Search results for: gradient boosting machines (GBM)

Authors: Kingsley Oturu, Winifred Ijomah, Wale Coker, Chibueze Achi

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With the impact of BREXIT and the need for cross-border collaboration, this international research investigated the use of a conceptual model for remanufacturing medical equipment (with a focus on anesthetic machines and baby incubators). Early findings of the research suggest that contextual factors need to be taken into consideration, as well as an emphasis on cleaning (e.g., sterilization) during the process of remanufacturing medical equipment. For example, copper tubings may be more important in the remanufacturing of anesthetic equipment in tropical climates than in cold climates.

Keywords: medical equipment remanufacture, sustainability, circular business models, remanufacture process model

Procedia PDF Downloads 172

Authors: Ezzeldin M. T. Ali

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Arguably viewers hardly benefit from screen subtitles due to the inconsistency between scenarios and their subtitles. Research in this area will provide an understanding of the association between these scenarios and subtitles via context. It attempts to eliminate the inconsistency existing between contexts and screen subtitles providing insights into the problem. Specifically, the study aims at examining the extent to which the understanding of screen subtitles largely depends on the force of linguistic and situational contexts. This is because the context is assumed to have a powerful effect on the interpretation of the source text. Both descriptive and experimental methods were adopted for data collection. These included a test and paper-pencil-questionnaires where participants provided their impressions about the role of context in eliminating interpretation problems of screen subtitles. Participants developed a good background about screen subtitles watching films. Results showed that context forms a powerful element in understanding screen subtitles. Results also revealed that communicative translation fits well screen translation boosting the contextual meaning. The association of context and communicative translation makes subtitles globally more economical and intelligible. Context forms a central element for film language to be intelligible.

Keywords: communicative translation, context, scenario, powerful, intellgible

Procedia PDF Downloads 163

Authors: B. Bouadjemi, S. Bentata, W. Benstaali, A. Abbad, T. Lantri, A. Zitouni

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The purpose of this study was to investigate the structural,electronic and magnetic properties of the cubic praseodymium oxides perovskites PrMnO3. It includes our calculations based on the use of the density functional theory (DFT) with both generalized gradient approximation (GGA) and GGA+U approaches, The spin polarized electronic band structures and densities of states as well as the integer value of the magnetic moment of the unit cell (6 μB) illustrate that PrMnO3 is half-metallic ferromagnetic. The study prove that the compound is half-metallic ferromagnetic however the results obtained, make the cubic PrMnO3 a promising candidate for application in spintronics.

Keywords: cubic, DFT, electronic properties, magnetic moment, spintronics

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Authors: G. Patricia Abdel Rahim, Jairo Arbey Rodriguez M, María Guadalupe Moreno Armenta

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The present study shows the structural, electronic and magnetic properties of magnesium (Mg) and bismuth (Bi) in a supercell (1X1X5). For both materials were studied in five crystalline structures: rock salt (NaCl), cesium chloride (CsCl), zinc-blende (ZB), wurtzite (WZ), and nickel arsenide (NiAs), using the Density Functional Theory (DFT), the Generalized Gradient Approximation (GGA), and the Full Potential Linear Augmented Plane Wave (FP-LAPW) method. By means of fitting the Murnaghan's state equation we determine the lattice constant, the bulk modulus and it's derived with the pressure. Also we calculated the density of states (DOS) and the band structure.

Keywords: bismuth, magnesium, pseudo-potential, supercell

Procedia PDF Downloads 822

Authors: Alexandra Andrade Brandão Soares, Paulo Batista Gonçalves

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Using a modal expansion that satisfies the boundary and continuity conditions and expresses the modal couplings characteristic of cylindrical shells in the nonlinear regime, the equations of motion are discretized using the Galerkin method. The resulting algebraic equations are solved by the Newton-Raphson method, thus obtaining the nonlinear frequency-amplitude relation. Finally, a parametric analysis is conducted to study the influence of the geometry of the shell, the gradient of the functional material and vibration modes on the degree and type of nonlinearity of the cylindrical shell, which is the main contribution of this research work.

