Search results for: kinetic models

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

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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

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Authors: Saeed Vahedikamal, Ian Hepburn

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Microwave Kinetic Inductance Detectors (MKIDs) are considered as one of the most promising photon detectors of the future in many Astronomical applications such as exoplanet detections. The MKID advantages stem from their single photon sensitivity (ranging from UV to optical and near infrared), photon energy resolution and high temporal capability (~microseconds). There has been substantial progress in the development of these detectors and MKIDs with Megapixel arrays is now possible. The unique capability of recording an incident photon and its energy (or wavelength) while also registering its time of arrival to within a microsecond enables an array of MKIDs to produce a four-dimensional data block of x, y, z and t comprising x, y spatial, z axis per pixel spectral and t axis per pixel which is temporal. This offers the possibility that the spectrum and brightness variation for any detected piece of space debris as a function of time might offer a unique identifier or fingerprint. Such a fingerprint signal from any object identified in multiple detections by different observers has the potential to determine the orbital features of the object and be used for their tracking. Modelling performed so far shows that with a 20 cm telescope located at an Astronomical observatory (e.g. La Palma, Canary Islands) we could detect sub cm objects at GEO. By considering a Lambertian sphere with a 10 % reflectivity (albedo of the Moon) we anticipate the following for a GEO object: 10 cm object imaged in a 1 second image capture; 1.2 cm object for a 70 second image integration or 0.65 cm object for a 4 minute image integration. We present details of our modelling and the potential instrument for a dedicated GEO surveillance system.

Keywords: space debris, orbital debris, detection system, observation, microwave kinetic inductance detectors, MKID

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Authors: Ayman Aboelkassem, Mahmoud Ali

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Introduction: The models of soul houses have appeared in the prehistory, old kingdom and middle kingdom period. These soul houses represented the imagination of the deceased about his house in the afterlife, some of these soul houses were two floors and the study will examine five models of soul houses which were discovered near Saqqara site by an Egyptian mission. These models had been transferred to The Grand Egyptian Museum (GEM) to be ready to display at the new museum. We focus on models of soul houses (GEM Numbers, 1276, 1280, 1281, 1282, 8711) these models of soul houses were related to the old kingdom period. These models were all made of pottery, the five models have an oval shape and were decorated with relief. Methodology: The study will focus on the development of soul houses during the different periods in ancient Egypt, the function of soul houses, the kind of offerings which were put in it and the symbolism of the offerings colors in ancient Egyptian believe. Conclusion: This study is useful for the heritage and ancient civilizations especially when we talk about opening new museums like The Grand Egyptian Museum which will display a new collection of soul houses. The study of soul houses and The kinds of offerings which put in it reflect the economic situation in the Egyptian society and kinds of oils which were famous in ancient Egypt.

Keywords: archaeology study, Grand Egyptian Museum, relief, soul houses

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Hamid Rezaei, Xiaotao Bi, C. Jim Lim, Anthony Lau, Shahab Sokhansanj

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A one-dimensional heat transfer model coupled with the kinetic information has been used to predict the overall pyrolysis mass loss of a single wood particle. The kinetic parameters were determined experimentally and the regime and characteristics of the conversion were evaluated in terms of the particle size and reactor temperature. The order of overall mass loss changed from n=1 at temperatures lower than 350 °C to n=0.5 at temperatures higher that 350 °C. Conversion time analysis showed that particles larger than 0.5 mm were controlled by internal thermal resistances. The valid range of particle size to use the simplified lumped model depends on the fluid temperature around the particles. The critical particle size was 0.6-0.7 mm for the fluid temperature of 500 °C and 0.9-1.0 mm for the fluid temperature of 100 °C. Experimental pyrolysis of moist particles did not show distinct drying and pyrolysis stages. The process was divided into two hypothetical drying and pyrolysis dominated zones and empirical correlations are developed to predict the rate of mass loss in each zone.

