Search results for: differential invariant signature curves

Authors: Ram Mohan, Mahendran Samykano, Shyam Aravamudhan

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Metallic nanowires with sub-micron and hundreds of nanometer diameter have a diversity of applications in nano/micro-electromechanical systems (NEMS/MEMS). Characterizing the mechanical properties of such sub-micron and nano-scale metallic nanowires are tedious; require sophisticated and careful experimentation to be performed within high-powered microscopy systems (scanning electron microscope (SEM), atomic force microscope (AFM)). Also, needed are nanoscale devices for placing the nanowires; loading them with the intended conditions; obtaining the data for load–deflection during the deformation within the high-powered microscopy environment poses significant challenges. Even picking the grown nanowires and placing them correctly within a nanoscale loading device is not an easy task. Mechanical characterizations through experimental methods for such nanowires are still very limited. Various techniques at different levels of fidelity, resolution, and induced errors have been attempted by material science and nanomaterial researchers. The methods for determining the load, deflection within the nanoscale devices also pose a significant problem. The state of the art is thus still at its infancy. All these factors result and is seen in the wide differences in the characterization curves and the reported properties in the current literature. In this paper, we discuss and present our experimental method, results, and discussions of uniaxial tensile loading and the development of subsequent stress–strain characteristics curves for Nickel nanowires. Nickel nanowires in the diameter range of 220–270 nm were obtained in our laboratory via an electrodeposition method, which is a solution based, template method followed in our present work for growing 1-D Nickel nanowires. Process variables such as the presence of magnetic field, its intensity; and varying electrical current density during the electrodeposition process were found to influence the morphological and physical characteristics including crystal orientation, size of the grown nanowires1. To further understand the correlation and influence of electrodeposition process variables, associated formed structural features of our grown Nickel nanowires to their mechanical properties, careful experiments within scanning electron microscope (SEM) were conducted. Details of the uniaxial tensile characterization, testing methodology, nanoscale testing device, load–deflection characteristics, microscopy images of failure progression, and the subsequent stress–strain curves are discussed and presented.

Keywords: uniaxial tensile characterization, nanowires, electrodeposition, stress-strain, nickel

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Authors: E. T. El Shenawy, O. N. A. Esmail, Adel A. Elbaset, Hesham F. A. Hamed

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Generation of the electrical energy based on photovoltaic (PV) technology has been increased over the world due to either the continuous reduction in the traditional energy sources in addition to the pollution problems related to their usage, or the clean nature and safe usage of the PV technology. Also, PV systems can generate clean electricity in the site of use without any transmission, which can be considered cost effective than other generation systems. The performance of the PV system is highly affected by the amount of solar radiation incident on it. Completely or partially shaded PV systems can affect its output. The PV system can be shaded by trees, buildings, dust, incorrect system configuration, or other obstacles. The present paper studies the effect of the partial shading on the performance of a thin film PV module under climatic conditions of Cairo, Egypt. This effect was measured and evaluated according to practical measurement of the characteristic curves such as current-voltage and power-voltage for two identical PV modules (with and without shading) placed at the same time on one mechanical structure for comparison. The measurements have been carried out for the following shading patterns; half cell (bottom, middle, and top of the PV module); complete cell; and two adjacent cells. The results showed that partially shading the PV module changes the shapes of the I-V and P-V curves and produces more than one maximum power point, that can disturb the traditional maximum power point trackers. Also, the output power from the module decreased according to the incomplete solar radiation reaching the PV module due to shadow patterns. The power loss due shading was 7%, 22%, and 41% for shading of half-cell, one cell, and two adjacent cells of the PV module, respectively.

Keywords: I-V measurements, PV module characteristics, PV module power loss, PV module shading

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Authors: Yuri V. Kim

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This article presents a new approach to the Functional Testing of Space Systems (SS). It can be considered as a generic test and used for a wide class of SS that from the point of view of System Dynamics and Control may be described by the ordinary differential equations. Suggested methodology is based on using semi-natural experiment- laboratory stand that doesn’t require complicated, precise and expensive technological control-verification equipment. However, it allows for testing system as a whole totally assembled unit during Assembling, Integration and Testing (AIT) activities, involving system hardware (HW) and software (SW). The test physically activates system input (sensors) and output (actuators) and requires recording their outputs in real time. The data is then inserted in laboratory PC where it is post-experiment processed by Matlab/Simulink Identification Toolbox. It allows for estimating system dynamics in form of estimation of system differential equations by the experimental way and comparing them with expected mathematical model prematurely verified by mathematical simulation during the design process.

