Search results for: models synthesis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8723

Search results for: models synthesis

7343 Experimental and Numerical Investigation on the Torque in a Small Gap Taylor-Couette Flow with Smooth and Grooved Surface

Authors: L. Joseph, B. Farid, F. Ravelet

Abstract:

Fundamental studies were performed on bifurcation, instabilities and turbulence in Taylor-Couette flow and applied to many engineering applications like astrophysics models in the accretion disks, shrouded fans, and electric motors. Such rotating machinery performances need to have a better understanding of the fluid flow distribution to quantify the power losses and the heat transfer distribution. The present investigation is focused on high gap ratio of Taylor-Couette flow with high rotational speeds, for smooth and grooved surfaces. So far, few works has been done in a very narrow gap and with very high rotation rates and, to the best of our knowledge, not with this combination with grooved surface. We study numerically the turbulent flow between two coaxial cylinders where R1 and R2 are the inner and outer radii respectively, where only the inner is rotating. The gap between the rotor and the stator varies between 0.5 and 2 mm, which corresponds to a radius ratio η = R1/R2 between 0.96 and 0.99 and an aspect ratio Γ= L/d between 50 and 200, where L is the length of the rotor and d being the gap between the two cylinders. The scaling of the torque with the Reynolds number is determined at different gaps for different smooth and grooved surfaces (and also with different number of grooves). The fluid in the gap is air. Re varies between 8000 and 30000. Another dimensionless parameter that plays an important role in the distinction of the regime of the flow is the Taylor number that corresponds to the ratio between the centrifugal forces and the viscous forces (from 6.7 X 105 to 4.2 X 107). The torque will be first evaluated with RANS and U-RANS models, and compared to empirical models and experimental results. A mesh convergence study has been done for each rotor-stator combination. The results of the torque are compared to different meshes in 2D dimensions. For the smooth surfaces, the models used overestimate the torque compared to the empirical equations that exist in the bibliography. The closest models to the empirical models are those solving the equations near to the wall. The greatest torque achieved with grooved surface. The tangential velocity in the gap was always higher in between the rotor and the stator and not on the wall of rotor. Also the greater one was in the groove in the recirculation zones. In order to avoid endwall effects, long cylinders are used in our setup (100 mm), torque is measured by a co-rotating torquemeter. The rotor is driven by an air turbine of an automotive turbo-compressor for high angular velocities. The results of the experimental measurements are at rotational speed of up to 50 000 rpm. The first experimental results are in agreement with numerical ones. Currently, quantitative study is performed on grooved surface, to determine the effect of number of grooves on the torque, experimentally and numerically.

Keywords: Taylor-Couette flow, high gap ratio, grooved surface, high speed

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7342 Synthesis of Nanoparticles and Thin Film of Cu₂ZnSnS₄ by Hydrothermal Method and Its Application as Congo Red Photocatalyst

Authors: Paula Salazar, Rodrigo Henríquez, Pablo Zerega

Abstract:

The textile, food and pharmaceutical industries are expanding daily worldwide, and they are located within the most polluting industries due to the fact that wastewater is discharged into watercourses with high concentrations of dyes and traces of drugs. Many of these compounds are stable to light and biodegradation, being considered as emerging organic contaminants. Advanced oxidation processes (AOPs) emerge as an effective alternative for the removal and elimination of this type of contaminants. Heterogeneous photocatalysis has been extensively studied as it is an efficient, low-cost and durable method. As the main photocatalyst, TiO₂ has been used for the degradation of a large number of dyes and drugs. The disadvantage of TiO₂ is its absorption in the UV region of the solar spectrum. On the other hand, quaternary chalcogenides based on Cu₂SnZnX₄ (X = S, Se) are a possible alternative due to their narrow bandgap (ca. between 0.8 to 1.5 eV depending on the phase considered), low cost, an abundance of its constituent elements in the earth's crust and its low toxicity. The objective of this research was to synthesize Cu₂SnZnS₄ (CZTS) through of a low-cost hydrothermal method and evaluate it as a potential photo-catalyst in the photo-degradation process of Congo Red. The synthesis of the nanoparticle in suspension and film onto fluorine-doped tin oxide coated glass (FTO) was carried out using a mixture of: 2 mmol CuCl₂, 1 mmol ZnCl₂, 1 mmol SnCl₂ and 4 mmol CH4N₂S in a Teflon reactor at 180⁰C for 72 h. Characterization was performed through scanning electron microscopy (SEM), X-ray diffraction (XRD) and UV VIS spectroscopy. Photo-degradation monitoring was carried out employing a UV VIS spectrophotometer. The results show that photodegradation of 55% of the dye can be obtained after 4h of exposure to polychromatic light, it should be noted that the Congo Red dye is being studied for the first time.

