Search results for: estimation of properties of the model

Authors: V. Marzal, J. C. Torres, B. Garcia-Camara, Manuel Cano-Garcia, Xabier Quintana, I. Perez Garcilopez, J. M. Sanchez-Pena

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At the present time, the use of nanostructures in complex media, like liquid crystals, is widely extended to manipulate their properties, either electrical or optical. In addition, these media can also be used to control the optical properties of the nanoparticles, for instance when they are resonant. In this work, the change on electrical properties of a liquid crystal cell by adding TiO₂ nanoparticles on one of the alignment layers has been analyzed. These nanoparticles, with a diameter of 100 nm and spherical shape, were deposited in one of the substrates (ITO + polyimide) by spin-coating in order to produce a homogeneous layer. These substrates were checked using an optical microscope (objective x100) to avoid potential agglomerates. The liquid crystal cell is then fabricated, using one of these substrates and another without nanoparticles, and filled with E7. The study of the electrical response was done through impedance measurements in a long range of frequencies (3 Hz- 6 MHz) and at ambient temperature. Different nanoparticle concentrations were considered, as well as pure E7 and an empty cell for comparison purposes. Results about the effective dielectric permittivity and conductivity are presented along with models of equivalent electric circuits and its physical interpretation. As a summary, it has been observed the clear influence of the presence of the nanoparticles, strongly modifying the electric response of the device. In particular, a variation of both the effective permittivity and the conductivity of the device have been observed. This result requires a deep analysis of the effect of these nanoparticles on the trapping of free ions in the device, allowing a controlled manipulation and frequency tuning of the electrical response of these devices.

Keywords: alignment layer, electrical behavior, liquid crystal, TiO₂ nanoparticles

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Authors: Se-Han Lee, Kwang-Woo Go, Gwang-Hyun Ahn, Hee-Sung Park, Cheol-Kyu Han, Jun-Bo Shim, Geun-Chul Kang, Hyun-Jung Lee

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In recent years, with the advent of smart cars and the expansion of the market, the announcement of 'Adventures in Automotive Networks and Control Units' at the DEFCON21 conference in 2013 revealed that cars are not safe from hacking. As a result, the HEAVENS model considering not only the functional safety of the vehicle but also the security has been suggested. However, the HEAVENS model only presents a simple process, and there are no detailed procedures and activities for each process, making it difficult to apply it to the actual vehicle security vulnerability check. In this paper, we propose an automated attack database that systematically summarizes attack vectors, attack types, and vulnerable vehicle models to prepare for various car hacking attacks, and data flow diagrams that can detect various vulnerabilities and suggest a way to materialize the HEAVENS model.

Keywords: automotive security, HEAVENS, car hacking, security model, information security

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Authors: Javad Karimi, Prashanth Konda Gokuldoss

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Microstructural inhomogeneity in additively manufactured materials affects the material properties. The present study aims in minimizing such microstructural inhomogeneity in Ti6Al4V alloy fabricated using selective laser melting (SLM) from the gas atomized powder. A detailed and systematic study of the effect of remelting on the microstructure and mechanical properties of Ti6Al4V manufactured by SLM was compared with electron beam melting and spark plasma sintering.

Keywords: additive manufacturing, selective laser melting, Ti6Al4V, microstructure

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Authors: Jian Li

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The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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Authors: Muhammad Shafiq Ahmed, Sabastine Ezugwu

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Thermophysical properties of Carbon Tetrachloride (CCl₄), a photothermal fluid used frequently in Photothermal Deflection Spectroscopy (PDS), containing different volume fractions of single walled carbon nanotube (SWCNTs) and their effect on the amplitude of PDS signal are investigated. It is found that the presence of highly thermally conducting SWCNTs in CCl₄ enhances the heat transfer from heated sample to the adjoining photothermal fluid, resulting in an increase in the intensity of amplitude of PDS signal. With the increasing volume fraction of SWCNTs in CCl₄, the amplitude of PDS signal is nearly doubled for volume fraction fopt =3.7X10⁻³ %., after that the signal drops with a further increase in the fraction of SWCNTs. It is shown that the use of highly thermally conducting carbon nanotubes enhances the heat exchange coefficient between the heated sample surface and adjoining fluid, resulting to an enhancement of PDS signal and consequently the improvement in the sensitivity of PDS technique.

