Search results for: Signal to Noise Peak-Peak Ratio (PSNR)

Authors: Amir Rastegarnia, Mohammad Ali Tinati, Azam Khalili

Abstract:

In this paper we consider the problem of distributed adaptive estimation in wireless sensor networks for two different observation noise conditions. In the first case, we assume that there are some sensors with high observation noise variance (noisy sensors) in the network. In the second case, different variance for observation noise is assumed among the sensors which is more close to real scenario. In both cases, an initial estimate of each sensor-s observation noise is obtained. For the first case, we show that when there are such sensors in the network, the performance of conventional distributed adaptive estimation algorithms such as incremental distributed least mean square (IDLMS) algorithm drastically decreases. In addition, detecting and ignoring these sensors leads to a better performance in a sense of estimation. In the next step, we propose a simple algorithm to detect theses noisy sensors and modify the IDLMS algorithm to deal with noisy sensors. For the second case, we propose a new algorithm in which the step-size parameter is adjusted for each sensor according to its observation noise variance. As the simulation results show, the proposed methods outperforms the IDLMS algorithm in the same condition.

Keywords: Distributes estimation, sensor networks, adaptive filter, IDLMS.

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Authors: S. Ghorbani, N. I. Polushin

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Chatter vibrations, occurring during cutting process, cause vibration between the cutting tool and workpiece, which deteriorates surface roughness and reduces tool life. The purpose of this study is to investigate the influence of cutting parameters and tool construction on surface roughness and vibration in turning of aluminum alloy AA2024. A new design of cutting tool is proposed, which is filled up with epoxy granite in order to improve damping capacity of the tool. Experiments were performed at the lathe using carbide cutting insert coated with TiC and two different cutting tools made of AISI 5140 steel. Taguchi L9 orthogonal array was applied to design of experiment and to optimize cutting conditions. By the help of signal-to-noise ratio and analysis of variance the optimal cutting condition and the effect of the cutting parameters on surface roughness and vibration were determined. Effectiveness of Taguchi method was verified by confirmation test. It was revealed that new cutting tool with epoxy granite has reduced vibration and surface roughness due to high damping properties of epoxy granite in toolholder.

Keywords: ANOVA, damping capacity, surface roughness, Taguchi method, vibration.

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Authors: Amir Rastegarnia, Mohammad Ali Tinati, Azam Khalili

Abstract:

In this paper we consider the issue of distributed adaptive estimation over sensor networks. To deal with more realistic scenario, different variance for observation noise is assumed for sensors in the network. To solve the problem of different variance of observation noise, the proposed method is divided into two phases: I) Estimating each sensor-s observation noise variance and II) using the estimated variances to obtain the desired parameter. Our proposed algorithm is based on a diffusion least mean square (LMS) implementation with linear combiner model. In the proposed algorithm, the step-size parameter the coefficients of linear combiner are adjusted according to estimated observation noise variances. As the simulation results show, the proposed algorithm considerably improves the diffusion LMS algorithm given in literature.

Keywords: Adaptive filter, distributed estimation, sensor network, diffusion.

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Authors: F. Nejadebrahimi, M. ArdebiliPour

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In this paper, we are going to determine the threshold levels of adaptive modulation in a burst by burst CDMA system by a suboptimum method so that the above method attempts to increase the average bit per symbol (BPS) rate of transceiver system by switching between the different modulation modes in variable channel condition. In this method, we choose the minimum values of average bit error rate (BER) and maximum values of average BPS on different values of average channel signal to noise ratio (SNR) and then calculate the relative threshold levels of them, so that when the instantaneous SNR increases, a higher order modulation be employed for increasing throughput and vise-versa when the instantaneous SNR decreases, a lower order modulation be employed for improvement of BER. In transmission step, by this adaptive modulation method, in according to comparison between obtained estimation of pilot symbols and a set of above suboptimum threshold levels, above system chooses one of states no transmission, BPSK, 4QAM and square 16QAM for modulation of data. The expected channel in this paper is a slow Rayleigh fading.

