Abstract: In this paper, two bandstop filters resonating at 5.25 GHz and 7.3 GHz using Defected Microstrip Structure (DMS) are discussed. These slots are incorporated in the feed lines of filters to perform a serious LC resonance property in certain frequency and suppress the spurious signals. Therefore, this method keeps the filter size unchanged and makes a resonance frequency that is due to the abrupt change of the current path of the filter. If the application requires elimination of this band of frequencies, additional filter elements are required, which can only be accomplished by adding this DMS element resonant at desired frequency band rejection. The filters are optimized and simulated with Computer Simulation Technology (CST) tool.
Abstract: Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.
Abstract: This paper presents a self-sustaining mobile system for
counting and classification of vehicles through processing video. It
proposes a counting and classification algorithm divided in four steps
that can be executed multiple times in parallel in a SBC (Single
Board Computer), like the Raspberry Pi 2, in such a way that it
can be implemented in real time. The first step of the proposed
algorithm limits the zone of the image that it will be processed.
The second step performs the detection of the mobile objects using
a BGS (Background Subtraction) algorithm based on the GMM
(Gaussian Mixture Model), as well as a shadow removal algorithm
using physical-based features, followed by morphological operations.
In the first step the vehicle detection will be performed by using
edge detection algorithms and the vehicle following through Kalman
filters. The last step of the proposed algorithm registers the vehicle
passing and performs their classification according to their areas.
An auto-sustainable system is proposed, powered by batteries and
photovoltaic solar panels, and the data transmission is done through
GPRS (General Packet Radio Service)eliminating the need of using
external cable, which will facilitate it deployment and translation to
any location where it could operate. The self-sustaining trailer will
allow the counting and classification of vehicles in specific zones
with difficult access.
Abstract: This paper presents a nonlinear differential model,
for a three-bladed horizontal axis wind turbine (HAWT) suited
for control applications. It is based on a 8-dofs, lumped
parameters structural dynamics coupled with a quasi-steady sectional
aerodynamics. In particular, using the Euler-Lagrange Equation
(Energetic Variation approach), the authors derive, and successively
validate, such model. For the derivation of the aerodynamic model,
the Greenbergs theory, an extension of the theory proposed by
Theodorsen to the case of thin airfoils undergoing pulsating flows,
is used. Specifically, in this work, the authors restricted that theory
under the hypothesis of low perturbation reduced frequency k,
which causes the lift deficiency function C(k) to be real and equal
to 1. Furthermore, the expressions of the aerodynamic loads are
obtained using the quasi-steady strip theory (Hodges and Ormiston),
as a function of the chordwise and normal components of relative
velocity between flow and airfoil Ut, Up, their derivatives, and
section angular velocity ε˙. For the validation of the proposed model,
the authors carried out open and closed-loop simulations of a 5
MW HAWT, characterized by radius R =61.5 m and by mean chord
c = 3 m, with a nominal angular velocity Ωn = 1.266rad/sec.
The first analysis performed is the steady state solution, where
a uniform wind Vw = 11.4 m/s is considered and a collective
pitch angle θ = 0.88◦ is imposed. During this step, the authors
noticed that the proposed model is intrinsically periodic due to
the effect of the wind and of the gravitational force. In order
to reject this periodic trend in the model dynamics, the authors
propose a collective repetitive control algorithm coupled with a PD
controller. In particular, when the reference command to be tracked
and/or the disturbance to be rejected are periodic signals with a
fixed period, the repetitive control strategies can be applied due to
their high precision, simple implementation and little performance
dependency on system parameters. The functional scheme of a
repetitive controller is quite simple and, given a periodic reference
command, is composed of a control block Crc(s) usually added
to an existing feedback control system. The control block contains
and a free time-delay system eτs in a positive feedback loop, and a
low-pass filter q(s). It should be noticed that, while the time delay
term reduces the stability margin, on the other hand the low pass
filter is added to ensure stability. It is worth noting that, in this
work, the authors propose a phase shifting for the controller and
the delay system has been modified as e^(−(T−γk)), where T is the
period of the signal and γk is a phase shifting of k samples of the
same periodic signal. It should be noticed that, the phase shifting
technique is particularly useful in non-minimum phase systems, such
as flexible structures. In fact, using the phase shifting, the iterative
algorithm could reach the convergence also at high frequencies.
