Search results for: nonlinear resonance vibration method

Authors: Farzad Abdous

Abstract:

Fuel cell's system requires regulating circuit for voltage and current in order to control power in case of connecting to other generative devices or load. In this paper Fuel cell system and convertor, which is a multi-variable system, are controlled using sliding mode method. Use of weighting matrix in design procedure made it possible to regulate speed of control. Simulation results show the robustness and accuracy of proposed controller for controlling desired of outputs.

Keywords: DC-DC converter, Fuel cell, PEM, Slides mode control.

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Authors: M. R. Daneshgar, S. E. Habibi, E. Daneshgar, A. Daneshgar

Abstract:

In this paper, a two-dimensional method is developed to simulate the fillet welds in a stiffened cylindrical shell, using finite element method. The stiffener material is aluminum 2519. The thermo-elasto-plastic analysis is used to analyze the thermo-mechanical behavior. Due to the high heat flux rate of the welding process, two uncouple thermal and mechanical analysis are carried out instead of performing a single couple thermo-mechanical simulation. In order to investigate the effects of the welding procedures, two different welding techniques are examined. The resulted residual stresses and distortions due to different welding procedures are obtained. Furthermore, this study employed the technique of element birth and death to simulate the weld filler variation with time in fillet welds. The obtained results are in good agreement with the published experimental and three-dimensional numerical simulation results. Therefore, the proposed 2D modeling technique can effectively give the corresponding results of 3D models. Furthermore, by inspection of the obtained residual hoop and transverse stresses and angular distortions, proper welding procedure is suggested.

Keywords: Stiffened cylindrical shell, fillet welds, residual stress, angular distortion, finite element method.

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Authors: András Barta, István Vajk

Abstract:

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.

Keywords: Object recognition, Bayesian network, Wavelets, Document processing.

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Authors: Chayanon Hansapinyo

Abstract:

This paper presents experimental investigation and finite element analysis on buckling behavior of irregular section coldformed steel columns under axially concentric loading. For the experimental study, four different sections of columns were tested to investigate effect of stiffening and width-to-thickness ratio on buckling behavior. For each of the section, three lengths of 230, 950 and 1900 mm. were studied representing short, intermediate long and long columns, respectively. Then, nonlinear finite element analyses of the tested columns were performed. The comparisons in terms of load-deformation response and buckling mode show good agreement and hence the FEM models were validated. Parametric study of stiffening element and thickness of 1.0, 1.15, 1.2, 1.5, 1.6 and 2.0 mm. was analyzed. The test results showed that stiffening effect pays a large contribution to prevent distortional mode. The increase in wall thickness enhanced buckling stress beyond the yielding strength in short and intermediate columns, but not for the long columns.

Keywords: Buckling behavior, Irregular section, Cold-formed steel, Concentric loading.

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Authors: Mohammad Shafigh, Nasser Fatouraee, Amirsaied Seddighi

Abstract:

Mechanical properties of cerebral arteries are, due to their relationship with cerebrovascular diseases, of clinical worth. To acquire these properties, eight samples were obtained from middle cerebral arteries of human cadavers, whose death were not due to injuries or diseases of cerebral vessels, and tested within twelve hours after resection, by a precise biaxial tensile test device specially developed for the present study considering the dimensions, sensitivity and anisotropic nature of samples. The resulting stress-stretch curve was plotted and subsequently fitted to a hyperelastic three-parameter Fung model. It was found that the arteries were noticeably stiffer in circumferential than in axial direction. It was also demonstrated that the use of multi-parameter hyperelastic constitutive models is useful for mathematical description of behavior of cerebral vessel tissue. The reported material properties are a proper reference for numerical modeling of cerebral arteries and computational analysis of healthy or diseased intracranial arteries.

Keywords: Anisotropic Tissue, Cerebral Blood Vessels, Fung Model, Nonlinear Material, Plain Stress.

