Search results for: ğarametric modeling

Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

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In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building, Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that this simplification would only lead to the error that is less than 7% for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which can cover most situations.

Keywords: building energy model, simulation, geometric simplification, design, regression

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Authors: Mayar A. Omar, Ismail Gomaa, Heba Badawy, Hosam Moubarak

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Enterprise resource planning (ERP) is an integrated system that helps companies in managing their resources. There are two types of ERP systems, traditional ERP systems and cloud ERP systems. Cloud ERP systems were introduced after the development of cloud computing technology. This research aims to identify the factors that affect the adoption of cloud ERP in Egyptian companies. Moreover, the aim of our study is to provide guidance to Egyptian companies in the cloud ERP adoption decision and to participate in increasing the number of cloud ERP studies that are conducted in the Middle East and in developing countries. There are many factors influencing the adoption of cloud ERP in Egyptian organizations, which are discussed and explained in the research. Those factors are examined by combining the diffusion of innovation theory (DOI) and technology-organization-environment framework (TOE). Data were collected through a survey that was developed using constructs from the existing studies of cloud computing and cloud ERP technologies and was then modified to fit our research. The analysis of the data was based on structural equation modeling (SEM) using Smart PLS software that was used for the empirical analysis of the research model.

Keywords: cloud computing, cloud ERP systems, DOI, Egypt, SEM, TOE

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Authors: Getachew Tilahun, Oluwole Makinde, David Malonza

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We propose and analyze a non-linear mathematical model for the transmission dynamics of pneumonia disease in a population of varying size. The deterministic compartmental model is studied using stability theory of differential equations. The effective reproduction number is obtained and also the local and global asymptotically stability conditions for the disease free and as well as for the endemic equilibria are established. The model exhibit a backward bifurcation and the sensitivity indices of the basic reproduction number to the key parameters are determined. Using Pontryagin’s maximum principle, the optimal control problem is formulated with three control strategies; namely disease prevention through education, treatment and screening. The cost effectiveness analysis of the adopted control strategies revealed that the combination of prevention and treatment is the most cost effective intervention strategies to combat the pneumonia pandemic. Numerical simulation is performed and pertinent results are displayed graphically.

Keywords: cost effectiveness analysis, optimal control, pneumonia dynamics, stability analysis, numerical simulation

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Authors: Yu-Lin Shen, Ming-Kuen Chang

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In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

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Authors: Fahad Alahmadi, Norhan Abd Rahman, Mohammad Abdulrazzak, Zulikifli Yusop

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Runoff prediction of ungauged catchment is still a challenging task especially in arid regions with a unique land cover such as volcanic basalt rocks where geological weathering and fractures are highly significant. In this study, Bathan catchment in Madinah western Saudi Arabia was selected for analysis. The aim of this paper is to evaluate different rainfall loss methods; soil conservation Services curve number (SCS-CN), green-ampt and initial-constant rate. Different direct runoff methods were evaluated: soil conservation services dimensionless unit hydrograph (SCS-UH), Snyder unit hydrograph and Clark unit hydrograph. The study showed the superiority of SCS-CN loss method and Clark unit hydrograph method for ungauged catchment where there is no observed runoff data.

Keywords: urban runoff modelling, arid regions, ungauged catchments, volcanic rocks, Madinah, Saudi Arabia

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Authors: Salem B. Abdalla

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This study investigated the current Building Information Modelling (BIM) trends and practices in the UAE, particularly to shed light on a recently circulated Dubai BIM mandate. Two sets of surveys were mailed to the AEC industry and the corresponding academic sector within the UAE to collect up-to-date data on BIM awareness and utilization. The surveys showed startling results concerning the academic sector in the UAE where almost 70% of respondents were not aware of the BIM mandate. Among the rest, even when aware, the majority of mechanical and electrical engineering schools felt that BIM is not pertinent to their discipline. Therefore, the response to offering BIM in their curriculum was substantially low (35%). On the other hand, the industrial survey identified a large majority (76.5%) of the AEC industry in the UAE are using BIM. The results clearly indicate that the academia should include BIM in their curriculum to produce qualified graduates to support the market. However, the academia is also faced with several obstacles to implement BIM in their curriculum, where the main pretext is that there is “no room for new courses in existing curriculum”.

