Search results for: forward modeling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4887

Search results for: forward modeling

4737 Mathematical Modeling of Bi-Substrate Enzymatic Reactions in the Presence of Different Types of Inhibitors

Authors: Rafayel Azizyan, Valeri Arakelyan, Aram Gevorgyan, Varduhi Balayan, Emil Gevorgyan

Abstract:

Currently, mathematical and computer modeling are widely used in different biological studies to predict or assess behavior of such complex systems as biological ones. This study deals with mathematical and computer modeling of bi-substrate enzymatic reactions, which play an important role in different biochemical pathways. The main objective of this study is to represent the results from in silico investigation of bi-substrate enzymatic reactions in the presence of uncompetitive inhibitors, as well as to describe in details the inhibition effects. Four models of uncompetitive inhibition were designed using different software packages. Particularly, uncompetitive inhibitor to the first [ES1] and the second ([ES1S2]; [FS2]) enzyme-substrate complexes have been studied. The simulation, using the same kinetic parameters for all models allowed investigating the behavior of reactions as well as determined some interesting aspects concerning influence of different cases of uncompetitive inhibition. Besides that shown, that uncompetitive inhibitors exhibit specific selectivity depending on mechanism of bi-substrate enzymatic reaction.

Keywords: mathematical modeling, bi-substrate enzymatic reactions, reversible inhibition

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4736 Design of Visual Repository, Constraint and Process Modeling Tool Based on Eclipse Plug-Ins

Authors: Rushiraj Heshi, Smriti Bhandari

Abstract:

Master Data Management requires creation of Central repository, applying constraints on Repository and designing processes to manage data. Designing of Repository, constraints on repository and business processes is very tedious and time consuming task for large Enterprise. Hence Visual Repository, constraints and Process (Workflow) modeling is the most critical step in Master Data Management.In this paper, we realize a Visual Modeling tool for implementing Repositories, Constraints and Processes based on Eclipse Plugin using GMF/EMF which follows principles of Model Driven Engineering (MDE).

Keywords: EMF, GMF, GEF, repository, constraint, process

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4735 Object-Oriented Modeling Simulation and Control of Activated Sludge Process

Authors: J. Fernandez de Canete, P. Del Saz Orozco, I. Garcia-Moral, A. Akhrymenka

Abstract:

Object-oriented modeling is spreading in current simulation of wastewater treatments plants through the use of the individual components of the process and its relations to define the underlying dynamic equations. In this paper, we describe the use of the free-software OpenModelica simulation environment for the object-oriented modeling of an activated sludge process under feedback control. The performance of the controlled system was analyzed both under normal conditions and in the presence of disturbances. The object-oriented described approach represents a valuable tool in teaching provides a practical insight in wastewater process control field.

Keywords: object-oriented programming, activated sludge process, OpenModelica, feedback control

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4734 Dynamic Process Monitoring of an Ammonia Synthesis Fixed-Bed Reactor

Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

Abstract:

This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

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4733 Investigating Effects of Vehicle Speed and Road PSDs on Response of a 35-Ton Heavy Commercial Vehicle (HCV) Using Mathematical Modelling

Authors: Amal G. Kurian

Abstract:

The use of mathematical modeling has seen a considerable boost in recent times with the development of many advanced algorithms and mathematical modeling capabilities. The advantages this method has over other methods are that they are much closer to standard physics theories and thus represent a better theoretical model. They take lesser solving time and have the ability to change various parameters for optimization, which is a big advantage, especially in automotive industry. This thesis work focuses on a thorough investigation of the effects of vehicle speed and road roughness on a heavy commercial vehicle ride and structural dynamic responses. Since commercial vehicles are kept in operation continuously for longer periods of time, it is important to study effects of various physical conditions on the vehicle and its user. For this purpose, various experimental as well as simulation methodologies, are adopted ranging from experimental transfer path analysis to various road scenario simulations. To effectively investigate and eliminate several causes of unwanted responses, an efficient and robust technique is needed. Carrying forward this motivation, the present work focuses on the development of a mathematical model of a 4-axle configuration heavy commercial vehicle (HCV) capable of calculating responses of the vehicle on different road PSD inputs and vehicle speeds. Outputs from the model will include response transfer functions and PSDs and wheel forces experienced. A MATLAB code will be developed to implement the objectives in a robust and flexible manner which can be exploited further in a study of responses due to various suspension parameters, loading conditions as well as vehicle dimensions. The thesis work resulted in quantifying the effect of various physical conditions on ride comfort of the vehicle. An increase in discomfort is seen with velocity increase; also the effect of road profiles has a considerable effect on comfort of the driver. Details of dominant modes at each frequency are analysed and mentioned in work. The reduction in ride height or deflection of tire and suspension with loading along with load on each axle is analysed and it is seen that the front axle supports a greater portion of vehicle weight while more of payload weight comes on fourth and third axles. The deflection of the vehicle is seen to be well inside acceptable limits.

