Search results for: fast Fourier transform algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6597

Search results for: fast Fourier transform algorithm

5817 Iron Oxide Nanoparticles: Synthesis, Properties, and Environmental Application

Authors: Shalini Rajput, Dinesh Mohan

Abstract:

Water is the most important and essential resources for existing of life on the earth. Water quality is gradually decreasing due to increasing urbanization and industrialization and various other developmental activities. It can pose a threat to the environment and public health therefore it is necessary to remove hazardous contaminants from wastewater prior to its discharge to the environment. Recently, magnetic iron oxide nanoparticles have been arise as significant materials due to its distinct properties. This article focuses on the synthesis method with a possible mechanism, structure and application of magnetic iron oxide nanoparticles. The various characterization techniques including X-ray diffraction, transmission electron microscopy, scanning electron microscopy with energy dispersive X-ray, Fourier transform infrared spectroscopy and vibrating sample magnetometer are useful to describe the physico-chemical properties of nanoparticles. Nanosized iron oxide particles utilized for remediation of contaminants from aqueous medium through adsorption process. Due to magnetic properties, nanoparticles can be easily separate from aqueous media. Considering the importance and emerging trend of nanotechnology, iron oxide nanoparticles as nano-adsorbent can be of great importance in the field of wastewater treatment.

Keywords: nanoparticles, adsorption, iron oxide, nanotechnology

Procedia PDF Downloads 552
5816 Hybrid Wavelet-Adaptive Neuro-Fuzzy Inference System Model for a Greenhouse Energy Demand Prediction

Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

Abstract:

Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

Procedia PDF Downloads 79
5815 Vision Based People Tracking System

Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

Abstract:

In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: camshift algorithm, computer vision, Kalman filter, object tracking

Procedia PDF Downloads 441
5814 Stochastic Variation of the Hubble's Parameter Using Ornstein-Uhlenbeck Process

Authors: Mary Chriselda A

Abstract:

This paper deals with the fact that the Hubble's parameter is not constant and tends to vary stochastically with time. This premise has been proven by converting it to a stochastic differential equation using the Ornstein-Uhlenbeck process. The formulated stochastic differential equation is further solved analytically using the Euler and the Kolmogorov Forward equations, thereby obtaining the probability density function using the Fourier transformation, thereby proving that the Hubble's parameter varies stochastically. This is further corroborated by simulating the observations using Python and R-software for validation of the premise postulated. We can further draw conclusion that the randomness in forces affecting the white noise can eventually affect the Hubble’s Parameter leading to scale invariance and thereby causing stochastic fluctuations in the density and the rate of expansion of the Universe.

Keywords: Chapman Kolmogorov forward differential equations, fourier transformation, hubble's parameter, ornstein-uhlenbeck process , stochastic differential equations

Procedia PDF Downloads 196
5813 Corrosion Inhibition of AA2024 Alloy with Graphene Oxide Derivative: Electrochemical and Surface Analysis

Authors: Nisrine Benzbiria, Abderrahmane Thoume, Mustapha Zertoubi

Abstract:

The goal of this research is to investigate the corrosion inhibition potential of functionalized graphene oxide (GO) with oxime derivative on AA2024-T3 surface in synthetic seawater. The utilization of functionalized graphene oxide is creating a category of corrosion inhibitors known as organically modified nanomaterials. In our work, the functionalization of GO by chalcone oxime enables graphene oxide to have enhanced water solubility and a good corrosion mitigation capacity. Fourier-transform infrared (FT-IR) spectroscopy was utilized to evaluate the main functional groups of the inhibitor. Electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization curves (PDP) showed that the inhibitor acts as a mixed-type inhibitor. The inhibitory efficiency (IE) improved as the concentration increased to a value of 96% after one hour of exposure to a medium containing 60 mg/L ppm of the inhibitor. According to thermodynamic calculations, the adsorption of the inhibitor on the AA2024-T3 surface in 3% NaCl followed the Langmuir isotherm. The formation of a barrier layer was further confirmed by surface analysis. The protective film prevented the alloy dissolution and limited the accessibility of attacking ions, as evinced by solution analysis techniques.