Keywords: system dynamics, space system ground tests and space qualification, system dynamics identification, satellite attitude control, assembling, integration and testing

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Authors: Kwan-Ho Kim, Jin-Hong Park

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The multi-valued logic (MVL) circuits, which can handle more than two logic states, are one of the promising solutions to overcome the bit density limitations of conventional binary logic systems. Recently, tunneling devices such as Esaki diode and resonant tunneling diode (RTD) have been extensively explored to construct the MVL circuits. These tunneling devices present a negative differential resistance (NDR) phenomenon in which a current decreases as a voltage increases in a specific applied voltage region. Due to this non-monotonic current behavior, the tunneling devices have more than two threshold voltages, consequently enabling construction of MVL circuits. Recently, the emergence of two dimensional (2D) van der Waals (vdW) crystals has opened up the possibility to fabricate such tunneling devices easily. Owing to the defect-free surface of the 2D crystals, a very abrupt junction interface could be formed through a simple stacking process, which subsequently allowed the implementation of a high-performance tunneling device. Here, we report a vdW heterostructure based tunneling device with multiple threshold voltages, which was fabricated with black phosphorus (BP) and hafnium diselenide (HfSe₂). First, we exfoliated BP on the SiO₂ substrate and then transferred HfSe₂ on BP using dry transfer method. The BP and HfSe₂ form type-Ⅲ heterojunction so that the highly doped n+/p+ interface can be easily implemented without additional electrical or chemical doping process. Owing to high natural doping at the junction, record high peak to valley ratio (PVCR) of 16 was observed to the best our knowledge in 2D materials based NDR device. Furthermore, based on this, we first demonstrate the feasibility of the ternary latch by connecting two multi-threshold voltage devices in series.

Keywords: two dimensional van der Waals crystal, multi-valued logic, negative differential resistnace, tunneling device

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Authors: Mohammed Mesrar, Hamza El Malki, Hamza Mesrar

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In this study, ceramics of (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3 were synthesized through a conventional calcination process (solid-state method) at 1000°C for 4 hours, with x(%) values ranging from 0.0 to 100. Room temperature XRD patterns confirmed the phase formation of the samples. The Rietveld refinement method was employed to verify the morphotropic phase boundary (MPB) at x(%)=16-20. We investigated the average crystallite size and lattice strain using Scherrer's formula and Williamson-Hall (W-H) analysis. SEM image analyses provided additional evidence of the impact of doping on structural growth under low temperatures. Relaxation time extracted from Z″(f) and M″(f) spectra for x(%) = 0.0, 12, 16, 20, and 30 followed the Arrhenius law, revealing the presence of three distinct relaxation mechanisms with varying activation energies. The shoulder response in M″(f) indirectly indicated the existence of highly polarizable entities in the samples, serving as a signature of polar nanoregions (PNRs) within the grains.In this study, ceramics of (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3 were synthesized through a conventional calcination process (solid-state method) at 1000°C for 4 hours, with x(%) values ranging from 0.0 to 100. Room temperature XRD patterns confirmed the phase formation of the samples. The Rietveld refinement method was employed to verify the morphotropic phase boundary (MPB) at x(%)=16-20. We investigated the average crystallite size and lattice strain using Scherrer's formula and Williamson-Hall (W-H) analysis. SEM image analyses provided additional evidence of the impact of doping on structural growth under low temperatures. Relaxation time extracted from Z″(f) and M″(f) spectra for x(%) = 0.0, 12, 16, 20, and 30 followed the Arrhenius law, revealing the presence of three distinct relaxation mechanisms with varying activation energies. The shoulder response in M″(f) indirectly indicated the existence of highly polarizable entities in the samples, serving as a signature of polar nanoregions (PNRs) within the grains.

