Search results for: 3D Modeling

Authors: Isaac O. Asante, Yushi Jiang, Hailin Tao

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Livestreaming marketing, the new electronic commerce element, has become an optional marketing channel following the COVID-19 pandemic, and many sellers are leveraging the features presented by livestreaming to increase sales. This study was conducted to measure real-time observable interactions between consumers and sellers. Based on the affordance theory, this study conceptualized constructs representing the interactive features and examined how they drive consumers’ purchase willingness during livestreaming sessions using 1238 datasets from Amazon Live, following the manual observation of transaction records. Using structural equation modeling, the ordinary least square regression suggests that live viewers, new followers, live chats, and likes positively affect purchase willingness. The Sobel and Monte Carlo tests show that new followers, live chats, and likes significantly mediate the relationship between live viewers and purchase willingness. The study presents a way of measuring interactions in livestreaming commerce and proposes a way to manually gather data on consumer behaviors in livestreaming platforms when the application programming interface (API) of such platforms does not support data mining algorithms.

Keywords: Livestreaming marketing, live chats, live viewers, likes, new followers, purchase willingness.

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Authors: M. Orefice, V. Di Vito

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This paper provides a description of a Collision Avoidance algorithm that has been developed starting from the mathematical modeling of the flight of insects, in terms of spirals and conchospirals geometric paths. It is able to calculate a proper avoidance manoeuver aimed to prevent the infringement of a predefined distance threshold between ownship and the considered intruder, while minimizing the ownship trajectory deviation from the original path and in compliance with the aircraft performance limitations and dynamic constraints. The algorithm is designed in order to be suitable for real-time applications, so that it can be considered for the implementation in the most recent airborne automatic collision avoidance systems using the traffic data received through an ADS-B IN device. The presented approach is able to take into account the rules-of-the-air, due to the possibility to select, through specifically designed decision making logic based on the consideration of the encounter geometry, the direction of the calculated collision avoidance manoeuver that allows complying with the rules-of-the-air, as for instance the fundamental right of way rule. In the paper, the proposed collision avoidance algorithm is presented and its preliminary design and software implementation is described. The applicability of this method has been proved through preliminary simulation tests performed in a 2D environment considering single intruder encounter geometries, as reported and discussed in the paper.

Keywords: collision avoidance, RPAS, spiral geometry, ADS-B based application

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Authors: W. Katsarapong, W. Srisang, K. Jaroensutasinee, M. Jaroensutasinee

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National Biodiversity Database System (NBIDS) has been developed for collecting Thai biodiversity data. The goal of this project is to provide advanced tools for querying, analyzing, modeling, and visualizing patterns of species distribution for researchers and scientists. NBIDS data record two types of datasets: biodiversity data and environmental data. Biodiversity data are specie presence data and species status. The attributes of biodiversity data can be further classified into two groups: universal and projectspecific attributes. Universal attributes are attributes that are common to all of the records, e.g. X/Y coordinates, year, and collector name. Project-specific attributes are attributes that are unique to one or a few projects, e.g., flowering stage. Environmental data include atmospheric data, hydrology data, soil data, and land cover data collecting by using GLOBE protocols. We have developed webbased tools for data entry. Google Earth KML and ArcGIS were used as tools for map visualization. webMathematica was used for simple data visualization and also for advanced data analysis and visualization, e.g., spatial interpolation, and statistical analysis. NBIDS will be used by park rangers at Khao Nan National Park, and researchers.

Keywords: GLOBE protocol, Biodiversity, Database System, ArcGIS, Google Earth and webMathematica.