Keywords: AA2024-T3, NaCl, electrochemical methods, FT-IR, SEM/AFM, DFT, MC simulation

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5812 Sub-Pixel Mapping Based on New Mixed Interpolation

Authors: Zeyu Zhou, Xiaojun Bi

Abstract:

Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

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5811 A Fast Chemiresistive H₂ Gas Sensor Based on Sputter Grown Nanocrystalline P-TiO₂ Thin Film Decorated with Catalytic Pd-Pt Layer on P-Si Substrate

Authors: Jyoti Jaiswal, Satyendra Mourya, Gaurav Malik, Ramesh Chandra

Abstract:

In the present work, we have fabricated and studied a resistive H₂ gas sensor based on Pd-Pt decorated room temperature sputter grown nanocrystalline porous titanium dioxide (p-TiO₂) thin film on porous silicon (p-Si) substrate for fast H₂ detection. The gas sensing performance of Pd-Pt/p-TiO₂/p-Si sensing electrode towards H₂ gas under low (10-500 ppm) detection limit and operating temperature regime (25-200 °C) was discussed. The sensor is highly sensitive even at room temperature, with response (Ra/Rg) reaching ~102 for 500 ppm H₂ in dry air and its capability of sensing H₂ concentrations as low as ~10 ppm was demonstrated. At elevated temperature of 200 ℃, the response reached more than ~103 for 500 ppm H₂. Overall the fabricated resistive gas sensor exhibited high selectivity, good sensing response, and fast response/recovery time with good stability towards H₂.

Keywords: sputtering, porous silicon (p-Si), TiO₂ thin film, hydrogen gas sensor

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5810 Ge₁₋ₓSnₓ Alloys with Tuneable Energy Band Gap on GaAs (100) Substrate Manufactured by a Modified Magnetron Co-Sputtering

Authors: Li Qian, Jinchao Tong, Daohua Zhang, Weijun Fan, Fei Suo

Abstract:

Photonic applications based on group IV semiconductors have always been an interest but also a challenge for the research community. We report manufacturing group IV Ge₁₋ₓSnₓ alloys with tuneable energy band gap on (100) GaAs substrate by a modified radio frequency magnetron co-sputtering. Images were taken by atomic force microscope, and scanning electron microscope clearly demonstrates a smooth surface profile, and Ge₁₋ₓSnₓ nano clusters are with the size of several tens of nanometers. Transmittance spectra were measured by Fourier Transform Infrared Spectroscopy that showed changing energy gaps with the variation in elementary composition. Calculation results by 8-band k.p method are consistent with measured gaps. Our deposition system realized direct growth of Ge₁₋ₓSnₓ thin film on GaAs (100) substrate by sputtering. This simple deposition method was modified to be able to grow high-quality photonic materials with tuneable energy gaps. This work provides an alternative and successful method for fabricating Group IV photonic semiconductor materials.

Keywords: GeSn, crystal growth, sputtering, photonic

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5809 Implementation of a Predictive DTC-SVM of an Induction Motor

Authors: Chebaani Mohamed, Gplea Amar, Benchouia Mohamed Toufik

Abstract:

Direct torque control is characterized by the merits of fast response, simple structure and strong robustness to the motor parameters variations. This paper proposes the implementation of DTC-SVM of an induction motor drive using Predictive controller. The principle of the method is explained and the system mathematical description is provided. The derived control algorithm is implemented both in the simulation software MatLab/Simulink and on the real induction motor drive with dSPACE control system. Simulated and measured results in steady states and transients are presented.

Keywords: induction motor, DTC-SVM, predictive controller, implementation, dSPACE, Matlab, Simulink

Procedia PDF Downloads 507
5808 Titanium Dioxide Modified with Glutathione as Potential Drug Carrier with Reduced Toxic Properties

Authors: Olga Długosz, Jolanta Pulit-Prociak, Marcin Banach

Abstract:

The paper presents a process to obtain glutathione-modified titanium oxide nanoparticles. The processes were carried out in a microwave radiation field. The influence of the molar ratio of glutathione to titanium oxide and the effect of the fold of NaOH vs. stoichiometric amount on the size of the formed TiO₂ nanoparticles was determined. The physicochemical properties of the obtained products were evaluated using dynamic light scattering (DLS), transmission electron microscope- energy-dispersive X-ray spectroscopy (TEM-EDS), low-temperature nitrogen adsorption method (BET), X-Ray Diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) microscopy methods. The size of TiO₂ nanoparticles was characterized from 30 to 336 nm. The release of titanium ions from the prepared products was evaluated. These studies were carried out using different media in which the powders were incubated for a specific time. These were water, SBF and Ringer's solution. The release of titanium ions from modified products is weaker compared to unmodified titanium oxide nanoparticles. The reduced release of titanium ions may allow the use of such modified materials as substances in drug delivery systems.

Keywords: titanium dioxide, nanoparticles, drug carrier, glutathione

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5807 Titanium Dioxide Modified with Glutathione as Potential Drug Carrier with Reduced Toxic Properties

Authors: Olga Długosz, Jolanta Pulit-Prociak, Marcin Banach

Abstract:

The paper presents a process to obtain glutathione-modified titanium oxide nanoparticles. The processes were carried out in a microwave radiation field. The influence of the molar ratio of glutathione to titanium oxide and the effect of the fold of NaOH vs. stoichiometric amount on the size of the formed TiO₂ nanoparticles was determined. The physicochemical properties of the obtained products were evaluated using dynamic light scattering (DLS), transmission electron microscope- energy-dispersive X-ray spectroscopy (TEM-EDS), low-temperature nitrogen adsorption method (BET), X-Ray Diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR) microscopy methods. The size of TiO₂ nanoparticles was characterized from 30 to 336 nm. The release of titanium ions from the prepared products was evaluated. These studies were carried out using different media in which the powders were incubated for a specific time. These were: water, SBF, and Ringer's solution. The release of titanium ions from modified products is weaker compared to unmodified titanium oxide nanoparticles. The reduced release of titanium ions may allow the use of such modified materials as substances in drug delivery systems.

Keywords: titanium dioxide, nanoparticles, drug carrier, glutathione

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5806 Hydrodynamic Behavior Study of Fast Mono Hull and Catamaran Vessels in Calm Waters Using Free Surface Flow Analysis

Authors: Mohammad Ali Badri, Pouya Molana, Amin Rezvanpour

Abstract:

In this paper, planning catamaran and mono-hull vessels resistance and trim in calm waters were considered. Hydrodynamic analysis of fast mono-hull planning vessel was also investigated. In order to hull form geometry optimization, numerical methods of different parameters were used for this type of vessels. Hull material was selected in carbon fiber composite. Exact architectural aspects were specified and stability calculations were performed as well. Hydrodynamic calculations to extract the resistance force using semi-analytical methods and numerical modeling were carried out. Free surface numerical analysis of vessel in designed draft using finite volume method and double phase were evaluated and verified by experimental tests.

Keywords: fast vessel, hydrostatic and hydrodynamic optimization, free surface flow, computational fluid dynamics

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5805 Rheological and Morphological Properties of Investment Casting Pattern Material Based on Paraffin Wax Fortified with Linear Low-Density Polyethylene and Filled with Poly Methyl Methacrylate

Authors: Robert Kimutai Tewo, Hilary Limo Rutto, Tumisang Seodigeng

Abstract:

The rheological and morphological properties of paraffin wax, linear low-density polyethylene (LLDPE), and poly (methyl methacrylate) (PMMA) microbeads formulations were prepared via an extrusion process. The blends were characterized by rheometry, scanning electron microscopy (SEM), and Fourier transform infrared (FTIR) spectroscopy. The results indicated that the viscosity of the blends increased as compared to that of neat wax. SEM confirmed that LLDPE alters the wax crystal habit at higher concentrations. The rheological experimental data fitted with predicted data using the modified Krieger and Dougherty expression. The SEM micrograph of wax/LLDPE/PMMA revealed a near-perfect spherical nature for the filler particles in the wax/EVA polymer matrix. The FT-IR spectra show the deformation vibrations stretch of a long-chain aliphatic hydrocarbon (C-H) and also the presence of carbonyls absorption group denoted by -C=O- stretch.