Keywords: cylindrical shells, dynamics, functionally graded material, nonlinear vibrations

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Authors: Eylem Koç, Hasan Arda Burhan

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Location selection presents a crucial decision problem in today’s business world where strategic decision making processes have critical importance. Thus, location selection has strategic importance for companies in boosting their strength regarding competition, increasing corporate performances and efficiency in addition to lowering production and transportation costs. A right choice in location selection has a direct impact on companies’ commercial success. In this study, a store location selection problem of Carglass Turkey which operates in vehicle glass branch is handled. As this problem includes both tangible and intangible criteria, Analytic Network Process (ANP) was accepted as the main methodology. The model consists of control hierarchy and BOCR subnetworks which include clusters of actors, alternatives and criteria. In accordance with the management’s choices, five different locations were selected. In addition to the literature review, a strict cooperation with the actor group was ensured and maintained while determining the criteria and during whole process. Obtained results were presented to the management as a report and its feasibility was confirmed accordingly.

Keywords: analytic network process (ANP), BOCR, multi-actor decision making, multi-criteria decision making, real-life problem, location selection

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Authors: Syed Najeeb-Uz-Zaman Haider, Yang Juan

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Antibiotic overuse raises environmental concerns, boosting the demand for efficient removal from pharmaceutical wastewater. Photocatalysis, particularly using semiconductor photocatalysts, offers a promising solution and garners significant scientific interest. In this study, a Z-scheme 0.15BWO/CCN heterojunction was developed, analyzed, and employed for the photocatalytic degradation of tetracycline hydrochloride (TC) under visible light. The study revealed that the dosage of 0.15BWO@CCN and the presence of coexisting ions significantly influenced the degradation efficiency, achieving up to 87% within 20 minutes under optimal conditions (at pH 9-11/strongly basic conditions) while maintaining 84% efficiency under standard conditions (unaltered pH). Photoinduced electrons gathered on the conduction band of BWO while holes accumulated on the valence band of CCN, creating more favorable conditions to produce superoxide and hydroxyl radicals. Additionally, through comprehensive experimental analysis, the degradation pathway and mechanism were thoroughly explored. The superior photocatalytic performance of 0.15BWO@CCN was attributed to its Z-scheme heterojunction structure, which significantly reduced the recombination of photoinduced electrons and holes. The radicals produced were identified using ESR, and their involvement in tetracycline degradation was further analyzed through active species trapping experiments.

Keywords: CCN, Bi₂WO₆, TC, photocatalytic degradation, heterojunction

Procedia PDF Downloads 44

Authors: B. Bouadjemi, S. Bentata, W. Benstaali, A. Abbad, T. Lantri, A. Zitouni

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The purpose of this study was to investigate the structural,electronic and magnetic properties of the cubic praseodymium oxides perovskites PrMnO3. It includes our calculations based on the use of the density functional theory (DFT) with both generalized gradient approximation (GGA) and GGA+U approaches, The spin polarized electronic band structures and densities of states aswellas the integer value of the magnetic moment of the unit cell (6 μB) illustrate that PrMnO3 is half-metallic ferromagnetic. The study shows that the robust half-metallicity makes the cubic PrMnO3 a promising candidate for application in spintronics.

Keywords: Perovskite, DFT, electronic properties, Magnetic moment, half-metallic

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Authors: Douhi Reda Bouabdellah, Khalafi Hamid, Belamri Samir

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The desire to improve the safety of nuclear reactor containment has revealed the need for data on the thermo mechanical behavior of concrete in case of accident during which the concrete is exposed to high temperatures. The aim of the present work is to study the influence of high temperature on the behavior of ordinary concrete specimens loaded by an effort of compression. A thermal model is developed by discretization volume elements (CASTEM). The results of different simulations, combined with other findings help to bring a physical phenomenon explanation Thermo mechanical concrete structures, which allowed to obtain the variation of the stresses anywhere in point or node and each subsequent temperature different directions X, Y and Z.

Keywords: concrete, thermic-gradient, fire resistant, simulation by CASTEM, mechanical strength

Procedia PDF Downloads 309

Authors: A. Zitouni, S. Bentata, B. Bouadjemi, T. Lantri, W. Benstaali, A. Zoubir, S. Cherid, A. Sefir

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The structural, electronic, and magnetic properties of transition metal Co and Mn doped zinc-blende semiconductor CdTe were calculated using the density functional theory (DFT) with both generalized gradient approximation (GGA). We have analyzed the structural parameters, charge and spin densities, total and partial densities of states. We find that the Co and Mn doped zinc blende CdTe show half-metallic behavior with a total magnetic moment of 6.0 and 10.0 µB, respectively.The results obtained, make the Co and Mn doped CdTe a promising candidate for application in spintronics.