Keywords: pyrolysis, kinetics, model, single particle

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Authors: I. Behroyan, P. Ganesan, S. He, S. Sivasankaran

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This study compares the predictions of five types of Computational Fluid Dynamics (CFD) models, including two single-phase models (i.e. Newtonian and non-Newtonian) and three two-phase models (Eulerian-Eulerian, mixture and Eulerian-Lagrangian), to investigate turbulent forced convection of Cu-water nanofluid in a tube with a constant heat flux on the tube wall. The Reynolds (Re) number of the flow is between 10,000 and 25,000, while the volume fraction of Cu particles used is in the range of 0 to 2%. The commercial CFD package of ANSYS-Fluent is used. The results from the CFD models are compared with results from experimental investigations from literature. According to the results of this study, non-Newtonian single-phase model, in general, does not show a good agreement with Xuan and Li correlation in prediction of Nu number. Eulerian-Eulerian model gives inaccurate results expect for φ=0.5%. Mixture model gives a maximum error of 15%. Newtonian single-phase model and Eulerian-Lagrangian model, in overall, are the recommended models. This work can be used as a reference for selecting an appreciate model for future investigation. The study also gives a proper insight about the important factors such as Brownian motion, fluid behavior parameters and effective nanoparticle conductivity which should be considered or changed by the each model.

Keywords: heat transfer, nanofluid, single-phase models, two-phase models

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Authors: Constantinos Vayenas, Athanasios Fokas, Dimitrios Grigoriou

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We use special relativity to compute the inertial and thus gravitational mass of relativistic electron and muon neutrinos, and we find that, for neutrino kinetic energies above 150 MeV/c2, these masses are in the Planck mass range. Consequently, we develop a simple Bohr-type model using gravitational rather than electrostatic forces between the rotating neutrinos as the centripetal force in order to examine the bound rotational states formed by two or three such relativistic neutrinos. We find that the masses of the composite rotational structures formed, are in the meson and baryon mass ranges, respectively. These models contain no adjustable parameters and by comparing their predictions with the experimental values of the masses of protons and pions, we compute a mass of 0.0437 eV/c2 for the heaviest electron neutrino mass and of 1.1 x10-3 eV/c2 for the heaviest muon neutrino mass.

Keywords: geons, gravitational confinement, neutrino masses, special relativity

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Mayuresh Thombre, Prajyot Borkar, Mangirish Bhobe

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New advancement of technology and never satisfying demands of the civilization are putting huge pressure on the natural fuel resources and these resources are at a constant threat to its sustainability. To get the best out of the automobile, the optimum balance between performance and fuel economy is important. In the present state of art, either of the above two aspects are taken into mind while designing and development process which puts the other in the loss as increase in fuel economy leads to decrement in performance and vice-versa. In-depth observation of the vehicle dynamics apparently shows that large amount of energy is lost during braking and likewise large amount of fuel is consumed to reclaim the initial state, this leads to lower fuel efficiency to gain the same performance. Current use of Kinetic Energy Recovery System is only limited to sports vehicles only because of the higher cost of this system. They are also temporary in nature as power can be squeezed only during a small time duration and use of superior parts leads to high cost, which results on concentration on performance only and neglecting the fuel economy. In this paper Kinetic Energy Recovery System for storing the power and then using the same while accelerating has been discussed. The major storing element in this system is a Flat Spiral Spring that will store energy by compression and torsion. The use of spring ensure the permanent storage of energy until used by the driver unlike present mechanical regeneration system in which the energy stored decreases with time and is eventually lost. A combination of internal gears and spur gears will be used in order to make the energy release uniform which will lead to safe usage. The system can be used to improve the fuel efficiency by assisting in overcoming the vehicle’s inertia after braking or to provide instant acceleration whenever required by the driver. The performance characteristics of the system including response time, mechanical efficiency and overall increase in efficiency are demonstrated. This technology makes the KERS (Kinetic Energy Recovery System) more flexible and economical allowing specific application while at the same time increasing the time frame and ease of usage.

