Search results for: band pass filter

Authors: B. Ghebouli, M. A. Ghebouli, H. Choutri, M. Fatmi, L. Louail

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The structural, elastic, electronic and magnetic properties of the diluted magnetic semiconductors MnxCa1-xS in the rock-salt phase have been investigated using first-principles calculations. Features such as lattice constant, bulk modulus, elastic constants, spin-polarized band structure, total and local densities of states have been computed. We predict the values of the exchange constants and the band edge spin splitting of the valence and conduction bands. The hybridization between S-3p and Mn-3d produces small local magnetic moment on the nonmagnetic Ca and S sites. The ferromagnetism is induced due to the exchange splitting of S-3p and Mn-3d hybridized bands. The total magnetic moment per Mn of MnxCa1-xS is 4.4µB and is independent of the Mn concentration. The unfilled Mn -3d levels reduce the local magnetic moment of Mn from its free space charge value of 5µB to 4.4µB due to 3p–3d hybridization.

Keywords: semiconductors, Ab initio calculations, band-structure, magnetic properties

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Authors: L. Foudia, K. Haddadi, M. Reffas

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First principles study of structural, elastic, electronic and optical properties of the monoclinic perovskite type ScRhO₃ has been reported using the pseudo-potential plane wave method within the local density approximation. The calculated lattice parameters, including the lattice constants and angle β are in excellent agreement with the available experimental data, which proving the reliability of the chosen theoretical approach. Pressure dependence up to 20 GPa of the single crystal and polycrystalline elastic constants has been investigated in details using the strain-stress approach. The mechanical stability, ductility, average elastic wave velocity, Debye temperature and elastic anisotropy were also assessed. Electronic band structure and density of states (DOS) demonstrated its semiconducting nature showing a direct band gap of 1.38 eV. Furthermore, several optical properties, such as absorption coefficient, reflectivity, refractive index, dielectric function, optical conductivity and electron energy loss function have been calculated for radiation up to 40 eV.

Keywords: ab-initio, perovskite, DFT, band gap.

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Authors: Maryam Rasool, Farhan Munir, Fahad Nawaz, Saad Ahmad

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A patch antenna operating in the Ultra-Wide Band of frequency (3.1 GHz – 10.6 GHz) is designed with enhanced security from interference from other applications by incorporating the notching technique. Patch antennas in the Ultra-Wide Band are becoming widely famous due to their low power, light weight and high data rate capability. Micro strip patch antenna’s patch can be altered to increase its bandwidth and introduce UWB character in it. The designed antenna is a patch antenna consisting of a conductive sheet of metal mounted over a large sheet of metal called the ground plane with a substrate separating the two. Notched bands are public safety WLAN, WLAN and FSS. Different techniques used to implement the UWB antenna were individually implemented and there results were examined. V shaped patch was then chosen and modified to an arrow shaped patch to give the optimized results operating on the entire UWB region with considerable return loss. The frequency notch prevents the operation of the antenna at a particular range of frequency, hence minimizing interference from other systems. There are countless techniques for introducing the notch but we have used inverted C-shaped slots in the UWB patch to get the notch characteristics as output and also wavelength resonators to introduce notch in UWB band. The designed antenna is simulated in High Frequency Structural Simulator (HFSS) 13.0 by Ansoft.

Keywords: HFSS, Notch, UWB, WLAN

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Authors: Rahmat Purwoko, Bambang Riyanto Trilaksono

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This paper gives comparison of INS/GNSS architecture namely Loosely Coupled and Tightly Coupled using Hardware in the Loop Simulation in Guided Missile RKX-200 rocket model. INS/GNSS Tightly Coupled architecture requires pseudo-range, pseudo-range rate, and position and velocity of each satellite in constellation from GPS (Global Positioning System) measurement. The Loosely Coupled architecture use estimated position and velocity from GNSS receiver. INS/GNSS architecture also requires angular rate and specific force measurement from IMU (Inertial Measurement Unit). Loosely Coupled arhitecture designed using 15 states Kalman Filter and Tightly Coupled designed using 17 states Kalman Filter. Integration algorithm calculation using ECEF frame. Navigation System implemented Zedboard All Programmable SoC.

