Search results for: polarization curve

Authors: W. Ait Ahmed, M. Aggour, M. Naciri

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Extracting energy from biomass is an important alternative to produce different types of energy (heat, electricity, or both) assuring low pollution and better efficiency. It is a new yet reliable approach to reduce green gas emission by extracting methane from industry effluents and use it to power machinery. We focused in our project on using paper and mill effluents, treated in a UASB reactor. The methane produced is used in the factory’s power supply. The aim of this work is to develop an electronic system using Arduino platform connected to a gas sensor, to measure and display the curve of daily methane production on processing. The sensor will send the gas values in ppm to the Arduino board so that the later sends the RS232 hardware protocol. The code developed with processing will transform the values into a curve and display it on the computer screen.

Keywords: biogas, Arduino, processing, code, methane, gas sensor, program

Procedia PDF Downloads 283

Authors: Chigozie Azunna

Abstract:

Various studies have been carried out in several countries to determine the relationship between inflation and unemployment. The study was carried out to review this relationship in South Africa. Secondary data was obtained from Statistics South Africa, Reserve bank, and other reliable secondary sources to review this relationship. The study incorporated yearly inflation and unemployment data in South Africa from 2000 to 2022 to explain the relationship between inflation and unemployment in South Africa. The study found the relationship to be nonlinear and lacking any significant association or relationship. Various economic schools of thought postulations were incorporated in the review as it is applied to South Africa. Essentially, the Phillips Curve was reviewed in-line with the study objective.

Keywords: inflation and unemployment in south africa, philips curve, monetarists, neo keynesian, new-classical

Procedia PDF Downloads 52

Authors: Hao Wang, Shengchun Wang, Weidong Wang

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On the influence of train vibration and environmental noise on the measurement of track wear, we proposed a method for automatic extraction of circular arc on the inner or outer side of the rail waist and achieved the high-precision registration of rail profile. Firstly, a polynomial fitting method based on truncated residual histogram was proposed to find the optimal fitting curve of the profile and reduce the influence of noise on profile curve fitting. Then, based on the curvature distribution characteristics of the fitting curve, the interval search algorithm based on dynamic window’s maximum curvature entropy was proposed to realize the automatic segmentation of small circular arc. At last, we fit two circle centers as matching reference points based on small circular arcs on both sides and realized the alignment from the measured profile to the standard designed profile. The static experimental results show that the mean and standard deviation of the method are controlled within 0.01mm with small measurement errors and high repeatability. The dynamic test also verified the repeatability of the method in the train-running environment, and the dynamic measurement deviation of rail wear is within 0.2mm with high repeatability.

Keywords: curvature entropy, profile registration, rail wear, structured light, train-running

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Authors: Yalda Zarnegarnia, Shari Messinger

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Receiver operating characteristic (ROC) curves have been widely used in medical research to illustrate the performance of the biomarker in correctly distinguishing the diseased and non-diseased groups. Correlated biomarker data arises in study designs that include subjects that contain same genetic or environmental factors. The information about correlation might help to identify family members at increased risk of disease development, and may lead to initiating treatment to slow or stop the progression to disease. Approaches appropriate to a case-control design matched by family identification, must be able to accommodate both the correlation inherent in the design in correctly estimating the biomarker’s ability to differentiate between cases and controls, as well as to handle estimation from a matched case control design. This talk will review some developed methods for ROC curve estimation in settings with correlated data from case control design and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using Conditional ROC curves will be demonstrated, to provide appropriate ROC curves for correlated paired data. The proposed approach will use the information about the correlation among biomarker values, producing conditional ROC curves that evaluate the ability of a biomarker to discriminate between diseased and non-diseased subjects in a familial paired design.

Keywords: biomarker, correlation, familial paired design, ROC curve

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Authors: Khalid Omari, Rene Chenier, Enrique Blondel, Ryan Ahola

Abstract:

Northern Canadian coasts have vulnerable and very dynamic intertidal zones with very high tides occurring in several areas. The impact of climate change presents challenges not only for maintaining this biodiversity but also for navigation safety adaptation due to the high sediment mobility in these coastal areas. Thus, frequent mapping of shorelines and intertidal changes is of high importance. To help in quantifying the changes in these fragile ecosystems, remote sensing provides practical monitoring tools at local and regional scales. Traditional methods based on high-resolution optical sensors are often used to map intertidal areas by benefiting of the spectral response contrast of intertidal classes in visible, near and mid-infrared bands. Tidal areas are highly reflective in visible bands mainly because of the presence of fine sand deposits. However, getting a cloud-free optical data that coincide with low tides in intertidal zones in northern regions is very difficult. Alternatively, the all-weather capability and daylight-independence of the microwave remote sensing using synthetic aperture radar (SAR) can offer valuable geophysical parameters with a high frequency revisit over intertidal zones. Multi-polarization SAR parameters have been used successfully in mapping intertidal zones using incoherence target decomposition. Moreover, the crustal displacements caused by ocean tide loading may reach several centimeters that can be detected and quantified across differential interferometric synthetic aperture radar (DInSAR). Soil moisture change has a significant impact on both the coherence and the backscatter. For instance, increases in the backscatter intensity associated with low coherence is an indicator for abrupt surface changes. In this research, we present primary results obtained following our investigation of the potential of the fully polarimetric Radarsat-2 data for mapping an inter-tidal zone located on Tasiujaq on the south-west shore of Ungava Bay, Quebec. Using the repeat pass cycle of Radarsat-2, multiple seasonal fine quad (FQ14W) images are acquired over the site between 2016 and 2018. Only 8 images corresponding to low tide conditions are selected and used to build an interferometric stack of data. The observed displacements along the line of sight generated using HH and VV polarization are compared with the changes noticed using the Freeman Durden polarimetric decomposition and Touzi degree of polarization extrema. Results show the consistency of both approaches in their ability to monitor the changes in intertidal zones.

Keywords: SAR, degree of polarization, DInSAR, Freeman-Durden, polarimetry, Radarsat-2

Procedia PDF Downloads 117

Authors: Iyad M. Muslih, Yehya Abdellatif

Abstract:

In general, shading will reduce the electrical power produced from PV modules and arrays in locations where shading is unavoidable or caused by dynamic moving parts. This reduction is based on the shade effect on the I-V curve of the PV module or array and how the DC/AC inverter can search and control the optimum value of power from this module or array configuration. This is a very complicated task due to different patterns of shaded PV modules and arrays. One solution presented by the inverter industry is to perform the maximum power point tracking (MPPT) at the module level rather than the series string level. This solution is supposed to reduce the shade effect on the total harvested energy. However, this isn’t necessarily the best solution to reduce the shade effect as will be shown in this study.

Keywords: photovoltaic, shade effect, I-V curve, MPPT

Procedia PDF Downloads 362

Authors: Anisul Islam

Abstract:

The U.S. has a very strong trade relationship with China but with a large and persistent trade deficit. Some has argued that the undervalued Chinese Yuan is to be blamed for the persistent trade deficit. The empirical results are mixed at best. This paper empirically estimates the U.S. export function along with the U.S. import function with its trade with China with the purpose of testing for the existence of the Marshall-Lerner (ML) condition as well for the possible existence of the J-curve hypothesis. Annual export and import data will be utilized for as long as the time series data exists. The export and import functions will be estimated using advanced econometric techniques, along with appropriate diagnostic tests performed to examine the validity and reliability of the estimated results. The annual time-series data covers from 1975 to 2022 with a sample size of 48 years, the longest period ever utilized before in any previous study. The data is collected from several sources, such as the World Bank’s World Development Indicators, IMF Financial Statistics, IMF Direction of Trade Statistics, and several other sources. The paper is expected to shed important light on the ongoing debate regarding the persistent U.S. trade deficit with China and the policies that may be useful to reduce such deficits over time. As such, the paper will be of great interest for the academics, researchers, think tanks, global organizations, and policy makers in both China and the U.S.

Keywords: exports, imports, marshall-lerner condition, j-curve hypothesis, united states, china

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Authors: Asiful Hossain Seikh, Mohammad Asif Alam, Ubair Abdus Samad, Jabair A. Mohammed, S. M. Al-Zahrani, El-Sayed M. Sherif

Abstract:

In this current investigation, aliphatic amine-cured diglycidyl ether of bisphenol-A (DGEBA) based epoxy coating was mixed with certain weight % hardener polyaminoamide (1:2) and was coated on carbon steel panels with and without 1% nano crystalline Al powder. The corrosion behavior of the coated samples were investigated by exposing them in the salt spray chamber, for 500 hours. According to ASTM-B-117, the bath was kept at 35 °C and 5% NaCl containing mist was sprayed at 1.3 bars pressure. Composition of coatings was confirmed using Fourier-transform infrared spectroscopy (FTIR). Electrochemical characterization of the coated samples was also performed using potentiodynamic polarization technique and electrochemical impedance spectroscopy (EIS) technique. All the experiments were done in 3.5% NaCl solution. The nano Al coated sample shows good corrosion resistance property compared to bare Al sample. In fact after salt spray exposure no pitting or local damage was observed for nano coated sample and the coating gloss was negligibly affected. The surface morphology of coated and corroded samples was studied using scanning electron microscopy (SEM).