Keywords: investment casting pattern, paraffin wax, LLDPE, PMMA, rheological properties, modified Krieger and Dougherty expression

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5804 Efficacy of TiO₂ in the Removal of an Acid Dye by Photo Catalytic Degradation

Authors: Laila Mahtout, Kerami Ahmed, Rabhi Souhila

Abstract:

The objective of this work is to reduce the impact on the environment of an acid dye (Black Eriochrome T) using catalytic photo-degradation in the presence of the semiconductor powder (TiO₂) previously characterized. A series of tests have been carried out in order to demonstrate the influence of certain parameters on the degree of dye degradation by titanium dioxide in the presence of UV rays, such as contact time, the powder mass and the pH of the solution. X-ray diffraction analysis of the powder showed that the anatase structure is predominant and the rutile phase is presented by peaks of low intensity. The various chemical groups which characterize the presence of the bands corresponding to the anatase and rutile form and other chemical functions have been detected by the Fourier Transform Infrared spectroscopy. The photo degradation of the NET by TiO₂ is very interesting because it gives encouraging results. The study of photo-degradation at different concentrations of the dye showed that the lower concentrations give better removal rates. The degree of degradation of the dye increases with increasing pH; it reaches the maximum value at pH = 9. The ideal mass of TiO₂ which gives the high removal rate is 1.2 g/l. Thermal treatment of TiO₂ with the addition of CuO with contents of 5%, 10%, and 15% respectively gives better results of degradation of the NET dye. The high percentage of elimination is observed at a CuO content of 15%.

Keywords: acid dye, ultraviolet rays, degradation, photocatalyse

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5803 Design an Algorithm for Software Development in CBSE Envrionment Using Feed Forward Neural Network

Authors: Amit Verma, Pardeep Kaur

Abstract:

In software development organizations, Component based Software engineering (CBSE) is emerging paradigm for software development and gained wide acceptance as it often results in increase quality of software product within development time and budget. In component reusability, main challenges are the right component identification from large repositories at right time. The major objective of this work is to provide efficient algorithm for storage and effective retrieval of components using neural network and parameters based on user choice through clustering. This research paper aims to propose an algorithm that provides error free and automatic process (for retrieval of the components) while reuse of the component. In this algorithm, keywords (or components) are extracted from software document, after by applying k mean clustering algorithm. Then weights assigned to those keywords based on their frequency and after assigning weights, ANN predicts whether correct weight is assigned to keywords (or components) or not, otherwise it back propagates in to initial step (re-assign the weights). In last, store those all keywords into repositories for effective retrieval. Proposed algorithm is very effective in the error correction and detection with user base choice while choice of component for reusability for efficient retrieval is there.

Keywords: component based development, clustering, back propagation algorithm, keyword based retrieval

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5802 Short Term Distribution Load Forecasting Using Wavelet Transform and Artificial Neural Networks

Authors: S. Neelima, P. S. Subramanyam

Abstract:

The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.

Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)

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5801 Identification and Quantification of Acid Sites of M(X)X Zeolites (M= Cu2+ and/or Zn2+,X = Level of Exchange): An In situ FTIR Study Using Pyridine Adsorption/Desorption

Authors: H. Hammoudi, S. Bendenia, I. Batonneau-Gener, J. Comparot, K. Marouf-Khelifa, A. Khelifa

Abstract:

X zeolites were prepared by ion-exchange with Cu2+ and/or Zn2+ cations, at different concentrations of the exchange solution, and characterised by thermal analysis and nitrogen adsorption. The acidity of the samples was investigated by pyridine adsorption–desorption followed by in situ Fourier transform infrared (FTIR) spectroscopy. Desorption was carried out at 150, 250 and 350 °C. The objective is to estimate the nature and concentration of acid sites. A comparison between the binary (Cu(x)X, Zn(x)X) and ternary (CuZn(x)X) exchanges was also established (x = level of exchange) through the Cu(43)X, Zn(48)X and CuZn(50)X samples. Lewis acidity decreases overall with desorption temperature and the level of exchange. As the latter increases, there is a conversion of some Lewis sites into those of Brønsted during thermal treatment. In return, the concentration of Brønsted sites increases with the degree of exchange. The Brønsted acidity of CuZn(50)X at 350 °C is more important than the sum of those of Cu(43)X and Zn(48)X. The found values were 73, 32 and 15 μmol g-1, respectively. Besides, the concentration of Brønsted sites for CuZn(50)X increases with desorption temperature. These features indicate the presence of a synergistic effect amplifying the strength of these sites when Cu2+ and Zn2+ cations compete for the occupancy of sites distributed inside zeolitic cavities.