Keywords: kalman filter, loosely coupled, navigation system, tightly coupled

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Authors: Takashi Shimizu, Tomoaki Hashimoto

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Controlling the flow of fluids is a challenging problem that arises in many fields. Burgers’ equation is a fundamental equation for several flow phenomena such as traffic, shock waves, and turbulence. The optimal feedback control method, so-called model predictive control, has been proposed for Burgers’ equation. However, the model predictive control method is inapplicable to systems whose all state variables are not exactly known. In practical point of view, it is unusual that all the state variables of systems are exactly known, because the state variables of systems are measured through output sensors and limited parts of them can be only available. In fact, it is usual that flow velocities of fluid systems cannot be measured for all spatial domains. Hence, any practical feedback controller for fluid systems must incorporate some type of state estimator. To apply the model predictive control to the fluid systems described by Burgers’ equation, it is needed to establish a state estimation method for Burgers’ equation with limited measurable state variables. To this purpose, we apply unscented Kalman filter for estimating the state variables of fluid systems described by Burgers’ equation. The objective of this study is to establish a state estimation method based on unscented Kalman filter for Burgers’ equation. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: observer systems, unscented Kalman filter, nonlinear systems, Burgers' equation

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Authors: Cemil Turan, Mohammad Shukri Salman

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The convergence rate of the least-mean-square (LMS) algorithm deteriorates if the input signal to the filter is correlated. In a system identification problem, this convergence rate can be improved if the signal is white and/or if the system is sparse. We recently proposed a sparse transform domain LMS-type algorithm that uses a variable step-size for a sparse system identification. The proposed algorithm provided high performance even if the input signal is highly correlated. In this work, we investigate the performance of the proposed TD-LMS algorithm for a large number of filter tap which is also a critical issue for standard LMS algorithm. Additionally, the optimum value of the most important parameter is calculated for all experiments. Moreover, the convergence analysis of the proposed algorithm is provided. The performance of the proposed algorithm has been compared to different algorithms in a sparse system identification setting of different sparsity levels and different number of filter taps. Simulations have shown that the proposed algorithm has prominent performance compared to the other algorithms.

Keywords: adaptive filtering, sparse system identification, TD-LMS algorithm, VSSLMS algorithm

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Authors: Ankit Kargeti, Ravikant Shrivastav, Tabish Rasheed

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The electronic structure calculation for the nanoclusters of AsSiTeB/SiAsBTe quaternary semiconductor alloy belonging to the III-V Group elements was performed. Motivation for this research work was to look for accurate electronic and geometric data of small nanoclusters of AsSiTeB/SiAsBTe in the gaseous form. The two clusters, one in the linear form and the other in the bent form, were studied under the framework of Density Functional Theory (DFT) using the B3LYP functional and LANL2DZ basis set with the software packaged Gaussian 16. We have discussed the Optimized Energy, Frontier Orbital Energy Gap in terms of HOMO-LUMO, Dipole Moment, Ionization Potential, Electron Affinity, Binding Energy, Embedding Energy, Density of States (DoS) spectrum for both structures. The important findings of the predicted nanostructures are that these structures have wide band gap energy, where linear structure has band gap energy (Eg) value is 2.375 eV and bent structure (Eg) value is 2.778 eV. Therefore, these structures can be utilized as wide band gap semiconductors. These structures have high electron affinity value of 4.259 eV for the linear structure and electron affinity value of 3.387 eV for the bent structure form. It shows that electron acceptor capability is high for both forms. The widely known application of these compounds is in the light emitting diodes due to their wide band gap nature.

Keywords: density functional theory, DFT, density functional theory, nanostructures, HOMO-LUMO, density of states

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Authors: Zeid A. Alothman

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Silver nanoparticle (AgNP) has been synthesized using adrenaline. Adrenaline readily undergoes an autoxidation reaction in an alkaline medium with the dissolved oxygen to form adrenochrome, thus behaving as a mild reducing agent for the dissolved oxygen. This reducing behavior of adrenaline when employed to reduce Ag(+) ions yielded a large enhancement in the intensity of absorbance in the visible region. Transmission electron microscopy (TEM) and X-ray diffraction (XRD) studies have been performed to confirm the surface morphology of AgNPs. Further, the metallic nanoparticles with size greater than 2 nm caused a strong and broad absorption band in the UV-visible spectrum called surface plasmon band or Mie resonance. The formation of AgNPs caused the large enhancement in the absorbance values with λmax at 436 nm through the excitation of the surface plasmon band. The formation of AgNPs was adapted to for the quantitative assessment of adrenaline using spectrophotometry with lower detection limit and higher precision values.