Keywords: CZTS, hydrothermal, photocatalysis, dye

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7341 Extraction, Synthesis, Characterization and Antioxidant Properties of Oxidized Starch from an Abundant Source in Nigeria

Authors: Okafor E. Ijeoma, Isimi C. Yetunde, Okoh E. Judith, Kunle O. Olobayo, Emeje O. Martins

Abstract:

Starch has gained interest as a renewable and environmentally compatible polymer due to the increase in its use. However, starch by itself could not be satisfactorily applied in industrial processes due to some inherent disadvantages such as its hydrophilic character, poor mechanical properties, its inability to withstand processing conditions such as extreme temperatures, diverse pH, high shear rate, freeze-thaw variation and dimensional stability. The range of physical properties of parent starch can be enlarged by chemical modification which invariably enhances their use in a number of applications found in industrial processes and food manufacture. In this study, Manihot esculentus starch was subjected to modification by oxidation. Fourier Transmittance Infra- Red (FTIR) and Raman spectroscopies were used to confirm the synthesis while Scanning Electron Microscopy (SEM) and X- Ray Diffraction (XRD) were used to characterize the new polymer. DPPH (2, 2-diphenyl-1-picryl-hydrazyl-hydrate) free radical assay was used to determine the antioxidant property of the oxidized starch. Our results show that the modification had no significant effect on the foaming capacity as well as on the emulsion capacity. Scanning electron microscopy revealed that oxidation did not alter the predominantly circular-shaped starch granules, while the X-ray pattern of both starch, native and modified were similar. FTIR results revealed a new band at 3007 and 3283cm-1. Differential scanning calorimetry returned two new endothermic peaks in the oxidized starch with an improved gelation capacity and increased enthalpy of gelatinization. The IC50 of oxidized starch was notably higher than that of the reference standard, ascorbic acid.

Keywords: antioxidant activity, DPPH, M. esculentus, oxidation, starch

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7340 Enhancing Patch Time Series Transformer with Wavelet Transform for Improved Stock Prediction

Authors: Cheng-yu Hsieh, Bo Zhang, Ahmed Hambaba

Abstract:

Stock market prediction has long been an area of interest for both expert analysts and investors, driven by its complexity and the noisy, volatile conditions it operates under. This research examines the efficacy of combining the Patch Time Series Transformer (PatchTST) with wavelet transforms, specifically focusing on Haar and Daubechies wavelets, in forecasting the adjusted closing price of the S&P 500 index for the following day. By comparing the performance of the augmented PatchTST models with traditional predictive models such as Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Transformers, this study highlights significant enhancements in prediction accuracy. The integration of the Daubechies wavelet with PatchTST notably excels, surpassing other configurations and conventional models in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE). The success of the PatchTST model paired with Daubechies wavelet is attributed to its superior capability in extracting detailed signal information and eliminating irrelevant noise, thus proving to be an effective approach for financial time series forecasting.

Keywords: deep learning, financial forecasting, stock market prediction, patch time series transformer, wavelet transform

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7339 Non-Targeted Adversarial Object Detection Attack: Fast Gradient Sign Method

Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

Abstract:

Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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7338 Polymerization: An Alternative Technology for Heavy Metal Removal

Authors: M. S. Mahmoud

Abstract:

In this paper, the adsorption performance of a novel environmental friendly material, calcium alginate gel beads as a non-conventional technique for the successful removal of copper ions from aqueous solution are reported on. Batch equilibrium studies were carried out to evaluate the adsorption capacity and process parameters such as pH, adsorbent dosages, initial metal ion concentrations, stirring rates and contact times. It was observed that the optimum pH for maximum copper ions adsorption was at pH 5.0. For all contact times, an increase in copper ions concentration resulted in decrease in the percent of copper ions removal. Langmuir and Freundlich's isothermal models were used to describe the experimental adsorption. Adsorbent was characterization using Fourier transform-infrared (FT-IR) spectroscopy and Transmission electron microscopy (TEM).

Keywords: adsorption, alginate polymer, isothermal models, equilibrium

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7337 New Moment Rotation Model of Single Web Angle Connections

Authors: Zhengyi Kong, Seung-Eock Kim

Abstract:

Single angle connections, which are bolted to the beam web and the column flange, are studied to investigate moment-rotation behavior. Elastic–perfectly plastic material behavior is assumed. ABAQUS software is used to analyze the nonlinear behavior of a single angle connection. The same geometric and material conditions with Yanglin Gong’s test are used for verifying finite element models. Since Kishi and Chen’s Power model and Lee and Moon’s Log model are accurate only for a limited range, simpler and more accurate hyperbolic function models are proposed. The equation for calculating rotation at ultimate moment is first proposed.

Keywords: finite element method, moment and rotation, rotation at ultimate moment, single-web angle connections

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7336 Decision Support System for Diagnosis of Breast Cancer

Authors: Oluwaponmile D. Alao

Abstract:

In this paper, two models have been developed to ascertain the best network needed for diagnosis of breast cancer. Breast cancer has been a disease that required the attention of the medical practitioner. Experience has shown that misdiagnose of the disease has been a major challenge in the medical field. Therefore, designing a system with adequate performance for will help in making diagnosis of the disease faster and accurate. In this paper, two models: backpropagation neural network and support vector machine has been developed. The performance obtained is also compared with other previously obtained algorithms to ascertain the best algorithms.

