Search results for: Detecting of Envelope Modulation on Noise.

Authors: Pei-Chun Lee, Sheng-Shih Wang, Pei-Hsuan Ku

Abstract:

Many existing amusement parks have been operated with assistance of a variety of information and communications technologies to design friendly and efficient service systems for tourists. However, these systems leave various levels of decisions to tourists to make by themselves. This incurs pressure on tourists and thereby bringing negative experience in their tour. This paper proposes a smart amusement park system to offer each tourist the GPS-based customized plan without tourists making decisions by themselves. The proposed system consists of the mobile app subsystem, the central subsystem, and the detecting/counting subsystem. The mobile app subsystem interacts with the central subsystem. The central subsystem performs the necessary computing and database management of the proposed system. The detecting/counting subsystem aims to detect and compute the number of visitors to an attraction. Experimental results show that the proposed system can not only work well, but also provide an innovative business operating model for owners of amusement parks.

Keywords: Amusement park, location-based service (LBS), mobile app, tourist service.

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Authors: Essam Al-Daoud

Abstract:

Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-to- Noise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify the effectiveness of the proposed classifier, seven well known classifiers are applied to four datasets. The experiments show that using the suggested classifier enhances the classification rates for all datasets.

Keywords: AdaBoost, Bayesian neural network, Signal-to-Noise, support vector machine, MCMC.

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Authors: Yunjung Lee, Pil Un Kim, Gyhyoun Lee, Jin Ho Cho, Myoung Nam Kim

Abstract:

Various sounds generated in the chest are included in auscultation sound. Adaptive Noise Canceller (ANC) is one of the useful techniques for biomedical signal. But the ANC is not suitable for auscultation sound. Because the ANC needs two input channels as a primary signal and a reference signals, but a stethoscope can provide just one input sound. Therefore, in this paper, it was proposed the Single Input ANC (SIANC) for suppression of breath sound in a cardiac auscultation sound. For the SIANC, it was proposed that the reference generation system which included Heart Sound Detector, Control and Reference Generator. By experiment and comparison, it was confirmed that the proposed SIANC was efficient for heart sound enhancement and it was independent of variations of a heartbeat.

Keywords: Adaptive noise canceller, Auscultation, Breath soundsuppression, Signal enhancement.

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Authors: Wang Tong, He Pi-lian

Abstract:

This paper sets forth the possibility and importance about applying Data Mining in Web logs mining and shows some problems in the conventional searching engines. Then it offers an improved algorithm based on the original AprioriAll algorithm which has been used in Web logs mining widely. The new algorithm adds the property of the User ID during the every step of producing the candidate set and every step of scanning the database by which to decide whether an item in the candidate set should be put into the large set which will be used to produce next candidate set. At the meantime, in order to reduce the number of the database scanning, the new algorithm, by using the property of the Apriori algorithm, limits the size of the candidate set in time whenever it is produced. Test results show the improved algorithm has a more lower complexity of time and space, better restrain noise and fit the capacity of memory.

Keywords: Candidate Sets Pruning, Data Mining, ImprovedAlgorithm, Noise Restrain, Web Log

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Authors: Suman Senapati, Goutam Saha

Abstract:

This work presents a fusion of Log Gabor Wavelet (LGW) and Maximum a Posteriori (MAP) estimator as a speech enhancement tool for acoustical background noise reduction. The probability density function (pdf) of the speech spectral amplitude is approximated by a Generalized Laplacian Distribution (GLD). Compared to earlier estimators the proposed method estimates the underlying statistical model more accurately by appropriately choosing the model parameters of GLD. Experimental results show that the proposed estimator yields a higher improvement in Segmental Signal-to-Noise Ratio (S-SNR) and lower Log-Spectral Distortion (LSD) in two different noisy environments compared to other estimators.

Keywords: Speech Enhancement, Generalized Laplacian Distribution, Log Gabor Wavelet, Bayesian MAP Marginal Estimator.