Keywords: mathematical modeling, HCV, suspension, ride analysis

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4732 Characterization of current–voltage (I–V) and capacitance–voltage–frequency (C–V–f) features of Au/GaN Schottky diodes

Authors: Abdelaziz Rabehi

Abstract:

The current–voltage (I–V) characteristics of Au/GaN Schottky diodes were measured at room temperature. In addition, capacitance–voltage–frequency (C–V–f) characteristics are investigated by considering the interface states (Nss) at frequency range 100 kHz to 1 MHz. From the I–V characteristics of the Schottky diode, ideality factor (n) and barrier height (Φb) values of 1.22 and 0.56 eV, respectively, were obtained from a forward bias I–V plot. In addition, the interface states distribution profile as a function of (Ess − Ev) was extracted from the forward bias I–V measurements by taking into account the bias dependence of the effective barrier height (Φe) for the Schottky diode. The C–V curves gave a barrier height value higher than those obtained from I–V measurements. This discrepancy is due to the different nature of the I–V and C–V measurement techniques.

Keywords: Schottky diodes, frequency dependence, barrier height, interface states

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4731 Decision Tree Modeling in Emergency Logistics Planning

Authors: Yousef Abu Nahleh, Arun Kumar, Fugen Daver, Reham Al-Hindawi

Abstract:

Despite the availability of natural disaster related time series data for last 110 years, there is no forecasting tool available to humanitarian relief organizations to determine forecasts for emergency logistics planning. This study develops a forecasting tool based on identifying probability of disaster for each country in the world by using decision tree modeling. Further, the determination of aggregate forecasts leads to efficient pre-disaster planning. Based on the research findings, the relief agencies can optimize the various resources allocation in emergency logistics planning.

Keywords: decision tree modeling, forecasting, humanitarian relief, emergency supply chain

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4730 Dry Relaxation Shrinkage Prediction of Bordeaux Fiber Using a Feed Forward Neural

Authors: Baeza S. Roberto

Abstract:

The knitted fabric suffers a deformation in its dimensions due to stretching and tension factors, transverse and longitudinal respectively, during the process in rectilinear knitting machines so it performs a dry relaxation shrinkage procedure and thermal action of prefixed to obtain stable conditions in the knitting. This paper presents a dry relaxation shrinkage prediction of Bordeaux fiber using a feed forward neural network and linear regression models. Six operational alternatives of shrinkage were predicted. A comparison of the results was performed finding neural network models with higher levels of explanation of the variability and prediction. The presence of different reposes are included. The models were obtained through a neural toolbox of Matlab and Minitab software with real data in a knitting company of Southern Guanajuato. The results allow predicting dry relaxation shrinkage of each alternative operation.

Keywords: neural network, dry relaxation, knitting, linear regression

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4729 Transition 1970 Volkswagen Beetle from Internal Combustion Engine Vehicle to Electric Vehicle, Modeling and Simulation

Authors: Jamil Khalil Izraqi

Abstract:

This paper investigates the transition of a 1970 Volkswagen Beetle from an internal combustion engine (ICE) to an EV using Matlab/Simulink modeling and simulation. The performance of the EV drivetrain system was simulated under various operating conditions, including standard and custom driving cycles in Turkey and Jordan (Amman), respectively. The results of this paper indicate that the transition is viable and that modeling and simulation can help in understanding the performance and efficiency of the electric drivetrain system, including battery pack, power electronics, and brushless direct current (BLDC) Motor.

