Search results for: primary synchronization signal (PSS)

Authors: Labiba Gilani, Asifullah Khan, Anwar M. Mirza

Abstract:

This paper introduces a technique of distortion estimation in image watermarking using Genetic Programming (GP). The distortion is estimated by considering the problem of obtaining a distorted watermarked signal from the original watermarked signal as a function regression problem. This function regression problem is solved using GP, where the original watermarked signal is considered as an independent variable. GP-based distortion estimation scheme is checked for Gaussian attack and Jpeg compression attack. We have used Gaussian attacks of different strengths by changing the standard deviation. JPEG compression attack is also varied by adding various distortions. Experimental results demonstrate that the proposed technique is able to detect the watermark even in the case of strong distortions and is more robust against attacks.

Keywords: Blind Watermarking, Genetic Programming (GP), Fitness Function, Discrete Cosine Transform (DCT).

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Authors: Nagulapati Kiran, V. Rangavalli, B. Vanajakshi

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This paper designs the four-phase Boost Converter which overcomes the problem of high input ripple current and output ripple voltage. Digital control is more convenient for such a topology on basis of synchronization, phase shift operation, etc. Simulation results are presented for open-loop and closed-loop for four phase boost converter. This control scheme is applicable for PFC rectifiers as well. Thus a comparative analysis based on the obtained results is performed.

Keywords: Boost Converter, Bode plot, PI Controller, Four phase.

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Authors: Magdalena Naplavova, Tomas Ludik, Petr Hruza, Frantisek Bozek

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The use of IT equipment has become a part of every day. However, each device that is part of cyberspace should be secured against unauthorized use. It is very important to know the basics of these security devices, but also the basics of safe conduct their owners. This information should be part of every curriculum computer science education in primary and secondary schools. Therefore, the work focuses on the education of pupils in primary and secondary schools on the Internet. Analysis of the current state describes approaches to the education of pupils in security issues on the Internet. The paper presents a questionnaire-based survey which was carried out in the Czech Republic, whose task was to ascertain the level of opinion pupils in primary and secondary schools on the issue of communication in social networks. The research showed that awareness of socio-pathological phenomena on the Internet environment is very low. Based on the results it was proposed appropriate ways of teaching to this issue and its inclusion a proposal of curriculum for primary and secondary schools.

Keywords: Cyberspace, educational system, general awareness, information security, questionnaire, socio-pathological phenomena.

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Authors: R. Fan, Q. Wan, H. Chen, Y.L. Liu, Y.P. Liu

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This paper considers a robust recovery of sparse frequencies from partial phase-only measurements. With the proposed method, sparse frequencies can be reconstructed, which makes full use of the sparse distribution in the Fourier representation of the complex-valued time signal. Simulation experiments illustrate the proposed method-s advantages over conventional methods in both noiseless and additive white Gaussian noise cases.

Keywords: Sparse signal recovery, phase-only measurements, Compressive sensing, convex relaxation.

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Authors: Maan M. Shaker

Abstract:

The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field due to its rich information about human tasks. In this work EEG waves classification is achieved using the Discrete Wavelet Transform DWT with Fast Fourier Transform (FFT) by adopting the normalized EEG data. The DWT is used as a classifier of the EEG wave's frequencies, while FFT is implemented to visualize the EEG waves in multi-resolution of DWT. Several real EEG data sets (real EEG data for both normal and abnormal persons) have been tested and the results improve the validity of the proposed technique.

Keywords: Bioinformatics, DWT, EEG waves, FFT.

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Authors: Nagesha, G. Hemantha Kumar

Abstract:

Although the level crossing concept has been the subject of intensive investigation over the last few years, certain problems of great interest remain unsolved. One of these concern is distribution of threshold levels. This paper presents a new threshold level allocation schemes for level crossing based on nonuniform sampling. Intuitively, it is more reasonable if the information rich regions of the signal are sampled finer and those with sparse information are sampled coarser. To achieve this objective, we propose non-linear quantization functions which dynamically assign the number of quantization levels depending on the importance of the given amplitude range. Two new approaches to determine the importance of the given amplitude segment are presented. The proposed methods are based on exponential and logarithmic functions. Various aspects of proposed techniques are discussed and experimentally validated. Its efficacy is investigated by comparison with uniform sampling.

