Search results for: wavelet transform

Authors: Saja M. Nabat Al-Ajrash, Charles Browning, Rose Eckerle, Li Cao

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Three preceramic polymer formulations for potential use in 3D printing technologies were investigated. The polymeric precursors include an allyl hydrido polycarbosilane (SMP-10), SMP-10/1,6-dexanediol diacrylate (HDDA) mixture, and polydimethylsiloxane (PDMS). The rheological property of the polymeric precursors, including the viscosity within a wide shear rate range was compared to determine the applicability in additive manufacturing technology. The structural properties of the polymeric solutions and their photocureability were investigated using Fourier transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC). Moreover, thermogravimetric analysis (TGA) and X-ray diffraction (XRD) were utilized to study polymeric to ceramic conversion for versatile precursors. The prepared precursor resin proved to have outstanding photo-curing properties and the ability to transform to the silicon carbide phase at temperatures as low as 850 °C. The obtained ceramic was fully dense with nearly linear shrinkage and a shiny, smooth surface after pyrolysis. Furthermore, after pyrolysis to 1350 °C and TGA analysis, PDMS polymer showed the highest onset decomposition temperature and the lowest retained weight (52 wt%), while SMP.10/HDDA showed the lowest onset temperature and ceramic yield (71.7 wt%). In terms of crystallography, the ceramic matrix composite appeared to have three coexisting phases, including silicon carbide, and silicon oxycarbide. The results are very promising to fabricate ceramic materials working at high temperatures with complex geometries.

Keywords: preceramic polymer, silicon carbide, photocuring, allyl hydrido polycarbosilane, SMP-10

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Authors: Saad M. Darwish, Adel A. El-Zoghabi, Moustafa F. Ashry

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The popularity of the Internet and the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we use computers today. These technical opportunities have led to the possibility of using geographically distributed and multi-owner resources to solve large-scale problems in science, engineering, and commerce. Recent research on these topics has led to the emergence of a new paradigm known as Grid computing. To achieve the promising potentials of tremendous distributed resources, effective and efficient load balancing algorithms are fundamentally important. Unfortunately, load balancing algorithms in traditional parallel and distributed systems, which usually run on homogeneous and dedicated resources, cannot work well in the new circumstances. In this paper, the concept of a fast fractal transform in heterogeneous grid computing based on R-tree and the domain-range entropy is proposed to improve fault tolerance and load balancing algorithm by improve connectivity, communication delay, network bandwidth, resource availability, and resource unpredictability. A novel two-dimension figure of merit is suggested to describe the network effects on load balance and fault tolerance estimation. Fault tolerance is enhanced by adaptively decrease replication time and message cost while load balance is enhanced by adaptively decrease mean job response time. Experimental results show that the proposed method yields superior performance over other methods.

Keywords: Grid computing, load balancing, fault tolerance, R-tree, heterogeneous systems

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Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

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The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

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Authors: Vedant Janapaty

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Estuaries are wetlands where fresh water from streams mixes with salt water from the sea. Also known as “kidneys of our planet”- they are extremely productive environments that filter pollutants, absorb floods from sea level rise, and shelter a unique ecosystem. However, eutrophication and loss of native species are ailing our wetlands. There is a lack of uniform data collection and sparse research on correlations between satellite data and in situ measurements. Remote sensing (RS) has shown great promise in environmental monitoring. This project attempts to use satellite data and correlate metrics with in situ observations collected at five estuaries. Images for satellite data were processed to calculate 7 bands (SIs) using Python. Average SI values were calculated per month for 23 years. Publicly available data from 6 sites at ELK was used to obtain 10 parameters (OPs). Average OP values were calculated per month for 23 years. Linear correlations between the 7 SIs and 10 OPs were made and found to be inadequate (correlation = 1 to 64%). Fourier transform analysis on 7 SIs was performed. Dominant frequencies and amplitudes were extracted for 7 SIs, and a machine learning(ML) model was trained, validated, and tested for 10 OPs. Better correlations were observed between SIs and OPs, with certain time delays (0, 3, 4, 6 month delay), and ML was again performed. The OPs saw improved R² values in the range of 0.2 to 0.93. This approach can be used to get periodic analyses of overall wetland health with satellite indices. It proves that remote sensing can be used to develop correlations with critical parameters that measure eutrophication in situ data and can be used by practitioners to easily monitor wetland health.

Keywords: estuary, remote sensing, machine learning, Fourier transform

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Authors: Piyush Samant, Ravinder Agarwal

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Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

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Authors: M. H. M. Rashid

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Given H a Hilbert space and B(H) the algebra of bounded linear operator in H, let δAB denote the generalized derivation defined by A and B. The main objective of this article is to study Weyl type theorems for generalized derivation for (A,B) satisfying a couple of Fuglede.