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Authors: E. Cesarini, M. Lorenzini, R. Cardarelli, S. Chao, E. Coccia, V. Fafone, Y. Minenkow, I. Nardecchia, I. M. Pinto, A. Rocchi, V. Sequino, C. Taranto

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Structural relaxation processes in optical coatings represent a fundamental limit to the sensitivity of gravitational waves detectors, MEMS, optical metrology and entangled state experiments. To face this problem, many research lines are now active, in particular the characterization of new materials and novel solutions to be employed as coatings in future gravitational wave detectors. Nano-layered coating deposition is among the most promising techniques. We report on the measurement of acoustic loss of nm-layered composites (Ti₂O/SiO₂), performed with the GeNS nodal suspension, compared with sputtered λ/4 thin films nowadays employed.

Keywords: Mechanical measurement, nanomaterials, optical coating, thermal noise.

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Authors: Watcharin Kaewapichai, Pakorn Kaewtrakulpong

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In this paper, a method to detect multiple ellipses is presented. The technique is efficient and robust against incomplete ellipses due to partial occlusion, noise or missing edges and outliers. It is an iterative technique that finds and removes the best ellipse until no reasonable ellipse is found. At each run, the best ellipse is extracted from randomly selected edge patches, its fitness calculated and compared to a fitness threshold. RANSAC algorithm is applied as a sampling process together with the Direct Least Square fitting of ellipses (DLS) as the fitting algorithm. In our experiment, the method performs very well and is robust against noise and spurious edges on both synthetic and real-world image data.

Keywords: Direct Least Square Fitting, Ellipse Detection, RANSAC

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Authors: Seo Young Kim, Toshimitsu Hamasaki

Abstract:

Microarrays have become the effective, broadly used tools in biological and medical research to address a wide range of problems, including classification of disease subtypes and tumors. Many statistical methods are available for analyzing and systematizing these complex data into meaningful information, and one of the main goals in analyzing gene expression data is the detection of samples or genes with similar expression patterns. In this paper, we express and compare the performance of several clustering methods based on data preprocessing including strategies of normalization or noise clearness. We also evaluate each of these clustering methods with validation measures for both simulated data and real gene expression data. Consequently, clustering methods which are common used in microarray data analysis are affected by normalization and degree of noise and clearness for datasets.

Keywords: Gene expression, clustering, data preprocessing.

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Authors: Dongwon Lee, Eon Kyeong Joo

Abstract:

In this paper, the performance of three types of serial concatenated convolutional codes (SCCC) is compared and analyzed in additive white Gaussian noise (AWGN) channel. In Type I, only the parity bits of outer encoder are passed to inner encoder. In Type II and Type III, both the information bits and the parity bits of outer encoder are transferred to inner encoder. As results of simulation, Type I shows the best bit error rate (BER) performance at low signal-to-noise ratio (SNR). On the other hand, Type III shows the best BER performance at high SNR in AWGN channel. The simulation results are analyzed using the distance spectrum.

Keywords: Distance spectrum, MAP algorithm, SCCC.

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Authors: Young-Hwan Song, Doo-Heon Kyun, Jong-Kuk Kim, Myung-Jin Bae

Abstract:

People have the habitual pitch level which is used when people say something generally. However this pitch should be changed irregularly in the presence of noise. So it is useful to estimate SNR of speech signal by pitch. In this paper, we obtain the energy of input speech signal and then we detect a stationary region on voiced speech. And we get the pitch period by NAMDF for the stationary region that is not varied pitch rapidly. After getting pitch, each frame is divided by pitch period and the likelihood of closed pitch is estimated. In this paper, we proposed new parameter, NLF, to estimate the SNR of received speech signal. The NLF is derived from the correlation of near pitch periods. The NLF is obtained for each stationary region in voiced speech. Finally we confirmed good performance of the estimation of the SNR of received input speech in the presence of noise.

Keywords: Likelihood, pitch, SNR, speech.

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Authors: R. Kanmaniraja, R. Freshipali, J. Abdullah, K. Niranjan, K. Balasubramani, V. R. Sanal Kumar

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The present environmental issues have made aircraft jet noise reduction a crucial problem in aero-acoustics research. Acoustic studies reveal that addition of chevrons to the nozzle reduces the sound pressure level reasonably with acceptable reduction in performance. In this paper comprehensive numerical studies on acoustic characteristics of different types of chevron nozzles have been carried out with non-reacting flows for the shape optimization of chevrons in supersonic nozzles for aerospace applications. The numerical studies have been carried out using a validated steady 3D density based, k-ε turbulence model. In this paper chevron with sharp edge, flat edge, round edge and U-type edge are selected for the jet acoustic characterization of supersonic nozzles. We observed that compared to the base model a case with round-shaped chevron nozzle could reduce 4.13% acoustic level with 0.6% thrust loss. We concluded that the prudent selection of the chevron shape will enable an appreciable reduction of the aircraft jet noise without compromising its overall performance. It is evident from the present numerical simulations that k-ε model can predict reasonably well the acoustic level of chevron supersonic nozzles for its shape optimization.