Keywords: AQAM, burst, BER, BPS, CDMA, threshold.

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Authors: H. P. Singh, S. Singh

Abstract:

The voice signal in Voice over Internet protocol (VoIP) system is processed through the best effort policy based IP network, which leads to the network degradations including delay, packet loss jitter. The work in this paper presents the implementation of finite impulse response (FIR) filter for voice quality improvement in the VoIP system through distributed arithmetic (DA) algorithm. The VoIP simulations are conducted with AMR-NB 6.70 kbps and G.729a speech coders at different packet loss rates and the performance of the enhanced VoIP signal is evaluated using the perceptual evaluation of speech quality (PESQ) measurement for narrowband signal. The results show reduction in the computational complexity in the system and significant improvement in the quality of the VoIP voice signal.

Keywords: VoIP, Signal Quality, Distributed Arithmetic, Packet Loss, Speech Coder.

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Authors: Srilekha Mukherjee, Subha Ash, Goutam Sanyal

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Information security plays a major role in uplifting the standard of secured communications via global media. In this paper, we have suggested a technique of encryption followed by insertion before transmission. Here, we have implemented two different concepts to carry out the above-specified tasks. We have used a two-point crossover technique of the genetic algorithm to facilitate the encryption process. For each of the uniquely identified rows of pixels, different mathematical methodologies are applied for several conditions checking, in order to figure out all the parent pixels on which we perform the crossover operation. This is done by selecting two crossover points within the pixels thereby producing the newly encrypted child pixels, and hence the encrypted cover image. In the next lap, the first and second order derivative operators are evaluated to increase the security and robustness. The last lap further ensures reapplication of the crossover procedure to form the final stego-image. The complexity of this system as a whole is huge, thereby dissuading the third party interferences. Also, the embedding capacity is very high. Therefore, a larger amount of secret image information can be hidden. The imperceptible vision of the obtained stego-image clearly proves the proficiency of this approach.

Keywords: Steganography, Crossover, Differential Calculus, Peak Signal to Noise Ratio, Cross-correlation Coefficient.

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Authors: Anatoli Torokhti, Stanley Miklavcic

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Suppose KY and KX are large sets of observed and reference signals, respectively, each containing N signals. Is it possible to construct a filter F : KY → KX that requires a priori information only on few signals, p  N, from KX but performs better than the known filters based on a priori information on every reference signal from KX? It is shown that the positive answer is achievable under quite unrestrictive assumptions. The device behind the proposed method is based on a special extension of the piecewise linear interpolation technique to the case of random signal sets. The proposed technique provides a single filter to process any signal from the arbitrarily large signal set. The filter is determined in terms of pseudo-inverse matrices so that it always exists.

Keywords: Wiener filter, filtering of stochastic signals.

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Authors: Abdelkader Magdy, Magdy Saeb, A. Baith Mohamed, Ahmed Khadragi

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The Deoxyribonucleic Acid (DNA) which is a doublestranded helix of nucleotides consists of: Adenine (A), Cytosine (C), Guanine (G) and Thymine (T). In this work, we convert this genetic code into an equivalent digital signal representation. Applying a wavelet transform, such as Haar wavelet, we will be able to extract details that are not so clear in the original genetic code. We compare between different organisms using the results of the Haar wavelet Transform. This is achieved by using the trend part of the signal since the trend part bears the most energy of the digital signal representation. Consequently, we will be able to quantitatively reconstruct different biological families.

Keywords: Digital Signal, DNA, Fluctuation part, Haar wavelet, Nucleotides, Trend part.