Keywords: breast cancer, data mining, neural network, support vector machine

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7335 Selective Adsorption of Anionic Textile Dyes with Sustainable Composite Materials Based on Physically Activated Carbon and Basic Polyelectrolytes

Authors: Mari Carmen Reyes Angeles, Dalia Michel Reyes Villeda, Ana María Herrera González

Abstract:

This work reports the design and synthesis of two composite materials based on physically activated carbon and basic polyelectrolytes useful in the adsorption of textile dyes present in aqueous solutions and wastewater. The synthesis of basic polyelectrolytes poly(2-vinylpyridine) (P2VP) and poly(4-vinylpyridine) (P4VP) was made by means of free radical polymerization. The carbon made from prickly pear peel (CarTunaF) was thermally activated in the presence of combustion gases. Composite materials CarTunaF2VP and CarTunaF4VP were obtained from CarTunaF and polybasic polyelectrolytes P2VP and P4VP with a ratio of 67:33 wt. The structure of each polyelectrolyte, P2VP, and P4VP, was elucidated by means of the FTIR and 1H NMR spectrophotometric techniques. Their thermal stability was evaluated using TGA. The characterization of CarTunaF and composite materials CarTunaF2VP and CarTunaF4VP was made by means of FTIR, TGA, SEM, and N2 adsorption. The adsorptive capacities of the polyelectrolytes and the composite materials were evaluated by adsorption of direct dyes present in aqueous solutions. The polyelectrolytes removed between 90 and 100% of the dyes, and the composite materials removed between 68 and 93% of the dyes. Using the four adsorbents P2VP, P4VP, CarTuna2VP, and CarTuna4VP, it was observed that the dyes studied, Direct Blue 80, Direct Turquoise 86, and Direct Orange 26, were adsorbed in the range between 46.1 and 188.7mg∙g-1 by means of electrostatic interactions between the anionic groups in the dyes with the cationic groups in the adsorbents. By using adsorbent materials in the treatment of wastewater from the textile industry, an improvement in the quality of the water was observed by decreasing its pH, COD, conductivity, and color considerably

Keywords: adsorption, anionic dyes, composite, polyelectrolytes

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7334 Fusion Models for Cyber Threat Defense: Integrating Clustering, Random Forests, and Support Vector Machines to Against Windows Malware

Authors: Azita Ramezani, Atousa Ramezani

Abstract:

In the ever-escalating landscape of windows malware the necessity for pioneering defense strategies turns into undeniable this study introduces an avant-garde approach fusing the capabilities of clustering random forests and support vector machines SVM to combat the intricate web of cyber threats our fusion model triumphs with a staggering accuracy of 98.67 and an equally formidable f1 score of 98.68 a testament to its effectiveness in the realm of windows malware defense by deciphering the intricate patterns within malicious code our model not only raises the bar for detection precision but also redefines the paradigm of cybersecurity preparedness this breakthrough underscores the potential embedded in the fusion of diverse analytical methodologies and signals a paradigm shift in fortifying against the relentless evolution of windows malicious threats as we traverse through the dynamic cybersecurity terrain this research serves as a beacon illuminating the path toward a resilient future where innovative fusion models stand at the forefront of cyber threat defense.

Keywords: fusion models, cyber threat defense, windows malware, clustering, random forests, support vector machines (SVM), accuracy, f1-score, cybersecurity, malicious code detection

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7333 An Eco-Systemic Typology of Fashion Resale Business Models in Denmark

Authors: Mette Dalgaard Nielsen

Abstract:

The paper serves the purpose of providing an eco-systemic typology of fashion resale business models in Denmark while pointing to possibilities to learn from its wisdom during a time when a fundamental break with the dominant linear fashion paradigm has become inevitable. As we transgress planetary boundaries and can no longer continue the unsustainable path of over-exploiting the Earth’s resources, the global fashion industry faces a tremendous need for change. One of the preferred answers to the fashion industry’s sustainability crises lies in the circular economy, which aims to maximize the utilization of resources by keeping garments in use for longer. Thus, in the context of fashion, resale business models that allow pre-owned garments to change hands with the purpose of being reused in continuous cycles are considered to be among the most efficient forms of circularity. Methodologies: The paper is based on empirical data from an ongoing project and a series of qualitative pilot studies that have been conducted on the Danish resale market over a 2-year time period from Fall 2021 to Fall 2023. The methodological framework is comprised of (n) ethnography and fieldwork in selected resale environments, as well as semi-structured interviews and a workshop with eight business partners from the Danish fashion and textiles industry. By focusing on the real-world circulation of pre-owned garments, which is enabled by the identified resale business models, the research lets go of simplistic hypotheses to the benefit of dynamic, vibrant and non-linear processes. As such, the paper contributes to the emerging research field of circular economy and fashion, which finds itself in a critical need to move from non-verified concepts and theories to empirical evidence. Findings: Based on the empirical data and anchored in the business partners, the paper analyses and presents five distinct resale business models with different product, service and design characteristics. These are 1) branded resale, 2) trade-in resale, 3) peer-2-peer resale, 4) resale boutiques and consignment shops and 5) resale shelf/square meter stores and flea markets. Together, the five business models represent a plurality of resale-promoting business model design elements that have been found to contribute to the circulation of pre-owned garments in various ways for different garments, users and businesses in Denmark. Hence, the provided typology points to the necessity of prioritizing several rather than single resale business model designs, services and initiatives for the resale market to help reconfigure the linear fashion model and create a circular-ish future. Conclusions: The article represents a twofold research ambition by 1) presenting an original, up-to-date eco-systemic typology of resale business models in Denmark and 2) using the typology and its eco-systemic traits as a tool to understand different business model design elements and possibilities to help fashion grow out of its linear growth model. By basing the typology on eco-systemic mechanisms and actual exemplars of resale business models, it becomes possible to envision the contours of a genuine alternative to business as usual that ultimately helps bend the linear fashion model towards circularity.