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Authors: Madhusudan Purohit, Stephen Philip, Bharathkumar Inturi

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In this paper we report the quantitative structure activity relationship of novel bis-triazole derivatives for predicting the activity profile. The full model encompassed a dataset of 46 Bis- triazoles. Tripos Sybyl X 2.0 program was used to conduct CoMSIA QSAR modeling. The Partial Least-Squares (PLS) analysis method was used to conduct statistical analysis and to derive a QSAR model based on the field values of CoMSIA descriptor. The compounds were divided into test and training set. The compounds were evaluated by various CoMSIA parameters to predict the best QSAR model. An optimum numbers of components were first determined separately by cross-validation regression for CoMSIA model, which were then applied in the final analysis. A series of parameters were used for the study and the best fit model was obtained using donor, partition coefficient and steric parameters. The CoMSIA models demonstrated good statistical results with regression coefficient (r²) and the cross-validated coefficient (q²) of 0.575 and 0.830 respectively. The standard error for the predicted model was 0.16322. In the CoMSIA model, the steric descriptors make a marginally larger contribution than the electrostatic descriptors. The finding that the steric descriptor is the largest contributor for the CoMSIA QSAR models is consistent with the observation that more than half of the binding site area is occupied by steric regions.

Keywords: 3D QSAR, CoMSIA, Triazoles.

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Authors: Mohammed Kamil, M. M. Rahman, Rosli A. Bakar

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Modeling of hydrogen fueled engine (H₂ICE) injection system is a very important tool that can be used for explaining or predicting the effect of advanced injection strategies on combustion and emissions. In this paper, a common rail injection system (CRIS) is proposed for 4-strokes 4-cylinders hydrogen fueled engine with port injection feeding system (PIH₂ICE). For this system, a numerical one-dimensional gas dynamic model is developed considering single injection event for each injector per a cycle. One-dimensional flow equations in conservation form are used to simulate wave propagation phenomenon throughout the CR (accumulator). Using this model, the effect of common rail on the injection system characteristics is clarified. These characteristics include: rail pressure, sound velocity, rail mass flow rate, injected mass flow rate and pressure drop across injectors. The interaction effects of operational conditions (engine speed and rail pressure) and geometrical features (injector hole diameter) are illustrated; and the required compromised solutions are highlighted. The CRIS is shown to be a promising enhancement for PIH₂ICE.

Keywords: Common rail, hydrogen engine, port injection, wave propagation.

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Authors: N. Neysani Samany, M.R. Delavar, N. Chrisman, M.R. Malek

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Location-aware computing is a type of pervasive computing that utilizes user-s location as a dominant factor for providing urban services and application-related usages. One of the important urban services is navigation instruction for wayfinders in a city especially when the user is a tourist. The services which are presented to the tourists should provide adapted location aware instructions. In order to achieve this goal, the main challenge is to find spatial relevant objects and location-dependent information. The aim of this paper is the development of a reusable location-aware model to handle spatial relevancy parameters in urban location-aware systems. In this way we utilized ontology as an approach which could manage spatial relevancy by defining a generic model. Our contribution is the introduction of an ontological model based on the directed interval algebra principles. Indeed, it is assumed that the basic elements of our ontology are the spatial intervals for the user and his/her related contexts. The relationships between them would model the spatial relevancy parameters. The implementation language for the model is OWLs, a web ontology language. The achieved results show that our proposed location-aware model and the application adaptation strategies provide appropriate services for the user.

Keywords: Spatial relevancy, Context-aware, Ontology, Modeling

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Authors: Yu Shi, Rong Liu, Jingyun Lv

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Compression textiles with ergonomic-fit and controllable pressure performance have demonstrated positive effect on prevention and treatment of chronic venous insufficiency (CVI). Well-designed compression textile products contribute to improving user compliance in their daily application. This study explored the effects of multiple knitting variables (yarn-machinery settings) on the physical-mechanical properties and the produced pressure magnitudes of tubular compression fabrics (TCFs) through experimental testing and multiple regression modeling. The results indicated that fabric physical (stitch densities and circumference) and mechanical (tensile) properties were affected by the linear density of inlay yarns, which, to some extent, influenced pressure magnitudes of the TCFs. Knitting variables (e.g., feeding velocity of inlay yarns and loop size settings) can alter circumferences and tensile properties of tubular fabrics, respectively, and significantly varied pressure values of the TCFs. This study enhanced the understanding of the effects of knitting factors on pressure controlling of TCFs, thus facilitating dimension and pressure design of compression textiles in future development.

Keywords: Laid-in knitted fabric, yarn-machinery settings, pressure magnitudes, quantitative analysis, compression textiles.

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition (HAR) modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view Football datasets. Our HAR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH Multi-view Football datasets, respectively.