Keywords: electric control unit, energy, mechanical KERS, planetary gear system, power, smart braking, spiral spring

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Authors: Farida Kaouah, Chahida Oussalah, Wassila Hachi, Salim Boumaza, Mohamed Trari

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A catalyst of ZnO nanoparticles was used in the photocatalytic process of treatment for potential use towards bisphenol A (BPA) degradation in an aqueous solution. To achieve this study, the effect of parameters such as the catalyst dose, initial concentration of BPA and pH on the photocatalytic degradation of BPA was studied. The results reveal that the maximum degradation (more than 93%) of BPA occurred with ZnO catalyst in 120 min of stirring at natural pH (7.1) under solar light irradiation. It was found that chemical oxygen demand (COD) reduction takes place at a faster rate under solar light as compared to that of UV light. The kinetic studies were achieved and revealed that the photocatalytic degradation process obeyed a Langmuir–Hinshelwood model and followed a pseudo-first order rate expression. This work envisages the great potential that sunlight mediated photocatalysis has in the removal of bisphenol A from wastewater.

Keywords: bisphenol A, photocatalytic degradation, sunlight, zinc oxide, Langmuir–Hinshelwood model, chemical oxygen demand

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Authors: Vinh Duy Cao, Carlos Salas-Bringas, Anna M. Szczotok, Marianne Hiorth, Anna-Lena Kjøniksen

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The increasing cost of energy supply for the purposes of heating and cooling creates a demand for more energy efficient buildings. Improved construction techniques and enhanced material technology can greatly reduce the energy consumption needed for the buildings. Microencapsulated phase change materials (MPCM) suspensions utilized as heat transfer fluids for energy storage and heat transfer applications provide promising potential solutions. A full understanding of the flow and thermal characteristics of microcapsule suspensions is needed to optimize the design of energy storage systems, in order to reduce the capital cost, system size, and energy consumption. The MPCM suspensions exhibited pseudoplastic and thixotropic behaviour, and significantly improved the thermal performance of the suspensions. Three different models were used to characterize the thixotropic behaviour of the MPCM suspensions: the second-order structural, kinetic model was found to give a better fit to the experimental data than the Weltman and Figoni-Shoemaker models. For all samples, the initial shear stress increased, and the breakdown rate accelerated significantly with increasing concentration. The thermal performance and rheological properties, especially the selection of rheological models, will be useful for developing the applications of microcapsules as heat transfer fluids in thermal energy storage system such as calculation of an optimum MPCM concentration, pumping power requirement, and specific power consumption. The effect of temperature on the shear thinning properties of the samples suggests that some of the phase change material is located outside the capsules, and contributes to agglomeration of the samples.

Keywords: latent heat, microencapsulated phase change materials, pseudoplastic, suspension, thixotropic behaviour

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Authors: Tai-Yue Wang, Yi-Ho Chen

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In this study, we investigate a two-echelon supply chain with two suppliers and three retailers among which one retailer dominates other retailers. A price competition demand function is used to model this dominant retailer, which is leading market. The promotion strategies and negotiation schemes are integrated to form decision-making models under different scenarios. These models are then formulated into different mathematical programming models. The decision variables such as promotional costs, retailer prices, wholesale price, and order quantity are included in these models. At last, the distributions of promotion costs under different cost allocation strategies are discussed. Finally, an empirical example used to validate our models. The results from this empirical example show that the profit model will create the largest profit for the supply chain but with different profit-sharing results. At the same time, the more risk a member can take, the more profits are distributed to that member in the utility model.