Keywords: speech signals, sampling, signal reconstruction, asynchronousdelta modulation, non-linear quantization.

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Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy

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A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.

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Authors: Maha Sharkas, Dahlia ElShafie, Nadder Hamdy

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Image watermarking has become an important tool for intellectual property protection and authentication. In this paper a watermarking technique is suggested that incorporates two watermarks in a host image for improved protection and robustness. A watermark, in form of a PN sequence (will be called the secondary watermark), is embedded in the wavelet domain of a primary watermark before being embedded in the host image. The technique has been tested using Lena image as a host and the camera man as the primary watermark. The embedded PN sequence was detectable through correlation among other five sequences where a PSNR of 44.1065 dB was measured. Furthermore, to test the robustness of the technique, the watermarked image was exposed to four types of attacks, namely compression, low pass filtering, salt and pepper noise and luminance change. In all cases the secondary watermark was easy to detect even when the primary one is severely distorted.

Keywords: DWT, Image watermarking, watermarkingtechniques, wavelets.

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Authors: Beata Zima, Octavio A. Márquez Reyes, Masoud Mohammadgholiha, Jochen Moll, Luca De Marchi

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This document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled using PIC255 piezoelectric material. The special shape of the FSAT, allows for focusing wave energy in a certain direction, accordingly to the frequency components of its actuation signal, which makes a larger monitored area available. The process begins when a FSAT detects and records reflection from damage in the structure, this signal is then encoded and prepared for transmission, using a combined approach, based on Compressed Sensing Matching Pursuit and Quadrature Amplitude Modulation (QAM). After codification of the signal is in binary, the information is transmitted between the nodes in the network. The message reaches the last node, where it is finally decoded and processed, to be used for damage detection and localization purposes. The main aim of the investigation is to determine the location of detected damage using reconstructed signals. The study demonstrates that the special steerable capabilities of FSATs, not only facilitate the detection of damage but also permit transmitting the damage information to a chosen area in a specific direction of the investigated structure.

Keywords: Data compression, ultrasonic communication, guided waves, FEM analysis.

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Authors: Juan David Arango, Alejandro Restrepo-Martinez

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The Rolling Element Bearing (REB) vibration diagnosis is worth of special interest by the variety of REB and the wide necessity of those elements in industrial applications. The presence of a localized fault in a REB gives rise to a vibrational response, characterized by the modulation of a carrier signal. Frequency content of carrier signal (Spectral Frequency –f) is mainly related to resonance frequencies of the REB. This carrier signal is modulated by another signal, governed by the periodicity of the fault impact (Cyclic Frequency –α). In this sense, REB fault vibration response gives rise to a second-order cyclostationary signal. Second order cyclostationary signals could be represented in a bi-spectral map, where Spectral Coherence –SCoh are plotted against f and α. The Improved Envelope Spectrum –IES, is a useful approach to execute REB fault diagnosis. IES could be applied by the integration of SCoh over a predefined bandwidth on the f axis. Approaches to select f-bandwidth have been recently exposed by the definition of a metric which intends to evaluate the magnitude of the IES at the fault characteristics frequencies. This metric is represented in a 1/3-binary tree as a function of the frequency bandwidth and centre. Based on this binary tree the optimal frequency band is selected. However, some advantages have been seen if the metric is changed, which in fact tends to dictate different optimal f-bandwidth and so improve the IES representation. This paper evaluates the behaviour of the IES from a different metric optimization. This metric is based on the sample correlation coefficient, detecting high peaks in the selected frequencies while penalizing high peaks in the neighbours of the selected frequencies. Prior results indicate an improvement on the signal-noise ratio (SNR) on around 86% of samples analysed, which belong to IMS database.