Keywords: first-principles, half-metallic, diluted magnetic semiconductor, magnetic moment

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Authors: Luis Rodrigo Valencia Perez, Francisco Flores Aguero, Gibran Aguilar Rangel

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Artificial Intelligence (AI) is rapidly transforming diverse sectors, and higher education in Latin America is no exception. This article explores the impact of AI on higher education institutions in the region, highlighting the imperative need for well-trained teachers in emerging technologies and a cultural shift towards the adoption and efficient use of these tools. AI offers significant opportunities to improve learning personalization, optimize administrative processes, and promote more inclusive and accessible education. However, the effectiveness of its implementation depends largely on the preparation and willingness of teachers to integrate these technologies into their pedagogical practices. Furthermore, it is essential that Latin American countries develop and implement public policies that encourage the adoption of AI in the education sector, thus ensuring that institutions can compete globally. Policies should focus on the continuous training of educators, investment in technological infrastructure, and the creation of regulatory frameworks that promote innovation and the ethical use of AI. Only through a comprehensive and collaborative approach will it be possible to fully harness the potential of AI to transform higher education in Latin America, thereby boosting the region's development and competitiveness on the global stage.

Keywords: artificial intelligence (AI), higher education, teacher training, public policies, latin america, global competitiveness

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Authors: Ezeoke Callistus Obiora, Ezeoke Nneka Angela

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The study investigated the effect of deficit financing on macroeconomic variables in Nigeria. The specific objectives included to find out the relationship between deficit financing and GDP, interest rate, inflation rate, money supply, exchange rate and private investment respectively on a time series covering a period of 44 years (1970 – 2013). The Ordinary Least Square multiple regression produced statistics for the coefficient of determination (R2), F-test, t-test used for the interpretation of the study. The findings revealed that Deficit financing has significant positive effect on GDP and exchange rate. Again, deficit financing has a positive and insignificant relationship inflation, money supply and investment. Only interest rate recorded negative yet insignificant relationship with deficit financing. The implications of the findings are that deficit financing can be a veritable tool for boosting economic development in Nigeria, but the influential positively rising exchange rate implies that deficit financing devalues the Naira exchange rate to other currencies indicating that deficit financing can affect Nigerians competitive advantage at the world market. Thus, the study concludes that deficit financing has not encouraged economic growth in Nigeria.

Keywords: deficit financing, money supply, exchange rate, inflation, GDP, investment, Nigeria

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Authors: Fayaz Moosavi, Saeid Moradyfard

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One of the methods in avoiding management fraud and increasing the quality of financial information, is the notification of qualitative features of financial information, including conservatism characteristic. Although taking a conservatism approach, while boosting the quality of financial information, is able to reduce the informational risk and the cost of capital stock of commercial department, by presenting an improper image about the situation of the commercial department, raises the risk of failure in returning the main and capital interest, and consequently the cost of capital of the commercial department. In order to know if conservatism finally leads to the increase or decrease of the cost of capital or does not have any influence on it, information regarding accepted companies in Tehran stock exchange is utilized by application of pooling method from 2007 to 2012 and it included 124 companies. The results of the study revealed that there is an opposite and meaningful relationship between conditional conservatism and the cost of capital of the company. In other words, if bad and unsuitable news and signs are reflected sooner than good news in accounting profit, the cost of capital of the company increases. In addition, there is a positive and meaningful relationship between the cost of capital and lack of information asymmetry.

Keywords: conditional conservatism, lack of information asymmetry, the cost of capital, stock exchange

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

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

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

Procedia PDF Downloads 132

Authors: Jie Zhang, Chaomin Zhang, Jihua Zhang, Haitong Li

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Using the theory of optimal distinctiveness, this study examines the effects of conformity and differentiation within corporate social responsibility (CSR) practices on capital market performance. Analysing data from Chinese A-share listed firms from 2007 to 2022, this paper demonstrates that when firms conform to the expected scope of CSR, such behaviour enhances investor attention and market acceptance, thereby boosting stock liquidity. Conversely, emphasising differentiation in CSR practices more effectively mitigates stock price crash risk by addressing principal–agent problems and decreasing information asymmetry. This paper also investigates how organisational and environmental factors moderate the relationship between conformity and differentiation in CSR practices and their impact on capital market performance. The results also show that the influence of conformity on stock liquidity is accentuated in smaller firms and environments with stringent legal oversight. By contrast, the benefits of differentiation in reducing stock price crash risk are amplified in firms with robust corporate governance and markets characterised by high uncertainty.