Keywords: carbon nanotubes, heat transfer, nanofluid, photothermal deflection spectroscopy, thermophysical properties

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Authors: J. Ritonja, B. Grcar

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For the synchronous generator simulation and analysis and for the power system stabilizer design and synthesis a mathematical model of synchronous generator is needed. The model has to accurately describe dynamics of oscillations, while at the same time has to be transparent enough for an analysis and sufficiently simplified for design of control system. To study the oscillations of the synchronous generator against to the rest of the power system, the model of the synchronous machine connected to an infinite bus through a transmission line having resistance and inductance is needed. In this paper, the linearized reduced order dynamic model of the synchronous generator connected to the infinite bus is presented and analysed in details. This model accurately describes dynamics of the synchronous generator only in a small vicinity of an equilibrium state. With the digression from the selected equilibrium point the accuracy of this model is decreasing considerably. In this paper, the equations’ descriptions and the parameters’ determinations for the linearized reduced order mathematical model of the synchronous generator are explained and summarized and represent the useful origin for works in the areas of synchronous generators’ dynamic behaviour analysis and synchronous generator’s control systems design and synthesis. The main contribution of this paper represents the detailed analysis of the accuracy of the linearized reduced order dynamic model in the entire synchronous generator’s operating range. Borders of the areas where the linearized reduced order mathematical model represents accurate description of the synchronous generator’s dynamics are determined with the systemic numerical analysis. The thorough eigenvalue analysis of the linearized models in the entire operating range is performed. In the paper, the parameters of the linearized reduced order dynamic model of the laboratory salient poles synchronous generator were determined and used for the analysis. The theoretical conclusions were confirmed with the agreement of experimental and simulation results.

Keywords: eigenvalue analysis, mathematical model, power system stability, synchronous generator

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Authors: Han Bing, Yin Zhenjie

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In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.

Keywords: fault prediction, neural network, GM(1, 5) genetic algorithm, GBPGA

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Authors: Esubalew Yehualaw Melaku, Tizazu Abeza

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ZnSe thin films in an aqueous solution of zinc acetate and hydrazine hydrate (HH) using the non-toxic complexing agent EDTA along with the films were annealed at 200, 300, and 400oC. This research aimed to investigate the effect of annealing on the structural, optical, and electrical properties of the films. X-ray diffraction (XRD) analysis was used to study the structure and crystallite size of the ZnSe thin film. The ZnSe thin films are annealed in an oven at various temperatures which are characterized by structural and optical properties. An increase in annealing temperature distorted the nanocrystillinity and made the ZnSe thin films amorphous. The variation of resistivity indicates the semiconducting nature of the thin film. The electrical resistivity of the films decreases with increasing annealing temperature. In this study, the Band gap of ZnSe decreases from 2.8eV to 2.65eV with the increase in temperature and decreases for as-deposited to 2.5eV. As a result of this research, ZnSe is used for certain applications; it has been widely utilized in various optoelectronic devices such as thin film solar cells, green-blue light emitting diodes, lasers, photo-luminescent, and electro-luminescent devices.

Keywords: chemical bath deposition, ZnSe thin film, band gap, solar cells

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Authors: Vladimir A. Todiras

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Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

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Authors: Sh. Hamada

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The current work aims to study the rainbow like-structure observed in the elastic scattering of alpha particles on both ¹²C and ¹⁶O nuclei. We reanalyzed the experimental elastic scattering angular distributions data for α+¹²C and α+¹⁶O nuclear systems at different energies using both optical model and double folding potential of different interaction models such as: CDM3Y1, DDM3Y1, CDM3Y6 and BDM3Y1. Potential created by BDM3Y1 interaction model has the shallowest depth which reflects the necessity to use higher renormalization factor (N_r). Both optical model and double folding potential of different interaction models fairly reproduce the experimental data.

