Search results for: Median Filter

Authors: N. Ben Ameur, M. Loulou

Abstract:

This paper study the high-level modelling and design of delta-sigma (ΔΣ) noise shapers for audio Digital-to-Analog Converter (DAC) so as to eliminate the in-band Signal-to-Noise- Ratio (SNR) degradation that accompany one channel mismatch in audio signal. The converter combines a cascaded digital signal interpolation, a noise-shaping single loop delta-sigma modulator with a 5-bit quantizer resolution in the final stage. To reduce sensitivity of Digital-to-Analog Converter (DAC) nonlinearities of the last stage, a high pass second order Data Weighted Averaging (R2DWA) is introduced. This paper presents a MATLAB description modelling approach of the proposed DAC architecture with low distortion and swing suppression integrator designs. The ΔΣ Modulator design can be configured as a 3rd-order and allows 24-bit PCM at sampling rate of 64 kHz for Digital Video Disc (DVD) audio application. The modeling approach provides 139.38 dB of dynamic range for a 32 kHz signal band at -1.6 dBFS input signal level.

Keywords: DVD-audio, DAC, Interpolator and Interpolation Filter, Single-Loop ΔΣ Modulation, R2DWA, Clock Jitter

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Authors: Harpreet Kaur, Sudipta Majumdar

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In this paper a method for image dehazing is proposed in lifting wavelet transform domain. Lifting Daubechies (D4) wavelet has been used to obtain the approximate image and detail images.  As the haze is contained in low frequency part, only the approximate image is used for further processing. This region is processed by dehazing algorithm based on dark channel prior (DCP). The dehazed approximate image is then recombined with the detail images using inverse lifting wavelet transform. Implementation of lifting wavelet transform has the advantage of auxiliary memory saving, fast implementation and simplicity. Also, the proposed method deals with near white scene problem, blue horizon issue and localized light sources in a way to enhance image quality and makes the algorithm robust. Simulation results present improvement in terms of visual quality, parameters such as root mean square (RMS) contrast, structural similarity index (SSIM), entropy and execution time.

Keywords: Dark channel prior, image dehazing, lifting wavelet transform.

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Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

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Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: Active suspension, bending vibration, railway vehicle, vibration control.

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Authors: Simon Huston, Ebraheim Lahbash, Ali Parsa

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The development of the United Arab Emirates (UAE) into a regional trade, tourism, finance and logistics hub has transformed its real estate markets. However, speculative activity and price volatility remain concerns. UAE residential market values (MV) are exposed to fluctuations in capital flows and migration which, in turn, are affected by geopolitical uncertainty, oil price volatility and global investment market sentiment. Internally, a complex interplay between administrative boundaries, land tenure, building quality and evolving location characteristics fragments UAE residential property markets. In short, the UAE Residential Valuation System (UAE-RVS) confronts multiple challenges to collect, filter and analyze relevant information in complex and dynamic spatial and capital markets. A robust (RVS) can mitigate the risk of unhelpful volatility, speculative excess or investment mistakes. The research outlines the institutional, ontological, dynamic and epistemological issues at play. We highlight the importance of system capabilities, valuation standard salience and stakeholders trust.

Keywords: Valuation, property rights, information, institutions, trust, salience.

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Authors: Amir Rastegarnia, Mohammad Ali Tinati, Azam Khalili

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

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

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Authors: SP. Chokkalingam, K. Komathy