Keywords: (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3, Rietveld refinement, Scanning electron microscopy (SEM), Williamson-Hall plots, charge density distribution, dielectric properties

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Authors: Adilah Shariff, Nur Syairah Mohamad Aziz, Norsyahidah Md Saleh, Nur Syuhada Izzati Ruzali

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The first objective of this study is to investigate the suitability of coconut frond (CF) and coconut husk (CH) as feedstocks using a laboratory-scale slow pyrolysis experimental setup. The second objective is to investigate the effect of pyrolysis temperature on the biochar yield. The properties of CF and CH feedstocks were compared. The properties of the CF and CH feedstocks were investigated using proximate and elemental analysis, lignocellulosic determination, and also thermogravimetric analysis (TGA). The CF and CH feedstocks were pyrolysed at 300, 400, 500, 600 and 700 °C for 2 hours at 10 °C/min heating rate. The proximate analysis showed that CF feedstock has 89.96 mf wt% volatile matter, 4.67 mf wt% ash content and 5.37 mf wt% fixed carbon. The lignocelluloses analysis showed that CF feedstock contained 21.46% lignin, 39.05% cellulose and 22.49% hemicelluloses. The CH feedstock contained 84.13 mf wt% volatile matter, 0.33 mf wt% ash content, 15.54 mf wt% fixed carbon, 28.22% lignin, 33.61% cellulose and 22.03% hemicelluloses. Carbon and oxygen are the major component of the CF and CH feedstock compositions. Both of CF and CH feedstocks contained very low percentage of sulfur, 0.77% and 0.33%, respectively. TGA analysis indicated that coconut wastes are easily degraded. It may be due to their high volatile content. Between the temperature ranges of 300 and 800 °C, the TGA curves showed that the weight percentage of CF feedstock is lower than CH feedstock by 0.62%-5.88%. From the D TGA curves, most of the weight loss occurred between 210 and 400 °C for both feedstocks. The maximum weight loss for both CF and CH are 0.0074 wt%/min and 0.0061 wt%/min, respectively, which occurred at 324.5 °C. The yield percentage of both CF and CH biochars decreased significantly as the pyrolysis temperature was increased. For CF biochar, the yield decreased from 49.40 wt% to 28.12 wt% as the temperature increased from 300 to 700 °C. The yield for CH biochars also decreased from 52.18 wt% to 28.72 wt%. The findings of this study indicated that both CF and CH are suitable feedstock for slow pyrolysis of biochar.

Keywords: biochar, biomass, coconut wastes, slow pyrolysis

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Authors: Merouane Salhi, Mohamed Roudane, Abdelkader Kirad

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In this work, we present a new form of characteristics method, which is a technique for solving partial differential equations. Typically, it applies to first-order equations; the aim of this method is to reduce a partial differential equation to a family of ordinary differential equations along which the solution can be integrated from some initial data. This latter developed under the real gas theory, because when the thermal and the caloric imperfections of a gas increases, the specific heat and their ratio do not remain constant anymore and start to vary with the gas parameters. The gas doesn’t stay perfect. Its state equation change and it becomes for a real gas. The presented equations of the characteristics remain valid whatever area or field of study. Here we need have inserted the developed Prandtl Meyer function in the mathematical system to find a new model when the effect of stagnation pressure is taken into account. In this case, the effects of molecular size and intermolecular attraction forces intervene to correct the state equation, the thermodynamic parameters and the value of Prandtl Meyer function. However, with the assumptions that Berthelot’s state equation accounts for molecular size and intermolecular force effects, expressions are developed for analyzing the supersonic flow for thermally and calorically imperfect gas. The supersonic parameters depend directly on the stagnation parameters of the combustion chamber. The resolution has been made by the finite differences method using the corrector predictor algorithm. As results, the developed mathematical model used to design 2D minimum length nozzles under effect of the stagnation parameters of fluid flow. A comparison for air with the perfect gas PG and high temperature models on the one hand and our results by the real gas theory on the other of nozzles shapes and characteristics are made.

Keywords: numerical methods, nozzles design, real gas, stagnation parameters, supersonic expansion, the characteristics method

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Authors: Amir Bahrami

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In the fields of chemical graph theory, molecular topology, and mathematical chemistry, a topological index or a descriptor index also known as a connectivity index is a type of a molecular descriptor that is calculated based on the molecular graph of a chemical compound. Topological indices are numerical parameters of a graph which characterize its topology and are usually graph invariant. Topological indices are used for example in the development of quantitative structure-activity relationships (QSARs) in which the biological activity or other properties of molecules are correlated with their chemical structure. In this paper some descriptor index (descriptor index) of single-walled carbon nanotubes, is determined.