Keywords: epoxy, nano aluminium, potentiodynamic polarization, salt spray, electrochemical impedence spectroscopy

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Authors: Apra Sinha

Abstract:

The inverted U-shaped Environmental Kuznets curve (EKC) demonstrates(pollution-income relationship)that initially the pollution and environmental degradation surpass the level of income per capita; however this trend reverses since at the higher income levels, economic growth initiates environmental upgrading. However, what effect does increased environmental degradation has on growth is the missing feedback link which has not been addressed in the EKC hypothesis. This paper examines the missing feedback link in EKC hypothesis in Indian context by examining the casual association between fossil fuel consumption, carbon dioxide emissions and economic growth for India. Fossil fuel consumption here has been taken as a proxy of driver of economic growth. The casual association between the aforementioned variables has been analyzed using five interventions namely 1) urban development for which urbanization has been taken proxy 2) industrial development for which industrial value added has been taken proxy 3) trade liberalization for which sum of exports and imports as a share of GDP has been taken as proxy 4)financial development for which a)domestic credit to private sector and b)net foreign assets has been taken as proxies. The choice of interventions for this study has been done keeping in view the economic liberalization perspective of India. The main aim of the paper is to investigate the missing feedback link for Environmental Kuznets Curve Hypothesis before and after incorporating the intervening variables. The period of study is from 1971 to 2011 as it covers pre and post liberalization era in India. All the data has been taken from World Bank country level indicators. The Johansen and Juselius cointegration testing methodology and Error Correction based Granger causality have been applied on all the variables. The results clearly show that out of five interventions, only in two interventions the missing feedback link is being addressed. This paper can put forward significant policy implications for environment protection and sustainable development.

Keywords: environmental Kuznets curve hypothesis, fossil fuel consumption, industrialization, trade liberalization, urbanization

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Authors: Mansi Srivastava, Uzma Saqib, Adnan Naim, Anjali Roy, Dongfang Liu, Deepak Bhatnagar, Ravinder Ravinder, Mirza S. Baig

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Macrophages polarize to proinflammatory M1 or anti-inflammatory M2 states with distinct physiological functions. This transition within the M1 to M2 phenotypes decides the nature, duration, and severity of an inflammatory response. However, inspite of a substantial understanding of the fate of these phenotypes, the underlying molecular mechanisms are not well understood. We have investigated the role of Neuronal nitric oxide synthase (NOS1) mediated regulation of Activator protein 1 (AP-1) transcription factor in macrophages as a critical effector of macrophage phenotypic change. Activator protein 1 (AP-1) is a group of dimeric transcription factors composed of jun, Fos, and ATF family proteins. We determined that NOS1-derived nitric oxide (NO) facilitate Fos and jun interaction which induces IL12 & IL23 expression. Pharmacological inhibition of NOS1 inhibits Fos and jun interaction but increases ATF2 and Fos dimerization. Switching of Fos and jun dimer to ATF2 and jun dimerization switches phenotype from IL–12high IL-23high IL-10low to IL–12low IL-23lowIL-10high phenotype, respectively. Together, these findings highlight a key role of the TLR4-NOS1-AP1 signaling axis in regulating macrophage polarization.

Keywords: inflammation, macrophage, lipopolysaccharide (LPS), proinflammatory cytokines, activator protein 1 (AP-1), neuronal nitric oxide synthase (NOS1)

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Authors: Arash Ahmadi, Amirreza Kavousizadeh, Sanaz Heidarzadeh

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Stage-discharge curve is one of the conventional methods for continuous river flow measurement. In this paper, an innovative approach is proposed for predicting the stage-discharge relationship using the application of isovel contours. Using the proposed method, it is possible to estimate the stage-discharge curve in the whole section with only using discharge information from just one arbitrary water level. For this purpose, multivariate relationships are used to determine the mean velocity in a cross-section. The unknown exponents of the proposed relationship have been obtained by using the second version of the Strength Pareto Evolutionary Algorithm (SPEA2), and the appropriate equation was selected by applying the TOPSIS (Technique for Order Preferences by Similarity to an Ideal Solution) approach. Results showed a close agreement between the estimated and observed data in the different cross-sections.

