Search results for: passivation layer

Authors: Chaitanya Kanakamedala, Hansa Pradhan, Carter Gilbert

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Social media platforms, such as Twitter, are excellent datasets for understanding human interactions and sentiments. This report explores social dynamics among US Congressional members through a network analysis applied to a dataset of tweets spanning 2008 to 2017 from the ’US Congressional Tweets Dataset’. In this report, we preform network analysis where connections between users (edges) are established based on a similarity threshold: two tweets are connected if the tweets they post are similar. By utilizing the Natural Language Toolkit (NLTK) and NetworkX, we quantified tweet similarity and constructed a graph comprising various interconnected components. Each component represents a cluster of users with closely aligned content. We then preform sentiment analysis on each cluster to explore the prevalent emotions and opinions within these groups. Our findings reveal that despite the initial expectation of distinct ideological divisions typically aligning with party lines, the analysis exposed a high degree of topical convergence across tweets from different political affiliations. The analysis preformed in this report not only highlights the potential of social media as a tool for political communication but also suggests a complex layer of interaction that transcends traditional partisan boundaries, reflecting a complicated landscape of politics in the digital age.

Keywords: natural language processing, sentiment analysis, centrality analysis, topic modeling

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: Hubert Beisch, Janik Marx, Svenja Garlof, Roman Shvets, Ivan Grygorchak, Andriy Kityk, Bodo Fiedler

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Three-dimensional carbon materials can be used as electrode materials for energy storage systems such as batteries and supercapacitors. Fast charging and discharging times are realizable without reducing the performance due to aging processes. Furthermore high specific surface area (SSA) of three-dimensional carbon structures leads to high specific capacities. One newly developed carbon foam is Globugraphite. This interconnected globular carbon morphology with statistically distributed hierarchical pores is manufactured by a chemical vapor deposition (CVD) process from ceramic templates resulting from a sintering process. Via scanning electron (SEM) and transmission electron microscopy (TEM), the morphology is characterized. Moreover, the SSA was measured by the Brunauer–Emmett–Teller (BET) theory. Measurements of Globugraphite in an organic and inorganic electrolyte show high energy densities and power densities resulting from ion absorption by forming an electrochemical double layer. A comparison of the specific values is summarized in a Ragone diagram. Energy densities up to 48 Wh/kg and power densities to 833 W/kg could be achieved for an SSA from 376 m²/g to 859 m²/g. For organic electrolyte, a specific capacity of 100 F/g at a density of 20 mg/cm³ was achieved.

Keywords: BET, carbon foam, CVD process, electrochemical cell, Ragone diagram, SEM, TEM

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Authors: Indri Mahadiraka Rumamby, R. R. Dwinanti Rika Marthanty, Jessica Sjah

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Smoothed particle hydrodynamics (SPH) was originally created to simulate nonaxisymmetric phenomena in astrophysics. However, this method still has several shortcomings, namely the high computational cost required to model values with high resolution and problems with boundary conditions. The difficulty of modeling boundary conditions occurs because the SPH method is influenced by particle deficiency due to the integral of the kernel function being truncated by boundary conditions. This research aims to answer if SPH modeling with a focus on boundary layer interactions and continuous flow can produce quantifiably accurate values with low computational cost. This research will combine algorithms and coding in the main program of meandering river, continuous flow algorithm, and solid-fluid algorithm with the aim of obtaining quantitatively accurate results on solid-fluid interactions with the continuous flow on a meandering channel using the SPH method. This study uses the Fortran programming language for modeling the SPH (Smoothed Particle Hydrodynamics) numerical method; the model is conducted in the form of a U-shaped meandering open channel in 3D, where the channel walls are soil particles and uses a continuous flow with a limited number of particles.

Keywords: smoothed particle hydrodynamics, computational fluid dynamics, numerical simulation, fluid mechanics