Keywords: density distribution, double folding, elastic scattering, nuclear rainbow, optical model

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Authors: Osei Kwabena Brefo

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The Germany takeover regulations mandate the minimum offer price to be set in accordance with section 31 (1) of the WpÜG. To safeguard this right of the shareholders, the WpÜG contains minimum price regulations that are based on the fundamental principle of equal treatment of shareholders. The minimum offer price is determined based on the maximum of either the highest price the bidder has offered other shareholders within the last six months (§ 4 WpÜG) or the three-month weighted average stock price (§ 5 Abs. 1 WpÜG) before the announcement of the offer. This study provides the first empirical evidence on differences between setting the minimum offer price based on the highest price paid to another shareholder within the last six months (“6MH offers”) as against the three-month weighted average stock before the announcement of the offer (“VWAP offers”) in terms of their impact on acquisition outcome. Using a sample of 358 acquisitions announced between 2004 and 2023, the study finds that the market and legal minimum premium in 6MH offers are significantly lower than three-month weighted average stock price offers. The study also employed Propensity Score Matching and endogenous Linear regression model to address for endogeneity concerns. Consistent with the Ordinary Least Square estimation, the study finds that after controlling for self-selection bias, market and legal premiums in 6MH offers are significantly lower than VWAP offers.

Keywords: mergers and acquisition, offer premium, minimum price regulation, takeover regulation

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Authors: Anil Ranjitbhai Patel, Clement John Shaji, Peter Liggesmeyer

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Safety and security of autonomous vehicles (AVs) is a growing concern, first, due to the increased number of safety-critical functions taken over by automotive embedded systems; second, due to the increased exposure of the software-intensive systems to potential attackers; third, due to dynamic interaction in an uncertain and unknown environment at runtime which results in changed functional and non-functional properties of the system. Frequently occurring environmental uncertainties, random component failures, and compromise security of the AVs might result in hazardous events, sometimes even in an accident, if left undetected. Beyond these technical issues, we argue that the safety and security of AVs against accidental and deliberate faults are poorly understood and rarely implemented. One possible way to overcome this is through a well-known diversity approach. As an effective approach to increase safety and security, diversity has been widely used in the aviation, railway, and aerospace industries. Thus, the paper proposes fault-tolerance by diversity model takes into consideration the mitigation of accidental and deliberate faults by application of structure and variant redundancy. The model can be used to design the AVs with various types of diversity in hardware and software-based multi-version system. The paper evaluates the presented approach by employing an example from adaptive cruise control, followed by discussing the case study with initial findings.

Keywords: autonomous vehicles, diversity, fault-tolerance, adaptive cruise control, safety, security

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Authors: Maryam Ghareh Chaei, Masuzyo Chilwesa, Ali Akbarnezhad, Arnaud Castel, Redmond Lloyd, Stephen Foster

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Cement hydration is an exothermic chemical reaction generally leading to a rise in concrete’s temperature. This internal heating of concrete may, in turn, lead to a temperature difference between the hotter interior and the cooler exterior of concrete and thus differential thermal stresses in early ages which could be particularly significant in mass concrete. Such differential thermal stresses result in early age thermal cracking of concrete when exceeding the concrete’s tensile strength. The extent of temperature rise and thus early age differential thermal stresses is generally a function of hydration heat intensity, thermal properties of concrete and size of the concrete element. Both hydration heat intensity and thermal properties of concrete may vary considerably with variations in the type cementitious materials and other constituents. With this in mind, partial replacement of cement with supplementary cementitious materials including fly ash and ground granulated blast furnace slag has been investigated widely as an effective strategy to moderate the heat generation rate and thus reduce the risk of early age thermal cracking of concrete. However, there is currently a lack of adequate literature on effect of partial replacement of cement with fly ash and/or ground granulated blast furnace slag on the thermal properties of concrete. This paper presents the results of an experimental conducted to evaluate the effect of addition of varying percentages of fly ash (up to 60%) and ground granulated blast furnace slag (up to 50%) on the heat capacity and thermal conductivity of early age cement paste. The water to cementitious materials ratio is kept 0.45 for all the paste samples. The results of the experimental studies were used in a numerical analysis performed using Comsol Multiphysics to highlight the effects of variations in the thermal properties of concrete, due to variations in the type of aggregate and content of supplemenraty cementitious materials, on the risk of early age cracking of a concrete raft.

