Search results for: Radon Transform

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: 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: 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: M. Shokry Rashwan

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This study follows a number of experiments conducted at Red River College (RRC) to investigate the short term properties of tire derived aggregate (TDA) produced from shredding off-the-road (OTR) wasted tires in a proposed new application. The application targets replacing natural material used under concrete slabs and as backfills for residential homes’ basement slabs and walls, respectively, with TDA. The experimental work included determining: compressibility, gradation distribution, unit weight, hydraulic conductivity and lateral pressure. Based on the results of those short term properties; it was decided to move forward to study the long-term performance of this otherwise waste material through on-site demonstration. A full-scale basement replicating a typical Manitoba home was therefore built at RRC where both TDA and Natural Materials (NM) were used side-by-side. A large number of sensing and measuring systems are used to compare between the performances of each material when exposed to the typical ground and weather conditions. Parameters monitored and measured include heat losses, moisture migration, drainage ability, lateral pressure, relative movements of slabs and walls, an integrity of ground water and radon emissions. Up-to-date results have confirmed part of the conclusions reached from the earlier laboratory experiments. However, other results have shown that construction practices; such as placing and compaction, may need some adjustments to achieve more desirable outcomes. This presentation provides a review of both short-term tests as well as up-to-date analysis of the on-site demonstration.

Keywords: tire derived aggregate (TDA), basement construction, TDA material properties, lateral pressure of TDA, hydraulic conductivity of TDA

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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

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Authors: Amit Kumar Happy

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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

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Authors: Jae-Neung Lee, Keun-Chang Kwak

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This paper describes an analysis of Yacht Simulator international trends and also explains about Yacht. Examples of yacht Simulator using Yacht Simulator include image processing for totaling the total number of vehicles, edge/target detection, detection and evasion algorithm, image processing using SIFT (scale invariant features transform) matching, and application of median filter and thresholding.

Keywords: yacht simulator, simulator, trends analysis, SIFT

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Authors: Neha Thakur, Pravin S. More

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The interaction of CO, H2 and LPG with Cu-dosed SnO2 catalysts was studied by means of Fourier transform infrared spectroscopy (FTIR). With increasing Cu loading, pronounced and progressive red shifts of the C–O stretching frequency associated with molecular CO adsorbed on the Cu/SnO2 component were observed. This decrease in n(CO) correlates with enhancement of CO dissociation at higher temperatures on Cu promoted SnO2 catalysts under conditions, where clean Cu is almost ineffective. In the conclusion, the capability of our technique is discussed, and a technique for enhancing the sensitivity in our technique is proposed.

Keywords: FTIR, spectroscopic, dissociation, n(CO)

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Authors: Pudji Astuti, C. P. C. Putro, C. M. Airin, L. Sjahfirdi, S. Widiyanto, H. Maheshwari

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Stress of slaughter animals starting long before until at the time of process of slaughtering which cause misery and decrease of meat quality. Meanwhile, determination of animal stress using hormonal such as cortisol is expensive and less practical so that portable stress indicator for cows based on Fourier Transform Infrared Spectroscopy (FTIR) must be provided. The aims of this research are to find out the comparison process of slaughter between Rope Casting Local (RCL) and Restraining Box Method (RBM) by measuring of cortisol and wavelength in FTIR methods. Thirty two of male Ongole crossbred cattle were used in this experiment. Blood sampling was taken from jugular vein when they were rested and repeated when slaughtered. All of blood samples were centrifuged at 3000 rpm for 20 minutes to get serum, and then divided into two parts for cortisol assayed using ELISA and for measuring the wavelength using FTIR. The serum then measured at the wavelength between 4000-400 cm-1 using MB3000 FTIR. Band data absorption in wavelength of FTIR is analyzed descriptively by using FTIR Horizon MBTM. For RCL, average of serum cortisol when the animals rested were 11.47 ± 4.88 ng/mL, when the time of slaughter were 23.27 ± 7.84 ng/mL. For RBM, level of cortisol when rested animals were 13.67 ± 3.41 ng/mL and 53.47 ± 20.25 ng/mL during the slaughter. Based on student t-Test, there were significantly different between RBM and RCL methods when beef cattle were slaughtered (P < 0.05), but no significantly different when animals were rested (P > 0.05). Result of FTIR with the various of wavelength such as methyl group (=CH3) 2986cm-1, methylene (=CH2) 2827 cm-1, hydroxyl (-OH) 3371 cm-1, carbonyl (ketones) (C=O) 1636 cm-1, carboxyl (COO-1) 1408 cm-1, glucosa 1057 cm-1, urea 1011 cm-1have been obtained. It can be concluded that the RCL slaughtered method is better than the RBM method based on the increase of cortisol as an indicator of stress in beef cattle (P<0.05). FTIR is really possible to be used as stub of stress tool due to differentiate of resting and slaughter condition by recognizing the increase of absorption and the separation of component group at the wavelength.