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Authors: Daniel Pereiro, Felix Martinez, Iker Urresti, Ana Gomez Gonzalez

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Today modern simulations solutions in the wind turbine industry have achieved a high degree of complexity and detail in result. Limitations exist when it is time to validate model results against measurements. Regarding Model validation it is of special interest to identify mode frequencies and to differentiate them from the different excitations. A wind turbine is a complex device and measurements regarding any part of the assembly show a lot of noise. Input excitations are difficult or even impossible to measure due to the stochastic nature of the environment. Traditional techniques for frequency analysis or features extraction are widely used to analyze wind turbine sensor signals, but have several limitations specially attending to non stationary signals (Events). A new technique based on autoregresive analysis techniques is introduced here for a specific application, a comparison and examples related to different events in the wind turbine operations are presented.

Keywords: Wind turbine, signal processing, mode extraction.

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Authors: Morgan Cheng, Wilson Ho, Max Yiu, Dragon Tsui, Wylog Wong, Yasir A. Naveed, C. S. Loong, Richard Kwan, K. C. Lam, Hannah Lo, C. L. Wong

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Hong Kong is known worldwide for high density living and the ability to thrive under trying circumstances. The 7.5 million residents of this busy metropolis live primarily in high-rise buildings which are built and demolished incessantly. Hong Kong residents are therefore affected continuously by numerous construction activities. In 2020, the Hong Kong Environmental Protection Department (EPD) commissioned a feasibility study on the management of construction noise, including those associated with renovation of domestic premises. A key component of the study focused on the review of practices concerning the management and control of construction noise in metropolitans in other parts of the world. To benefit from international best practices, this extensive review aimed at identifying possible areas of improvement in Hong Kong. The study first referred to the United Nations “The World’s Cities in 2016” Report and examined the top 100 cities therein. The 20 most suitable cities were then chosen for further review. Upon further screening, 12 cities with more relevant management practices were selected for further scrutiny. These 12 cities include: Asia – Tokyo, Seoul, Taipei, Guangzhou, Singapore; Europe – City of Westminster (London), Berlin; North America – Toronto, New York City, San Francisco; Oceania – Sydney, Melbourne. Subsequently, three cities, namely Sydney, City of Westminster, and New York City, were selected for in-depth review. These three were chosen primarily because of the maturity, success, and effectiveness of their construction noise management and control measures, as well as their similarity to Hong Kong in certain key aspects. One of the more important findings of the review is the importance of early focus on potential noise issues, with the objective of designing the noise away wherever practicable. The study examined the similar yet different construction noise early focus mechanisms of these three cities. This paper describes this landmark, worldwide and extensive review on international best construction noise management and control practices at the source, along the noise transmission path and at the receiver end. The methodology, approach, and key findings are presented succinctly in this paper. By sharing the findings with the acoustics professionals worldwide, it is hoped that more advanced and mature construction noise management practices can be developed to attain urban sustainability.

Keywords: construction noise, international best practices, noise control and noise management

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Authors: Frank Emmert Streib, Matthias Dehmer, Gökhan H. Bakır, Max Mühlhauser

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In this paper we investigate the influence of external noise on the inference of network structures. The purpose of our simulations is to gain insights in the experimental design of microarray experiments to infer, e.g., transcription regulatory networks from microarray experiments. Here external noise means, that the dynamics of the system under investigation, e.g., temporal changes of mRNA concentration, is affected by measurement errors. Additionally to external noise another problem occurs in the context of microarray experiments. Practically, it is not possible to monitor the mRNA concentration over an arbitrary long time period as demanded by the statistical methods used to learn the underlying network structure. For this reason, we use only short time series to make our simulations more biologically plausible.

Keywords: Dynamic Bayesian networks, structure learning, gene networks, Markov chain Monte Carlo, microarray data.

