Sensitivity Analysis during the Optimization Process Using Genetic Algorithms
Genetic algorithms (GA) are applied to the solution
of high-dimensional optimization problems. Additionally, sensitivity
analysis (SA) is usually carried out to determine the effect on optimal
solutions of changes in parameter values of the objective function.
These two analyses (i.e., optimization and sensitivity analysis)
are computationally intensive when applied to high-dimensional
functions. The approach presented in this paper consists in performing
the SA during the GA execution, by statistically analyzing the data
obtained of running the GA. The advantage is that in this case
SA does not involve making additional evaluations of the objective
function and, consequently, this proposed approach requires less
computational effort than conducting optimization and SA in two
An Analytical Method for Solving General Riccati Equation
In this paper, the general Riccati equation is analytically solved by a new transformation. By the method developed, looking at the transformed equation, whether or not an explicit solution can be obtained is readily determined. Since the present method does not require a proper solution for the general solution, it is especially suitable for equations whose proper solutions cannot be seen at first glance. Since the transformed second order linear equation obtained by the present transformation has the simplest form that it can have, it is immediately seen whether or not the original equation can be solved analytically. The present method is exemplified by several examples.
Development of a Paediatric Head Model for the Computational Analysis of Head Impact Interactions
Head injury in childhood is a common cause of death or permanent disability from injury. However, despite its frequency and significance, there is little understanding of how a child’s head responds during injurious loading. Whilst Infant Post Mortem Human Subject (PMHS) experimentation is a logical approach to understand injury biomechanics, it is the authors’ opinion that a lack of subject availability is hindering potential progress. Computer modelling adds great value when considering adult populations; however, its potential remains largely untapped for infant surrogates. The complexities of child growth and development, which result in age dependent changes in anatomy, geometry and physical response characteristics, present new challenges for computational simulation. Further geometric challenges are presented by the intricate infant cranial bones, which are separated by sutures and fontanelles and demonstrate a visible fibre orientation. This study presents an FE model of a newborn infant’s head, developed from high-resolution computer tomography scans, informed by published tissue material properties. To mimic the fibre orientation of immature cranial bone, anisotropic properties were applied to the FE cranial bone model, with elastic moduli representing the bone response both parallel and perpendicular to the fibre orientation. Biofiedility of the computational model was confirmed by global validation against published PMHS data, by replicating experimental impact tests with a series of computational simulations, in terms of head kinematic responses. Numerical results confirm that the FE head model’s mechanical response is in favourable agreement with the PMHS drop test results.
A Comparative Study of Additive and Nonparametric Regression Estimators and Variable Selection Procedures
One of the biggest challenges in nonparametric
regression is the curse of dimensionality. Additive models are known
to overcome this problem by estimating only the individual additive
effects of each covariate. However, if the model is misspecified, the
accuracy of the estimator compared to the fully nonparametric one
is unknown. In this work the efficiency of completely nonparametric
regression estimators such as the Loess is compared to the estimators
that assume additivity in several situations, including additive and
non-additive regression scenarios. The comparison is done by
computing the oracle mean square error of the estimators with regards
to the true nonparametric regression function. Then, a backward
elimination selection procedure based on the Akaike Information
Criteria is proposed, which is computed from either the additive or
the nonparametric model. Simulations show that if the additive model
is misspecified, the percentage of time it fails to select important
variables can be higher than that of the fully nonparametric approach.
A dimension reduction step is included when nonparametric estimator
cannot be computed due to the curse of dimensionality. Finally, the
Boston housing dataset is analyzed using the proposed backward
elimination procedure and the selected variables are identified.
Mathematical Study for Traffic Flow and Traffic Density in Kigali Roads
This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.
Simulation of the Large Hadrons Collisions Using Monte Carlo Tools
In many cases, theoretical treatments are available for models for which there is no perfect physical realization. In this situation, the only possible test for an approximate theoretical solution is to compare with data generated from a computer simulation. In this paper, Monte Carlo tools are used to study and compare the elementary particles models. All the experiments are implemented using 10000 events, and the simulated energy is 13 TeV. The mean and the curves of several variables are calculated for each model using MadAnalysis 5. Anomalies in the results can be seen in the muons masses of the minimal supersymmetric standard model and the two Higgs doublet model.