Keywords: silver nanoparticle, adrenaline, XRD, TEM, analysis

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Authors: D. K. Maurya, S. M. Saini

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We investigate theoretically the electronic and optical properties of YNi₄Si-type HoNi₄Si compound from first principle calculations. Calculations are performed using full-potential augmented plane wave (FPLAPW) method in the frame work of density functional theory (DFT). The Coulomb corrected local-spin density approximation (LSDA+U) in the self-interaction correction (SIC) has been used for exchange-correlation potential. Analysis of the calculated band structure of HoNi₄Si compound demonstrates their metallic character. We found Ni-3d states mainly contribute to density of states from -5.0 eV to the Fermi level while the Ho-f states peak stands tall in comparison to the small contributions made by the Ni-d and Ho-d states above Fermi level, which is consistent with experiment, in HoNi4Si compound. Our calculated optical conductivity compares well with the experimental data and the results are analyzed in the light of band to band transitions.

Keywords: electronic properties, density of states, optical properties, LSDA+U approximation, YNi₄Si-type HoNi4Si compound

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Authors: Nimisha Elsa Koshy, Varun P. Gopi, V. I. Thajudin Ahamed

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The entire visualization of GastroIntestinal (GI) tract is not possible with conventional endoscopic exams. Wireless Capsule Endoscopy (WCE) is a low risk, painless, noninvasive procedure for diagnosing diseases such as bleeding, polyps, ulcers, and Crohns disease within the human digestive tract, especially the small intestine that was unreachable using the traditional endoscopic methods. However, analysis of massive images of WCE detection is tedious and time consuming to physicians. Hence, researchers have developed software methods to detect these diseases automatically. Thus, the effectiveness of WCE can be improved. In this paper, a novel textural feature extraction method is proposed based on Contourlet transform and Log Gabor filter to distinguish ulcer regions from normal regions. The results show that the proposed method performs well with a high accuracy rate of 94.16% using Support Vector Machine (SVM) classifier in HSV colour space.

Keywords: contourlet transform, log gabor filter, ulcer, wireless capsule endoscopy

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Authors: A. C. Sarmah

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The Al-MoO3-P-CdTe-Al MOS sandwich structures were fabricated by vacuum deposition method on cleaned glass substrates. Capacitance versus voltage measurements were performed at different frequencies and sweep rates of applied voltages for oxide and semiconductor films of different thicknesses. In the negative voltage region of the C-V curve a high differential capacitance of the semiconductor was observed and at high frequencies (<10 kHz) the transition from accumulation to depletion and further to deep depletion was observed as the voltage was swept from negative to positive. A study have been undertaken to determine the value of acceptor density and some depletion layer parameters such as depletion layer capacitance, depletion width, impurity concentration, flat band voltage, Debye length, flat band capacitance, diffusion or built-in-potential, space charge per unit area etc. These were determined from C-V measurements for different oxide and semiconductor thicknesses.

Keywords: debye length, depletion width, flat band capacitance, impurity concentration

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Authors: Dehini Rachid, Ferdi Brahim

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The shunt active power filter (SAPF) is not destined only to improve the power factor, but also to compensate the unwanted harmonic currents produced by nonlinear loads. This paper presents a SAPF with identification and control method based on artificial neural network (ANN). To identify harmonics, many techniques are used, among them the conventional p-q theory and the relatively recent one the artificial neural network method. It is difficult to get satisfied identification and control characteristics by using a normal (ANN) due to the nonlinearity of the system (SAPF + fast nonlinear load variations). This work is an attempt to undertake a systematic study of the problem to equip the (SAPF) with the harmonics identification and DC link voltage control method based on (ANN). The latter has been applied to the (SAPF) with fast nonlinear load variations. The results of computer simulations and experiments are given, which can confirm the feasibility of the proposed active power filter.

Keywords: artificial neural networks (ANN), p-q theory, harmonics, total harmonic distortion