Keywords: cows, cortisol, FTIR, RBM, RCL, stress indicator

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Authors: Marwa A. A. Ragab, Hadir M. Maher, Eman I. El-Kimary

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Co-administration of methotrexate (MTX) and aspirin (ASP) can cause a pharmacokinetic interaction and a subsequent increase in blood MTX concentrations which may increase the risk of MTX toxicity. Therefore, it is important to develop a sensitive, selective, accurate and precise method for their simultaneous determination in urine. A new hybrid chemometric method has been applied to the emission response data of the two drugs. Spectrofluorimetric method for determination of MTX through measurement of its acid-degradation product, 4-amino-4-deoxy-10-methylpteroic acid (4-AMP), was developed. Moreover, the acid-catalyzed degradation reaction enables the spectrofluorimetric determination of ASP through the formation of its active metabolite salicylic acid (SA). The proposed chemometric method deals with convolution of emission data using 8-points sin xi polynomials (discrete Fourier functions) after the derivative treatment of these emission data. The first and second derivative curves (D1 & D2) were obtained first then convolution of these curves was done to obtain first and second derivative under Fourier functions curves (D1/FF) and (D2/FF). This new application was used for the resolution of the overlapped emission bands of the degradation products of both drugs to allow their simultaneous indirect determination in human urine. Not only this chemometric approach was applied to the emission data but also the obtained data were subjected to non-parametric linear regression analysis (Theil’s method). The proposed method was fully validated according to the ICH guidelines and it yielded linearity ranges as follows: 0.05-0.75 and 0.5-2.5 µg mL-1 for MTX and ASP respectively. It was found that the non-parametric method was superior over the parametric one in the simultaneous determination of MTX and ASP after the chemometric treatment of the emission spectra of their degradation products. The work combines the advantages of derivative and convolution using discrete Fourier function together with the reliability and efficacy of the non-parametric analysis of data. The achieved sensitivity along with the low values of LOD (0.01 and 0.06 µg mL-1) and LOQ (0.04 and 0.2 µg mL-1) for MTX and ASP respectively, by the second derivative under Fourier functions (D2/FF) were promising and guarantee its application for monitoring the two drugs in patients’ urine samples.

Keywords: chemometrics, emission curves, derivative, convolution, Fourier transform, human urine, non-parametric regression, Theil’s method

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Authors: Olivier Delage, Thierry Portafaix, Hassan Bencherif, Guillaume Guimbretiere