Keywords: chemical graph theory, molecular topology, molecular descriptor, single-walled carbon nanotubes

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Authors: Issam Ben Jami

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Information retrieval in digital libraries is very important because most famous historical documents occupy a significant value. The word spotting in historical documents is a very difficult notion, because automatic recognition of such documents is naturally cursive, it represents a wide variability in the level scale and translation words in the same documents. We first present a system for the automatic recognition, based on the extraction of interest points words from the image model. The extraction phase of the key points is chosen from the representation of the image as a synthetic description of the shape recognition in a multidimensional space. As a result, we use advanced methods that can find and describe interesting points invariant to scale, rotation and lighting which are linked to local configurations of pixels. We test this approach on documents of the 15th century. Our experiments give important results.

Keywords: feature matching, historical documents, pattern recognition, word spotting

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Authors: Siraa Ben Ftima, Mourad Talbi, Tahar Ezzedine

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In this paper, we present a technique of secure watermarking of grayscale and color images. This technique consists in applying the Singular Value Decomposition (SVD) in LWT (Lifting Wavelet Transform) domain in order to insert the watermark image (grayscale) in the host image (grayscale or color image). It also uses signature in the embedding and extraction steps. The technique is applied on a number of grayscale and color images. The performance of this technique is proved by the PSNR (Pick Signal to Noise Ratio), the MSE (Mean Square Error) and the SSIM (structural similarity) computations.

Keywords: lifting wavelet transform (LWT), sub-space vectorial decomposition, secure, image watermarking, watermark

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Authors: Maria Arechavaleta, Mark Halpin

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In the United States, costs of solar energy systems have declined to the point that they are viable options for most consumers. However, there are no consistent procedures for specifying sufficient systems. The factors that must be considered are energy consumption, potential solar energy production, and cost. The traditional method of specifying solar energy systems is based on assumed daily levels of available solar energy and average amounts of daily energy consumption. The mismatches between energy production and consumption are usually mitigated using battery energy storage systems, and energy use is curtailed when necessary. The main consumer decision question that drives the total system cost is how much unserved (or curtailed) energy is acceptable? Of course additional solar conversion equipment can be installed to provide greater peak energy production and extra energy storage capability can be added to mitigate longer lasting low solar energy production periods. Each option increases total cost and provides a benefit which is difficult to quantify accurately. An approach to quantify the cost-benefit of adding additional resources, either production or storage or both, based on the statistical concepts of loss-of-energy probability and expected unserved energy, is presented in this paper. Relatively simple calculations, based on site-specific energy availability and consumption data, can be used to show the value of each additional increment of production or storage. With this incremental benefit-cost information, consumers can select the best overall performance combination for their application at a cost they are comfortable paying. The approach is based on a statistical analysis of energy consumption and production characteristics over time. The characteristics are in the forms of curves with each point on the curve representing an energy consumption or production value over a period of time; a one-minute period is used for the work in this paper. These curves are measured at the consumer location under the conditions that exist at the site and the duration of the measurements is a minimum of one week. While greater accuracy could be obtained with longer recording periods, the examples in this paper are based on a single week for demonstration purposes. The weekly consumption and production curves are overlaid on each other and the mismatches are used to size the battery energy storage system. Loss-of-energy probability and expected unserved energy indices are calculated in addition to the total system cost. These indices allow the consumer to recognize and quantify the benefit (probably a reduction in energy consumption curtailment) available for a given increase in cost. Consumers can then make informed decisions that are accurate for their location and conditions and which are consistent with their available funds.

Keywords: battery energy storage systems, loss of load probability, residential renewable energy, solar energy systems

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Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang

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Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.

Keywords: source identification, ordinary differential equations, label propagation, complex networks

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Authors: Chong Hu, Tiantian Wang, Zhe Li, Ourui Huang, Yichen Pan

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When the train is running in a high geothermal tunnel, changes in the temperature field will cause disturbances in the propagation and superposition of pressure waves in the tunnel, which in turn have an effect on the aerodynamic resistance of the train. The aim of this paper is to investigate the effect of the changes in the lengths of the high-temperature zone of the tunnel on the aerodynamic resistance of the train, clarifying the evolution mechanism of aerodynamic resistance of trains in tunnels with high ground temperatures. Firstly, moving model tests of trains passing through wall-heated tunnels were conducted to verify the reliability of the numerical method in this paper. Subsequently, based on the three-dimensional unsteady compressible RANS method and the standard k-ε two-equation turbulence model, the change laws of the average aerodynamic resistance under different high-temperature zone lengths were analyzed, and the influence of frictional resistance and pressure difference resistance on total resistance at different times was discussed. The results show that as the length of the high-temperature zone LH increases, the average aerodynamic resistance of a train running in a tunnel gradually decreases; when LH = 330 m, the aerodynamic resistance can be reduced by 5.7%. At the moment of maximum resistance, the total resistance, differential pressure resistance, and friction resistance all decrease gradually with the increase of LH and then remain basically unchanged. At the moment of the minimum value of resistance, with the increase of LH, the total resistance first increases and then slowly decreases; the differential pressure resistance first increases and then remains unchanged, while the friction resistance first remains unchanged and then gradually decreases, and the ratio of the differential pressure resistance to the total resistance gradually increases with the increase of LH. The results of this paper can provide guidance for scholars who need to investigate the mechanism of aerodynamic resistance change of trains in high geothermal environments, as well as provide a new way of thinking for resistance reduction in non-high geothermal tunnels.