Keywords: Supersonic nozzle, Chevron, Acoustic level, Shape Optimization of Chevron Nozzles, Jet noise suppression.

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Authors: V. K. Ananthashayana, Jyothirmayi M.

Abstract:

This paper addresses the problem of source separation in images. We propose a FastICA algorithm employing a modified Gaussian contrast function for the Blind Source Separation. Experimental result shows that the proposed Modified Gaussian FastICA is effectively used for Blind Source Separation to obtain better quality images. In this paper, a comparative study has been made with other popular existing algorithms. The peak signal to noise ratio (PSNR) and improved signal to noise ratio (ISNR) are used as metrics for evaluating the quality of images. The ICA metric Amari error is also used to measure the quality of separation.

Keywords: Amari error, Blind Source Separation, Contrast function, Gaussian function, Independent Component Analysis.

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Authors: Moussa Yahia, Pascal Acco, Malek Benslama

Abstract:

Polynomial maps offer analytical properties used to obtain better performances in the scope of chaos synchronization under noisy channels. This paper presents a new method to simplify equations of the Exact Polynomial Kalman Filter (ExPKF) given in [1]. This faster algorithm is compared to other estimators showing that performances of all considered observers vanish rapidly with the channel noise making application of chaos synchronization intractable. Simulation of ExPKF shows that saturation drawn on the emitter to keep it stable impacts badly performances for low channel noise. Then we propose a particle filter that outperforms all other Kalman structured observers in the case of noisy channels.

Keywords: Chaos synchronization, Saturation, Fast ExPKF, Particlefilter, Polynomial maps.

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Authors: K. Nirmala Devi, V. Murali Bhaskaran

Abstract:

The exponential growth of social media arouses much attention on public opinion information. The online forums, blogs, micro blogs are proving to be extremely valuable resources and are having bulk volume of information. However, most of the social media data is unstructured and semi structured form. So that it is more difficult to decipher automatically. Therefore, it is very much essential to understand and analyze those data for making a right decision. The online forums hotspot detection is a promising research field in the web mining and it guides to motivate the user to take right decision in right time. The proposed system consist of a novel approach to detect a hotspot forum for any given time period. It uses aging theory to find the hot terms and E-K-means for detecting the hotspot forum. Experimental results demonstrate that the proposed approach outperforms k-means for detecting the hotspot forums with the improved accuracy.

Keywords: Hotspot forums, Micro blog, Blog, Sentiment Analysis, Opinion Mining, Social media, Twitter, Web mining.

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Authors: Madina Hamiane, May Hashim Ali

Abstract:

This paper presents the processing and analysis of ECG signals. The study is based on wavelet transform and uses exclusively the MATLAB environment. This study includes removing Baseline wander and further de-noising through wavelet transform and metrics such as signal-to noise ratio (SNR), Peak signal-to-noise ratio (PSNR) and the mean squared error (MSE) are used to assess the efficiency of the de-noising techniques. Feature extraction is subsequently performed whereby signal features such as heart rate, rise and fall levels are extracted and the QRS complex was detected which helped in classifying the ECG signal. The classification is the last step in the analysis of the ECG signals and it is shown that these are successfully classified as Normal rhythm or Abnormal rhythm.  The final result proved the adequacy of using wavelet transform for the analysis of ECG signals.

Keywords: ECG Signal, QRS detection, thresholding, wavelet decomposition, feature extraction.