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Authors: Aminu Yakubu Umar

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X-ray is the major contributor to the effective dose of both the patient and the personnel. Because of the radiological risks involved, it is usually recommended that dose to patient from X-ray be kept as low as reasonably achievable (ALARA) with adequate image quality. The implementation of quality assurance in diagnostic radiology can help greatly in achieving that, as it is a technique designed to reduce X-ray doses to patients undergoing radiological examination. In this study, quality control was carried out in six hospitals, which involved KVp test, evaluation of total filtration, test for constancy of radiation output, and check for mA linearity. Equipment used include KVp meter, Rad-check meter, aluminum sheets (0.1–1.0 mm) etc. The results of this study indicate that, the age of the X-ray machines in the hospitals ranges from 3-13 years, GHI and GH2 being the oldest and FMC being the newest. In the evaluation of total filtration, the HVL of the X-ray machines in the hospitals varied, ranging from 2.3-5.2 mm. The HVL was found to be highest in AHC (5.2 mm), while it was lowest in GH3 (2.3 mm). All HVL measurements were done at 80 KVp. The variation in voltage accuracy in the hospitals ranges from 0.3%-127.5%. It was only in GH1 that the % variation was below the allowed limit. The test for constancy of radiation output showed that, the coefficient of variation ranges from 0.005–0.550. In GH3, FMC and AHC, the coefficient of linearity were less than the allowed limit, while in GH1, GH2 and GH4 the coefficient of linearity had exceeded the allowed limit. As regard to mA linearity, FMC and AHC had their coefficients of linearity as 0.12 and 0.10 respectively, which were within the accepted limit, while GH1, GH3 and GH4 had their coefficients as 0.16, 0.69 and 0.98 respectively, which exceeded the allowed limit.

Keywords: radiation, X-ray output, quality control, half-value layer, mA linearity, KVp variation

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Authors: Lebea Nthunya, Arne Verliefde, Bhekie Mamba, Sabelo Mhlanga

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A study aimed at developing membrane distillation (MD) processes that can be used for brackish/saline water purification will be presented. MD is a membrane-based technology that presents a possibility to counteract challenges associated with pressure driven membranes at high separation efficiencies. Membrane distillation membranes (MDM) are affected by wettability and fouling. Wetting inside the pores of the membrane is elevated by the hydrophilic characteristic of the membrane, while fouling is mostly induced by the hydrophobic-hydrophobic interaction of pollutants and the surface of the hydrophobic membranes, hence block the pores of the membranes. These properties are not desirable. As such, a carefully designed polyvinylidene fluoride (PVDF) MDM composed of a super-hydrophobic modified backbone and a super-hydrophilic thin layer has been developed to concurrently overcome these challenges. The membranes were characterized using contact angle measurements to confirm their hydrophobicity/hydrophilicity. SEM and SAXS were used to study the morphology and pore distribution on the surface of the membrane. The contact angles of the active surface ≤ 30º and that of the backbone ≥ 140º has thus revealed that the active surface was highly hydrophilic while the backbone was highly hydrophobic. The SEM and the SAXS results have also confirmed that the membranes are highly porous. These materials demonstrated a potential to remove salts from water at high efficiencies.

Keywords: membrane distillation, modification, energy efficiency, desalination

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Authors: Yunpeng Xia, Jiajia Zha, Haoxin Huang, Hau Ping Chan, Chaoliang Tan

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Although the crystal phase of two-dimensional (2D) transition metal dichalcogenides (TMDs) has been proven to play an essential role in fabricating high-performance electronic devices in the past decade, its effect on the performance of 2D material-based flash memory devices still remains unclear. Here, we report the exploration of the effect of MoTe₂ in different phases as the charge trapping layer on the performance of 2D van der Waals (vdW) heterostructure-based flash memory devices, where the metallic 1T′-MoTe₂ or semiconducting 2H-MoTe₂ nanoflake is used as the floating gate. By conducting comprehensive measurements on the two kinds of vdW heterostructure-based devices, the memory device based on MoS2/h-BN/1T′-MoTe₂ presents much better performance, including a larger memory window, faster switching speed (100 ns) and higher extinction ratio (107), than that of the device based on MoS₂/h-BN/2H-MoTe₂ heterostructure. Moreover, the device based on MoS₂/h-BN/1T′-MoTe₂ heterostructure also shows a long cycle (>1200 cycles) and retention (>3000 s) stability. Our study clearly demonstrates that the crystal phase of 2D TMDs has a significant impact on the performance of nonvolatile flash memory devices based on 2D vdW heterostructures, which paves the way for the fabrication of future high-performance memory devices based on 2D materials.