Keywords: thermal diffusivity, early age thermal cracking, concrete, supplementary cementitious materials

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Authors: Kumaran Letchmanan, Shou-Cang Shen, Wai Kiong Ng

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Postoperative implant-associated infections in soft tissues and bones remain a serious complication in orthopaedic surgery, which leads to impaired healing, re-implantation, prolong hospital stay and increase cost. Drug-loaded implants with sustained release of antibiotics at the local site are current research interest to reduce the risk of post-operative infections and osteomyelitis, thus, minimize the need for follow-up care and increase patient comfort. However, the improved drug release of the drug-loaded bone cements is usually accompanied by a loss in mechanical strength, which is critical for weight-bearing bone cement. Recently, more attempts have been undertaken to develop techniques to enhance the antibiotic elution as well as preserve the mechanical properties of the bone cements. The present study investigates the potential influence of addition of mesoporous silica nanoparticles (MSN) on the in vitro drug release kinetics of gentamicin (GTMC), along with the mechanical properties of bone cements. Simplex P was formulated with MSN and loaded with GTMC by direct impregnation. Meanwhile, Simplex P with water soluble poragen (xylitol) and high loading of GTMC as well as commercial bone cement CMW Smartset GHV were used as controls. MSN-formulated bone cements are able to increase the drug release of GTMC by 3-fold with a cumulative release of more than 46% as compared with other control groups. Furthermore, a sustained release could be achieved for two months. The loaded nano-sized MSN with uniform pore channels significantly build up an effective nano-network path in the bone cement facilitates the diffusion and extended release of GTMC. Compared with formulations using xylitol and high GTMC loading, incorporation of MSN shows no detrimental effect on biomechanical properties of the bone cements as no significant changes in the mechanical properties as compared with original bone cement. After drug release for two months, the bending modulus of MSN-formulated bone cements is 4.49 ± 0.75 GPa and the compression strength is 92.7 ± 2.1 MPa (similar to the compression strength of Simplex-P: 93.0 ± 1.2 MPa). The unaffected mechanical properties of MSN-formulated bone cements was due to the unchanged microstructures of bone cement, whereby more than 98% of MSN remains in the matrix and supports the bone cement structures. In contrast, the large portions of extra voids can be observed for the formulations using xylitol and high drug loading after the drug release study, thus caused compressive strength below the ASTM F541 and ISO 5833 minimum of 70 MPa. These results demonstrate the potential applicability of MSN-functionalized poly(methyl methacrylate)-based bone cement as a highly efficient, sustained and local drug delivery system with good mechanical properties.

Keywords: antibiotics, biomechanical properties, bone cement, sustained release

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Authors: Julian Thrash, Douglas Folk, Michael Ciracy, Audrey C. Tseng, Kristen M. Stromsodt, Amber Younggren, Christopher Maciolek

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The cardiopulmonary system is comprised of the heart, lungs, and many dynamic feedback mechanisms that control its function based on a multitude of variables. The next generation of cardiopulmonary medical devices will involve adaptive control and smart pacing techniques. However, testing these smart devices on living systems may be unethical and exceedingly expensive. As a solution, a comprehensive computational model of the cardiopulmonary system was implemented in Simulink. The model contains over 240 state variables and over 100 equations previously described in a series of published articles. Simulink was chosen because of its ease of introducing machine learning elements. Initial results indicate that physiologically correct waveforms of pressures and volumes were obtained in the simulation. With the development of a comprehensive computational model, we hope to pioneer the future of predictive medicine by applying our research towards the initial stages of smart devices. After validation, we will introduce and train reinforcement learning agents using the cardiopulmonary model to assist in adaptive control system design. With our cardiopulmonary model, we will accelerate the design and testing of smart and adaptive medical devices to better serve those with cardiovascular disease.

Keywords: adaptive control, cardiopulmonary, computational model, machine learning, predictive medicine

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Authors: Chi-Chung Marven Chick, Chu-Po Ho, Sau-Chuen Joe Au, Wing-Fai Sidney Wong, Chi-Wai Kan

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Recently, 3D printing becomes popular process for manufacturing, especially has special attention in textile applications. However, there are various types of 3D printing materials, including plastic, resin, rubber, ceramics, gold, platinum, silver, iron, titanium but not all these materials are suitable for textile application. Generally speaking, 3D printing of textile mainly uses thermoplastic polymers such as acrylonitrile butadiene styrene (ABS), polylactide (PLA), polycaprolactone (PCL), thermoplastic polyurethane (TPU), polyethylene terephthalate glycol-modified (PETG), polystyrene (PS), polypropylene (PP). Due to the characteristics of the polymers, 3D printed textiles usually have low air permeability and poor comfortable. Therefore, in this paper, we will review the possible materials suitable for textile application with desired physical and mechanical properties.