Keywords: corporate social responsibility, social responsibility practices, capital market performance, optimal distinctiveness

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Authors: Iddy Iddy, Qin Jiang, Changkuan Zhang

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This paper addresses the hydraulic performance of curtain wall breakwaters as a coastal structure protection based on the particles method modelling. The hydraulic functions of curtain wall as wave barriers by reflecting large parts of incident waves through the vertical wall, a part transmitted and a particular part was dissipating the wave energies through the eddy flows formed beneath the lower end of the plate. As a Lagrangian particle, the Moving Particle Semi-implicit (MPS) method which has a robust capability for numerical representation has proven useful for design of structures application that concern free-surface hydrodynamic flow, such as wave breaking and overtopping. In this study, a vertical two-dimensional numerical model for the simulation of violent flow associated with the interaction between the curtain-wall breakwaters and progressive water waves is developed by MPS method in which a higher precision pressure gradient model and free surface particle recognition model were proposed. The wave transmission, reflection, and energy dissipation of the vertical wall were experimentally and theoretically examined. With the numerical wave flume by particle method, very detailed velocity and pressure fields around the curtain-walls under the action of waves can be computed in each calculation steps, and the effect of different wave and structural parameters on the hydrodynamic characteristics was investigated. Also, the simulated results of temporal profiles and distributions of velocity and pressure in the vicinity of curtain-wall breakwaters are compared with the experimental data. Herein, the numerical investigation of hydraulic performance of curtain wall breakwaters indicated that the incident wave is largely reflected from the structure, while the large eddies or turbulent flows occur beneath the curtain-wall resulting in big energy losses. The improved MPS method shows a good agreement between numerical results and analytical/experimental data which are compared to related researches. It is thus verified that the improved pressure gradient model and free surface particle recognition methods are useful for enhancement of stability and accuracy of MPS model for water waves and marine structures. Therefore, it is possible for particle method (MPS method) to achieve an appropriate level of correctness to be applied in engineering fields through further study.

Keywords: curtain wall breakwaters, free surface flow, hydraulic performance, improved MPS method

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Authors: Magda Kosmal, Anna A. Kuśnierz, Joanna Rybicka-Łada

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In the case of waste glass cullet, a fully functioning recycling system for individual glass industries was developed, while recycling of cement dust encounters a number of difficulties and is conducted to a limited extent in the packaging and flat glass industry. The aim of the project was to examine the possibility of using dust arising in cement plants in the process of melting various types of glasses. Dust management has a positive effect on the aspect of environmental protection and ecology. Sets have been designed, and the parameters of the melting process have been optimized. Glasses were obtained with the addition of selected cement dust on a laboratory scale, using DTA, XRD, SEM tests, and a gradient furnace was conducted to check the tendency to crystallization.

Keywords: cement dust, crystallization, glass, XRD, SEM

Procedia PDF Downloads 85

Authors: Vivek Rangarajan, Kim G. Clarke

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Bacillus lipopeptides are biosurfactants with wide ranging applications in the medical, food, agricultural, environmental and cosmetic industries. They are produced as a mix of three families, surfactin, iturin and fengycin, each comprising a large number of homologues of varying functionalities. Consequently, the method and degree of purification of the lipopeptide cocktail becomes particularly important if the functionality of the lipopeptide end-product is to be maximized for the specific application. However, downstream processing of Bacillus lipopeptides is particularly challenging due to the subtle variations observed in the different lipopeptide homologues and isoforms. To date, the most frequently used lipopeptide purification operations have been acid precipitation, solvent extraction, membrane ultrafiltration, adsorption and size exclusion. RP-HPLC (reverse phase high pressure liquid chromatography) also has potential for fractionation of the lipopeptide homologues. In the studies presented here, membrane ultrafiltration and RP-HPLC were evaluated for lipopeptide purification to different degrees of purities for maximum functionality. Batch membrane ultrafiltration using 50 kDa polyether sulphone (PES) membranes resulted in lipopeptide recovery of about 68% for surfactin and 82 % for fengycin. The recovery was further improved to 95% by using size-conditioned lipopeptide micelles. The conditioning of lipopeptides with Ca2+ ions resulted in uniformly sized micelles with average size of 96.4 nm and a polydispersity index of 0.18. The size conditioning also facilitated removal of impurities (molecular weight ranging between 2335-3500 Da) through operation of the system under dia-filtration mode, in a way similar to salt removal from protein by dialysis. The resultant purified lipopeptide was devoid of macromolecular impurities and could ideally suit applications in the cosmetic and food industries. Enhanced purification using RP-HPLC was carried out in an analytical C18 column, with the aim to fractionate lipopeptides into their constituent homologues. The column was eluted with mobile phase comprising acetonitrile and water over an acetonitrile gradient, 35% - 80%, over 70 minutes. The gradient elution program resulted in as many as 41 fractions of individual lipopeptide homologues. The efficacy test of these fractions against fungal phytopathogens showed that first 21 fractions, identified to be homologues of iturins and fengycins, displayed maximum antifungal activities, suitable for biocontrol in the agricultural industry. Thus, in the current study, the downstream processing of lipopeptides leading to tailor-made products for selective applications was demonstrated using two major downstream unit operations.