Keywords: Sample Correlation IESFOgram, cyclostationary analysis, improved envelope spectrum, IES, rolling element bearing diagnosis, spectral coherence.

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Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, adaptive antenna array, Deep Neural Network, LS-SVM optimization model, radial basis function, MSE.

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Authors: Danilo López, Johana Hernández, Edwin Rivas

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The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: Cognitive radio, neural network, prediction, primary user.

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Authors: Dipali Bansal, Rashima Mahajan, Shweta Singh, Dheeraj Rathee, Sujit Roy

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Non-invasive Brain Computer Interface like Electroencephalography (EEG) which directly taps neurological signals, is being widely explored these days to connect paralytic patients/elderly with the external environment. However, in India the research is confined to laboratory settings and is not reaching the mass for rehabilitation purposes. An attempt has been made in this paper to analyze real time acquired EEG signal using cost effective and portable headset unit EMOTIV. Signal processing of real time acquired EEG is done using EEGLAB in MATLAB and EDF Browser application software platforms. Independent Component Analysis algorithm of EEGLAB is explored to identify deliberate eye blink in the attained neural signal. Time Frequency transforms and Data statistics obtained using EEGLAB along with component activation results of EDF browser clearly indicate voluntary eye blink in AF3 channel. The spectral analysis indicates dominant frequency component at 1.536000Hz representing the delta wave component of EEG during voluntary eye blink action. An algorithm is further designed to generate an active high signal based on thoughtful eye blink that can be used for plethora of control applications for rehabilitation.

Keywords: Brain Computer Interface, EDF Browser, EEG, EEGLab, EMOTIV, Real time Acquisition

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Authors: Nil Duban

Abstract:

The curriculum of the primary school science course was redesigned on the basis of constructivism in 2005-2006 academic years, in Turkey. In this context, the name of this course has been changed as “Science and Technology"; and both content and course books, students workbooks for this course have been redesigned in light of constructivism. The aim of this study is to determine whether the Science and Technology course books and student work books for primary school 5th grade are appropriate for the constructivism by evaluating them in terms of the fundamental principles of constructivism. In this study, out of qualitative research methods, documentation technique (i.e. document analysis) is applied; while selecting samples, criterion-sampling is used out of purposeful sampling techniques. When the Science and Technology course book and workbook for the 5th grade in primary education are examined, it is seen that both books complete each other in certain areas. Consequently, it can be claimed that in spite of some inadequate and missing points in the course book and workbook of the primary school Science and Technology course for the 5th grade students, these books are attempted to be designed in terms of the principles of constructivism. To overcome the inadequacies in the books, it can be suggested to redesign them. In addition to them, not to ignore the technology dimension of the course, the activities that encourage the students to prepare projects using technology cycle should be included.

Keywords: Constructivism, coursebooks, science and technology education.

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Authors: G. Stillo, L. Bonzano, M. Chiappalone, A. Vato, F. Davide, S. Martinoia

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Electrophysiological signals were recorded from primary cultures of dissociated rat cortical neurons coupled to Micro-Electrode Arrays (MEAs). The neuronal discharge patterns may change under varying physiological and pathological conditions. For this reason, we developed a new burst detection method able to identify bursts with peculiar features in different experimental conditions (i.e. spontaneous activity and under the effect of specific drugs). The main feature of our algorithm (i.e. Burst On Hurst), based on the auto-similarity or fractal property of the recorded signal, is the independence from the chosen spike detection method since it works directly on the raw data.

Keywords: Burst detection, cortical neuronal networks, Micro-Electrode Array (MEA), wavelets.

