Search results for: fast Fourier transform

Authors: Anderson Rocha, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar

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Machine vision has been widely used in recent years in agriculture, as a tool to promote the automation of processes and increase the levels of productivity. The aim of this work is the development of a path recognition algorithm based on image processing to guide a terrestrial robot in-between tree rows. The proposed algorithm was developed using the software MATLAB, and it uses several image processing operations, such as threshold detection, morphological erosion, histogram equalization and the Hough transform, to find edge lines along tree rows on an image and to create a path to be followed by a mobile robot. To develop the algorithm, a set of images of different types of orchards was used, which made possible the construction of a method capable of identifying paths between trees of different heights and aspects. The algorithm was evaluated using several images with different characteristics of quality and the results showed that the proposed method can successfully detect a path in different types of environments.

Keywords: agricultural mobile robot, image processing, path recognition, hough transform

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Authors: Mariame Taibi, Marouane Aouiji, Rachid Bengueddour

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The Moroccan coastline is particularly rich in algae and constitutes a reserve of species with considerable economic, social and ecological potential. This work focuses on the research and characterization of algae bioactive compounds that can be used in pharmacology or phytopathology. The biochemical composition of the green alga Ulva lactuca (Ulvophyceae) was studied by determining the content of moisture, ash, phenols, flavonoids, total tannins, and chlorophyll. Seven solvents: distilled water, methanol, ethyl acetate, chloroform, benzene, petroleum ether, and hexane, were tested for their effectiveness in recovering chemical compounds. The identification of functional groupings, as well as the bioactive chemical compounds, was determined by FT-IR and GC-MS. The moisture content of the alga was 77%, while the ash content was 15%. Phenol content differed from one solvent studied to another, while chlorophyll a, b, and total chlorophyll were determined at 14%, 9.52%, and 25%, respectively. Carotenoid was present in a considerable amount (8.17%). The experimental results show that methanol is the most effective solvent for recovering bioactive compounds, followed by water. Moreover, the green alga Ulva lactuca is characterized by a high level of total polyphenols (45±3.24 mg GAE/gDM), average levels of total tannins and flavonoids (22.52±8.23 mg CE/gDM, 15.49±0.064 mg QE/gDM) respectively. The results of Fourier transform infrared spectroscopy (FT-IR) confirmed the presence of alcohol/phenol and amide functions in Ulva lactuca. The GC-MS analysis gave precisely the compounds contained in the various extracts, such as phenolic compounds, fatty acids, terpenoids, alcohols, alkanes, hydrocarbons, and steroids. All these results represent only a first step in the search for biologically active natural substances from seaweed. Additional tests are envisaged to confirm the bioactivity of seaweed.

Keywords: algae, Ulva lactuca, phenolic compounds, FTIR, GC-MS

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Huan-Chieh Chiu, Hung-Shuo Wu, Chien-Hao Wang, Yu-Cheng Yang, Ching-Ya Tseng, Joe-Air Jiang

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Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.

Keywords: damage level monitoring, drift ratio, fragility curve, smart grid, transmission tower

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Authors: Lina F. Ballesteros, Hafsae Lamsaf, Miguel A. Cerqueira, Lorenzo M. Pastrana, Sandra Carvalho, Jose A. Teixeira, S. Calderon V.

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The use of bio-based packaging materials containing metallic and bimetallic nanostructures is relatively modern technology. In this sense, the food packaging industry has been investigating biological and renewable resources that can replace petroleum-based materials to reduce the environmental impact and, at the same time, including new functionalities using nanotechnology. Therefore, the main objective of the present work consisted of developing bio-based poly-lactic acid (PLA) films with Zinc (Zn) and Zinc-Iron (Zn-Fe) nanostructures deposited by magnetron sputtering. The structural, antimicrobial, and optical properties of the films were evaluated when exposed at 60% and 96% relative humidity (RH). The morphology and elemental analysis of the samples were determined by scanning (transmission) electron microscopy (SEM and STEM), and inductively coupled plasma optical emission spectroscopy (ICP-OES). The structure of the PLA was monitored before and after deposition by Fourier transform infrared spectroscopy (FTIR) analysis, and the antimicrobial and color assays were performed by using the zone of inhibition (ZOI) test and a Minolta colorimeter, respectively. Finally, the films were correlated in terms of the deposit conditions, Zn or Zn-Fe concentrations, and thickness. The results revealed PLA films with different morphologies, compositions, and thicknesses of Zn or Zn-Fe nanostructures. The samples showed a significant antibacterial and antifungal activity against E. coli, P. aeruginosa, P. fluorescens, S. aureus, and A. niger, and considerable changes of color and opacity at 96% RH, especially for the thinner nanostructures (150-250 nm). On the other hand, when the Fe fraction was increased, the lightness of samples increased, as well as their antimicrobial activity when compared to the films with pure Zn. Hence, these findings are relevant to the food packaging field since intelligent and active films with multiple properties can be developed.