Keywords: Computer vision, human motion analysis, random forest, machine learning.

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Authors: John Kabuba, Antoine Mulaba-Bafubiandi, Kim Battle

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This paper presents a critical study about the application of Neural Networks to ion-exchange process. Ionexchange is a complex non-linear process involving many factors influencing the ions uptake mechanisms from the pregnant solution. The following step includes the elution. Published data presents empirical isotherm equations with definite shortcomings resulting in unreliable predictions. Although Neural Network simulation technique encounters a number of disadvantages including its “black box", and a limited ability to explicitly identify possible causal relationships, it has the advantage to implicitly handle complex nonlinear relationships between dependent and independent variables. In the present paper, the Neural Network model based on the back-propagation algorithm Levenberg-Marquardt was developed using a three layer approach with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and linear transfer function (purelin) at out layer. The above mentioned approach has been used to test the effectiveness in simulating ion exchange processes. The modeling results showed that there is an excellent agreement between the experimental data and the predicted values of copper ions removed from aqueous solutions.

Keywords: Copper, ion-exchange process, neural networks, simulation

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Authors: L. L. Ivy-Yap, H. A. Bekhet

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As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-2011 period. Unlike previous studies on Malaysia, the current study focuses on the residential sector, a sector that is important for the contemplation of energy policy. The Phillips-Perron (P-P) unit root test is employed to infer the stationarity of each variable while the bound test is executed to determine the existence of co-integration relationship among the variables, modelled in an Autoregressive Distributed Lag (ARDL) framework. The CUSUM and CUSUM of squares tests are applied to ensure the stability of the model. The results suggest the existence of long-run equilibrium relationship and bidirectional Granger causality between EC and the macroeconomic variables. The empirical findings will help policy makers of Malaysia in developing new monitoring standards of energy consumption. As it is the major contributing factor in economic growth and CO₂ emission, there is a need for more proper planning in Malaysia to attain future targets in order to cut emissions.

Keywords: Co-integration, Elasticity, Granger causality, Malaysia, Residential electricity consumption.

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Authors: K. Mushtaq, M. Umar

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The research aims to study the association between job satisfaction, motivation and the five factors of organizational citizenship behavior (i.e. Altruism, Conscientiousness, Sportsmanship, Courtesy and Civic virtue) among Public Sector Employees in Pakistan. In this research Structure Equation Modeling with confirmatory factor analysis was used to test the relationship between two independent and five dependent variables. Data was collected through questionnaire survey from 152 Public Servants Working in Gujrat District-Pakistan in different capacities. Stratified Random Sampling Technique was used to conduct this survey. The results of the study indicate that five factors of OCB have positive significant relation with both motivation and job satisfaction except the relationship of Civic Virtue with Motivation. The research findings implicate that factors other than motivation and job satisfaction may also affect OCB. Likewise, all the five factors of OCB may not be present in all populations. Thus, Managers must concentrate on increasing motivation and job satisfaction to increase OCB. Furthermore, the present research gives a direction to future researchers to use more independent variables (e.g. Culture, leadership, workplace environment, various job attitudes, types of motivation, etc.) on different types of populations with larger sample size in order to find the reasons behind insignificant relationship of civic virtue with Motivation in the research in hand and to generalize the tested model.

Keywords: Five Factors of Organizational Citizenship Behavior (OCB), Motivation, Job Satisfaction, Public Sector Employees in Pakistan.

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Authors: Jinliang Yuan, Jong-Sung Yu, Bengt Sundén

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A computational fluid dynamics (CFD) model is developed for rechargeable non-aqueous electrolyte lithium-air batteries with a partial opening for oxygen supply to the cathode. Multi-phase transport phenomena occurred in the battery are considered, including dissolved lithium ions and oxygen gas in the liquid electrolyte, solid-phase electron transfer in the porous functional materials and liquid-phase charge transport in the electrolyte. These transport processes are coupled with the electrochemical reactions at the active surfaces, and effects of discharge reaction-generated solid Li2O2 on the transport properties and the electrochemical reaction rate are evaluated and implemented in the model. The predicted results are discussed and analyzed in terms of the spatial and transient distribution of various parameters, such as local oxygen concentration, reaction rate, variable solid Li2O2 volume fraction and porosity, as well as the effective diffusion coefficients. It is found that the effect of the solid Li2O2 product deposited at the solid active surfaces is significant on the transport phenomena and the overall battery performance.