Keywords: high-speed trains, aerodynamic resistance, high-ground temperature, tunnel

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Authors: Silas A. Ihedioha

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In this work; it is considered that an investor’s portfolio is comprised of two assets; a risky stock which price process is driven by the geometric Brownian motion and a risk-free asset with Ornstein-Uhlenbeck Stochastic interest rate of return, where consumption, taxes, transaction costs and dividends are involved. This paper aimed at the optimization of the investor’s expected utility of consumption and terminal return on his investment at the terminal time having power utility preference. Using dynamic optimization procedure of maximum principle, a second order nonlinear partial differential equation (PDE) (the Hamilton-Jacobi-Bellman equation HJB) was obtained from which an ordinary differential equation (ODE) obtained via elimination of variables. The solution to the ODE gave the closed form solution of the investor’s problem. It was found the optimal investment in the risky asset is horizon dependent and a ratio of the total amount available for investment and the relative risk aversion coefficient.

Keywords: optimal, investment, Ornstein-Uhlenbeck, utility maximization, stochastic interest rate, maximum principle

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Authors: Roslinda Nazar, Amin Noor, Khamisah Jafar, Ioan Pop

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In this paper, the steady laminar three-dimensional boundary layer flow and heat transfer of a copper (Cu)-water nanofluid in the vicinity of a permeable shrinking flat surface in an otherwise quiescent fluid is studied. The nanofluid mathematical model in which the effect of the nanoparticle volume fraction is taken into account is considered. The governing nonlinear partial differential equations are transformed into a system of nonlinear ordinary differential equations using a similarity transformation which is then solved numerically using the function bvp4c from Matlab. Dual solutions (upper and lower branch solutions) are found for the similarity boundary layer equations for a certain range of the suction parameter. A stability analysis has been performed to show which branch solutions are stable and physically realizable. The numerical results for the skin friction coefficient and the local Nusselt number as well as the velocity and temperature profiles are obtained, presented and discussed in detail for a range of various governing parameters.

Keywords: heat transfer, nanofluid, shrinking surface, stability analysis, three-dimensional flow

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Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães

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This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.

Keywords: path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart

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Authors: M. François, L. Sigot, C. Vallières

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Volatile Organic Compounds (VOCs) are a real health issue, particularly in domestic indoor environments. Among these VOCs, acetaldehyde is frequently monitored in dwellings ‘air, especially due to smoking and spontaneous emissions from the new wall and soil coverings. It is responsible for respiratory complaints and is classified as possibly carcinogenic to humans. Adsorption processes are commonly used to remove VOCs from the air. Metal-Organic Frameworks (MOFs) are a promising type of material for high adsorption performance. These hybrid porous materials composed of metal inorganic clusters and organic ligands are interesting thanks to their high porosity and surface area. The HKUST-1 (also referred to as MOF-199) is a copper-based MOF with the formula [Cu₃(BTC)₂(H₂O)₃]n (BTC = benzene-1,3,5-tricarboxylate) and exhibits unsaturated metal sites that can be attractive sites for adsorption. The objective of this study is to investigate the impact of HKUST-1 pretreatment on acetaldehyde adsorption. Thus, dynamic adsorption experiments were conducted in 1 cm diameter glass column packed with 2 cm MOF bed height. MOF were sieved to 630 µm - 1 mm. The feed gas (Co = 460 ppmv ± 5 ppmv) was obtained by diluting a 1000 ppmv acetaldehyde gas cylinder in air. The gas flow rate was set to 0.7 L/min (to guarantee a suitable linear velocity). Acetaldehyde concentration was monitored online by gas chromatography coupled with a flame ionization detector (GC-FID). Breakthrough curves must allow to understand the interactions between the MOF and the pollutant as well as the impact of the HKUST-1 humidity in the adsorption process. Consequently, different MOF water content conditions were tested, from a dry material with 7 % water content (dark blue color) to water saturated state with approximately 35 % water content (turquoise color). The rough material – without any pretreatment – containing 30 % water serves as a reference. First, conclusions can be drawn from the comparison of the evolution of the ratio of the column outlet concentration (C) on the inlet concentration (Co) as a function of time for different HKUST-1 pretreatments. The shape of the breakthrough curves is significantly different. The saturation of the rough material is slower (20 h to reach saturation) than that of the dried material (2 h). However, the breakthrough time defined for C/Co = 10 % appears earlier in the case of the rough material (0.75 h) compared to the dried HKUST-1 (1.4 h). Another notable difference is the shape of the curve before the breakthrough at 10 %. An abrupt increase of the outlet concentration is observed for the material with the lower humidity in comparison to a smooth increase for the rough material. Thus, the water content plays a significant role on the breakthrough kinetics. This study aims to understand what can explain the shape of the breakthrough curves associated to the pretreatments of HKUST-1 and which mechanisms take place in the adsorption process between the MOF, the pollutant, and the water.