Keywords: crystal Phase, 2D van der Waals heretostructure, flash memory device, floating gate

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Authors: Amir Hossein Haji, Nabeel Al-Rawahi, Gholamreza Vakili-Nezhaad

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An innovative design has been examined for a gas-oil separator based on pressure reduction over an airfoil surface. The primary motivations are to shorten the release trajectory of the bubbles by minimizing the thickness of the oil layer as well as improving uniform pressure reduction zones. Restricted airflow over an airfoil is investigated for its effect on the pressure drop enhancement and the maximum attainable attack angle prior to the stall condition. Aerodynamic separation is delayed based on numerical simulation of Wortmann FX 63137 Airfoil in a confined domain using FLUENT 6.3.26. The proposed set up results in higher pressure drop compared with the free stream case. With the aim of optimum power consumption we have pursued further restriction to an air jet case over the airfoil. Then, a curved strip model is suggested for the air jet which can be applied as an analysis/design tool for the best performance conditions. Pressure reduction is shown to be inversely proportional to the curvature of the upper airfoil profile. This reduction occurs within the tracking zones where the air jet is effectively attached to the airfoil surface. The zero slope condition is suggested to estimate the onset of these zones after which the minimum curvature should be searched. The corresponding zero slope curvature is applied for estimation of the maximum pressure drop which shows satisfactory agreement with the simulation results.

Keywords: airfoil, air jet, curved fluid flow, gas-oil separator

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Authors: Siddharth Sarma, Ayush Majumdar, Nidhi Sabu, Mufaddal Jiruwaala, Shilpa Paygude

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Digital Elevation Models (DEMs) are digital representations of the Earth’s topography, which include information about the elevation, slope, aspect, and other terrain attributes. DEMs play a crucial role in various applications, including terrain analysis, urban planning, and environmental modeling. In this paper, TerraEnhance is proposed, a distinct approach for high-resolution DEM generation using Generative Adversarial Networks (GANs) combined with Real-ESRGANs. By learning from a dataset of low-resolution DEMs, the GANs are trained to upscale the data by 10 times, resulting in significantly enhanced DEMs with improved resolution and finer details. The integration of Real-ESRGANs further enhances visual quality, leading to more accurate representations of the terrain. A post-processing layer is introduced, employing high-pass filtering to refine the generated DEMs, preserving important details while reducing noise and artifacts. The results demonstrate that TerraEnhance outperforms existing methods, producing high-fidelity DEMs with intricate terrain features and exceptional accuracy. These advancements make TerraEnhance suitable for various applications, such as terrain analysis and precise environmental modeling.

Keywords: DEM, ESRGAN, image upscaling, super resolution, computer vision

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Authors: Kamal Bahrin Jaafar

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The study area is located at Bukit Kukus, Penang where the construction of twin road project in ongoing. A landslide event has occurred on 19th October 2018, which causes fatal deaths. The purpose of this study is to figure out the causes of failure, the estimated volume of failure, and its balance. The study comprises of unmanned aerial vehicle (UAV) sensing and resistivity survey. The resistivity method includes spreading three lines of 200m length resistivity survey with the depth of penetration in the subsurface not exceeding 35m. The result of UAV shows the current view of the site condition. Based on resistivity result, the dominant layer in the study area consists of residual soil/filling material with a thickness of more than 35m. Three selected cross sections from construction drawing are overlain with the current cross sections to understand more on the condition of the subsurface profile. By comparison, there is a difference between past and present topography. The combination of result from the previous data and current condition shows the calculated volume of failure is 85,000 m³, and its balance is 50,000 m³. In conclusion, the failure occurs since the contractor has conducted the construction works without following the construction drawing supplied by the consultant. Besides, the cause of failure is triggered by the geology condition, such as a fault that should be considered prior to the commencement of work.

Keywords: UAV, landslide, resistivity survey, cause of failure

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Authors: Milad Alizadeh Galdiani, Navid Sabet, Mohamad Ali Mohit, Fatemeh Palizdar

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Railway as one of the most important transportation modes, passes through ‎various areas with different conditions ‎inevitably, and in many countries such as ‎China, United States, Australia, and Iran, it passes through sandy ‎desert areas. One ‎of the main problems in these areas is the movement of sand, causing various ‎damages ‎to ballasted railway track such as corrosion in the railway fastening system. ‎The soil composition of some desert areas like Fahraj in Iran consists of sand ‎and ‎salt. Due to the movement of sand and corrosive ions of salt, the fastening system ‎of the railway is ‎corroded, which, in turn, reduces the thickness of the components ‎and their life span.‎ In this research, the Nano-coating for fastening system of ‎the railway is ‎introduced, and its performance has been investigated in both ‎laboratory and field tests. The Nano-coating of ‎the fastening system consists of zinc-rich, epoxy, polyurethane, and additive, which is produced through ‎Nano ‎technology. This layer covers the surface of the fastening system and ‎prohibits the chemical reactions, which result in ‎corrosion. The results of ‎Electrochemical Impedance Spectroscopy (EIS) ‎indicate that corrosion resistance ‎increases 315 times by using nano-coating, salt spray test results demonstrate that ‎nano-coated components remained intact after 1000 hours.‎