Keywords: circular business models, circular economy, fashion, resale, strategic design, sustainability

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7332 Cluster Analysis of Retailers’ Benefits from Their Cooperation with Manufacturers: Business Models Perspective

Authors: M. K. Witek-Hajduk, T. M. Napiórkowski

Abstract:

A number of studies discussed the topic of benefits of retailers-manufacturers cooperation and coopetition. However, there are only few publications focused on the benefits of cooperation and coopetition between retailers and their suppliers of durable consumer goods; especially in the context of business model of cooperating partners. This paper aims to provide a clustering approach to segment retailers selling consumer durables according to the benefits they obtain from their cooperation with key manufacturers and differentiate the said retailers’ in term of the business models of cooperating partners. For the purpose of the study, a survey (with a CATI method) collected data on 603 consumer durables retailers present on the Polish market. Retailers are clustered both, with hierarchical and non-hierarchical methods. Five distinctive groups of consumer durables’ retailers are (based on the studied benefits) identified using the two-stage clustering approach. The clusters are then characterized with a set of exogenous variables, key of which are business models employed by the retailer and its partnering key manufacturer. The paper finds that the a combination of a medium sized retailer classified as an Integrator with a chiefly domestic capital and a manufacturer categorized as a Market Player will yield the highest benefits. On the other side of the spectrum is medium sized Distributor retailer with solely domestic capital – in this case, the business model of the cooperating manufactrer appears to be irreleveant. This paper is the one of the first empirical study using cluster analysis on primary data that defines the types of cooperation between consumer durables’ retailers and manufacturers – their key suppliers. The analysis integrates a perspective of both retailers’ and manufacturers’ business models and matches them with individual and joint benefits.

Keywords: benefits of cooperation, business model, cluster analysis, retailer-manufacturer cooperation

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7331 A Framework on Data and Remote Sensing for Humanitarian Logistics

Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

Abstract:

Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

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7330 LAMOS - Layered Amorphous Metal Oxide Gas Sensors: New Interfaces for Gas Sensing Applications

Authors: Valentina Paolucci, Jessica De Santis, Vittorio Ricci, Giacomo Giorgi, Carlo Cantalini

Abstract:

Despite their potential in gas sensing applications, the major drawback of 2D exfoliated metal dichalcogenides (MDs) is that they suffer from spontaneous oxidation in air, showing poor chemical stability under dry/wet conditions even at room temperature, limiting their practical exploitation. The aim of this work is to validate a synthesis strategy allowing microstructural and electrical stabilization of the oxides that inevitably form on the surface of 2D dichalcogenides. Taking advantage of spontaneous oxidation of MDs in air, we report on liquid phase exfoliated 2D-SnSe2 flakes annealed in static air at a temperature below the crystallization temperature of the native a-SnO2 oxide. This process yields a new class of 2D Layered Amorphous Metal Oxides Sensors (LAMOS), specifically few-layered amorphous a-SnO2, showing excellent gas sensing properties. Sensing tests were carried out at low operating temperature (i.e. 100°C) by exposing a-SnO2 to both oxidizing and reducing gases (i.e. NO2, H2S and H2) and different relative humidities ranging from 40% to 80% RH. The formation of stable nanosheets of amorphous a-SnO2 guarantees excellent reproducibility and stability of the response over one year. These results pave the way to new interesting research perspectives out considering the opportunity to synthesize homogeneous amorphous textures with no grain boundaries, no grains, no crystalline planes with different orientations, etc., following gas sensing mechanisms that likely differ from that of traditional crystalline metal oxide sensors. Moreover, the controlled annealing process could likely be extended to a large variety of Transition Metal Dichalcogenides (TMDs) and Metal Chalcogenides (MCs), where sulfur, selenium, or tellurium atoms can be easily displaced by O2 atoms (ΔG < 0), enabling the synthesis of a new family of amorphous interfaces.

Keywords: layered 2D materials, exfoliation, lamos, amorphous metal oxide sensors

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7329 Characterization, Antibacterial and Cytotoxicity Evaluation of Silver Nanoparticles Synthesised Using Grewia lasiocarpa E. Mey. Ex Harv. Plant Extracts

Authors: Nneka Augustina Akwu, Yougasphree Naidoo

Abstract:

Molecular advancement in technology has created a means whereby the atoms and molecules (solid forms) of certain materials such as plants, can now be reduced to a range of 1-100 nanometres. Green synthesis of silver nanoparticles (AgNPs) was carried out at room temperature (RT) 25 ± 2°C and 80°C, using the metabolites in the aqueous extracts of the leaves and stem bark of Grewia lasiocarpa as reductants and stabilizing agents. The biosynthesized AgNPs were characterized by UV-Vis spectrophotometry, attenuated total reflectance - Fourier transforms infrared (ATR-FTIR) spectroscopy, nanoparticle tracking analysis (NTA), Energy Dispersive X-ray fluorescence scanning electron microscope (SEM-EDXRF) and high-resolution transmission electron microscopy (HRTEM). The AgNPs were biologically evaluated for antioxidant, antibacterial and cytotoxicity activities. The phytochemical and FTIR analyses revealed the presence of metabolites that act as reducing and capping agents, while the UV-Vis spectroscopy of the biosynthesized NPs showed absorption between 380-460 nm, confirming AgNP synthesis. The Zeta potential values were between -9.1 and -20.6 mV with a hydrodynamics diameter ranging from 38.3 to 46.7 nm. SEM and HRTEM analyses revealed that AgNPs were predominately spherical with an average particle size of 2- 31 nm for the leaves and 5-27 nm for the stem bark. The cytotoxicity IC50 values of the AgNPs against HeLa, Caco-2 and MCF-7 were >1 mg/mL. The AgNPs were sensitive to all strains of bacteria used, with methicillin-resistant Staphylococcus aureus (MRSA), Staphylococcus aureus (ATCC 25923) and Escherichia coli (ATCC 25922) being more sensitive to the AgNPs. Our findings propose that antibacterial and anticancer agents could be derived from these AgNPs of G. lasiocarpa, and warrant their further investigation.