Keywords: rating curves, SPEA2, natural rivers, bed roughness distribution

Procedia PDF Downloads 127

Authors: N. Boshkova, K. Kamburova, N. Tabakova, N. Boshkov, Ts. Radeva

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Coatings based on polyaniline (PANI) can improve the resistance of steel against corrosion. In this work, the preparation of stable suspensions of colloidal PANI-SiO₂ particles, suitable for obtaining of composite anticorrosive coating on steel, is described. Electrokinetic data as a function of pH are presented, showing that the zeta potentials of the PANI-SiO₂ particles are governed primarily by the charged groups at the silica oxide surface. Electrosteric stabilization of the PANI-SiO₂ particles’ suspension against aggregation is realized at pH>5.5 (EB form of PANI) by adsorption of positively charged polyelectrolyte molecules onto negatively charged PANI-SiO₂ particles. The PANI-SiO₂ particles are incorporated by electrodeposition into the metal matrix of zinc in order to obtain composite (hybrid) coatings. The latter are aimed to ensure sacrificial protection of steel mainly in aggressive media leading to local corrosion damages. The surface morphology of the composite zinc coatings is investigated with SEM. The influence of PANI-SiO₂ particles on the cathodic and anodic processes occurring in the starting electrolyte for obtaining of the coatings is followed with cyclic voltammetry. The electrochemical and corrosion behavior is evaluated with potentiodynamic polarization curves and polarization resistance measurements. The beneficial effect of the stabilized PANI-SiO₂ particles for the increased protective ability of the composites is commented and discussed.

Keywords: corrosion, polyaniline-silica particles, zinc, protective ability

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Authors: Nakarin Prempri

Abstract:

Single-phase induction motors are widely used in industry. Most manufacturing processes use capacitor-run single-phase induction motors to drive mechanical loads. The selection of a suitable motor for driving is important. The optimum operating range of the motor can help the motor operate efficiently. Thus, this paper presents an operating range analysis of capacitor-run single-phase induction motors and a determination of suitability between motor and mechanical loads. an observational study found that the optimum operating range of the motor can be used to determine the suitability between the motor and the mechanical load. Such considerations ensure that the motor uses no more current than necessary and operates efficiently.

Keywords: single phase induction motor, operating range, torque curve, efficiency curve

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Authors: G. Shiha, S. Seif, W. Samir, K. Zalata

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Prospective Validation of the FibroTest Score in assessing Liver Fibrosis in Hepatitis C Infection with Genotype 4 FibroTest (FT) is non-invasive score of liver fibrosis that combines the quantitative results of 5 serum biochemical markers (alpha-2-macroglobulin, haptoglobin, apolipoprotein A1, gamma glutamyl transpeptidase (GGT) and bilirubin) and adjusted with the patient's age and sex in a patented algorithm to generate a measure of fibrosis. FT has been validated in patients with chronic hepatitis C (CHC) (Halfon et al., Gastroenterol. Clin Biol.( 2008), 32 6suppl 1, 22-39). The validation of fibro test ( FT) in genotype IV is not well studied. Our aim was to evaluate the performance of FibroTest in an independent prospective cohort of hepatitis C patients with genotype 4. Subject was 122 patients with CHC. All liver biopsies were scored using METAVIR system. Our fibrosis score(FT) were measured, and the performance of the cut-off score were done using ROC curve. Among patients with advanced fibrosis, the FT was identically matched with the liver biopsy in 18.6%, overestimated the stage of fibrosis in 44.2% and underestimated the stage of fibrosis in 37.7% of cases. Also in patients with no/mild fibrosis, identical matching was detected in 39.2% of cases with overestimation in 48.1% and underestimation in 12.7%. So, the overall results of the test were identical matching, overestimation and underestimation in 32%, 46.7% and 21.3% respectively. Using ROC curve it was found that (FT) at the cut-off point of 0.555 could discriminate early from advanced stages of fibrosis with an area under ROC curve (AUC) of 0.72, sensitivity of 65%, specificity of 69%, PPV of 68%, NPV of 66% and accuracy of 67%. As FibroTest Score overestimates the stage of advanced fibrosis, it should not be considered as a reliable surrogate for liver biopsy in hepatitis C infection with genotype 4.

