Search results for: array signal processing

Authors: I. M. Salama, R. N. Miftahof

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A functional element of the myenteric nervous plexus is a morphologically distinct ganglion. Composed of sensory, inter- and motor neurons and arranged via synapses in neuronal circuits, their task is to decipher and integrate spike coded information within the plexus into regulatory output signals. The stability of signal processing in response to a wide range of internal/external perturbations depends on the plasticity of individual neurons. Any aberrations in this inherent property may lead to instability with the development of a dynamics chaos and can be manifested as pathological conditions, such as intestinal dysrhythmia, irritable bowel syndrome. The aim of this study is to investigate patterns of signal transduction within a two-neuronal chain - a ganglion - under normal physiological and structurally altered states. The ganglion contains the primary sensory (AH-type) and motor (S-type) neurons linked through a cholinergic dendro somatic synapse. The neurons have distinguished electrophysiological characteristics including levels of the resting and threshold membrane potentials and spiking activity. These are results of ionic channel dynamics namely: Na+, K+, Ca++- activated K+, Ca++ and Cl-. Mechanical stretches of various intensities and frequencies are applied at the receptive field of the AH-neuron generate a cascade of electrochemical events along the chain. At low frequencies, ν < 0.3 Hz, neurons demonstrate strong connectivity and coherent firing. The AH-neuron shows phasic bursting with spike frequency adaptation while the S-neuron responds with tonic bursts. At high frequency, ν > 0.5 Hz, the pattern of electrical activity changes to rebound and mixed mode bursting, respectively, indicating ganglionic loss of plasticity and adaptability. A simultaneous increase in neuronal conductivity for Na+, K+ and Ca++ ions results in tonic mixed spiking of the sensory neuron and class 2 excitability of the motor neuron. Although the signal transduction along the chain remains stable the synchrony in firing pattern is not maintained and the number of discharges of the S-type neuron is significantly reduced. A concomitant increase in Ca++- activated K+ and a decrease in K+ in conductivities re-establishes weak connectivity between the two neurons and converts their firing pattern to a bistable mode. It is thus demonstrated that neuronal plasticity and adaptability have a stabilizing effect on the dynamics of signal processing in the ganglion. Functional modulations of neuronal ion channel permeability, achieved in vivo and in vitro pharmacologically, can improve connectivity between neurons. These findings are consistent with experimental electrophysiological recordings from myenteric ganglia in intestinal dysrhythmia and suggest possible pathophysiological mechanisms.

Keywords: neuronal chain, signal transduction, plasticity, stability

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Authors: Carolina Gouveia, José Vieira, Pedro Pinho

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The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.

Keywords: bio-signals, DC component, Doppler effect, ellipse fitting, radar, SDR

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Authors: Miljan B. Petrović, Dušan B. Petrović, Goran S. Nikolić

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This paper describes a method for AWGN (Additive White Gaussian Noise) variance estimation in noisy stochastic signals, referred to as Multiplicative-Noising Variance Estimation (MNVE). The aim was to develop an estimation algorithm with minimal number of assumptions on the original signal structure. The provided MATLAB simulation and results analysis of the method applied on speech signals showed more accuracy than standardized AR (autoregressive) modeling noise estimation technique. In addition, great performance was observed on very low signal-to-noise ratios, which in general represents the worst case scenario for signal denoising methods. High execution time appears to be the only disadvantage of MNVE. After close examination of all the observed features of the proposed algorithm, it was concluded it is worth of exploring and that with some further adjustments and improvements can be enviably powerful.

Keywords: noise, signal-to-noise ratio, stochastic signals, variance estimation

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Authors: Ana Serafimovic, Karthik Devarajan

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Non-negative matrix factorization approximates a high dimensional non-negative matrix V as the product of two non-negative matrices, W and H, and allows only additive linear combinations of data, enabling it to learn parts with representations in reality. It has been successfully applied in the analysis and interpretation of high dimensional data arising in neuroscience, computational biology, and natural language processing, to name a few. The objective of this paper is to assess a hybrid algorithm for non-negative matrix factorization with multiplicative updates. The method aims to minimize the symmetric version of Kullback-Leibler divergence known as intrinsic information and assumes that the noise is signal-dependent and that it originates from an arbitrary distribution from the exponential family. It is a generalization of currently available algorithms for Gaussian, Poisson, gamma and inverse Gaussian noise. We demonstrate the potential usefulness of the new generalized algorithm by comparing its performance to the baseline methods which also aim to minimize symmetric divergence measures.