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Advances in the field of image processing envision a new era of evaluation techniques and application of procedures in various different fields. One such field being considered is the biomedical field for prognosis as well as diagnosis of diseases. This plethora of methods though provides a wide range of options to select from, it also proves confusion in selecting the apt process and also in finding which one is more suitable. Our objective is to use a series of techniques on bone scans, so as to detect the occurrence of rheumatoid arthritis (RA) as accurately as possible. Amongst other techniques existing in the field our proposed system tends to be more effective as it depends on new methodologies that have been proved to be better and more consistent than others. Computer aided diagnosis will provide more accurate and infallible rate of consistency that will help to improve the efficiency of the system. The image first undergoes histogram smoothing and specification, morphing operation, boundary detection by edge following algorithm and finally image subtraction to determine the presence of rheumatoid arthritis in a more efficient and effective way. Using preprocessing noises are removed from images and using segmentation, region of interest is found and Histogram smoothing is applied for a specific portion of the images. Gray level co-occurrence matrix (GLCM) features like Mean, Median, Energy, Correlation, Bone Mineral Density (BMD) and etc. After finding all the features it stores in the database. This dataset is trained with inflamed and noninflamed values and with the help of neural network all the new images are checked properly for their status and Rough set is implemented for further reduction.

Keywords: Computer Aided Diagnosis, Edge Detection, Histogram Smoothing, Rheumatoid Arthritis.

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Authors: Kay-Anne Haykal, Issack Biyong

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The post-traumatic stress disorder (PTSD) rises from exposure to a traumatic event and appears by a persistent experience of this event. Several psychiatric co-morbidities are associated with PTSD and include mood disorders, anxiety disorders, and substance abuse. The main objective was to compare the criteria for PTSD according to the literature to those used to diagnose a patient in a francophone hospital and to check the correspondence of these two criteria. 700 medical charts of admitted patients on the medicine or psychiatric unit at the Montfort Hospital were identified with the following diagnoses: major depressive disorder, bipolar disorder, anxiety disorder, substance abuse, and PTSD for the period of time between April 2005 and March 2006. Multiple demographic criteria were assembled. Also, for every chart analyzed, the PTSD criteria, according to the Manual of Mental Disorders (DSM) IV were found, identified, and grouped according to pre-established codes. An analysis using the receiver operating characteristic (ROC) method was elaborated for the study of data. A sample of 57 women and 50 men was studied. Age was varying between 18 and 88 years with a median age of 48. According to the PTSD criteria in the DSM IV, 12 patients should have the diagnosis of PTSD in opposition to only two identified in the medical charts. The ROC method establishes that with the combination of data from PTSD and depression, the sensitivity varies between 0,127 and 0,282, and the specificity varies between 0,889 and 0,917. Otherwise, if we examine the PTSD data alone, the sensibility jumps to 0.50, and the specificity varies between 0,781 and 0,895. This study confirms the presence of an underdiagnosed and treated PTSD that causes severe perturbations for the affected individual.

Keywords: Post-Traumatic Stress Disorder, diagnosis, co-morbidities, mental health disorders.

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient, but not the magnitude. A neural network with two hidden layers was then used to learn the coefficient magnitudes, along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: Quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction.

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Authors: Jedol Dayou, Jackson Hian Wui Chang, Rubena Yusoff, Ag. Sufiyan Abd. Hamid, Fauziah Sulaiman, Justin Sentian

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Aerosols are small particles suspended in air that have wide varying spatial and temporal distributions. The concentration of aerosol in total columnar atmosphere is normally measured using aerosol optical depth (AOD). In long-term monitoring stations, accurate AOD retrieval is often difficult due to the lack of frequent calibration. To overcome this problem, a near-sea-level Langley calibration algorithm is developed using the combination of clear-sky detection model and statistical filter. It attempts to produce a dataset that consists of only homogenous and stable atmospheric condition for the Langley calibration purposes. In this paper, a radiance-based validation method is performed to further investigate the feasibility and consistency of the proposed algorithm at different location, day, and time. The algorithm is validated using SMARTS model based n DNI value. The overall results confirmed that the proposed calibration algorithm feasible and consistent for measurements taken at different sites and weather conditions.

Keywords: Aerosol optical depth, direct normal irradiance, Langley calibration, radiance-based validation, SMARTS.