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Authors: Linjun Wu, Shihua Zhu, Xingle Feng

Abstract:

In an Orthogonal Frequency Division Multiplexing (OFDM) systems, the Peak to Average power Ratio (PAR) is high. The clipping signal scheme is a useful and simple method to reduce the PAR. However, it introduces additional noise that degrades the systems performance. We propose an oversampling scheme to deal with the received signal in order to reduce the clipping noise by using Finite Impulse Response (FIR) filter. Coefficients of filter are obtained by correlation function of the received signal and the oversampling information at receiver. The performance of the proposed technique is evaluated for frequency selective channel. Results show that the proposed scheme can mitigate the clipping noise significantly for OFDM systems and in order to maintain the system's capacity, the clipping ratio should be larger than 2.5.

Keywords: Orthogonal frequency division multiplexing, peak-to-average power ratio, oversampling.

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Authors: Robert Krause

Abstract:

Primary progressive aphasia (PPA) is a neurodegenerative disease similar to frontotemporal and semantic dementia, while having a different clinical image and anatomic pathology topography. Nonetheless, they are often included under an umbrella term: frontotemporal lobar degeneration (FTLD). In the study, examples of diagnosing PPA are presented through the multidisciplinary lens of specialists from different fields (neurologists, psychiatrists, clinical speech therapists, clinical neuropsychologists and others) using a variety of diagnostic tools such as MR, PET/CT, genetic screening and neuropsychological and logopedic methods. Thanks to that, specialists can get a better and clearer understanding of PPA diagnosis. The study summarizes the concrete procedures and results of different specialists while diagnosing PPA in a patient of younger middle age and illustrates the importance of multidisciplinary approach to differential diagnosis of PPA.

Keywords: Primary progressive aphasia, etiology, diagnosis, younger middle age.

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Authors: Jerin John, Subanesh Shyam R., Aravind Kumar T. R., Naveen N., Vignesh R., Krishna Ganesh B, Sanal Kumar V. R.

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Numerical studies have been carried out using a validated two-dimensional RNG k-epsilon turbulence model for the design optimization of a thrust vector control system using shock induced supersonic secondary jet. Parametric analytical studies have been carried out with various secondary jets at different divergent locations, jet interaction angles, jet pressures. The results from the parametric studies of the case on hand reveal that the primary nozzle with a small divergence angle, downstream injections with a distance of 2.5 times the primary nozzle throat diameter from the primary nozzle throat location warrant higher efficiency over a certain range of jet pressures and jet angles. We observed that the supersonic secondary jet opposing the core flow with jets interaction angle of 40o to the axis far downstream of the nozzle throat facilitates better thrust vectoring than the secondary jet with same direction as that of core flow with various interaction angles. We concluded that fixing of the supersonic secondary jet nozzle pointing towards the throat direction with suitable angle at a distance 2 to 4 times of the primary nozzle throat diameter, as the case may be, from the primary nozzle throat location could facilitate better thrust vectoring for the supersonic aerospace vehicles.

Keywords: Fluidic thrust vectoring, rocket steering, supersonic secondary jet location, TVC in spacecraft.

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Authors: G. Balakayeva, A. Aktymbayeva

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In this paper, we consider components of discrete event imitating model, implementing a simulation model by using JAVA and performing an input analysis of the data and an output analysis of the simulation results. Was lead development of imitating model of mass service system with n (n≥1) devices of service. On the basis of the developed process of a multithreading simulated the distributed processes with presence of synchronization. Was developed the algorithm of event-oriented simulation, was received results of system functioning with n devices of service.

Keywords: Imitating modeling, Mass service system, Multi agentsystem.

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Authors: S. Pullteap

Abstract:

In this paper, a fiber based Fabry-Perot interferometer is proposed and demonstrated for a non-contact displacement measurement. A piece of micro-prism which attached to the mechanical vibrator is served as the target reflector. Interference signal is generated from the superposition between the sensing beam and the reference beam within the sensing arm of the fiber sensor. This signal is then converted to the displacement value by using a developed program written in visual Cµ programming with a resolution of λ/8. A classical function generator is operated for controlling the vibrator. By fixing an excitation frequency of 100 Hz and varying the excitation amplitude range of 0.1 – 3 Volts, the output displacements measured by the fiber sensor are obtained from 1.55 μm to 30.225 μm. A reference displacement sensor with a sensitivity of ~0.4 μm is also employed for comparing the displacement errors between both sensors. We found that over the entire displacement range, a maximum and average measurement error are obtained of 0.977% and 0.44% respectively.