Keywords: acidity, adsorption, pyridine, zeolites

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5800 Characterizing of CuO Incorporated CMOS Dielectric for Fast Switching System

Authors: Nissar Mohammad Karim, Norhayati Soin

Abstract:

To ensure fast switching in high-K incorporated Complementary Metal Oxide Semiconductor (CMOS) transistors, the results on the basis of d (NBTI) by incorporating SiO2 dielectric with aged samples of CuO sol-gels have been reported. Precursor ageing has been carried out for 4 days. The minimum obtained refractive index is 1.0099 which was found after 3 hours of adhesive UV curing. Obtaining a low refractive index exhibits a low dielectric constant and hence a faster system.

Keywords: refractive index, sol-gel, precursor ageing, metallurgical and materials engineering

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5799 Efficiency of Grover’s Search Algorithm Implemented on Open Quantum System in the Presence of Drive-Induced Dissipation

Authors: Nilanjana Chanda, Rangeet Bhattacharyya

Abstract:

Grover’s search algorithm is the fastest possible quantum mechanical algorithm to search a certain element from an unstructured set of data of N items. The algorithm can determine the desired result in only O(√N) steps. It has been demonstrated theoretically and experimentally on two-qubit systems long ago. In this work, we investigate the fidelity of Grover’s search algorithm by implementing it on an open quantum system. In particular, we study with what accuracy one can estimate that the algorithm would deliver the searched state. In reality, every system has some influence on its environment. We include the environmental effects on the system dynamics by using a recently reported fluctuation-regulated quantum master equation (FRQME). We consider that the environment experiences thermal fluctuations, which leave its signature in the second-order term of the master equation through its appearance as a regulator. The FRQME indicates that in addition to the regular relaxation due to system-environment coupling, the applied drive also causes dissipation in the system dynamics. As a result, the fidelity is found to depend on both the drive-induced dissipative terms and the relaxation terms, and we find that there exists a competition between them, leading to an optimum drive amplitude for which the fidelity becomes maximum. For efficient implementation of the search algorithm, precise knowledge of this optimum drive amplitude is essential.

Keywords: dissipation, fidelity, quantum master equation, relaxation, system-environment coupling

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5798 An Improved Cuckoo Search Algorithm for Voltage Stability Enhancement in Power Transmission Networks

Authors: Reza Sirjani, Nobosse Tafem Bolan

Abstract:

Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability

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5797 Removal of Nickel and Zinc Ions from Aqueous Solution by Graphene Oxide and Graphene Oxide Functionalized Glycine

Authors: M. Rajabi, O. Moradi

Abstract:

In this study, removal of Nickel and Zinc by graphene oxide and functionalized graphene oxide–gelaycin surfaces was examined. Amino group was added to surface of graphene oxide to produced functionalized graphene oxide–gelaycin. Effect of contact time and initial concentration of Ni (II) and Zn(II) ions were studied. Results showed that with increase of initial concentration of Ni (II) and Zn(II) adsorption capacity was increased. After 50 min has not a large change at adsorption capacity therefore, 50 min was selected as optimaze time. Scanning electron microscope (SEM) and fourier transform infrared (FT-IR) spectroscopy spectra used for the analysis confirmed the successful fictionalization of the Graphene oxide surface. Adsorption experiments of Ni (II) and Zn(II) ions graphene oxide and functionalized graphene oxide–gelaycin surfaces fixed at 298 K and pH=6. The Pseudo Firs-order and the Pseudo Second-order (types I, II, III and IV) kinetic models were tested for adsorption process and results showed that the kinetic parameters best fits with to type (I) of pseudo-second-order model because presented low X2 values and also high R2 values.