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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The utilization of Large Eddy Simulation (LES) has been extensive in turbulence research. LES concentrates on resolving the significant grid-scale motions while representing smaller scales through subfilter-scale (SFS) models. The deconvolution model, among the available SFS models, has proven successful in LES of engineering and geophysical flows. Nevertheless, the thorough investigation of how sub-filter scale dynamics and filter anisotropy affect SFS modeling accuracy remains lacking. The outcomes of LES are significantly influenced by filter selection and grid anisotropy, factors that have not been adequately addressed in earlier studies. This study examines two crucial aspects of LES: Firstly, the accuracy of direct deconvolution models (DDM) is evaluated concerning sub-filter scale (SFS) dynamics across varying filter-to-grid ratios (FGR) in isotropic turbulence. Various invertible filters are employed, including Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The importance of FGR becomes evident as it plays a critical role in controlling errors for precise SFS stress prediction. When FGR is set to 1, the DDM models struggle to faithfully reconstruct SFS stress due to inadequate resolution of SFS dynamics. Notably, prediction accuracy improves when FGR is set to 2, leading to accurate reconstruction of SFS stress, except for cases involving Helmholtz I and II filters. Remarkably high precision, nearly 100%, is achieved at an FGR of 4 for all DDM models. Furthermore, the study extends to filter anisotropy and its impact on SFS dynamics and LES accuracy. By utilizing the dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with anisotropic filters, aspect ratios (AR) ranging from 1 to 16 are examined in LES filters. The results emphasize the DDM’s proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. Notably high correlation coefficients exceeding 90% are observed in the a priori study for the DDM’s reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as filter anisotropy increases. In the a posteriori analysis, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, including velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strainrate tensors, and SFS stress. It is evident that as filter anisotropy intensifies, the results of DSM and DMM deteriorate, while the DDM consistently delivers satisfactory outcomes across all filter-anisotropy scenarios. These findings underscore the potential of the DDM framework as a valuable tool for advancing the development of sophisticated SFS models for LES in turbulence research.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Takuro Kida, Yuichi Kida

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We show a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detailed algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory and it is indicated that introducing conversations with feedback does not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: signal prediction, pseudo inverse matrix, artificial intelligence, conditional optimization

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Authors: Yi Huang, Clemens Guehmann

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In order to monitor the thermal behavior of an asynchronous machine with squirrel cage rotor, a 9th-order extended Kalman filter (EKF) algorithm is implemented to estimate the temperatures of the stator windings, the rotor cage and the stator core. The state-space equations of EKF are established based on the electrical, mechanical and the simplified thermal models of an asynchronous machine. The asynchronous machine with simplified thermal model in Dymola is compiled as DymolaBlock, a physical model in MATLAB/Simulink. The coolant air temperature, three-phase voltages and currents are exported from the physical model and are processed by EKF estimator as inputs. Compared to the temperatures exported from the physical model of the machine, three parts of temperatures can be estimated quite accurately by the EKF estimator. The online EKF estimator is independent from the machine control algorithm and can work under any speed and load condition if the stator current is nonzero current system.

Keywords: asynchronous machine, extended Kalman filter, resistance, simulation, temperature estimation, thermal model

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Authors: Jongwoo Lee, Dae-Eun Kang, Sang-Young Park

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This study presents a precise relative navigational method for satellites flying in formation using laser-based intermittent measurement data. The measurement data for the relative navigation between two satellites consist of a relative distance measured by a laser instrument and relative attitude angles measured by attitude determination. The relative navigation solutions are estimated by both the Extended Kalman filter (EKF) and unscented Kalman filter (UKF). The solutions estimated by the EKF may become inaccurate or even diverge as measurement outage time gets longer because the EKF utilizes a linearization approach. However, this study shows that the UKF with the appropriate scaling parameters provides a stable and accurate relative navigation solutions despite the long measurement outage time and large initial error as compared to the relative navigation solutions of the EKF. Various navigation results have been analyzed by adjusting the scaling parameters of the UKF.

Keywords: satellite relative navigation, laser-based measurement, intermittent measurement, unscented Kalman filter

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Authors: Jin Xu

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5G network developers need to satisfy the necessary requirements of additional capacity from massive users and spectrally efficient wireless technologies. Therefore, the significant amount of underutilized spectrum in network is motivating operators to combine long-term evolution (LTE) with intelligent spectrum management technology. This new LTE intelligent spectrum management in unlicensed band (LTE-U) has the physical layer topology to access spectrum, specifically the 5-GHz band. We proposed a new intelligent cloud RAN for 5G.

Keywords: cloud radio access network, wireless network, cloud computing, multi-agent

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Authors: Ebrahim Izadi-Darbandi, Masoud Azad, Masumeh Dehghan