Keywords: BLDC, buck-boost, inverter, SOC, drive-cycle

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4728 Cooperative Coevolution for Neuro-Evolution of Feed Forward Networks for Time Series Prediction Using Hidden Neuron Connections

Authors: Ravneil Nand

Abstract:

Cooperative coevolution uses problem decomposition methods to solve a larger problem. The problem decomposition deals with breaking down the larger problem into a number of smaller sub-problems depending on their method. Different problem decomposition methods have their own strengths and limitations depending on the neural network used and application problem. In this paper we are introducing a new problem decomposition method known as Hidden-Neuron Level Decomposition (HNL). The HNL method is competing with established problem decomposition method in time series prediction. The results show that the proposed approach has improved the results in some benchmark data sets when compared to the standalone method and has competitive results when compared to methods from literature.

Keywords: cooperative coevaluation, feed forward network, problem decomposition, neuron, synapse

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4727 A Modeling Approach for Blockchain-Oriented Information Systems Design

Authors: Jiaqi Yan, Yani Shi

Abstract:

The blockchain technology is regarded as the most promising technology that has the potential to trigger a technological revolution. However, besides the bitcoin industry, we have not yet seen a large-scale application of blockchain in those domains that are supposed to be impacted, such as supply chain, financial network, and intelligent manufacturing. The reasons not only lie in the difficulties of blockchain implementation, but are also root in the challenges of blockchain-oriented information systems design. As the blockchain members are self-interest actors that belong to organizations with different existing information systems. As they expect different information inputs and outputs of the blockchain application, a common language protocol is needed to facilitate communications between blockchain members. Second, considering the decentralization of blockchain organization, there is not any central authority to organize and coordinate the business processes. Thus, the information systems built on blockchain should support more adaptive business process. This paper aims to address these difficulties by providing a modeling approach for blockchain-oriented information systems design. We will investigate the information structure of distributed-ledger data with conceptual modeling techniques and ontology theories, and build an effective ontology mapping method for the inter-organization information flow and blockchain information records. Further, we will study the distributed-ledger-ontology based business process modeling to support adaptive enterprise on blockchain.

Keywords: blockchain, ontology, information systems modeling, business process

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4726 Transport Related Air Pollution Modeling Using Artificial Neural Network

Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

Abstract:

Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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4725 A Review of BIM Applications for Heritage and Historic Buildings: Challenges and Solutions

Authors: Reza Yadollahi, Arash Hejazi, Dante Savasta

Abstract:

Building Information Modeling (BIM) is growing so fast in construction projects around the world. Considering BIM's weaknesses in implementing existing heritage and historical buildings, it is critical to facilitate BIM application for such structures. One of the pieces of information to build a model in BIM is to import material and its characteristics. Material library is essential to speed up the entry of project information. To save time and prevent cost overrun, a BIM object material library should be provided. However, historical buildings' lack of information and documents is typically a challenge in renovation and retrofitting projects. Due to the lack of case documents for historic buildings, importing data is a time-consuming task, which can be improved by creating BIM libraries. Based on previous research, this paper reviews the complexities and challenges in BIM modeling for heritage, historic, and architectural buildings. Through identifying the strengths and weaknesses of the standard BIM systems, recommendations are provided to enhance the modeling platform.

Keywords: building Information modeling, historic, heritage buildings, material library

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4724 Light-Scattering Characteristics of Ordered Arrays Nobel Metal Nanoparticles

Authors: Yassine Ait-El-Aoud, Michael Okomoto, Andrew M. Luce, Alkim Akyurtlu, Richard M. Osgood III

Abstract:

Light scattering of metal nanoparticles (NPs) has a unique, and technologically important effect on enhancing light absorption in substrates because most of the light scatters into the substrate near the localized plasmon resonance of the NPs. The optical response, such as the resonant frequency and forward- and backward-scattering, can be tuned to trap light over a certain spectral region by adjusting the nanoparticle material size, shape, aggregation state, Metallic vs. insulating state, as well as local environmental conditions. In this work, we examined the light scattering characteristics of ordered arrays of metal nanoparticles and the light trapping, in order to enhance absorption, by measuring the forward- and backward-scattering using a UV/VIS/NIR spectrophotometer. Samples were fabricated using the popular self-assembly process method: dip coating, combined with nanosphere lithography.