Keywords: Computational Fluid Dynamics (CFD), Modeling, Multi-phase, Transport Phenomena, Lithium-air battery.

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Authors: Ahmed M. Hemeida, Wael A. Farag, Osama A. Mahgoub

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This paper focuses on developing an integrated reliable and sophisticated model for ultra large wind turbines And to study the performance and analysis of vector control on large wind turbines. With the advance of power electronics technology, direct driven multi-pole radial flux PMSG (Permanent Magnet Synchronous Generator) has proven to be a good choice for wind turbines manufacturers. To study the wind energy conversion systems, it is important to develop a wind turbine simulator that is able to produce realistic and validated conditions that occur in real ultra MW wind turbines. Three different packages are used to simulate this model, namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind simulator developed by National Renewable Energy Laboratory (NREL). The wind turbine mechanical parts are modeled by FAST (Fatigue, Aerodynamics, Structures and Turbulence) code which is also developed by NREL. Simulink is used to model the PMSG, full scale back to back IGBT converters, and the grid.

Keywords: FAST, Permanent Magnet Synchronous Generator(PMSG), TurbSim, Vector Control and Pitch Control

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Authors: S. Deswal, M. Pal

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The paper aims to compare the performance of vertical and inclined multiple plunging jets and to model and predict their mass transfer capacity by multi-linear regression based approach. The multiple vertical plunging jets have jet impact angle of θ = 90^O; whereas, multiple inclined plunging jets have jet impact angle of θ = 60^O. The results of the study suggests that mass transfer is higher for multiple jets, and inclined multiple plunging jets have up to 1.6 times higher mass transfer than vertical multiple plunging jets under similar conditions. The derived relationship, based on multi-linear regression approach, has successfully predicted the volumetric mass transfer coefficient (K_La) from operational parameters of multiple plunging jets with a correlation coefficient of 0.973, root mean square error of 0.002 and coefficient of determination of 0.946. The results suggests that predicted overall mass transfer coefficient is in good agreement with actual experimental values; thereby, suggesting the utility of derived relationship based on multi-linear regression based approach and can be successfully employed in modeling mass transfer by multiple plunging jets.

Keywords: Mass transfer, multiple plunging jets, multi-linear regression.

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Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an Artificial Neural Network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study include granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R2), Root Mean Square Error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: National development, granite, profitability assessment, ANN models.

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Authors: Mutuku Muvengei, John Kihiu

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In this paper, a bond graph dynamic model for a valvecontrolled hydraulic cylinder has been developed. A simplified bond graph model of the inter-actuator interactions in a multi-cylinder hydraulic system has also been presented. The overall bond graph model of a valve-controlled hydraulic cylinder was developed by combining the bond graph sub-models of the pump, spool valve and the actuator using junction structures. Causality was then assigned in order to obtain a computational model which could be simulated. The causal bond graph model of the hydraulic cylinder was verified by comparing the open loop state responses to those of an ODE model which had been developed in literature based on the same assumptions. The results were found to correlate very well both in the shape of the curves, magnitude and the response times, thus indicating that the developed model represents the hydraulic dynamics of a valve-controlled cylinder. A simplified model for interactuator interaction was presented by connecting an effort source with constant pump pressure to the zero-junction from which the cylinders in a multi-cylinder system are supplied with a constant pressure from the pump. On simulating the state responses of the developed model under different situations of cylinder operations, indicated that such a simple model can be used to predict the inter-actuator interactions.

Keywords: Bond graphs, Inter-actuator interactions, Valvecontrolledhydraulic cylinder.