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In order to study the effects of nitrogen and phosphoruse management and wheat sowing method on wheat yield, two experiments was performed as factorial, based on completely randomized design with three replications at Research Farm, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran in 2009. In the first experiment nitrogen application rates (100kg ha-1, 200 kg ha-1, 300 kg ha-1), phosphorus application rates (100 kg ha-1, 200 kg ha-1) and two levels of their application methods (Broadcast and Band) were studied. The second experiment treatments included of wheat sowing methods (single-row with 30 cm distance and twine row on 60 cm width ridges), as main plots and nitrogen and phosphorus application methods (Broadcast and Band) as sub plots (150 kg ha-1). Phosphorus and nitrogen sources for fertilization at both experiment were respectively super phosphate, applied before wheat sowing and incorporated with soil and urea, applied in two phases (50% pre plant) and (50%) near wheat shooting. Results from first experiment showed that the effect of fertilizers application methods were significant (p≤0.01) on wheat yield increasing. Band application of phosphorus and nitrogen were increased biomass and seed yield of wheat with nine and 15% respectively compared to their broadcast application. The interaction between the effects of nitrogen and phosphorus application rate with phosphorus and nitrogen application methods, showed that band application of fertilizers and the rate of application of 200kg/ha phosphorus and 300kg/ha nitrogen were the best methods in wheat yield improvement. The second experiment also showed that the effect of wheat sowing method and fertilizers application methods were significant (p≤0.01) on wheat seed and biomass yield improvement. Wheat twine row on 60 cm width ridges sowing method, increased its biomass and seed yield for 22% and 30% respectively compared to single-row with 30 cm. Wheat sowing method and fertilizers application methods interaction indicated that band application of fertilizers and wheat twine row on 60 cm width ridges sowing method was the best treatment on winter wheat yield improvement. In conclusion these results indicated that nitrogen and phosphorus management in wheat and modifying wheat sowing method have important role in increasing fertilizers use efficiency.

Keywords: band application, broadcast application, rate of fertilizer application, wheat seed yield, wheat biomass yield

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Authors: Girmaye Abebe, Brook Lemma

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Adsorption of phosphorus (P as PO43-) in filter cake was studied to assess the media's capability in removing phosphorous from wastewaters. The composition of the filter cake that was generated from alum manufacturing process as waste residue has high amount of silicate from the complete silicate analysis of the experiment. Series of batches adsorption experiments were carried out to evaluate parameters that influence the adsorption capacity of PO43-. The factors studied include the effect of contact time, adsorbent dose, thermal pretreatment of the adsorbent, neutralization of the adsorbent, initial PO43- concentration, pH of the solution and effect of co-existing anions. Results showed that adsorption of PO43- is fairly rapid in first 5 min and after that it increases slowly to reach the equilibrium in about 1 h. The treatment efficiency of PO43- was increased with adsorbent extent. About 90% removal efficiency was increased within 1 h at an optimum adsorbent dose of 10 g/L for initial PO43- concentration of 10 mg/L. The amount of PO43- adsorbed increased with increasing initial PO43- concentration. Heat treatment and surface neutralization of the adsorbent did not improve the PO43- removal capacity and efficiency. The percentage of PO43- removal remains nearly constant within the pH range of 3-8. The adsorption data at ambient pH were well fitted to the Langmuir Isotherm and Dubinin–Radushkevick (D–R) isotherm model with a capacity of 25.84 and 157.55 mg/g of the adsorbent respectively. The adsorption kinetic was found to follow a pseudo-second-order rate equation with an average rate constant of 3.76 g.min−1.mg−1. The presence of bicarbonate or carbonate at higher concentrations (10–1000 mg/L) decreased the PO43- removal efficiency slightly while other anions (Cl-, SO42-, and NO3-) have no significant effect within the concentration range tested. The overall result shows that the filter cake is an efficient PO43- removing adsorbent against many parameters.

Keywords: wastewater, filter cake, adsorption capacity, phosphate (PO43-)

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Authors: Nuray Güy, Mahmut Özacar

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Semiconductor nanoparticles such as TiO₂ and ZnO as photocatalysts are very efficient catalysts for wastewater treatment by the chemical utilization of light energy, which is capable of converting the toxic and nonbiodegradable organic compounds into carbon dioxide and mineral acids. ZnO semiconductor has a wide bandgap energy of 3.37 eV and a relatively large exciton binding Energy (60 meV), thus can absorb only UV light with the wavelength equal to or less than 385 nm. It exhibits low efficiency under visible light illumination due to its wide band gap energy. In order to improve photocatalytic activity of ZnO under visible light, band gap of ZnO may be narrowed by doping such as N, C, S nonmetal ions and coupled two separate semiconductors possessing different energy levels for their corresponding conduction and valence bands. ZnS has a wider band gap (Eg=3.7 eV) than ZnO and generates electron–hole pairs by photoexcitation rapidly. In the present work, N doped ZnO/ZnS nano photocatalysts with visible-light response were synthesized by microwave-hydrothermal method using thiourea as N source. The prepared photocatalysts were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and UV–visible (UV–vis). The photocatalytic activities samples and undoped ZnO have been studied for the degradation of dye, and have also been compared with together.