Keywords: Fuglede Property, Weyl’s theorem, generalized derivation, Aluthge transform

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Authors: Merve Gücen

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One of the aims of education is to educate individuals who have embraced universal moral principles and transform universal moral principles into moral values. Character education aims to educate behaviors of individuals in their mental activities to transform moral principles into moral values in their lives. As the result of this education, individuals are expected to develop positive character traits and become morally indifferent individuals. What are the characteristics of the factors that influence character education at this stage? How should character education help individuals develop positive character traits? Which methods are more effective? These questions come to mind when studying character education. Our research was developed within the framework of these questions. The aim of our study is to provide the most effective use of the education factor that affects character. In this context, we tried to explain character definition, character development, character education and the factors affecting character education using qualitative research methods. At this stage, character education programs applied in various countries were examined and a character education program consisting of Islamic values was prepared and implemented in an International Imam Hatip High School in Istanbul. Our application was carried out with the collaboration of school and families. Various seminars were organized in the school and participation of families was ensured. In the last phase of our study, we worked with the students and their families on the effectiveness of the events held during the program. In this study, it was found that activities such as storytelling and theater in character education programs were effective in recognizing wrong behaviors in individuals. It was determined that our program had a positive effect on the quality of education. It was seen that applications of this educational program affected the behavior of the employees in the educational institution.

Keywords: character development, family activities, values education, education program

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Authors: Ying Wang, Jianhong Xiang, Yu Zhong

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The offset Quadrature Amplitude Modulation-based Filter Bank Multi-Carrier (FBMC) system provides superior spectral properties over Orthogonal Frequency Division Multiplexing. However, seriously affected by imaginary interference, its performances are hampered in many areas. In this paper, we propose a Precoding-Assisted Frequency Division Multiple Access (PA-FDMA) modulation scheme. By spreading FBMC symbols into the frequency domain and transmitting them with a precoding matrix, the impact of imaginary interference can be eliminated. Specifically, we first generate the coding pre-solution matrix with a nonuniform Fast Fourier Transform and pick the best columns by introducing auxiliary factors. Secondly, according to the column indexes, we obtain the precoding matrix for one symbol and impose scaling factors to ensure that the power is approximately constant throughout the transmission time. Finally, we map the precoding matrix of one symbol to multiple symbols and transmit multiple data frames, thus achieving frequency-division multiple access. Additionally, observing the interference between adjacent frames, we mitigate them by adding frequency Cyclic Prefixes (CP) and evaluating them with a signal-to-interference ratio. Note that PA-FDMA can be considered a CP-available FBMC technique because the underlying strategy is FBMC. Simulation results show that the proposed scheme has better performance compared to Single Carrier Frequency Division Multiple Access (SC-FDMA), etc.

Keywords: PA-FDMA, SC-FDMA, FBMC, non-uniform fast fourier transform

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Authors: Eliane G. Tótoli, Hérida Regina N. Salgado

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Daptomycin is an important antimicrobial agent used in clinical practice nowadays, since it is very active against some Gram-positive bacteria that are particularly challenges for the medicine, such as methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE). The importance of environmental preservation has receiving special attention since last years. Considering the evident need to protect the natural environment and the introduction of strict quality requirements regarding analytical procedures used in pharmaceutical analysis, the industries must seek environmentally friendly alternatives in relation to the analytical methods and other processes that they follow in their routine. In view of these factors, green analytical chemistry is prevalent and encouraged nowadays. In this context, infrared spectroscopy stands out. This is a method that does not use organic solvents and, although it is formally accepted for the identification of individual compounds, also allows the quantitation of substances. Considering that there are few green analytical methods described in literature for the analysis of daptomycin, the aim of this work was the development and validation of a green analytical method for the quantification of this drug in lyophilized powder for injectable solution, by Fourier-transform infrared spectroscopy (FT-IR). Method: Translucent potassium bromide pellets containing predetermined amounts of the drug were prepared and subjected to spectrophotometric analysis in the mid-infrared region. After obtaining the infrared spectrum and with the assistance of the IR Solution software, quantitative analysis was carried out in the spectral region between 1575 and 1700 cm-1, related to a carbonyl band of the daptomycin molecule, and this band had its height analyzed in terms of absorbance. The method was validated according to ICH guidelines regarding linearity, precision (repeatability and intermediate precision), accuracy and robustness. Results and discussion: The method showed to be linear (r = 0.9999), precise (RSD% < 2.0), accurate and robust, over a concentration range from 0.2 to 0.6 mg/pellet. In addition, this technique does not use organic solvents, which is one great advantage over the most common analytical methods. This fact contributes to minimize the generation of organic solvent waste by the industry and thereby reduces the impact of its activities on the environment. Conclusion: The validated method proved to be adequate to quantify daptomycin in lyophilized powder for injectable solution and can be used for its routine analysis in quality control. In addition, the proposed method is environmentally friendly, which is in line with the global trend.