Keywords: graphene oxide, gelaycin, nickel, zinc, adsorption, kinetic, graphene oxide, gelaycin, nickel, zinc, adsorption, kinetic

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5796 Two Coordination Polymers Synthesized from Various N-Donor Clusters Spaced by Terephtalic Acid for Efficient Photocatalytic Degradation of Ibuprofen in Water under Solar and Artificial Irradiation

Authors: Amina Adala, Nadra Debbache, Tahar Sehili

Abstract:

Coordination polymers and uniformly {[Zn(II)(BIPY)(Pht)]n} (1), {[Zn (HYD)(Pht)]n} (2) (BIPY = 4,4’ bipyridine, Pht = terephtalic acid, HYD = 8-hydroxyquinoline) have been successfully synthesized by a hydrothermal process using aqueous zinc solution. The as-prepared compounds phases were characterized by X-ray diffraction (XRD), Fourier Transform Infrared spectroscopy, UV-visible spectroscopy, thermogravimetric analysis (TGA), and the electrochemistry study by the voltammetry cyclic. The results showed a crystalline phase for CP1 however, CP2 requires recrystallization; the FTIR showed the presence of characteristic bands of all ligands; besides that, TGA shows thermal stability up to 300°C. The electrochemistry study showed a good charge transfer between the ligands and Zn metal for the two components. UV-Vis measurement showed strong absorption in a wide range from UV to visible light with a band gap of 2.69 eV for CP1 and 2.56 eV for CP2, smaller than that of ZnO. This represents an alternative to using ZnO. The Ibuprofen IBP decomposition kinetics of 5.10⁻⁵ mol.L⁻¹ under solar and artificial light were studied for different irradiation conditions. Good photocatalytic properties were observed due to their high surface area.

Keywords: metal-organic frameworks, photocatalysis, photodegradation, organic pollutant, ibuprofen

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5795 Diffusion MRI: Clinical Application in Radiotherapy Planning of Intracranial Pathology

Authors: Pomozova Kseniia, Gorlachev Gennadiy, Chernyaev Aleksandr, Golanov Andrey

Abstract:

In clinical practice, and especially in stereotactic radiosurgery planning, the significance of diffusion-weighted imaging (DWI) is growing. This makes the existence of software capable of quickly processing and reliably visualizing diffusion data, as well as equipped with tools for their analysis in terms of different tasks. We are developing the «MRDiffusionImaging» software on the standard C++ language. The subject part has been moved to separate class libraries and can be used on various platforms. The user interface is Windows WPF (Windows Presentation Foundation), which is a technology for managing Windows applications with access to all components of the .NET 5 or .NET Framework platform ecosystem. One of the important features is the use of a declarative markup language, XAML (eXtensible Application Markup Language), with which you can conveniently create, initialize and set properties of objects with hierarchical relationships. Graphics are generated using the DirectX environment. The MRDiffusionImaging software package has been implemented for processing diffusion magnetic resonance imaging (dMRI), which allows loading and viewing images sorted by series. An algorithm for "masking" dMRI series based on T2-weighted images was developed using a deformable surface model to exclude tissues that are not related to the area of interest from the analysis. An algorithm of distortion correction using deformable image registration based on autocorrelation of local structure has been developed. Maximum voxel dimension was 1,03 ± 0,12 mm. In an elementary brain's volume, the diffusion tensor is geometrically interpreted using an ellipsoid, which is an isosurface of the probability density of a molecule's diffusion. For the first time, non-parametric intensity distributions, neighborhood correlations, and inhomogeneities are combined in one segmentation of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) algorithm. A tool for calculating the coefficient of average diffusion and fractional anisotropy has been created, on the basis of which it is possible to build quantitative maps for solving various clinical problems. Functionality has been created that allows clustering and segmenting images to individualize the clinical volume of radiation treatment and further assess the response (Median Dice Score = 0.963 ± 0,137). White matter tracts of the brain were visualized using two algorithms: deterministic (fiber assignment by continuous tracking) and probabilistic using the Hough transform. The proposed algorithms test candidate curves in the voxel, assigning to each one a score computed from the diffusion data, and then selects the curves with the highest scores as the potential anatomical connections. White matter fibers were visualized using a Hough transform tractography algorithm. In the context of functional radiosurgery, it is possible to reduce the irradiation volume of the internal capsule receiving 12 Gy from 0,402 cc to 0,254 cc. The «MRDiffusionImaging» will improve the efficiency and accuracy of diagnostics and stereotactic radiotherapy of intracranial pathology. We develop software with integrated, intuitive support for processing, analysis, and inclusion in the process of radiotherapy planning and evaluating its results.

