keywords: Pattern recognition, evolutionary computation, biological signal, functional programming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17502151 TS Fuzzy Controller to Stochastic Systems
Authors: Joabe Silva, Ginalber Serra
Abstract:
This paper proposes the analysis and design of robust fuzzy control to Stochastic Parametrics Uncertaint Linear systems. This system type to be controlled is partitioned into several linear sub-models, in terms of transfer function, forming a convex polytope, similar to LPV (Linear Parameters Varying) system. Once defined the linear sub-models of the plant, these are organized into fuzzy Takagi- Sugeno (TS) structure. From the Parallel Distributed Compensation (PDC) strategy, a mathematical formulation is defined in the frequency domain, based on the gain and phase margins specifications, to obtain robust PI sub-controllers in accordance to the Takagi- Sugeno fuzzy model of the plant. The main results of the paper are based on the robust stability conditions with the proposal of one Axiom and two Theorems.Keywords: Fuzzy Systems; Robust Stability, Stochastic Control, Stochastic Process
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17052150 Wavelet Based Identification of Second Order Linear System
Authors: Sudipta Majumdar, Harish Parthasarathy
Abstract:
In this paper, a wavelet based method is proposed to identify the constant coefficients of a second order linear system and is compared with the least squares method. The proposed method shows improved accuracy of parameter estimation as compared to the least squares method. Additionally, it has the advantage of smaller data requirement and storage requirement as compared to the least squares method.Keywords: Least squares method, linear system, system identification, wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15822149 Sensitivity of Input Blocking Capacitor on Output Voltage and Current of a PV Inverter Employing IGBTs
Authors: Z.A. Jaffery, Vinay Kumar Chandna, Sunil Kumar Chaudhary
Abstract:
This paper present a MATLAB-SIMULINK model of a single phase 2.5 KVA, 240V RMS controlled PV VSI (Photovoltaic Voltage Source Inverter) inverter using IGBTs (Insulated Gate Bipolar Transistor). The behavior of output voltage, output current, and the total harmonic distortion (THD), with the variation in input dc blocking capacitor (Cdc), for linear and non-linear load has been analyzed. The values of Cdc as suggested by the other authors in their papers are not clearly defined and it poses difficulty in selecting the proper value. As the dc power stored in Cdc, (generally placed parallel with battery) is used as input to the VSI inverter. The simulation results shows the variation in the output voltage and current with different values of Cdc for linear and non-linear load connected at the output side of PV VSI inverter and suggest the selection of suitable value of Cdc.
Keywords: DC Blocking capacitor, IGBTs, PV VSI, THD.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21362148 Study of Adaptive Filtering Algorithms and the Equalization of Radio Mobile Channel
Authors: Said Elkassimi, Said Safi, B. Manaut
Abstract:
This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm.
Keywords: Adaptive filtering second equalizer, LMS, RLS Bran A, Proakis (B) MMSE, ZF.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21272147 A PSO-Based Optimum Design of PID Controller for a Linear Brushless DC Motor
Authors: Mehdi Nasri, Hossein Nezamabadi-pour, Malihe Maghfoori
Abstract:
This Paper presents a particle swarm optimization (PSO) method for determining the optimal proportional-integral-derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modelled in Simulink and the PSO algorithm is implemented in MATLAB. Comparing with Genetic Algorithm (GA) and Linear quadratic regulator (LQR) method, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of a linear brushless DC motor.
Keywords: Brushless DC motor, Particle swarm optimization, PID Controller, Optimal control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 49702146 Performance Evaluation of Music and Minimum Norm Eigenvector Algorithms in Resolving Noisy Multiexponential Signals
Authors: Abdussamad U. Jibia, Momoh-Jimoh E. Salami
Abstract:
Eigenvector methods are gaining increasing acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals with real decay constants buried in noise. In particular, MUSIC (Multiple Signal Classification) and minimum-norm techniques are examined. It is shown that these methods perform almost equally well on multiexponential signals with MUSIC displaying better defined peaks.