Keywords: biopolymers, functional properties, magnetron sputtering, Zn and Zn-Fe nanostructures

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Authors: T. Yılmaz, Ş. Tavman

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In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

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Authors: Mehdi Ghommem, Daniel Garcia, Nathan Collier, Victor Calo

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We develop a fast, user-friendly implementation of a potential flow solver based on the unsteady vortex lattice method (UVLM). The computational framework uses the Python programming language which has easy integration with the scripts requiring computationally-expensive operations written in Fortran. The mixed-language approach enables high performance in terms of solution time and high flexibility in terms of easiness of code adaptation to different system configurations and applications. This computational tool is intended to predict the unsteady aerodynamic behavior of multiple moving bodies (e.g., flapping wings, rotating blades, suspension bridges...) subject to an incoming air. We simulate different aerodynamic problems to validate and illustrate the usefulness and effectiveness of the developed computational tool.

Keywords: unsteady aerodynamics, numerical simulations, mixed-language approach, potential flow

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Authors: Mai Anh Tuan, Wenlong Liu, Meng Li

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Despite warnings and concerns about the use of fast food that has health effects, the fast-food industry is actually a source of profit for the global food industry. Obviously, in the face of such huge economic benefits, investors will not hesitate to continuously add recipes, processing methods, menu diversity, etc., to improve and apply information technology in enhancing the diners' experience; the ultimate goal is still to attract diners to find their brand and give them the fastest, most convenient and enjoyable service. In China, as the achievements of the industrial revolution 4.0, big data and artificial intelligence are reaching new heights day by day, now fast-food diners can instantly pay the bills only by identifying the biometric signature available on the self-ordering kiosk, using their own face without any additional form of confirmation. In this study, the author will evaluate the acceptance level of customers with this new form of payment through a survey of customers who have used and witnessed the use of smart kiosks and biometric payments within the city of Nanjing, China. A total of 200 valid volunteers were collected in order to test the customers' intentions and feelings when choosing and experiencing payment through AI services. 55% think that it bothers them because of the need for personal information, but more than 70% think that smart kiosk brings out many benefits and convenience. According to the data analysis findings, perceived innovativeness has a positive influence on satisfaction which in turn affects behavioral intentions, including reuse and word-of-mouth intentions.

Keywords: artificial intelligence, catering industry, smart kiosks, technology acceptance

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Authors: Jefri Draup, Antoine Ambard, Chi-Toan Nguyen

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Zirconium alloys exhibit solid-state phase transformations under thermal loading. These can lead to a significant evolution of the microstructure and associated mechanical properties of materials used in nuclear fuel cladding structures. Therefore, the ability to capture effects of phase transformation on the material constitutive behavior is of interest during conditions of severe transient thermal loading. Whilst typical Avrami, or Johnson-Mehl-Avrami-Kolmogorov (JMAK), type models for phase transformations have been shown to have a good correlation with the behavior of Zircaloy-4 under constant heating rates, the effects of variable and fast heating rates are not fully explored. The present study utilises the results of in-situ high energy synchrotron X-ray diffraction (SXRD) measurements in order to validate the phase transformation models for Zircaloy-4 under fast variable heating rates. These models are used to assess the performance of fuel cladding structures under loss of coolant accident (LOCA) scenarios. The results indicate that simple Avrami type models can provide a reasonable indication of the phase distribution in experimental test specimens under variable fast thermal loading. However, the accuracy of these models deteriorates under the faster heating regimes, i.e., 100Cs⁻¹. The studies highlight areas for improvement of simple Avrami type models, such as the inclusion of temperature rate dependence of the JMAK n-exponent.