Keywords: supply chain, price promotion, mathematical models, dominant retailer

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Authors: Mohammad Anwar, Shah Waliullah

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This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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Authors: K. Verma, v. S. Moholkar

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In developed countries, water pollution caused by industrial discharge has emerged as a significant environmental concern over the past decades. However, despite ongoing efforts, a fully effective and sustainable remediation strategy has yet to be identified. This paper describes how enzymatic and sonochemical treatments have demonstrated great promise in degrading bio-refractory pollutants. Mainly, a compelling area of interest lies in the combined technique of sono-enzymatic treatment, which has exhibited a synergistic enhancement effect surpassing that of the individual techniques. This study employed the covalent attachment method to immobilize Laccase from Trametes versicolor onto amino-functionalized magnetic Fe₃O₄ nanoparticles. To comprehensively characterize the synthesized free nanoparticles and the laccase-immobilized nanoparticles, various techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), vibrating sample magnetometer (VSM), and surface area through Brunauer-Emmett-Teller (BET) were employed. The size of immobilized Fe₃O₄@Laccase was found to be 60 nm, and the maximum loading of laccase was found to be 24 mg/g of nanoparticle. An investigation was conducted to study the effect of various process parameters, such as immobilized Fe₃O₄ Laccase dose, temperature, and pH, on the % Chemical oxygen demand (COD) removal as a response. The statistical design pinpointed the optimum conditions (immobilized Fe₃O₄ Laccase dose = 1.46 g/L, pH = 4.5, and temperature = 66 oC), resulting in a remarkable 65.58% COD removal within 60 minutes. An even more significant improvement (90.31% COD removal) was achieved with ultrasound-assisted enzymatic reaction utilizing a 10% duty cycle. The investigation of various kinetic models for free and immobilized laccase, such as the Haldane, Yano, and Koga, and Michaelis-Menten, showed that ultrasound application impacted the kinetic parameters Vmax and Km. Specifically, Vmax values for free and immobilized laccase were found to be 0.021 mg/L min and 0.045 mg/L min, respectively, while Km values were 147.2 mg/L for free laccase and 136.46 mg/L for immobilized laccase. The lower Km and higher Vmax for immobilized laccase indicate its enhanced affinity towards the substrate, likely due to ultrasound-induced alterations in the enzyme's confirmation and increased exposure of active sites, leading to more efficient degradation. Furthermore, the toxicity and Liquid chromatography-mass spectrometry (LC-MS) analysis revealed that after the treatment process, the wastewater exhibited 70% less toxicity than before treatment, with over 25 compounds degrading by more than 75%. At last, the prepared immobilized laccase had excellent recyclability retaining 70% activity up to 6 consecutive cycles. A straightforward manufacturing strategy and outstanding performance make the recyclable magnetic immobilized Laccase (Fe₃O₄ Laccase) an up-and-coming option for various environmental applications, particularly in water pollution control and treatment.

Keywords: kinetic, laccase enzyme, sonoenzymatic, ultrasound irradiation

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Authors: Y. Laidani, G. Henini, S. Hanini, A. Labbaci, F. Souahi

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In this study, pomegranate skin, a material suitable for the conditions in Algeria, was chosen as adsorbent material for removal of lead in an aqueous solution. Biosorption studies were carried out under various parameters such as mass adsorbent particle, pH, contact time, the initial concentration of metal, and temperature. The experimental results show that the percentage of biosorption increases with an increase in the biosorbent mass (0.25 g, 0.035 mg/g; 1.25 g, 0.096 mg/g). The maximum biosorption occurred at pH value of 8 for the lead. The equilibrium uptake was increased with an increase in the initial concentration of metal in solution (Co = 4 mg/L, q_t = 1.2 mg/g). Biosorption kinetic data were properly fitted with the pseudo-second-order kinetic model. The best fit was obtained by the Langmuir model with high correlation coefficients (R² > 0.995) and a maximum monolayer adsorption capacity of 0.85 mg/g for lead. The adsorption of the lead was exothermic in nature (ΔH° = -17.833 kJ/mol for Pb (II). The reaction was accompanied by a decrease in entropy (ΔS° = -0.056 kJ/K. mol). The Gibbs energy (ΔG°) increased from -1.458 to -0.305 kJ/mol, respectively for Pb (II) when the temperature was increased from 293 to 313 K.