Keywords: 3D printing, 3D printing materials, textile, properties

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Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

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A Functional Model to mimic the functional correctness of a Neural Network Compute Accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of gcc compilers to BF-16 datatype, which we addressed with a native BF-16 generator integrated to our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex Neural Network Accelerator design by proposing a Functional Model-based scoreboard or Software model using SystemC. The proposed Functional Model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT bringing up micro-steps of execution.

Keywords: ISA (instruction set architecture), NN (neural network), TLM (transaction-level modeling), GEMM (general matrix multiplication)

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Authors: Siti Hasnah Kamarudin, Luqman Chuah Abdullah, Min Min Aung, Chantara Thevy Ratnam

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The primary objective of this work was to develop fully nanocomposite material based on poly(lactic acid), epoxidized jatropha oil (EJO) and nanocrystalline cellulose. EJO was investigated as a sustainable alternative to petrochemical-based plasticizers to reinforce the ductility and toughness of plastics, in this case, nanocellulose/poly(lactic acid) (PLA). The EJO was melt blended into nanocellulose/PLA at concentrations from 1 wt% to 5 wt%. The blends were then hot-pressed into sheets to characterize their mechanical and physical properties. Microcrystalline cellulose had been converted to nanocrystalline cellulose by acid mercerisation technique and the effects thereof on the composites’ tensile, flexural, and impact properties, as well as their water absorption and density, were studied. The impact strengths of the nanocomposites were improved with the addition of NCC up to 0.5 wt%, with a maximum over 10 times that of the neat PLA. The flexural strength and modulus increased 4% and 50%, respectively, for NCC/PLA plasticized with EJO. This increase demonstrated the nanocrystalline cellulose addition gave notable improvements to the composites’ properties. Furthermore, analysis by scanning electron microscopy (SEM) of the nanocomposites’ tensile fracture surfaces indicated better interaction adhesion of the NCC/PLA plasticized with EJO compared with the PLA/EJO composites.

Keywords: nanocrystalline cellulose, nanocomposite, poly (lactic acid), epoxidised jatropha oil

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Authors: Renata Swislocka, Grzegorz Swiderski, Agata Jablonska-Trypuc, Wlodzimierz Lewandowski

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Forming a complex of a phenolic compound with a metal not only alters the physicochemical properties of the ligand (including increase in stability or changes in lipophilicity), but also its biological activity, including antioxidant, antimicrobial and many others. As part of our previous projects, we examined the physicochemical and antimicrobial properties of phenolic acids and their complexes with metals naturally occurring in foods. Previously we studied the complexes of manganese(II), copper(II), cadmium(II) and alkali metals with ferulic, caffeic and p-coumaric acids. In the framework of this study, the physicochemical and biological properties of cicoric acid, its sodium salt, and complexes with copper and zinc were investigated. Cichoric acid is a derivative of both caffeic acid and tartaric acid. It has first been isolated from Cichorium intybus (chicory) but also it occurs in significant amounts in Echinacea, particularly E. purpurea, dandelion leaves, basil, lemon balm and in aquatic plants, including algae and sea grasses. For the study of spectroscopic and biological properties of cicoric acid, its sodium salt, and complexes with zinc and copper a variety of methods were used. Studies of antioxidant properties were carried out in relation to selected stable radicals (method of reduction of DPPH and reduction of FRAP). As a result, the structure and spectroscopic properties of cicoric acid and its complexes with selected metals in the solid state and in the solutions were defined. The IR and Raman spectra of cicoric acid displayed a number of bands that were derived from vibrations of caffeic and tartaric acids moieties. At 1746 and 1716 cm-1 the bands assigned to the vibrations of the carbonyl group of tartaric acid occurred. In the spectra of metal complexes with cichoric these bands disappeared what indicated that metal ion was coordinated by the carboxylic groups of tartaric acid. In the spectra of the sodium salt, a characteristic wide-band vibrations of carboxylate anion occurred. In the spectra of cicoric acid and its salt and complexes, a number of bands derived from the vibrations of the aromatic ring (caffeic acid) were assigned. Upon metal-ligand attachment, the changes in the values of the wavenumbers of these bands occurred. The impact of metals on the antioxidant properties of cicoric acid was also examined. Cichoric acid has a high antioxidant potential. Complexation by metals (zinc, copper) did not significantly affect its antioxidant capacity. The work was supported by the National Science Centre, Poland (grant no. 2015/17/B/NZ9/03581).