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Authors: Takashi Kaburagi, Takamasa Komura, Yosuke Kurihara

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Absolute pitch is the ability to identify a musical note without a reference tone. Training for absolute pitch often occurs in preschool education. It is necessary to clarify how well the trainee can make use of synesthesia in order to evaluate the effect of the training. To the best of our knowledge, there are no existing methods for objectively confirming whether the subject is using synesthesia. Therefore, in this study, we present a method to distinguish the use of color-auditory synesthesia from the separate use of color and audition during absolute pitch training. This method measures blood volume in the prefrontal cortex using functional Near-infrared spectroscopy (fNIRS) and assumes that the cognitive step has two parts, a non-linear step and a linear step. For the linear step, we assume a second order ordinary differential equation. For the non-linear part, it is extremely difficult, if not impossible, to create an inverse filter of such a complex system as the brain. Therefore, we apply a method based on a self-organizing map (SOM) and are guided by the available data. The presented method was tested using 15 subjects, and the estimation accuracy is reported.

Keywords: Absolute pitch, functional near-infrared spectroscopy, prefrontal cortex, synesthesia.

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Authors: Rezaul Azim, A. Toaha Mobashsher, M. Tariqul Islam

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In this paper a novel ultra-wideband (UWB) slot antenna with band notch characteristics for world interoperability for microwave access (WiMAX) is proposed. The designed antenna consists of a rectangular radiating patch and a ground plane with tapered shape slot. To realize a notch band, a curved parasitic element has been etched out along with the radiating patch. It is observed that by adjusting the length, thickness and position of the parasitic element, the proposed antenna can achieved an impedance bandwidth of 8.01GHz (2.84 to 10.85GHz) with a notched band of 3.28-3.85GHz. Compared to the recently reported band notch antennas, the proposed antenna has a simple configuration to realize band notch characteristics in order to mitigate the potential interference between WiMAX and UWB system. Furthermore, a stable radiation pattern and moderate gain except at the notched band makes the proposed antenna suitable for various UWB applications. 

Keywords: Band notch, Filter element, Ultra-wideband (UWB), WiMAX.

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Authors: Viktor Achter, Sebastian Breuers, Marc Seifert, Ulrich Lang, Joachim Götze, Bernd Reuther, Paul Müller

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Within the last years, several technologies have been developed to help building e-learning portals. Most of them follow approaches that deliver a vast amount of functionalities, suitable for class-like learning. The SuGI project, as part of the D-Grid (funded by the BMBF), targets on delivering a highly scalable and sustainable learning solution to provide materials (e.g. learning modules, training systems, webcasts, tutorials, etc.) containing knowledge about Grid computing to the D-Grid community. In this article, the process of the development of an e-learning portal focused on the requirements of this special user group is described. Furthermore, it deals with the conceptual and technical design of an e-learning portal, addressing the special needs of heterogeneous target groups. The main focus lies on the quality management of the software development process, Web templates for uploading new contents, the rich search and filter functionalities which will be described from a conceptual as well as a technical point of view. Specifically, it points out best practices as well as concepts to provide a sustainable solution to a relatively unknown and highly heterogeneous community.

Keywords: D-Grid, e-learning, e-science, Grid computing, SuGI.

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Authors: S. Montenegro, W. Hu

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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: Ramaswamy Palaniappan

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In this paper, several improvements are proposed to previous work of automated classification of alcoholics and nonalcoholics. In the previous paper, multiplayer-perceptron neural network classifying energy of gamma band Visual Evoked Potential (VEP) signals gave the best classification performance using 800 VEP signals from 10 alcoholics and 10 non-alcoholics. Here, the dataset is extended to include 3560 VEP signals from 102 subjects: 62 alcoholics and 40 non-alcoholics. Three modifications are introduced to improve the classification performance: i) increasing the gamma band spectral range by increasing the pass-band width of the used filter ii) the use of Multiple Signal Classification algorithm to obtain the power of the dominant frequency in gamma band VEP signals as features and iii) the use of the simple but effective knearest neighbour classifier. To validate that these two modifications do give improved performance, a 10-fold cross validation classification (CVC) scheme is used. Repeat experiments of the previously used methodology for the extended dataset are performed here and improvement from 94.49% to 98.71% in maximum averaged CVC accuracy is obtained using the modifications. This latest results show that VEP based classification of alcoholics is worth exploring further for system development.