Keywords: ballasted railway, Nano-coating, railway fastening system, sandy desert

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Authors: Bao Liu, Maarten Vanierschot, Frank Buysschaert

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The present work examines the wake dynamics of a rim-driven thruster (RDT) with Computational Fluid Dynamics (CFD). Unsteady Reynolds-averaged Navier-Stokes (URANS) equations were solved in the commercial solver ANSYS Fluent in combination with the SST k-ω turbulence model. The application of the moving reference frame (MRF) and sliding mesh (SM) approach to handling the rotational movement of the propeller were compared in the transient simulations. Validation and verification of the numerical model was performed to ensure numerical accuracy. Two representative scenarios were considered, i.e., the bollard condition (J=0) and a very light loading condition(J=0.7), respectively. From the results, it’s confirmed that compared to the SM method, the MRF method is not suitable for resolving the unsteady flow features as it only gives the general mean flow but smooths out lots of characteristic details in the flow field. By evaluating the simulation results with the SM technique, the instantaneous wake flow field under both conditions is presented and analyzed, most notably the helical vortex structure. It’s observed from the results that the tip vortices, blade shed vortices, and hub vortices are present in the wake flow field and convect downstream in a highly non-linear way. The shear layer vortices shedding from the duct displayed a strong interaction with the distorted tip vortices in an irregularmanner.

Keywords: computational fluid dynamics, rim-driven thruster, sliding mesh, wake dynamics

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Authors: Wu Wei-Ting, Liu Po-Yen, Chang Chin-Tzu, Cheng Wei-Chun

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Three types of low-temperature phase transformations in an Fe-12.5 Mn-6.53 Al-1.28 C (wt %) alloy have been studied. The steel underwent solution heat treatment at 1100℃ and isothermal holding at low temperatures. γ’ phase appears in the austenite matrix in the air-cooled steel. Coherent ultra-fine particles of γ’ phase precipitated uniformly in the austenite matrix after the air-cooling process. These ultra-fine particles were very small and only could be detected by TEM through dark-field images. After short periods of isothermal holding at low temperatures these particles of γ’ phase grew and could be easily detected by TEM. A pro-eutectoid reaction happened after isothermal holding at temperatures below 875 ℃. Proeutectoid κ-carbide and ferrite appear in the austenite matrix as grain boundary precipitates and cellular precipitates. The cellular precipitates are composed of lamellar κ-carbide and austenite. The lamellar κ-carbide grains are always accompanied by layers of austenite twins. The presence of twin layers adhering to the κ-carbide plates might be attributed to the lower activation energy for the precipitation of κ-carbide plates in the austenite. The final form of phase transformation is the eutectoid reaction for the decomposition of supersaturated austenite into stable κ-carbide and ferrite phases at temperatures below 700℃. The ferrite and κ-carbide are in the form of pearlite lamellae.

Keywords: austenite, austenite twin layers, κ-carbide, twins

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Authors: Soumitri Bag Majumder, Anindita Chaudhuri

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This exploratory study delves into the perception of job dignity among delivery agents in Kolkata, focusing on both food and grocery delivery sectors. The rapid expansion of online delivery platforms in India has led to a significant rise in the delivery service industry. Despite its growth, there is a dearth of research addressing the multifaceted challenges faced by delivery agents. This study aims to bridge this gap by shedding light on their experiences. The study’s objectives include exploring the lived experiences of delivery agents, their work-life balance, and their perception of job dignity. Using a qualitative research approach, the study will conduct semi-structured in-depth interviews with a purposive sample of 10 participants from each sector, consisting of individuals with lower socio-economic backgrounds aged between 18 and 35 years. The Three-Layer Coding framework proposed by Charmaz will guide the data analysis process, encompassing open coding, axial coding, and selective coding. Through this method, the study seeks to uncover emergent themes and patterns that illuminate the participants’ perspectives on job dignity, recognition, and the challenges they encounter. By uncovering their perceptions of job dignity and the challenges they face, the research aims to contribute to the well-being of these workers and inform relevant stakeholders for a more equitable work environment.