Keywords: biosorption, Pb (+II), pomegranate skin, wastewater

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Authors: O. Benturki, A. Benturki

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Activated carbon was prepared from Jujube seeds by chemical activation with potassium hydroxide (KOH), followed by pyrolysis at 800°C. Batch studies were conducted for kinetic, thermodynamic and equilibrium studies on the adsorption of phenol (P) and 2-4 dichlorophenol (2-4 DCP) from aqueous solution, than the adsorption capacities followed the order of 2-4 dichlorophenol > phenol. The operating variables studied were initial phenols concentration, contact time, temperature and solution pH. Results show that the pH value of 7 is favorable for the adsorption of phenols. The sorption data have been analyzed using Langmuir and Freundlich isotherms. The isotherm data followed Langmuir Model. The adsorption processes conformed to the pseudo-second-order rate kinetics. Thermodynamic parameters such as enthalpy, entropy and Gibb’s free energy changes were also calculated and it was found that the sorption of phenols by Jujuba seeds activated carbon was a spontaneous process The maximum adsorption efficiency of phenol and 2-4 dichlorophenol was 142.85 mg.g−1 and 250 mg.g−1, respectively.

Keywords: activated carbon, adsorption, isotherms, Jujuba seeds, phenols, langmuir

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Authors: Padmesh Tirunelveli Narayanapillai, Joel Sharwinkumar, Gaitri Saravanan

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The biosorption of Xylenol Orange (XO) and Eriochrome Black T (EBT) from aqueous solutions by chemically activated Cocos nucifera and mango seed as a low-cost, natural, and eco-friendly biosorbents was investigated. The study for biosorption of XO and EBT was optimized by different experimental parameters, initial pH 2–7, temperature 30–60 °C, biosorbent dosage 0.1 – 0.5 g, and XO: EBT dye proportions 0 – 100 by weight %. Physicochemical characteristic studies were conducted by Fourier Transform Infrared (FTIR). The equilibrium uptake was increased with an increase in the initial dye concentrations in the solution. Biosorption kinetic data were properly fitted with the pseudo-second-order kinetic model. The experimental isotherms data were analyzed using Langmuir, Freundlich, Redlich-Peterson, and Toth isotherm equations. Thermodynamic parameters ∆Go, ∆Ho, and ∆So were calculated indicating that the biosorption of Xo and EBT dye is a spontaneous and endothermic process. The Langmuir model gave the best fit by higher correlation coefficient (R2 =0.9971) for both biosorbents at optimum circumstances as pH 3, temperature 30°C, dosage 0.5 g for chemically activated Cocos nucifera and 0.4 g for chemically activated mango seeds it assumes as monolayer adsorption. The maximum dye removal efficiency was determined as 79.75% with chemically activated mango seeds compared to chemically activated Cocos nucifera. In summary, this research work showed that chemically modified activated mango seed can be effectively used as a promising low-cost biosorbent for the removal of different XO and EBT mixed dye combinations from aqueous solutions.

Keywords: mixed dye proportions, xylenol orange and eriochrome black t, chemically activated cocos nucifera and mango seed, kinetic, isotherm and thermodynamic studies, FTIR

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Authors: Alfonso Ippolito, Cristiana Bartolomei

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A growing demand is felt today for realistic 3D models enabling the cognition and popularization of historical-artistic heritage. Evaluation and preservation of Cultural Heritage is inextricably connected with the innovative processes of gaining, managing, and using knowledge. The development and perfecting of techniques for acquiring and elaborating photorealistic 3D models, made them pivotal elements for popularizing information of objects on the scale of architectonic structures.