Keywords: fibrotest, chronic Hepatitis C, genotype 4, liver biopsy

Procedia PDF Downloads 386

Authors: A. A. Vasin, N. V. Klassen, A. M. Likhter

Abstract:

Water suspensions of in-organic (metals and oxides) and organic nano-objects (chitozan and collagen) were subjected to the treatment of direct and alternative electrical fields. In addition to quasi-periodical spatial patterning resonance-like performance of spatial distributions of these suspensions has been found at low frequencies of alternating electrical field. These resonances are explained as the result of creation of equilibrium states of groups of charged nano-objects with opposite signs of charges at the interparticle distances where the forces of Coulomb attraction are compensated by the repulsion forces induced by relatively negative polarization of hydrated regions surrounding the nanoparticles with respect to pure water. The low frequencies of these resonances are explained by comparatively big distances between the particles and their big masses with t\respect to masses of atoms constituting molecules with high resonance frequencies. These new resonances open a new approach to detailed modeling and understanding of mechanisms of the influence of electrical fields on the functioning of internal organs of living organisms at the level of cells and neurons.

Keywords: bio-polymers, chitosan, collagen, nanoparticles, coulomb attraction, polarization repulsion, periodical patterning, electrical low frequency resonances, transformations

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Authors: Giorgio Visentin, Alexei A. Buchachenko

Abstract:

Recent proposals to use Yb dimer as an optical clock and as a sensor for non-Newtonian gravity imply the knowledge of its interaction potential. Here, the ground-state Born-Oppenheimer Yb₂ potential energy curve is represented by a semi-analytical function, consisting of short- and long-range contributions. For the former, the systematic ab initio all-electron exact 2-component scalar-relativistic CCSD(T) calculations are carried out. Special care is taken to saturate diffuse basis set component with the atom- and bond-centered primitives and reach the complete basis set limit through n = D, T, Q sequence of the correlation-consistent polarized n-zeta basis sets. Similar approaches are used to the long-range dipole and quadrupole dispersion terms by implementing the CCSD(3) polarization propagator method for dynamic polarizabilities. Dispersion coefficients are then computed through Casimir-Polder integration. The semiclassical constraint on the number of the bound vibrational levels known for the ¹⁷⁴Yb isotope is used to scale the potential function. The scaling, based on the most accurate ab initio results, bounds the interaction energy of two Yb atoms within the narrow 734 ± 4 cm⁻¹ range, in reasonable agreement with the previous ab initio-based estimations. The resulting potentials can be used as the reference for more sophisticated models that go beyond the Born-Oppenheimer approximation and provide the means of their uncertainty estimations. The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: ab initio coupled cluster methods, interaction potential, semi-analytical function, ytterbium dimer

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Authors: Fatimah Al-Hayazi, Ehteram. A. Noor, Aisha H. Moubaraki

Abstract:

The inhibitive effect of Securigera securidaca seed extract (SSE) on mild steel corrosion in 1 M HCl solution has been studied by weight loss and electrochemical techniques at four different temperatures. All techniques studied provided data that the studied extract does well at all temperatures, and its inhibitory action increases with increasing its concentration. SEM images indicate thin-film formation on mild steel when corroded in solutions containing 1 g L-1 of inhibitor either at low or high temperatures. The polarization studies showed that SSE acts as an anodic inhibitor. Both polarization and impedance techniques show an acceleration behaviour for SSE at concentrations ≤ 0.1 g L-1 at all temperatures. At concentrations ≥ 0.1 g L-1, the efficiency of SSE is dramatically increased with increasing concentration, and its value does not change appreciably with increasing temperature. It was found that all adsorption data obeyed Temkin adsorption isotherm. Kinetic activation and thermodynamic adsorption parameters are evaluated and discussed. The results revealed an endothermic corrosion process with an associative activation mechanism, while a comprehensive adsorption mechanism for SSE on mild steel surfaces is suggested, in which both physical and chemical adsorption are involved in the adsorption process. A good correlation between inhibitor constituents and their inhibitory action was obtained.

Keywords: corrosion, inhibition of steel, hydrochloric acid, thermodynamic study

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Amr Mohamadien, Ali Imanpour, Sylvester Agbo, Nader Yoosef-Ghodsi, Samer Adeeb

Abstract:

The fracture toughness resistance curve (e.g., J-R curve and crack tip opening displacement (CTOD) or δ-R curve) is important in facilitating strain-based design and integrity assessment of oil and gas pipelines. This paper aims to present laboratory experimental data to characterize the fracture behavior of pipeline steel. The influential parameters associated with the fracture of API 5L X52 pipeline steel, including different initial crack sizes, were experimentally investigated for a single notch edge bend (SENB). A total of 9 small-scale specimens with different crack length to specimen depth ratios were conducted and tested using single edge notch bending (SENB). ASTM E1820 and BS7448 provide testing procedures to construct the fracture resistance curve (Load-CTOD, CTOD-R, or J-R) from test results. However, these procedures are limited by standard specimens’ dimensions, displacement gauges, and calibration curves. To overcome these limitations, this paper presents the use of small-scale specimens and a 3D-digital image correlation (DIC) system to extract the parameters required for fracture toughness estimation. Fracture resistance curve parameters in terms of crack mouth open displacement (CMOD), crack tip opening displacement (CTOD), and crack growth length (∆a) were carried out from test results by utilizing the DIC system, and an improved regression fitting resistance function (CTOD Vs. crack growth), or (J-integral Vs. crack growth) that is dependent on a variety of initial crack sizes was constructed and presented. The obtained results were compared to the available results of the classical physical measurement techniques, and acceptable matchings were observed. Moreover, a case study was implemented to estimate the maximum strain value that initiates the stable crack growth. This might be of interest to developing more accurate strain-based damage models. The results of laboratory testing in this study offer a valuable database to develop and validate damage models that are able to predict crack propagation of pipeline steel, accounting for the influential parameters associated with fracture toughness.

Keywords: fracture toughness, crack propagation in pipeline steels, CTOD-R, strain-based damage model

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: S. Y. Park, S. M. Lee, S. H. Lee, K. M. Lim

Abstract:

In this research analyzed the effects that phase formation reaction change in the grey cast iron makes on characteristics of microstructures, liquidity, and mechanical properties through cooling curve when adding rare earth elements (R.E). This research was analyzed with comparison between the case of not adding the rare earth elements (R.E) into the grey cast iron with the standard composition (as 3.3%C-2.1%Si-0.7%Mn-0.1%S) and the case of adding 0.3% rare earth elements (R.E). The thermal analysis parameters have been drawn through eutectic temperature theoretically calculated, recalescence temperature, and undercooling temperature measured from start of eutectic reaction to end of solidification in the cooling curve obtained by thermal analysis to analyze formation behavior of graphite, and the effects by addition of rare earth elements on this have been reviewed. When adding rare earth elements (R.E), the cause of liquidity slowdown was analyzed trough the solidification starting temperature and change of solidification ending temperature. The strength and hardness have been measured to evaluate the mechanical properties, and the sound tensile strength has been evaluated through quality coefficient after measuring relative hardness and normality degree of tensile strength by calculating theoretical tensile strength and theoretical hardness. The change of Pearlite Inter-lamellar Spacing of matrix microstructure and eutectic cell count of macrostructure was measured to analyze the effects of the rare earth elements on the sound tensile strength. The change of eutectic cell count has been clarified through activation of the eutectic reaction, and the cause of pearlite inter-lamellar spacing clarified through eutectoid reaction temperature.

Keywords: cooling curve, element, grey cast iron, thermal analysis, rare earth element

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Authors: Liping Wu, Durga Bhakta Pokharel, Junhua Dong, Changgang Wang, Lin Zhao, Wei Ke, Nan Chen

Abstract:

Hazenite conversion coating was deposited on AZ31 Mg alloy in a deaerated phosphate solution containing 0.1 M K₂HPO₄ and 0.1 M Na₂HPO₄ (Na₀.₁K0₀.₁) with pH 9 at −0.8 V. The coating mechanism of hazenite was elucidated by in situ potentiostatic current decay, scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FT-IR), electron probe micro-analyzer (EPMA) and differential scanning calorimetry (DSC). The volume of H₂ evolved during potentiostatic polarization was measured by a gas collection apparatus. The degradation resistance of the hazenite coating was evaluated in simulated body fluid (SBF) at 37℃ by using potentiodynamic polarization (PDP). The results showed that amorphous Mg(OH)₂ was deposited first, followed by the transformation of Mg(OH)₂ to amorphous MgHPO₄, subsequently the conversion of MgHPO₄ to crystallized K-struvite (KMgPO₄·6H₂O), finally the crystallization of crystallized hazenite (NaKMg₂(PO₄)₂·14H₂O). The deposited coating was composed of four layers where the inner layer is comprised of Mg(OH)₂, the middle layer of Mg(OH)₂ and MgHPO₄, the top layer of Mg(OH)₂, MgHPO₄ and K-struvite, the topmost layer of Mg(OH)₂, MgHPO₄, K-struvite and hazenite (NaKMg₂(PO₄)₂·14H₂O). The PD results showed that the hazenite coating decreased the corrosion rate by two orders of magnitude.