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Authors: C.Ramesh, V.Vaidehi

Abstract:

Ultra-wide band (UWB) communication is one of the most promising technologies for high data rate wireless networks for short range applications. This paper proposes a blind channel estimation method namely IMM (Interactive Multiple Model) Based Kalman algorithm for UWB OFDM systems. IMM based Kalman filter is proposed to estimate frequency selective time varying channel. In the proposed method, two Kalman filters are concurrently estimate the channel parameters. The first Kalman filter namely Static Model Filter (SMF) gives accurate result when the user is static while the second Kalman filter namely the Dynamic Model Filter (DMF) gives accurate result when the receiver is in moving state. The static transition matrix in SMF is assumed as an Identity matrix where as in DMF, it is computed using Yule-Walker equations. The resultant filter estimate is computed as a weighted sum of individual filter estimates. The proposed method is compared with other existing channel estimation methods.

Keywords: Channel estimation, Kalman filter, UWB, Channel model, AR model

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Authors: B. Al-Naami, N. Gharaibeh, A. AlRazzaq Kheshman

Abstract:

Alzheimer is known as the loss of mental functions such as thinking, memory, and reasoning that is severe enough to interfere with a person's daily functioning. The appearance of Alzheimer Disease symptoms (AD) are resulted based on which part of the brain has a variety of infection or damage. In this case, the MRI is the best biomedical instrumentation can be ever used to discover the AD existence. Therefore, this paper proposed a fusion method to distinguish between the normal and (AD) MRIs. In this combined method around 27 MRIs collected from Jordanian Hospitals are analyzed based on the use of Low pass -morphological filters to get the extracted statistical outputs through intensity histogram to be employed by the descriptive box plot. Also, the artificial neural network (ANN) is applied to test the performance of this approach. Finally, the obtained result of t-test with confidence accuracy (95%) has compared with classification accuracy of ANN (100 %). The robust of the developed method can be considered effectively to diagnose and determine the type of AD image.

Keywords: Alzheimer disease, Brain MRI analysis, Morphological filter, Box plot, Intensity histogram, ANN.

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Authors: Matko Šaric, Hrvoje Dujmic, Vladan Papic, Nikola Rožic

Abstract:

Detection of player identity is challenging task in sport video content analysis. In case of soccer video player number recognition is effective and precise solution. Jersey numbers can be considered as scene text and difficulties in localization and recognition appear due to variations in orientation, size, illumination, motion etc. This paper proposed new method for player number localization and recognition. By observing hue, saturation and value for 50 different jersey examples we noticed that most often combination of low and high saturated pixels is used to separate number and jersey region. Image segmentation method based on this observation is introduced. Then, novel method for player number localization based on internal contours is proposed. False number candidates are filtered using area and aspect ratio. Before OCR processing extracted numbers are enhanced using image smoothing and rotation normalization.

Keywords: player number, soccer video, HSV color space

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Authors: I. Falconett, K. Nagasaka

Abstract:

This study investigates the performance of radial basis function networks (RBFN) in forecasting the monthly CO2 emissions of an electric power utility. We also propose a method for input variable selection. This method is based on identifying the general relationships between groups of input candidates and the output. The effect that each input has on the forecasting error is examined by removing all inputs except the variable to be investigated from its group, calculating the networks parameter and performing the forecast. Finally, the new forecasting error is compared with the reference model. Eight input variables were identified as the most relevant, which is significantly less than our reference model with 30 input variables. The simulation results demonstrate that the model with the 8 inputs selected using the method introduced in this study performs as accurate as the reference model, while also being the most parsimonious.

Keywords: Correlation analysis, CO2 emissions forecasting, electric power utility, radial basis function networks.