Keywords: acetaldehyde, dynamic adsorption, HKUST-1, pretreatment influence

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Authors: Afaf Alharbi, Qianni Zhang

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The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper introduces a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple-instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation of an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: attention multiple instance learning, MIL and transfer learning, histopathological slides, cancer tissue classification

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Authors: Saeid Sahmani

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Due to size-dependent behavior of nanostrustures, the classical continuum models are not applicable for the analyses at this submicrion size. Surface stress effect is one of the most important matters which make the nanoscale structures to have different properties compared to the conventional structures due to high surface to volume ratio. In the present study, free vibration characteristics of nanoplates are investigated including surface stress effects. To this end, non-classical plate model based on Gurtin-Murdoch elasticity theory is proposed to evaluate the surface stress effects on the vibrational behavior of nanoplates subjected to different boundary conditions. Generalized differential quadrature (GDQ) method is employed to discretize the governing non-classical differential equations along with various edge supports. Selected numerical results are given to demonstrate the distinction between the behavior of nanoplates predicted by the classical and present non-classical plate models that leads to illustrate the great influence of surface stress effect. It is observed that this influence quite depends on the magnitude of the surface elastic constants which are relevant to the selected material.

Keywords: nanomechanics, surface stress, free vibration, GDQ method, small scale effect

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Authors: Elisabetta Cianfanelli, Paolo Pupparo, Maria Claudia Coppola

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The recent evolutions in the innovation processes and in the intrinsic tendencies of the product development process, lead to new considerations on the design flow. The instability and complexity that contemporary life describes, defines new problems in the production of products, stimulating at the same time the adoption of new solutions across the entire design process. The advent of Additive Manufacturing, but also of IOT and AI technologies, continuously puts us in front of new paradigms regarding design as a social activity. The totality of these technologies from the point of view of application describes a whole series of problems and considerations immanent to design thinking. Addressing these problems may require some initial intuition and the use of some provisional set of rules or plausible strategies, i.e., heuristic reasoning. At the same time, however, the evolution of digital technology and the computational speed of new design tools describe a new and contrary design framework in which to operate. It is therefore interesting to understand the opportunities and boundaries of the new man-algorithm relationship. The contribution investigates the man-algorithm relationship starting from the state of the art of the Made in Italy model, the most known fields of application are described and then focus on specific cases in which the mutual relationship between man and AI becomes a new driving force of innovation for entire production chains. On the other hand, the use of algorithms could engulf many design phases, such as the definition of shape, dimensions, proportions, materials, static verifications, and simulations. Operating in this context, therefore, becomes a strategic action, capable of defining fundamental choices for the design of product systems in the near future. If there is a human-algorithm combination within a new integrated system, quantitative values can be controlled in relation to qualitative and material values. The trajectory that is described therefore becomes a new design horizon in which to operate, where it is interesting to highlight the good practices that already exist. In this context, the designer developing new forms can experiment with ways still unexpressed in the project and can define a new synthesis and simplification of algorithms, so that each artifact has a signature in order to define in all its parts, emotional and structural. This signature of the designer, a combination of values and design culture, will be internal to the algorithms and able to relate to digital technologies, creating a generative dialogue for design purposes. The result that is envisaged indicates a new vision of digital technologies, no longer understood only as of the custodians of vast quantities of information, but also as a valid integrated tool in close relationship with the design culture.