Keywords: delivery agents, equitable work environment, perception of job dignity, work-life balance

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Authors: Abdull Halim

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The Standard Penetration Test (SPT-N) is the most common in situ test for soil investigations. The Shearing Seismic Standard Penetration Test (SSPT-N), on the other hand, is a new method using shearing wave with propagation exponent equation between the shearing wave, Vs., and hardness, N values without any need for borehole data. Due to the fast and accurate results that can be obtained, the SSPT has found many applications such as in the field rectification buried pipe line, the acid tank settlement and foundation design analyses, and the quality control assessment. Many geotechnical regimes and properties have attempted to correlate both the SSPT and the SPT-N values. Various foundation design methods have been developed based on the outcomes of these tests. Hence, it is pertinent to correlate these tests so that either one of the test can be used in the absence of the other, especially for preliminary evaluation and design purposes. The primary purpose of this study was to investigate the relationship between the SSPT-N and SPT-N values for different types of cohesive soil in Peninsular Malaysia. Data were collected from four different sites, and the correlations were established between the hardness N values, principal stress-strain Mohr circle curve, cohesion, friction angle and vertical effective stress. A positive exponent relationship was found between the shearing wave, sVs., and the hardness N values of the soil. In general, the SSPT-N value was slightly lower than the SPT-N value due to the upper limit boundary of the soil layer.

Keywords: InsituSoil determination; shearing wave; hardness; correlation, SSPT-N, SPT-N

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Authors: Hadi Rouhi Belvirdi

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Reinforced concrete structures, in addition to bearing service loads and seismic effects, may also be subjected to impact loads resulting from unforeseen incidents. Understanding the behavior of these structures is crucial, as they serve to protect against such sudden loads and can significantly reduce damage and destruction. In examining the behavior of structures under such loading conditions, a total of eight specimens of single-layer reinforced concrete slabs were subjected to impact loading through the free fall of weights from specified heights. The weights and dimensions of the specimens were uniform, and the amount of reinforcement was consistent. By altering the slabs' overall shape and the reinforcement details, efforts were made to optimize the behavior of the slabs against impact loads. The results indicated that utilizing ductile features in the slabs increased their resistance to impact loading. However, the compressive strength of the reinforcement did not significantly enhance the flexural resistance. Assuming a constant amount of longitudinal steel, changes in the placement of tensile reinforcement led to a decrease in resistance. With a fixed amount of transverse steel, merely adjusting the angle of the transverse reinforcement could help control cracking and mitigate premature failures. An increase in compressive resistance beyond a certain limit resulted in local buckling of the compressive zone, subsequently decreasing the impact resistance.

Keywords: reinforced concrete slab, high-strength concrete, impact loading, impact resistance

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Authors: Abootaleb Shirvani, Svetlozar Rachev

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ESG stands for Environmental, Social, and Governance and is a non-financial factor that investors use to specify material risks and growth opportunities in their analysis process. ESG ratings provide a quantitative measure of socially responsible investment, and it is essential to incorporate ESG ratings when modeling the dynamics of asset returns. In this article, we propose a triple subordinated Lévy process for incorporating numeric ESG ratings into dynamic asset pricing theory to model the time series properties of the stock returns. The motivation for introducing three layers of subordinator is twofold. The first two layers of subordinator capture the skew and fat-tailed properties of the stock return distribution that cannot be explained well by the existing Lévy subordinated model. The third layer of the subordinator introduces ESG valuation and incorporates numeric ESG ratings into dynamic asset pricing theory and option pricing. We employ the triple subordinator Lévy model for developing the ESG-valued stock return model, derive the implied ESG score surfaces for Microsoft, Apple, and Amazon stock returns, and compare the shape of the ESG implied surface scores for these stocks.

Keywords: ESG scores, dynamic asset pricing theory, multiple subordinated modeling, Lévy processes, option pricing

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Authors: Bunakiye R. Japheth, Ogude U. Cyril

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Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.

Keywords: control process, metrics of engineering, structured abstraction, semantic model

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Authors: Jiwuer Jilili, Iogann Tolbatov, Mousumi U. Kahaly

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Metal to insulator transition and interfacial magnetism of the LaNiO₃ based superlattice are main interest due to thickness dependent electronic response and tunable magnetic behavior. We investigate the structural, electronic, and magnetic properties of recently experimentally synthesized (LaNiO₃)n/(CaMnO₃)m superlattices with varying LaNiO₃ thickness using density functional theory. The effect of the on-site Coulomb interaction is discussed. In switching from zero to finite U value for Ni atoms, LaNiO₃ shows transitions from half-metallic to metallic character, while spinning ordering changes from paramagnetic to ferromagnetic (FM). For CaMnO₃, U < 3 eV on Mn atoms results in G-type anti-FM spin ordering whereas increasing U value yields FM ordering. In superlattices, metal to insulator transition was achieved with a reduction of LaNiO₃ thickness. The system with one layer of LaNiO₃ yields insulating character. Increasing LaNiO₃ to two layers and above results in the onset of the metallic character with a major contribution from Ni and Mn 3d eg states. Our results for interfacial ferromagnetism, induced Ni magnetic moments and novel antiferromagnetically coupled Ni atoms are consistent with the recent experimental findings. The possible origin of the emergent magnetism is proposed in terms of the exchange interaction and Anderson localization.