Keywords: non-negative matrix factorization, dimension reduction, clustering, intrinsic information, symmetric information divergence, signal-dependent noise, exponential family, generalized Kullback-Leibler divergence, dual divergence

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Authors: Maryam Hasheminasab, Ahmed Cheldavi, Ahmed Kishk

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Frequency-diverse arrays (FDAs) have garnered significant attention from researchers due to their ability to combine frequency diversity with the inherent spatial diversity of an array. The introduction of frequency diversity in FDAs enables the generation of auto-scanning patterns that are range-dependent, which can have advantageous applications in communication and radar systems. However, the main challenge in implementing FDAs lies in determining the technique for distributing frequencies among the array elements. One approach to address this challenge is by utilizing coupled oscillators, which are a technique commonly employed in active microwave theory. Nevertheless, the limited stability range of coupled oscillators poses another obstacle to effectively utilizing this technique. In this paper, we explore the possibility of employing a coupled oscillator array in the mode lock state (MLS) for implementing frequency distribution in FDAs. Additionally, we propose and simulate the use of a digital phase-locked loop (DPLL) as a backup technique to stabilize the oscillators. Through simulations, we validate the functionality of this technique. This technique holds great promise for advancing the implementation of phased arrays and overcoming current scan rate and phase shifter limitations, especially in millimeter wave frequencies.

Keywords: angle-changing rate, auto scanning beam, pull-in range, hold-in range, locking range, mode locked state, frequency locked state

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Authors: Jing Wu, Wei Lv, Yibing Li, Yuanfan You

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The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix.

Keywords: DBSCAN, potential function, speech signal, the UBSS model

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Authors: K. K. Lee, H. W. Han, H. L. Kang, T. A. Kim, S. H. Han

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For the robust optimization of the manufacturing product design, there are design objectives that must be achieved, such as a minimization of the mean and standard deviation in objective functions within the required sensitivity constraints. The authors utilized the sensitivity of objective functions and constraints with respect to the effective design variables to reduce the computational burden associated with the evaluation of the probabilities. The individual mean and sensitivity values could be estimated easily by using the 9 level orthogonal array based response surface models optimized by the stepwise regression. The present study evaluates a proposed procedure from the robust optimization of rubber domes that are commonly used for keyboard switching, by using the 9 level orthogonal array and stepwise regression along with a desirability function. In addition, a new robust optimization process, i.e., the I2GEO (Identify, Integrate, Generate, Explore and Optimize), was proposed on the basis of the robust optimization in rubber domes. The optimized results from the response surface models and the estimated results by using the finite element analysis were consistent within a small margin of error. The standard deviation of objective function is decreasing 54.17% with suggested sensitivity based robust optimization. (Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2017, S2455569)

Keywords: objective function, orthogonal array, response surface model, robust optimization, stepwise regression

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Authors: Subha D. Puthankattil, Paul K. Joseph

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Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy.

Keywords: EEG, depression, wavelet entropy, approximate entropy, relative wavelet energy, multiresolution decomposition

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Authors: Najiya Omar, Hamed Aly, Timothy Little

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The optimal size of a photovoltaic (PV) array is considered a critical factor in designing an efficient PV system due to the dependence of the PV cell performance on temperature. A high temperature can lead to voltage losses of solar panels, whereas a low temperature can cause voltage overproduction. There are two possible scenarios of the inverter’s operation in which they are associated with the erroneous calculations of the number of PV panels: 1) If the number of the panels is scant and the temperature is high, the minimum voltage required to operate the inverter will not be reached. As a result, the inverter will shut down. 2) Comparably, if the number of panels is excessive and the temperature is low, the produced voltage will be more than the maximum limit of the inverter which can cause the inverter to get disconnected or even damaged. This article aims to assess theoretical and practical methodologies to calculate size and determine the topology of a PV array. The results are validated by applying an experimental evaluation for a 100 kW Grid-connected PV system for a location in Halifax, Nova Scotia and achieving a satisfactory system performance compared to the previous work done.