Keywords: daptomycin, Fourier-transform infrared spectroscopy, green analytical chemistry, quality control, spectrometry in IR region

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Authors: Mahdi Bazarganigilani

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Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

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Authors: Surabhi Pandey, Pavuluri Srinivasa Rao

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Extrusion processing is a high-temperature short time (HTST) treatment which can improve protein quality and digestibility together with retaining active nutrients. In-vitro protein digestibility of plant protein-based foods is generally enhanced by extrusion. The current study aimed to investigate the effect of extrusion cooking on in-vitro protein digestibility (IVPD) and conformational modification of protein in green banana flour extrudates. Green banana flour was extruded through a co-rotating twin-screw extruder varying the moisture content, barrel temperature, screw speed in the range of 10-20 %, 60-80 °C, 200-300 rpm, respectively, at constant feed rate. Response surface methodology was used to optimise the result for IVPD. Fourier-transform infrared spectroscopy (FTIR) analysis provided a convenient and powerful means to monitor interactions and changes in functional and conformational properties of extrudates. Results showed that protein digestibility was highest in extrudate produced at 80°C, 250 rpm and 15% feed moisture. FTIR analysis was done for the optimised sample having highest IVPD. FTIR analysis showed that there were no changes in primary structure of protein while the secondary protein structure changed. In order to explain this behaviour, infrared spectroscopy analysis was carried out, mainly in the amide I and II regions. Moreover, curve fitting analysis showed the conformational changes produced in the flour due to protein denaturation. The quantitative analysis of the changes in the amide I and II regions provided information about the modifications produced in banana flour extrudates.

Keywords: extrusion, FTIR, protein conformation, raw banana flour, SDS-PAGE method

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Authors: Benjamin Anderson-Sackaney, Amr Abdel-Dayem

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This paper presents a comprehensive survey of recent source camera identification (SCI) systems. Then, the performance of various sensor pattern noise (SPN) estimators was experimentally assessed, under common photo response non-uniformity (PRNU) frameworks. The experiments used 1350 natural and 900 flat-field images, captured by 18 individual cameras. 12 different experiments, grouped into three sets, were conducted. The results were analyzed using the receiver operator characteristic (ROC) curves. The experimental results demonstrated that combining the basic SPN estimator with a wavelet-based filtering scheme provides promising results. However, the phase SPN estimator fits better with both patch-based (BM3D) and anisotropic diffusion (AD) filtering schemes.

Keywords: sensor pattern noise, source camera identification, photo response non-uniformity, anisotropic diffusion, peak to correlation energy ratio

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Authors: A. S. Issa, S. K. Q. AL-Omari

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In this paper, we investigate certain spaces of generalized functions for the Fourier and Fourier type integral transforms. We discuss convolution theorems and establish certain spaces of distributions for the considered integrals. The new Fourier type integral is well-defined, linear, one-to-one and continuous with respect to certain types of convergences. Many properties and an inverse problem are also discussed in some details.

Keywords: Boehmian, Fourier integral, Fourier type integral, generalized quotient

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Authors: Somya R. Patro, Arnab Banerjee, G. V. Ramana

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A flexural beam carrying elastically mounted concentrated masses, such as engines, motors, oscillators, or vibration absorbers, is often encountered in mechanical, civil, and aeronautical engineering domains. To prevent resonance conditions, the designers must predict the natural frequencies of such a constrained beam system. This paper investigates experimental and analytical studies on vibration suppression in a cantilever beam with a tip mass with the help of spring-mass to achieve local resonance conditions. The system consists of a 3D printed polylactic acid (PLA) beam screwed at the base plate of the shaker system. The top of the free end is connected by an accelerometer which also acts as a tip mass. A spring and a mass are attached at the bottom to replicate the mechanism of the spring-mass resonator. The Fast Fourier Transform (FFT) algorithm converts time acceleration plots into frequency amplitude plots from which transmittance is calculated as a function of the excitation frequency. The mathematical formulation is based on the transfer matrix method, and the governing differential equations are based on Euler Bernoulli's beam theory. The experimental results are successfully validated with the analytical results, providing us essential confidence in our proposed methodology. The beam spring-mass system is then converted to an equivalent two-degree of freedom system, from which frequency response function is obtained. The H2 optimization technique is also used to obtain the closed-form expression of optimum spring stiffness, which shows the influence of spring stiffness on the system's natural frequency and vibration response.