Keywords: accident, fuel, modelling, zirconium

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Authors: F. A. Gberindyer, M. O.Abatan, A. B. Saba

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Background: Gentamicin is an aminoglycoside antibiotic used in the treatment of infections caused by Gram-negative aerobic bacteria organisms in human and animals. In Nigeria, there are arrays of multisource generic versions of injectable gentamicin sulphate in the drug markets. There is a high prevalence of counterfeit and substandard drugs in the third world countries with consequent effect on their therapeutic efficacy and safety. Aim: The aim of this study was to investigate pharmaceutical equivalence of some of these generics used in veterinary practice in Nigeria. Methodology: About 20 generics of injectable gentamicin sulphate were sampled randomly across Nigeria but 15 were analyzed for identity and potency. Identity test was done using Fourier transform infra red spectroscopy and the spectral for each product compared with that of the USP reference standard for similarity. Microbiological assay using agar diffusion method with E. coli as a test organism on nutrient agar was employed and the respective diameters of bacterial inhibition zones obtained after 24 hour incubation at 37°C. The percent potency for each product was thereafter calculated and compared with the official specification. Result And Discussion: None of the generics is produced in any African country. About 75 % of the products are imported from China whereas 60 % of the veterinary generics are manufactured in Holland. Absorption spectra for the reference and test samples were similar. Percent potencies of all test products were within the official specification of 95-115 %. Nigeria relies solely on imported injectable gentamicin sulphate products. All sampled generic versions passed both identity and potency tests. Clinicians should ensure that drugs are used rationally since the converse could be contributing to the therapeutic failures reported for most of these generics. Bioequivalence study is recommended to ascertain their interchangeability when parenteral extra venous routes are indicated.

Keywords: generics, gentamicin, identity, multisource, potency

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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: Florian Wagner, Christoph Schmidt, Vincent Bagnoud

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Understanding the interaction of ultra-intense laser pulses with overcritical targets is of major interest for many applications such as laser-driven ion acceleration, fast ignition in the frame of inertial confinement fusion or high harmonic generation and the creation of attosecond pulses. One particular aspect of this interaction is the shift of the critical surface, where the laser pulse is stopped and the absorption is at maximum, due to the radiation pressure induced by the laser pulse, also referred to as laser hole boring. We investigate laser-hole boring experimentally by measuring the backscattered spectrum which is doppler-broadened because of the movement of the reflecting surface. Using the high-power, high-energy laser system PHELIX in Darmstadt, we gathered an extensive set of data for different laser intensities ranging from 10^18 W/cm2 to 10^21 W/cm2, two different levels of the nanosecond temporal contrast (10^6 vs. 10^11), elliptical and linear polarization and varying target configurations. In this contribution we discuss how the maximum velocity of the critical surface depends on these parameters. In particular we show that by increasing the temporal contrast the maximum hole boring velocity is decreased by more than a factor of three. Our experimental findings are backed by a basic analytical model based on momentum and mass conservation as well as particle in cell simulations. These results are of particular importance for fast ignition since they contribute to a better understanding of the transport of the ignitor pulse into the overdense region.

Keywords: laser-hole boring, interaction of ultra-intense lasers with overcritical targets, fast ignition, relativistic laser motter interaction

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Authors: Yahya Al-Wahaibi, Saif Al-Bahry, Abdulkadir Elshafie, Ali Al-Bemani, Sanket Joshi

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Microbial enhanced oil recovery is one of the most economical and efficient methods for extending the life of production wells in a declining reservoir. There are a variety of metabolites produced by microorganisms that can be useful for oil recovery, like biopolymers-polysaccharides secreted by microbes, biodegradable thus environmentally friendly. Some fungi like Schizophyllum commune (a type of mushroom), and Aureobasidium pullulans are reported to produce biopolymers-schizophyllan and pullulan. Hence, we have procured a microbial strain (Schizophyllum commune) from American Type Culture Collection, which is reported for producing a biopolymer and also isolated several Omani strains of Aureobasidium pullulans from different samples. Studies were carried out for maintenance of the strains and primary screening of production media and environmental conditions for growth of S. commune and Omani A. pullulans isolates, for 30 days. The observed optimum growth and production temperature was ≤35 °C for S. commune and Omani A. pullulans isolates. Better growth was observed for both types of fungi under shaking conditions. The initial yield of lyophilized schizophyllan was ≥3.0 g/L, and the yield of pullulan was ≥0.5g/L. Both schizophyllan and pullulan were extracted in crude form and were partially identified by Fourier transform infrared spectroscopy (FTIR), which showed partial similarity in chemical structure with published biopolymers. The produced pullulan and schizophyllan increased the viscosity from 9-20 cp of the control media (without biopolymer) to 20 - 121.4 cp of the cell free broth at 0.1 s-1 shear rate at range of temperatures from 25–45 °C. Enhanced biopolymer production and its physicochemical and rheological properties under different environmental conditions (different temperatures, salt concentrations and wide range of pH), complete characterization and effects on oil recovery enhancement were also investigated in this study.