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Authors: Jamal S. Yassin

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This paper is to formulate a mathematical model to predict the amounts of the emissions produced from the combustion process of the gas turbine unit of the jet engine. These emissions have bad impacts on the environment if they are out of standards, which cause real threats to all type of life on the earth. The amounts of the emissions from the gas turbine engine are functions to many operational and design factors. In landing-takeoff (LTO) these amounts are not the same as in taxi or cruise of the plane using jet engines, because of the difference in the activity period during these operating modes. These emissions can be affected by several physical and chemical variables, such as fuel type, fuel to air ratio or equivalence ratio, flame temperature, combustion pressure, in addition to some inlet conditions such as ambient temperature and air humidity. To study the influence of these variables on the amounts of these emissions during the combustion process in the gas turbine unit, a computer program has been developed by using the visual basic 6 software. Here, the analysis of the combustion process is carried out by considering it as a chemical reaction with shifting equilibrium to find the products of the combustion of the octane fuel, at different equivalence ratios, compressor pressure ratios (CPR) and combustion temperatures. The results obtained have shown that there is noticeable influence of the equivalence ratio, CPR, and the combustion temperature on the amounts of the main emissions which are considered pollutants, such as CO, CO₂ and NO.

Keywords: Mathematical model, gas turbine unit, equivalence ratio, emissions, shifting equilibrium.

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Authors: Sheena Christabel Pravin, M. Palanivelan

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Speech disfluencies are common in spontaneous speech. The primary purpose of this study was to distinguish linguistic disfluencies from stuttering disfluencies in bilingual Tamil–English (TE) speaking children. The secondary purpose was to determine whether their disfluencies are mediated by native language dominance and/or on an early onset of developmental stuttering at childhood. A detailed study was carried out to identify the prosodic and acoustic features that uniquely represent the disfluent regions of speech. This paper focuses on statistical modeling of repetitions, prolongations, pauses and interjections in the speech corpus encompassing bilingual spontaneous utterances from school going children – English and Tamil. Two classifiers including Hidden Markov Models (HMM) and the Multilayer Perceptron (MLP), which is a class of feed-forward artificial neural network, were compared in the classification of disfluencies. The results of the classifiers document the patterns of disfluency in spontaneous speech samples of school-aged children to distinguish between Children Who Stutter (CWS) and Children with Language Impairment CLI). The ability of the models in classifying the disfluencies was measured in terms of F-measure, Recall, and Precision.

Keywords: Bilingual, children who stutter, children with language impairment, Hidden Markov Models, multi-layer perceptron, linguistic disfluencies, stuttering disfluencies.

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

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Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.

Keywords: Enhanced ideal gas molecular movement, Kriging, probability-based damage detection, probability of damage existence, surrogate modeling, uncertainty quantification.

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Authors: T. C. Manjunath, B. Bandyopadhyay

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This paper deals with the design of a periodic output feedback controller for a flexible beam structure modeled with Timoshenko beam theory, Finite Element Method, State space methods and embedded piezoelectrics concept. The first 3 modes are considered in modeling the beam. The main objective of this work is to control the vibrations of the beam when subjected to an external force. Shear piezoelectric sensors and actuators are embedded into the top and bottom layers of a flexible aluminum beam structure, thus making it intelligent and self-adaptive. The composite beam is divided into 5 finite elements and the control actuator is placed at finite element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. 4 state space SISO models are thus developed. Periodic Output Feedback (POF) Controllers are designed for the 4 SISO models of the same plant to control the flexural vibrations. The effect of placing the sensor at different locations on the beam is observed and the performance of the controller is evaluated for vibration control. Conclusions are finally drawn.

Keywords: Smart structure, Timoshenko beam theory, Periodic output feedback control, Finite Element Method, State space model, SISO, Embedded sensors and actuators, Vibration control.

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Authors: M. H. Mehrabi, S. S. Ghodsi, Zainah Ibrahim, Meldi Suhatril

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Standard routes for upgrading existing buildings to improve their seismic response can be expensive in terms of both time and cost due to the modifications required to the foundations. As a result, interest has grown in the installation of viscoelastic dampers (VEDs) in mid and high-rise buildings. Details of a low-cost viscoelastic passive control device, the rotary rubber braced damper (RRBD), are presented in this paper. This design has the added benefits of being lightweight and simple to install. Experimental methods and finite element modeling were used to assess the performance of the proposed VED design and its effect on building response during earthquakes. The analyses took into account the behaviors of non-linear materials and large deformations. The results indicate that the proposed RRBD provides high levels of energy absorption, ensuring the stable cyclical response of buildings in all scenarios considered. In addition, time history analysis was employed in this study to evaluate the RRBD’s ability to control the displacements and accelerations experienced by steel frame structures. It was demonstrated that the device responds well even at low displacements, highlighting its suitability for use in seismic events of varying severity.