Keywords: building information modeling, BIM adoption, UAE BIM industry survey, UAE BIM academia survey, Dubai BIM mandate, UK BIM mandate, BIM education, architecture education, engineering schools, BIM implementation, BIM curriculum

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Authors: Javad Abdi, Azam Famil Khalili

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Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

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Authors: Nermin Mahmoud Gohar, Aisha Tarek Noour

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Learner satisfaction has been a vital field of interest in the literature. Accordingly, the paper will explore the reasons behind individual differences in motivation and satisfaction. This study examines the effect of both; Herzberg’s and Maslow’s theories on learners satisfaction. A self-administered questionnaire was used to collect data from learners who were geographically widely spread around the College of Maritime Transport and Technology (CMTT) at the Arab Academy for Science, Technology and Maritime Transport (AAST&MT) in Egypt. One hundred and fifty undergraduates responded to a questionnaire survey. Respondents were drawn from two branches in Alexandria and Port Said. The data analysis used was SPSS 22 and AMOS 18. Factor analysis technique was used to find out the dimensions under study verified by Herzberg’s and Maslow’s theories. In addition, regression analysis and structural equation modeling were applied to find the effect of the above-mentioned theories on maritime transport learners’ satisfaction. Concerning the limitation of this study, it used the available number of learners in the CMTT due to the relatively low population in this field.

Keywords: motivation, satisfaction, needs, education, Herzberg’s and Maslow’s theories

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Authors: A. A. Okafor, C. H. Achebe, J. L. Chukwuneke, C. G. Ozoegwu

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The performance of an engine whose basic design parameters are known can be predicted with the assistance of simulation programs into the less time, cost and near value of actual. This paper presents a comprehensive mathematical model of the performance parameters of four stroke spark ignition engine. The essence of this research work is to develop a mathematical model for the analysis of engine performance parameters of four stroke spark ignition engine before embarking on full scale construction, this will ensure that only optimal parameters are in the design and development of an engine and also allow to check and develop the design of the engine and it’s operation alternatives in an inexpensive way and less time, instead of using experimental method which requires costly research test beds. To achieve this, equations were derived which describe the performance parameters (sfc, thermal efficiency, mep and A/F). The equations were used to simulate and optimize the engine performance of the model for various engine speeds. The optimal values obtained for the developed bivariate mathematical models are: sfc is 0.2833kg/kwh, efficiency is 28.77% and a/f is 20.75.

Keywords: bivariate models, engine performance, injector engine, optimization, performance parameters, simulation, spark ignition

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Authors: E. Dehghan, R. Dehghan

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Generally, the slender structural walls have flexural behavior. Since behavior of bending members can be explained by moment–curvature relation, therefore, an analytical model is proposed based on moment–curvature relation for slender structural walls. The moment–curvature relationships of RC sections are constructed through section analysis. Governing equations describing the bond-slip behavior in walls are derived and applied to moment–curvature relations. For the purpose of removing the imprecision in analytical results, the plastic hinge length is included in the finite element modeling. Finally, correlation studies between analytical and experimental results are conducted with the objective to establish the validity of the proposed algorithms. The results show that bond-slip effect is more significant in walls subjected to larger axial compression load. Moreover, preferable results are obtained when ultimate strain of concrete is assumed conservatively.

Keywords: nonlinear analysis, slender structural walls, moment-curvature relation, bond-slip, plastic hinge length

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Authors: Rubens P. Costa, Marcelo A. Leigui de Oliveira