Keywords: Eigenvector, minimum norm, multiexponential, subspace.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17422145 New Method for Determining the Distribution of Birefringence and Linear Dichroism in Polymer Materials Based On Polarization-Holographic Grating
Authors: Barbara Kilosanidze, George Kakauridze, Levan Nadareishvili, Yuri Mshvenieradze
Abstract:
A new method for determining the distribution of birefringence and linear dichroism in optical polymer materials is presented. The method is based on the use of polarizationholographic diffraction grating that forms an orthogonal circular basis in the process of diffraction of probing laser beam on the grating. The intensities ratio of the orders of diffraction on this grating enables the value of birefringence and linear dichroism in the sample to be determined. The distribution of birefringence in the sample is determined by scanning with a circularly polarized beam with a wavelength far from the absorption band of the material. If the scanning is carried out by probing beam with the wavelength near to a maximum of the absorption band of the chromophore then the distribution of linear dichroism can be determined. An appropriate theoretical model of this method is presented. A laboratory setup was created for the proposed method. An optical scheme of the laboratory setup is presented. The results of measurement in polymer films with two-dimensional gradient distribution of birefringence and linear dichroism are discussed.
Keywords: Birefringence, graded oriented polymers, linear dichroism, optical polymers, optical anisotropy, polarization-holographic grating,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15132144 Development of a Feedback Control System for a Lab-Scale Biomass Combustion System Using Programmable Logic Controller
Authors: Samuel O. Alamu, Seong W. Lee, Blaise Kalmia, Marc J. Louise Caballes, Xuejun Qian
Abstract:
The application of combustion technologies for thermal conversion of biomass and solid wastes to energy has been a major solution to the effective handling of wastes over a long period of time. Lab-scale biomass combustion systems have been observed to be economically viable and socially acceptable, but major concerns are the environmental impacts of the process and deviation of temperature distribution within the combustion chamber. Both high and low combustion chamber temperature may affect the overall combustion efficiency and gaseous emissions. Therefore, there is an urgent need to develop a control system which measures the deviations of chamber temperature from set target values, sends these deviations (which generates disturbances in the system) in the form of feedback signal (as input), and control operating conditions for correcting the errors. In this research study, major components of the feedback control system were determined, assembled, and tested. In addition, control algorithms were developed to actuate operating conditions (e.g., air velocity, fuel feeding rate) using ladder logic functions embedded in the Programmable Logic Controller (PLC). The developed control algorithm having chamber temperature as a feedback signal is integrated into the lab-scale swirling fluidized bed combustor (SFBC) to investigate the temperature distribution at different heights of the combustion chamber based on various operating conditions. The air blower rates and the fuel feeding rates obtained from automatic control operations were correlated with manual inputs. There was no observable difference in the correlated results, thus indicating that the written PLC program functions were adequate in designing the experimental study of the lab-scale SFBC. The experimental results were analyzed to study the effect of air velocity operating at 222-273 ft/min and fuel feeding rate of 60-90 rpm on the chamber temperature. The developed temperature-based feedback control system was shown to be adequate in controlling the airflow and the fuel feeding rate for the overall biomass combustion process as it helps to minimize the steady-state error.
Keywords: Air flow, biomass combustion, feedback control system, fuel feeding, ladder logic, programmable logic controller, temperature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5952143 Development of a Multi-Factorial Instrument for Accident Analysis Based on Systemic Methods
Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu
Abstract:
The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.