Keywords: sizing PV panels, theoretical and practical methodologies, topology of PV array, grid-connected PV

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Authors: Shengqi Yu, Jinwei Zhao

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This paper presents a kind of analog circuit based temperature control system, which is mainly composed by threshold control signal circuit, synchronization signal circuit and trigger pulse circuit. Firstly, the temperature feedback signal function is realized by temperature sensor TS503F3950E. Secondly, the main control circuit forms the cycle controlled pulse signal to control the thyristor switching model. Finally two reverse paralleled thyristors regulate the output power by their switching state. In the consequence, this is a modernized and energy-saving domestic electric heating system.

Keywords: time base circuit, automatic control, zero-crossing trigger, temperature control

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Authors: Kwan Hee Han, Jun Woo Lee, Sung Moon Bae, Twae Kyung Park

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ECA (Event-Condition-Action) languages are largely adopted for event processing since they are an intuitive and powerful paradigm for programming reactive systems. However, there are some limitations about ECA rules for processing of complex events such as coupling of event producer and consumer. The objective of this paper is to propose an ECA rule pattern to improve the current limitations of ECA rule, and to develop a prototype system. In this paper, conventional ECA rule is separated into 3 parts and each part is extended to meet the requirements of CEP. Finally, event processing logic is established by combining the relevant elements of 3 parts. The usability of proposed extended ECA rule is validated by a test scenario in this study.

Keywords: complex event processing, ECA rule, Event processing system, event-driven architecture, internet of things

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Authors: Fabricio Costa Silva, Samuel Xavier de Souza

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A Global Positioning System (GPS) receiver is responsible to determine position, velocity and timing information by using satellite information. To get this information are necessary to combine an incoming and a locally generated signal. The procedure called acquisition need to found two information, the frequency and phase of the incoming signal. This is very time consuming, so there are several techniques to reduces the computational complexity, but each of then put projects issues in conflict. I this papers we present a method that can reduce the computational complexity by reducing the search space and paralleling the search.

Keywords: GPS, acquisition, complexity, parallelism

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Authors: Israa Sh. Tawfic, Sema Koc Kayhan

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Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.

Keywords: compressed sensing, lest support orthogonal matching pursuit, partial knowing support, restricted isometry property, signal reconstruction

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Authors: Jongbae Lee, Seongsoo Lee

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Modern sensors often embed small-size digital controller for sensor control, value calibration, and signal processing. These sensors require digital data communication with host microprocessors, but conventional digital communication protocols are too heavy for price reduction. SAE J2716 SENT (single edge nibble transmission) protocol transmits direct digital waveforms instead of complicated analog modulated signals. In this paper, a SENT interface is designed in Verilog HDL (hardware description language) and implemented in FPGA (field-programmable gate array) evaluation board. The designed SENT interface consists of frame encoder/decoder, configuration register, tick period generator, CRC (cyclic redundancy code) generator/checker, and TX/RX (transmission/reception) buffer. Frame encoder/decoder is implemented as a finite state machine, and it controls whole SENT interface. Configuration register contains various parameters such as operation mode, tick length, CRC option, pause pulse option, and number of nibble data. Tick period generator generates tick signals from input clock. CRC generator/checker generates or checks CRC in the SENT data frame. TX/RX buffer stores transmission/received data. The designed SENT interface can send or receives digital data in 25~65 kbps at 3 us tick. Synthesized in 0.18 um fabrication technologies, it is implemented about 2,500 gates.