Keywords: antioxidant, cytotoxicity, Grewia lasiocarpa, silver nanoparticles, Zeta potentials

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7328 Electricity Demand Modeling and Forecasting in Singapore

Authors: Xian Li, Qing-Guo Wang, Jiangshuai Huang, Jidong Liu, Ming Yu, Tan Kok Poh

Abstract:

In power industry, accurate electricity demand forecasting for a certain leading time is important for system operation and control, etc. In this paper, we investigate the modeling and forecasting of Singapore’s electricity demand. Several standard models, such as HWT exponential smoothing model, the ARMA model and the ANNs model have been proposed based on historical demand data. We applied them to Singapore electricity market and proposed three refinements based on simulation to improve the modeling accuracy. Compared with existing models, our refined model can produce better forecasting accuracy. It is demonstrated in the simulation that by adding forecasting error into the forecasting equation, the modeling accuracy could be improved greatly.

Keywords: power industry, electricity demand, modeling, forecasting

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7327 Learn through AR (Augmented Reality)

Authors: Prajakta Musale, Bhargav Parlikar, Sakshi Parkhi, Anshu Parihar, Aryan Parikh, Diksha Parasharam, Parth Jadhav

Abstract:

AR technology is basically a development of VR technology that harnesses the power of computers to be able to read the surroundings and create projections of digital models in the real world for the purpose of visualization, demonstration, and education. It has been applied to education, fields of prototyping in product design, development of medical models, battle strategy in the military and many other fields. Our Engineering Design and Innovation (EDAI) project focuses on the usage of augmented reality, visual mapping, and 3d-visualization along with animation and text boxes to help students in fields of education get a rough idea of the concepts such as flow and mechanical movements that may be hard to visualize at first glance.

Keywords: spatial mapping, ARKit, depth sensing, real-time rendering

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7326 Synthesis of Flexible Mn1-x-y(CexLay)O2-δ Ultrathin-Film Device for Highly-Stable Pseudocapacitance from end-of-life Ni-MH batteries

Authors: Samane Maroufi, Rasoul Khayyam Nekouei, Sajjad Sefimofarah, Veena Sahajwalla

Abstract:

The present work details a three-stage strategy based on selective purification of rare earth oxide (REOs) isolated from end-of-life nickel-metal hydride (Ni-MH) batteries leading to high-yield fabrication of defect-rich Mn1-x-y(CeₓLaᵧ)O2-δ film. In step one, major impurities (Fe and Al) were removed from a REE-rich solution. In step two, the resulting solution with trace content of Mn was further purified through electrodeposition which resulted in the synthesis of a non-stoichiometric Mn₋₁₋ₓ₋ᵧ(CeₓLaₓᵧ)O2-δ ultra-thin film, with controllable thicknesses (5-650 nm) and transmittance (~29-100%)in which Ce4+/3+ and La3+ ions were dissolved in MnO2-x lattice. Due to percolation impacts on the optoelectronic properties of ultrathin films, a representative Mn1-x-y(CexLay)O2-δ film with 86% transmittance exhibited an outstanding areal capacitance of 3.4 mF•cm-2, mainly attributed to the intercalation/de-intercalation of anionic O2- charge carriers through the atomic tunnels of the stratified Mn1-x-y(CexLay)O2-δ crystallites. Furthermore, the Mn1-x-y(CexLay)O2-δ exhibited excellent capacitance retention of ~90% after 16,000 cycles. Such stability was shown to be associated with intervalence charge transfers occurring among interstitial Ce/La cations and Mn oxidation states within the Mn₋₁₋ₓ₋ᵧ(CexLay)O2-δ structure. The energy and power densities of the transparent flexible Mn₋₁₋ₓ₋ᵧ(CexLay)O2-δ full-cell pseudocapacitor device with a solid-state electrolyte was measured to be 0.088 µWh.cm-2 and 843 µW.cm-2, respectively. These values showed insignificant changes under vigorous twisting and bending to 45-180˚, confirming these materials are intriguing alternatives for size-sensitive energy storage devices. In step three, the remaining solution purified further, that led to the formation of REOs (La, Ce, and Nd) nanospheres with ~40-50 nm diameter.