Keywords: cultural heritage, databases, non-contact survey, 2D-3D models

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Authors: Nichole Haag, Kimberly Velk, Tyler McCune, Chun Wu

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Methicillin/multiple-resistant Staphylococcus aureus (MRSA) are infectious bacteria that are resistant to common antibiotics. A previous in silico study in our group has identified a hypothetical protein SAV1226 as one of the potential drug targets. In this study, we reported the bioinformatics characterization, as well as cloning, expression, purification and kinetic assays of hypothetical protein SAV1226 from methicillin/vancomycin-resistant Staphylococcus aureus Mu50 strain. MALDI-TOF/MS analysis revealed a low degree of structural similarity with known proteins. Kinetic assays demonstrated that hypothetical protein SAV1226 is neither a domain of an ATP dependent dihydroxyacetone kinase nor of a phosphotransferase system (PTS) dihydroxyacetone kinase, suggesting that the function of hypothetical protein SAV1226 might be misannotated on public databases such as UniProt and InterProScan 5.

Keywords: Methicillin-resistant Staphylococcus aureus, dihydroxyacetone kinase, essential genes, drug target, phosphoryl group donor

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Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

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Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

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Authors: Giriraj Achari, Malay Bhattacharyya

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In this paper, the effectiveness of Copula Markov Switching Multifractal (MSM) models at forecasting Value-at-Risk of a two-stock portfolio is studied. The innovations are allowed to be drawn from distributions that can capture skewness and leptokurtosis, which are well documented empirical characteristics observed in financial returns. The candidate distributions considered for this purpose are Johnson-SU, Pearson Type-IV and α-Stable distributions. The two univariate marginal distributions are combined using the Student-t copula. The estimation of all parameters is performed by Maximum Likelihood Estimation. Finally, the models are compared in terms of accurate Value-at-Risk (VaR) forecasts using tests of unconditional coverage and independence. It is found that Copula-MSM-models with leptokurtic innovation distributions perform slightly better than Copula-MSM model with Normal innovations. Copula-MSM models, in general, produce better VaR forecasts as compared to traditional methods like Historical Simulation method, Variance-Covariance approach and Copula-Generalized Autoregressive Conditional Heteroscedasticity (Copula-GARCH) models.

Keywords: Copula, Markov Switching, multifractal, value-at-risk

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Authors: Elina Bakhtieva

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The variety of available digital tools, strategies and activities might confuse and disorient even an experienced marketer. This applies in particular to B2B companies, which are usually less flexible in uptaking of digital technology than B2C companies. B2B companies are lacking a framework that corresponds to the specifics of the B2B business, and which helps to evaluate a company’s capabilities and to choose an appropriate path. A B2B digital marketing maturity model helps to fill this gap. However, modern marketing offers no widely approved digital marketing maturity model, and thus, some marketing institutions provide their own tools. The purpose of this paper is building an optimized B2B digital marketing maturity model based on a SWOT (strengths, weaknesses, opportunities, and threats) analysis of existing models. The current study provides an analytical review of the existing digital marketing maturity models with open access. The results of the research are twofold. First, the provided SWOT analysis outlines the main advantages and disadvantages of existing models. Secondly, the strengths of existing digital marketing maturity models, helps to identify the main characteristics and the structure of an optimized B2B digital marketing maturity model. The research findings indicate that only one out of three analyzed models could be used as a separate tool. This study is among the first examining the use of maturity models in digital marketing. It helps businesses to choose between the existing digital marketing models, the most effective one. Moreover, it creates a base for future research on digital marketing maturity models. This study contributes to the emerging B2B digital marketing literature by providing a SWOT analysis of the existing digital marketing maturity models and suggesting a structure and main characteristics of an optimized B2B digital marketing maturity model.

Keywords: B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis

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Authors: Majdi M. Alomari, Nafesah I. Alshdaifat, Mohammad S. Widyan

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Different countries have introduced different schemes and policies to counter global warming. The rationale behind the proposed policies and the potential barriers to successful implementation of the policies adopted by the countries were analyzed and estimated based on different models. It is argued that these models enhance the transparency and provide a better understanding to the policy makers. However, these models are underpinned with several structural and baseline assumptions. These assumptions, modeling features and future prediction of emission reductions and other implication such as cost and benefits of a transition to a low-carbon economy and its economy wide impacts were discussed. On the other hand, there are potential barriers in the form political, financial, and cultural and many others that pose a threat to the mitigation options.

