Search results for: Noise Variance
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1245

Search results for: Noise Variance

525 Digital Image Encryption Scheme using Chaotic Sequences with a Nonlinear Function

Authors: H. Ogras, M. Turk

Abstract:

In this study, a system of encryption based on chaotic sequences is described. The system is used for encrypting digital image data for the purpose of secure image transmission. An image secure communication scheme based on Logistic map chaotic sequences with a nonlinear function is proposed in this paper. Encryption and decryption keys are obtained by one-dimensional Logistic map that generates secret key for the input of the nonlinear function. Receiver can recover the information using the received signal and identical key sequences through the inverse system technique. The results of computer simulations indicate that the transmitted source image can be correctly and reliably recovered by using proposed scheme even under the noisy channel. The performance of the system will be discussed through evaluating the quality of recovered image with and without channel noise.

Keywords: Digital image, Image encryption, Secure communication

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524 Mechanical Properties of Pea Pods (Pisium sativum Var. Shamshiri)

Authors: M. Azadbakht, N. Tajari, R. Alimoradzade

Abstract:

Knowing pea pods mechanical resistance against dynamic forces are important for design of combine harvester. In pea combine harvesters, threshing is accomplished by two mechanical actions of impact and friction forces. In this research, the effects of initial moisture content and needed impact and friction energy on threshing of pea pods were studied. An impact device was built based on pendulum mechanism. The experiments were done at three initial moisture content levels of 12.1, 23.5 and 39.5 (%w.b.) for both impact and friction methods. Three energy levels of 0.088, 0.126 and 0.202 J were used for impact method and for friction method three energy levels of 0.784, 0.930 and 1.351 J. The threshing percentage was measured in each method. By using a frictional device, kinetic friction coefficients at above moisture contents were measured 0.257, 0.303 and 0.336, respectively. The results of variance analysis of the two methods showed that moisture content and energy have significant effects on the threshing percentage.

Keywords: Pea pod, Energy, Friction, Impact, Initial moisture content, Threshing.

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523 Sorption of Congo Red from Aqueous Solution by Surfactant-Modified Bentonite: Kinetic and Factorial Design Study

Authors: B. Guezzen, M. A. Didi, B. Medjahed

Abstract:

An organoclay (HDTMA-B) was prepared from sodium bentonite (Na-B). The starting material was modified using the hexadecyltrimethylammonium ion (HDTMA+) in the amounts corresponding to 100 % of the CEC value. Batch experiments were carried out in order to model and optimize the sorption of Congo red dye from aqueous solution. The pseudo-first order and pseudo-second order kinetic models have been developed to predict the rate constant and the sorption capacity at equilibrium with the effect of temperature, the solid/solution ratio and the initial dye concentration. The equilibrium time was reached within 60 min. At room temperature (20 °C), optimum dye sorption of 49.4 mg/g (98.9%) was achieved at pH 6.6, sorbent dosage of 1g/L and initial dye concentration of 50 mg/L, using surfactant modified bentonite. The optimization of adsorption parameters mentioned above on dye removal was carried out using Box-Behnken design. The sorption parameters were analyzed statistically by means of variance analysis by using the Statgraphics Centurion XVI software.

Keywords: Adsorption, dye, factorial design, kinetic, organo-bentonite.

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522 Investigation of Interference Conditions in BFWA System Applying Adaptive TDD

Authors: Gábor Szládek, Balázs Héder, János Bitó

Abstract:

In a BFWA (Broadband Fixed Wireless Access Network) the evolved SINR (Signal to Interference plus Noise Ratio) is relevant influenced by the applied duplex method. The TDD (Time Division Duplex), especially adaptive TDD method has some advantage contrary to FDD (Frequency Division Duplex), for example the spectrum efficiency and flexibility. However these methods are suffering several new interference situations that can-t occur in a FDD system. This leads to reduced SINR in the covered area what could cause some connection outages. Therefore, countermeasure techniques against interference are necessary to apply in TDD systems. Synchronization is one way to handling the interference. In this paper the TDD systems – applying different system synchronization degree - will be compared by the evolved SINR at different locations of the BFWA service area and the percentage of the covered area by the system.