Stability Analysis of a Human-Mosquito Model of Malaria with Infective Immigrants
In this paper, we analyse the stability of the SEIR model
of malaria with infective immigrants which was recently formulated
by the authors. The model consists of an SEIR model for the human
population and SI Model for the mosquitoes. Susceptible humans
become infected after they are bitten by infectious mosquitoes and
move on to the Exposed, Infected and Recovered classes respectively.
The susceptible mosquito becomes infected after biting an infected
person and remains infected till death. We calculate the reproduction
number R0 using the next generation method and then discuss about
the stability of the equilibrium points. We use the Lyapunov function
to show the global stability of the equilibrium points.
Mathematical Modeling of Human Cardiovascular System: A Lumped Parameter Approach and Simulation
The purpose of this work is to develop a mathematical
model of Human Cardiovascular System using lumped parameter
method. The model is divided in three parts: Systemic Circulation,
Pulmonary Circulation and the Heart. The established mathematical
model has been simulated by MATLAB software. The innovation of
this study is in describing the system based on the vessel diameters
and simulating mathematical equations with active electrical
elements. Terminology of human physical body and required
physical data like vessel’s radius, thickness etc., which are required
to calculate circuit parameters like resistance, inductance and
capacitance, are proceeds from well-known medical books. The
developed model is useful to understand the anatomic of human
cardiovascular system and related syndromes. The model is deal with
vessel’s pressure and blood flow at certain time.
Transport of Analytes under Mixed Electroosmotic and Pressure Driven Flow of Power Law Fluid
In this study, we have analyzed the transport of analytes
under a two dimensional steady incompressible flow of power-law
fluids through rectangular nanochannel. A mathematical model
based on the Cauchy momentum-Nernst-Planck-Poisson equations is
considered to study the combined effect of mixed electroosmotic
(EO) and pressure driven (PD) flow. The coupled governing
equations are solved numerically by finite volume method. We
have studied extensively the effect of key parameters, e.g., flow
behavior index, concentration of the electrolyte, surface potential,
imposed pressure gradient and imposed electric field strength on
the net average flow across the channel. In addition to study
the effect of mixed EOF and PD on the analyte distribution
across the channel, we consider a nonlinear model based on
general convective-diffusion-electromigration equation. We have also
presented the retention factor for various values of electrolyte
concentration and flow behavior index.
Jointly Learning Python Programming and Analytic Geometry
The paper presents an original Python-based application that outlines the advantages of combining some elementary notions of mathematics with the study of a programming language. The application support refers to some of the first lessons of analytic geometry, meaning conics and quadrics and their reduction to a standard form, as well as some related notions. The chosen programming language is Python, not only for its closer to an everyday language syntax – and therefore, enhanced readability – but also for its highly reusable code, which is of utmost importance for a mathematician that is accustomed to exploit already known and used problems to solve new ones. The purpose of this paper is, on one hand, to support the idea that one of the most appropriate means to initiate one into programming is throughout mathematics, and reciprocal, one of the most facile and handy ways to assimilate some basic knowledge in the study of mathematics is to apply them in a personal project. On the other hand, besides being a mean of learning both programming and analytic geometry, the application subject to this paper is itself a useful tool for it can be seen as an independent original Python package for analytic geometry.
Effects of Thermal Radiation on Mixed Convection in a MHD Nanofluid Flow over a Stretching Sheet Using a Spectral Relaxation Method
The effects of thermal radiation, Soret and Dufour
parameters on mixed convection and nanofluid flow over a stretching
sheet in the presence of a magnetic field are investigated. The flow is
subject to temperature dependent viscosity and a chemical reaction
parameter. It is assumed that the nanoparticle volume fraction at the
wall may be actively controlled. The physical problem is modelled
using systems of nonlinear differential equations which have been
solved numerically using a spectral relaxation method. In addition
to the discussion on heat and mass transfer processes, the velocity,
nanoparticles volume fraction profiles as well as the skin friction
coefficient are determined for different important physical parameters.