Notice that, in our case study, the shifting of k samples depends
both on the rotor angular velocity Ω and on the rotor azimuth
angle Ψ: we refer to this controller as a spatial repetitive controller.
The collective repetitive controller has also been coupled with a C(s) = PD(s), in order to dampen oscillations of the blades.
The performance of the spatial repetitive controller is compared
with an industrial PI controller. In particular, starting from wind
speed velocity Vw = 11.4 m/s the controller is asked to maintain the
nominal angular velocity Ωn = 1.266rad/s after an instantaneous
increase of wind speed (Vw = 15 m/s). Then, a purely periodic
external disturbance is introduced in order to stress the capabilities
of the repetitive controller. The results of the simulations show that,
contrary to a simple PI controller, the spatial repetitive-PD controller
has the capability to reject both external disturbances and periodic
trend in the model dynamics. Finally, the nominal value of the
angular velocity is reached, in accordance with results obtained with
commercial software for a turbine of the same type.
Abstract: GaInAsSb cells probably show better performance than GaSb cells in low-temperature thermophotovoltaic systems due to lower bandgap; however, few experiments proved this phenomenon so far. In this paper, numerical simulation is used to evaluate GaInAsSb and GaSb cells with similar structures under different radiation temperatures. We found that GaInAsSb cells with n-type emitters show slightly higher output power densities compared with that of GaSb cells with n-type emitters below 1,550 K-blackbody radiation, and the power density of the later cells will suppress the formers above this temperature point. During the temperature range of 1,000~2,000 K, the efficiencies of GaSb cells are about twice of GaInAsSb cells if perfect filters are used to prevent the emission of the non-absorbed long wavelength photons. Several parameters that affect the GaInAsSb cell were analyzed, such as doping profiles, thicknesses of GaInAsSb epitaxial layer and surface recombination velocity. The non-p junctions, i.e., n-type emitters are better for GaInAsSb cell fabrication, which is similar to that of GaSb cells.
Abstract: Design of compact UWB multilayered microstrip filter with E-shape resonator is presented, which provides wide stopband up to 20 GHz and arbitrary impedance matching. The design procedure is developed based on the method of least squares and theory of N-coupled transmission lines. The dimensions of designed filter are about 11 mm × 11 mm and the three E-shape resonators are placed among four dielectric layers. The average insertion loss in the passband is less than 1 dB and in the stopband is about 30 dB up to 20 GHz. Its group delay in the UWB region is about 0.5 ns. The performance of the optimized filter design perfectly agrees with the microwave simulation softwares.
Abstract: In this paper, we analyze major components of activity recognition (AR) in wearable device with 9-axis sensors and sensor fusion filters. 9-axis sensors commonly include 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We chose sensor fusion filters as Kalman filter and Direction Cosine Matrix (DCM) filter. We also construct sensor fusion data from each activity sensor data and perform classification by accuracy of AR using Naïve Bayes and SVM. According to the classification results, we observed that the DCM filter and the specific combination of the sensing axes are more effective for AR in wearable devices while classifying walking, running, ascending and descending.
Abstract: 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.
Abstract: Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.
Abstract: All optical wavelength conversion is essential in present day optical networks for transparent interoperability, contention resolution, and wavelength routing. The incorporation of all optical wavelength convertors leads to better utilization of the network resources and hence improves the efficiency of optical networks. Wavelength convertors that can work with Dispersion Managed (DM) solitons are attractive due to their superior transmission capabilities. In this paper, wavelength conversion for dispersion managed soliton signals was demonstrated at 100 Gbps through semiconductor optical amplifier and an optical filter. The wavelength conversion was achieved for a 1550 nm input signal to1555nm output signal. The output signal was measured in terms of BER, Q factor and system margin.