Keywords: Adaptive TDD, BFWA networks, duplex methods, intra system interferences.

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521 Target Signal Detection Using MUSIC Spectrum in Noise Environment

Authors: Sangjun Park, Sangbae Jeong, Moonsung Han, Minsoo hahn

Abstract:

In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. The algorithm detects the DOAs of multiple sources using the inverse of the eigenvalue-weighted eigen spectra. To apply the algorithm to target signal detection for GSC-based beamforming, we utilize its spectral response for the target DOA in noisy conditions. For evaluation of the algorithm, the performance of the proposed target signal detection method is compared with that of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics(ROC) curves.

Keywords: Beamforming, direction of arrival, multiple signal classification, target signal detection.

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520 Investigations on the Influence of Process Parameters on the Sliding Wear Behavior of Components Produced by Direct Metal Laser Sintering (DMLS)

Authors: C. D. Naiju, K. Annamalai, Siva Prasad Darla, Y. Murali Krishna

Abstract:

This work presents the results of a study carried out to determine the sliding wear behavior and its effect on the process parameters of components manufactured by direct metal laser sintering (DMLS). A standard procedure and specimen had been used in the present study to find the wear behavior. Using Taguchi-s experimental technique, an orthogonal array of modified L8 had been developed. Sliding wear testing using pin-on-disk machine was carried out and analysis of variance (ANOVA) technique was used to investigate the effect of process parameters and to identify the main process parameter that influences the properties of wear behavior on the DMLS components. It has been found that part orientation, one of the selected process parameter had more influence on wear as compared to other selected process parameters.

Keywords: ANOVA, DMLS, Taguchi, Wear.

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519 VaR Forecasting in Times of Increased Volatility

Authors: Ivo Jánský, Milan Rippel

Abstract:

The paper evaluates several hundred one-day-ahead VaR forecasting models in the time period between the years 2004 and 2009 on data from six world stock indices - DJI, GSPC, IXIC, FTSE, GDAXI and N225. The models model mean using the ARMA processes with up to two lags and variance with one of GARCH, EGARCH or TARCH processes with up to two lags. The models are estimated on the data from the in-sample period and their forecasting accuracy is evaluated on the out-of-sample data, which are more volatile. The main aim of the paper is to test whether a model estimated on data with lower volatility can be used in periods with higher volatility. The evaluation is based on the conditional coverage test and is performed on each stock index separately. The primary result of the paper is that the volatility is best modelled using a GARCH process and that an ARMA process pattern cannot be found in analyzed time series.

Keywords: VaR, risk analysis, conditional volatility, garch, egarch, tarch, moving average process, autoregressive process

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518 Immobilization of Lipase Enzyme by Low Cost Material: A Statistical Approach

Authors: Md. Z. Alam, Devi R. Asih, Md. N. Salleh

Abstract:

Immobilization of lipase enzyme produced from palm oil mill effluent (POME) by the activated carbon (AC) among the low cost support materials was optimized. The results indicated that immobilization of 94% was achieved by AC as the most suitable support material. A sequential optimization strategy based on a statistical experimental design, including one-factor-at-a-time (OFAT) method was used to determine the equilibrium time. Three components influencing lipase immobilization were optimized by the response surface methodology (RSM) based on the face-centered central composite design (FCCCD). On the statistical analysis of the results, the optimum enzyme concentration loading, agitation rate and carbon active dosage were found to be 30 U/ml, 300 rpm and 8 g/L respectively, with a maximum immobilization activity of 3732.9 U/g-AC after 2 hrs of immobilization. Analysis of variance (ANOVA) showed a high regression coefficient (R2) of 0.999, which indicated a satisfactory fit of the model with the experimental data. The parameters were statistically significant at p<0.05.

Keywords: Activated carbon, adsorption, immobilization, POME based lipase.