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The comprehension of features on the energy spectra, the chemical compositions, and the origins of Ultra-High Energy Cosmic Rays (UHECRs) - mainly atomic nuclei with energies above ~1.0 EeV (exa-electron volts) - are intrinsically linked to the problem of determining the magnitude of their deflections in cosmic magnetic fields on cosmological scales. In addition, as they propagate from the source to the observer, modifications are expected in their original energy spectra, anisotropy, and the chemical compositions due to interactions with low energy photons and matter. This means that any consistent interpretation of the nature and origin of UHECRs has to include the detailed knowledge of their propagation in a three-dimensional environment, taking into account the magnetic deflections and energy losses. The parameter space range for the magnetic fields in the universe is very large because the field strength and especially their orientation have big uncertainties. Particularly, the strength and morphology of the Extragalactic Magnetic Fields (EGMFs) remain largely unknown, because of the intrinsic difficulty of observing them. Monte Carlo simulations of charged particles traveling through a simulated magnetized universe is the straightforward way to study the influence of extragalactic magnetic fields on UHECRs propagation. However, this brings two major difficulties: an accurate numerical modeling of charged particles diffusion in magnetic fields, and an accurate numerical modeling of the magnetized Universe. Since magnetic fields do not cause energy losses, it is important to impose that the particle tracking method conserve the particle’s total energy and that the energy changes are results of the interactions with background photons only. Hence, special attention should be paid to computational effects. Additionally, because of the number of particles necessary to obtain a relevant statistical sample, the particle tracking method must be computationally efficient. In this work, we present an analysis of the propagation of ultra-high energy charged particles in the intergalactic medium. The EGMFs are considered to be coherent within cells of 1 Mpc (mega parsec) diameter, wherein they have uniform intensities of 1 nG (nano Gauss). Moreover, each cell has its field orientation randomly chosen, and a border region is defined such that at distances beyond 95% of the cell radius from the cell center smooth transitions have been applied in order to avoid discontinuities. The smooth transitions are simulated by weighting the magnetic field orientation by the particle's distance to the two nearby cells. The energy losses have been treated in the continuous approximation parameterizing the mean energy loss per unit path length by the energy loss length. We have shown, for a particle with the typical energy of interest the integration method performance in the relative error of Larmor radius, without energy losses and the relative error of energy. Additionally, we plotted the distance amplification from rectilinear propagation as a function of the traveled distance, particle's magnetic rigidity, without energy losses, and particle's energy, with energy losses, to study the influence of particle's species on these calculations. The results clearly show when it is necessary to use a full three-dimensional simulation.

Keywords: cosmic rays propagation, extragalactic magnetic fields, magnetic deflections, ultra-high energy

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Authors: S. O. Oyamakin, A. U. Chukwu,

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We proposed a Hyperbolic Gompertz Growth Model (HGGM), which was developed by introducing a stabilizing parameter called θ using hyperbolic sine function into the classical gompertz growth equation. The resulting integral solution obtained deterministically was reprogrammed into a statistical model and used in modeling the height and diameter of Pines (Pinus caribaea). Its ability in model prediction was compared with the classical gompertz growth model, an approach which mimicked the natural variability of height/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using goodness of fit tests and model selection criteria. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the compliance of the error term to normality assumptions while using testing the independence of the error term using the runs test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic gompertz growth models better than the source model (classical gompertz growth model) while the results of R2, Adj. R2, MSE, and AIC confirmed the predictive power of the Hyperbolic Monomolecular growth models over its source model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, gompertz

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Authors: Mohieddine Benghersallah, Mohamed Zakaria Zahaf, Ali Medjber, Idriss Tibakh

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The objective of this study is to analyse the effects of cutting parameters on surface roughness in dry face milling using statistical techniques. We studied the effect of the microstructure of AISI 52100 steel on machinability before and after hardening. The machining tests were carried out on a high rigidity vertical milling machine with a 25 mm diameter face milling cutter equipped with micro-grain bicarbide inserts with PVD (Ti, AlN) coating in GC1030 grade. A Taguchi L9 experiment plan is adopted. Analysis of variance (ANOVA) was used to determine the effects of cutting parameters (Vc, fz, ap) on the roughness (Ra) of the machined surface. Regression analysis to assess the machinability of steel presented mathematical models of roughness and the combination of parameters to minimize it. The recorded results show that feed per tooth has the most significant effect on the surface condition for both steel treatment conditions. The best roughnesses were obtained for the hardened AISI 52100 steel.

Keywords: machinability, heat treatment, microstructure, surface roughness, Taguchi method

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Tseng-Lung Huang

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Sensory breadth experiences, such as visualization, a sense of self-location, and haptic experiences, are critical in an online try-on environment. This research adopts an emotional appeal perspective, including concrete and abstract effects, to clarify the relationship between sensory experience and consumer's behavior intention in an online try-on context. This study employed an augmented reality interactive technology (ARIT) in an online clothes-fitting context and applied snowball sampling using e-mail to invite online consumers, first to use ARIT for trying on online apparel and then to complete a questionnaire. One hundred sixty-eight valid questionnaires were collected, and partial least squares (PLS) path modeling was used to test our hypotheses. The results showed that sensory breadth, by arousing concrete effect, induces impulse buying intention and willingness to pay a price premium of online shopping. Parasocial presence, as an abstract effect, diminishes the effect of concrete effects on willingness to pay a price premium.