Keywords: Alcoholic, Multilayer-perceptron, Nearest neighbour, Gamma band, MUSIC, Visual evoked potential.

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Authors: Raghad Jawad Ahmed

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Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields. The decision of the optimum number of segmentation areas in an image when it contains similar and/or un stationary texture fields. A novel neighborhood-based segmentation approach is proposed. A genetic algorithm is used in the proposed segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. In this paper we use an adaptive threshold estimation method for image thresholding in the wavelet domain based on the generalized Gaussian distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quad tree is employed to implement the multi resolution framework, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results using the proposed segmentation approach are very encouraging.

Keywords: Color image segmentation, Genetic algorithm, Markov random field, Scale space filter.

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Authors: Ehab F. Badran, Guoxiang Gu

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We consider optimal channel equalization for MIMO (multi-input/multi-output) time-varying channels in the sense of MMSE (minimum mean-squared-error), where the observation noise can be non-stationary. We show that all ZF (zero-forcing) receivers can be parameterized in an affine form which eliminates completely the ISI (inter-symbol-interference), and optimal channel equalizers can be designed through minimization of the MSE (mean-squarederror) between the detected signals and the transmitted signals, among all ZF receivers. We demonstrate that the optimal channel equalizer is a modified Kalman filter, and show that under the AWGN (additive white Gaussian noise) assumption, the proposed optimal channel equalizer minimizes the BER (bit error rate) among all possible ZF receivers. Our results are applicable to optimal channel equalization for DWMT (discrete wavelet multitone), multirate transmultiplexers, OFDM (orthogonal frequency division multiplexing), and DS (direct sequence) CDMA (code division multiple access) wireless data communication systems. A design algorithm for optimal channel equalization is developed, and several simulation examples are worked out to illustrate the proposed design algorithm.

Keywords: Channel equalization, Kalman filtering, Time-varying systems.

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Authors: Mehran Bakhshi, Mohammad Raouf Hosseini, Mohammadhosein Rahimi

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The cadmium sulfide nanoparticles were synthesized from the nickel-cadmium cake of a hydrometallurgical zinc producing plant and sodium sulfide as Cd²⁺ and S^-2 sources, respectively. Also, the synthesis process was performed by using the secretions of Bacillus licheniformis as bio-surfactant. Initially, in order to obtain a cadmium rich solution, two following steps were carried out: 1) Alkaline leaching for the removal of zinc oxide from the cake, and 2) acidic leaching to dissolve cadmium from the remained solid residue. Afterward, the obtained CdSO₄ solution was used for the nanoparticle biosynthesis. Nanoparticles were characterized by the energy dispersive spectroscopy (EDS) and X-ray diffraction (XRD) to confirm the formation of CdS crystals with cubic structure. Also, transmission electron microscopy (TEM) was applied to determine the particle sizes which were in 2-10 nm range. Moreover, the presence of the protein containing bio-surfactants was approved by using infrared analysis (FTIR). In addition, the absorbance below 400 nm confirms quantum particles’ size. Finally, it was shown that valuable CdS quantum dots could be obtained from the industrial waste products via environment-friendly biological approaches.

Keywords: Biosynthesis, cadmium cake, cadmium sulfide, nanoparticle, zinc smelter.

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Authors: Sun Li-ping, Zhu Jian-xun, Liu Sheng-nan

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In order to study the performance of dynamic positioning system during S-lay operations, dynamic positioning system is simulated with the hull-stinger-pipe coupling effect. The roller of stinger is simulated by the generalized elastic contact theory. The stinger is composed of Morrison members. Force on pipe is calculated by lumped mass method. Time domain of fully coupled barge model is analyzed combining with PID controller, Kalman filter and allocation of thrust using Sequential Quadratic Programming method. It is also analyzed that the effect of hull wave frequency motion on pipe-stinger coupling force and dynamic positioning system. Besides, it is studied that how S-lay operations affect the dynamic positioning accuracy. The simulation results are proved to be available by checking pipe stress with API criterion. The effect of heave and yaw motion cannot be ignored on hull-stinger-pipe coupling force and dynamic positioning system. It is important to decrease the barge’s pitch motion and lay pipe in head sea in order to improve safety of the S-lay installation and dynamic positioning.