Keywords: euler bernoulli beam theory, fast fourier transform, natural frequencies, polylactic acid, transmittance, vibration absorbers

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Authors: Lucky Malise, Hilary Rutto, Tumisang Seodigeng

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The use of tires in automobiles is very important in the automobile industry. However, there is a serious environmental problem concerning the disposal of these rubber tires once they become worn out. The main aim of this study was to prepare activated carbon from waste tire pyrolysis char by impregnating KOH on pyrolytic char. Adsorption studies on lead onto chemically activated carbon was carried out using response surface methodology. The effect of process parameters such as temperature (°C), adsorbent dosage (g/1000ml), pH, contact time (minutes) and initial lead concentration (mg/l) on the adsorption capacity were investigated. It was found that the adsorption capacity increases with an increase in contact time, pH, temperature and decreases with an increase in lead concentration. Optimization of the process variables was done using a numerical optimization method. Fourier Transform Infrared Spectra (FTIR) analysis, XRay diffraction (XRD), Thermogravimetric analysis (TGA) and scanning electron microscope was used to characterize the pyrolytic carbon char before and after activation. The optimum points 1g/ 100 ml for adsorbent dosage, 7 for pH value of the solution, 115.2 min for contact time, 100 mg/l for initial metal concentration, and 25°C for temperature were obtained to achieve the highest adsorption capacity of 93.176 mg/g with a desirability of 0.994. Fourier Transform Infrared Spectra (FTIR) analysis and Thermogravimetric analysis (TGA) show the presence of oxygen-containing functional groups on the surface of the activated carbon produced and that the weight loss taking place during the activation step is small.

Keywords: waste tire pyrolysis char, chemical activation, central composite design (CCD), adsorption capacity, numerical optimization

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Authors: Avoseh Funmilola, Osman Khalid, Wayne Nelson, Paramespri Naidoo, Deresh Ramjugernath

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The increasing global atmospheric temperature is of great concern and this has led to the development of technologies to reduce the emission of greenhouse gases into the atmosphere. Flue gas emissions from fossil fuel combustion are major sources of greenhouse gases. One of the ways to reduce the emission of CO₂ from flue gases is by post combustion capture process and this can be done by absorbing the gas into suitable chemical solvents before emitting the gas into the atmosphere. Alkanolamines are promising solvents for this capture process. Vapour liquid equilibrium of CO₂-alkanolamine systems is often represented by CO₂ loading and partial pressure of CO₂ without considering the liquid phase. The liquid phase of this system is a complex one comprising of 9 species. Online analysis of the process is important to monitor the concentrations of the liquid phase reacting and product species. Liquid phase analysis of CO₂-diethanolamine (DEA) solution was performed by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. A robust Calibration was performed for the CO₂-aqueous DEA system prior to an online monitoring experiment. The partial least square regression method was used for the analysis of the calibration spectra obtained. The models obtained were used for prediction of DEA and CO₂ concentrations in the online monitoring experiment. The experiment was performed with a newly built recirculating experimental set up in the laboratory. The set up consist of a 750 ml equilibrium cell and ATR-FTIR liquid flow cell. Measurements were performed at 400°C. The results obtained indicated that the FTIR spectroscopy combined with Partial least square method is an effective tool for online monitoring of speciation.

Keywords: ATR-FTIR, CO₂ capture, online analysis, PLS regression

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Authors: V. P. Muhamed Shajudheen, K. Viswanathan, K. Anitha Rani, A. Uma Maheswari, S. Saravana Kumar

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We are reporting a simple and low-cost chemical precipitation method adopted to prepare zinc oxide nanoparticles (ZnO) using polyvinyl pyrrolidone (PVP) as a capping agent. The Differential Scanning Calorimetry (DSC) and Thermo Gravimetric Analysis (TGA) was applied on the dried gel sample to record the phase transformation temperature of zinc hydroxide Zn(OH)2 to zinc oxide (ZnO) to obtain the annealing temperature of 800C. The thermal, structure, morphology and optical properties have been employed by different techniques such as DSC-TGA, X-Ray Diffraction (XRD), Fourier Transform Infra-Red spectroscopy (FTIR), Micro Raman spectroscopy, UV-Visible absorption spectroscopy (UV-Vis), Photoluminescence spectroscopy (PL) and Field Effect Scanning Electron Microscopy (FESEM). X-ray diffraction results confirmed the wurtzite hexagonal structure of ZnO nanoparticles. The two intensive peaks at 160 and 432 cm-1 in the Raman Spectrum are mainly attributed to the first order modes of the wurtzite ZnO nanoparticles. The energy band gap obtained from the UV-Vis absorption spectra, shows a blue shift, which is attributed to increase in carrier concentration (Burstein Moss Effect). Photoluminescence studies of the single crystalline ZnO nanoparticles, show a strong peak centered at 385 nm, corresponding to the near band edge emission in ultraviolet range. The mixed shape of grapes, sphere, hexagonal and rock like structure has been noticed in FESEM. The results showed that PVP is a suitable capping agent for the preparation of ZnO nanoparticles by simple chemical precipitation method.