Keywords: Dynamic response, passive control, performance test, seismic protection.

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Authors: Marco Raciti Castelli, Ernesto Benini

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This paper presents a model for the evaluation of energy performance and aerodynamic forces acting on a small straight-bladed Darrieus-type vertical axis wind turbine depending on blade geometrical section. It consists of an analytical code coupled to a solid modeling software, capable of generating the desired blade geometry based on the desired blade design geometric parameters. Such module is then linked to a finite volume commercial CFD code for the calculation of rotor performance by integration of the aerodynamic forces along the perimeter of each blade for a full period of revolution.After describing and validating the computational model with experimental data, the results of numerical simulations are proposed on the bases of two candidate airfoil sections, that is a classical symmetrical NACA 0021 blade profile and the recently developed DU 06-W-200 non-symmetric and laminar blade profile.Through a full CFD campaign of analysis, the effects of blade geometrical section on angle of attack are first investigated and then the overall rotor torque and power are analyzed as a function of blade azimuthal position, achieving a numerical quantification of the influence of airfoil geometry on overall rotor performance.

Keywords: Wind turbine, NACA 0021, DU 06-W-200.

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Authors: Eakong Atiptamvaree, Twittie Senivongse

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A new paradigm for software design and development models software by its business process, translates the model into a process execution language, and has it run by a supporting execution engine. This process-oriented paradigm promotes modeling of software by less technical users or business analysts as well as rapid development. Since business process models may be shared by different organizations and sometimes even by different business domains, it is interesting to apply a technique used in traditional software component technology to design reusable business processes. This paper discusses an approach to apply a technique for software component fabrication to the design of process-oriented software units, called process components. These process components result from decomposing a business process of a particular application domain into subprocesses with an aim that the process components can be reusable in different process-based software models. The approach is quantitative because the quality of process component design is measured from technical features of the process components. The approach is also strategic because the measured quality is determined against business-oriented component management goals. A software tool has been developed to measure how good a process component design is, according to the required managerial goals and comparing to other designs. We also discuss how we benefit from reusable process components.

Keywords: Business process model, process component, component management goals, measurement

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Authors: Ali Komakpanah, Maryam Yazdi

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Few studies have been conducted on polymeric strip and the behavior of soil retaining walls. This paper will present the effect of frequency on the dynamic behavior of reinforced soil retaining walls with polymeric strips. The frequency content describes how the amplitude of a ground motion is distributed among different frequencies. Since the frequency content of an earthquake motion will strongly influence the effects of that motion, the characterization of the motion cannot be completed without the consideration of its frequency content. The maximum axial force of reinforcements and horizontal displacement of the reinforced walls are focused in this research. To clarify the dynamic behavior of reinforced soil retaining walls with polymeric strips, a numerical modeling using Finite Difference Method is benefited. As the results indicate, the frequency of input base acceleration has an important effect on the behavior of these structures. Because of resonant in the system, where the frequency of the input dynamic load is equal to the natural frequency of the system, the maximum horizontal displacement and the maximum axial forces in polymeric strips is occurred. Moreover, they were to increase the structure flexibility because of the main advantages of polymeric strips; i.e. being simple method of construction, having a homogeneous behavior with soils, and possessing long durability, which are of great importance in dynamic analysis.

Keywords: dynamic analysis, frequency, polymeric strip, reinforced soil.

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Authors: Ayman El Ansary, Mohamed Shalaby

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The current study describes a multi-objective optimization technique for positioning of houses in a residential neighborhood. The main task is the placement of residential houses in a favorable configuration satisfying a number of objectives. Solving the house layout problem is a challenging task. It requires an iterative approach to satisfy design requirements (e.g. energy efficiency, skyview, daylight, roads network, visual privacy, and clear access to favorite views). These design requirements vary from one project to another based on location and client preferences. In the Gulf region, the most important socio-cultural factor is the visual privacy in indoor space. Hence, most of the residential houses in this region are surrounded by high fences to provide privacy, which has a direct impact on other requirements (e.g. daylight and direction to favorite views). This investigation introduces a novel technique to optimally locate and orient residential buildings to satisfy a set of design requirements. The developed technique explores the search space for possible solutions. This study considers two dimensional house planning problems. However, it can be extended to solve three dimensional cases.