Keywords: photocatalyst, synthesis, visible light, ZnO/ZnS

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Authors: Abdelkhalek Bouchikhi, Elyes Benmokhtar, Sebastien Saletzki

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The aeronautical field is experiencing issues with RF spectrum congestion due to the constant increase in the number of flights, aircrafts and telecom systems on board. In addition, these systems are bulky in size, weight and energy consumption. The cognitive radio helps particularly solving the spectrum congestion issue by its capacity to detect idle frequency channels then, allowing an opportunistic exploitation of the RF spectrum. The present work aims to propose a new use case for aeronautical spectrum sharing and to study the performances of three different detection techniques: energy detector, matched filter and cyclostationary detector within the aeronautical use case. The spectrum in the proposed cognitive radio is allocated dynamically where each cognitive radio follows a cognitive cycle. The spectrum sensing is a crucial step. The goal of the sensing is gathering data about the surrounding environment. Cognitive radio can use different sensors: antennas, cameras, accelerometer, thermometer, etc. In IEEE 802.22 standard, for example, a primary user (PU) has always the priority to communicate. When a frequency channel witch used by the primary user is idle, the secondary user (SU) is allowed to transmit in this channel. The Distance Measuring Equipment (DME) is composed of a UHF transmitter/receiver (interrogator) in the aircraft and a UHF receiver/transmitter on the ground. While the future cognitive radio will be used jointly to alleviate the spectrum congestion issue in the aeronautical field. LDACS, for example, is a good candidate; it provides two isolated data-links: ground-to-air and air-to-ground data-links. The first contribution of the present work is a strategy allowing sharing the L-band. The adopted spectrum sharing strategy is as follow: the DME will play the role of PU which is the licensed user and the LDACS1 systems will be the SUs. The SUs could use the L-band channels opportunely as long as they do not causing harmful interference signals which affect the QoS of the DME system. Although the spectrum sensing is a key step, it helps detecting holes by determining whether the primary signal is present or not in a given frequency channel. A missing detection on primary user presence creates interference between PU and SU and will affect seriously the QoS of the legacy radio. In this study, first brief definitions, concepts and the state of the art of cognitive radio will be presented. Then, a study of three communication channel detection algorithms in a cognitive radio context is carried out. The study is made from the point of view of functions, material requirements and signal detection capability in the aeronautical field. Then, we presented a modeling of the detection problem by three different methods (energy, adapted filter, and cyclostationary) as well as an algorithmic description of these detectors is done. Then, we study and compare the performance of the algorithms. Simulations were carried out using MATLAB software. We analyzed the results based on ROCs curves for SNR between -10dB and 20dB. The three detectors have been tested with a synthetics and real world signals.

Keywords: aeronautic, communication, navigation, surveillance systems, cognitive radio, spectrum sensing, software defined radio

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Authors: Muhamad Hafiz Ismail, Ahmad H., Nelfianty M. R.

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The longitudinal study is conducted to identify predictive factors of soccer talent among male players aged 14 to 17 years. Convenience sampling involving elite respondents (n=20) and sub-elite respondents (n=20) male soccer players. Descriptive statistics were reported as frequencies and percentages. The inferential statistical analysis is used to report the status of reliability, independent samples t-test, paired samples t-test, and multiple regression analysis. Generally, there are differences in mean of height, muscular strength, muscular endurance, cardiovascular endurance, task orientation, cognitive anxiety, self-confidence, juggling skills, short pass skills, long pass skills, dribbling skills, and shooting skills for 20 elite players and sub-elite players. Accordingly, there was a significant difference between pre and post-test for thirteen variables of height, weight, fat percentage, muscle strength, muscle endurance, cardiovascular endurance, flexibility, BMI, task orientation, juggling skills, short pass skills, a long pass skills, and dribbling skills. Based on the first predictive factors (physical), second predictive factors (fitness), third predictive factors (psychological), and fourth predictive factors (skills in playing football) pledged to the soccer talent; four multiple regression models were produced. The first predictive factor (physical) contributed 53.5 percent, supported by height and percentage of fat in soccer talents. The second predictive factor (fitness) contributed 63.2 percent and the third predictive factors (psychology) contributed 66.4 percent of soccer talent. The fourth predictive factors (skills) contributed 59.0 percent of soccer talent. The four multiple regression models could be used as a guide for talent scouting for soccer players of the future.