Keywords: ZnO nanoparticles, simple chemical precipitation route, mixed shape morphology, UV-visible absorption, photoluminescence, Fourier transform infra-Red spectroscopy

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Authors: Javad Yarmahmoudi, Alireza Mirzaee

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Many active and passive structural health monitoring (SHM) techniques have been developed for detection of the defects of plates. Generally, riveted joints hold the plates together and their failure may create accidents. In this study, well known active and passive methods were modified for the evaluation of the health of the riveted joints between the plates. The active method generated Lamb waves and monitored their propagation by using lead zirconate titanate (PZT) disks. The signal was analyzed by using the wavelet transformations. The passive method used the Fiber Bragg Grating (FBG) sensors and evaluated the spectral characteristics of the signals by using Fast Fourier Transformation (FFT). The results indicated that the existing methods designed for the evaluation of the health of individual plates may be used for inspection of riveted joints with software modifications.

Keywords: structural health monitoring, SHM, active SHM, passive SHM, fiber bragg grating sensor, lead zirconate titanate, PZT

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Authors: C. S. Jeba Samuel

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Soil, especially from oil field has posed a great hazard for terrestrial and marine ecosystems. The traditional treatment of oil contaminated soil cannot degrade the crude oil completely. So far, biodegradation proves to be an efficient method. During biodegradation, crude oil is used as the carbon source and addition of nitrogenous compounds increases the microbial growth, resulting in the effective breakdown of crude oil components to low molecular weight components. The present study was carried out to evaluate the biodegradation of crude oil by hydrocarbon-degrading microorganism Pseudomonas aeruginosa isolated from natural environment like oil contaminated soil. Pseudomonas aeruginosa, an oil degrading microorganism also called as hydrocarbon utilizing microorganism (or “HUM” bug) can utilize crude oil as sole carbon source. In this study, the biodegradation of crude oil was conducted with modified mineral basal salt medium and nitrogen sources so as to increase the degradation. The efficacy of the plasmid from the isolated strain was incorporated into E.coli DH5 α host to speed up the degradation of oil. The usage of molecular techniques has increased oil degradation which was confirmed by the degradation of aromatic and aliphatic rings of hydrocarbons and was inferred by the lesser number of peaks in Fourier Transform Infrared Spectroscopy (FTIR). The gas chromatogram again confirms better degradation by transformed cells by the lesser number of components obtained in the oil treated with transformed cells. This study demonstrated the technical feasibility of using direct inoculation of transformed cells onto the oil contaminated region thereby leading to the achievement of better oil degradation in a shorter time than the degradation caused by the wild strain.

Keywords: biodegradation, aromatic rings, plasmid, hydrocarbon, Fourier Transform Infrared Spectroscopy (FTIR)

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Authors: Kamel Malik Bensafta, Gervasio Bensafta

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The purpose of this paper is to investigate the relationship between oil prices and socks markets. The empirical analysis in this paper is conducted within the context of Multivariate GARCH models, using a transform version of the so-called BEKK parameterization. We show that mean and uncertainty of US market are transmitted to oil market and European market. We also identify an important transmission from WTI prices to Brent Prices.

Keywords: oil volatility, stock markets, MGARCH, transmission, structural break

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Authors: E. Gandomkar, S. Sabbaghi

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In this paper, the effects of variation synthesized methods on morphology and size of silica nanostructure via modifying sol-gel and precipitation method have been investigated. Meanwhile, resulting products have been characterized by particle size analyzer, scanning electron microscopy (SEM), X-ray Diffraction (XRD) and Fourier transform infrared (FT-IR) spectra. As result, the shape of SiO2 with sol-gel and precipitation methods was spherical but with modifying sol-gel method we have been had nanolayer structure.