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Authors: Nor Asrina Binti Ramlee

Abstract:

Voltage sag, voltage swell, high-frequency noise and voltage transients are kinds of disturbances in power quality. They are also known as power quality events. Equipment used in the industry nowadays has become more sensitive to these events with the increasing complexity of equipment. This leads to the importance of distributing clean power quality to the consumer. To provide better service, the best analysis on power quality is very vital. Thus, this paper presents the events detection focusing on voltage sag and swell. The method is developed by applying time domain signal analysis using wavelet transform approach in MATLAB. Four types of mother wavelet namely Haar, Dmey, Daubechies, and Symlet are used to detect the events. This project analyzed real interrupted signal obtained from 22 kV transmission line in Skudai, Johor Bahru, Malaysia. The signals will be decomposed through the wavelet mothers. The best mother is the one that is capable to detect the time location of the event accurately.

Keywords: Power quality, voltage sag, voltage swell, wavelet transform.

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Authors: Jagadish H. Pujar, Pallavi S. Gurjal, Shambhavi D. S, Kiran S. Kunnur

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Medical image segmentation based on image smoothing followed by edge detection assumes a great degree of importance in the field of Image Processing. In this regard, this paper proposes a novel algorithm for medical image segmentation based on vigorous smoothening by identifying the type of noise and edge diction ideology which seems to be a boom in medical image diagnosis. The main objective of this algorithm is to consider a particular medical image as input and make the preprocessing to remove the noise content by employing suitable filter after identifying the type of noise and finally carrying out edge detection for image segmentation. The algorithm consists of three parts. First, identifying the type of noise present in the medical image as additive, multiplicative or impulsive by analysis of local histograms and denoising it by employing Median, Gaussian or Frost filter. Second, edge detection of the filtered medical image is carried out using Canny edge detection technique. And third part is about the segmentation of edge detected medical image by the method of Normalized Cut Eigen Vectors. The method is validated through experiments on real images. The proposed algorithm has been simulated on MATLAB platform. The results obtained by the simulation shows that the proposed algorithm is very effective which can deal with low quality or marginal vague images which has high spatial redundancy, low contrast and biggish noise, and has a potential of certain practical use of medical image diagnosis.

Keywords: Image Segmentation, Image smoothing, Edge Detection, Impulsive noise, Gaussian noise, Median filter, Canny edge, Eigen values, Eigen vector.

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Authors: Babu Sena Paul, Ratnajit Bhattacharjee

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Relay based communication has gained considerable importance in the recent years. In this paper we find the end-toend statistics of a two hop non-regenerative relay branch, each hop being Nakagami-m faded. Closed form expressions for the probability density functions of the signal envelope at the output of a selection combiner and a maximal ratio combiner at the destination node are also derived and analytical formulations are verified through computer simulation. These density functions are useful in evaluating the system performance in terms of bit error rate and outage probability.

Keywords: co-operative diversity, diversity combining, maximal ratio combining, selection combining.

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Authors: Samir Khrais, Adel Mahammod Hassan , Amro Gazawi

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The aim of this research is to evaluate surface roughness and develop a multiple regression model for surface roughness as a function of cutting parameters during the turning of flame hardened medium carbon steel with TiN-Al2O3-TiCN coated inserts. An experimental plan of work and signal-to-noise ratio (S/N) were used to relate the influence of turning parameters to the workpiece surface finish utilizing Taguchi methodology. The effects of turning parameters were studied by using the analysis of variance (ANOVA) method. Evaluated parameters were feed, cutting speed, and depth of cut. It was found that the most significant interaction among the considered turning parameters was between depth of cut and feed. The average surface roughness (Ra) resulted by TiN-Al2O3- TiCN coated inserts was about 2.44 μm and minimum value was 0.74 μm. In addition, the regression model was able to predict values for surface roughness in comparison with experimental values within reasonable limit.