Keywords: energy models, environmental policy instruments, mitigating CO2 emission, economic wide impact

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Authors: Mohammadreza Kashizadeh, Mohammadamin Hashemi

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Solymorph, a kinetic building facade designed for optimal energy capture and architectural expression, is explored in this paper. The system integrates photovoltaic panels with soft robotic actuators for precise solar tracking, resulting in enhanced electricity generation compared to static facades. Driven by the growing interest in dynamic building envelopes, the exploration of novel facade systems is necessitated. Increased energy generation and regulation of energy flow within buildings are potential benefits offered by integrating photovoltaic (PV) panels as kinetic elements. However, incorporating these technologies into mainstream architecture presents challenges due to the complexity of coordinating multiple systems. To address this, Solymorph leverages soft robotic actuators, known for their compliance, resilience, and ease of integration. Additionally, the project investigates the potential for employing Large Language Models (LLMs) to streamline the design process. The research methodology involved design development, material selection, component fabrication, and system assembly. Grasshopper (GH) was employed within the digital design environment for parametric modeling and scripting logic, and an LLM was experimented with to generate Python code for the creation of a random surface with user-defined parameters. Various techniques, including casting, 3D printing, and laser cutting, were utilized to fabricate the physical components. Finally, a modular assembly approach was adopted to facilitate installation and maintenance. A case study focusing on the application of Solymorph to an existing library building at Politecnico di Milano is presented. The facade system is divided into sub-frames to optimize solar exposure while maintaining a visually appealing aesthetic. Preliminary structural analyses were conducted using Karamba3D to assess deflection behavior and axial loads within the cable net structure. Additionally, Finite Element (FE) simulations were performed in Abaqus to evaluate the mechanical response of the soft robotic actuators under pneumatic pressure. To validate the design, a physical prototype was created using a mold adapted for a 3D printer's limitations. Casting Silicone Rubber Sil 15 was used for its flexibility and durability. The 3D-printed mold components were assembled, filled with the silicone mixture, and cured. After demolding, nodes and cables were 3D-printed and connected to form the structure, demonstrating the feasibility of the design. Solymorph demonstrates the potential of soft robotics and Artificial Intelligence (AI) for advancements in sustainable building design and construction. The project successfully integrates these technologies to create a dynamic facade system that optimizes energy generation and architectural expression. While limitations exist, Solymorph paves the way for future advancements in energy-efficient facade design. Continued research efforts will focus on cost reduction, improved system performance, and broader applicability.

Keywords: artificial intelligence, energy efficiency, kinetic photovoltaics, pneumatic control, soft robotics, sustainable building

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Authors: Dražen Cvitanić, Biljana Maljković

Abstract:

This paper presents models for predicting operating speeds on tangent sections of two-lane rural roads developed on continuous speed data. The data corresponds to 20 drivers of different ages and driving experiences, driving their own cars along an 18 km long section of a state road. The data were first used for determination of maximum operating speeds on tangents and their comparison with speeds in the middle of tangents i.e. speed data used in most of operating speed studies. Analysis of continuous speed data indicated that the spot speed data are not reliable indicators of relevant speeds. After that, operating speed models for tangent sections were developed. There was no significant difference between models developed using speed data in the middle of tangent sections and models developed using maximum operating speeds on tangent sections. All developed models have higher coefficient of determination then models developed on spot speed data. Thus, it can be concluded that the method of measuring has more significant impact on the quality of operating speed model than the location of measurement.

Keywords: operating speed, continuous speed data, tangent sections, spot speed, consistency

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Authors: Cemre Polat, Dogan B. Saydam, Mustafa Soyler, Coskun Ozalp

Abstract:

In this study, the flow structure was investigated by particle imaging velocimetry (PIV) method at Re = 26000 for two different rectangular cylinders placed perpendicular and parallel to the flow direction. After obtaining streamwise and spanwise velocity data, average vorticity, streamlines, velocity magnitude, turbulence kinetic energy, root mean square of streamwise and spanwise velocity fluctuations are calculated, and critical points of flow structure are explained. As a result of the study, it was seen that the vertical configuration has less effect on the flow structure in the back region of the body compared to the horizontal configuration. When the streamwise velocity component is examined in both configurations, it is seen that the negative velocity component is stronger on the long sides compared to the short sides. It has been observed that the vertically positioned cylinder expands the flow separation point compared to the horizontally positioned cylinder; also the vertical cylinder creates an increase in turbulence kinetic energy compared to the horizontal cylinder.