Keywords: chicoric acid, metal complexes, natural antioxidant, phenolic acids

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Authors: Li Chen, Alex Skvortsov, Chris Norwood

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Gas releasing into water can be found in for many industrial situations. This process results in the formation of bubbles and acoustic emission which depends upon the bubble characteristics. If the bubble creation rates (bubble volume flow rate) are of interest, an inverse method has to be used based on the measurement of acoustic emission. However, there will be sound attenuation through the bubbly plume which will influence the measurement and should be taken into consideration in the model. The sound transmission through the bubbly plume depends on the characteristics of the bubbly plume, such as the shape and the bubble distributions. In this study, the bubbly plume shape is modelled using a self-similarity model, which has been normally applied for a single phase buoyant plume. The prediction is compared with the experimental data. It has been found the model can be applied to a buoyant plume of gas-liquid mixture. The influence of the gas flow rate and discharge nozzle size is studied.

Keywords: bubbly plume, buoyant plume, bubble acoustics, self-similarity model

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Authors: B. Gueridi, T. Chihi, M. Fatmi, A. Faci

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Some fundamental physical properties of BiGaO₃ were investigated under pressure and temperature effect using generalized gradient approximation and local density approximation approaches. The effect of orientation on Debye temperature and sound waves velocities were estimated from elastic constants. The value of the bulk modulus of BiGaO₃ is a sign of its high hardness because it is linked to an isotropic deformation. BiGaO₃ is a semiconductor and ductile material with covalent bonding (Ga–O), and the Bi-O bonding is ionic. The optical transitions were observed when electrons pass from the top of the valence band (O-2p) to the bottom of the conduction band (Ga-4p or Bi-6p). The thermodynamic parameters are determined in temperature and pressure ranging from 0 to 1800 K and 0 to 50 GPa.

Keywords: BiGaO₃ perovskite, optical absorption, first principle, band structure

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Authors: Vidhu Mitha Goutham, Ruma Mukherjee

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The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.

Keywords: attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation

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Authors: S. Benzitouni, M. Zaabat, A. Mahdjoub, A. Benaboud, T.Saidani ‎

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To improve the physical properties of ZnO nanostructures textured (103) by sol-gel ‎dip coating method, Al and In are used as dopant with different weight ratios (5%, 10%). ‎The comparative study between Al doped ZnO thin films (AZO) and In doped ZnO (IZO) ‎are made by different analysis technic. XRD showed that the films are Pollycristallins with ‎hexagonal wûrtzite structure and preferred orientation (002) and (103). UV-Vis ‎spectroscopy showed that all films have a high transmission (> 85%); the interference ‎fringes are only observed for IZO. The optical gap is reduced due to the introduction of In ‎‎(minimum value is 3.12 eV), but increased in the presence of Al (maximum value is 3.34 ‎eV). The thickness of the layers was obtained by modeling (using Forouhi Bloomer ‎method). AFM used to observe the surface texture of the films and determined grain size ‎and surface roughness (RMS) which varies in a small range [3.14 to 1.25] nm‎.

Keywords: ZnO, optical gap, roughness (RMS), nanostructures‎

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Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

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River is the main source of water. It is a form of natural open channel which gives rise to many complex phenomenon of sciences that needs to be tackled such as the critical flow conditions, boundary shear stress and depth averaged velocity. The development of society more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, Conveyance Estimation System (CES) software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel and the results are compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth , velocity distribution

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Authors: Jin Gang Lee, Hyun-Soo Lee, Moonseo Park

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The utilization of BIM and IFC allows project participants to collaborate across different areas by consistently sharing interoperable product information represented in a model. Comments or markups generated during the coordination process can be categorized as communication information, which can be shared in less standardized manner. It can be difficult to manage and reuse such information compared to the product information in a model. The present study proposes an interoperable coordination method using BCF (the BIM Collaboration Format) for managing and sharing the communication information during BIM based coordination process. A management function for coordination in the BIM collaboration system is developed to assess its ability to share the communication information in BIM collaboration projects. This approach systematically links communication information during the coordination process to the building model and serves as a type of storage system for retrieving knowledge created during BIM collaboration projects.