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Authors: Hamid A. Jalab, Rabha W. Ibrahim

Abstract:

This paper introduces an image denoising algorithm based on generalized Srivastava-Owa fractional differential operator for removing Gaussian noise in digital images. The structures of nxn fractional masks are constructed by this algorithm. Experiments show that, the capability of the denoising algorithm by fractional differential-based approach appears efficient to smooth the Gaussian noisy images for different noisy levels. The denoising performance is measured by using peak signal to noise ratio (PSNR) for the denoising images. The results showed an improved performance (higher PSNR values) when compared with standard Gaussian smoothing filter.

Keywords: Fractional calculus, fractional differential operator, fractional mask, fractional filter.

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Authors: Hassan Yousif Ahmed, Ibrahima Faye, N.M.Saad, S.A. Aljined

Abstract:

Multi-user interference (MUI) is the main reason of system deterioration in the Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system. MUI increases with the number of simultaneous users, resulting into higher probability bit rate and limits the maximum number of simultaneous users. On the other hand, Phase induced intensity noise (PIIN) problem which is originated from spontaneous emission of broad band source from MUI severely limits the system performance should be addressed as well. Since the MUI is caused by the interference of simultaneous users, reducing the MUI value as small as possible is desirable. In this paper, an extensive study for the system performance specified by MUI and PIIN reducing is examined. Vectors Combinatorial (VC) codes families are adopted as a signature sequence for the performance analysis and a comparison with reported codes is performed. The results show that, when the received power increases, the PIIN noise for all the codes increases linearly. The results also show that the effect of PIIN can be minimized by increasing the code weight leads to preserve adequate signal to noise ratio over bit error probability. A comparison study between the proposed code and the existing codes such as Modified frequency hopping (MFH), Modified Quadratic- Congruence (MQC) has been carried out.

Keywords: FBG, MUI, PIIN, SAC-OCDMA, VCC.

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Authors: Richard Grünes, Karel Roubik

Abstract:

The article deals with technical support of intracranial single unit activity measurement. The parameters of the whole measuring set were tested in order to assure the optimal conditions of extracellular single-unit recording. Metal microelectrodes for measuring the single-unit were tested during animal experiments. From signals recorded during these experiments, requirements for the measuring set parameters were defined. The impedance parameters of the metal microelectrodes were measured. The frequency-gain and autonomous noise properties of preamplifier and amplifier were verified. The measurement and the description of the extracellular single unit activity could help in prognoses of brain tissue damage recovery.

Keywords: Measuring set, metal microelectrodes, single-unit, noise, impedance parameters, gain characteristics.

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Authors: G. Renuka Devi

Abstract:

This paper analyzes the experimental investigation of indirect field oriented control of Field Programmable Gate Array (FPGA) based five-phase induction motor drive. A detailed d-q modeling and Space Vector Pulse Width Modulation (SVPWM) technique of 5-phase drive is elaborated in this paper. In the proposed work, the prototype model of 1 hp 5-phase Voltage Source Inverter (VSI) fed drive is implemented in hardware. SVPWM pulses are generated in FPGA platform through Very High Speed Integrated Circuit Hardware Description Language (VHDL) coding. The experimental results are observed under different loading conditions and compared with simulation results to validate the simulation model.

Keywords: Five-phase induction motor drive, field programmable gate array, indirect field oriented control, multi-phase, space vector pulse width modulation, voltage source inverter, very high speed integrated circuit hardware description language.

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Authors: Ehsan Hassankhan, Davood A. Khaburi

Abstract:

Direct Torque Control is a control technique in AC drive systems to obtain high performance torque control. The conventional DTC drive contains a pair of hysteresis comparators. DTC drives utilizing hysteresis comparators suffer from high torque ripple and variable switching frequency. The most common solution to those problems is to use the space vector depends on the reference torque and flux. In this Paper The space vector modulation technique (SVPWM) is applied to 2 level inverter control in the proposed DTC-based induction motor drive system, thereby dramatically reducing the torque ripple. Then the controller based on space vector modulation is designed to be applied in the control of Induction Motor (IM) with a three-level Inverter. This type of Inverter has several advantages over the standard two-level VSI, such as a greater number of levels in the output voltage waveforms, Lower dV/dt, less harmonic distortion in voltage and current waveforms and lower switching frequencies. This paper proposes a general SVPWM algorithm for three-level based on standard two-level SVPWM. The proposed scheme is described clearly and simulation results are reported to demonstrate its effectiveness. The entire control scheme is implemented with Matlab/Simulink.