Keywords: Medium carbon steel, Prediction, Surface roughness, Taguchi method

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Authors: Lei Zhang, Wen-jun Ruan, Hao Wang, Peng-xin Wang

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The source of the jet noise is generated by rocket exhaust plume during rocket engine testing. A domain decomposition approach is applied to the jet noise prediction in this paper. The aerodynamic noise coupling is based on the splitting into acoustic sources generation and sound propagation in separate physical domains. Large Eddy Simulation (LES) is used to simulate the supersonic jet flow. Based on the simulation results of the flow-fields, the jet noise distribution of the sound pressure level is obtained by applying the Ffowcs Williams-Hawkings (FW-H) acoustics equation and Fourier transform. The calculation results show that the complex structures of expansion waves, compression waves and the turbulent boundary layer could occur due to the strong interaction between the gas jet and the ambient air. In addition, the jet core region, the shock cell and the sound pressure level of the gas jet increase with the nozzle size increasing. Importantly, the numerical simulation results of the far-field sound are in good agreement with the experimental measurements in directivity.

Keywords: Supersonic gas jet, Large Eddy Simulation(LES), acoustic noise, Ffowcs Williams-Hawkings (FW-H) equations, nozzle size.

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Authors: Mario Mastriani

Abstract:

This work deals with unsupervised image deblurring. We present a new deblurring procedure on images provided by lowresolution synthetic aperture radar (SAR) or simply by multimedia in presence of multiplicative (speckle) or additive noise, respectively. The method we propose is defined as a two-step process. First, we use an original technique for noise reduction in wavelet domain. Then, the learning of a Kohonen self-organizing map (SOM) is performed directly on the denoised image to take out it the blur. This technique has been successfully applied to real SAR images, and the simulation results are presented to demonstrate the effectiveness of the proposed algorithms.

Keywords: Blur, Kohonen self-organizing map, noise, speckle, synthetic aperture radar.

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Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: Machine learning, Imbalanced data, Data mining, Big data.

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Authors: Arthur David Snider, Laiq Azam

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The classic problem of recovering arbitrary values of a band-limited signal from its samples has an added complication in software radio applications; namely, the resampling calculations inevitably fold aliases of the analog signal back into the original bandwidth. The phenomenon is quantified by the spur-free dynamic range. We demonstrate how a novel application of the Remez (Parks- McClellan) algorithm permits optimal signal recovery and SFDR, far surpassing state-of-the-art resamplers.

Keywords: Sampling methods, Signal sampling, Digital radio, Digital-analog conversion.

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Authors: Somkiat Lerkvaranyu, Yoshikazu Miyanaga

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In this paper, a new technique of signal detection has been proposed for detecting the orthogonal frequency-division multiplexing (OFDM) signal in the presence of nonlinear distortion.There are several advantages of OFDM communications system.However, one of the existing problems is remain considered as the nonlinear distortion generated by high-power-amplifier at the transmitter end due to the large dynamic range of an OFDM signal. The proposed method is the maximum likelihood detection with the symbol estimation. When the training data are available, the neural network has been used to learn the characteristic of received signal and to estimate the new positions of the transmitted symbol which are provided to the maximum likelihood detector. Resulting in the system performance, the nonlinear distortions of a traveling wave tube amplifier with OFDM signal are considered in this paper.Simulation results of the bit-error-rate performance are obtained with 16-QAM OFDM systems.

Keywords: OFDM, TWTA, nonlinear distortion, detection.

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Authors: Syed Fahad Tahir, Asifullah Khan, Abdul Majid, Anwar M. Mirza

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In this paper, we present an innovative scheme of blindly extracting message bits from an image distorted by an attack. Support Vector Machine (SVM) is used to nonlinearly classify the bits of the embedded message. Traditionally, a hard decoder is used with the assumption that the underlying modeling of the Discrete Cosine Transform (DCT) coefficients does not appreciably change. In case of an attack, the distribution of the image coefficients is heavily altered. The distribution of the sufficient statistics at the receiving end corresponding to the antipodal signals overlap and a simple hard decoder fails to classify them properly. We are considering message retrieval of antipodal signal as a binary classification problem. Machine learning techniques like SVM is used to retrieve the message, when certain specific class of attacks is most probable. In order to validate SVM based decoding scheme, we have taken Gaussian noise as a test case. We generate a data set using 125 images and 25 different keys. Polynomial kernel of SVM has achieved 100 percent accuracy on test data.