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517 Quality Control of Automotive Gearbox Based On Vibration Signal Analysis

Authors: Nilson Barbieri, Bruno Matos Martins, Gabriel de Sant'Anna Vitor Barbieri

Abstract:

In more complex systems, such as automotive gearbox, a rigorous treatment of the data is necessary because there are several moving parts (gears, bearings, shafts, etc.), and in this way, there are several possible sources of errors and also noise. The basic objective of this work is the detection of damage in automotive gearbox. The detection methods used are the wavelet method, the bispectrum; advanced filtering techniques (selective filtering) of vibrational signals and mathematical morphology. Gearbox vibration tests were performed (gearboxes in good condition and with defects) of a production line of a large vehicle assembler. The vibration signals are obtained using five accelerometers in different positions of the sample. The results obtained using the kurtosis, bispectrum, wavelet and mathematical morphology showed that it is possible to identify the existence of defects in automotive gearboxes.

Keywords: Automotive gearbox, mathematical morphology, wavelet, bispectrum.

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516 A New Method for Contour Approximation Using Basic Ramer Idea

Authors: Ali Abdrhman Ukasha

Abstract:

This paper presented two new efficient algorithms for contour approximation. The proposed algorithm is compared with Ramer (good quality), Triangle (faster) and Trapezoid (fastest) in this work; which are briefly described. Cartesian co-ordinates of an input contour are processed in such a manner that finally contours is presented by a set of selected vertices of the edge of the contour. In the paper the main idea of the analyzed procedures for contour compression is performed. For comparison, the mean square error and signal-to-noise ratio criterions are used. Computational time of analyzed methods is estimated depending on a number of numerical operations. Experimental results are obtained both in terms of image quality, compression ratios, and speed. The main advantages of the analyzed algorithm is small numbers of the arithmetic operations compared to the existing algorithms.

Keywords: Polygonal approximation, Ramer, Triangle and Trapezoid methods.

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515 Speech Enhancement of Vowels Based on Pitch and Formant Frequency

Authors: R. Rishma Rodrigo, R. Radhika, M. Vanitha Lakshmi

Abstract:

Numerous signal processing based speech enhancement systems have been proposed to improve intelligibility in the presence of noise. Traditionally, studies of neural vowel encoding have focused on the representation of formants (peaks in vowel spectra) in the discharge patterns of the population of auditory-nerve (AN) fibers. A method is presented for recording high-frequency speech components into a low-frequency region, to increase audibility for hearing loss listeners. The purpose of the paper is to enhance the formant of the speech based on the Kaiser window. The pitch and formant of the signal is based on the auto correlation, zero crossing and magnitude difference function. The formant enhancement stage aims to restore the representation of formants at the level of the midbrain. A MATLAB software’s are used for the implementation of the system with low complexity is developed.

Keywords: Formant estimation, formant enhancement, pitch detection, speech analysis.

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514 Quantifying Freeway Capacity Reductions by Rainfall Intensities Based on Stochastic Nature of Flow Breakdown

Authors: Hoyoung Lee, Dong-Kyu Kim, Seung-Young Kho, R. Eddie Wilson

Abstract:

This study quantifies a decrement in freeway capacity during rainfall. Traffic and rainfall data were gathered from Highway Agencies and Wunderground weather service. Three inter-urban freeway sections and its nearest weather stations were selected as experimental sites. Capacity analysis found reductions of maximum and mean pre-breakdown flow rates due to rainfall. The Kruskal-Wallis test also provided some evidence to suggest that the variance in the pre-breakdown flow rate is statistically insignificant. Potential application of this study lies in the operation of real time traffic management schemes such as Variable Speed Limits (VSL), Hard Shoulder Running (HSR), and Ramp Metering System (RMS), where speed or flow limits could be set based on a number of factors, including rainfall events and their intensities.

Keywords: Capacity randomness, flow breakdown, freeway capacity, rainfall.