Keywords: sensory breadth, impulsive behavior, price premium, emotional appeal, online try-on context

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Authors: Rajwanlop Kumpoopong, Sukit Yindeesuk, Pornchai Silarom

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Modeling cracks in concrete is complicated by its strain-softening behavior which requires the use of sophisticated energy criteria of fracture mechanics to assure stable and convergent solutions in the finite-element (FE) analysis particularly for relatively large structures. However, for small-scale structures such as beams and slabs, a simpler approach relies on retaining some shear stiffness in the cracking plane has been adopted in literature to model the strain-softening behavior of concrete under monotonically increased loading. According to the shear retaining approach, each element is assumed to be an isotropic material prior to cracking of concrete. Once an element is cracked, the isotropic element is replaced with an orthotropic element in which the new orthotropic stiffness matrix is formulated with respect to the crack orientation. The shear transfer factor of 0.5 is used in parallel to the crack plane. The shear retaining approach is adopted in this research to model cracks in RC bridge deck with some modifications to take into account the effect of repetitive moving truck wheel loads as they cause fatigue cracking of concrete. First modification is the introduction of fatigue tests of concrete and reinforcing steel and the Palmgren-Miner linear criterion of cumulative damage in the conventional FE analysis. For a certain loading, the number of cycles to failure of each concrete or RC element can be calculated from the fatigue or S-N curves of concrete and reinforcing steel. The elements with the minimum number of cycles to failure are the failed elements. For the elements that do not fail, the damage is accumulated according to Palmgren-Miner linear criterion of cumulative damage. The stiffness of the failed element is modified and the procedure is repeated until the deck slab fails. The total number of load cycles to failure of the deck slab can then be obtained from which the S-N curve of the deck slab can be simulated. Second modification is the modification in shear transfer factor. Moving loading causes continuous rubbing of crack interfaces which greatly reduces shear transfer mechanism. It is therefore conservatively assumed in this study that the analysis is conducted with shear transfer factor of zero for the case of moving loading. A customized FE program has been developed using the MATLAB software to accomodate such modifications. The developed procedure has been validated with the fatigue test of the 1/6.6-scale AASHTO bridge deck under the applications of both fixed-point repetitive loading and moving loading presented in the literature. Results are in good agreement both experimental vs. simulated S-N curves and observed vs. simulated crack patterns. Significant contribution of the developed procedure is a series of S-N relations which can now be simulated at any desired levels of cracking in addition to the experimentally derived S-N relation at the failure of the deck slab. This permits the systematic investigation of crack propagation or deterioration of RC bridge deck which is appeared to be useful information for highway agencies to prolong the life of their bridge decks.

Keywords: bridge deck, cracking, deterioration, fatigue, finite-element, moving truck, reinforced concrete

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Authors: Seyed Amin Vakili, Sahar Sadat Vakili, Seyed Ehsan Vakili, Nader Abdoli Yazdi

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The purpose of this article is to analyze the finite displacement of Columns by applying the Modified Newmark Method. This research will be performed on Columns subjected to compressive axial load, therefore the non-linearity of the geometry is also considered. If the considered strut is perfect, the governing differential equation contains a branching point in the solution path. Investigation into the Elastica is a part of generalizing the developed method. It presents the ability of the Modified Newmark Method in treating non-linear differential equations Derived from elastic strut stability problems. These include not only an approximate polynomial solution for the Elastica problems, but can also recognize the branching point and the stable solution. However, this investigation deals with the post-buckling response of elastic and pin ended columns subjected to central or equally eccentric axial loads.

Keywords: columns, structural modeling, structures & structural stability, loads

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Authors: S. R. Nikhashemi, Laily Haj Paim, Ali Khatibi

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Structural Equation Modeling (SEM) was used to test a hypothesized model explaining Malaysian hypermarket customers’ perceptions of brand trust (BT), customer perceived value (CPV) and perceived service quality (PSQ) on building their brand loyalty (CBL) and generating positive word-of-mouth communication (WOM). Self-administered questionnaires were used to collect data from 374 Malaysian hypermarket customers from Mydin, Tesco, Aeon Big and Giant in Kuala Lumpur, a metropolitan city of Malaysia. The data strongly supported the model exhibiting that BT, CPV and PSQ are prerequisite factors in building customer brand loyalty, while PSQ has the strongest effect on prediction of customer brand loyalty compared to other factors. Besides, the present study suggests the effect of the aforementioned factors via customer brand loyalty strongly contributes to generate positive word of mouth communication.