Keywords: decision making, design euristics, product design, product design process, design paradigms

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Authors: R. K. Saket

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This paper presents design aspects and probabilistic approach for generation reliability evaluation of an alternative resource: municipal waste water based micro hydro power generation system. Annual and daily flow duration curves have been obtained for design, installation, development, scientific analysis and reliability evaluation of the MHPP. The hydro potential of the waste water flowing through sewage system of the BHU campus has been determined to produce annual flow duration and daily flow duration curves by ordering the recorded water flows from maximum to minimum values. Design pressure, the roughness of the pipe’s interior surface, method of joining, weight, ease of installation, accessibility to the sewage system, design life, maintenance, weather conditions, availability of material, related cost and likelihood of structural damage have been considered for design of a particular penstock for reliable operation of the MHPP. A MHPGS based on MWW and SEIG is designed, developed, and practically implemented to provide reliable electric energy to suitable load in the campus of the Banaras Hindu University, Varanasi, (UP), India. Generation reliability evaluation of the developed MHPP using Gaussian distribution approach, safety factor concept, peak load consideration and Simpson 1/3rd rule has presented in this paper.

Keywords: self excited induction generator, annual and daily flow duration curve, sewage system, municipal waste water, reliability evaluation, Gaussian distribution, Simpson 1/3rd rule

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Authors: Hamsini Pulugurtha, P. V. S. L. Jagadamba

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Programmed Speech to Text and Text Summarization Using Graph-based Algorithms can be utilized in gatherings to get the short depiction of the gathering for future reference. This gives signature check utilizing Siamese neural organization to confirm the personality of the client and convert the client gave sound record which is in English into English text utilizing the discourse acknowledgment bundle given in python. At times just the outline of the gathering is required, the answer for this text rundown. Thus, the record is then summed up utilizing the regular language preparing approaches, for example, solo extractive text outline calculations

Keywords: Siamese neural network, English speech, English text, natural language processing, unsupervised extractive text summarization

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Authors: Alma Sobrevilla

Abstract:

Using panel data from Mexico, this paper studies the determinants of women’s intrahousehold decision-making power using a generalised ordered logit model. Fixed effects estimations are also carried out to solve potential endogeneity coming from unobservable time-invariant factors. Finally, the paper analyses quadratic and community divergence effects of education on power. Results show heterogeneity in the effect of each of the determinants across different levels of decision-making power and suggest the presence of a significant quadratic effect of education. Having more education than the community average has a negative effect on power, supporting the notion that women tend to compensate their success outside the household with submissive attitudes at home.

Keywords: women, decision-making power, intrahousehold, Mexico

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Authors: H. Niranjan, S. Sivasankaran

Abstract:

Heat and mass transfer near a steady stagnation point boundary layer flow of viscous incompressible fluid through porous media investigates along a vertical plate is thoroughly studied under the presence of magneto hydrodynamic (MHD) effects. The fluid flow is steady, laminar, incompressible and in two-dimensional. The nonlinear differential coupled parabolic partial differential equations of continuity, momentum, energy and specie diffusion are converted into the non-similar boundary layer equations using similarity transformation, which are then solved numerically using the Runge-Kutta method along with shooting method. The effects of the conjugate heat transfer parameter, the porous medium parameter, the permeability parameter, the mixed convection parameter, the magnetic parameter, and the thermal radiation on the velocity and temperature profiles as well as on the local skin friction and local heat transfer are presented and analyzed. The validity of the methodology and analysis is checked by comparing the results obtained for some specific cases with those available in the literature. The various parameters on local skin friction, heat and mass transfer rates are presented in tabular form.

Keywords: MHD, porous medium, slip, convective boundary condition, stagnation point

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Authors: Elzbieta Babula, Juhyun Park

Abstract:

Tversky and Kahneman’s cumulative prospect theory assumes symmetric probability cumulation with regard to the reference point within decision weights. Theoretically, this model should be invariant under the change of the direction of probability cumulation. In the present study, this phenomenon is being investigated by creating a reference model that allows verifying the parameter interactions in the cumulative prospect theory specifications. The simultaneous parametric fitting of utility and weighting functions is applied to binary choice data from the experiment. The results show that the flexibility of the probability weighting function is a crucial characteristic allowing to prevent parameter interactions while estimating cumulative prospect theory.