Keywords: magnesium alloy, potentiostatic technique, hazenite, mineral conversion coating

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Authors: Ines Elouedi, Atef Hammouda

Abstract:

This paper presents a new fast version of the generalized Multi-Directional Radon Transform method. The new method uses the inverse Fast Fourier Transform to lead to a faster Generalized Radon projections. We prove in this paper that the fast algorithm leads to almost the same results of the eldest one but with a considerable lower time computation cost. The projection end result of the fast method is a parameterized Radon space where a high valued pixel allows the detection of a curve from the original image. The proposed fast inversion algorithm leads to an exact reconstruction of the initial image from the Radon space. We show examples of the impact of this algorithm on the pattern recognition domain.

Keywords: fast generalized multi-directional Radon transform, curve, exact reconstruction, pattern recognition

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Authors: H. Ben Khlifa, W. Cheikhrouhou-Koubaa, A. Cheikhrouhou

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The orthorhombic Pr₀.₈Na₀.₂−ₓKₓMnO₃ (x = 0.10 and 0.15) manganites are prepared by using the solid-state reaction at high temperatures. The critical exponents (β, γ, δ) are investigated through various techniques such as modified Arrott plot, Kouvel-Fisher method, and critical isotherm analysis based on the data of the magnetic measurements recorded around the Curie temperature. The critical exponents are derived from the magnetization data using the Kouvel-Fisher method, are found to be β = 0.32(4) and γ = 1.29(2) at TC ~ 123 K for x = 0.10 and β = 0.31(1) and γ = 1.25(2) at TC ~ 133 K for x = 0.15. The critical exponent values obtained for both samples are comparable to the values predicted by the 3D-Ising model and have also been verified by the scaling equation of state. Such results demonstrate the existence of ferromagnetic short-range order in our materials. The magnetic entropy changes of polycrystalline samples with a second-order phase transition are investigated. A large magnetic entropy change deduced from isothermal magnetization curves, is observed in our samples with a peak centered on their respective Curie temperatures (TC). The field dependence of the magnetic entropy changes are analyzed, which shows power-law dependence ΔSmax ≈ a(μ0 H)n at the transition temperature. The values of n obey the Curie Weiss law above the transition temperature. It is shown that for the investigated materials, the magnetic entropy change follows a master curve behavior. The rescaled magnetic entropy change curves for different applied fields collapse onto a single curve for both samples.

Keywords: manganites, critical exponents, magnetization, magnetocaloric, master curve

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Authors: Guilherme Ribeiro, Alexandre Oliveira, Antonio Ferreira, Shyam Visweswaran, Gregory Cooper

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Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions.

Keywords: approach instance-based, area under the ROC curve, patient-specific decision path, clinical predictions

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Authors: Sugandha Gupta, Arun Kumar Jha

Abstract:

A large number of ferroelectric materials have been intensely investigated for applications in non-volatile ferroelectric random access memories (FeRAMs), piezoelectric transducers, actuators, pyroelectric sensors, high dielectric constant capacitors, etc. Bismuth layered ferroelectric materials such as Strontium Bismuth Tantalate (SBT) has attracted a lot of attention due to low leakage current, high remnant polarization and high fatigue endurance up to 1012 switching cycles. However, pure SBT suffers from various major limitations such as high dielectric loss, low remnant polarization values, high processing temperature, bismuth volatilization, etc. Significant efforts have been made to improve the dielectric and ferroelectric properties of this compound. Firstly, it has been reported that electrical properties vary with the Sr/ Bi content ratio in the SrBi2Ta2O9 compsition i.e. non-stoichiometric compositions with Sr-deficient / Bi excess content have higher remnant polarization values than stoichiometic SBT compositions. With the objective to improve structural, dielectric, ferroelectric and piezoelectric properties of SBT compound, rare earth holmium (Ho3+) was chosen as a donor cation for substitution onto the Bi2O2 layer. Moreover, hardly any report on holmium substitution in stoichiometric SrBi2Ta2O9 and non-stoichiometric Sr0.8Bi2.2Ta2O9 compositions were available in the literature. The holmium substituted SrBi2-xHoxTa2O9 (x= 0.00-2.0) and Sr0.8Bi2.2Ta2O9 (x=0.0 and 0.01) compositions were synthesized by the solid state reaction method. The synthesized specimens were characterized for their structural and electrical properties. X-ray diffractograms reveal single phase layered perovskite structure formation for holmium content in stoichiometric SBT samples up to x ≤ 0.1. The granular morphology of the samples was investigated using scanning electron microscope (Hitachi, S-3700 N). The dielectric measurements were carried out using a precision LCR meter (Agilent 4284A) operating at oscillation amplitude of 1V. The variation of dielectric constant with temperature shows that the Curie temperature (Tc) decreases on increasing the holmium content. The specimen with x=2.0 i.e. the bismuth free specimen, has very low dielectric constant and does not show any appreciable variation with temperature. The dielectric loss reduces significantly with holmium substitution. The polarization–electric field (P–E) hysteresis loops were recorded using a P–E loop tracer based on Sawyer–Tower circuit. It is observed that the ferroelectric property improve with Ho substitution. Holmium substituted specimen exhibits enhanced value of remnant polarization (Pr= 9.22 μC/cm²) as compared to holmium free specimen (Pr= 2.55 μC/cm²). Piezoelectric co-efficient (d33 values) was measured using a piezo meter system (Piezo Test PM300). It is observed that holmium substitution enhances piezoelectric coefficient. Further, the optimized holmium content (x=0.01) in stoichiometric SrBi2-xHoxTa2O9 composition has been substituted in non-stoichiometric Sr0.8Bi2.2Ta2O9 composition to obtain further enhanced structural and electrical characteristics. It is expected that a new class of ferroelectric materials i.e. Rare Earth Layered Structured Ferroelectrics (RLSF) derived from Bismuth Layered Structured Ferroelectrics (BLSF) will generate which can be used to replace static (SRAM) and dynamic (DRAM) random access memories with ferroelectric random access memories (FeRAMS).