A comparison of current findings with previously published results
for some special cases of the problem shows an excellent agreement.
Group Invariant Solutions of Nonlinear Time-Fractional Hyperbolic Partial Differential Equation
In this paper, we have investigated the nonlinear
time-fractional hyperbolic partial differential equation (PDE) for
its symmetries and invariance properties. With the application of
this method, we have tried to reduce it to time-fractional ordinary
differential equation (ODE) which has been further studied for exact
Consensus of Multi-Agent Systems under the Special Consensus Protocols
Two consensus problems are considered in this
paper. One is the consensus of linear multi-agent systems with
weakly connected directed communication topology. The other
is the consensus of nonlinear multi-agent systems with strongly
connected directed communication topology. For the first problem,
a simplified consensus protocol is designed: Each child agent can
only communicate with one of its neighbors. That is, the real
communication topology is a directed spanning tree of the original
communication topology and without any cycles. Then, the necessary
and sufficient condition is put forward to the multi-agent systems can
be reached consensus. It is worth noting that the given conditions do
not need any eigenvalue of the corresponding Laplacian matrix of the
original directed communication network. For the second problem,
the feedback gain is designed in the nonlinear consensus protocol.
Then, the sufficient condition is proposed such that the systems can
be achieved consensus. Besides, the consensus interval is introduced
and analyzed to solve the consensus problem. Finally, two numerical
simulations are included to verify the theoretical analysis.
Moment Estimators of the Parameters of Zero-One Inflated Negative Binomial Distribution
In this paper, zero-one inflated negative binomial distribution is considered, along with some of its structural properties, then its parameters were estimated using the method of moments. It is found that the method of moments to estimate the parameters of the zero-one inflated negative binomial models is not a proper method and may give incorrect conclusions.
Warning about the Risk of Blood Flow Stagnation after Transcatheter Aortic Valve Implantation
In this work, the hemodynamics in the sinuses of
Valsalva after Transcatheter Aortic Valve Implantation is numerically
examined. We focus on the physical results in the two-dimensional
case. We use a finite element methodology based on a Lagrange
multiplier technique that enables to couple the dynamics of blood
flow and the leaflets’ movement. A massively parallel implementation
of a monolithic and fully implicit solver allows more accuracy and
significant computational savings. The elastic properties of the aortic
valve are disregarded, and the numerical computations are performed
under physiologically correct pressure loads. Computational results
depict that blood flow may be subject to stagnation in the lower
domain of the sinuses of Valsalva after Transcatheter Aortic Valve
Topological Sensitivity Analysis for Reconstruction of the Inverse Source Problem from Boundary Measurement
In this paper, we consider a geometric inverse source
problem for the heat equation with Dirichlet and Neumann boundary
data. We will reconstruct the exact form of the unknown source
term from additional boundary conditions. Our motivation is to
detect the location, the size and the shape of source support.
We present a one-shot algorithm based on the Kohn-Vogelius
formulation and the topological gradient method. The geometric
inverse source problem is formulated as a topology optimization
one. A topological sensitivity analysis is derived from a source
function. Then, we present a non-iterative numerical method for the
geometric reconstruction of the source term with unknown support
using a level curve of the topological gradient. Finally, we give
several examples to show the viability of our presented method.
A Hyperexponential Approximation to Finite-Time and Infinite-Time Ruin Probabilities of Compound Poisson Processes
This article considers the problem of evaluating
infinite-time (or finite-time) ruin probability under a given compound
Poisson surplus process by approximating the claim size distribution
by a finite mixture exponential, say Hyperexponential, distribution. It
restates the infinite-time (or finite-time) ruin probability as a solvable
ordinary differential equation (or a partial differential equation).
Application of our findings has been given through a simulation study.