Keywords: design coordination, building information model, BIM collaboration format, industry foundation classes

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Authors: Allé Dieng, Mamadou Bousso, Latif Dramani

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The purpose of this work is to show the complexity behind economical interrelations in a country and provide a linear dynamic model of economical dependency evolution in a country. The model is based on National Transfer Account which is one of the most robust methodology developed in order to measure a level of demographic dividend captured in a country. It is built upon three major factors: demography, economical dependency and migration. The established mathematical model has been simulated using Netlogo software. The innovation of this study is in describing economical dependency as a complex system and simulating using mathematical equation the evolution of the two populations: the economical dependent and the non-economical dependent as defined in the National Transfer Account methodology. It also allows us to see the interactions and behaviors of both populations. The model can track individual characteristics and look at the effect of birth and death rates on the evolution of these two populations. The developed model is useful to understand how demographic and economic phenomenon are related

Keywords: ABM, demographic dividend, National Transfer Accounts (NTA), ODE

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Authors: Nuray Yılmaz Baran

Abstract:

The conjugated Schiff base polymers which are also called as polyazomethines are promising materials for various applications due to their good thermal resistance semiconductive, liquid crystal, fiber forming, nonlinear optical outstanding photo- and electroluminescence and antimicrobial properties. In recent years, polyazomethines have attracted intense attention of researchers especially due to optoelectronic properties which have made its usage possible in organic light emitting diodes (OLEDs), solar cells (SCs), organic field effect transistors (OFETs), and photorefractive holographic materials (PRHMs). In this study, N-(pyridin-2-ylmethylidene)pyridin-2-amine Schiff base was synthesized from condensation reaction of 2-aminopyridine with 2-pyridine carbaldehyde. Polymerization of Schiff base was achieved by polycondensation reaction using NaOCl oxidant in methanol medium at various time and temperatures. The synthesized Schiff base monomer and polymer (Poly(N-(pyridin-2-ylmethylidene)pyridin-2-amine)) was characterized by UV-vis, FT-IR, 1H-NMR, XRD techniques. Molecular weight distribution and the surface morphology of the polymer was determined by GPC and SEM-EDAX techniques. Thermal behaviour of the monomer and polymer was investigated by TG/DTG, DTA and DSC techniques.

Keywords: polyazomethines, polycondensation reaction, Schiff base polymers, thermal stability

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Authors: Basil Manos, Parthena Chatzinikolaou, Fedra Kiomourtzi

Abstract:

This paper presents a Multicriteria Mathematical Programming model for farm planning and sustainable optimization of agricultural production. The model can be used as a tool for the analysis and simulation of agricultural production plans, as well as for the study of impacts of various measures of Common Agriculture Policy in the member states of European Union. The model can achieve the optimum production plan of a farm or an agricultural region combining in one utility function different conflicting criteria as the maximization of gross margin and the minimization of fertilizers used, under a set of constraints for land, labor, available capital, Common Agricultural Policy etc. The proposed model was applied to the region of Larisa in central Greece. The optimum production plan achieves a greater gross return, a less fertilizers use, and a less irrigated water use than the existent production plan.

Keywords: sustainable optimization, multicriteria analysis, agricultural production, farm planning

Procedia PDF Downloads 606

Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

Abstract:

Many quality models have been used to measure e-government portals quality. However, the absence of an international consensus for e-government portals quality models results in many differences in terms of quality attributes and measures. The aim of this paper is to compare and analyze the existing e-government quality models proposed in literature (those that are based on ISO standards and those that are not) in order to propose guidelines to build a good and useful e-government portals quality model. Our findings show that, there is no e-government portal quality model based on the new international standard ISO 25010. Besides that, the quality models are not based on a best practice model to allow agencies to both; measure e-government portals quality and identify missing best practices for those portals.

Keywords: e-government, portal, best practices, quality model, ISO, standard, ISO 25010, ISO 9126

Procedia PDF Downloads 562

Authors: Krishang Surapaneni

Abstract:

The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

Procedia PDF Downloads 78