Keywords: digital sensor interface, SAE J2716, SENT, verilog HDL

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Authors: Arth J. Shah, Madhu R. Kamble

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Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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Authors: Maher Ali Rusho, Sudipta Halder

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The purpose of the study is to develop optimal solutions for models of parallel computing systems using the Java language. During the study, programmes were written for the examined models of parallel computing systems. The result of the parallel sorting code is the output of a sorted array of random numbers. When processing data in parallel, the time spent on processing and the first elements of the list of squared numbers are displayed. When processing requests asynchronously, processing completion messages are displayed for each task with a slight delay. The main results include the development of optimisation methods for algorithms and processes, such as the division of tasks into subtasks, the use of non-blocking algorithms, effective memory management, and load balancing, as well as the construction of diagrams and comparison of these methods by characteristics, including descriptions, implementation examples, and advantages. In addition, various specialised libraries were analysed to improve the performance and scalability of the models. The results of the work performed showed a substantial improvement in response time, bandwidth, and resource efficiency in parallel computing systems. Scalability and load analysis assessments were conducted, demonstrating how the system responds to an increase in data volume or the number of threads. Profiling tools were used to analyse performance in detail and identify bottlenecks in models, which improved the architecture and implementation of parallel computing systems. The obtained results emphasise the importance of choosing the right methods and tools for optimising parallel computing systems, which can substantially improve their performance and efficiency.

Keywords: algorithm optimisation, memory management, load balancing, performance profiling, asynchronous programming.

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Authors: Fabricio Costa Silva, Samuel Xavier de Souza

Abstract:

A Global Positioning System (GPS) receiver is responsible to determine position, velocity and timing information by using satellite information. To get this information's are necessary to combine an incoming and a locally generated signal. The procedure called acquisition need to found two information, the frequency and phase of the incoming signal. This is very time consuming, so there are several techniques to reduces the computational complexity, but each of then put projects issues in conflict. I this papers we present a method that can reduce the computational complexity by reducing the search space and paralleling the search.

Keywords: GPS, acquisition, low complexity, parallelism

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Authors: Ahmed Elaksher, Islam Omar

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Accurate geometric relation algorithms are imperative in Earth and planetary satellite and aerial image processing, particularly for high-resolution images that are used for topographic mapping. Most of these satellites carry push-broom sensors. These sensors are optical scanners equipped with linear arrays of CCDs. These sensors have been deployed on most EOSs. In addition, the LROC is equipped with two push NACs that provide 0.5 meter-scale panchromatic images over a 5 km swath of the Moon. The HiRISE carried by the MRO and the HRSC carried by MEX are examples of push-broom sensor that produces images of the surface of Mars. Sensor models developed in photogrammetry relate image space coordinates in two or more images with the 3D coordinates of ground features. Rigorous sensor models use the actual interior orientation parameters and exterior orientation parameters of the camera, unlike approximate models. In this research, we generate a generic push-broom sensor model to process imageries acquired through linear array cameras and investigate its performance, advantages, and disadvantages in generating topographic models for the Earth, Mars, and the Moon. We also compare and contrast the utilization, effectiveness, and applicability of available photogrammetric techniques and softcopies with the developed model. We start by defining an image reference coordinate system to unify image coordinates from all three arrays. The transformation from an image coordinate system to a reference coordinate system involves a translation and three rotations. For any image point within the linear array, its image reference coordinates, the coordinates of the exposure center of the array in the ground coordinate system at the imaging epoch (t), and the corresponding ground point coordinates are related through the collinearity condition that states that all these three points must be on the same line. The rotation angles for each CCD array at the epoch t are defined and included in the transformation model. The exterior orientation parameters of an image line, i.e., coordinates of exposure station and rotation angles, are computed by a polynomial interpolation function in time (t). The parameter (t) is the time at a certain epoch from a certain orbit position. Depending on the types of observations, coordinates, and parameters may be treated as knowns or unknowns differently in various situations. The unknown coefficients are determined in a bundle adjustment. The orientation process starts by extracting the sensor position and, orientation and raw images from the PDS. The parameters of each image line are then estimated and imported into the push-broom sensor model. We also define tie points between image pairs to aid the bundle adjustment model, determine the refined camera parameters, and generate highly accurate topographic maps. The model was tested on different satellite images such as IKONOS, QuickBird, and WorldView-2, HiRISE. It was found that the accuracy of our model is comparable to those of commercial and open-source software, the computational efficiency of the developed model is high, the model could be used in different environments with various sensors, and the implementation process is much more cost-and effort-consuming.