Keywords: brand trust, perceived value, Perceived Service Quality, Brand loyalty, positive word of mouth communication

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Authors: Mohamed Khallaf, Hossein M Rizeei

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Simulating wind pattern behavior over proposed urban features is critical in the early stage of the conceptual design of both architectural and urban disciplines. However, it is typically not possible for designers to explore the impact of wind flow profiles across new urban developments due to a lack of real data and inaccurate estimation of building parameters. Modeling the details of existing and proposed urban features and testing them against wind flows is the missing part of the conceptual design puzzle where architectural and urban discipline can focus. This research aims to develop a spatial decision-support design method utilizing LiDAR, GIS, and performance-based wind simulation technology to mitigate wind-related hazards on a design by simulating alternative design scenarios at the pedestrian level prior to its implementation in Sydney, Australia. The result of the experiment demonstrates the capability of the proposed framework to improve pedestrian comfort in relation to wind profile.

Keywords: spatial decision-support design, performance-based wind simulation, LiDAR, GIS

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Authors: Ramin Shadani

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This study introduces adaptive performance as a key organizational performance dimension and explores the relationship between the dimensions of a learning organization and adaptive performance. A survey was therefore conducted using the dimensions of the Learning Organization Questionnaire (DLOQ), followed by factor analysis and structural equation modeling in order to investigate the dynamics between learning organization practices and adaptive performance. Results confirm that adaptive performance is indeed one important dimension of organizational performance. The study also shows that perceived knowledge and adaptive performance mediate the positive relationship between the practices of a learning organization with perceived financial performance. We extend existing DLOQ research by demonstrating that adaptive performance, as a nonfinancial organizational learning outcome, has a significant impact on financial performance. Our study also provides additional validation of the measures of DLOQ's performance. Indeed, organizations need to take a glance at how the activities of learning and development can provide better overall improvement in performance, especially in enhancing adaptive capability. The study has provided requisite empirical support that activities of learning and development within organizations allow much-improved intangible performance outcomes, especially through adaptive performance.

Keywords: adaptive performance, continuous learning, financial performance, leadership style, organizational learning, organizational performance

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Authors: Mohammad Moonesun, Ehsan Asadi Asrami, Julia Bodnarchuk

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In the case of Solar Autonomous Underwater Vehicle, which uses photovoltaic panels to provide its required power, due to limitation of energy, accurate estimation of resistance and energy has major sensitivity. In this work, hydrodynamic calculations by numerical method for a solar autonomous underwater vehicle equipped by two 50 W photovoltaic panels has been studied. To evaluate the required power and energy, hull hydrodynamic resistance in several velocities should be taken into account. To do this assessment, the ANSYS FLUENT 18 applied as Computational Fluid Dynamics (CFD) tool that solves Reynolds Average Navier Stokes (RANS) equations around AUV hull, and K-ω SST is used as turbulence model. To validate of solution method and modeling approach, the model of Myring submarine that it’s experimental data was available, is simulated. There is good agreement between numerical and experimental results. Also, these results showed that the K-ω SST Turbulence model is an ideal method to simulate the AUV motion in low velocities.

Keywords: underwater vehicle, hydrodynamic resistance, numerical modelling, CFD, RANS

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Authors: Tomas Linas Šepetys