Keywords: Aureobasidium pullulans, biopolymer, oil recovery enhancement, Schizophyllum commune

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Authors: Thang V. Kieu, Long P. Nguyen

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Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

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Authors: Pascal Mwenge, Tumisang Seodigeng

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The combination of world population and the third industrial revolution led to high demand for fuels. On the other hand, the decrease of global fossil 8fuels deposits and the environmental air pollution caused by these fuels has compounded the challenges the world faces due to its need for energy. Therefore, new forms of environmentally friendly and renewable fuels such as biodiesel are needed. The primary analytical techniques for methanolysis yield monitoring have been chromatography and spectroscopy, these methods have been proven reliable but are more demanding, costly and do not provide real-time monitoring. In this work, the in situ monitoring of biodiesel from sunflower oil using FTIR (Fourier Transform Infrared) has been studied; the study was performed using EasyMax Mettler Toledo reactor equipped with a DiComp (Diamond) probe. The quantitative monitoring of methanolysis was performed by building a quantitative model with multivariate calibration using iC Quant module from iC IR 7.0 software. 15 samples of known concentrations were used for the modelling which were taken in duplicate for model calibration and cross-validation, data were pre-processed using mean centering and variance scale, spectrum math square root and solvent subtraction. These pre-processing methods improved the performance indexes from 7.98 to 0.0096, 11.2 to 3.41, 6.32 to 2.72, 0.9416 to 0.9999, RMSEC, RMSECV, RMSEP and R2Cum, respectively. The R² value of 1 (training), 0.9918 (test), 0.9946 (cross-validation) indicated the fitness of the model built. The model was tested against univariate model; small discrepancies were observed at low concentration due to unmodelled intermediates but were quite close at concentrations above 18%. The software eliminated the complexity of the Partial Least Square (PLS) chemometrics. It was concluded that the model obtained could be used to monitor methanol of sunflower oil at industrial and lab scale.

Keywords: biodiesel, calibration, chemometrics, methanolysis, multivariate analysis, transesterification, FTIR

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Authors: L. O. Luengas, E. V. Morales, L. F. G. De Souza, I. S. Bott

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Duplex Stainless Steels are well known for its good mechanical properties, and corrosion resistance. However, when submitted to heating, these features can be lost since the good properties are strongly dependent on the austenite-ferrite phase ratio which has to be approximately 1:1 to keep the phase balance. In a welded joint, the transformation kinetics at the heat affected zone (HAZ) is a function of the cooling rates applied which in turn are dependent on the heat input. The HAZ is usually ferritized at these temperatures, and it has been argued that small variations of the chemical composition can play a role in the solid state transformation sequence of ferrite to austenite during cooling. The δ → γ transformation has been reported to be massive and diffusionless due to the fast cooling rate, but it is also considered a diffusion controlled transformation. The aim of this work is to evaluate the effect of different heat inputs on the HAZ of two duplex stainless steels UNS S32304 and S32750, obtained by physical simulation.

Keywords: duplex stainless steels, HAZ, microstructural characterization, physical simulation

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Authors: Ahmed Abdrabou, Medhat Abdalla

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The studied stele dates back to Third Intermediate Period (1075-664) B.C in an ancient Egypt. It is made of wood and covered with painted gesso layers. This study aims to use a combination of multi spectral imaging {visible, infrared (IR), Visible-induced infrared luminescence (VIL), Visible-induced ultraviolet luminescence (UVL) and ultraviolet reflected (UVR)}, along with portable x-ray fluorescence in order to map and identify the pigments as well as to provide a deeper understanding of the painting techniques. Moreover; the authors were significantly interested in the identification of wood species. Multispectral imaging acquired in 3 spectral bands, ultraviolet (360-400 nm), visible (400-780 nm) and infrared (780-1100 nm) using (UV Ultraviolet-induced luminescence (UVL), UV Reflected (UVR), Visible (VIS), Visible-induced infrared luminescence (VIL) and Infrared photography. False color images are made by digitally editing the VIS with IR or UV images using Adobe Photoshop. Optical Microscopy (OM), potable X-ray fluorescence spectroscopy (p-XRF) and Fourier Transform Infrared Spectroscopy (FTIR) were used in this study. Mapping and imaging techniques provided useful information about the spatial distribution of pigments, in particular visible-induced luminescence (VIL) which allowed the spatial distribution of Egyptian blue pigment to be mapped and every region containing Egyptian blue, even down to single crystals in some instances, is clearly visible as a bright white area; however complete characterization of the pigments requires the use of p. XRF spectroscopy. Based on the elemental analysis found by P.XRF, we conclude that the artists used mixtures of the basic mineral pigments to achieve a wider palette of hues. Identification of wood species Microscopic identification indicated that the wood used was Sycamore Fig (Ficus sycomorus L.) which is recorded as being native to Egypt and was used to make wooden artifacts since at least the Fifth Dynasty.