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Authors: A. Natsir, M. Nadir, S. Syahrir, A. Mujnisa, N. Purnomo, A. R. Egan, B. J. Leury

Abstract:

Rumen degradation characteristic of feedstuff is one of the prominent factors affecting microbial population in rumen of animal. High rumen degradation rate of faba bean protein may lead to inconstant rumen conditions that could have a prominent impact on rumen microbial diversity. Amplified Ribosomal DNA Restriction Analysis (ARDRA) is utilized to monitor diversity of rumen microbes on sheep fed low quality forage supplemented by faba beans. Four mature merino sheep with existing rumen cannula were used in this study according to 4 x 4 Latin square design. The results of study indicated that there were 37 different ARDRA types identified out of 136 clones examined. Among those clones, five main clone types existed across the treatments with different percentages. In conclusion, the ARDRA method is potential to be used as a routine tool to assess the temporary changes in the rumen community as a result of different feeding strategies.

Keywords: ARDRA method, clones, microbial diversity, ribotypes, ruminants.

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Authors: Mashitah Mohd Hussain, Salleh Serwan, Zuhaina Hj Zakaria

Abstract:

This paper presents a method to estimate load profile in a multiple power flow solutions for every minutes in 24 hours per day. A method to calculate multiple solutions of non linear profile is introduced. The Power System Simulation/Engineering (PSS®E) and python has been used to solve the load power flow. The result of this power flow solutions has been used to estimate the load profiles for each load at buses using Independent Component Analysis (ICA) without any knowledge of parameter and network topology of the systems. The proposed algorithm is tested with IEEE 69 test bus system represents for distribution part and the method of ICA has been programmed in MATLAB R2012b version. Simulation results and errors of estimations are discussed in this paper.

Keywords: Electrical Distribution System, Power Flow Solution, Distribution Network, Independent Component Analysis, Newton Raphson, Power System Simulation for Engineering.

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Authors: H. Abaali, M. T. Lamchich, M. Raoufi

Abstract:

In this paper, we propose the Modified Synchronous Detection (MSD) Method for determining the reference compensating currents of the shunt active power filter under non sinusoidal voltages conditions. For controlling the inverter switching we used the PI regulator. The numerical simulation results, using Power System Blockset Toolbox PSB of Matlab, from a complete structure, are presented and discussed.

Keywords: Distorted, harmonic, Modified Synchronous Detection Method, PI regulator, Shunt Active Power Filter, unbalanced.

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Authors: Luay A. Fraiwan, Natheer Y. Khaswaneh, Khaldon Y. Lweesy

Abstract:

Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.

Keywords: Features selection, regression trees, sleep stagescoring, wavelet packets.

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Authors: M. E. Marwan, A. R. Madar, N. Fuad

Abstract:

Mobile communication provides access to the outside world without borders everywhere and at any time. The learning method that related to mobile communication technology is known as mobile learning (M-learning). It is a method that communicates learning materials with mobile device technology. The purpose of this method is to increase the interest in learning among students and assist them in obtaining learning materials at Kolej Poly-Tech MARA (KPTM) in order to improve the student’s performance in their study and to encourage educators to diversify the teaching practices. This paper discusses the student’s awareness for enhancement of learning style using mobile technologies and their readiness to apply the elements of mobile learning in learning to improve performance and interest in learning among students. An application called Mobile EEF Learning System (MEEFLS) has been developed as a tool to be used as a pilot test in KPTM.

Keywords: Awareness, MEEFLS, mobile learning, readiness.

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Authors: B. Tiseo, V. Quaranta, G. Bruno, G. Sisinni

Abstract:

There is an increasing demand of nano-satellite development among universities, small companies, and emerging countries. Low-cost and fast-delivery are the main advantages of such class of satellites achieved by the extensive use of commercial-off-the-shelf components. On the other side, the loss of reliability and the poor success rate are limiting the use of nano-satellite to educational and technology demonstration and not to the commercial purpose. Standardization of nano-satellite environmental testing by tailoring the existing test standard for medium/large satellites is then a crucial step for their market growth. Thus, it is fundamental to find the right trade-off between the improvement of reliability and the need to keep their low-cost/fast-delivery advantages. This is particularly even more essential for satellites of CubeSat family. Such miniaturized and standardized satellites have 10 cm cubic form and mass no more than 1.33 kilograms per 1 unit (1U). For this class of nano-satellites, the qualification process is mandatory to reduce the risk of failure during a space mission. This paper reports the description and results of the space qualification test campaign performed on Endurosat’s CubeSat nano-satellite and modules. Mechanical and environmental tests have been carried out step by step: from the testing of the single subsystem up to the assembled CubeSat nano-satellite. Functional tests have been performed during all the test campaign to verify the functionalities of the systems. The test duration and levels have been selected by tailoring the European Space Agency standard ECSS-E-ST-10-03C and GEVS: GSFC-STD-7000A.