Keywords: photogrammetry, push-broom sensors, IKONOS, HiRISE, collinearity condition

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Authors: Musefiu Aderinola, F. A. Amuda

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Outages of GSM signals may be experienced at some indoor locations even when there are strong outdoor receptions. This is often traced to the building penetration loss, which account for increased attenuation of received GSM signals level when a mobile signal device is moved indoor from outdoor. In this work, measurement of two existing GSM operators signal level were made outside and inside two selected buildings- mud and block which represent the prevalent building types in Kazaure, Jigawa State, Nigeria. A gionee P2 mobile phone with RF signal tracker software installed in it was used and the result shows that an average loss of 10.62dBm and 4.25dBm for mud and block buildings respectively.

Keywords: penetration loss, outdoor reception, Gionee P2, RF signal tracker, mud and block building

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Authors: Lukasz Szydlowski, Jiri Ehlich, Igor Goryanin

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We demonstrate a single chamber, 96-well-plated based Microbial Fuel Cell (MFC) with printed, electronic components. This invention is aimed at robust selection of electrogenic microbial community under specific conditions, e.g., electrode potential, pH, nutrient concentration, salt concentration that can be altered within the 96 well plate array. This invention enables robust selection of electrogenic microbial community under the homogeneous reactor, with multiple conditions that can be altered to allow comparative analysis. It can be used as a standalone technique or in conjunction with other selective processes, e.g., flow cytometry, microfluidic-based dielectrophoretic trapping. Mobile conductive elements, like carbon paper, carbon sponge, activated charcoal granules, metal mesh, can be inserted inside to increase the anode surface area in order to collect electrogenic microorganisms and to transfer them into new reactors or for other analytical works. An array of 96-well plate allows this device to be operated by automated pipetting stations.

Keywords: bioengineering, electrochemistry, electromicrobiology, microbial fuel cell

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Authors: S. S. Sree Sanker, K. N. Madhusoodanan

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Optical biosensors are dominant alternative for traditional analytical methods, because of their small size, simple design and high sensitivity. Photonic sensing method is one of the recent advancing technology for biosensors. It measures the change in refractive index which is induced by the difference in molecular interactions due to the change in concentration of the analyte. Glucose is an aldosic monosaccharide, which is a metabolic source in many of the organisms. The terahertz waves occupies the space between infrared and microwaves in the electromagnetic spectrum. Terahertz waves are expected to be applied to various types of sensors for detecting harmful substances in blood, cancer cells in skin and micro bacteria in vegetables. We have designed glucose sensors using silicon based 1D and 2D photonic crystal pillar arrays in terahertz frequency range. 1D photonic crystal has rectangular pillars with height 100 µm, length 1600 µm and width 50 µm. The array period of the crystal is 500 µm. 2D photonic crystal has 5×5 cylindrical pillar array with an array period of 75 µm. Height and diameter of the pillar array are 160 µm and 100 µm respectively. Two samples considered in the work are blood and glucose solution, which are labelled as sample 1 and sample 2 respectively. The proposed sensor detects the concentration of glucose in the samples from 0 to 100 mg/dL. For this, the crystal was irradiated with 0.3 to 3 THz waves. By analyzing the obtained S parameter, the refractive index of the crystal corresponding to the particular concentration of glucose was measured using the parameter retrieval method. Refractive indices of the two crystals decreased gradually with the increase in concentration of glucose in the sample. For 1D photonic crystals, a gradual decrease in refractive index was observed at 1 THz. 2D photonic crystal showed this behavior at 2 THz. The proposed sensor was simulated using CST Microwave studio. This will enable us to develop a model which can be used to characterize a glucose sensor. The present study is expected to contribute to blood glucose monitoring.