Keywords: polychrome wooden stele, multispectral imaging, IR luminescence, Wood identification, Sycamore Fig, p-XRF

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Authors: R. M. S. Sachini Amararathne

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This research is striving to develop a thermo degradable starch plastic compound/ masterbatch for industrial packaging applications. A native corn starch-modified with an esterification reaction of lauric acid is melt blent with an unsaturated elastomer (styrene-butadiene-rubber/styrene-butadiene-styrene). A trace amount of metal salt is added into the internal mixer to study the effect of pro-oxidants in a thermo oxidative environment. Then the granulated polymer composite which is consisted with 80-86% of polyolefin (LLDP/LDPE/PP) as the pivotal agent; is extruded with processing aids, antioxidants and some other additives in a co-rotating twin-screw extruder. The pelletized composite is subjected to compression molding/ Injection molding or blown film extrusion processes to acquire the samples/specimen for tests. The degradation process is explicated by analyzing the results of fourier transform infrared spectroscopy (FTIR) measurements, thermo oxidative aging studies (placing the dumb-bell specimen in an air oven at 70 °C for four weeks of exposure.) governed by tensile and impact strength test reports. Furthermore, the samples were elicited into manifold outdoors to inspect the degradation process. This industrial process is implemented to reduce the volume of fossil-based garbage by achieving the biodegradability and compostability in the natural cycle. Hence the research leads to manufacturing a degradable plastic packaging compound which is now available in the Sri Lankan market.

Keywords: blown film extrusion, compression moulding, polyolefin, pro-oxidant, styrene-butadine-rubber, styrene-butadiene-styrene, thermo oxidative aging, unsaturated elastomer

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Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: Laroussi Chaabane, Amel El Ghali, Emmanuel Beyou, Mohamed Hassen V. Baouab

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In this research, the functionalization of graphene oxide sheets by ethylenediamine (EDA) was accomplished and followed by the grafting of bis(2-pyridylmethyl) amino group (BPED) onto the activated graphene oxide sheets in the presence of chloroacetylchloride (CAC) and then combined with magnetic nanoparticles (Fe₃O₄NPs) to produce a magnetic graphene-based composite [(Go-EDA-CAC)@Fe₃O₄NPs-BPED]. The physicochemical properties of [(Go-EDA-CAC)@Fe₃O₄NPs-BPED] composites were investigated by Fourier transform infrared (FT-IR), scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA). Additionally, the catalysts can be easily recycled within ten seconds by using an external magnetic field. Moreover, [(Go-EDA-CAC)@Fe₃O₄NPs-BPED] was used for removing Cu(II) ions from aqueous solutions using a batch process. The effect of pH, contact time and temperature on the metal ions adsorption were investigated, however weakly dependent on ionic strength. The maximum adsorption capacity values of Cu(II) on the [(Go-EDA-CAC)@Fe₃O₄NPs-BPED] at the pH of 6 is 3.46 mmol.g⁻¹. To examine the underlying mechanism of the adsorption process, pseudo-first, pseudo-second-order, and intraparticle diffusion models were fitted to experimental kinetic data. Results showed that the pseudo-second-order equation was appropriate to describe the Cu (II) adsorption by [(Go-EDA-CAC)@Fe₃O₄NPs-BPED]. Adsorption data were further analyzed by the Langmuir, Freundlich, and Jossens adsorption approaches. Additionally, the adsorption properties of the [(Go-EDA-CAC)@Fe₃O₄NPs-BPED], their reusability (more than 6 cycles) and durability in the aqueous solutions open the path to removal of Cu(II) from water solution. Based on the results obtained, we report the activity of Cu(II) supported on [(Go-EDA-CAC)@Fe₃O₄NPs-BPED] as a catalyst for the cross-coupling of symmetric alkynes.