Keywords: dip coating, light-scattering, metal nanoparticles, nanosphere lithography

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4723 Enhanced Tensor Tomographic Reconstruction: Integrating Absorption, Refraction and Temporal Effects

Authors: Lukas Vierus, Thomas Schuster

Abstract:

A general framework is examined for dynamic tensor field tomography within an inhomogeneous medium characterized by refraction and absorption, treated as an inverse source problem concerning the associated transport equation. Guided by Fermat’s principle, the Riemannian metric within the specified domain is determined by the medium's refractive index. While considerable literature exists on the inverse problem of reconstructing a tensor field from its longitudinal ray transform within a static Euclidean environment, limited inversion formulas and algorithms are available for general Riemannian metrics and time-varying tensor fields. It is established that tensor field tomography, akin to an inverse source problem for a transport equation, persists in dynamic scenarios. Framing dynamic tensor tomography as an inverse source problem embodies a comprehensive perspective within this domain. Ensuring well-defined forward mappings necessitates establishing existence and uniqueness for the underlying transport equations. However, the bilinear forms of the associated weak formulations fail to meet the coercivity condition. Consequently, recourse to viscosity solutions is taken, demonstrating their unique existence within suitable Sobolev spaces (in the static case) and Sobolev-Bochner spaces (in the dynamic case), under a specific assumption restricting variations in the refractive index. Notably, the adjoint problem can also be reformulated as a transport equation, with analogous results regarding uniqueness. Analytical solutions are expressed as integrals over geodesics, facilitating more efficient evaluation of forward and adjoint operators compared to solving partial differential equations. Certainly, here's the revised sentence in English: Numerical experiments are conducted using a Nesterov-accelerated Landweber method, encompassing various fields, absorption coefficients, and refractive indices, thereby illustrating the enhanced reconstruction achieved through this holistic modeling approach.

Keywords: attenuated refractive dynamic ray transform of tensor fields, geodesics, transport equation, viscosity solutions

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4722 Association between a Forward Lag of Historical Total Accumulated Gasoline Lead Emissions and Contemporary Autism Prevalence Trends in California, USA

Authors: Mark A. S. Laidlaw, Howard W. Mielke

Abstract:

In California between the late 1920’s and 1986 the lead concentrations in urban soils and dust climbed rapidly following the deposition of greater than 387,000 tonnes of lead emitted from gasoline. Previous research indicates that when children are lead exposed around 90% of the lead is retained in their bones and teeth due to the substitution of lead for calcium. Lead in children’s bones has been shown to accumulate over time and is highest in inner-city urban areas, lower in suburban areas and lowest in rural areas. It is also known that women’s bones demineralize during pregnancy due to the foetus's high demand for calcium. Lead accumulates in women’s bones during childhood and the accumulated lead is subsequently released during pregnancy – a lagged response. This results in calcium plus lead to enter the blood stream and cross the placenta to expose the foetus with lead. In 1970 in the United States, the average age of a first‐time mother was about 21. In 2008, the average age was 25.1. In this study, it is demonstrated that in California there is a forward lagged relationship between the accumulated emissions of lead from vehicle fuel additives and later autism prevalence trends between the 1990’s and current time period. Regression analysis between a 24 year forward lag of accumulated lead emissions and autism prevalence trends in California are associated strongly (R2=0.95, p=0.00000000127). It is hypothesized that autism in genetically susceptible children may stem from vehicle fuel lead emission exposures of their mothers during childhood and that the release of stored lead during subsequent pregnancy resulted in lead exposure of foetuses during a critical developmental period. It is furthermore hypothesized that the 24 years forward lag between lead exposures has occurred because that is time period is the average length for women to enter childbearing age. To test the hypothesis that lead in mothers bones is associated with autism, it is hypothesized that retrospective case-control studies would show an association between the lead in mother’s bones and autism. Furthermore, it is hypothesized that the forward lagged relationship between accumulated historical vehicle fuel lead emissions (or air lead concentrations) and autism prevalence trends will be similar in cities at the national and international scale. If further epidemiological studies indicate a strong relationship between accumulated vehicle fuel lead emissions (or accumulated air lead concentrations) and lead in mother’s bones and autism rates, then urban areas may require extensive soil intervention to prevent the development of autism in children.

Keywords: autism, bones, lead, gasoline, petrol, prevalence

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4721 Stochastic Variation of the Hubble's Parameter Using Ornstein-Uhlenbeck Process

Authors: Mary Chriselda A

Abstract:

This paper deals with the fact that the Hubble's parameter is not constant and tends to vary stochastically with time. This premise has been proven by converting it to a stochastic differential equation using the Ornstein-Uhlenbeck process. The formulated stochastic differential equation is further solved analytically using the Euler and the Kolmogorov Forward equations, thereby obtaining the probability density function using the Fourier transformation, thereby proving that the Hubble's parameter varies stochastically. This is further corroborated by simulating the observations using Python and R-software for validation of the premise postulated. We can further draw conclusion that the randomness in forces affecting the white noise can eventually affect the Hubble’s Parameter leading to scale invariance and thereby causing stochastic fluctuations in the density and the rate of expansion of the Universe.