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513 Mechanisms in Regulating Language Practices in Electronics Engineering: A Program Plan for Outcomes-Based Education

Authors: Analiza Acuña-Villacorte

Abstract:

The underlying principle behind the harmonization in international education does not solely aim for the comparability but also the compatibility of outputs produced. The international standard in the different professions particularly in engineering defines the required graduate attributes to attain suitable qualifications and recognitions. This study described the language practices of the Electronics Engineering students of Bulacan State University, Philippines who will be deployed for their internship program. The purpose of the study was achieved by determining the language proficiency of the students in terms of speaking, listening, reading, and writing, and checking the adherence of the University to the commitment of intensifying community building for the Association of Southeast Asian Nation Vision 2020. The analysis of variance of the variables defined the significance between the causal variables and dependent variables. Thus, this study identified the mechanism that would regulate language practices in the Electronics Engineering program.

Keywords: Communicative competence, descriptive design, language practices, mechanisms, outcomes-based education.

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512 Multiwavelet and Biological Signal Processing

Authors: Morteza Moazami-Goudarzi, Ali Taheri, Mohammad Pooyan, Reza Mahboobi

Abstract:

In this paper we are to find the optimum multiwavelet for compression of electrocardiogram (ECG) signals and then, selecting it for using with SPIHT codec. At present, it is not well known which multiwavelet is the best choice for optimum compression of ECG. In this work, we examine different multiwavelets on 24 sets of ECG data with entirely different characteristics, selected from MIT-BIH database. For assessing the functionality of the different multiwavelets in compressing ECG signals, in addition to known factors such as Compression Ratio (CR), Percent Root Difference (PRD), Distortion (D), Root Mean Square Error (RMSE) in compression literature, we also employed the Cross Correlation (CC) criterion for studying the morphological relations between the reconstructed and the original ECG signal and Signal to reconstruction Noise Ratio (SNR). The simulation results show that the Cardinal Balanced Multiwavelet (cardbal2) by the means of identity (Id) prefiltering method to be the best effective transformation. After finding the most efficient multiwavelet, we apply SPIHT coding algorithm on the transformed signal by this multiwavelet.

Keywords: ECG compression, Prefiltering, Cardinal Balanced Multiwavelet.

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511 Development of Electric Performance Testing System for Ceramic Chips using PZT Actuator

Authors: Jin-Ho Bae, Yong-Tae Kim, S K Deb Nath, Seo-Ik Kang, Sung-Gaun Kim

Abstract:

Reno-pin contact test is a method that is controlled by DC motor used to characterize electronic chips. This method is used in electronic and telecommunication devices. A new electric performance testing system is developed in which the testing method is controlled by using Piezoelectric Transducer (PZT) instead of DC motor which reduces vibration and noise. The vertical displacement of the Reno-pin is very short in the Reno-pin contact testing system. Now using a flexible guide in the new Reno-pin contact system, the vertical movement of the Reno-pin is increased many times of the existing Reno-pin contact testing method using DC motor. Using the present electric performance testing system with a flexible hinge and PZT instead of DC motor, manufacturing of electronic chips are able to characterize chips with low cost and high speed.

Keywords: PZT Actuator, Chip test, Mechanical amplifier

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510 Real-time Tracking in Image Sequences based-on Parameters Updating with Temporal and Spatial Neighborhoods Mixture Gaussian Model

Authors: Hu Haibo, Zhao Hong

Abstract:

Gaussian mixture background model is widely used in moving target detection of the image sequences. However, traditional Gaussian mixture background model usually considers the time continuity of the pixels, and establishes background through statistical distribution of pixels without taking into account the pixels- spatial similarity, which will cause noise, imperfection and other problems. This paper proposes a new Gaussian mixture modeling approach, which combines the color and gradient of the spatial information, and integrates the spatial information of the pixel sequences to establish Gaussian mixture background. The experimental results show that the movement background can be extracted accurately and efficiently, and the algorithm is more robust, and can work in real time in tracking applications.

Keywords: Gaussian mixture model, real-time tracking, sequence image, gradient.