Keywords: CST microwave studio, glucose sensor, photonic crystal, terahertz waves

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Jyoti Rani, Ashima Anand, Shivendra Shivani

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In recent years, physiological signals obtained in telemedicine have been stored independently from patient information. In addition, people have increasingly turned to mobile devices for information on health-related topics. Major authentication and security issues may arise from this storing, degrading the reliability of diagnostics. This study introduces an approach to reversible watermarking, which ensures security by utilizing the electrocardiogram (ECG) signal as a carrier for embedding patient information. In the proposed work, Pan-Tompkins++ is employed to convert the 1D ECG signal into a 2D signal. The frequency subbands of a signal are extracted using RDWT(Redundant discrete wavelet transform), and then one of the subbands is subjected to MSVD (Multiresolution singular valued decomposition for masking. Finally, the encrypted watermark is embedded within the signal. The experimental results show that the watermarked signal obtained is indistinguishable from the original signals, ensuring the preservation of all diagnostic information. In addition, the DnCNN (Denoising convolutional neural network) concept is used to denoise the retrieved watermark for improved accuracy. The proposed ECG signal-based watermarking method is supported by experimental results and evaluations of its effectiveness. The results of the robustness tests demonstrate that the watermark is susceptible to the most prevalent watermarking attacks.

Keywords: ECG, VMD, watermarking, PanTompkins++, RDWT, DnCNN, MSVD, chaotic encryption, attacks

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Authors: Kwazikwenkosi Sikhakhane, Suvendi Rimer, Mpho Gololo, Khmaies Oahada, Adnan Abu-Mahfouz

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Medical ultrasound imaging is a crucial diagnostic technique due to its affordability and non-invasiveness compared to other imaging methods. However, the presence of speckle noise, which is a form of multiplicative noise, poses a significant obstacle to obtaining clear and accurate images in ultrasound imaging. Speckle noise reduces image quality by decreasing contrast, resolution, and signal-to-noise ratio (SNR). This makes it difficult for medical professionals to interpret ultrasound images accurately. To address this issue, various techniques have been developed to reduce speckle noise in ultrasound images, which improves image quality. This paper aims to review some of these techniques, highlighting the advantages and disadvantages of each algorithm and identifying the scenarios in which they work most effectively.

Keywords: image processing, noise, speckle, ultrasound

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Authors: Yinjun Tu, Qiang Fang, Glenn I. Matthews, Shuenn-Yuh Lee

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This paper reports an efficient and rigorous self-adaptive stimulus artifacts removal approach for a mixed surface EMG (Electromyography) and stimulus signal during muscle stimulation. The recording of EMG and the stimulation of muscles were performing simultaneously. It is difficult to generate muscle fatigue feature from the mixed signal, which can be further used in closed loop system. A self-adaptive method is proposed in this paper, the stimulation frequency was calculated and verified firstly. Then, a mask was created based on this stimulation frequency to remove the undesired stimulus. 20 EMG signal recordings were analyzed, and the ANOVA (analysis of variance) approach illustrated that the decreasing trend of median power frequencies was successfully generated from the 'cleaned' EMG signal.

Keywords: EMG, FES, stimulus artefacts, self-adaptive

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Authors: G. Rajeshwari, V. D. M. Jabez Daniel

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Radio Frequency Identification systems are used for automated identification in various applications such as automobiles, health care and security. It is also called as the automated data collection technology. RFID readers are placed in any area to scan large number of tags to cover a wide distance. The placement of the RFID elements may result in several types of collisions. A major challenge in RFID system is collision avoidance. In the previous works the collision was avoided by using algorithms such as ALOHA and tree algorithm. This work proposes collision reduction and increased throughput through reading enhancement method with tree algorithm. The reading enhancement is done by improving interrogation procedure and increasing the data handling capacity of RFID reader with parallel processing. The work is simulated using Xilinx ISE 14.5 verilog language. By implementing this in the RFID system, we can able to achieve high throughput and avoid collision in the reader at a same instant of time. The overall system efficiency will be increased by implementing this.

Keywords: antenna, anti-collision protocols, data management system, reader, reading enhancement, tag

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Authors: Jalal Karam

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The methods of Fourier, Laplace, and Wavelet Transforms provide transfer functions and relationships between the input and the output signals in linear time invariant systems. This paper shows the equivalence among these three methods and in each case presenting an application of the appropriate (Fourier, Laplace or Wavelet) to the convolution theorem. In addition, it is shown that the same holds for a direct integration method. The Biorthogonal wavelets Bior3.5 and Bior3.9 are examined and the zeros distribution of their polynomials associated filters are located. This paper also presents the significance of utilizing wavelets as effective tools in processing speech signals for common multimedia applications in general, and for recognition and compression in particular. Theoretically and practically, wavelets have proved to be effective and competitive. The practical use of the Continuous Wavelet Transform (CWT) in processing and analysis of speech is then presented along with explanations of how the human ear can be thought of as a natural wavelet transformer of speech. This generates a variety of approaches for applying the (CWT) to many paradigms analysing speech, sound and music. For perception, the flexibility of implementation of this transform allows the construction of numerous scales and we include two of them. Results for speech recognition and speech compression are then included.