Keywords: CubeSat, Nano-satellite, shock, testing, vibration.

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Authors: R. M. Barron, B. Zogheib

Abstract:

A new numerical method for solving the twodimensional, steady, incompressible, viscous flow equations on a Curvilinear staggered grid is presented in this paper. The proposed methodology is finite difference based, but essentially takes advantage of the best features of two well-established numerical formulations, the finite difference and finite volume methods. Some weaknesses of the finite difference approach are removed by exploiting the strengths of the finite volume method. In particular, the issue of velocity-pressure coupling is dealt with in the proposed finite difference formulation by developing a pressure correction equation in a manner similar to the SIMPLE approach commonly used in finite volume formulations. However, since this is purely a finite difference formulation, numerical approximation of fluxes is not required. Results obtained from the present method are based on the first-order upwind scheme for the convective terms, but the methodology can easily be modified to accommodate higher order differencing schemes.

Keywords: Curvilinear, finite difference, finite volume, SIMPLE.

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Authors: C. Ardil

Abstract:

Being effective in every organizational activity has become necessary due to the escalating level of competition in all areas of corporate life. In the context of supply chain management, aircraft supplier selection is currently one of the most crucial activities. It is possible to choose the best aircraft supplier and deliver efficiency in terms of cost, quality, delivery time, economic status, and institutionalization if a systematic supplier selection approach is used. In this study, an effective multiple criteria decision-making methodology, proximity measure method (PMM), is used within a fuzzy environment based on the vague structure of the real working environment. The best appropriate aircraft suppliers are identified and ranked after the proposed multiple criteria decision making technique is used in a real-life scenario.

Keywords: Aircraft supplier selection, multiple criteria decision making, fuzzy sets, proximity measure method, Minkowski distance family function, Hausdorff distance function, PMM, MCDM

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Authors: Mubarak Saif Mohsen, Zurinahni Zainol, Rosalina Abdul Salam, Wahidah Husain

Abstract:

One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.

Keywords: Protein sequence algorithm, dynamic programming algorithm, multithread

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Authors: S. Ben Chaabane, M. Sayadi, F. Fnaiech, E. Brassart

Abstract:

In this paper we propose a new knowledge model using the Dempster-Shafer-s evidence theory for image segmentation and fusion. The proposed method is composed essentially of two steps. First, mass distributions in Dempster-Shafer theory are obtained from the membership degrees of each pixel covering the three image components (R, G and B). Each membership-s degree is determined by applying Fuzzy C-Means (FCM) clustering to the gray levels of the three images. Second, the fusion process consists in defining three discernment frames which are associated with the three images to be fused, and then combining them to form a new frame of discernment. The strategy used to define mass distributions in the combined framework is discussed in detail. The proposed fusion method is illustrated in the context of image segmentation. Experimental investigations and comparative studies with the other previous methods are carried out showing thus the robustness and superiority of the proposed method in terms of image segmentation.

Keywords: Fuzzy C-means, Color image, data fusion, Dempster-Shafer's evidence theory

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Authors: Hyun-Woo Cho

Abstract:

Detection of incipient abnormal events is important to improve safety and reliability of machine operations and reduce losses caused by failures. Improper set-ups or aligning of parts often leads to severe problems in many machines. The construction of prediction models for predicting faulty conditions is quite essential in making decisions on when to perform machine maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of machine measurement data. The calibration model is used to predict two faulty conditions from historical reference data. This approach utilizes genetic algorithms (GA) based variable selection, and we evaluate the predictive performance of several prediction methods using real data. The results shows that the calibration model based on supervised probabilistic principal component analysis (SPPCA) yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: Prediction, operation monitoring, on-line data, nonlinear statistical methods, empirical model.