Keywords: soccer talent identification, fitness and physical test, soccer skills test, psychological test

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Authors: Martín Pratto Burgos

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The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

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Authors: Baso Hamdani, Arniati Massinai, Jamaluddin Jompa

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Coral diseases are one of the factors affect reef degradation. This research had analysed the progression rate, incidence, and prevalence of Black Band Disease (BBD) on stony coral (Pachyseris sp.) in relation to the environmental parameters (pH, nitrate, phospate, Dissolved Organic Matter (DOM), and turbidity). The incidence of coral disease was measured weekly for 6 weeks using Belt Transect Method. The progression rate of BBD was measured manually. Furthermore, the prevalence and incidence of BBD were calculated each colonies infected. The relationship between environmental parameters and the progression rate, prevalence and incidence of BBD was analysed by Principal Component Analysis (PCA). The results showed the average of progression rate is 0,07 ± 0,02 cm/ hari. The prevalence of BBD increased from 0,92% - 19,73% in 7 weeks observation with the average incidence of new infected colonies coral 0,2 - 0,65 colony/day The environment factors which important were pH, Nitrate, Phospate, DOM, and Turbidity.

Keywords: progression rate, incidence, prevalence, Black Band Disease, Barranglompo

Procedia PDF Downloads 630

Authors: Youtao Gao, Bingyu Jin, Tanran Zhao, Bo Xu

Abstract:

The history of satellite navigation can be dated back to the 1960s. From the U.S. Transit system and the Russian Tsikada system to the modern Global Positioning System (GPS) and the Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS), performance of satellite navigation has been greatly improved. Nowadays, the navigation accuracy and coverage of these existing systems have already fully fulfilled the requirement of near-Earth users, but these systems are still beyond the reach of deep space targets. Due to the renewed interest in space exploration, a novel high-precision satellite navigation system is becoming even more important. The increasing demand for such a deep space navigation system has contributed to the emergence of a variety of new constellation architectures, such as the Lunar Global Positioning System. Apart from a Walker constellation which is similar to the one adopted by GPS on Earth, a novel constellation architecture which consists of libration point satellites in the Earth-Moon system is also available to construct the lunar navigation system, which can be called accordingly, the libration point satellite navigation system. The concept of using Earth-Moon libration point satellites for lunar navigation was first proposed by Farquhar and then followed by many other researchers. Moreover, due to the special characteristics of Libration point orbits, an autonomous orbit determination technique, which is called ‘Liaison navigation’, can be adopted by the libration point satellites. Using only scalar satellite-to-satellite tracking data, both the orbits of the user and libration point satellites can be determined autonomously. In this way, the extensive Earth-based tracking measurement can be eliminated, and an autonomous satellite navigation system can be developed for future space exploration missions. The method of state estimate is an unnegligible factor which impacts on the orbit determination accuracy besides type of orbit, initial state accuracy and measurement accuracy. We apply the extended Kalman filter(EKF) and the unscented Kalman filter(UKF) to determinate the orbits of Lagrangian navigation satellites. The autonomous orbit determination errors are compared. The simulation results illustrate that UKF can improve the accuracy and z-axis convergence to some extent.

Keywords: extended Kalman filter, autonomous orbit determination, unscented Kalman filter, navigation constellation

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Authors: S. Bouhouche, R. Drai, J. Bast

Abstract:

This paper is concerned with a method for uncertainty evaluation of steel sample content using X-Ray Fluorescence method. The considered method of analysis is a comparative technique based on the X-Ray Fluorescence; the calibration step assumes the adequate chemical composition of metallic analyzed sample. It is proposed in this work a new combined approach using the Kalman Filter and Markov Chain Monte Carlo (MCMC) for uncertainty estimation of steel content analysis. The Kalman filter algorithm is extended to the model identification of the chemical analysis process using the main factors affecting the analysis results; in this case, the estimated states are reduced to the model parameters. The MCMC is a stochastic method that computes the statistical properties of the considered states such as the probability distribution function (PDF) according to the initial state and the target distribution using Monte Carlo simulation algorithm. Conventional approach is based on the linear correlation, the uncertainty budget is established for steel Mn(wt%), Cr(wt%), Ni(wt%) and Mo(wt%) content respectively. A comparative study between the conventional procedure and the proposed method is given. This kind of approaches is applied for constructing an accurate computing procedure of uncertainty measurement.