Keywords: binary choice experiment, cumulative prospect theory, decision weights, parameter interactions

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Authors: Seyed Abbas Tabatabaei, Fereydoon Moghadas Nejad, Mohammad Saed

Abstract:

The bleeding prediction of the asphalt is one of the most complex subjects in the pavement engineering. In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) is used for modeling the effect of important parameters on bleeding is trained and tested with the experimental results. bleeding index based on the asphalt film thickness differential as target parameter,asphalt content, temperature depth of two centemeter, heavy traffic, dust to effective binder, Marshall strength, passing 3/4 sieves, passing 3/8 sieves,passing 3/16 sieves, passing NO8, passing NO50, passing NO100, passing NO200 as input parameters. Then, we randomly divided empirical data into train and test sections in order to accomplish modeling. We instructed ANFIS network by 72 percent of empirical data. 28 percent of primary data which had been considered for testing the approprativity of the modeling were entered into ANFIS model. Results were compared by two statistical criterions (R2, RMSE) with empirical ones. Considering the results, it is obvious that our proposed modeling by ANFIS is efficient and valid and it can also be promoted to more general states.

Keywords: bleeding, asphalt film thickness differential, Anfis Modeling

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Authors: Sofiane Grira, Hichem Eleuch

Abstract:

We explore the analytical soliton-pair solutions for unbalanced coupling between the two coherent lights and the atomic transitions in a dissipative three-level system in lambda configuration. The two allowed atomic transitions are interacting resonantly with two laser fields. For unbalanced coupling, it is possible to derive an explicit solution for non-linear differential equations describing the soliton-pair propagation in this three-level system with the same velocity. We suppose that the spontaneous emission rates from the excited state to both ground states are the same. In this work, we focus on such case where we consider the coupling between the transitions and the optical fields are unbalanced. The existence conditions for the soliton-pair propagations are determined. We will show that there are four possible configurations of the soliton-pair pulses. Two of them can be interpreted as a couple of solitons with same directions of polarization and the other two as soliton-pair with opposite directions of polarization. Due to the fact that solitons have stable shapes while propagating in the considered media, they are insensitive to noise and dispersion. Our results have potential applications in data transfer with the soliton-pair pulses, where a dissipative three-level medium could be a realistic model for the optical communication media.

Keywords: non-linear differential equations, solitons, wave propagations, optical fiber

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Authors: Sharmila Pradhan, Ralf Lach, George Michler, Jean Mark Saiter, Rameshwar Adhikari

Abstract:

Ethylene/1-octene copolymer was modified incorporating three types of nanofillers differed in their dimensionality in order to investigate the effect of filler dimensionality on mechanical properties, for instance, tensile strength, microhardness etc. The samples were prepared by melt mixing followed by compression moldings. The microstructure of the novel material was characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) method and Transmission electron microscopy (TEM). Other important properties such as melting, crystallizing and thermal stability were also investigated via differential scanning calorimetry (DSC) and Thermogravimetry analysis (TGA). The FTIR and XRD results showed that the composites were formed by physical mixing. The TEM result supported the homogeneous dispersion of nanofillers in the matrix. The mechanical characterization performed by tensile testing showed that the composites with 1D nanofiller effectively reinforced the polymer. TGA results revealed that the thermal stability of pure EOC is marginally improved by the addition of nanofillers. Likewise, melting and crystallizing properties of the composites are not much different from that of pure.

Keywords: copolymer, differential scanning calorimetry, nanofiller, tensile strength

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Authors: Kirti Gosavi, Anita Bhole

Abstract:

The paper demonstrates simulation and steady-state performance of three phase squirrel cage induction motor and detection of rotor broken bar fault using MATLAB. This simulation model is successfully used in the fault detection of rotor broken bar for the induction machines. A dynamic model using PWM inverter and mathematical modelling of the motor is developed. The dynamic simulation of the small power induction motor is one of the key steps in the validation of the design process of the motor drive system and it is needed for eliminating advertent design errors and the resulting error in the prototype construction and testing. The simulation model will be helpful in detecting the faults in three phase induction motor using Motor current signature analysis.

Keywords: squirrel cage induction motor, pulse width modulation (PWM), fault diagnosis, induction motor

Procedia PDF Downloads 633

Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

Abstract:

In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: equivalent martingale measure, European put option, girsanov theorem, martingales, monte carlo method, option price valuation formula

Procedia PDF Downloads 134