Keywords: Non-contact displacement measurement, extrinsicfiber based Fabry-Perot interferometer, interference signal, zerocrossingfringe counting technique.

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Authors: Farzaneh Akhavan Mahdavi, Siti Anom Ahmad, Mohd Hamiruce Marhaban, Mohammad-R. Akbarzadeh-T

Abstract:

Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements.

Keywords: Electromyography signal, feature extraction, wavelettransform, means absolute value.

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Authors: Adeniran Ademuwagun, Alastair Allen

Abstract:

The relationship dependence between RSS and distance in an enclosed environment is an important consideration because it is a factor that can influence the reliability of any localization algorithm founded on RSS. Several algorithms effectively reduce the variance of RSS to improve localization or accuracy performance. Our proposed algorithm essentially avoids this pitfall and consequently, its high adaptability in the face of erratic radio signal. Using 3 anchors in close proximity of each other, we are able to establish that RSS can be used as reliable indicator for localization with an acceptable degree of accuracy. Inherent in this concept, is the ability for each prospective anchor to validate (guarantee) the position or the proximity of the other 2 anchors involved in the localization and vice versa. This procedure ensures that the uncertainties of radio signals due to multipath effects in enclosed environments are minimized. A major driver of this idea is the implicit topological relationship among sensors due to raw radio signal strength. The algorithm is an area based algorithm; however, it does not trade accuracy for precision (i.e the size of the returned area).

Keywords: Anchor nodes, centroid algorithm, communication graph, received signal strength (RSS).

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Authors: Fang Ye, Han Yu, Yibing Li

Abstract:

Radio interference is one of the major concerns in using the global positioning system (GPS) for civilian and military applications. Interference signals are produced not only through all electronic systems but also illegal jammers. Among different types of interferences, continuous wave (CW) interference has strong adverse impacts on the quality of the received signal. In this paper, we make more detailed analysis for CW interference effects on GPS signal quality. Based on the C/A code spectrum lines, the influence of CW interference on the acquisition performance of GPS receivers is further analysed. This influence is supported by simulation results using GPS software receiver. As the most important user parameter of GPS receivers, the mathematical expression of bit error probability is also derived in the presence of CW interference, and the expression is consistent with the Monte Carlo simulation results. The research on CW interference provides some theoretical gist and new thoughts on monitoring the radio noise environment and improving the anti-jamming ability of GPS receivers.

Keywords: GPS, CW interference, acquisition performance, bit error probability, Monte Carlo.

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Authors: Samba Raju, Chiluveru, Manoj Tripathy

Abstract:

Intelligibility is an essential characteristic of a speech signal, which is used to help in the understanding of information in speech signal. Background noise in the environment can deteriorate the intelligibility of a recorded speech. In this paper, we presented a simple variance subtracted - variable level discrete wavelet transform, which improve the intelligibility of speech. The proposed algorithm does not require an explicit estimation of noise, i.e., prior knowledge of the noise; hence, it is easy to implement, and it reduces the computational burden. The proposed algorithm decides a separate decomposition level for each frame based on signal dominant and dominant noise criteria. The performance of the proposed algorithm is evaluated with speech intelligibility measure (STOI), and results obtained are compared with Universal Discrete Wavelet Transform (DWT) thresholding and Minimum Mean Square Error (MMSE) methods. The experimental results revealed that the proposed scheme outperformed competing methods

Keywords: Discrete Wavelet Transform, speech intelligibility, STOI, standard deviation.