Keywords: density functional theory, interfacial magnetism, metal-insulator transition, Ni magnetism.

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Authors: Rujia Chen, Ajit Narayanan

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Convolutional neural networks (CNN), as typically applied in deep learning, use layer-wise backpropagation (BP) to construct filters and kernels for feature extraction. Such filters are 2D or 3D groups of weights for constructing feature maps at subsequent layers of the CNN and are shared across the entire input. BP as a gradient descent algorithm has well-known problems of getting stuck at local optima. The use of genetic algorithms (GAs) for evolving weights between layers of standard artificial neural networks (ANNs) is a well-established area of neuroevolution. In particular, the use of crossover techniques when optimizing weights can help to overcome problems of local optima. However, the application of GAs for evolving the weights of filters and kernels in CNNs is not yet an established area of neuroevolution. In this paper, a GA-based filter development algorithm is proposed. The results of the proof-of-concept experiments described in this paper show the proposed GA algorithm can find filter weights through evolutionary techniques rather than BP learning. For some simple classification tasks like geometric shape recognition, the proposed algorithm can achieve 100% accuracy. The results for MNIST classification, while not as good as possible through standard filter learning through BP, show that filter and kernel evolution warrants further investigation as a new subarea of neuroevolution for deep architectures.

Keywords: neuroevolution, convolutional neural network, genetic algorithm, filters, kernels

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Authors: W. Mahmood Mat Yunus, Faris Mohammed Ali, Zainal Abidin Talib

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In this study we present new data for the thermal conductivity enhancement in four nanofluids containing 11, 25, 50, 63 nm diameter aluminum oxide (Al2O3) nanoparticles in distilled water. The nanofluids were prepared using single step method (i.e. by dispersing nanoparticle directly in base fluid) which was gathered in ultrasonic device for approximately 7 hours. The transient hot-wire laser beam displacement technique was used to measure the thermal conductivity and thermal diffusivity of the prepared nanofluids. The thermal conductivity and thermal diffusivity were obtained by fitting the experimental data to the numerical data simulated for aluminum oxide in distilled water. The results show that the thermal conductivity and thermal diffusivity of nanofluids increases in non-linear behavior as the particle size increases. While, the thermal conductivity and thermal diffusivity of Al2O3 nanofluids was observed increasing linearly with concentration as the volume fraction concentration increases. We believe that the interfacial layer between solid/fluid is the main factor for the enhancement of thermal conductivity and thermal diffusivity of Al2O3 nanofluids in the present work.

Keywords: transient hot wire-laser beam technique, Al2O3 nanofluid, particle size, volume fraction concentration

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Authors: Zohreh Derikvand, Hadis Cheraghi, Azadeh Azadbakht, Vaclav Eigner, Michal Dusek

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Two new one and two dimensional metal organic coordination polymers of Cu(II), [Cu(3-nph)2(H2O)2pz]n (1) and Ag(I), {[Ag(3-nph)pz].H2O}n (2) with pyrazine (pz) and 3- nitrophthalic acid (3-nph) have been synthesized and characterized by elemental analysis, spectral (IR, UV-Vis), thermal (TG/DTG) analysis and single crystal X-ray diffraction. We used these compounds to preparation modified electrode with Au/Pt nanosparticles in order to investigation electrochemistry and electrocatalysis activities. The surface structure and composition of the sensor were characterized by scanning electron microscopy (SEM). The Ag(I) coordination polymer shows a 2D layer structure constructed from dinuclear silver (I) building blocks in which two crystallographically Ag+ ions are connected to each other by a covalent bond. The pyrazine ligands adopt μ2 bridging modes, linking the metal centers into a one and two -dimensional coordination framework in 1 and 2. The two AgI cations are surrounded by pyrazine and 3-nitrophthalate mono anions and indicate distorted tetrahedral geometry. In the crystal structures of Ag(I) complex there are non-classical hydrogen bonding arrangements, C–O•••π and π–π stacking interactions. In Cu(II) coordination polymer, the coordination geometry around Cu(II) atom is a distorted octahedron. Interestingly, the structural analysis illustrates that the strong and weak hydrogen bond accompanied with C–H•••π and C–O•••π stacking interactions assemble the crystal structure of 1 and 2 into fascinating 3D supramolecular architecture.