Keywords: graphene, magnetic nanoparticles, adsorption kinetics/isotherms, cross coupling

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Authors: Morteza Taherinezhad, Ahmad Reza Rabbani, Morteza Asemani, Rudy Swennen

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Oil-oil correlation is one of the most important issues in geochemical studies that enables to classify oils genetically. Oil-oil correlation is generally estimated based on non-polar fractions of crude oil (e.g., saturate and aromatic compounds). Despite several advantages, the drawback of using these compounds is their susceptibility of being affected by secondary processes. The polar fraction of crude oil (e.g., asphaltenes) has similar characteristics to kerogen, and this structural similarity is preserved during migration, thermal maturation, biodegradation, and water washing. Therefore, these structural characteristics can be considered as a useful correlation parameter, and it can be concluded that asphaltenes from different reservoirs with the same genetic signatures have a similar origin. Hence in this contribution, an integrated study by using both non-polar and polar fractions of oil was performed to use the merits of both fractions. Therefore, five oil samples from oil fields in the Persian Gulf were studied. Structural characteristics of extracted asphaltenes were investigated by Fourier transform infrared (FTIR) spectroscopy. Graphs based on aliphatic and aromatic compounds (predominant compounds in asphaltenes structure) and sulphoxide and carbonyl functional groups (which are representatives of sulphur and oxygen abundance in asphaltenes) were used for comparison of asphaltenes structures in different samples. Non-polar fractions were analyzed by GC-MS. The study of asphaltenes showed the studied oil samples comprise two oil families with distinct genetic characteristics. The first oil family consists of Salman and Reshadat oil samples, and the second oil family consists of Resalat, Siri E, and Siri D oil samples. To validate our results, biomarker parameters were employed, and this approach completely confirmed previous results. Based on biomarker analyses, both oil families have a marine source rock, whereby marl and carbonate source rocks are the source rock for the first and the second oil family, respectively.

Keywords: biomarker, non-polar fraction, oil-oil correlation, petroleum geochemistry, polar fraction

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Authors: Quin Emparan, Razif Harun, Dayang R. A. Biak, Rozita Omar, Michael K. Danquah

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Cultivation of immobilized microalgae cells is on the rise for biotechnological applications. In this study, cultivation of Chlorella vulgaris was carried out in the form of suspended free-cell and immobilized cells system. NaCS-PDMDAAC capsules were used to immobilize C. vulgaris. Initially, the synthesized NaCS with C. vulgaris culture were prepared at various concentration of 5- 20% (w/v) using a 6% hardening solution (PDMDAAC) to investigate the capsules' gel stability and suitability for microalgae cells growth. Then, the capsules produced from 15% NaCS with C. vulgaris culture were furthered investigated using 5%, 10%, and 15% (w/v) of PDMDAAC solution. The capsules' gel stability was evaluated through dissolution time and loss of uniform spherical shape of capsules, while suitability for microalgae cells growth was evaluated through the optical density of microalgae. In this study, the 15% NaCS-10% PDMDAAC capsules were found to be the most suitable to sustain the capsules' gel stability and microalgae cells growth in MLA. For that reason, the C. vulgaris immobilized in the 15% NaCS-10% PDMDAAC capsules were further characterized using physicochemical analysis in terms of morphological, carbon (C), hydrogen (H) and nitrogen (N), Fourier transform-infrared (FT-IR), scanning electron microscopy-energy dispersive X-ray (SEM-EDX), zeta potential and Brunauer-Emmet-Teller (BET) analyses. The results revealed that the presence of sulfonates in the synthesized NaCS and NaCS-PDMDAAC capsules without and with C. vulgaris proves that cellulose alcohol group was successfully bonded by sulfo group. Besides that, immobilized microalgae cells have a smaller cell size of 6.29 ± 1.09 µm and zeta potential of -11.93 ± 0.91 mV than suspended free-cells microalgae culture. It can be summarized that immobilization of C. vulgaris in the 15% NaCS-10% PDMDAAC capsules are relevant as a bioremediator for wastewater treatment purposes due to its suitable size of pore and capsules as well as structural and compositional properties.

Keywords: biological capsules, immobilized cultivation, microalgae, physico-chemical analysis

Procedia PDF Downloads 157

Authors: Qing Lyu, Hang Zhu

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Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm.