Keywords: Chapman Kolmogorov forward differential equations, fourier transformation, hubble's parameter, ornstein-uhlenbeck process , stochastic differential equations

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4720 Diversity in Finance Literature Revealed through the Lens of Machine Learning: A Topic Modeling Approach on Academic Papers

Authors: Oumaima Lahmar

Abstract:

This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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4719 Importance of Mathematical Modeling in Teaching Mathematics

Authors: Selahattin Gultekin

Abstract:

Today, in engineering departments, mathematics courses such as calculus, linear algebra and differential equations are generally taught by mathematicians. Therefore, during mathematicians’ classroom teaching there are few or no applications of the concepts to real world problems at all. Most of the times, students do not know whether the concepts or rules taught in these courses will be used extensively in their majors or not. This situation holds true of for all engineering and science disciplines. The general trend toward these mathematic courses is not good. The real-life application of mathematics will be appreciated by students when mathematical modeling of real-world problems are tackled. So, students do not like abstract mathematics, rather they prefer a solid application of the concepts to our daily life problems. The author highly recommends that mathematical modeling is to be taught starting in high schools all over the world In this paper, some mathematical concepts such as limit, derivative, integral, Taylor Series, differential equations and mean-value-theorem are chosen and their applications with graphical representations to real problems are emphasized.

Keywords: applied mathematics, engineering mathematics, mathematical concepts, mathematical modeling

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4718 Improved Qualitative Modeling of the Magnetization Curve B(H) of the Ferromagnetic Materials for a Transformer Used in the Power Supply for Magnetron

Authors: M. Bassoui, M. Ferfra, M. Chrayagne

Abstract:

This paper presents a qualitative modeling for the nonlinear B-H curve of the saturable magnetic materials for a transformer with shunts used in the power supply for the magnetron. This power supply is composed of a single phase leakage flux transformer supplying a cell composed of a capacitor and a diode, which double the voltage and stabilize the current, and a single magnetron at the output of the cell. A procedure consisting of a fuzzy clustering method and a rule processing algorithm is then employed for processing the constructed fuzzy modeling rules to extract the qualitative properties of the curve.

Keywords: B(H) curve, fuzzy clustering, magnetron, power supply

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4717 Excitation Modeling for Hidden Markov Model-Based Speech Synthesis Based on Wavelet Analysis

Authors: M. Kiran Reddy, K. Sreenivasa Rao

Abstract:

The conventional Hidden Markov Model (HMM)-based speech synthesis system (HTS) uses only a pulse excitation model, which significantly differs from natural excitation signal. Hence, buzziness can be perceived in the speech generated using HTS. This paper proposes an efficient excitation modeling method that can significantly reduce the buzziness, and improve the quality of HMM-based speech synthesis. The proposed approach models the pitch-synchronous residual frames extracted from the residual excitation signal. Each pitch synchronous residual frame is parameterized using 30 wavelet coefficients. These 30 wavelet coefficients are found to accurately capture the perceptually important information present in the residual waveform. In synthesis phase, the residual frames are reconstructed from the generated wavelet coefficients and are pitch-synchronously overlap-added to generate the excitation signal. The proposed excitation modeling method is integrated into HMM-based speech synthesis system. Evaluation results indicate that the speech synthesized by the proposed excitation model is significantly better than the speech generated using state-of-the-art excitation modeling methods.

Keywords: excitation modeling, hidden Markov models, pitch-synchronous frames, speech synthesis, wavelet coefficients

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4716 Modeling of a Small Unmanned Aerial Vehicle

Authors: Ahmed Elsayed Ahmed, Ashraf Hafez, A. N. Ouda, Hossam Eldin Hussein Ahmed, Hala Mohamed ABD-Elkader

Abstract:

Unmanned Aircraft Systems (UAS) are playing increasingly prominent roles in defense programs and defense strategies around the world. Technology advancements have enabled the development of it to do many excellent jobs as reconnaissance, surveillance, battle fighters, and communications relays. Simulating a small unmanned aerial vehicle (SUAV) dynamics and analyzing its behavior at the preflight stage is too important and more efficient. The first step in the UAV design is the mathematical modeling of the nonlinear equations of motion. In this paper, a survey with a standard method to obtain the full non-linear equations of motion is utilized,and then the linearization of the equations according to a steady state flight condition (trimming) is derived. This modeling technique is applied to an Ultrastick-25e fixed wing UAV to obtain the valued linear longitudinal and lateral models. At the end, the model is checked by matching between the behavior of the states of the non-linear UAV and the resulted linear model with doublet at the control surfaces.