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Most observation data sequences in geophysics can be interpreted as resulting from the interaction of several physical processes at several time and space scales. As a consequence, measurements time series in geophysics have often characteristics of non-linearity and non-stationarity and thereby exhibit strong fluctuations at all time-scales and require a time-frequency representation to analyze their variability. Empirical Mode Decomposition (EMD) is a relatively new technic as part of a more general signal processing method called the Hilbert-Huang transform. This analysis method turns out to be particularly suitable for non-linear and non-stationary signals and consists in decomposing a signal in an auto adaptive way into a sum of oscillating components named IMFs (Intrinsic Mode Functions), and thereby acts as a bank of bandpass filters. The advantages of the EMD technic are to be entirely data driven and to provide the principal variability modes of the dynamics represented by the original time series. However, the main limiting factor is the frequency resolution that may give rise to the mode mixing phenomenon where the spectral contents of some IMFs overlap each other. To overcome this problem, J. Gilles proposed an alternative entitled “Empirical Wavelet Transform” (EWT) which consists in building from the segmentation of the original signal Fourier spectrum, a bank of filters. The method used is based on the idea utilized in the construction of both Littlewood-Paley and Meyer’s wavelets. The heart of the method lies in the segmentation of the Fourier spectrum based on the local maxima detection in order to obtain a set of non-overlapping segments. Because linked to the Fourier spectrum, the frequency resolution provided by EWT is higher than that provided by EMD and therefore allows to overcome the mode-mixing problem. On the other hand, if the EWT technique is able to detect the frequencies involved in the original time series fluctuations, EWT does not allow to associate the detected frequencies to a specific mode of variability as in the EMD technic. Because EMD is closer to the observation of physical phenomena than EWT, we propose here a new technic called EAWD (Empirical Adaptive Wavelet Decomposition) based on the coupling of the EMD and EWT technics by using the IMFs density spectral content to optimize the segmentation of the Fourier spectrum required by EWT. In this study, EMD and EWT technics are described, then EAWD technic is presented. Comparison of results obtained respectively by EMD, EWT and EAWD technics on time series of ozone total columns recorded at Reunion island over [1978-2019] period is discussed. This study was carried out as part of the SOLSTYCE project dedicated to the characterization and modeling of the underlying dynamics of time series issued from complex systems in atmospheric sciences

Keywords: adaptive filtering, empirical mode decomposition, empirical wavelet transform, filter banks, mode-mixing, non-linear and non-stationary time series, wavelet

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Authors: Sharmin Akhter, M. Salahuddin, Sukalyan Kumar Kundu, Mohammad Fahim Kadir

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Relatively insoluble candidate drug like carbamazepine (CBZ) often exhibit incomplete or erratic absorption; and hence wide consideration is given to improve aqueous solubility of such compound. Solid dispersions were formulated with an aim of improving aqueous solubility, oral bioavailability and the rate of dissolution of Carbamazepine using different hydrophyllic polymer like Polyethylene Glycol (PEG) 6000, Polyethylene Glycol (PEG) 4000, kollidon 30, HPMC 6 cps, poloxamer 407 and povidone k 30. Solid dispersions were prepared with different drug to polymer weight ratio by the solvent evaporation method where methanol was used as solvent. Drug-polymer physical mixtures were also prepared to compare the rate of dissolution. Effects of different polymer were studied for solid dispersion formulation as well as physical mixtures. These formulations were characterized in the solid state by Fourier Transform Infrared (FTIR) spectroscopy and Scanning Electron Microscopy (SEM). Solid state characterization indicated CBZ was present as fine particles and entrapped in carrier matrix of PEG 6000 and PVP K30 solid dispersions. Fourier Transform Infrared (FTIR) spectroscopic studies showed the stability of CBZ and absence of well-defined drug-polymer interactions. In contrast to the very slow dissolution rate of pure CBZ, dispersions of drug in polymers considerably improved the dissolution rate. This can be attributed to increased wettability and dispersibility, as well as decreased crystallinity and increase in amorphous fraction of drug. Solid dispersion formulations containing PEG 6000 and Povidone K 30 showed maximum drug release within one hour at the ratio of 1:1:1. Even physical mixtures of CBZ prepared with both carriers also showed better dissolution profiles than those of pure CBZ. In conclusions, solid dispersions could be a promising delivery of CBZ with improved oral bioavailability and immediate release profiles.