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Authors: Mohamed I. Mahmoud, Moawad I. M. Dessouky, Salah Deyab, Fatma H. Elfouly

Abstract:

Recently, the Field Programmable Gate Array (FPGA) technology offers the potential of designing high performance systems at low cost. The discrete wavelet transform has gained the reputation of being a very effective signal analysis tool for many practical applications. However, due to its computation-intensive nature, current implementation of the transform falls short of meeting real-time processing requirements of most application. The objectives of this paper are implement the Haar and Daubechies wavelets using FPGA technology. In addition, the comparison between the Haar and Daubechies wavelets is investigated. The Bit Error Rat (BER) between the input audio signal and the reconstructed output signal for each wavelet is calculated. It is seen that the BER using Daubechies wavelet techniques is less than Haar wavelet. The design procedure has been explained and designed using the stat-of-art Electronic Design Automation (EDA) tools for system design on FPGA. Simulation, synthesis and implementation on the FPGA target technology has been carried out.

Keywords: Daubechies wavelet, discrete wavelet transform, Haar wavelet, Xilinx FPGA.

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Authors: Farhan Beg

Abstract:

A Space Vector based Pulse Width Modulation control technique for the three-phase PWM converter is proposed in this paper. The proposed control scheme is based on a synchronous reference frame model. High performance and efficiency is obtained with regards to the DC bus voltage and the power factor considerations of the PWM rectifier thus leading to low losses. MATLAB/SIMULINK are used as a platform for the simulations and a SIMULINK model is presented in the paper. The results show that the proposed model demonstrates better performance and properties compared to the traditional SPWM method and the method improves the dynamic performance of the closed loop drastically. For the Space Vector based Pulse Width Modulation, Sine signal is the reference waveform and triangle waveform is the carrier waveform. When the value sine signal is large than triangle signal, the pulse will start produce to high. And then when the triangular signals higher than sine signal, the pulse will come to low. SPWM output will changed by changing the value of the modulation index and frequency used in this system to produce more pulse width. The more pulse width produced, the output voltage will have lower harmonics contents and the resolution increase.

Keywords: Power Factor, SVPWM, PWM rectifier, SPWM.

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Authors: A. Arya, R. Laha, V. R. Dantham

Abstract:

We report the enhancement of Raman scattering signal by one order of magnitude using photonic nanojet (PNJ) of a lollipop shaped dielectric microstructure (LSDM) fabricated by a pulsed CO₂ laser. Here, the PNJ is generated by illuminating sphere portion of the LSDM with non-resonant laser. Unlike the surface enhanced Raman scattering (SERS) technique, this technique is simple, and the obtained results are highly reproducible. In addition, an efficient technique is proposed to enhance the SERS signal with the help of high quality factor optical resonance (whispering gallery mode) of a LSDM. From the theoretical simulations, it has been found that at least an order of magnitude enhancement in the SERS signal could be achieved easily using the proposed technique. We strongly believe that this report will enable the research community for improving the Raman scattering signals.

Keywords: Localized surface plasmons, photonic nanojet, SERS, whispering gallery mode.

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Authors: Ni Ni Soe , Masahiro Nakagawa

Abstract:

Functional near infrared spectroscopy (fNIRS) is a practical non-invasive optical technique to detect characteristic of hemoglobin density dynamics response during functional activation of the cerebral cortex. In this paper, fNIRS measurements were made in the area of motor cortex from C4 position according to international 10-20 system. Three subjects, aged 23 - 30 years, were participated in the experiment. The aim of this paper was to evaluate the effects of different motor activation tasks of the hemoglobin density dynamics of fNIRS signal. The chaotic concept based on deterministic dynamics is an important feature in biological signal analysis. This paper employs the chaotic properties which is a novel method of nonlinear analysis, to analyze and to quantify the chaotic property in the time series of the hemoglobin dynamics of the various motor imagery tasks of fNIRS signal. Usually, hemoglobin density in the human brain cortex is found to change slowly in time. An inevitable noise caused by various factors is to be included in a signal. So, principle component analysis method (PCA) is utilized to remove high frequency component. The phase pace is reconstructed and evaluated the Lyapunov spectrum, and Lyapunov dimensions. From the experimental results, it can be conclude that the signals measured by fNIRS are chaotic.