Keywords: S-lay operation, dynamic positioning, coupling motion; time domain, allocation of thrust.

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Authors: Hong-Ren Chen, Fang-Yu Yeh

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In the past, there were more researches of recommendation system in applied electronic commerce. However, because all circles promote information technology integrative instruction actively, the quantity of instruction resources website is more and more increasing on the Internet. But there are less website including recommendation service, especially for teachers. This study established an instruction resource recommendation website that analyzed teaching style of teachers, then provided appropriate instruction resources for teachers immediately. We used the questionnaire survey to realize teacher-s suggestions and satisfactions with the instruction resource contents and recommendation results. The study shows: (1)The website used “Transactional Ability Inventory" that realized teacher-s style and provided appropriate instruction resources for teachers in a short time, it reduced the step of data filter. (2)According to the content satisfaction of questionnaire survey, four styles teachers were almost satisfied with the contents of the instruction resources that the website recommended, thus, the conception of developing instruction resources with different teaching style is accepted. (3) According to the recommendation satisfaction of questionnaire survey, four styles teachers were almost satisfied with the recommendation service of the website, thus, the recommendation strategy that provide different results for teachers in different teaching styles is accepted.

Keywords: Instruction resource, recommendation service, teaching style.

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Authors: Rachid.Dehini, Abdesselam.Bassou, Brahim.Ferdi

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Active Power Filters (APFs) are today the most widely used systems to eliminate harmonics compensate power factor and correct unbalanced problems in industrial power plants. We propose to improve the performances of conventional APFs by using artificial neural networks (ANNs) for harmonics estimation. This new method combines both the strategies for extracting the three-phase reference currents for active power filters and DC link voltage control method. The ANNs learning capabilities to adaptively choose the power system parameters for both to compute the reference currents and to recharge the capacitor value requested by VDC voltage in order to ensure suitable transit of powers to supply the inverter. To investigate the performance of this identification method, the study has been accomplished using simulation with the MATLAB Simulink Power System Toolbox. The simulation study results of the new (SAPF) identification technique compared to other similar methods are found quite satisfactory by assuring good filtering characteristics and high system stability.

Keywords: Artificial Neural Networks (ANN), p-q theory, (SAPF), Harmonics, Total Harmonic Distortion.

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Authors: Gye-rok Jeon, Jae-hee Jung, In-cheol Kim, Ah-young Jeon, Sang-hwa Yoon, Jung-man Son, Jae-hyung Kim, Soo-young Ye, Jung-hoon Ro, Dong-hyun Kim, Chul-han Kim

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A analysis on the conventional the blood pressure estimation method using an oscillometric sphygmomanometer was performed through a computer simulation using an arterial pressure-volume (APV) model. Traditionally, the maximum amplitude algorithm (MAP) was applied on the oscillation waveforms of the APV model to obtain the mean arterial pressure and the characteristic ratio. The estimation of mean arterial pressure and characteristic ratio was significantly affected with the shape of the blood pressure waveforms and the cutoff frequency of high-pass filter (HPL) circuitry. Experimental errors are due to these effects when estimating blood pressure. To find out an algorithm independent from the influence of waveform shapes and parameters of HPL, the volume oscillation of the APV model and the phase shift of the oscillation with fast fourier transform (FFT) were testified while increasing the cuff pressure from 1 mmHg to 200 mmHg (1 mmHg per second). The phase shift between the ranges of volume oscillation was then only observed between the systolic and the diastolic blood pressures. The same results were also obtained from the simulations performed on two different the arterial blood pressure waveforms and one hyperthermia waveform.