Keywords: Bit Correct Ratio (BCR), Grid Search, Intelligent Decoding, Jackknife Technique, Support Vector Machine (SVM), Watermarking.

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Authors: Shiang-Hwua Yu, Han-Sheng Tseng

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This paper presents a novel sinusoidal modulation scheme that features least correlated noise and high linearity. The modulation circuit, which is composed of a quantizer, a resonator, and a comparator, is capable of eliminating correlated modulation noise while doing modulation. The proposed modulation scheme combined with the linear quadratic optimal control is applied to a single-phase voltage source inverter and validated with the experiment results. The experiments show that the inverter supplies stable 60Hz 110V AC power with a total harmonic distortion of less than 1%, under the DC input variation from 190 V to 300 V and the output power variation from 0 to 600 W.

Keywords: Pulse width modulation, feedback dithering, linear quadratic control, inverter.

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Authors: Yoshio Kurosawa, Takao Yamaguchi

Abstract:

High frequency automotive interior noise above 500 Hz considerably affects automotive passenger comfort. To reduce this noise, sound insulation material is often laminated on body panels or interior trim panels. For a more effective noise reduction, the sound reduction properties of this laminated structure need to be estimated. We have developed a new calculate tool that can roughly calculate the sound absorption and insulation properties of laminate structure and handy for designers. In this report, the outline of this tool and an analysis example applied to floor mat are introduced.

Keywords: Automobile, acoustics, porous material, Transfer Matrix Method.

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Authors: Samad Nejatian, Vahideh Rezaie, Vahid Asadpour

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This paper presents a novel approach for the design of microwave circuits using Adaptive Network Fuzzy Inference Optimizer (ANFIO). The method takes advantage of direct synthesis of subsections of the amplifier using very fast and accurate ANFIO models based on exact simulations using ADS. A mapping from course space to fine space known as space mapping is also used. The proposed synthesis approach takes into account the noise and scattering parameters due to parasitic elements to achieve optimal results. The overall ANFIO system is capable of designing different LNAs at different noise and scattering criteria. This approach offers significantly reduced time in the design of microwave amplifiers within the validity range of the ANFIO system. The method has been proven to work efficiently for a 2.4GHz LNA example. The S21 of 10.1 dB and noise figure (NF) of 2.7 dB achieved for ANFIO while S21 of 9.05 dB and NF of 2.6 dB achieved for ANN.

Keywords: fuzzy system, low noise amplifier, microwaveamplifier, space mapping

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Authors: Muhanned Alfarras

Abstract:

The recent growth of using multimedia transmission over wireless communication systems, have challenges to protect the data from lost due to wireless channel effect. Images are corrupted due to the noise and fading when transmitted over wireless channel, in wireless channel the image is transmitted block by block, Due to severe fading, entire image blocks can be damaged. The aim of this paper comes out from need to enhance the digital images at the wireless receiver side. Proposed Boundary Interpolation (BI) Algorithm using wavelet, have been adapted here used to reconstruction the lost block in the image at the receiver depend on the correlation between the lost block and its neighbors. New Proposed technique by using Boundary Interpolation (BI) Algorithm using wavelet with Pixel interleaver has been implemented. Pixel interleaver work on distribute the pixel to new pixel position of original image before transmitting the image. The block lost through wireless channel is only effects individual pixel. The lost pixels at the receiver side can be recovered by using Boundary Interpolation (BI) Algorithm using wavelet. The results showed that the New proposed algorithm boundary interpolation (BI) using wavelet with pixel interleaver is better in term of MSE and PSNR.