Abstract: This study aims to evaluate the diversity of microorganisms in filters PM2.5 and PM10; and determine the genotoxic and cytotoxic activity of the complex mixture present in PM2.5 filters used in the Aburrá Valley Air Quality Monitoring Network (Colombia). The research results indicate that particulate matter PM2.5 of different monitoring stations are bacteria; however, this study of detection of bacteria and their phylogenetic relationship is not complete evidence to connect the microorganisms with pathogenic or degrading activities of compounds present in the air. Additionally, it was demonstrated the damage induced by the particulate material in the cell membrane, lysosomal and endosomal membrane and in the mitochondrial metabolism; this damage was independent of the PM2.5 concentrations in almost all the cases.
Abstract: Collaborative filtering (CF) algorithm has been popularly used for recommender systems in both academic and practical applications. It basically generates recommendation results using users’ numeric ratings. However, the additional use of the information other than user ratings may lead to better accuracy of CF. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's review can be regarded as the new informative source for identifying user's preference with accuracy. Under this background, this study presents a hybrid recommender system that fuses CF and user's review mining. Our system adopts conventional memory-based CF, but it is designed to use both user’s numeric ratings and his/her text reviews on the items when calculating similarities between users.
Abstract: In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.
Abstract: This paper presents experimental results on testing the symbol-error-rate (SER) performance of quadrature amplitude modulation (QAM) systems employing symmetric pulse-shaping square-root (SR) filters designed by minimizing the roughness function and by minimizing the peak-to-average power ratio (PAR). The device used in the experiments is the 'bladeRF' software-defined-radio platform. PAR is a well-known measurement, whereas the roughness function is a concept for measuring the jitter-induced interference. The experimental results show that the system employing minimum-roughness pulse-shaping SR filters outperforms the system employing minimum-PAR pulse-shaping SR filters in the sense of SER performance.
Abstract: Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.
Abstract: In this work, the IMC-PID controller cascaded filter based on Internal Model Control (IMC) scheme is systematically proposed for the simplified decoupling control system. The simplified decoupling is firstly introduced for multivariable processes by using coefficient matching to obtain a stable, proper, and causal simplified decoupler. Accordingly, transfer functions of decoupled apparent processes can be expressed as a set of n equivalent independent processes and then derived as a ratio of the original open-loop transfer function to the diagonal element of the dynamic relative gain array. The IMC-PID controller in series with filter is then directly employed to enhance the overall performance of the decoupling control system while avoiding difficulties arising from properties inherent to simplified decoupling. Some simulation studies are considered to demonstrate the simplicity and effectiveness of the proposed method. Simulations were conducted by tuning various controllers of the multivariate processes with multiple time delays. The results indicate that the proposed method consistently performs well with fast and well-balanced closed-loop time responses.
Abstract: The thermoelectric properties of nano-scaled In2O3:Sn films deposited by spray pyrolysis are considered in the present report. It is shown that multicomponent In2O3:Sn-based films are promising material for the application in thermoelectric devices. It is established that the increase in the efficiency of thermoelectric conversion at CSn~5% occurred due to nano-scaled structure of the films studied and the effect of the grain boundary filtering of the low energy electrons. There are also analyzed the limitations that may appear during such material using in devices developed for the market of thermoelectric generators and refrigerators. Studies showed that the stability of nano-scaled film’s parameters is the main problem which can limit the application of these materials in high temperature thermoelectric converters.
Abstract: Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.
Abstract: In this paper, the analytical tuning rules of IMC-PID controller are presented for the multivariable Smith predictor that involved the ideal decoupling. Accordingly, the decoupler is first introduced into the multivariable Smith predictor control system by a well-known approach of ideal decoupling, which is compactly extended for general nxn multivariable processes and the multivariable Smith predictor controller is then obtained in terms of the multiple single-loop Smith predictor controllers. The tuning rules of PID controller in series with filter are found by using Maclaurin approximation. Many multivariable industrial processes are employed to demonstrate the simplicity and effectiveness of the presented method. The simulation results show the superior performances of presented method in compared with the other methods.
Abstract: Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.