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In online content-sharing service platforms, the ability of creators to restrict illicit use of audiovisual creative works has effectively been abolished, largely due to specific infrastructure where a huge volume of copyrighted audiovisual content can be made available to the public. The European Union legislator has attempted to strengthen the positions of creators in the realm of online content-sharing services. Article 17 of the new Digital Single Market Directive considers online content-sharing service providers to carry out acts of communication to the public of any creative content uploaded to their platforms by users and posits requirements to obtain licensing agreements. While such regulation intends to assert authors‘ ability to effectively control the dissemination of their creative works, it also creates threats of parody content overblocking through automated content monitoring. Such potentially paradoxical outcome of the efforts of the EU legislator to deliver economic safeguards for the creators in the online content-sharing service platforms leads to presume lack of informity on legislator‘s part regarding creative works‘ economic exploitation opportunities provided to creators in the online content-sharing infrastructure. Analysis conducted in this scientific research discloses that the aforementioned irregularities of parody and other creative content dissemination are caused by EU legislators‘ lack of assessment of value extraction conditions for parody creators in the online content-sharing service platforms. Historical and modeling research method application reveals the existence of two creative content dissemination models and their unique mechanisms of commercial value creation. Obligations to obtain licenses and liability over creative content uploaded to their platforms by users set in Article 17 of the Digital Single Market Directive represent technological replication of the proprietary dissemination model where the creator is able to restrict access to creative content apart from licensed retail channels. The online content-sharing service platforms represent an open dissemination model where the economic potential of creative content is based on the infrastructure of unrestricted access by users and partnership with advertising services offered by the platform. Balanced modeling of proprietary dissemination models in such infrastructure requires not only automated content monitoring measures but also additional regulatory monitoring solutions to separate parody and other types of creative content. An example of the Digital Single Market Directive proves that regulation can dictate not only the technological establishment of a proprietary dissemination model but also a partial reduction of the open dissemination model and cause a disbalance between the economic interests of creators relying on such models. The results of this scientific research conclude an informative role of the creative works dissemination model in the EU copyright law modernization process. A thorough understanding of the commercial prospects of the open dissemination model intrinsic to the online content-sharing service platform structure requires and encourages EU legislators to regulate safeguards for parody content dissemination. Implementing such safeguards would result in a common application of proprietary and open dissemination models in the online content-sharing service platforms and balanced protection of creators‘ economic interests explicitly based on those creative content dissemination models.

Keywords: copyright law, creative works dissemination model, digital single market directive, online content-sharing services

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Authors: Saeb Ahmadi, Mohsen Vafaie Sefti, Mohammad Mahdi Shadman, Ebrahim Tangestani

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Carbon nanotube has shown great potential for the removal of various inorganic and organic components due to properties such as large surface area and high adsorption capacity. Central composite design is widely used method for determining optimal conditions. Also due to the economic reasons and wide application, the rare earth elements are important components. The analyses of cerium (Ce(III)) adsorption as one of the Rare Earth Elements (REEs) adsorption on Multiwall Carbon Nanotubes (MWCNTs) have been studied. The optimization process was performed using Response Surface Methodology (RSM). The optimum amount conditions were pH of 4.5, initial Ce (III) concentration of 90 mg/l and MWCNTs dosage of 80 mg. Under this condition, the optimum adsorption percentage of Ce (III) was obtained about 96%. Next, at the obtained optimum conditions the kinetic and isotherm studied and result showed the pseudo-second order and Langmuir isotherm are more fitted with experimental data than other models.

Keywords: cerium, rare earth element, MWCNTs, adsorption, optimization

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Authors: Elham Rezaee, Sayyed Abbas Tabatabai

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Dual inhibition of COX-2 and sEH enzymes represents one of the distinct pharmaceutical approaches for the treatment of inflammation, pain, cancers, and other diseases. The discovery of these inhibitors for treatment is a great deal of attention because of some advantages such as increased efficacy, a promising safety profile, ease of formulation, and better target engagement. In this research, based on the structure-activity relationship of COX-2 and sEH inhibitors, some amide derivatives with oxadiazole and dihydropyrimidinone rings against sEH and COX-2 enzymes were developed. The designed compounds showed high affinity to the active site of both enzymes in docking studies and were synthesized in good yield and characterized by IR, Mass, 1HNMR, and 13CNMR. All of the novel compounds exhibited considerable in-vitro sEH and COX-2 inhibitory activities in comparison with 12-(3-Adamantan-1-yl-ureido)- dodecanoic acid and celecoxib (a potent urea-based sEH inhibitor and selective nonsteroidal anti-inflammatory drug, respectively). Ethyl 6-methyl-4-(4-(4-(methylsulfonyl)benzamido)phenyl)-2-oxo-1,2,3,4-tetrahydropyrimidine-5-carboxylate was found to be the most selective COX-2 inhibitor (COX-2/COX-1 ratio: 683) with IC50 value of 2.1 nM targeting sEH enzyme.