Keywords: 3-nithrophethalic acid, crystal structure, coordination polymer, electrocatalysis

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Authors: Ikram Kamal, Mohamed Blaghen

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Biosurfactants are amphiphilic biological compounds consisting of hydrophobic and hydrophilic domains produced extracellularly or as part of the cell membrane by a variety of yeast, bacteria and filamentous fungi. Biosurfactant applications in the environmental industries are promising due to their biodegradability, low toxicity, and effectiveness in enhancing biodegradation and solubilization of low solubility compounds. Currently, the main application is for enhancement of oil recovery and hydrocarbon bioremediation due to their biodegradability and low critical micelle concentration (CMC). The use of biosurfactants has also been proposed for various industrial applications, such as in food additives, cosmetics, detergent formulations and in combinations with enzymes for wastewater treatment. In this study, we have investigated the potential of bacterial strains: Mannheimia haemolytica, Burkholderia cepacia and Serratia ficaria were collected aseptically from the lagoon Marchika (water and soil) in Nador, Morocco; for the production of biosurfactants. This study also aimed to optimize the biosurfactant production process by changing the variables that influence the type and amount of biosurfactant produced by these microorganisms such as: carbon sources and also other physical and chemical parameters such as temperature and pH. Emulsification index, methylene blue test, and thin layer chromatography (TLC) revealed the ability of strains used in this study to produce compounds that could emulsify gasoline. In addition, a GC/MS was used to separate and identify different biosurfactants purified.

Keywords: biosurfactants, Mannheimia haemolytica, biodegradability, Burkholderia cepacia, Serratia ficaria

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Authors: Abdelmajid Timoumi, Salah Alamri, Hatem Alamri

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TiO₂ Graphene Oxide (TiO₂-GO) nanocomposite was prepared using the spin coating technique of suspension of Graphene Oxide (GO) nanosheets and Titanium Tetra Isopropoxide (TIP). The prepared nanocomposites samples were characterized by X-ray diffractometer, Scanning Electron Microscope and Atomic Force Microscope to examine their structures and morphologies. UV-vis transmittance and reflectance spectroscopy was employed to estimate band gap energies. From the TiO₂-GO samples, a 0.25 μm thin layer on a piece of glass 2x2 cm was created. The X-ray diffraction analysis revealed that the as-deposited layers are amorphous in nature. The surface morphology images demonstrate that the layers grew in distributed with some spherical/rod-like and partially agglomerated TiGO on the surface of the composite. The Atomic Force Microscopy indicated that the films are smooth with slightly larger surface roughness. The analysis of optical absorption data of the layers showed that the values of band gap energy decreased from 3.46 eV to 1.40 eV, depending on the grams of GO doping. This reduction might be attributed to electron and/or hole trapping at the donor and acceptor levels in the TiO₂ band structure. Observed results have shown that the inclusion of GO in the TiO₂ matrix have exhibited significant and excellent properties, which would be promising for application in the photovoltaic application.

Keywords: titanium dioxide, graphene oxide, thin films, solar cells

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Authors: Fatima Zohra Rahou, A. Guen Bouazza, B. Bouazza

Abstract:

Multi-gate SOI MOSFETs has shown better results in subthreshold performances. The replacement of SiO2 by high-k dielectric can fulfill the requirements of Multi-gate MOSFETS with a scaling trend in device dimensions. The advancement in fabrication technology has also boosted the use of different high -k dielectric materials as oxide layer at different places in MOSFET structures. One of the most important multi-gate structures is square GAA SOI MOSFET that is a strong candidate for the next generation nanoscale devices; show an even stronger control of short channel effects. In this paper, GAA SOI MOSFET structure with using high -k dielectrics materials Al2O3 (k~9), HfO2 (k~20), La2O3 (k~30) and metal gate TiN are simulated by using 3-D device simulator DevEdit and Atlas of SILVACO TCAD tools. Square GAA SOI MOSFET transistor with High-k HfO2 gate dielectrics and TiN metal gate exhibits significant improvements performances compared to Al2O3 and La2O3 dielectrics for the same structure. Simulation results of GAA SOI MOSFET transistor with HfO2 dielectric show the increase in saturation current and Ion/Ioff ratio while leakage current, subthreshold slope and DIBL effect are decreased.