Keywords: flow path, latency, middlebox, network

Procedia PDF Downloads 196

Authors: Innocent O. Arukalam, Emeka E. Oguzie

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Interest in the development of eco-friendly anti-corrosion coatings using bio-based renewable materials is gaining momentum recently. To this effect, chitin biopolymer, which is non-toxic, biodegradable, and inherently possesses anti-microbial property, was successfully synthesized from snail shells and used as a filler in the preparation of epoxy coating. The chitin particles were characterized with contact angle goniometer, scanning electron microscope (SEM), Fourier transform infrared (FTIR) spectrophotometer, and X-ray diffractometer (XRD). The performance of the coatings was evaluated by immersion and electrochemical impedance spectroscopy (EIS) tests. Electronic structure properties of the coating ingredients and molecular level interaction of the corrodent and coated Q235 steel were appraised by quantum chemical computations (QCC) and molecular dynamics (MD) simulation techniques, respectively. The water contact angle (WCA) measurement of chitin particles was found to be 129.3o while that of chitin particles modified with amino trimethoxy silane (ATMS) was 149.6o, suggesting it is highly hydrophobic. Immersion and EIS analyses revealed that epoxy coating containing silane-modified chitin exhibited lowest water absorption and highest barrier as well as anti-corrosion performances. The QCC showed that quantum parameters for the coating containing silane-modified chitin are optimum and therefore corresponds to high corrosion protection. The high negative value of adsorption energies (Eads) for the coating containing silane-modified chitin indicates the coating molecules interacted and adsorbed strongly on the steel surface. The observed results have shown that silane-modified epoxy-chitin coating would perform satisfactorily for surface protection of metal structures in saline environment.

Keywords: chitin, EIS, epoxy coating, hydrophobic, molecular dynamics simulation, quantum chemical computation

Procedia PDF Downloads 80

Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

Procedia PDF Downloads 59

Authors: Amhimmid Mohammed Saffour, Mustafa Mohamed Abdullah

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The use of computers for handling image data in the healthcare is growing. However, the amount of data produced by modern image generating techniques is vast. This data might be a problem from a storage point of view or when the data is sent over a network. This paper using wavelet transform technique for medical images compression. MATLAB program, are designed to evaluate medical images storage and transmission time problem at Sebha Medical Center Libya. In this paper, three different Computed Tomography images which are abdomen, brain and chest have been selected and compressed using wavelet transform. Objective evaluation has been performed to measure the quality of the compressed images. For this evaluation, the results show that the Peak Signal to Noise Ratio (PSNR) which indicates the quality of the compressed image is ranging from (25.89db to 34.35db for abdomen images, 23.26db to 33.3db for brain images and 25.5db to 36.11db for chest images. These values shows that the compression ratio is nearly to 30:1 is acceptable.

Keywords: medical image, Matlab, image compression, wavelet's, objective evaluation

Procedia PDF Downloads 280

Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

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DNA Barcode, a short mitochondrial DNA fragment, made up of three subunits; a phosphate group, sugar and nucleic bases (A, T, C, and G). They provide good sources of information needed to classify living species. Such intuition has been confirmed by many experimental results. Species classification with DNA Barcode sequences has been studied by several researchers. The classification problem assigns unknown species to known ones by analyzing their Barcode. This task has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. To make this type of analysis feasible, heuristics, like progressive alignment, have been developed. Another tool for similarity search against a database of sequences is BLAST, which outputs shorter regions of high similarity between a query sequence and matched sequences in the database. However, all these methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. This method permits to avoid the complex problem of form and structure in different classes of organisms. On empirical data and their classification performances are compared with other methods. Our system consists of three phases. The first is called transformation, which is composed of three steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. The second is called approximation, which is empowered by the use of Multi Llibrary Wavelet Neural Networks (MLWNN).The third is called the classification of DNA Barcodes, which is realized by applying the algorithm of hierarchical classification.

Keywords: DNA barcode, electron-ion interaction pseudopotential, Multi Library Wavelet Neural Networks (MLWNN)

Procedia PDF Downloads 304

Authors: Qiong Tian, Lifeng Zhang, Demei Yu, Ajit D. Kelkar

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Low specific weight and high strength is the basic requirement for aerospace materials. Fiber-reinforced epoxy resin composites are attractive materials for this purpose. Boron nitride nanoparticles (BNNPs) have good radiation shielding capacity, which is very important to aerospace materials. Herein a processing route for an advanced hybrid composite material is demonstrated by introducing dispersed BNNPs in standard prepreg manufacturing. The hybrid materials contain three parts: E-fiberglass, an aerospace-grade epoxy resin system, and BNNPs. A vacuum assisted resin transfer molding (VARTM) was utilized in this processing. Two BNNP functionalization approaches are presented in this study: (a) covalent functionalization with 3-aminopropyltriethoxysilane (KH-550); (b) non-covalent functionalization with cetyltrimethylammonium bromide (CTAB). The functionalized BNNPs were characterized by Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction(XRD) and scanning electron microscope (SEM). The results showed that BN powder was successfully functionalized via the covalent and non-covalent approaches without any crystal structure change and big agglomerate particles were broken into platelet-like nanoparticles (BNNPs) after functionalization. Compared to pristine BN powder, surface modified BNNPs could result in significant improvement in mechanical properties such as tensile, flexural and compressive strength and modulus. CTAB functionalized BNNPs (CTAB-BNNPs) showed higher tensile and flexural strength but lower compressive strength than KH-550 functionalized BNNPs (KH550-BNNPs). These reinforcements are mainly attributed to good BNNPs dispersion and interfacial adhesion between epoxy matrix and BNNPs. This study reveals the potential in improving mechanical properties of BNNPs-containing composites laminates through surface functionalization of BNNPs.