Keywords: UAV, equations of motion, modeling, linearization

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4715 Process Modeling and Problem Solving: Connecting Two Worlds by BPMN

Authors: Gionata Carmignani, Mario G. C. A. Cimino, Franco Failli

Abstract:

Business Processes (BPs) are the key instrument to understand how companies operate at an organizational level, taking an as-is view of the workflow, and how to address their issues by identifying a to-be model. In last year’s, the BP Model and Notation (BPMN) has become a de-facto standard for modeling processes. However, this standard does not incorporate explicitly the Problem-Solving (PS) knowledge in the Process Modeling (PM) results. Thus, such knowledge cannot be shared or reused. To narrow this gap is today a challenging research area. In this paper we present a framework able to capture the PS knowledge and to improve a workflow. This framework extends the BPMN specification by incorporating new general-purpose elements. A pilot scenario is also presented and discussed.

Keywords: business process management, BPMN, problem solving, process mapping

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4714 Boundary Motion by Curvature: Accessible Modeling of Oil Spill Evaporation/Dissipation

Authors: Gary Miller, Andriy Didenko, David Allison

Abstract:

The boundary of a region in the plane shrinks according to its curvature. A simple algorithm based upon this motion by curvature performed by a spreadsheet simulates the evaporation/dissipation behavior of oil spill boundaries.

Keywords: mathematical modeling, oil, evaporation, dissipation, boundary

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4713 First-Principles Modeling of Nanoparticle Magnetization, Chaining, and Motion

Authors: Pierce Radecki, Pulkit Malik, Bharath Ramaswamy, Ben Shapiro

Abstract:

The ability to effectively design and test magnetic nanoparticles for controlled movement has been an elusive goal in the design of these particles. Magnetic nanoparticles of various characteristics have been created for use towards therapeutic effects, however the challenge of designing for controlled movement remains unmet. A step towards design in this aspect is a first principles model that captures and predicts the behaviors of particles in a magnetic field. The model is governed by four forces acting on the particles, the magnetic gradient, the dipole-dipole forces, the steric forces, and the viscous drag force. The particles are multi-core or single core, and incorporate a preferred magnetization axis. Particles exhibit behaviors, such as chaining, in simulations that are similar to those witnessed through experimentation. Currently, experimental results are being compared to the modeling results for verification of the model, through the analysis of chaining behaviors. This modeling system will be used in designing magnetic nanoparticles for specific chaining and movement behaviors.

Keywords: controlled movement, modeling, magnetic nanoparticles, nanoparticle design

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4712 Climate Physical Processes Mathematical Modeling for Dome-Like Traditional Residential Building

Authors: Artem Sedov, Aigerim Uyzbayeva, Valeriya Tyo

Abstract:

The presented article is showing results of dynamic modeling with Mathlab software of optimal automatic room climate control system for two experimental houses in Astana, one of which has circle plan and the other one has square plan. These results are showing that building geometry doesn't influence on climate system PID-controls configuring. This confirms theoretical implication that optimal automatic climate control system parameters configuring should depend on building's internal space volume, envelope heat transfer, number of people inside, supply ventilation air flow and outdoor temperature.

Keywords: climate control system, climate physics, dome-like building, mathematical modeling

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4711 Experimental Approach and Numerical Modeling of Thermal Properties of Porous Materials: Application to Construction Materials

Authors: Nassima Sotehi

Abstract:

This article presents experimental and numerical results concerning the thermal properties of the porous materials used as heat insulator in the buildings sector. Initially, the thermal conductivity of three types of studied walls (classic concrete, concrete with cork aggregate and polystyrene concrete) was measured in experiments by the method of the boxes. Then a numerical modeling of the heat and mass transfers which occur within porous materials was applied to these walls. This work shows the influence of the presence of water in building materials on their thermophysical properties, as well as influence of the nature of materials and dosage of fibers introduced within these materials on the thermal and mass transfers.