Keywords: modified sol-gel, precipitation, nanolayer, Na2SiO3, nanoparticle

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Authors: Brayden Mi

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Reverse time migration has been widely used in the Petroleum exploration industry to reveal subsurface images and to detect rock and fluid properties since the early 1980s. The seismic technology involves the construction of a velocity model through interpretive model construction, seismic tomography, or full waveform inversion, and the application of the reverse-time propagation of acquired seismic data and the original wavelet used in the acquisition. The methodology has matured from 2D, simple media to present-day to handle full 3D imaging challenges in extremely complex geological conditions. Conventional Ultrasound computed tomography (USCT) utilize travel-time-inversion to reconstruct the velocity structure of an organ. With the velocity structure, USCT data can be migrated with the “bend-ray” method, also known as migration. Its seismic application counterpart is called Kirchhoff depth migration, in which the source of reflective energy is traced by ray-tracing and summed to produce a subsurface image. It is well known that ray-tracing-based migration has severe limitations in strongly heterogeneous media and irregular acquisition geometries. Reverse time migration (RTM), on the other hand, fully accounts for the wave phenomena, including multiple arrives and turning rays due to complex velocity structure. It has the capability to fully reconstruct the image detectable in its acquisition aperture. The RTM algorithms typically require a rather accurate velocity model and demand high computing powers, and may not be applicable to real-time imaging as normally required in day-to-day medical operations. However, with the improvement of computing technology, such a computational bottleneck may not present a challenge in the near future. The present-day (RTM) algorithms are typically implemented from a flat datum for the seismic industry. It can be modified to accommodate any acquisition geometry and aperture, as long as sufficient illumination is provided. Such flexibility of RTM can be conveniently implemented for the application in USCT imaging if the spatial coordinates of the transmitters and receivers are known and enough data is collected to provide full illumination. This paper proposes an implementation of a full 3D RTM algorithm for USCT imaging to produce an accurate 3D acoustic image based on the Phase-shift-plus-interpolation (PSPI) method for wavefield extrapolation. In this method, each acquired data set (shot) is propagated back in time, and a known ultrasound wavelet is propagated forward in time, with PSPI wavefield extrapolation and a piece-wise constant velocity model of the organ (breast). The imaging condition is then applied to produce a partial image. Although each image is subject to the limitation of its own illumination aperture, the stack of multiple partial images will produce a full image of the organ, with a much-reduced noise level if compared with individual partial images.

Keywords: illumination, reverse time migration (RTM), ultrasound computed tomography (USCT), wavefield extrapolation

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Authors: Kamel Malik Bensafta, Gervasio Semedo

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The purpose of this paper is to investigate the relationship between oil prices and socks markets. The empirical analysis in this paper is conducted within the context of Multivariate GARCH models, using a transform version of the so-called BEKK parameterization. We show that mean and uncertainty of US market are transmitted to oil market and European market. We also identify an important transmission from WTI prices to Brent Prices.

Keywords: oil volatility, stock markets, MGARCH, transmission, structural break

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Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in various domains has created a pressing need for effective methods to transform this data into meaningful knowledge. In this era of big data, mathematical and statistical innovations play a crucial role in unlocking insights and facilitating informed decision-making in data analytics. This abstract aims to explore the transformative potential of these innovations and their impact on converting raw data into actionable knowledge. Drawing upon a comprehensive review of existing literature, this research investigates the cutting-edge mathematical and statistical techniques that enable the conversion of data into knowledge. By evaluating their underlying principles, strengths, and limitations, we aim to identify the most promising innovations in data analytics. To demonstrate the practical applications of these innovations, real-world datasets will be utilized through case studies or simulations. This empirical approach will showcase how mathematical and statistical innovations can extract patterns, trends, and insights from complex data, enabling evidence-based decision-making across diverse domains. Furthermore, a comparative analysis will be conducted to assess the performance, scalability, interpretability, and adaptability of different innovations. By benchmarking against established techniques, we aim to validate the effectiveness and superiority of the proposed mathematical and statistical innovations in data analytics. Ethical considerations surrounding data analytics, such as privacy, security, bias, and fairness, will be addressed throughout the research. Guidelines and best practices will be developed to ensure the responsible and ethical use of mathematical and statistical innovations in data analytics. The expected contributions of this research include advancements in mathematical and statistical sciences, improved data analysis techniques, enhanced decision-making processes, and practical implications for industries and policymakers. The outcomes will guide the adoption and implementation of mathematical and statistical innovations, empowering stakeholders to transform data into actionable knowledge and drive meaningful outcomes.