Keywords: bluff body, flow characteristics, PIV, rectangular cylinder

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Authors: Razieh Arian, Hadi Adibi-Asl

Abstract:

This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine

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Authors: Horiya Boukhatem, Lila Djouadi, Hussein Khalaf, Rufino Manuel Navarro Yerga, Fernando Vaquero Gonzalez

Abstract:

Heterogeneous photo catalysis is an alternative method for the removal of organic pollutants in water. The photo excitation of a semi-conductor under ultra violet (UV) irradiation entails the production of hydroxyl radicals, one of the most oxidative chemical species. The objective of this study is the synthesis of nano materials based on montmorillonite and CuxCd1-xS with different Cu concentration (0.3 < x < 0.7) and their application in photocatalysis of a cationic dye: methylene blue. The synthesized nano materials and montmorillonite were characterized by fourier transform infrared (FTIR). Test results of photo catalysis of methylene blue under UV-Visible irradiation show that the photoactivity of nano materials montmorillonite/ CuxCd1-xS increase with the increasing of Cu concentration and it is significantly higher compared to that of sodium montmorillonite alone. The application of the kinetic model of Langmuir-Hinshelwood (L-H) to the photocatalytic test results showed that the reaction rate obeys to the first-order kinetic model.

Keywords: heterogeneous photo catalysis, methylene blue, montmorillonite, nano material

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Authors: Gokturk Memduh Ozkan, Huseyin Akilli

Abstract:

The aim of present study is to control the unsteady flow structure downstream of a circular cylinder by use of attached permeable plates. Particle image velocimetry (PIV) technique and dye visualization experiments were performed in deep water and the flow characteristics were evaluated by means of time-averaged streamlines, Reynolds Shear Stress and Turbulent Kinetic Energy concentrations. The permeable plate was made of a chrome-nickel screen having a porosity value of β=0.6 and it was attached on the cylinder surface along its midspan. Five different angles were given to the plate (θ=0°, 15°, 30°, 45°, 60°) with respect to the centerline of the cylinder in order to examine its effect on the flow control. It was shown that the permeable plate is effective on elongating the vortex formation length and reducing the fluctuations in the wake region. Compared to the plain cylinder, the reductions in the values of maximum Reynolds shear stress and Turbulent Kinetic Energy were evaluated as 72.5% and 66%, respectively for the plate angles of θ=45° and 60° which were also found to be suggested for applications concerning the vortex shedding and consequent Vortex-Induced Vibrations.

Keywords: bluff body, flow control, permeable plate, PIV, VIV, vortex shedding

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Authors: Rehab Abdulmajed, Amr Hamada, Ahmed Elsaid, Hisashi Hayakawa, Ayman Mahrous

Abstract:

Solar emissions have a high impact on the Earth’s magnetic field, and the prediction of solar events is of high interest. Various techniques have been used in the prediction of solar wind using mathematical models, MHD models, and neural network (NN) models. This study investigates the coronal hole (CH) derived high-speed streams (HSSs) and their correlation to the CH area and create a neural network model to predict the HSSs. Two different algorithms were used to compare different models to find a model that best simulates the HSSs. A dataset of CH synoptic maps through Carrington rotations 1601 to 2185 along with Omni-data set solar wind speed averaged over the Carrington rotations is used, which covers Solar cycles (sc) 21, 22, 23, and most of 24.

Keywords: artificial neural network, coronal hole area, feed-forward neural network models, solar high speed streams

Procedia PDF Downloads 56