Keywords: modeling, porous media, thermal materials, thermal properties

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4710 YHV-Responsive Gene Expression under the Influence of PmRelish Regulation

Authors: Suwattana Visetnan, Premruethai Supungul, Sureerat Tang, Ikuo Hirono, Anchalee Tassanakajon, Vichien Rimphanitchayakit

Abstract:

In animals, infection by Gram-negative bacteria and certain viruses activates the Imd signaling pathway wherein the a NF-κB transcription factor, Relish, is a key regulatory protein for the synthesis of antimicrobial proteins. Infection by yellow head virus (YHV) activates the Imd pathway. To investigate the expression of genes involved in YHV infection and under the influence of PmRelish regulation, RNA interference and suppression subtractive hybridization (SSH) are employed. The genes in forward library expressed in shrimp after YHV infection and under the activity of PmRelish were obtained by subtracting the cDNAs from YHV-infected and PmRelish-knockdown shrimp with cDNAs from YHV-infected shrimp. Opposite subtraction gave a reverse library whereby an alternative set of genes under YHV infection and no PmRelish expression was obtained. Sequencing of 252 and 99 cDNA clones from the respective forward and reverse libraries were done and annotated through blast search against the GenBank sequences. Genes involved in defense and homeostasis were abundant in both libraries, 31% and 23% in the forward and reverse libraries, respectively. They were predominantly antimicrobial proteins, proteinases and proteinase inhibitors. The expression of antimicrobial protein genes, ALFPm3, crustinPm1, penaeidin3 and penaeidin5 were tested under PmRelish silencing and Gram-negative bacterium V. harveyi infection. Together with the results previously reported, the expression of penaeidin5 and also penaeidin3 but not ALFPm3 and crustinPm1 were under the regulation of PmRelish in the Imd pathway.

Keywords: relish, yellow head virus, penaeus monodon, antimicrobial proteins

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4709 Mathematical Modeling of the Water Bridge Formation in Porous Media: PEMFC Microchannels

Authors: N. Ibrahim-Rassoul, A. Kessi, E. K. Si-Ahmed, N. Djilali, J. Legrand

Abstract:

The static and dynamic formation of liquid water bridges is analyzed using a combination of visualization experiments in a microchannel with a mathematical model. This paper presents experimental and theoretical findings of water plug/capillary bridge formation in a 250 μm squared microchannel. The approach combines mathematical and numerical modeling with experimental visualization and measurements. The generality of the model is also illustrated for flow conditions encountered in manipulation of polymeric materials and formation of liquid bridges between patterned surfaces. The predictions of the model agree favorably the observations as well as with the experimental recordings.

Keywords: green energy, mathematical modeling, fuel cell, water plug, gas diffusion layer, surface of revolution

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4708 Modeling Approach to Better Control Fouling in a Submerged Membrane Bioreactor for Wastewater Treatment: Development of Analytical Expressions in Steady-State Using ASM1

Authors: Benaliouche Hana, Abdessemed Djamal, Meniai Abdessalem, Lesage Geoffroy, Heran Marc

Abstract:

This paper presents a dynamic mathematical model of activated sludge which is able to predict the formation and degradation kinetics of SMP (Soluble microbial products) in membrane bioreactor systems. The model is based on a calibrated version of ASM1 with the theory of production and degradation of SMP. The model was calibrated on the experimental data from MBR (Mathematical modeling Membrane bioreactor) pilot plant. Analytical expressions have been developed, describing the concentrations of the main state variables present in the sludge matrix, with the inclusion of only six additional linear differential equations. The objective is to present a new dynamic mathematical model of activated sludge capable of predicting the formation and degradation kinetics of SMP (UAP and BAP) from the submerged membrane bioreactor (BRMI), operating at low organic load (C / N = 3.5), for two sludge retention times (SRT) fixed at 40 days and 60 days, to study their impact on membrane fouling, The modeling study was carried out under the steady-state condition. Analytical expressions were then validated by comparing their results with those obtained by simulations using GPS-X-Hydromantis software. These equations made it possible, by means of modeling approaches (ASM1), to identify the operating and kinetic parameters and help to predict membrane fouling.

Keywords: Activated Sludge Model No. 1 (ASM1), mathematical modeling membrane bioreactor, soluble microbial products, UAP, BAP, Modeling SMP, MBR, heterotrophic biomass

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