Keywords: Arterial blood pressure, oscillometric method

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Authors: Rizwan Ullah, Abdar Ali, Zahid Ullah

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This paper illustrates the study of three isolated zero voltage switched (ZVS) PWM full bridge (FB) converters to charge the high voltage battery in the charger of electric vehicle (EV). EV battery chargers have several challenges such as high efficiency, high reliability, low cost, isolation, and high power density. The cost of magnetic and filter components in the battery charger is reduced when switching frequency is increased. The increase in the switching frequency increases switching losses. ZVS is used to reduce switching losses and to operate the converter in the battery charger at high frequency. The performance of each of the three converters is evaluated on the basis of ZVS range, dead times of the switches, conduction losses of switches, circulating current stress, circulating energy, duty cycle loss, and efficiency. The limitations and merits of each PWM FB converter are reviewed. The converter with broader ZVS range, high efficiency and low switch stresses is selected for battery charger applications in EV.

Keywords: Electric vehicle, PWM FB converter, zero voltage switching, circulating energy, duty cycle loss, battery charger.

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Authors: Hao Mi, Ming Yang, Tian-yue Yang

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Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.

Keywords: Remote monitoring, non-destructive testing, embedded linux system, image processing.

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Authors: Alexander V. Libin, Manon Schladen, Assya Pascalev, Nawar Shara, Miriam Philmon, Yuri Millo, Joseph Verbalis

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Chronic conditions carry with them strong emotions and often lead to charged relationships between patients and their health providers and, by extension, patients and health researchers. Persons are both autonomous and relational and a purely cognitive model of autonomy neglects the social and relational basis of chronic illness. Ensuring genuine informed consent in research requires a thorough understanding of how participants perceive a study and their reasons for participation. Surveys may not capture the complexities of reasoning that underlies study participation. Contradictory reasons for participation, for instance an initial claim of altruism as rationale and a subsequent claim of personal benefit (therapeutic misconception), affect the quality of informed consent. Individuals apply principles through the filter of personal values and lived experience. Authentic autonomy, and hence authentic consent to research, occurs within the context of patients- unique life narratives and illness experiences.

Keywords: ethical dilemmas, open source technology, patient education, psychology of decision making

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Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: Distillation, machine learning, neural networks, quantization.

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Authors: Fekkak Bouazza, Menaa Mohamed, Loukriz Abdelhamid, Krim Mohamed L.

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This paper presents modeling and control strategy for the grid connected wind turbine system based on Permanent Magnet Synchronous Generator (PMSG). The considered system is based on back-to-back converter topology. The Grid Side Converter (GSC) achieves the DC bus voltage control and unity power factor. The Machine Side Converter (MSC) assures the PMSG speed control. The PMSG is used as a variable speed generator and connected directly to the turbine without gearbox. The pitch angle control is not either considered in this study. Further, Optimal Tip Speed Ratio (OTSR) based MPPT control strategy is used to ensure the most energy efficiency whatever the wind speed variations. A filter (L) is put between the GSC and the grid to reduce current ripple and to improve the injected power quality. The proposed grid connected wind system is built under MATLAB/Simulink environment. The simulation results show the feasibility of the proposed topology and performance of its control strategies.

Keywords: Wind, grid, PMSG, MPPT, OTSR.

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Authors: Samah. G. Babiker, Shuai Yong, Mohamed Osman Sid-Ahmed Xie Ming, A.M. Abdelbagi

Abstract:

In this paper, a one - dimensional microstructure tungsten grating (pyramids) is optimized for potential application as thermophotovoltaic (TPV) emitter. The influence of gratings geometric parameters on the spectral emittance are studied by using the rigorous coupled-wave analysis (RCWA).The results show that the spectral emittance is affected by the gratings geometrical parameters. The optimum parameters are grating period of 0.5µm, a filling ratio of 0.8 and grating height of h=0.2µm. A broad peak of high emittance is obtained at wavelengths between 0.5 and 1.8µm. The emittance drops below 0.2 at wavelengths above 1.8µm. This can be explained by the surface plasmon polaritons excitation coupled with the grating microstructures. At longer wavelengths, the emittance remains low and this is highly desired for thermophotovoltaic applications to reduce the thermal leakage due to low-energy photons that do not produce any photocurrent. The proposed structure can be used as a selective emitter for a narrow band gap cell such as GaSb. The performance of this simple 1-D emitter proved to be superior to that from more complicated structures. Almost all the radiation from the emitter incident, at angles up to 40°, on the cell, could be utilized to produce a photocurrent. There is no need for a filter.