Keywords: bacillus lipopeptides, membrane ultrafiltration, purification, RP-HPLC

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Authors: Juntao Li

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The metasurfaces for beam deflecting with gradient silicon posts in the square lattices were fabricated on the thin film crystal silicon with quartz substrate. By using the crystals silicon with high refractive index and high transmission to control the phase over 2π coverage, we demonstrated the polarization independent beam deflecting at wavelength of 532nm with 45% transmission in experiment and 70% in simulation into the desired angle. This simulation efficiency is almost close to the TiO2 metasurfaces but has higher refractive index and lower aspect ratio to reduce fabrication complexity. The result can extend the application of silicon metalsurfaces from 700 nm to 500 nm hence open a new way to use metasurfaces efficiently in visible light regime.

Keywords: metasurfaces, crystal silicon, light deflection, visible light

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Authors: Mustafa Sengul, Enes Sahin, Sertac Arslan

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Pumpjets are one of the marine propulsion systems frequently used in underwater vehicles nowadays. The reasons for frequent use of pumpjet as a propulsion system are that it has higher relative efficiency at high speeds, better cavitation, and acoustic performance than its rivals. Pumpjets are composed of rotor, stator, and duct, and there are two different types of pumpjet configurations depending on the desired hydrodynamic characteristic, which are with accelerating and decelerating duct. Pumpjet with an accelerating channel is used at cargo ships where it works at low speeds and high loading conditions. The working principle of this type of pumpjet is to maximize the thrust by reducing the pressure of the fluid through the channel and throwing the fluid out from the channel with high momentum. On the other hand, for decelerating ducted pumpjets, the main consideration is to prevent the occurrence of the cavitation phenomenon by increasing the pressure of the fluid about the rotor region. By postponing the cavitation, acoustic noise naturally falls down, so decelerating ducted systems are used at noise-sensitive vehicle systems where acoustic performance is vital. Therefore, duct design becomes a crucial step during pumpjet design. This study, it is aimed to optimize the duct geometry of a decelerating ducted pumpjet for a highly speed underwater vehicle by using proper optimization tools. The target output of this optimization process is to obtain a duct design that maximizes fluid pressure around the rotor region to prevent from cavitation and minimizes drag force. There are two main optimization techniques that could be utilized for this process which are parameter-based optimization and gradient-based optimization. While parameter-based algorithm offers more major changes in interested geometry, which makes user to get close desired geometry, gradient-based algorithm deals with minor local changes in geometry. In parameter-based optimization, the geometry should be parameterized first. Then, by defining upper and lower limits for these parameters, design space is created. Finally, by proper optimization code and analysis, optimum geometry is obtained from this design space. For this duct optimization study, a commercial codedparameter-based optimization algorithm is used. To parameterize the geometry, duct is represented with b-spline curves and control points. These control points have x and y coordinates limits. By regarding these limits, design space is generated.

Keywords: pumpjet, decelerating duct design, optimization, underwater vehicles, cavitation, drag minimization

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Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We present a taint analysis that can automatically detect when string operations result in a string that is free of taints, where all the tainted patterns have been removed. This is an improvement on the conservative behavior of previous taint analyzers, where a string operation on a tainted string always leads to a tainted string unless the operation is manually marked as a sanitizer. The taint analysis is built on top of a string analysis that uses finite state automata to approximate the sets of values that string variables can take during the execution of a program. The proposed approach has been implemented as an extension of FlowDroid and experimental results show that the resulting taint analyzer is much more precise than the original FlowDroid.