Keywords: Kalman filter, Markov chain Monte Carlo, x-ray fluorescence calibration and testing, steel content measurement, uncertainty measurement

Procedia PDF Downloads 266

Authors: Rimzhim Gupta, Bhanupriya Boruah, Jayant M. Modak, Giridhar Madras

Abstract:

Microbial contamination is one of the major concerns in the field of water treatment. AOP (advanced oxidation processes) is well-established method to resolve the issue of removal of contaminants in water. A Z-scheme composite g-C₃N₄/CuWO₄ was synthesized by sol-gel method for the photocatalytic inactivation of a mixed population of Gram-positive bacteria (S. aureus) and Gram-negative bacteria (E. coli). The photoinactivation was observed for different types of bacteria in the same medium together and individually in the absence of the nutrients. The lattice structures and phase purities were determined by X-ray diffraction. For morphological and topographical features, scanning electron microscopy and transmission electron microscopy analyses were carried out. The band edges of the semiconductor (valence band and conduction band) were determined by ultraviolet photoelectron microscopy. The lifetime of the charge carriers and band gap of the semiconductors were determined by time resolved florescence spectroscopy and diffused reflectance spectroscopy, respectively. The effect of weight ratio of C₃N₄ and CuWO₄ was observed by performing photocatalytic experiments. To investigate the exact mechanism and major responsible radicals for photocatalysis, scavenger studies were performed. The rate constants and order of the inactivation reactions were obtained by power law kinetics. For E. coli and S. aureus, the order of reaction and rate constants are 1.15, 0.9 and 1.39 ± 0.03 (CFU/mL)⁻⁰.¹⁵ h⁻¹, 47.95 ± 1.2 (CFU/mL)⁰.¹ h⁻¹, respectively.

Keywords: z-scheme, E. coli, S. aureus, sol-gel

Procedia PDF Downloads 132

Authors: Diego Aguirre, Olac Fuentes

Abstract:

In this paper, we present a taxonomy of weight initialization schemes used in deep learning. We survey the most representative techniques in each class and compare them in terms of overhead cost, convergence rate, and applicability. We also introduce a new weight initialization scheme. In this technique, we perform an initial feedforward pass through the network using an initialization mini-batch. Using statistics obtained from this pass, we initialize the weights of the network, so the following properties are met: 1) weight matrices are orthogonal; 2) ReLU layers produce a predetermined number of non-zero activations; 3) the output produced by each internal layer has a unit variance; 4) weights in the last layer are chosen to minimize the error in the initial mini-batch. We evaluate our method on three popular architectures, and a faster converge rates are achieved on the MNIST, CIFAR-10/100, and ImageNet datasets when compared to state-of-the-art initialization techniques.

Keywords: deep learning, image classification, supervised learning, weight initialization

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Authors: Ahmad H. Abdelgwad, Ahmed A. Nashat

Abstract:

Landmine detection is an important and yet challenging problem remains to be solved. Ground Penetrating Radar (GPR) is a powerful and rapidly maturing technology for subsurface threat identification. The detection methodology of GPR depends mainly on the contrast of the dielectric properties of the searched target and its surrounding soil. This contrast produces a partial reflection of the electromagnetic pulses that are being transmitted into the soil and then being collected by the GPR.  One of the most critical hardware components for the performance of GPR is the antenna system. The current paper explores the design and simulation of a pyramidal horn antenna operating at L-band frequencies (1- 2 GHz) to detect a landmine. A prototype model of the GPR system setup is developed to simulate full wave analysis of the electromagnetic fields in different soil types. The contrast in the dielectric permittivity of the landmine and the sandy soil is the most important parameter to be considered for detecting the presence of landmine. L-band horn antenna is proved to be well-versed in the investigation of landmine detection.

Keywords: full wave analysis, ground penetrating radar, horn antenna design, landmine detection

Procedia PDF Downloads 201

Authors: Harsh Vikram Singh, Ankur Rai, Anand Mohan

Abstract:

In this paper, we propose secure and robust data hiding algorithm based on DCT by Arnold transform and chaotic sequence. The watermark image is scrambled by Arnold cat map to increases its security and then the chaotic map is used for watermark signal spread in middle band of DCT coefficients of the cover image The chaotic map can be used as pseudo-random generator for digital data hiding, to increase security and robustness .Performance evaluation for robustness and imperceptibility of proposed algorithm has been made using bit error rate (BER), normalized correlation (NC), and peak signal to noise ratio (PSNR) value for different watermark and cover images such as Lena, Girl, Tank images and gain factor .We use a binary logo image and text image as watermark. The experimental results demonstrate that the proposed algorithm achieves higher security and robustness against JPEG compression as well as other attacks such as addition of noise, low pass filtering and cropping attacks compared to other existing algorithm using DCT coefficients. Moreover, to recover watermarks in proposed algorithm, there is no need to original cover image.

Keywords: data hiding, watermarking, DCT, chaotic sequence, arnold transforms

Procedia PDF Downloads 494