Keywords: carbamazepine, FTIR, kollidon 30, HPMC 6 CPS, PEG 6000, PEG 4000, poloxamer 407, water solubility, povidone k 30, SEM, solid dispersion

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Authors: Abdelhalim. N. Mohammed, Mohammed. Y. Esmail

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In the course of recent decades, medical imaging has been dominated by the use of costly film media for review and archival of medical investigation, however due to developments in networks technologies and common acceptance of a standard digital imaging and communication in medicine (DICOM) another approach in light of World Wide Web was produced. Web technologies successfully used in telemedicine applications, the combination of web technologies together with DICOM used to design a web-based and open source DICOM viewer. The Web server allowance to inquiry and recovery of images and the images viewed/manipulated inside a Web browser without need for any preinstalling software. The dynamic site page for medical images visualization and processing created by using JavaScript and HTML5 advancements. The XAMPP ‘apache server’ is used to create a local web server for testing and deployment of the dynamic site. The web-based viewer connected to multiples devices through local area network (LAN) to distribute the images inside healthcare facilities. The system offers a few focal points over ordinary picture archiving and communication systems (PACS): easy to introduce, maintain and independently platforms that allow images to display and manipulated efficiently, the system also user-friendly and easy to integrate with an existing system that have already been making use of web technologies. The wavelet-based image compression technique on which 2-D discrete wavelet transform used to decompose the image then wavelet coefficients are transmitted by entropy encoding after threshold to decrease transmission time, stockpiling cost and capacity. The performance of compression was estimated by using images quality metrics such as mean square error ‘MSE’, peak signal to noise ratio ‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when ‘coif3’ wavelet filter is used.

Keywords: DICOM, discrete wavelet transform, PACS, HIS, LAN

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Authors: Karen Miner-Romanoff

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Few art programs for incarcerated juveniles exist; however, evaluation results indicate decreased recidivism and behavior problems. This paper reports on an on-going study of a promising art program for incarcerated adolescents with community exhibits and charitable sale of their work. Voices from Inside, a partnership between Franklin University and the Ohio Department of Youth Services, sponsored three exhibits in 2012, 2013, and 2014. In 2013, youth exhibitor survey results (response rate 47%, 16 of 34) showed that 81% cited as benefits cooperation with others, task completion, and increased self-esteem from public recognition and art sales. Community attendee survey results (response rate 29.5%, 59 of 200) showed positive attitude changes toward juvenile offenders, from 40% to 53%. Qualitative responses were similarly positive. The 2014 youth exhibitor sample was larger (response rate 58%, 29 of 50) and showed that 93% cited positive benefits including increase in self-esteem, decrease in stress, pride or recognition of the ability to reach a goal from completing, exhibiting and selling their art to benefit a charity for at-risk youth. This year, the research was able to conduct ten one-on-one interviews inside of the youth facilities, and qualitative responses were even more positive with one youth explaining, “This art represents my joy, my tears, my pain and my hope.” Community attendee survey results (response rate 50%, 86 of 170) were transformative in that that they indicated significant impression on attitudes toward juvenile offenders and their rehabilitative needs with one attendee stating that the event had an, “Immense impact for me bringing into focus the humanity and value these youth still have for us and society.” Future research indicates a need for a correlation study to determine the extent to which these art programs reduce behavioral incidents inside of the facility and long-term reduction in reoffending rates. Generally, further study of juvenile offenders’ art for rehabilitation and restorative justice, the power of art to transform, and university-community partnerships implementing art programs for juvenile offenders should continue.

Keywords: art, juvenile, incarcerated, restorative justice

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

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In this paper, a simple chemical precipitation route for the preparation of titanium dioxide nanoparticles, synthesized by using titanium tetra isopropoxide as a precursor and polyvinyl pyrrolidone (PVP) as a capping agent, is reported. The Differential Scanning Calorimetry (DSC) and Thermo Gravimetric Analysis (TGA) of the samples were recorded and the phase transformation temperature of titanium hydroxide, Ti(OH)₄ to titanium oxide, TiO₂ was investigated. The as-prepared Ti(OH)₄ precipitate was annealed at 800°C to obtain TiO₂ nanoparticles. The thermal, structural, morphological and textural characterizations of the TiO₂ nanoparticle samples were carried out 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) techniques. The as-prepared precipitate was characterized using DSC-TGA and confirmed the mass loss of around 30%. XRD results exhibited no diffraction peaks attributable to anatase phase, for the reaction products, after the solvent removal. The results indicate that the product is purely rutile. The vibrational frequencies of two main absorption bands of prepared samples are discussed from the results of the FTIR analysis. The formation of nanosphere of diameter of the order of 10 nm, has been confirmed by FESEM. The optical band gap was found by using UV-Visible spectrum. From photoluminescence spectra, a strong emission was observed. The obtained results suggest that this method provides a simple, efficient and versatile technique for preparing TiO₂ nanoparticles and it has the potential to be applied to other systems for photocatalytic activity.