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Authors: Tahseen A. Jilani, Aqil S. Burney, C. Ardil

Abstract:

Time series models have been used to make predictions of academic enrollments, weather, road accident, casualties and stock prices, etc. Based on the concepts of quartile regression models, we have developed a simple time variant quantile based fuzzy time series forecasting method. The proposed method bases the forecast using prediction of future trend of the data. In place of actual quantiles of the data at each point, we have converted the statistical concept into fuzzy concept by using fuzzy quantiles using fuzzy membership function ensemble. We have given a fuzzy metric to use the trend forecast and calculate the future value. The proposed model is applied for TAIFEX forecasting. It is shown that proposed method work best as compared to other models when compared with respect to model complexity and forecasting accuracy.

Keywords: Quantile Regression, Fuzzy time series, fuzzy logicalrelationship groups, heuristic trend prediction.

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Authors: A. S. Poornima, R. Aparna, B. B. Amberker, Prashant Koulgi

Abstract:

In this paper, we propose use of convolutional codes for file dispersal. The proposed method is comparable in complexity to the information Dispersal Algorithm proposed by M.Rabin and for particular choices of (non-binary) convolutional codes, is almost as efficient as that algorithm in terms of controlling expansion in the total storage. Further, our proposed dispersal method allows string search.

Keywords: Convolutional codes, File dispersal, Filereconstruction, Information Dispersal Algorithm, String search.

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Authors: S. Montenegro, W. Hu

Abstract:

The objective of this paper is to develop a neural network-based residual generator to detect the fault in the actuators for a specific communication satellite in its attitude control system (ACS). First, a dynamic multilayer perceptron network with dynamic neurons is used, those neurons correspond a second order linear Infinite Impulse Response (IIR) filter and a nonlinear activation function with adjustable parameters. Second, the parameters from the network are adjusted to minimize a performance index specified by the output estimated error, with the given input-output data collected from the specific ACS. Then, the proposed dynamic neural network is trained and applied for detecting the faults injected to the wheel, which is the main actuator in the normal mode for the communication satellite. Then the performance and capabilities of the proposed network were tested and compared with a conventional model-based observer residual, showing the differences between these two methods, and indicating the benefit of the proposed algorithm to know the real status of the momentum wheel. Finally, the application of the methods in a satellite ground station is discussed.

Keywords: Satellite, Attitude Control, Momentum Wheel, Neural Network, Fault Detection.

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Authors: Maatoug Hassine, Mourad Hrizi

Abstract:

In this paper, we consider a geometric inverse source problem for the heat equation with Dirichlet and Neumann boundary data. We will reconstruct the exact form of the unknown source term from additional boundary conditions. Our motivation is to detect the location, the size and the shape of source support. We present a one-shot algorithm based on the Kohn-Vogelius formulation and the topological gradient method. The geometric inverse source problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a source function. Then, we present a non-iterative numerical method for the geometric reconstruction of the source term with unknown support using a level curve of the topological gradient. Finally, we give several examples to show the viability of our presented method.

Keywords: Geometric inverse source problem, heat equation, topological sensitivity, topological optimization, Kohn-Vogelius formulation.

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Authors: R. Estrada, A. Henriquez, R. Becerra, C. Laguna

Abstract:

Spatial Augmented Reality is a variation of Augmented Reality where the Head-Mounted Display is not required. This variation of Augmented Reality is useful in cases where the need for a Head-Mounted Display itself is a limitation. To achieve this, Spatial Augmented Reality techniques substitute the technological elements of Augmented Reality; the virtual world is projected onto a physical surface. To create an interactive spatial augmented experience, the application must be aware of the spatial relations that exist between its core elements. In this case, the core elements are referred to as a projection system and an input system, and the process to achieve this spatial awareness is called system calibration. The Spatial Augmented Reality system is considered calibrated if the projected virtual world scale is similar to the real-world scale, meaning that a virtual object will maintain its perceived dimensions when projected to the real world. Also, the input system is calibrated if the application knows the relative position of a point in the projection plane and the RGB-depth sensor origin point. Any kind of projection technology can be used, light-based projectors, close-range projectors, and screens, as long as it complies with the defined constraints; the method was tested on different configurations. The proposed procedure does not rely on a physical marker, minimizing the human intervention on the process. The tests are made using a Kinect V2 as an input sensor and several projection devices. In order to test the method, the constraints defined were applied to a variety of physical configurations; once the method was executed, some variables were obtained to measure the method performance. It was demonstrated that the method obtained can solve different arrangements, giving the user a wide range of setup possibilities.

Keywords: Color depth sensor, human computer interface, interactive surface, spatial augmented reality.

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Authors: Wanida Wonsawat

Abstract:

This research describes a voltammetric approach to determine amounts of vitamin C (Ascorbic acid) in orange juice sample, using three screen printed electrode. The anodic currents of vitamin C were proportional to vitamin C concentration in the range of 0 – 10.0 mM with the limit of detection of 1.36 mM. The method was successfully employed with 2 µL of the working solution dropped on the electrode surface. The proposed method was applied for the analysis of vitamin C in packed orange juice without sample purification or complexion of sample preparation step.

Keywords: Ascorbic acid, Vitamin C, Juice, Voltammetry

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Authors: S. Panda, N. P. Patidar, R. Singh

Abstract:

Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.

Keywords: Real-Coded Genetic Algorithm (RCGA), Static Var Compensator (SVC), Power System Stabilizer (PSS), Low Frequency Oscillations, Power System Stability.

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Authors: Nilson Barbieri, Renato Barbieri

Abstract:

–In this paper the damage in clamped-free, clampedclamped and free-free beam are analyzed considering samples without and with structural modifications. The damage location is investigated by the use of the bispectrum and wavelet analysis. The mathematical models are obtained using 2D elasticity theory and the Finite Element Method (FEM). The numerical and experimental data are approximated using the Particle Swarm Optimizer (PSO) method and this way is possible to adjust the localization and the severity of the damage. The experimental data are obtained through accelerometers placed along the sample. The system is excited using impact hammer.

Keywords: Damage, beam, PSO, bispectrum, wavelet transform

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Authors: Aree A. Mohammed

Abstract:

In this work we develop an object extraction method and propose efficient algorithms for object motion characterization. The set of proposed tools serves as a basis for development of objectbased functionalities for manipulation of video content. The estimators by different algorithms are compared in terms of quality and performance and tested on real video sequences. The proposed method will be useful for the latest standards of encoding and description of multimedia content – MPEG4 and MPEG7.

Keywords: Object extraction, Video indexing, Segmentation, Optical flow, Motion estimators.

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Authors: J. Prakash, K. Rajesh

Abstract:

In this paper we present a new method for coin identification. The proposed method adopts a hybrid scheme using Eigenvalues of covariance matrix, Circular Hough Transform (CHT) and Bresenham-s circle algorithm. The statistical and geometrical properties of the small and large Eigenvalues of the covariance matrix of a set of edge pixels over a connected region of support are explored for the purpose of circular object detection. Sparse matrix technique is used to perform CHT. Since sparse matrices squeeze zero elements and contain only a small number of non-zero elements, they provide an advantage of matrix storage space and computational time. Neighborhood suppression scheme is used to find the valid Hough peaks. The accurate position of the circumference pixels is identified using Raster scan algorithm which uses geometrical symmetry property. After finding circular objects, the proposed method uses the texture on the surface of the coins called texton, which are unique properties of coins, refers to the fundamental micro structure in generic natural images. This method has been tested on several real world images including coin and non-coin images. The performance is also evaluated based on the noise withstanding capability.

Keywords: Circular Hough Transform, Coin detection, Covariance matrix, Eigenvalues, Raster scan Algorithm, Texton.

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