Keywords: technology SOI, short-channel effects (SCEs), multi-gate SOI MOSFET, square GAA SOI MOSFET, high-k dielectric, Silvaco software

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Authors: Nikki A. Barla, P. K. Ghosh, Sourav Das

Abstract:

Two different groove sizes 13.6 mm (narrow groove) and 7.5 mm (ultra-narrow groove) of 304 LN austenitic stainless steel (ASS) plate was welded using pulse gas metal arc welding (P-GMAW). These grooves were welded using multi-pass single seam per layer (MSPPL) deposition technique with full assurance of groove wall fusion. During bead on plate deposition process, the thermal cycle was recorded using strain buster (temperature measuring device). Both the groove has heat affected Zone (HAZ) width of 1-2 mm. After welding, the microstructure studies was done which revealed that there was higher sensitization (Chromium carbide formation in grain boundary) in the HAZ of 13.6 mm groove weldment as compared to the HAZ of 7.5 mm weldment. Electrochemical potentiokinetic reactivation test (EPR) was done in 0.5 N H₂SO₄ + 1 M KSCN solution to study the degree of sensitization (DOS) and it was observed that 7.5 mm groove HAZ has lower DOS. Mass deposition in the 13.6 mm weld is higher than 7.5mm groove weld, which naturally induces higher residual stress in 13.6 mm weld. Comparison between microstructural studies and corrosion test summarized that the residual stress affects the sensitization property of welded ASS.

Keywords: austenitic stainless steel (ASS), electrochemical potentiokinetic reactivation test (EPR), microstructure, pulse gas metal arc welding (P-GMAW), sensitization

Procedia PDF Downloads 163

Authors: O. Smara, H. Dendougui, B. Legseir

Abstract:

Atriplex halimus L. is particularly well adapted to arid and salt-affected areas. In this species, salinity resistance is often attributed to the presence of vesiculated hairs covering leaf surface and containing a large amount of salt. Atriplex halimus L. (Chenopodiaceae) is a perennial shrub native to the Mediterranean basin with excellent tolerance to drought and salinity. The species is present in semiarid to subhumid areas of the north Mediterranean and in arid zones from North Africa and the eastern Mediterranean. The main aim of this study was to identify a medicinal plant used in the Ouargla (Est-southern Algeria) for the treatment of several human pathologies. This plant is an important source for livestock in nitrogenous matter, it is an effective and relatively inexpensive tool in the fight against erosion and desertification and rehabilitation of degraded lands. Phytochemical investigation is applied to the majority of extracts of the powder of the aerial parts of Atriplex halimus L. Different chromatographic methods after liquid-liquid extraction are used; it is the thin layer chromatography (TLC) and paper using multiple systems and chemical revelations. This study followed by an evaluation by the phenol assay the Folin-Ciocalteu method, using gallic acid as a reference for phenols and quercetin for flavonols. Some polar extracts showed an interesting result better than the less polar extracts.

Keywords: Atriples halimus L., chenopodiaceae, flavonoids, phenols

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Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

Abstract:

The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, gazebo, Rviz, Turtlebot2, slam algorithms, 2d indoor environment, cartographer

Procedia PDF Downloads 145

Authors: Hossain A., Chowdhury S. I.

Abstract:

Introduction: The use of a gamma camera is a standard procedure in nuclear medicine facilities or hospitals to diagnose chronic kidney disease (CKD), but the gamma camera does not precisely stage the disease. The authors sought to determine whether they could use an artificial neural network to determine whether CKD was in normal or abnormal stages based on GFR values (ANN). Method: The 250 kidney patients (Training 188, Testing 62) who underwent an ultrasonography test to diagnose a renal test in our nuclear medical center were scanned using a gamma camera. Before the scanning procedure, the patients received an injection of ⁹⁹ᵐTc-DTPA. The gamma camera computes the pre- and post-syringe radioactive counts after the injection has been pushed into the patient's vein. The artificial neural network uses the softmax function with cross-entropy loss to determine whether CKD is normal or abnormal based on the GFR value in the output layer. Results: The proposed ANN model had a 99.20 % accuracy according to K-fold cross-validation. The sensitivity and specificity were 99.10 and 99.20 %, respectively. AUC was 0.994. Conclusion: The proposed model can distinguish between normal and abnormal stages of CKD by using an artificial neural network. The gamma camera could be upgraded to diagnose normal or abnormal stages of CKD with an appropriate GFR value following the clinical application of the proposed model.

Keywords: artificial neural network, glomerular filtration rate, stages of the kidney, gamma camera

Procedia PDF Downloads 103

Authors: O. P. Oladipo, O. A. Falode

Abstract:

The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

Procedia PDF Downloads 441