Keywords: TiO2 nanoparticles, chemical precipitation route, phase transition, 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)

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Authors: Jiraporn Weenuttranon

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The ASEAN Economic Community (AEC) shall be the goal of regional economic integration among ASEAN countries. The goal of establishing AEC is to transform the region into a single market and production base with a highly competitive advantage to make it a stable and prosperous region. However, with the wild range of economic conditions in each country, the implementation of its objectives under the limited resources available in the past showed the weakness of the region. For this reason, the group of countries in the region should allocate its rich potential of the region by collaborating effectively.

Keywords: impact, AEC, influence, direction, politics, Thailand

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Authors: Saeed Khodabakhshi, Alimorad Rashidi, Ziba Tavakoli, Sajad Kiani, Sadegh Dastkhoon

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Alumina nanoparticles (γ-Al2O3 NPs) were prepared via a new and simple synthetic route and characterized by field emission scanning electron microscope, X-ray diffraction, and Fourier transform infrared spectroscopy. The catalytic activity of prepared γ-Al2O3 NPs was investigated for the one-pot, four-component synthesis of fused tri-heterocyclic compounds containing pyrazole, pyran, and pyrimidine. This procedure has some advantages such as high efficiency, simplicity, high rate and environmental safety.

Keywords: alumina nanoparticles, one-pot, fused tri-heterocyclic compounds, pyran

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Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

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Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

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Authors: Liang Cheng Chang, Wei Ju Huang, You Cheng Chen

Abstract:

Investigation and research are keys for conjunctive use of surface and groundwater resources. The hydrogeological structure is an important base for groundwater analysis and simulation. Traditionally, the hydrogeological structure is artificially determined based on geological drill logs, the structure of wells, groundwater levels, and so on. In Taiwan, groundwater observation network has been built and a large amount of groundwater-level observation data are available. The groundwater level is the state variable of the groundwater system, which reflects the system response combining hydrogeological structure, groundwater injection, and extraction. This study applies analytical tools to the observation database to develop a methodology for the identification of confined and unconfined aquifers. These tools include frequency analysis, cross-correlation analysis between rainfall and groundwater level, groundwater regression curve analysis, and decision tree. The developed methodology is then applied to groundwater layer identification of two groundwater systems: Zhuoshui River alluvial fan and Pingtung Plain. The abovementioned frequency analysis uses Fourier Transform processing time-series groundwater level observation data and analyzing daily frequency amplitude of groundwater level caused by artificial groundwater extraction. The cross-correlation analysis between rainfall and groundwater level is used to obtain the groundwater replenishment time between infiltration and the peak groundwater level during wet seasons. The groundwater regression curve, the average rate of groundwater regression, is used to analyze the internal flux in the groundwater system and the flux caused by artificial behaviors. The decision tree uses the information obtained from the above mentioned analytical tools and optimizes the best estimation of the hydrogeological structure. The developed method reaches training accuracy of 92.31% and verification accuracy 93.75% on Zhuoshui River alluvial fan and training accuracy 95.55%, and verification accuracy 100% on Pingtung Plain. This extraordinary accuracy indicates that the developed methodology is a great tool for identifying hydrogeological structures.