Keywords: data analytics, mathematical innovations, knowledge extraction, decision-making

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Authors: Adrián P. Gómez Mañas

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Autonomous vehicles have already transformed urban policies and cities. This is the main assumption of our research, which aims to understand how the representations of the possible arrival of autonomous vehicles already transform priorities or actions in transport and more largely, urban policies. This research is done within the framework of a Ph.D. doctorate directed by Professor Xavier Desjardins at the Sorbonne University of Paris. Our hypotheses are: (i) the perspectives, representations, and imaginaries on autonomous vehicles already affect the stakeholders of urban policies; (ii) the discourses on the opportunities or threats of autonomous vehicles reflect the current strategies of the stakeholders. Each stakeholder tries to integrate a discourse on autonomous vehicles that allows them to change as little as possible their current tactics and strategies. The objective is to eventually make a comparison between three different cases: Paris, United Arab Emirates, and Bogota. We chose those territories because their contexts are very different, but they all have important interests in mobility and innovation, and they all have started to reflect on the subject of self-driving mobility. The main methodology used is to interview actors of the metropolitan area (local officials, leading urban and transport planners, influent experts, and private companies). This work is supplemented with conferences, official documents, press articles, and websites. The objective is to understand: 1) What they know about autonomous vehicles and where does their knowledge come from; 2) What they expect from autonomous vehicles; 3) How their ideas about autonomous vehicles are transforming their action and strategy in managing daily mobility, investing in transport, designing public spaces and urban planning. We are going to present the research and some preliminary results; we will show that autonomous vehicles are often viewed by public authorities as a lever to reach something else. We will also present that speeches are very influenced by local context (political, geographical, economic, etc.), creating an interesting balance between global and local influences. We will analyze the differences and similarities between the three cases and will try to understand which are the causes.

Keywords: autonomous vehicles, self-driving mobility, urban planning, urban mobility, transport, public policies

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Authors: Anil Kumar Baral

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The research introduces a ground-breaking approach to waste management, emphasizing innovation, education, and transformation. Using Chandragiri Municipality as a case study, the study advocates a shift from traditional to progressive waste management strategies, contributing an inventive waste framework, sustainability advocacy, and a transformative blueprint. The waste composition analysis highlights Chandragiri's representative profile, leading to a comprehensive plan addressing challenges and recommending a transition to a profitable waste treatment model, supported by relevant statistics. The data-driven approach incorporates the official data of waste Composition from Chandragiri Municipality as secondary data and incorporates the primary data from Chandragiri households, ensuring a nuanced perspective. Discussions on implementation, viability, and environmental preservation underscore the dual benefit of sustainability. The study includes a comparative analysis, monitoring, and evaluation framework, examining international relevance and collaboration, and conducting a social and environmental impact assessment. The results indicate the necessity for creative changes in Chandragiri's waste practices, recommending separate treatment centers in wards level rather than Municipal level, composting machines, and a centralized waste treatment plant. Educational reforms involve revising school curricula and awareness campaigns. The transformation's success hinges on reducing waste size, efficient treatment center operation, and ongoing public literacy. The conclusion summarizes key findings, envisioning a future with sustainable waste management practices deeply embedded in the community fabric.

Keywords: innovate, educate, transform, municipality, method

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Authors: S. Guruprasad, M. Z. Kurian, H. N. Suma

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Medical imaging modalities are becoming life saving components. These modalities are very much essential to doctors for proper diagnosis, treatment planning and follow up. Some modalities provide anatomical information such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), X-rays and some provides only functional information such as Positron Emission Tomography (PET). Therefore, single modality image does not give complete information. This paper presents the fusion of structural information in CT and functional information present in PET image. This fused image is very much essential in detecting the stages and location of abnormalities and in particular very much needed in oncology for improved diagnosis and treatment. We have implemented and compared image fusion techniques like pyramid, wavelet, and principal components fusion methods along with hybrid method of DWT and PCA. The performances of the algorithms are evaluated quantitatively and qualitatively. The system is implemented and tested by using MATLAB software. Based on the MSE, PSNR and ENTROPY analysis, PCA and DWT-PCA methods showed best results over all experiments.

Keywords: image fusion, pyramid, wavelets, principal component analysis

Procedia PDF Downloads 258

Authors: Mostafa Shahriari, Sergio Rojas, David Pardo, Angel Rodriguez- Rozas, Shaaban A. Bakr, Victor M. Calo, Ignacio Muga