Analytical Solutions for Corotational Maxwell Model Fluid Arising in Wire Coating inside a Canonical Die
The present paper applies the optimal homotopy perturbation method (OHPM) and the optimal homotopy asymptotic method (OHAM) introduced recently to obtain analytic approximations of the non-linear equations modeling the flow of polymer in case of wire coating of a corotational Maxwell fluid. Expression for the velocity field is obtained in non-dimensional form. Comparison of the results obtained by the two methods at different values of non-dimensional parameter l10, reveal that the OHPM is more effective and easy to use. The OHPM solution can be improved even working in the same order of approximation depends on the choices of the auxiliary functions.
Travel Time Model for Cylinder Type Parking System
In this paper, we mainly analyze an automated parking system where the storage and retrieval requests are performed by a tower crane. In this parking system, the S/R crane which is located at the middle of the bottom of the cylinder parking area can rotate in both clockwise and counterclockwise and three kinds of movements can be done simultaneously. We develop some mathematical travel time models for the single command cycle under the random storage assignment using the characteristics of this system. Finally, we compare these travel models with discrete case and it is shown that these travel models display a good satisfactory performance.
Analysis of Multilayer Neural Network Modeling and Long Short-Term Memory
This paper analyzes fundamental ideas and concepts related to neural networks, which provide the reader a theoretical explanation of Long Short-Term Memory (LSTM) networks operation classified as Deep Learning Systems, and to explicitly present the mathematical development of Backward Pass equations of the LSTM network model. This mathematical modeling associated with software development will provide the necessary tools to develop an intelligent system capable of predicting the behavior of licensed users in wireless cognitive radio networks.
Algorithms for Computing of Optimization Problems with a Common Minimum-Norm Fixed Point with Applications
This research is aimed to study a two-step iteration
process defined over a finite family of σ-asymptotically
quasi-nonexpansive nonself-mappings. The strong convergence
is guaranteed under the framework of Banach spaces with some
additional structural properties including strict and uniform
convexity, reflexivity, and smoothness assumptions. With similar
projection technique for nonself-mapping in Hilbert spaces, we
hereby use the generalized projection to construct a point within
the corresponding domain. Moreover, we have to introduce the use
of duality mapping and its inverse to overcome the unavailability
of duality representation that is exploit by Hilbert space theorists.
We then apply our results for σ-asymptotically quasi-nonexpansive
nonself-mappings to solve for ideal efficiency of vector optimization
problems composed of finitely many objective functions. We also
showed that the obtained solution from our process is the closest to
the origin. Moreover, we also give an illustrative numerical example
to support our results.
An Implicit Methodology for the Numerical Modeling of Locally Inextensible Membranes
We present in this paper a fully implicit finite element
method tailored for the numerical modeling of inextensible fluidic
membranes in a surrounding Newtonian fluid. We consider a highly
simplified version of the Canham-Helfrich model for phospholipid
membranes, in which the bending force and spontaneous curvature
are disregarded. The coupled problem is formulated in a fully
Eulerian framework and the membrane motion is tracked using
the level set method. The resulting nonlinear problem is solved
by a Newton-Raphson strategy, featuring a quadratic convergence
behavior. A monolithic solver is implemented, and we report several
numerical experiments aimed at model validation and illustrating
the accuracy of the proposed method. We show that stability is
maintained for significantly larger time steps with respect to an
explicit decoupling method.
Bi-Lateral Comparison between NIS-Egypt and NMISA-South Africa for the Calibration of an Optical Time Domain Reflectometer
Calibration of Optical Time Domain Reflectometer (OTDR) has a crucial role for the accurate determination of fault locations and the accurate calculation of loss budget of long-haul optical fibre links during installation and repair. A comparison has been made between the Egyptian National Institute for Standards (NIS-Egypt) and the National Metrology institute of South Africa (NMISA-South Africa) for the calibration of an OTDR. The distance and the attenuation scales of a transfer OTDR have been calibrated by both institutes using their standards according to the standard IEC 61746-1 (2009). The results of this comparison have been compiled in this report.