Keywords: Thermophotovoltaic, RCWA, Grating, Emittance, Surface plasmon polaritons

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Authors: Stefan M. Goetz, Thomas Weyh, Hans-Georg Herzog

Abstract:

The triumph of inductive neuro-stimulation since its rediscovery in the 1980s has been quite spectacular. In lots of branches ranging from clinical applications to basic research this system is absolutely indispensable. Nevertheless, the basic knowledge about the processes underlying the stimulation effect is still very rough and rarely refined in a quantitative way. This seems to be not only an inexcusable blank spot in biophysics and for stimulation prediction, but also a fundamental hindrance for technological progress. The already very sophisticated devices have reached a stage where further optimization requires better strategies than provided by simple linear membrane models of integrate-and-fire style. Addressing this problem for the first time, we suggest in the following text a way for virtual quantitative analysis of a stimulation system. Concomitantly, this ansatz seems to provide a route towards a better understanding by using nonlinear signal processing and taking the nerve as a filter that is adapted for neuronal magnetic stimulation. The model is compact and easy to adjust. The whole setup behaved very robustly during all performed tests. Exemplarily a recent innovative stimulator design known as cTMS is analyzed and dimensioned with this approach in the following. The results show hitherto unforeseen potentials.

Keywords: Theory of magnetic stimulation, inversion, optimization, high voltage oscillator, TMS, cTMS.

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Authors: Michaela Wang

Abstract:

Since British established colonial settlements across the East Coast, Native Americans have suffered stark socio economic disparities in comparison to their neighboring communities. This paper employs the 1990, 2000, and 2010 United States Decennial Census to assess whether and to what extent the casino economy helped to close this socioeconomic gap between the Mohegan tribe and its surrounding community. These three Decennial Censuses cover two decades, from six years prior to the erection of Mohegan Sun casino to 14 years afterwards, including the Great Recession 2007-2009. Income, employment, education and housing parameters are selected as socio economic indicators. The profitable advent of the Mohegan Sun in 1996 dramatically improved the socio economic status of the Mohegan Tribe between 1990 and 2000. In fact, for most of these indicators––poverty, median household income, employment, home ownership, and car ownership––disparities shifted; tribal socioeconomic parameters improved from well below the level of New London County in 1990, to the same level or above the county rates in 2000. However, economic downturn in 2007-2009 Great Recession impacted Mohegan people remarkably. By 2010, disparities for household income, employment, home ownership, and car ownership returned. The casino bridged socio economic inequalities, but at the face of economic crises, the mono-product economy grew vulnerable.

Keywords: Indigenous tribe, socio economic inequalities, casino, native American.

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Authors: Kamarul Hawari Ghazali, Mohd. Marzuki Mustafa, Aini Hussain

Abstract:

Machine vision is an application of computer vision to automate conventional work in industry, manufacturing or any other field. Nowadays, people in agriculture industry have embarked into research on implementation of engineering technology in their farming activities. One of the precision farming activities that involve machine vision system is automatic weeding strategy. Automatic weeding strategy in oil palm plantation could minimize the volume of herbicides that is sprayed to the fields. This paper discusses an automatic weeding strategy in oil palm plantation using machine vision system for the detection and differential spraying of weeds. The implementation of vision system involved the used of image processing technique to analyze weed images in order to recognized and distinguished its types. Image filtering technique has been used to process the images as well as a feature extraction method to classify the type of weed images. As a result, the image processing technique contributes a promising result of classification to be implemented in machine vision system for automated weeding strategy.

Keywords: Machine vision, Automatic Weeding Strategy, filter, feature extraction

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