Keywords: spent Ni-MH batteries, green energy, flexible pseudocapacitor, rare earth elements

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7325 Study the Difference Between the Mohr-Coulomb and the Barton-Bandis Joint Constitutive Models: A Case Study from the Iron Open Pit Mine, Canada

Authors: Abbas Kamalibandpey, Alain Beland, Joseph Mukendi Kabuya

Abstract:

Since a rock mass is a discontinuum medium, its behaviour is governed by discontinuities such as faults, joint sets, lithologic contact, and bedding planes. Thus, rock slope stability analysis in jointed rock masses is largely dependent upon discontinuities constitutive equations. This paper studies the difference between the Mohr-Coulomb (MC) and the Barton-Bandis (BB) joint constitutive numerical models for lithological contacts and joint sets. For the rock in these models, generalized Hoek-Brown criteria have been considered. The joint roughness coefficient (JRC) and the joint wall compressive strength (JCS) are vital parameters in the BB model. The numerical models are applied to the rock slope stability analysis in the Mont-Wright (MW) mine. The Mont-Wright mine is owned and operated by ArcelorMittal Mining Canada (AMMC), one of the largest iron-ore open pit operations in Canada. In this regard, one of the high walls of the mine has been selected to undergo slope stability analysis with RS2D software, finite element method. Three piezometers have been installed in this zone to record pore water pressure and it is monitored by radar. In this zone, the AMP-IF and QRMS-IF contacts and very persistent and altered joint sets in IF control the rock slope behaviour. The height of the slope is more than 250 m and consists of different lithologies such as AMP, IF, GN, QRMS, and QR. To apply the B-B model, the joint sets and geological contacts have been scanned by Maptek, and their JRC has been calculated by different methods. The numerical studies reveal that the JRC of geological contacts, AMP-IF and QRMS-IF, and joint sets in IF had a significant influence on the safety factor. After evaluating the results of rock slope stability analysis and the radar data, the B-B constitutive equation for discontinuities has shown acceptable results to the real condition in the mine. It should be noted that the difference in safety factors in MC and BB joint constitutive models in some cases is more than 30%.

Keywords: barton-Bandis criterion, Hoek-brown and Mohr-Coulomb criteria, open pit, slope stability

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7324 Orthogonal Regression for Nonparametric Estimation of Errors-In-Variables Models

Authors: Anastasiia Yu. Timofeeva

Abstract:

Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Keywords: grade point average, orthogonal regression, penalized regression spline, locally weighted regression

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7323 Methodology for Obtaining Static Alignment Model

Authors: Lely A. Luengas, Pedro R. Vizcaya, Giovanni Sánchez

Abstract:

In this paper, a methodology is presented to obtain the Static Alignment Model for any transtibial amputee person. The proposed methodology starts from experimental data collected on the Hospital Militar Central, Bogotá, Colombia. The effects of transtibial prosthesis malalignment on amputees were measured in terms of joint angles, center of pressure (COP) and weight distribution. Some statistical tools are used to obtain the model parameters. Mathematical predictive models of prosthetic alignment were created. The proposed models are validated in amputees and finding promising results for the prosthesis Static Alignment. Static alignment process is unique to each subject; nevertheless the proposed methodology can be used in each transtibial amputee.

Keywords: information theory, prediction model, prosthetic alignment, transtibial prosthesis

Procedia PDF Downloads 252
7322 Steel Bridge Coating Inspection Using Image Processing with Neural Network Approach

Authors: Ahmed Elbeheri, Tarek Zayed

Abstract:

Steel bridges deterioration has been one of the problems in North America for the last years. Steel bridges deterioration mainly attributed to the difficult weather conditions. Steel bridges suffer fatigue cracks and corrosion, which necessitate immediate inspection. Visual inspection is the most common technique for steel bridges inspection, but it depends on the inspector experience, conditions, and work environment. So many Non-destructive Evaluation (NDE) models have been developed use Non-destructive technologies to be more accurate, reliable and non-human dependent. Non-destructive techniques such as The Eddy Current Method, The Radiographic Method (RT), Ultra-Sonic Method (UT), Infra-red thermography and Laser technology have been used. Digital Image processing will be used for Corrosion detection as an Alternative for visual inspection. Different models had used grey-level and colored digital image for processing. However, color image proved to be better as it uses the color of the rust to distinguish it from the different backgrounds. The detection of the rust is an important process as it’s the first warning for the corrosion and a sign of coating erosion. To decide which is the steel element to be repainted and how urgent it is the percentage of rust should be calculated. In this paper, an image processing approach will be developed to detect corrosion and its severity. Two models were developed 1st to detect rust and 2nd to detect rust percentage.

Keywords: steel bridge, bridge inspection, steel corrosion, image processing

Procedia PDF Downloads 298
7321 Synthesis of Highly Sensitive Molecular Imprinted Sensor for Selective Determination of Doxycycline in Honey Samples

Authors: Nadia El Alami El Hassani, Soukaina Motia, Benachir Bouchikhi, Nezha El Bari

Abstract:

Doxycycline (DXy) is a cycline antibiotic, most frequently prescribed to treat bacterial infections in veterinary medicine. However, its broad antimicrobial activity and low cost, lead to an intensive use, which can seriously affect human health. Therefore, its spread in the food products has to be monitored. The scope of this work was to synthetize a sensitive and very selective molecularly imprinted polymer (MIP) for DXy detection in honey samples. Firstly, the synthesis of this biosensor was performed by casting a layer of carboxylate polyvinyl chloride (PVC-COOH) on the working surface of a gold screen-printed electrode (Au-SPE) in order to bind covalently the analyte under mild conditions. Secondly, DXy as a template molecule was bounded to the activated carboxylic groups, and the formation of MIP was performed by a biocompatible polymer by the mean of polyacrylamide matrix. Then, DXy was detected by measurements of differential pulse voltammetry (DPV). A non-imprinted polymer (NIP) prepared in the same conditions and without the use of template molecule was also performed. We have noticed that the elaborated biosensor exhibits a high sensitivity and a linear behavior between the regenerated current and the logarithmic concentrations of DXy from 0.1 pg.mL−1 to 1000 pg.mL−1. This technic was successfully applied to determine DXy residues in honey samples with a limit of detection (LOD) of 0.1 pg.mL−1 and an excellent selectivity when compared to the results of oxytetracycline (OXy) as analogous interfering compound. The proposed method is cheap, sensitive, selective, simple, and is applied successfully to detect DXy in honey with the recoveries of 87% and 95%. Considering these advantages, this system provides a further perspective for food quality control in industrial fields.

Keywords: doxycycline, electrochemical sensor, food control, gold nanoparticles, honey, molecular imprinted polymer

Procedia PDF Downloads 309
7320 Analysis of the 2023 Karnataka State Elections Using Online Sentiment

Authors: Pranav Gunhal

Abstract:

This paper presents an analysis of sentiment on Twitter towards the Karnataka elections held in 2023, utilizing transformer-based models specifically designed for sentiment analysis in Indic languages. Through an innovative data collection approach involving a combination of novel methods of data augmentation, online data preceding the election was analyzed. The study focuses on sentiment classification, effectively distinguishing between positive, negative, and neutral posts while specifically targeting the sentiment regarding the loss of the Bharatiya Janata Party (BJP) or the win of the Indian National Congress (INC). Leveraging high-performing transformer architectures, specifically IndicBERT, coupled with specifically fine-tuned hyperparameters, the AI models employed in this study achieved remarkable accuracy in predicting the INC’s victory in the election. The findings shed new light on the potential of cutting-edge transformer-based models in capturing and analyzing sentiment dynamics within the Indian political landscape. The implications of this research are far-reaching, providing invaluable insights to political parties for informed decision-making and strategic planning in preparation for the forthcoming 2024 Lok Sabha elections in the nation.

Keywords: sentiment analysis, twitter, Karnataka elections, congress, BJP, transformers, Indic languages, AI, novel architectures, IndicBERT, lok sabha elections

Procedia PDF Downloads 80
7319 Piping Fragility Composed of Different Materials by Using OpenSees Software

Authors: Woo Young Jung, Min Ho Kwon, Bu Seog Ju

Abstract:

A failure of the non-structural component can cause significant damages in critical facilities such as nuclear power plants and hospitals. Historically, it was reported that the damage from the leakage of sprinkler systems, resulted in the shutdown of hospitals for several weeks by the 1971 San Fernando and 1994 North Ridge earthquakes. In most cases, water leakages were observed at the cross joints, sprinkler heads, and T-joint connections in piping systems during and after the seismic events. Hence, the primary objective of this study was to understand the seismic performance of T-joint connections and to develop an analytical Finite Element (FE) model for the T-joint systems of 2-inch fire protection piping system in hospitals subjected to seismic ground motions. In order to evaluate the FE models of the piping systems using OpenSees, two types of materials were used: 1) Steel 02 materials and 2) Pinching 4 materials. Results of the current study revealed that the nonlinear moment-rotation FE models for the threaded T-joint reconciled well with the experimental results in both FE material models. However, the system-level fragility determined from multiple nonlinear time history analyses at the threaded T-joint was slightly different. The system-level fragility at the T-joint, determined by Pinching 4 material was more conservative than that of using Steel 02 material in the piping system.

Keywords: fragility, t-joint, piping, leakage, sprinkler

Procedia PDF Downloads 299
7318 The Role of the STAT3 Signaling for Melatonergic Synthetic Pathway in the Rat Pineal Gland

Authors: Simona Moravcova, Jiri Novotny, Zdenka Bendova

Abstract:

The pineal gland of the vertebrate brain is a circumventricular organ which serves as a major neuroendocrine gland with the primary function of rhythmic secretion of neurohormone melatonin under the control of the hypothalamic suprachiasmatic nucleus (SCN). Soon after the onset of the darkness, the activity of the key rate-limiting enzyme for melatonin synthesis, arylalkylamine N-acetyltransferase (AANAT), raises due to the increased release of norepinephrine from sympathetic neurons terminating on the parenchymal cells where it binds to β-adrenergic receptors. Melatonin codes the length of the night, and it is well recognized for its anti-inflammatory effects. However, to our knowledge, less is known about the effect of the immune system on the melatonin biosynthesis and the precise role of the STAT3 in the signaling pathway leading to the expression of AANAT. Lipopolysaccharide (LPS) is the essential component in the outer surface membrane of gram-negative bacteria and acts as a strong stimulator of natural and innate immunity. STAT3 acts as an important factor in immune response. Here we investigated the effect of LPS on the components of the melatonergic synthetic pathway in the pineal gland. The experiments were performed both in vivo and in vitro. The changes in AANAT activity were determined by radioenzymatic assay. PCR analyses were carried out to detect aa-nat, icer, spi-3 and stat3 gene expression. From our results, it is apparent that the high basal level of phosphorylated forms of STAT3 can be elevated after systemic as well as in vitro administration of LPS. Our experiments have shown that LPS reduces melatonin synthesis, nevertheless, the activity of AANAT was increased. Moreover, the basal level of phosphorylated STAT3 counteracts β-adrenergic receptor-mediated aa-nat gene expression and sustains its own and spi-3 gene expression. In conclusion, LPS can affect immunomodulators such as melatonin in the pineal gland.