Keywords: android, static analysis, string analysis, taint analysis

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Authors: Mohamad Molavi Nojumi, Xiaodong Wang

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In this research fracture behaviour of linear elastic isotropic functionally graded materials (FGMs) are investigated using modified finite element method (FEM). FGMs are advantageous because they enhance the bonding strength of two incompatible materials, and reduce the residual stress and thermal stress. Ceramic/metals are a main type of FGMs. Ceramic materials are brittle. So, there is high possibility of crack existence during fabrication or in-service loading. In addition, damage analysis is necessary for a safe and efficient design. FEM is a strong numerical tool for analyzing complicated problems. Thus, FEM is used to investigate the fracture behaviour of FGMs. Here an accurate 9-node biquadratic quadrilateral graded element is proposed in which the influence of the variation of material properties is considered at the element level. The stiffness matrix of graded elements is obtained using the principle of minimum potential energy. The implementation of graded elements prevents the forced sudden jump of material properties in traditional finite elements for modelling FGMs. Numerical results are verified with existing solutions. Different numerical simulations are carried out to model stationary crack problems in nonhomogeneous plates. In these simulations, material variation is supposed to happen in directions perpendicular and parallel to the crack line. Two special linear and exponential functions have been utilized to model the material gradient as they are mostly discussed in literature. Also, various sizes of the crack length are considered. A major difference in the fracture behaviour of FGMs and homogeneous materials is related to the break of material symmetry. For example, when the material gradation direction is normal to the crack line, even under applying the mode I loading there exists coupled modes I and II of fracture which originates from the induced shear in the model. Therefore, the necessity of the proper modelling of the material variation should be considered in capturing the fracture behaviour of FGMs specially, when the material gradient index is high. Fracture properties such as mode I and mode II stress intensity factors (SIFs), energy release rates, and field variables near the crack tip are investigated and compared with results obtained using conventional homogeneous elements. It is revealed that graded elements provide higher accuracy with less effort in comparison with conventional homogeneous elements.

Keywords: finite element, fracture mechanics, functionally graded materials, graded element

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Authors: Masoomeh Alsadat Mirshafaei

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The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

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Authors: Yiwei Li, Boyu Tian, Mingyu Gao

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Hybrid main memory systems combine both performance and capacity advantages from heterogeneous memory technologies. With larger capacities, higher associativities, and finer granularities, hybrid memory systems currently exhibit significant metadata storage and lookup overheads for flexibly remapping data blocks between the two memory tiers. To alleviate the inefficiencies of existing designs, we propose Trimma, the combination of a multi-level metadata structure and an efficient metadata cache design. Trimma uses a multilevel metadata table to only track truly necessary address remap entries. The saved memory space is effectively utilized as extra DRAM cache capacity to improve performance. Trimma also uses separate formats to store the entries with non-identity and identity mappings. This improves the overall remap cache hit rate, further boosting the performance. Trimma is transparent to software and compatible with various types of hybrid memory systems. When evaluated on a representative DDR4 + NVM hybrid memory system, Trimma achieves up to 2.4× and on average 58.1% speedup benefits, compared with a state-of-the-art design that only leverages the unallocated fast memory space for caching. Trimma addresses metadata management overheads and targets future scalable large-scale hybrid memory architectures.

Keywords: memory system, data cache, hybrid memory, non-volatile memory

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Authors: Abdelaaty A. Shahat, Mansour S. Alsaid

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Four Acetylated flavonol glycosides were isolated from Centaurium spicatum (L.) Fritsch (Gentianaceae). Structure elucidation, especially the localization of the acetyl groups, and complete 1H and 13C NMR assignments of these biologically active compounds were carried out using one- and two-dimensional NMR methods, including CNMR, DEPT-135 and DEPT-90 and gradient-assisted experiments such as DQF-COSY, TOCSY, HSQC and HMBC experiments. The antioxidant activities of the new acetylated flavonoid glycosides using DPPH• assay were determined. The compounds tested showed a good DPPH• activity compared with control, but their activity was lower than that of their corresponding aglycone, quercetin.