Keywords: dielectrics, ferroelectrics, piezoelectrics, strontium bismuth tantalate

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Authors: Kenechi Kurtis Onochie

Abstract:

This paper shows the use of filter paper technique in the measurement of matric suction of unsaturated expansive soil around the Haspolat region of Lefkosa, North Cyprus in other to establish the soil water characteristics curve (SWCC) or soil water retention curve (SWRC). The dry filter paper approach which is standardized by ASTM, 2003, D 5298-03 in which the filter paper is initially dry was adopted. The whatman No. 42 filter paper was used in the matric suction measurement. The maximum dry density of the soil was obtained as 2.66kg/cm³ and the optimum moisture content as 21%. The soil was discovered to have high air entry value of 1847.46KPa indicating finer particles and 25% hydraulic capacity using filter paper technique. The filter paper technique proved to be very useful for measuring the hydraulic capacity of unsaturated expansive soil.

Keywords: SWCC, matric suction, filter paper, expansive soil

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Authors: Mehdi Fuladipanah, Mehdi Jorabloo

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Water flow management is one of the most important parts of river engineering. Non-uniformity distribution of rainfall and various flow demand with unreasonable flow management will be caused destroyed of the river ecosystem. Then, it is severe to determine ecosystem flow requirement. In this paper, Flow duration curve indices method which has hydrological based was used to evaluate environmental flow in Gharasou River, Ardabil, Iran. Using flow duration curve, Q90 and Q95 for different return periods were calculated. Their magnitude was determined as 1-day, 3-day, 7-day, and 30 days. According to the second method, hydraulic alteration indices often had low and medium range. To maintain river at an acceptable ecological condition, minimum daily discharge of index Q95 is 0.7 m^3.s^-1.

Keywords: Gharasou River, water flow management, non-uniformity distribution, ecosystem flow requirement, hydraulic alteration

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Authors: Vijaya Dixit Aasheesh Dixit

Abstract:

Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

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Authors: A. Bendarma, T. Jankowiak, A. Rusinek, T. Lodygowski, M. Klósak, S. Bouslikhane

Abstract:

The analysis of the mechanical characteristics and dynamic behavior of aluminum alloy sheet due to perforation tests based on the experimental tests coupled with the numerical simulation is presented. The impact problems (penetration and perforation) of the metallic plates have been of interest for a long time. Experimental, analytical as well as numerical studies have been carried out to analyze in details the perforation process. Based on these approaches, the ballistic properties of the material have been studied. The initial and residual velocities laser sensor is used during experiments to obtain the ballistic curve and the ballistic limit. The energy balance is also reported together with the energy absorbed by the aluminum including the ballistic curve and ballistic limit. The high speed camera helps to estimate the failure time and to calculate the impact force. A wide range of initial impact velocities from 40 up to 180 m/s has been covered during the tests. The mass of the conical nose shaped projectile is 28 g, its diameter is 12 mm, and the thickness of the aluminum sheet is equal to 1.0 mm. The ABAQUS/Explicit finite element code has been used to simulate the perforation processes. The comparison of the ballistic curve was obtained numerically and was verified experimentally, and the failure patterns are presented using the optimal mesh densities which provide the stability of the results. A good agreement of the numerical and experimental results is observed.

Keywords: aluminum alloy, ballistic behavior, failure criterion, numerical simulation

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