Keywords: Chaos, hemoglobin, Lyapunov spectrum, motorimagery, near infrared spectroscopy (NIRS), principal componentanalysis (PCA).

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Authors: Bimali Sanjeevani Weerakoon, Toshiaki Osuga, Takehisa Konishi

Abstract:

Magnetic Resonance Imaging Contrast Agents (MRI-CM) are significant in the clinical and biological imaging as they have the ability to alter the normal tissue contrast, thereby affecting the signal intensity to enhance the visibility and detectability of images. Superparamagnetic Iron Oxide (SPIO) nanoparticles, coated with dextran or carboxydextran are currently available for clinical MR imaging of the liver. Most SPIO contrast agents are T2 shortening agents and Resovist (Ferucarbotran) is one of a clinically tested, organ-specific, SPIO agent which has a low molecular carboxydextran coating. The enhancement effect of Resovist depends on its relaxivity which in turn depends on factors like magnetic field strength, concentrations, nanoparticle properties, pH and temperature. Therefore, this study was conducted to investigate the impact of field strength and different contrast concentrations on enhancement effects of Resovist. The study explored the MRI signal intensity of Resovist in the physiological range of plasma from T2-weighted spin echo sequence at three magnetic field strengths: 0.47 T (r1=15, r2=101), 1.5 T (r1=7.4, r2=95), and 3 T (r1=3.3, r2=160) and the range of contrast concentrations by a mathematical simulation. Relaxivities of r1 and r2 (L mmol-1 Sec-1) were obtained from a previous study and the selected concentrations were 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 2.0, and 3.0 mmol/L. T2-weighted images were simulated using TR/TE ratio as 2000 ms /100 ms. According to the reference literature, with increasing magnetic field strengths, the r1 relaxivity tends to decrease while the r2 did not show any systematic relationship with the selected field strengths. In parallel, this study results revealed that the signal intensity of Resovist at lower concentrations tends to increase than the higher concentrations. The highest reported signal intensity was observed in the low field strength of 0.47 T. The maximum signal intensities for 0.47 T, 1.5 T and 3 T were found at the concentration levels of 0.05, 0.06 and 0.05 mmol/L, respectively. Furthermore, it was revealed that, the concentrations higher than the above, the signal intensity was decreased exponentially. An inverse relationship can be found between the field strength and T2 relaxation time, whereas, the field strength was increased, T2 relaxation time was decreased accordingly. However, resulted T2 relaxation time was not significantly different between 0.47 T and 1.5 T in this study. Moreover, a linear correlation of transverse relaxation rates (1/T2, s–1) with the concentrations of Resovist can be observed. According to these results, it can conclude that the concentration of SPIO nanoparticle contrast agents and the field strengths of MRI are two important parameters which can affect the signal intensity of T2-weighted SE sequence. Therefore, when MR imaging those two parameters should be considered prudently.

Keywords: Concentration, Resovist, Field strength, Relaxivity, Signal intensity.

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Authors: Sukrit Shankar, Chetana Shanta Patsa, Jaydev Sharma

Abstract:

Fractional Fourier Transform is a generalization of the classical Fourier Transform. The Fractional Fourier span in general depends on the amplitude and phase functions of the signal and varies with the transform order. However, with the development of the Fractional Fourier filter banks, it is advantageous in some cases to have different transform orders for different filter banks to achieve better decorrelation of the windowed and overlapped time signal. We present an expression that is useful for finding the perturbation in the Fractional Fourier span due to the erroneous transform order and the possible variation in the window shape and length. The expression is based on the dependency of the time-Fractional Fourier span Uncertainty on the amplitude and phase function of the signal. We also show with the help of the developed expression that the perturbation of span has a varying degree of sensitivity for varying degree of transform order and the window coefficients.

Keywords: Fractional Fourier Transform, Perturbation, Fractional Fourier span, amplitude, phase, transform order, filterbanks.

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