Keywords: continuous wavelet transform, biorthogonal wavelets, speech perception, recognition and compression

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Authors: Subal Kar, Madhuja Ghosh, Soumik Das, Antara Saha

Abstract:

A novel technique has been developed to generate ultra-stable millimeter-wave signal by optical heterodyning of the output from two slave laser (SL) sources injection-locked to the sidebands of a frequency modulated (FM) master laser (ML). Precise thermal tuning of the SL sources is required to lock the particular slave laser frequency to the desired FM sidebands of the ML. The output signals from the injection-locked SL when coherently heterodyned in a fast response photo detector like high electron mobility transistor (HEMT), extremely stable millimeter-wave signal having very narrow line width can be generated. The scheme may also be used to generate ultra-stable sub-millimeter-wave/terahertz signal.

Keywords: FM sideband injection locking, master-slave injection locking, millimetre-wave signal generation, optical heterodyning

Procedia PDF Downloads 391

Authors: M. Y. Ismail, M. Inam

Abstract:

This paper presents the design and analysis of Liquid Crystal (LC) based tunable reflect array antenna with different design configurations within X-band frequency range. The effect of LC volume used for unit cell element on frequency tunability and reflection loss performance has been investigated. Moreover different slot embedded patch element configurations have been proposed for LC based tunable reflect array antenna design with enhanced performance. The detailed fabrication and measurement procedure for different LC based unit cells has been presented. The waveguide scattering parameter measured results demonstrated that by using the circular slot embedded patch elements, the frequency tunability and dynamic phase range can be increased from 180 MHz to 200 MHz and 120° to 124° respectively. Furthermore the circular slot embedded patch element can be designed at 10 GHz resonant frequency with a patch volume of 2.71 mm3 as compared to 3.47 mm3 required for rectangular patch without slot.

Keywords: liquid crystal, tunable reflect array, frequency tunability, dynamic phase range

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Authors: Meng-Chyi Wu, Bonn Lin, Jyun-Hao Liao, Chein-Ju Chen, Yu-Cheng Jhuang, Mau-Phon Houng, Fang-Hsing Wang, Min-Chu Liu, Cheng-Fu Yang, Cheng-Shong Hong

Abstract:

Since the use of wireless communications has become critical nowadays, the available RF spectrum has become limited. Ultraviolet (UV) communication system can alleviate the spectrum constraint making UV communication system a potential alternative to future communication demands. Also, UV links can provide faster communication rate and can be used in combination with existing RF communication links, providing new communications diversity with higher user capacity. The UV region of electromagnetic spectrum has been of interest to detector, imaging and communication technologies because the stratospheric ozone layer effectively absorbs some solar UV radiation from reaching the earth surface. The wavebands where most of UV radiation is absorbed by the ozone are commonly known as the solar blind region. By operating in UV-C band (200-280 nm) the communication system can minimize the transmission power consumption since it will have less radiation noise. UV communication uses the UV ray as the medium. Electric signal is carried on this band after being modulated and then be transmitted within the atmosphere as channel. Though the background noise of UV-C communication is very low owing to the solar-blind feature, it leads to a large propagation loss. The 370 nm UV provides a much lower propagation loss than that the UV-C does and the recent device technology for UV source on this band is more mature. The fabricated 370 nm AlGaN light-emitting diodes (LEDs) with an aperture size of 45 m exhibit a modulation bandwidth of 165 MHz at 30 mA and a high power of 7 W/cm2 at 230 A/cm2. In order to solve the problem of low power in single UV LED, a UV LED array is presented in.

Keywords: ultraviolet (UV) communication, light-emitting diodes (LEDs), modulation bandwidth, LED array, 370 nm

Procedia PDF Downloads 414