Keywords: Image Transmission, Wavelet, Pixel Interleaver, Boundary Interpolation Algorithm

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Authors: Kelvin Rozier, Vladimir E. Bondarenko

Abstract:

It is known that an analog Hopfield neural network with time delay can generate the outputs which are similar to the human electroencephalogram. To gain deeper insights into the mechanisms of rhythm generation by the Hopfield neural networks and to study the effects of noise on their activities, we investigated the behaviors of the networks with symmetric and asymmetric interneuron connections. The neural network under the study consists of 10 identical neurons. For symmetric (fully connected) networks all interneuron connections aij = +1; the interneuron connections for asymmetric networks form an upper triangular matrix with non-zero entries aij = +1. The behavior of the network is described by 10 differential equations, which are solved numerically. The results of simulations demonstrate some remarkable properties of a Hopfield neural network, such as linear growth of outputs, dependence of synchronization properties on the connection type, huge amplification of oscillation by the external uniform noise, and the capability of the neural network to transform one type of noise to another.

Keywords: Chaos, Hopfield neural network, noise, synchronization

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Authors: Jihad S. Daba (Jean-Pierre Dubois), Philip Jreije

Abstract:

Speckled images arise when coherent microwave, optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted by speckle noise is complicated by the nature of the noise and is not as straightforward as detection and estimation in additive noise. In this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series of Laguerre weighted exponential functions, resulting in a doubly stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form. It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.

Keywords: Doubly stochastic filtered process, Poisson point process, segmentation, speckle, ultrasound

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Authors: Hemalan Nambier a/l Vijiyan, Agileswari K. Ramasamy, Au Mau Teng, Syed Khaleel Ahmed

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Small signal stability causes small perturbations in the generator that can cause instability in the power network. It is generally known that small signal stability are directly related to the generator and load properties. This paper examines the effects of generator input variations on power system oscillations for a small signal stability study. Eigenvaules and eigenvectors are used to examine the stability of the power system. The dynamic power system's mathematical model is constructed and thus calculated using load flow and small signal stability toolbox on MATLAB. The power system model is based on a 3-machine 9-bus system that was modified to suit this study. In this paper, Participation Factors are a means to gauge the effects of variation in generation with other parameters on the network are also incorporated.

Keywords: Eigen-analysis, generation modeling, participationfactor, small signal stability.

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Authors: Sun K. Yoo, Chung K. Lee

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Determination of attentional status is important because working performance and an unexpected accident is highly related with the attention. The autonomic nervous and the central nervous systems can reflect the changes in person’s attentional status. Reduced number of suitable pysiological parameters among autonomic and central nervous systems related signal parameters will be critical in optimum design of attentional devices. In this paper, we analyze the EEG (Electroencephalography) and HRV (Heart Rate Variability) signals to demonstrate the effective relation with brain signal and cardiovascular signal during event-related attention, which will be later used in selecting the minimum set of attentional parameters. Time and frequency domain parameters from HRV signal and frequency domain parameters from EEG signal are used as input to the optimum feature parameters selector.

Keywords: EEG, HRV, attentional status.

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Authors: Ching-Fen Jiang

Abstract:

Edge detection is usually the first step in medical image processing. However, the difficulty increases when a conventional kernel-based edge detector is applied to ultrasonic images with a textural pattern and speckle noise. We designed an adaptive diffusion filter to remove speckle noise while preserving the initial edges detected by using a Sobel edge detector. We also propose a genetic algorithm for edge selection to form complete boundaries of the detected entities. We designed two fitness functions to evaluate whether a criterion with a complex edge configuration can render a better result than a simple criterion such as the strength of gradient. The edges obtained by using a complex fitness function are thicker and more fragmented than those obtained by using a simple fitness function, suggesting that a complex edge selecting scheme is not necessary for good edge detection in medical ultrasonic images; instead, a proper noise-smoothing filter is the key.

Keywords: edge detection, ultrasonic images, speckle noise

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