Keywords: Accident analysis, multi-factorial error modeling, risk, systemic methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10452142 Epileptic Seizure Prediction by Exploiting Signal Transitions Phenomena
Authors: Mohammad Zavid Parvez, Manoranjan Paul
Abstract:
A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/ deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.Keywords: Epilepsy, Seizure, Phase Correlation, Fluctuation, Deviation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24732141 A Virtual Simulation Environment for a Design and Verification of a GPGPU
Authors: Kwang Y. Lee, Tae R. Park, Jae C. Kwak, Yong S. Koo
Abstract:
When a small H/W IP is designed, we can develop an appropriate verification environment by observing the simulated signal waves, or using the serial test vectors for the fixed output. In the case of design and verification of a massive parallel processor with multiple IPs, it-s difficult to make a verification system with existing common verification environment, and to verify each partial IP. A TestDrive verification environment can build easy and reliable verification system that can produce highly intuitive results by applying Modelsim and SystemVerilog-s DPI. It shows many advantages, for example a high-level design of a GPGPU processor design can be migrate to FPGA board immediately.Keywords: Virtual Simulation, Verification, IP Design, GPGPU
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16642140 A Family of Zero Stable Block Integrator for the Solutions of Ordinary Differential Equations
Authors: A. M. Sagir
Abstract:
In this paper, linear multistep technique using power series as the basis function is used to develop the block methods which are suitable for generating direct solution of the special second order ordinary differential equations with associated initial or boundary conditions. The continuous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain two different four discrete schemes, each of order (5,5,5,5)T, which were used in block form for parallel or sequential solutions of the problems. The computational burden and computer time wastage involved in the usual reduction of second order problem into system of first order equations are avoided by this approach. Furthermore, a stability analysis and efficiency of the block methods are tested on linear and non-linear ordinary differential equations and the results obtained compared favorably with the exact solution.Keywords: Block Method, Hybrid, Linear Multistep Method, Self – starting, Special Second Order.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14862139 Applications of Stable Distributions in Time Series Analysis, Computer Sciences and Financial Markets
Authors: Mohammad Ali Baradaran Ghahfarokhi, Parvin Baradaran Ghahfarokhi
Abstract:
In this paper, first we introduce the stable distribution, stable process and theirs characteristics. The a -stable distribution family has received great interest in the last decade due to its success in modeling data, which are too impulsive to be accommodated by the Gaussian distribution. In the second part, we propose major applications of alpha stable distribution in telecommunication, computer science such as network delays and signal processing and financial markets. At the end, we focus on using stable distribution to estimate measure of risk in stock markets and show simulated data with statistical softwares.
Keywords: stable distribution, SaS, infinite variance, heavy tail networks, VaR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20702138 Optimum Cascaded Design for Speech Enhancement Using Kalman Filter
Authors: T. Kishore Kumar
Abstract:
Speech enhancement is the process of eliminating noise and increasing the quality of a speech signal, which is contaminated with other kinds of distortions. This paper is on developing an optimum cascaded system for speech enhancement. This aim is attained without diminishing any relevant speech information and without much computational and time complexity. LMS algorithm, Spectral Subtraction and Kalman filter have been deployed as the main de-noising algorithms in this work. Since these algorithms suffer from respective shortcomings, this work has been undertaken to design cascaded systems in different combinations and the evaluation of such cascades by qualitative (listening) and quantitative (SNR) tests.Keywords: LMS, Kalman filter, Speech Enhancement and Spectral Subtraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17382137 Comparison of Frequency Estimation Methods for Reflected Signals in Mobile Platforms
Authors: Kathrin Reinhold
Abstract:
Precise frequency estimation methods for pulseshaped echoes are a prerequisite to determine the relative velocity between sensor and reflector. Signal frequencies are analysed using three different methods: Fourier Transform, Chirp ZTransform and the MUSIC algorithm. Simulations of echoes are performed varying both the noise level and the number of reflecting points. The superposition of echoes with a random initial phase is found to influence the precision of frequency estimation severely for FFT and MUSIC. The standard deviation of the frequency using FFT is larger than for MUSIC. However, MUSIC is more noise-sensitive. The distorting effect of superpositions is less pronounced in experimental data.