Keywords: Direct torque control, space vector Pulsewidthmodulation(SVPWM), neutral point clamped(NPC), two-levelinverter.

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Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: Biometrics, identity verification, genetic data, k-nearest neighbor.

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Authors: Alireza Mallahzadeh, Hamid Dehghani, Iman Elyasi

Abstract:

A new method, based on the normal shrink and modified version of Katssagelous and Lay, is proposed for multiscale blind image restoration. The method deals with the noise and blur in the images. It is shown that the normal shrink gives the highest S/N (signal to noise ratio) for image denoising process. The multiscale blind image restoration is divided in two sections. The first part of this paper proposes normal shrink for image denoising and the second part of paper proposes modified version of katssagelous and Lay for blur estimation and the combination of both methods to reach a multiscale blind image restoration.

Keywords: Multiscale blind image restoration, image denoising, blur estimation.

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Authors: Asaad H. Ismail, Mohamad S. Jaafar

Abstract:

This study aims to assess the environmental hazards from radon exhalation rate in the soil samples in selected locations in Iraqi Kurdistan, using passive (CR-39NTDs) and active (RAD7) detecting method. Radon concentration, effective radium content and radon exhalation rate were estimated in soil samples that collected at the depth level of 30 cm inside 124 houses. The results show that the emanation rate for radon gas was variation from location to other, depending on the geological formation. Most health risks come from emanation of radon and its daughter due to its contribution for indoor radon, so the results showed that there is a linear relationship between the ratio of soil and indoor radon concentration (CSoil Rn222/ Cindoor Rn222) and the effective radium content in soil samples. The results show that radon concentration has high and low values in Hajyawa city and Er. Tyrawa Qr, respectively. A comparison between our results with that mentioned in international reports was done.

Keywords: Radon, CR-39NTDs, RAD7, Soil, Iraqi Kurdistan.

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Authors: M. Moslehpour, S. Khorsandi

Abstract:

As transition to widespread use of IPv6 addresses has gained momentum, it has been shown to be vulnerable to certain security attacks such as those targeting Neighbor Discovery Protocol (NDP) which provides the address resolution functionality in IPv6. To protect this protocol, Secure Neighbor Discovery (SEND) is introduced. This protocol uses Cryptographically Generated Address (CGA) and asymmetric cryptography as a defense against threats on integrity and identity of NDP. Although SEND protects NDP against attacks, it is computationally intensive due to Hash2 condition in CGA. To improve the CGA computation speed, we parallelized CGA generation process and used the available resources in a trusted network. Furthermore, we focused on the influence of the existence of malicious nodes on the overall load of un-malicious ones in the network. According to the evaluation results, malicious nodes have adverse impacts on the average CGA generation time and on the average number of tries. We utilized a Trust Management that is capable of detecting and isolating the malicious node to remove possible incentives for malicious behavior. We have demonstrated the effectiveness of the Trust Management System in detecting the malicious nodes and hence improving the overall system performance.

Keywords: NDP, SEND, CGA, modifier, malicious node.

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Authors: Wahiba Mohguen, Raïs El’hadi Bekka

Abstract:

This paper presents a denoising method called EMD-Custom that was based on Empirical Mode Decomposition (EMD) and the modified Customized Thresholding Function (Custom) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs got threshold by applying the presented thresholding function to suppress noise and to improve the signal to noise ratio (SNR). The method was tested on simulated data and real ECG signal, and the results were compared to the EMD-Based signal denoising methods using the soft and hard thresholding. The results showed the superior performance of the proposed EMD-Custom denoising over the traditional approach. The performances were evaluated in terms of SNR in dB, and Mean Square Error (MSE).

Keywords: Customized thresholding, ECG signal, EMD, hard thresholding, Soft-thresholding.

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Authors: Sunitha S. L., V. Udayashankara

Abstract:

Hearing impairment is the number one chronic disability affecting many people in the world. Background noise is particularly damaging to speech intelligibility for people with hearing loss especially for sensorineural loss patients. Several investigations on speech intelligibility have demonstrated sensorineural loss patients need 5-15 dB higher SNR than the normal hearing subjects. This paper describes Discrete Hartley Transform Power Normalized Least Mean Square algorithm (DHT-LMS) to improve the SNR and to reduce the convergence rate of the Least Means Square (LMS) for sensorineural loss patients. The DHT transforms n real numbers to n real numbers, and has the convenient property of being its own inverse. It can be effectively used for noise cancellation with less convergence time. The simulated result shows the superior characteristics by improving the SNR at least 9 dB for input SNR with zero dB and faster convergence rate (eigenvalue ratio 12) compare to time domain method and DFT-LMS.