Keywords: diffusion-weighted imaging, medical imaging, stereotactic radiosurgery, tractography

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5794 Water Equivalent from the Point of View of Fast Neutron Removal Cross-Section

Authors: Mohammed Alrajhi

Abstract:

Radiological properties of gel dosimeters and phantom materials are often evaluated in terms of effective atomic number, electron density, photon mass attenuation coefficient, photon mass energy absorption coefficient and total stopping power of electrons. To evaluate the water equivalence of such materials for fast neutron attenuation 19 different types of gel dosimeters and phantom materials were considered. Macroscopic removal cross-sections for fast neutrons (ΣR cm-1) have been calculated for a range of ferrous-sulphate and polymeric gel dosimeters using Nxcom Program. The study showed that the value of ΣR/ρ (cm2.g-1) for all polymer gels were in close agreement (1.5- 2.8%) with that of water. As such, the slight differences in ΣR/ρ between water and gels are small and may be considered negligible. Also, the removal cross-section of the studied phantom materials were very close (~ ±1.5%) to that of water except bone (cortical) which had about 38% variation. Finally, the variation of removal cross-section with hydrogen content was studied.

Keywords: cross-section, neutron, photon, coefficient, mathematics

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5793 Modern Detection and Description Methods for Natural Plants Recognition

Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

Abstract:

Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT

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5792 Poly (Acrylonitrile-Co-Methylacrylate)/Poly N-Methyl Pyrrole and Pyrrole Nanocomposites

Authors: Fatma Zehra Engin Sagirli, Eyup Sabri Kayali, A. Sezai Sarac

Abstract:

In this study, Poly (acrylonitrile-co-methylacrylate)/N-Methyl Pyrrole and Pyrrole ([P(AN-co-MA)]-NMPy and [P(AN-co-MA)]-PPy) core–shell nanoparticles were obtained by in situ emulsion polymerization in the presence of Sodium dodecyl benzene sulfonate and sodium dodecyl sulfate (SDBS and SDS) by using ammonium per sulphate in the aqueous medium. The spectroscopic characterizations during the formation of nanocomposites were studied using Attenuated total reflectance Fourier transform infrared (FTIR-ATR) spectroscopy, ultraviolet–visible spectrophotometer (Uv-Vis). Electrical conductivity of the emulsion solution was measured by Conductivity Meter from aqueous sample solution. Also, yield of the powder nanocomposites was measured. SDBS and SDS used for investigation of surfactant effect on yield, electrical conductivity and polymerization process. Determination of polymerization yield, (FTIR-ATR) and (Uv-Vis) prove that the SDBS surfactant become more incorporated into the conducting polymers and there is strong interaction between the [P(AN-co-MA)]-PPy derivatives which prepared by these surfactants. The similar inclusion of SDS into conducting polymers was not observed, there is a remarkable difference at nanocomposites which prepared with SDS.

Keywords: nanocomposites, core-shell, pyrole, surfactant

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5791 Meta-Learning for Hierarchical Classification and Applications in Bioinformatics

Authors: Fabio Fabris, Alex A. Freitas

Abstract:

Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

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5790 Chitosan Magnetic Nanoparticles and Its Analytical Applications

Authors: Eman Alzahrani

Abstract:

Efficient extraction of proteins by removing interfering materials is necessary in proteomics, since most instruments cannot handle such contaminated sample matrices directly. In this study, chitosan-coated magnetic nanoparticles (CS-MNPs) for purification of myoglobin were successfully fabricated. First, chitosan (CS) was prepared by a deacetylation reaction during its extraction from shrimp-shell waste. Second, magnetic nanoparticles (MNPs) were synthesised, using the coprecipitation method, from aqueous Fe2+ and Fe3+ salt solutions by the addition of a base under an inert atmosphere, followed by modification of the surface of MNPs with chitosan. The morphology of the formed nanoparticles, which were about 23 nm in average diameter, was observed by transmission electron microscopy (TEM). In addition, nanoparticles were characterised using X-ray diffraction patterns (XRD), which showed the naked magnetic nanoparticles have a spinel structure and the surface modification did not result in phase change of the Fe3O4. The coating of MNPs was also demonstrated by scanning electron microscopy (SEM) analysis, energy dispersive analysis of X-ray spectroscopy (EDAX), and Fourier transform infrared (FT-IR) spectroscopy. The adsorption behaviour of MNPs and CS-MNPs towards myoglobin was investigated. It was found that the difference in adsorption capacity between MNPs and CS-MNPs was larger for CS-MNPs. This result makes CS-MNPs good adsorbents and attractive for using in protein extraction from biological samples.

Keywords: chitosan, magnetic nanoparticles, coprecipitation, adsorption

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5789 Carbon-Doped TiO2 Nanofibers Prepared by Electrospinning

Authors: ChoLiang Chung, YuMin Chen

Abstract:

C-doped TiO2 nanofibers were prepared by electrospinning successfully. Different amounts of carbon were added into the nanofibers by using chitosan, aiming to shift the wave length that is required to excite the photocatalyst from ultraviolet light to visible light. Different amounts of carbon and different atmosphere fibers were calcined at 500oC, and the optical characteristic of C-doped TiO2 nanofibers had been changed. characterizes of nanofibers were identified by X-Ray Diffraction (XRD), Field Emission Scanning Electron Microscope (FE-SEM), UV-vis, Atomic Force Microscope (AFM), and Fourier Transform Infrared Spectroscopy (FTIR). The XRD is used to identify the phase composition of nanofibers. The morphology of nanofibers were explored by FE-SEM and AFM. Optical characteristics of absorption were measured by UV-Vis. Three dimension surface images of C-doped TiO2 nanofibers revealed different effects of processing. The results of XRD showed that the phase of C-doped TiO2 nanofibers transformed to rutile phase and anatase phase successfully. The results of AFM showed that the surface morphology of nanofibers became smooth after high temperature treatment. Images from FE-SEM revealed the average size of nanofibers. UV-vis results showed that the band-gap of TiO2 were reduced. Finally, we found out C-doped TiO2 nanofibers can change countenance of nanofiber and make it smoother.

Keywords: carbon, TiO2, chitosan, electrospinning

Procedia PDF Downloads 253
5788 Impact of Gd³⁺ Substitution on Structural, Optical and Magnetic Properties of ZnFe₂O₄ Nanoparticles

Authors: Raghvendra Singh Yadav, Ivo Kuřitka, Jarmila Vilcakova, Pavel Urbanek, Michal Machovsky, David Skoda

Abstract:

In this report, the impact of Gd³⁺ substitution in ZnFe₂O₄ spinel ferrite nanoparticles on structural, optical and magnetic properties was investigated. ZnFe₂₋ₓGdₓO₄ (x=0.00, 0.05, 0.10, 0.15, 0.20) nanoparticles were synthesized by honey-mediated sol-gel combustion method. X-ray diffraction, Raman Spectroscopy and Fourier Transform Infrared Spectroscopy confirmed the formation of cubic spinel ferrite crystal structure. The morphology and elemental analysis were studied using field emission scanning electron microscopy (FE-SEM) and energy dispersive X-ray spectroscopy, respectively. UV-Visible reflectance spectroscopy revealed band gap variation with concentration of Gd³⁺ substitution in ZnFe₂O₄ nanoparticles. Magnetic property was studied using vibrating sample magnetometer at room temperature. The synthesized spinel ferrite nanoparticles showed ferromagnetic behaviour. The evaluated magnetic parameters such as saturation magnetization, coercivity and remanence showed variation with Gd³⁺ substitution in spinel ferrite nanoparticles. This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic – Program NPU I (LO1504).

Keywords: sol-gel combustion method, nanoparticles, magnetic property, optical property

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