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509 Static Single Point Positioning Using The Extended Kalman Filter

Authors: I. Sarras, G. Gerakios, A. Diamantis, A. I. Dounis, G. P. Syrcos

Abstract:

Global Positioning System (GPS) technology is widely used today in the areas of geodesy and topography as well as in aeronautics mainly for military purposes. Due to the military usage of GPS, full access and use of this technology is being denied to the civilian user who must then work with a less accurate version. In this paper we focus on the estimation of the receiver coordinates ( X, Y, Z ) and its clock bias ( δtr ) of a fixed point based on pseudorange measurements of a single GPS receiver. Utilizing the instantaneous coordinates of just 4 satellites and their clock offsets, by taking into account the atmospheric delays, we are able to derive a set of pseudorange equations. The estimation of the four unknowns ( X, Y, Z , δtr ) is achieved by introducing an extended Kalman filter that processes, off-line, all the data collected from the receiver. Higher performance of position accuracy is attained by appropriate tuning of the filter noise parameters and by including other forms of biases.

Keywords: Extended Kalman filter, GPS, Pseudorange

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508 Face Recognition Using Morphological Shared-weight Neural Networks

Authors: Hossein Sahoolizadeh, Mahdi Rahimi, Hamid Dehghani

Abstract:

We introduce an algorithm based on the morphological shared-weight neural network. Being nonlinear and translation-invariant, the MSNN can be used to create better generalization during face recognition. Feature extraction is performed on grayscale images using hit-miss transforms that are independent of gray-level shifts. The output is then learned by interacting with the classification process. The feature extraction and classification networks are trained together, allowing the MSNN to simultaneously learn feature extraction and classification for a face. For evaluation, we test for robustness under variations in gray levels and noise while varying the network-s configuration to optimize recognition efficiency and processing time. Results show that the MSNN performs better for grayscale image pattern classification than ordinary neural networks.

Keywords: Face recognition, Neural Networks, Multi-layer Perceptron, masking.

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507 Impact of the Decoder Connection Schemes on Iterative Decoding of GPCB Codes

Authors: Fouad Ayoub, Mohammed Lahmer, Mostafa Belkasmi, El Houssine Bouyakhf

Abstract:

In this paper we present a study of the impact of connection schemes on the performance of iterative decoding of Generalized Parallel Concatenated block (GPCB) constructed from one step majority logic decodable (OSMLD) codes and we propose a new connection scheme for decoding them. All iterative decoding connection schemes use a soft-input soft-output threshold decoding algorithm as a component decoder. Numerical result for GPCB codes transmitted over Additive White Gaussian Noise (AWGN) channel are provided. It will show that the proposed scheme is better than Hagenauer-s scheme and Lucas-s scheme [1] and slightly better than the Pyndiah-s scheme.

Keywords: Generalized parallel concatenated block codes, OSMLD codes, threshold decoding, iterative decoding scheme, and performance.

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506 An LMI Approach of Robust H∞ Fuzzy State-Feedback Controller Design for HIV/AIDS Infection System with Dual Drug Dosages

Authors: Wudhichai Assawinchaichote

Abstract:

This paper examines the problem of designing robust H controllers for for HIV/AIDS infection system with dual drug dosages described by a Takagi-Sugeno (S) fuzzy model. Based on a linear matrix inequality (LMI) approach, we develop an H controller which guarantees the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value for the system. A sufficient condition of the controller for this system is given in term of Linear Matrix Inequalities (LMIs). The effectiveness of the proposed controller design methodology is finally demonstrated through simulation results. It has been shown that the anti-HIV vaccines are critically important in reducing the infected cells.

Keywords: H∞ Fuzzy control; Takagi-Sugeno (TS) fuzzy model; Linear Matrix Inequalities (LMIs); HIV/AIDS infection system

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505 Smartphones for In-home Diagnostics in Telemedicine

Authors: Nálevka Petr

Abstract:

Many contemporary telemedical applications rely on regular consultations over the phone or video conferencing which consumes valuable resources such as the time of the doctors. Some applications or treatments allow automated diagnostics on the patient side which only notifies the doctors in case a significant worsening of patient’s condition is measured. Such programs can save valuable resources but an important implementation issue is how to ensure effective and cheap diagnostics on the patient side. First, specific diagnostic devices on patient side are expensive and second, they need to be user-˜friendly to encourage patient’s cooperation and reduce errors in usage which may cause noise in diagnostic data. This article proposes the use of modern smartphones and various build-in or attachable sensors as universal diagnostic devices applicable in a wider range of telemedical programs and demonstrates their application on a case-study – a program for schizophrenic relapse prevention.