Keywords: AANAT, lipopolysaccharide, pineal gland, rat, STAT3

Procedia PDF Downloads 168
7317 Comparison of Two Neural Networks To Model Margarine Age And Predict Shelf-Life Using Matlab

Authors: Phakamani Xaba, Robert Huberts, Bilainu Oboirien

Abstract:

The present study was aimed at developing & comparing two neural-network-based predictive models to predict shelf-life/product age of South African margarine using free fatty acid (FFA), water droplet size (D3.3), water droplet distribution (e-sigma), moisture content, peroxide value (PV), anisidine valve (AnV) and total oxidation (totox) value as input variables to the model. Brick margarine products which had varying ages ranging from fresh i.e. week 0 to week 47 were sourced. The brick margarine products which had been stored at 10 & 25 °C and were characterized. JMP and MATLAB models to predict shelf-life/ margarine age were developed and their performances were compared. The key performance indicators to evaluate the model performances were correlation coefficient (CC), root mean square error (RMSE), and mean absolute percentage error (MAPE) relative to the actual data. The MATLAB-developed model showed a better performance in all three performance indicators. The correlation coefficient of the MATLAB model was 99.86% versus 99.74% for the JMP model, the RMSE was 0.720 compared to 1.005 and the MAPE was 7.4% compared to 8.571%. The MATLAB model was selected to be the most accurate, and then, the number of hidden neurons/ nodes was optimized to develop a single predictive model. The optimized MATLAB with 10 neurons showed a better performance compared to the models with 1 & 5 hidden neurons. The developed models can be used by margarine manufacturers, food research institutions, researchers etc, to predict shelf-life/ margarine product age, optimize addition of antioxidants, extend shelf-life of products and proactively troubleshoot for problems related to changes which have an impact on shelf-life of margarine without conducting expensive trials.

Keywords: margarine shelf-life, predictive modelling, neural networks, oil oxidation

Procedia PDF Downloads 190
7316 Flexural Behavior of Composite Hybrid Beam Models Combining Steel Inverted T-Section and RC Flange

Authors: Abdul Qader Melhem, Hacene Badache

Abstract:

This paper deals with the theoretical and experimental study of shear connection via simple steel reinforcement shear connectors, which are steel reinforcing bars bent into L-shapes, instead of commonly used headed studs. This suggested L-shape connectors are readily available construction material in steel reinforcement. The composite section, therefore, consists of steel inverted T-section being embedded within a lightly reinforced concrete flange at the top slab as a unit. It should be noted that the cross section of these composite models involves steel inverted T-beam, replacing the steel top flange of a standard commonly employed I-beam section. The paper concentrates on the elastic and elastic-plastic behavior of these composite models. Failure modes either by cracking of concrete or shear connection be investigated in details. Elastic and elastoplastic formulas of the composite model have been computed for different locations of NA. Deflection formula has been derived, its value was close to the test value. With a supportive designing curve, this curve is valuable for both designing engineers and researchers. Finally, suggested designing curves and valuable equations will be presented. A check is made between theoretical and experimental outcomes.

Keywords: composite, elastic-plastic, failure, inverted T-section, L-Shape connectors

Procedia PDF Downloads 226
7315 Analysis of Expert Information in Linguistic Terms

Authors: O. Poleshchuk, E. Komarov

Abstract:

In this paper, semantic spaces with the properties of completeness and orthogonality (complete orthogonal semantic spaces) were chosen as models of expert evaluations. As the theoretical and practical studies have shown all the properties of complete orthogonal semantic spaces correspond to the thinking activity of experts that is why these semantic spaces were chosen for modeling. Two methods of construction such spaces were proposed. Models of comparative and fuzzy cluster analysis of expert evaluations were developed. The practical application of the developed methods has demonstrated their viability and validity.

Keywords: expert evaluation, comparative analysis, fuzzy cluster analysis, theoretical and practical studies

Procedia PDF Downloads 526
7314 Proposal of Design Method in the Semi-Acausal System Model

Authors: Shigeyuki Haruyama, Ken Kaminishi, Junji Kaneko, Tadayuki Kyoutani, Siti Ruhana Omar, Oke Oktavianty

Abstract:

This study is used as a definition method to the value and function in manufacturing sector. In concurrence of discussion about present condition of modeling method, until now definition of 1D-CAE is ambiguity and not conceptual. Across all the physics fields, those methods are defined with the formulation of differential algebraic equation which only applied time derivation and simulation. At the same time, we propose semi-acausal modeling concept and differential algebraic equation method as a newly modeling method which the efficiency has been verified through the comparison of numerical analysis result between the semi-acausal modeling calculation and FEM theory calculation.

Keywords: system model, physical models, empirical models, conservation law, differential algebraic equation, object-oriented

Procedia PDF Downloads 480