Keywords: Hearing Impairment, DHT-LMS, Convergence rate, SNR improvement.

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Authors: K. A. Navas, S. Archana Thampy, M. Sasikumar

Abstract:

Medical image data hiding has strict constrains such as high imperceptibility, high capacity and high robustness. Achieving these three requirements simultaneously is highly cumbersome. Some works have been reported in the literature on data hiding, watermarking and stegnography which are suitable for telemedicine applications. None is reliable in all aspects. Electronic Patient Report (EPR) data hiding for telemedicine demand it blind and reversible. This paper proposes a novel approach to blind reversible data hiding based on integer wavelet transform. Experimental results shows that this scheme outperforms the prior arts in terms of zero BER (Bit Error Rate), higher PSNR (Peak Signal to Noise Ratio), and large EPR data embedding capacity with WPSNR (Weighted Peak Signal to Noise Ratio) around 53 dB, compared with the existing reversible data hiding schemes.

Keywords: Biomedical imaging, Data security, Datacommunication, Teleconferencing.

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Authors: S. P. Kozaitis, R. L. Kriner

Abstract:

The information revealed by derivatives can help to better characterize digital near-end crosstalk signatures with the ultimate goal of identifying the specific aggressor signal. Unfortunately, derivatives tend to be very sensitive to even low levels of noise. In this work we approximated the derivatives of both quiet and noisy digital signals using a wavelet-based technique. The results are presented for Gaussian digital edges, IBIS Model digital edges, and digital edges in oscilloscope data captured from an actual printed circuit board. Tradeoffs between accuracy and noise immunity are presented. The results show that the wavelet technique can produce first derivative approximations that are accurate to within 5% or better, even under noisy conditions. The wavelet technique can be used to calculate the derivative of a digital signal edge when conventional methods fail.

Keywords: digital signals, electronics, IBIS model, printedcircuit board, wavelets

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Authors: Jason Chien-Hsun Tseng

Abstract:

This paper evaluates performances of an adaptive noise cancelling (ANC) based target detection algorithm on a set of real test data supported by the Defense Evaluation Research Agency (DERA UK) for multi-target wideband active sonar echolocation system. The hybrid algorithm proposed is a combination of an adaptive ANC neuro-fuzzy scheme in the first instance and followed by an iterative optimum target motion estimation (TME) scheme. The neuro-fuzzy scheme is based on the adaptive noise cancelling concept with the core processor of ANFIS (adaptive neuro-fuzzy inference system) to provide an effective fine tuned signal. The resultant output is then sent as an input to the optimum TME scheme composed of twogauge trimmed-mean (TM) levelization, discrete wavelet denoising (WDeN), and optimal continuous wavelet transform (CWT) for further denosing and targets identification. Its aim is to recover the contact signals in an effective and efficient manner and then determine the Doppler motion (radial range, velocity and acceleration) at very low signal-to-noise ratio (SNR). Quantitative results have shown that the hybrid algorithm have excellent performance in predicting targets- Doppler motion within various target strength with the maximum false detection of 1.5%.

Keywords: Wideband Active Sonar Echolocation, ANC Neuro-Fuzzy, Wavelet Denoise, CWT, Hybrid Algorithm.

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

Abstract:

The aim of this work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. With our research and based on a feature selection in different phases, we are trying to design a neural network system with an optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each region of interest (ROI), 6 distinct sets of texture features are extracted such as: first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. When analyzing more phases, we show that the injection of liquid cause changes to the high relevant features in each region. Our results demonstrate that for detecting HCC tumor phase 3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between pathology and healthy classes, according to our method, relates to first order histogram parameters with accuracy of 85% in phase 1, 95% in phase 2, and 95% in phase 3.

Keywords: Feature selection, Multi-phasic liver images, Neural network, Texture analysis.

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