Keywords: Smartphones, Actigraphy, Telemedicine, In-home Diagnostics

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504 Robust and Transparent Spread Spectrum Audio Watermarking

Authors: Ali Akbar Attari, Ali Asghar Beheshti Shirazi

Abstract:

In this paper, we propose a blind and robust audio watermarking scheme based on spread spectrum in Discrete Wavelet Transform (DWT) domain. Watermarks are embedded in the low-frequency coefficients, which is less audible. The key idea is dividing the audio signal into small frames, and magnitude of the 6th level of DWT approximation coefficients is modifying based upon the Direct Sequence Spread Spectrum (DSSS) technique. Also, the psychoacoustic model for enhancing in imperceptibility, as well as Savitsky-Golay filter for increasing accuracy in extraction, is used. The experimental results illustrate high robustness against most common attacks, i.e. Gaussian noise addition, Low pass filter, Resampling, Requantizing, MP3 compression, without significant perceptual distortion (ODG is higher than -1). The proposed scheme has about 83 bps data payload.

Keywords: Audio watermarking, spread spectrum, discrete wavelet transform, psychoacoustic, Savitsky-Golay filter.

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503 Classification of Initial Stripe Height Patterns using Radial Basis Function Neural Network for Proportional Gain Prediction

Authors: Prasit Wonglersak, Prakarnkiat Youngkong, Ittipon Cheowanish

Abstract:

This paper aims to improve a fine lapping process of hard disk drive (HDD) lapping machines by removing materials from each slider together with controlling the strip height (SH) variation to minimum value. The standard deviation is the key parameter to evaluate the strip height variation, hence it is minimized. In this paper, a design of experiment (DOE) with factorial analysis by twoway analysis of variance (ANOVA) is adopted to obtain a statistically information. The statistics results reveal that initial stripe height patterns affect the final SH variation. Therefore, initial SH classification using a radial basis function neural network is implemented to achieve the proportional gain prediction.

Keywords: Stripe height variation, Two-way analysis ofvariance (ANOVA), Radial basis function neural network, Proportional gain prediction.

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502 Fault Detection and Identification of COSMED K4b2 Based On PCA and Neural Network

Authors: Jing Zhou, Steven Su, Aihuang Guo

Abstract:

COSMED K4b2 is a portable electrical device designed to test pulmonary functions. It is ideal for many applications that need the measurement of the cardio-respiratory response either in the field or in the lab is capable with the capability to delivery real time data to a sink node or a PC base station with storing data in the memory at the same time. But the actual sensor outputs and data received may contain some errors, such as impulsive noise which can be related to sensors, low batteries, environment or disturbance in data acquisition process. These abnormal outputs might cause misinterpretations of exercise or living activities to persons being monitored. In our paper we propose an effective and feasible method to detect and identify errors in applications by principal component analysis (PCA) and a back propagation (BP) neural network.

Keywords: BP Neural Network, Exercising Testing, Fault Detection and Identification, Principal Component Analysis.

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501 Two Stage Control Method Using a Disturbance Observer and a Kalman Filter

Authors: Hiromitsu Ogawa, Manato Ono, Naohiro Ban, Yoshihisa Ishida

Abstract:

This paper describes the two stage control using a disturbance observer and a Kalman filter. The system feedback uses the estimated state when it controls the speed. After the change-over point, its feedback uses the controlled plant output when it controls the position. To change the system continually, a change-over point has to be determined pertinently, and the controlled plant input has to be adjusted by the addition of the appropriate value. The proposed method has noise-reduction effect. It changes the system continually, even if the controlled plant identification has the error. Although the conventional method needs a speed sensor, the proposed method does not need it. The proposed method has a superior robustness compared with the conventional two stage control.

Keywords: Disturbance observer, kalman filter, optimal control, two stage control.