Keywords: Evolutionary optimization, Houses planning, Urban modeling, Daylight, Visual Privacy, Residential compounds.

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Authors: Mohanad Alata, Mohammad Molhim, Abdullah Ramini

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Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models.

Keywords: Fuzzy clustering, Fuzzy C-Means, Genetic Algorithm, Sugeno fuzzy systems.

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Authors: R. Kamali, A. R. Binesh, S. Hossainpour

Abstract:

To understand working features of a micro combustor, a computer code has been developed to study combustion of hydrogen–air mixture in a series of chambers with same shape aspect ratio but various dimensions from millimeter to micrometer level. The prepared algorithm and the computer code are capable of modeling mixture effects in different fluid flows including chemical reactions, viscous and mass diffusion effects. The effect of various heat transfer conditions at chamber wall, e.g. adiabatic wall, with heat loss and heat conduction within the wall, on the combustion is analyzed. These thermal conditions have strong effects on the combustion especially when the chamber dimension goes smaller and the ratio of surface area to volume becomes larger. Both factors, such as larger heat loss through the chamber wall and smaller chamber dimension size, may lead to the thermal quenching of micro-scale combustion. Through such systematic numerical analysis, a proper operation space for the micro-combustor is suggested, which may be used as the guideline for microcombustor design. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the micro-combustor design, optimization and performance analysis.

Keywords: Numerical simulation, Micro-combustion, MEMS, CFD, Chemical reaction.

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Authors: B.Rajendra Prasath, P.Tamilporai, Mohd.F.Shabir

Abstract:

An effort has been taken to simulate the combustion and performance characteristics of biodiesel fuel in direct injection (D.I) low heat rejection (LHR) diesel engine. Comprehensive analyses on combustion characteristics such as cylinder pressure, peak cylinder pressure, heat release and performance characteristics such as specific fuel consumption and brake thermal efficiency are carried out. Compression ignition (C.I) engine cycle simulation was developed and modified in to LHR engine for both diesel and biodiesel fuel. On the basis of first law of thermodynamics the properties at each degree crank angle was calculated. Preparation and reaction rate model was used to calculate the instantaneous heat release rate. A gas-wall heat transfer calculations are based on the ANNAND-s combined heat transfer model with instantaneous wall temperature to analyze the effect of coating on heat transfer. The simulated results are validated by conducting the experiments on the test engine under identical operating condition on a turbocharged D.I diesel engine. In this analysis 20% of biodiesel (derived from Jatropha oil) blended with diesel and used in both conventional and LHR engine. The simulated combustion and performance characteristics results are found satisfactory with the experimental value.

Keywords: Biodiesel, Direct injection, Low heat rejection, Turbocharged engine

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Authors: Farhad Asadi, Hossein Sadati

Abstract:

In fields such as neuroscience and especially in cognition modeling of mental processes, uncertainty processing in temporal zone of signal is vital. In this paper, Bayesian online inferences in estimation of change-points location in signal are constructed. This method separated the observed signal into independent series and studies the change and variation of the regime of data locally with related statistical characteristics. We give conditions on simulations of the method when the data characteristics of signals vary, and provide empirical evidence to show the performance of method. It is verified that correlation between series around the change point location and its characteristics such as Signal to Noise Ratios and mean value of signal has important factor on fluctuating in finding proper location of change point. And one of the main contributions of this study is related to representing of these influences of signal statistical characteristics for finding abrupt variation in signal. There are two different structures for simulations which in first case one abrupt change in temporal section of signal is considered with variable position and secondly multiple variations are considered. Finally, influence of statistical characteristic for changing the location of change point is explained in details in simulation results with different artificial signals.

Keywords: Time series, fluctuation in statistical characteristics, optimal learning.

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Authors: Joseph C. Chen, Venkata Mohan Kudapa

Abstract:

Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: Surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations.

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