Keywords: Frequency estimation, pulse-echo-method, superposition, echoes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11752136 The Effect of Chemical Treatment on TL Glow Curves of CdS/ZnS Thin Films Deposited by Vacuum Deposition Method
Authors: N. Dahbi, D-E. Arafah
Abstract:
The effect of chemical treatment in CdCl2 and thermal annealing in 400°C, on the defect structures of potentially useful ZnS\CdS solar cell thin films deposited onto quartz substrate and prepared by vacuum deposition method was studied using the Thermoluminesence (TL) techniques. A series of electron and hole traps are found in the various deposited samples studied. After annealing, however, it was observed that the intensity and activation energy of TL signal increases with loss of the low temperature electron traps.Keywords: CdS, chemical treatment, heat treatment, Thermoluminescence, trapping parameters, thin film, vacuumdeposition, ZnS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15272135 ICAM-2, A Protein of Antitumor Immune Response in Mekong Giant Catfish (Pangasianodon gigas)
Authors: Jiraporn Rojtinnakorn
Abstract:
ICAM-2 (intercellular adhesion molecule 2) or CD102 (Cluster of Differentiation 102) is type I transmembrane glycoproteins, composing 2-9 immunoglobulin-like C2-type domains. ICAM-2 plays the particular role in immune response and cell surveillance. It is concerned in innate and specific immunity, cell survival signal, apoptosis, and anticancer. EST clone of ICAM-2, from P. gigas blood cell EST libraries, showed high identity to human ICAM-2 (92%) with conserve region of ICAM N-terminal domain and part of Ig superfamily. Gene and protein of ICAM-2 has been founded in mammals. This is the first report of ICAM-2 in fish
Keywords: ICAM-2, CD102, Pangasianodon gigas, antitumor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18752134 MRI Reconstruction Using Discrete Fourier Transform: A tutorial
Authors: Abiodun M. Aibinu, Momoh J. E. Salami, Amir A. Shafie, Athaur Rahman Najeeb
Abstract:
The use of Inverse Discrete Fourier Transform (IDFT) implemented in the form of Inverse Fourier Transform (IFFT) is one of the standard method of reconstructing Magnetic Resonance Imaging (MRI) from uniformly sampled K-space data. In this tutorial, three of the major problems associated with the use of IFFT in MRI reconstruction are highlighted. The tutorial also gives brief introduction to MRI physics; MRI system from instrumentation point of view; K-space signal and the process of IDFT and IFFT for One and two dimensional (1D and 2D) data.
Keywords: Discrete Fourier Transform (DFT), K-space Data, Magnetic Resonance (MR), Spin, Windows.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 51172133 Trispectral Analysis of Voiced Sounds Defective Audition and Tracheotomisian Cases
Abstract:
This paper presents the cepstral and trispectral analysis of a speech signal produced by normal men, men with defective audition (deaf, deep deaf) and others affected by tracheotomy, the trispectral analysis based on parametric methods (Autoregressive AR) using the fourth order cumulant. These analyses are used to detect and compare the pitches and the formants of corresponding voiced sounds (vowel \a\, \i\ and \u\). The first results appear promising, since- it seems after several experimentsthere is no deformation of the spectrum as one could have supposed it at the beginning, however these pathologies influenced the two characteristics: The defective audition influences to the formants contrary to the tracheotomy, which influences the fundamental frequency (pitch).Keywords: Cepstrum, cumulant, defective audition, tracheotomisy, trispectrum.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14122132 Formulation, Analysis and Validation of Takagi-Sugeno Fuzzy Modeling For Robotic Monipulators
Authors: Rafael Jorge Menezes Santos, Ginalber Luiz de Oliveira Serra, Carlos César Teixeira Ferreira
Abstract:
This paper proposes a methodology for analysis of the dynamic behavior of a robotic manipulator in continuous time. Initially this system (nonlinear system) will be decomposed into linear submodels and analyzed in the context of the Linear and Parameter Varying (LPV) Systems. The obtained linear submodels, which represent the local dynamic behavior of the robotic manipulator in some operating points were grouped in a Takagi-Sugeno fuzzy structure. The obtained fuzzy model was analyzed and validated through analog simulation, as universal approximator of the robotic manipulator.Keywords: modeling of nonlinear dynamic systems, Takagi- Sugeno fuzzy model, Linear and Parameter Varying (LPV) System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2615