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500 Segmentation of Breast Lesions in Ultrasound Images Using Spatial Fuzzy Clustering and Structure Tensors

Authors: Yan Xu, Toshihiro Nishimura

Abstract:

Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.

Keywords: fuzzy c-means, spatial information, structure tensor, ultrasound image segmentation

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499 Contourlet versus Wavelet Transform for a Robust Digital Image Watermarking Technique

Authors: Ibrahim A. El rube, Mohamad Abou El Nasr , Mostafa M. Naim, Mahmoud Farouk

Abstract:

In this paper, a watermarking algorithm that uses the wavelet transform with Multiple Description Coding (MDC) and Quantization Index Modulation (QIM) concepts is introduced. Also, the paper investigates the role of Contourlet Transform (CT) versus Wavelet Transform (WT) in providing robust image watermarking. Two measures are utilized in the comparison between the waveletbased and the contourlet-based methods; Peak Signal to Noise Ratio (PSNR) and Normalized Cross-Correlation (NCC). Experimental results reveal that the introduced algorithm is robust against different attacks and has good results compared to the contourlet-based algorithm.

Keywords: image watermarking; discrete wavelet transform, discrete contourlet transform, multiple description coding, quantization index modulation

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498 H∞ Takagi-Sugeno Fuzzy State-Derivative Feedback Control Design for Nonlinear Dynamic Systems

Authors: N. Kaewpraek, W. Assawinchaichote

Abstract:

This paper considers an H TS fuzzy state-derivative feedback controller for a class of nonlinear dynamical systems. A Takagi-Sugeno (TS) fuzzy model is used to approximate a class of nonlinear dynamical systems. Then, based on a linear matrix inequality (LMI) approach, we design an HTS fuzzy state-derivative feedback control law which guarantees L2-gain of the mapping from the exogenous input noise to the regulated output to be less or equal to a prescribed value. We derive a sufficient condition such that the system with the fuzzy controller is asymptotically stable and H performance is satisfied. Finally, we provide and simulate a numerical example is provided to illustrate the stability and the effectiveness of the proposed controller.

Keywords: H∞ fuzzy control, LMI, Takagi-Sugano (TS) fuzzy model, nonlinear dynamic systems, state-derivative feedback.

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497 Grid–SVC: An Improvement in SVC Algorithm, Based On Grid Based Clustering

Authors: Farhad Hadinejad, Hasan Saberi, Saeed Kazem

Abstract:

Support vector clustering (SVC) is an important kernelbased clustering algorithm in multi applications. It has got two main bottle necks, the high computation price and labeling piece. In this paper, we presented a modified SVC method, named Grid–SVC, to improve the original algorithm computationally. First we normalized and then we parted the interval, where the SVC is processing, using a novel Grid–based clustering algorithm. The algorithm parts the intervals, based on the density function of the data set and then applying the cartesian multiply makes multi-dimensional grids. Eliminating many outliers and noise in the preprocess, we apply an improved SVC method to each parted grid in a parallel way. The experimental results show both improvement in time complexity order and the accuracy.

Keywords: Grid–based clustering, SVC, Density function, Radial basis function.

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496 Heterogenous Dimensional Super Resolution of 3D CT Scans Using Transformers

Authors: Helen Zhang

Abstract:

Accurate segmentation of the airways from CT scans is crucial for early diagnosis of lung cancer. However, the existing airway segmentation algorithms often rely on thin-slice CT scans, which can be inconvenient and costly. This paper presents a set of machine learning-based 3D super-resolution algorithms along heterogenous dimensions to improve the resolution of thicker CT scans to reduce the reliance on thin-slice scans. To evaluate the efficacy of the super-resolution algorithms, quantitative assessments using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural SIMilarity index) were performed. The impact of super-resolution on airway segmentation accuracy is also studied. The proposed approach has the potential to make airway segmentation more accessible and affordable, thereby facilitating early diagnosis and treatment of lung cancer.

Keywords: 3D super-resolution, airway segmentation, thin-slice CT scans, machine learning.

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