Keywords: COX-2, dual inhibitors, sEH, synthesis

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Authors: Neeta Kumari, Gopal Pathak

Abstract:

Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Fatemeh Keivanifard

Abstract:

E-learning is becoming increasingly prominent in higher education, with universities increasing provision and more students signing up. This paper examines factors that predict students' attitudes to adapt e-learning at the Khuzestan province Iran. Understanding the nature of these factors may assist these universities in promoting the use of information and communication technology in teaching and learning. The main focus of the paper is on the university students, whose decision supports effective implementation of e-learning. Data was collected through a survey of 300 post graduate students at the University of dezful, shooshtar and chamran in Khuzestan. The technology adoption model put forward by Davis is utilized in this study. Two more independent variables are added to the original model, namely, the pressure to act and resources availability. The results show that there are five factors that can be used in modeling students' attitudes to adapt e-learning. These factors are intention toward e-learning, perceived usefulness of e-learning, perceived ease of e-learning use, pressure to use e-learning, and the availability of resources needed to use e-learning.

Keywords: e-learning, intention, ease of use, pressure to use, usefulness

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Authors: Dhaladhuli Pranavi, Amirtham Rajagopal

Abstract:

There are various failure modes in ceramic matrix composites; notable ones are fiber breakage, matrix cracking and fiber matrix debonding. Crack nucleation and propagation in microstructure of such composites requires an understanding of interaction of crack with the multiple inclusion heterogeneous system and interfaces. In order to assess structural integrity, the material parameters especially of the interface that governs the crack growth should be determined. In the present work, a nonlocal phase field approach is proposed to model the crack interface interaction in such composites. Nonlocal approaches help in understanding the complex mechanisms of delamination growth and mitigation and operates at a material length scale. The performance of the proposed formulation is illustrated through representative numerical examples. The model proposed is implemented in the framework of the finite element method. Several parametric studies on interface crack interaction are conducted. The proposed model is easy and simple to implement and works very well in modeling fracture in composite systems.

Keywords: composite, interface, nonlocal, phase field

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Authors: Sukhbir Singh

Abstract:

This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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Authors: Mohammed Ali Hadj Ammar, Fethi Bouras, Kamel Sahlaoui

Abstract:

This article presents a detailed study of two working pairs intended for use in solar adsorption refrigeration (SAR) system. The study was based on two indicators: the daily production and coefficient of performance (COP). The thermodynamic cycle of the system is based on the adsorption phenomena at a constant temperature. A computer simulation program has been developed for modeling and performance evaluation for the solar-powered adsorption refrigeration cycle. It was found that maximal cycled mass is obtained by S40/water (0.280kg/kg) followed by CarboTech C40/1/methanol (0.260kg/kg). At a condenser temperature of 30°C, with an adsorbent mass of 38.59 kg, and an integrated collector/bed configuration, the couple CarboTech C40/1/methanol for the ice-maker purpose can reach cycle COP of 0.63 and can produce about 13.6kg ice per day, while the couple S40/water for the air-conditioning can reach cycle COP of 0.66 and 212kg as daily cold-water production. Additionally, adequate indicators are evaluated addressing the economic and environmental associated with each working pair.

Keywords: solar adsorption, refrigeration, activated carbon, silica gel

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Authors: Darwin Junnior Sabino Diego, Brando Burgos Guerrero, Diego Arroyo Villanueva

Abstract:

Additive manufacturing, commonly known as 3D printing, has revolutionized modern manufacturing by enabling the agile creation of complex objects. However, challenges persist in the consistency and quality of printed parts, particularly in their mechanical properties. This study focuses on addressing these challenges through the optimization of printing parameters in FDM technology, using Machine Learning techniques. Our aim is to improve the mechanical properties of printed objects by optimizing parameters such as speed, temperature, and orientation. We implement a methodology that combines experimental data collection with Machine Learning algorithms to identify relationships between printing parameters and mechanical properties. The results demonstrate the potential of this methodology to enhance the quality and consistency of 3D printed products, with significant applications across various industrial fields. This research not only advances understanding of additive manufacturing but also opens new avenues for practical implementation in industrial settings.

Keywords: 3D printing, additive manufacturing, machine learning, mechanical properties

Procedia PDF Downloads 49