Keywords: boron nitride, epoxy, functionalization, prepreg, composite

Procedia PDF Downloads 424

Authors: Mark Daniel De Luna, Ma. Katreena Pillejera, Wei-Hsin Chen

Abstract:

The raw bamboo (Phyllostachys mankinoi), with a moisture content of 13.54 % and a higher heating value (HHV) of 17.657 MJ/kg, was subjected to torrefaction under a high gravity (higee) environment using a rotating packed bed. The performance of the higee torrefaction was explored in two parts: (1) effect of rotation and temperature and (2) effect of duration on the solid yield, HHV and energy yield. By statistical analyses, the results indicated that the rotation, temperature and their interaction has a significant effect on the three responses. Same remarks on the effect of duration where when the duration (temperature and rotation) increases, the HHV increases, while the solid yield and energy yield decreases. Graphical interpretations showed that at 300 °C, the rotating speed has no evident effect on the responses. At 30-min holding time, the highest HHV reached (28.389 MJ/kg) was obtained in the most severe torrefaction condition (the rotating speed at 1800 rpm and temperature at 300 °C) with an enhancement factor of HHV corresponding to 1.61 and an energy yield of 63.51%. Upon inspection, the recommended operating condition under a 30-min holding time is at 255 °C-1800 rpm since the enhancement factor of HHV (1.53), HHV (26.988 MJ/kg), and energy yield (65.21%) values are relatively close to that of the aforementioned torrefaction condition. The Van Krevelen diagram of the torrefied biomass showed that the ratios decrease as the torrefaction intensifies, hence improving the hydrophobicity of the product. The spreads of the results of the solid yield, enhancement factor (EF) of HHV, energy yield, and H/C and O/C ratios were in accordance with the trends of the responses. Overall, from the results presented, it can be concluded that the quality of the product from the process is at par to that of coal (i.e. HHV of coal is 21-35 MJ/kg). The Fourier transform infrared (FTIR) spectroscopy results indicated that cellulose and lignin may have been degraded at a lower temperature accompanied with a high rotating speed. The results suggested that torrefaction under higee environment indicates promising process for the utilization of bamboo.

Keywords: heat transfer, high gravity environment, FTIR, rotation, rotating speed, torrefaction

Procedia PDF Downloads 260

Authors: Narek Margaryan, Zhozef Panosyan

Abstract:

Due to their unique properties, carbon nanofilms have become the object of general attention and intensive research. In this case it plays a very important role to study surface properties of these films. It is also important to study processes of forming of this films, which is accompanied by a process of self-organization at the nano and micro levels. For more detailed investigation, we examined diamond-like carbon (DLC) layers deposited by chemical vapor deposition (CVD) method on Ge substrate and hydro-generated grapheme layers obtained on surface of colloidal solution using grouping method. In this report surface transformation of these CVD nanolayers is studied by atomic force microscopy (AFM) upon deposition time. Also, it can be successfully used to study surface properties of self-assembled grapheme layers. In turn, it is possible to sketch out their boundary line, which enables one to draw an idea of peculiarities of formation of these layers. Images obtained by AFM are investigated as a mathematical set of numbers and fractal and roughness analysis were done. Fractal dimension, Regne’s fractal coefficient, histogram, Fast Fourier transformation, etc. were obtained. The dependence of fractal parameters on the deposition duration for CVD films and on temperature of solution tribolayers was revealed. As an important surface parameter for our carbon films, surface energy was calculated as function of Regne’s fractal coefficient. Surface potential was also measured with Kelvin probe method using semi-contacting AFM. The dependence of surface potential on the deposition duration for CVD films and on temperature of solution for hydro-generated graphene was found as well. Results obtained by fractal analysis method was related with purly esperimental results for number of samples.

Keywords: nanostructured films, self-assembled grapheme, diamond-like carbon, surface potential, Kelvin probe method, fractal analysis

Procedia PDF Downloads 257