Keywords: aquifer identification, decision tree, groundwater, Fourier transform

Procedia PDF Downloads 133

Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

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Authors: Lukas Vierus, Thomas Schuster

Abstract:

A general framework is examined for dynamic tensor field tomography within an inhomogeneous medium characterized by refraction and absorption, treated as an inverse source problem concerning the associated transport equation. Guided by Fermat’s principle, the Riemannian metric within the specified domain is determined by the medium's refractive index. While considerable literature exists on the inverse problem of reconstructing a tensor field from its longitudinal ray transform within a static Euclidean environment, limited inversion formulas and algorithms are available for general Riemannian metrics and time-varying tensor fields. It is established that tensor field tomography, akin to an inverse source problem for a transport equation, persists in dynamic scenarios. Framing dynamic tensor tomography as an inverse source problem embodies a comprehensive perspective within this domain. Ensuring well-defined forward mappings necessitates establishing existence and uniqueness for the underlying transport equations. However, the bilinear forms of the associated weak formulations fail to meet the coercivity condition. Consequently, recourse to viscosity solutions is taken, demonstrating their unique existence within suitable Sobolev spaces (in the static case) and Sobolev-Bochner spaces (in the dynamic case), under a specific assumption restricting variations in the refractive index. Notably, the adjoint problem can also be reformulated as a transport equation, with analogous results regarding uniqueness. Analytical solutions are expressed as integrals over geodesics, facilitating more efficient evaluation of forward and adjoint operators compared to solving partial differential equations. Certainly, here's the revised sentence in English: Numerical experiments are conducted using a Nesterov-accelerated Landweber method, encompassing various fields, absorption coefficients, and refractive indices, thereby illustrating the enhanced reconstruction achieved through this holistic modeling approach.

Keywords: attenuated refractive dynamic ray transform of tensor fields, geodesics, transport equation, viscosity solutions

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Authors: Miroslav Hyza, Petr Rulik, Vojtech Bednar, Jan Sury

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An early and reliable detection of an increased radioactivity level in the atmosphere is one of the key aspects of atmospheric radiological monitoring. Although the standard laboratory procedures provide detection limits as low as few µBq/m³, their major drawback is the delayed result reporting: typically a few days. This issue is the main objective of the HAMRAD project, which gave rise to a prototype of an autonomous monitoring device. It is based on the idea of sequential aerosol sampling using a carrousel sample changer combined with a gamma-ray spectrometer. In our hardware configuration, the air is drawn through a filter positioned on the carrousel so that it could be rotated into the measuring position after a preset sampling interval. Filter analysis is performed via a 50% HPGe detector inside an 8.5cm lead shielding. The spectrometer output signal is then analyzed using DSP electronics and Gamwin software with preset nuclide libraries and other analysis parameters. After the counting, the filter is placed into a storage bin with a capacity of 250 filters so that the device can run autonomously for several months depending on the preset sampling frequency. The device is connected to a central server via GPRS/GSM where the user can view monitoring data including raw spectra and technological data describing the state of the device. All operating parameters can be remotely adjusted through a simple GUI. The flow rate is continuously adjustable up to 10 m³/h. The main challenge in spectrum analysis is the natural background subtraction. As detection limits are heavily influenced by the deposited activity of radon decay products and the measurement time is fixed, there must exist an optimal sample decay time (delayed spectrum acquisition). To solve this problem, we adopted a simple procedure based on sequential spectrum acquisition and optimal partial spectral sum with respect to the detection limits for a particular radionuclide. The prototyped device proved to be able to detect atmospheric contamination at the level of mBq/m³ per an 8h sampling.

Keywords: aerosols, atmosphere, atmospheric radioactivity monitoring, autonomous sampler

Procedia PDF Downloads 124

Authors: Christine O. Wangia, Jennifer A. Orwa, Francis W. Muregi, Patrick G. Kareru, Kipyegon Cheruiyot, Eric Guantai

Abstract:

Ruellia (syn. Dipteracanthus) species are wild perennial creepers belonging to the Acanthaceae family. These species are reported to possess anti-inflammatory, analgesic, antioxidant, gastroprotective, anticancer, and immuno-stimulant properties. Phytochemical screening of both aqueous and methanolic extracts of Ruellia species revealed the presence of saponins. Saponins have been reported to possess anti-inflammatory, antioxidant, immuno-stimulant, antihepatotoxic, antibacterial, anticarcinogenic, and antiulcerogenic activities. The objective of this study was to quantify and analyze the Fourier transform infrared (FTIR) spectra of saponins in crude extracts of three Kenyan Ruellia species namely Ruellia prostrata (RPM), Ruellia lineari-bracteolata (RLB) and Ruellia bignoniiflora (RBK). Sequential organic extraction of the ground whole plant material was done using petroleum ether (PE), chloroform, ethyl acetate (EtOAc), and absolute methanol by cold maceration, while aqueous extraction was by hot maceration. The plant powders and extracts were mixed with spectroscopic grade KBr and compressed into a pellet. The infrared spectra were recorded using a Shimadzu FTIR spectrophotometer of 8000 series in the range of 3500 cm^-1 - 500 cm^-1. Quantitative determination of the saponins was done using standard procedures. Quantitative analysis of saponins showed that RPM had the highest quantity of crude saponins (2.05% ± 0.03), followed by RLB (1.4% ± 0.15) and RBK (1.25% ± 0.11), respectively. FTIR spectra revealed the spectral peaks characteristic for saponins in RPM, RLB, and RBK plant powders, aqueous and methanol extracts; O-H absorption (3265 - 3393 cm^-1), C-H absorption ranging from 2851 to 2924 cm^-1, C=C absorbance (1628 - 1655 cm^-1), oligosaccharide linkage (C-O-C) absorption due to sapogenins (1036 - 1042 cm^-1). The crude saponins from RPM, RLB and RBK showed similar peaks to their respective extracts. The presence of the saponins in extracts of RPM, RLB and RBK may be responsible for some of the biological activities reported in the Ruellia species.1

Keywords: Ruellia bignoniiflora, Ruellia linearibracteolata, Ruellia prostrata, Saponins

Procedia PDF Downloads 147

Authors: A. Kyprianou, A. Tjirkallis

Abstract:

Condition monitoring of structures in service is very important as it provides information about the risk of damage development. One of the essential constituents of structural condition monitoring is the damage detection methodology. In the context of condition monitoring of in service structures a damage detection methodology analyses data obtained from the structure while it is in operation. Usually, this means that the data could be affected by operational and environmental conditions in a way that could mask the effects of a possible damage on the data. This, depending on the damage detection methodology, could lead to either false alarms or miss existing damages. In this article a damage detection methodology that is based on the Spatio-temporal continuous wavelet transform (SPT-CWT) analysis of a sequence of experimental time responses of a cantilever beam is proposed. The cantilever is subjected to white and pink noise excitation to simulate different operating conditions. In addition, in order to simulate changing environmental conditions, the cantilever is subjected to heating by a heat gun. The response of the cantilever beam is measured by a high-speed camera. Edges are extracted from the series of images of the beam response captured by the camera. Subsequent processing of the edges gives a series of time responses on 439 points on the beam. This sequence is then analyzed using the SPT-CWT to identify damage. The algorithm proposed was able to clearly identify damage under any condition when the structure was excited by white noise force. In addition, in the case of white noise excitation, the analysis could also reveal the position of the heat gun when it was used to heat the structure. The analysis could identify the different operating conditions i.e. between responses due to white noise excitation and responses due to pink noise excitation. During the pink noise excitation whereas damage and changing temperature were identified it was not possible to clearly identify the effect of damage from that of temperature. The methodology proposed in this article for damage detection enables the separation the damage effect from that due to temperature and excitation on data obtained from measurements of a cantilever beam. This methodology does not require information about the apriori state of the structure.

Keywords: spatiotemporal continuous wavelet transform, damage detection, data normalization, varying temperature

Procedia PDF Downloads 261

Authors: Bououden Soraya

Abstract:

This paper aims to study the existence of the change of coordinates which permits to transform a class of nonlinear dynamical systems into the so-called nonlinear observer canonical form (NOCF). Moreover, an algorithm to construct such a change of coordinates is given. Based on this form, we can design an observer with a linear error dynamic. This enables us to estimate the state of a nonlinear dynamical system. A concrete example (biological model) is provided to illustrate the feasibility of the proposed results.

Keywords: nonlinear observer canonical form, observer, design, gene regulation, gene expression

Procedia PDF Downloads 411