Keywords: Centaurium spicatum, flavonoids, biological activity, isolation, glycosides

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Authors: Zouhair Issa Ahmed, Ahmed Abdulrasool Ahmed, Falah Hassan Abdulsada

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This paper presents a layout of a factory using Pro-Model simulation by choosing the best layout that gives the highest productivity and least work in process. The general problem is to find the best sequence in which jobs pass between the machines which are compatible with the technological constraints and optimal with respect to some performance criteria. The best simulation with Pro-Model program increased productivity and reduced work in process by balancing lines of production compared with the current layout of factory when productivity increased from 45 products to 180 products through 720 hours.

Keywords: scheduling, Pro-Model, simulation, balancing lines of production, layout planning, WIP

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Authors: Mohamed Amine El Hameur, Lyes Tarabet, Mahfoudh Cerdoun, Boubkr Zebiri, Giovanni Ferrara

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Due to the drastic environmental and energy regulations regarding the reduction of exhaust emissions and fuel consumption, added to the increasing demand for powerful performance, several automotive manufacturers are constantly obliged to redesign their existing products and/or develop novel powertrain techniques to respond to the aforementioned restrictions. In this aspect, an implemented approach is proposed in the present work to boost a 1.5 L, three-cylinder Diesel engine with a new turbocharger, based on 1D preliminary design codes, 3D design, and numerical assessment of a suitable radial turbine followed by an accurate selection procedure of an adequate centrifugal compressor. Furthermore, to investigate the effect of the turbine’s rotor position on the simulation convergence, stability, and calculation time; two combinations (rotor blade- volute) have been assessed. Consequently, significant results are obtained when comparing the original turbocharged engine and the new one at the engine’s full load and rated speed (@4500rpm) conditions. A maximum improvement in terms of brake-specific fuel consumption, thermal efficiency, total-to-static turbine efficiency, and total-to-total compressor efficiency equal 6.5% (corresponding to a decrease of 2.3 litre/hr in fuel consumption), 7%, 10.9%, and 19.9%, respectively.

Keywords: CFD investigation, engine boosting, turbine design, turbocharger, rotor blade positioning

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Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

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This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

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Authors: Xiao-Dong Wang, Wei-Mon Yan

Abstract:

The flow field design in the bipolar plates affects the performance of the proton exchange membrane (PEM) fuel cell. This work adopted a combined optimization procedure, including a simplified conjugate-gradient method and a completely three-dimensional, two-phase, non-isothermal fuel cell model, to look for optimal flow field design for a single serpentine fuel cell of size 9×9 mm with five channels. For the direct solution, the two-fluid method was adopted to incorporate the heat effects using energy equations for entire cells. The model assumes that the system is steady; the inlet reactants are ideal gases; the flow is laminar; and the porous layers such as the diffusion layer, catalyst layer and PEM are isotropic. The model includes continuity, momentum and species equations for gaseous species, liquid water transport equations in the channels, gas diffusion layers, and catalyst layers, water transport equation in the membrane, electron and proton transport equations. The Bulter-Volumer equation was used to describe electrochemical reactions in the catalyst layers. The cell output power density Pcell is maximized subjected to an optimal set of channel heights, H1-H5, and channel widths, W2-W5. The basic case with all channel heights and widths set at 1 mm yields a Pcell=7260 Wm-2. The optimal design displays a tapered characteristic for channels 1, 3 and 4, and a diverging characteristic in height for channels 2 and 5, producing a Pcell=8894 Wm-2, about 22.5% increment. The reduced channel heights of channels 2-4 significantly increase the sub-rib convection and widths for effectively removing liquid water and oxygen transport in gas diffusion layer. The final diverging channel minimizes the leakage of fuel to outlet via sub-rib convection from channel 4 to channel 5. Near-optimal design without huge loss in cell performance but is easily manufactured is tested. The use of a straight, final channel of 0.1 mm height has led to 7.37% power loss, while the design with all channel widths to be 1 mm with optimal channel heights obtained above yields only 1.68% loss of current density. The presence of a final, diverging channel has greater impact on cell performance than the fine adjustment of channel width at the simulation conditions set herein studied.

Keywords: optimization, flow field design, simplified conjugate-gradient method, serpentine flow field, sub-rib convection

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Authors: Taylan Kabbani, Ekrem Duman

Abstract:

The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

Procedia PDF Downloads 178