Implicit Eulerian Fluid-Structure Interaction Method for the Modeling of Highly Deformable Elastic Membranes
This paper is concerned with the development of a
fully implicit and purely Eulerian fluid-structure interaction method
tailored for the modeling of the large deformations of elastic
membranes in a surrounding Newtonian fluid. We consider a
simplified model for the mechanical properties of the membrane, in
which the surface strain energy depends on the membrane stretching.
The fully Eulerian description is based on the advection of a modified
surface tension tensor, and the deformations of the membrane are
tracked using a level set strategy. The resulting nonlinear problem
is solved by a Newton-Raphson method, featuring a quadratic
convergence behavior. A monolithic solver is implemented, and we
report several numerical experiments aimed at model validation and
illustrating the accuracy of the presented method. We show that
stability is maintained for significantly larger time steps.
Variational Evolutionary Splines for Solving a Model of Temporomandibular Disorders
The aim of this work is to modelize the occlusion of a
person with temporomandibular disorders as an evolutionary equation
and approach its solution by the construction and characterizing
of discrete variational splines. To formulate the problem, certain
boundary conditions have been considered. After showing the
existence and the uniqueness of the solution of such a problem, a
convergence result of a discrete variational evolutionary spline is
shown. A stress analysis of the occlusion of a human jaw with
temporomandibular disorders by finite elements is carried out in
FreeFem++ in order to prove the validity of the presented method.
Loading Factor Performance of a Centrifugal Compressor Impeller: Specific Features and Way of Modeling
A loading factor performance is necessary for the modeling of centrifugal compressor gas dynamic performance curve. Measured loading factors are linear function of a flow coefficient at an impeller exit. The performance does not depend on the compressibility criterion. To simulate loading factor performances, the authors present two parameters: a loading factor at zero flow rate and an angle between an ordinate and performance line. The calculated loading factor performances of non-viscous are linear too and close to experimental performances. Loading factor performances of several dozens of impellers with different blade exit angles, blade thickness and number, ratio of blade exit/inlet height, and two different type of blade mean line configuration. There are some trends of influence, which are evident – comparatively small blade thickness influence, and influence of geometry parameters is more for impellers with bigger blade exit angles, etc. Approximating equations for both parameters are suggested. The next phase of work will be simulating of experimental performances with the suggested approximation equations as a base.
Normalizing Logarithms of Realized Volatility in an ARFIMA Model
Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.
Conjugate Gradient Algorithm for the Symmetric Arrowhead Solution of Matrix Equation AXB=C
Based on the conjugate gradient (CG) algorithm, the constrained matrix equation AXB=C and the associate optimal approximation problem are considered for the symmetric arrowhead matrix solutions in the premise of consistency. The convergence results of the method are presented. At last, a numerical example is given to illustrate the efficiency of this method.
Optimization of Loudspeaker Part Design Parameters by Air Viscosity Damping Effect
This study optimized the design parameters of a cone loudspeaker as an example of high flexibility of the product design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to optimize each parameter of the loudspeaker design. To overcome the limitation of the design problem in practice, this study presents an acoustic analysis algorithm to optimize the design parameters of the loudspeaker. The material character of cone paper and the loudspeaker edge were the design parameters, and the vibration displacement of the cone paper was the objective function. The results of the analysis showed that the design had high accuracy as compared to the predicted value. These results suggested that although the parameter design is difficult, with experience and intuition, the design can be performed easily using the optimized design found with the acoustic analysis software.
On the Optimality of Blocked Main Effects Plans
In this article, experimental situations are considered
where a main effects plan is to be used to study m two-level factors
using n runs which are partitioned into b blocks, not necessarily
of same size. Assuming the block sizes to be even for all blocks,
for the case n ≡ 2 (mod 4), optimal designs are obtained with
respect to type 1 and type 2 optimality criteria in the class of designs
providing estimation of all main effects orthogonal to the block
effects. In practice, such orthogonal estimation of main effects is
often a desirable condition. In the wider class of all available m two
level even sized blocked main effects plans, where the factors do not
occur at high and low levels equally often in each block, E-optimal
designs are also characterized. Simple construction methods based on
Hadamard matrices and Kronecker product for these optimal designs