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Logging-While Drilling (LWD) is a technique to record down-hole logging measurements while drilling the well. Nowadays, LWD devices (e.g., nuclear, sonic, resistivity) are mostly used commercially for geo-steering applications. Modern borehole resistivity tools are able to measure all components of the magnetic field by incorporating tilted coils. The depth of investigation of LWD tools is limited compared to the thickness of the geological layers. Thus, it is a common practice to approximate the Earth’s subsurface with a sequence of 1D models. For a 1D model, we can reduce the dimensionality of the problem using a Hankel transform. We can solve the resulting system of ordinary differential equations (ODEs) either (a) analytically, which results in a so-called semi-analytic method after performing a numerical inverse Hankel transform, or (b) numerically. Semi-analytic methods are used by the industry due to their high performance. However, they have major limitations, namely: -The analytical solution of the aforementioned system of ODEs exists only for piecewise constant resistivity distributions. For arbitrary resistivity distributions, the solution of the system of ODEs is unknown by today’s knowledge. -In geo-steering, we need to solve inverse problems with respect to the inversion variables (e.g., the constant resistivity value of each layer and bed boundary positions) using a gradient-based inversion method. Thus, we need to compute the corresponding derivatives. However, the analytical derivatives of cross-bedded formation and the analytical derivatives with respect to the bed boundary positions have not been published to the best of our knowledge. The main contribution of this work is to overcome the aforementioned limitations of semi-analytic methods by solving each 1D model (associated with each Hankel mode) using an efficient multi-scale finite element method. The main idea is to divide our computations into two parts: (a) offline computations, which are independent of the tool positions and we precompute only once and use them for all logging positions, and (b) online computations, which depend upon the logging position. With the above method, (a) we can consider arbitrary resistivity distributions along the 1D model, and (b) we can easily and rapidly compute the derivatives with respect to any inversion variable at a negligible additional cost by using an adjoint state formulation. Although the proposed method is slower than semi-analytic methods, its computational efficiency is still high. In the presentation, we shall derive the mathematical variational formulation, describe the proposed multi-scale finite element method, and verify the accuracy and efficiency of our method by performing a wide range of numerical experiments and comparing the numerical solutions to semi-analytic ones when the latest are available.

Keywords: logging-While-Drilling, resistivity measurements, multi-scale finite elements, Hankel transform

Procedia PDF Downloads 359

Authors: Amit Kumar Happy

Abstract:

This paper is motivated by the importance of multi-sensor image fusion with a specific focus on infrared (IR) and visual image (VI) fusion for various applications, including military reconnaissance. Image fusion can be defined as the process of combining two or more source images into a single composite image with extended information content that improves visual perception or feature extraction. These images can be from different modalities like visible camera & IR thermal imager. While visible images are captured by reflected radiations in the visible spectrum, the thermal images are formed from thermal radiation (infrared) that may be reflected or self-emitted. A digital color camera captures the visible source image, and a thermal infrared camera acquires the thermal source image. In this paper, some image fusion algorithms based upon multi-scale transform (MST) and region-based selection rule with consistency verification have been proposed and presented. This research includes the implementation of the proposed image fusion algorithm in MATLAB along with a comparative analysis to decide the optimum number of levels for MST and the coefficient fusion rule. The results are presented, and several commonly used evaluation metrics are used to assess the suggested method's validity. Experiments show that the proposed approach is capable of producing good fusion results. While deploying our image fusion algorithm approaches, we observe several challenges from the popular image fusion methods. While high computational cost and complex processing steps of image fusion algorithms provide accurate fused results, they also make it hard to become deployed in systems and applications that require a real-time operation, high flexibility, and low computation ability. So, the methods presented in this paper offer good results with minimum time complexity.

Keywords: image fusion, IR thermal imager, multi-sensor, multi-scale transform

Procedia PDF Downloads 84

Authors: Ali Pour Yazdanpanah, Farideh Foroozandeh Shahraki, Emma Regentova

Abstract:

The reconstruction from sparse-view projections is one of important problems in computed tomography (CT) limited by the availability or feasibility of obtaining of a large number of projections. Traditionally, convex regularizers have been exploited to improve the reconstruction quality in sparse-view CT, and the convex constraint in those problems leads to an easy optimization process. However, convex regularizers often result in a biased approximation and inaccurate reconstruction in CT problems. Here, we present a nonconvex, Lipschitz continuous and non-smooth regularization model. The CT reconstruction is formulated as a nonconvex constrained L1 − L2 minimization problem and solved through a difference of convex algorithm and alternating direction of multiplier method which generates a better result than L0 or L1 regularizers in the CT reconstruction. We compare our method with previously reported high performance methods which use convex regularizers such as TV, wavelet, curvelet, and curvelet+TV (CTV) on the test phantom images. The results show that there are benefits in using the nonconvex regularizer in the sparse-view CT reconstruction.

Keywords: computed tomography, non-convex, sparse-view reconstruction, L1-L2 minimization, difference of convex functions

Procedia PDF Downloads 284