Abstract: In this paper, we have developed an explicit analytical
drain current model comprising surface channel potential and
threshold voltage in order to explain the advantages of the proposed
Gate Stack Double Diffusion (GSDD) MOSFET design over the
conventional MOSFET with the same geometric specifications that
allow us to use the benefits of the incorporation of the high-k layer
between the oxide layer and gate metal aspect on the immunity of the
proposed design against the self-heating effects. In order to show the
efficiency of our proposed structure, we propose the simulation of the
power chopper circuit. The use of the proposed structure to design a
power chopper circuit has showed that the (GSDD) MOSFET can
improve the working of the circuit in terms of power dissipation and
self-heating effect immunity. The results so obtained are in close
proximity with the 2D simulated results thus confirming the validity
of the proposed model.
Abstract: This paper considers the influence of promotion
instruments for renewable energy sources (RES) on a multi-energy
modeling framework. In Europe, so called Feed-in Tariffs are
successfully used as incentive structures to increase the amount of
energy produced by RES. Because of the stochastic nature of large
scale integration of distributed generation, many problems have
occurred regarding the quality and stability of supply. Hence, a
macroscopic model was developed in order to optimize the power
supply of the local energy infrastructure, which includes electricity,
natural gas, fuel oil and district heating as energy carriers. Unique
features of the model are the integration of RES and the adoption of
Feed-in Tariffs into one optimization stage. Sensitivity studies are
carried out to examine the system behavior under changing profits
for the feed-in of RES. With a setup of three energy exchanging
regions and a multi-period optimization, the impact of costs and
profits are determined.
Abstract: The linear methods of heart rate variability analysis
such as non-parametric (e.g. fast Fourier transform analysis) and
parametric methods (e.g. autoregressive modeling) has become an
established non-invasive tool for marking the cardiac health, but their
sensitivity and specificity were found to be lower than expected with
positive predictive value
Abstract: Soil organic carbon (SOC) plays a key role in soil
fertility, hydrology, contaminants control and acts as a sink or source
of terrestrial carbon content that can affect the concentration of
atmospheric CO2. SOC supports the sustainability and quality of
ecosystems, especially in semi-arid region. This study was
conducted to determine relative importance of 13 different
exploratory climatic, soil and geometric factors on the SOC contents
in one of the semiarid watershed zones in Iran. Two methods
canonical discriminate analysis (CDA) and feed-forward back
propagation neural networks were used to predict SOC. Stepwise
regression and sensitivity analysis were performed to identify
relative importance of exploratory variables. Results from sensitivity
analysis showed that 7-2-1 neural networks and 5 inputs in CDA
models output have highest predictive ability that explains %70 and
%65 of SOC variability. Since neural network models outperformed
CDA model, it should be preferred for estimating SOC.
Abstract: Sensory nerves in the foot play an important part in the diagnosis of various neuropathydisorders, especially in diabetes mellitus.However, a detailed description of the anatomical distribution of the nerves is currently lacking. A computationalmodel of the afferent nerves inthe foot may bea useful tool for the study of diabetic neuropathy. In this study, we present the development of an anatomically-based model of various major sensory nerves of the sole and dorsal sidesof the foot. In addition, we presentan algorithm for generating synthetic somatosensory nerve networks in the big-toe region of a right foot model. The algorithm was based on a modified version of the Monte Carlo algorithm, with the capability of being able to vary the intra-epidermal nerve fiber density in differentregionsof the foot model. Preliminary results from the combinedmodel show the realistic anatomical structure of the major nerves as well as the smaller somatosensory nerves of the foot. The model may now be developed to investigate the functional outcomes of structural neuropathyindiabetic patients.
Abstract: In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.
Abstract: Conception is the primordial part in the realization of
a computer system. Several tools have been used to help inventors to
describe their software. These tools knew a big success in the
relational databases domain since they permit to generate SQL script
modeling the database from an Entity/Association model. However,
with the evolution of the computer domain, the relational databases
proved their limits and object-relational model became used more
and more. Tools of present conception don't support all new concepts
introduced by this model and the syntax of the SQL3 language. We
propose in this paper a tool of help to the conception and
implementation of object-relational databases called «NAVIGTOOLS"
that allows the user to generate script modeling its database
in SQL3 language. This tool bases itself on the Entity/Association
and navigational model for modeling the object-relational databases.
Abstract: Advancements in the field of artificial intelligence
(AI) made during this decade have forever changed the way we look
at automating spacecraft subsystems including the electrical power
system. AI have been used to solve complicated practical problems
in various areas and are becoming more and more popular nowadays.
In this paper, a mathematical modeling and MATLAB–SIMULINK
model for the different components of the spacecraft power system is
presented. Also, a control system, which includes either the Neural
Network Controller (NNC) or the Fuzzy Logic Controller (FLC) is
developed for achieving the coordination between the components of
spacecraft power system as well as control the energy flows. The
performance of the spacecraft power system is evaluated by
comparing two control systems using the NNC and the FLC.
Abstract: Emerging Bio-engineering fields such as Brain
Computer Interfaces, neuroprothesis devices and modeling and
simulation of neural networks have led to increased research activity
in algorithms for the detection, isolation and classification of Action
Potentials (AP) from noisy data trains. Current techniques in the field
of 'unsupervised no-prior knowledge' biosignal processing include
energy operators, wavelet detection and adaptive thresholding. These
tend to bias towards larger AP waveforms, AP may be missed due to
deviations in spike shape and frequency and correlated noise
spectrums can cause false detection. Also, such algorithms tend to
suffer from large computational expense.
A new signal detection technique based upon the ideas of phasespace
diagrams and trajectories is proposed based upon the use of a
delayed copy of the AP to highlight discontinuities relative to
background noise. This idea has been used to create algorithms that
are computationally inexpensive and address the above problems.
Distinct AP have been picked out and manually classified from
real physiological data recorded from a cockroach. To facilitate
testing of the new technique, an Auto Regressive Moving Average
(ARMA) noise model has been constructed bases upon background
noise of the recordings. Along with the AP classification means this
model enables generation of realistic neuronal data sets at arbitrary
signal to noise ratio (SNR).
Abstract: A two dimensional three segments coupled pendulum system that mathematically models human arm configuration was developed along with constructing and solving the equations of motions for this model using the energy (work) based approach of Lagrange. The equations of motion of the model were solved iteratively both as an initial value problem and as a two point boundary value problem. In the initial value problem solutions, both the initial system configuration (segment angles) and initial system velocity (segment angular velocities) were used as inputs, whereas, in the two point boundary value problem solutions initial and final configurations and time were used as inputs to solve for the trajectory of motion. The results suggest that the model solutions are sensitive to small changes in the dynamic forces applied to the system as well as to the initial and boundary conditions used. To overcome the system sensitivity a new approach is suggested.
Abstract: The composition, vapour pressure, and heat capacity
of nine biodiesel fuels from different sources were measured. The
vapour pressure of the biodiesel fuels is modeled assuming an ideal
liquid phase of the fatty acid methyl esters constituting the fuel. New
methodologies to calculate the vapour pressure and ideal gas and
liquid heat capacities of the biodiesel fuel constituents are proposed.
Two alternative optimization scenarios are evaluated: 1) vapour
pressure only; 2) vapour pressure constrained with liquid heat
capacity. Without physical constraints, significant errors in liquid
heat capacity predictions were found whereas the constrained
correlation accurately fit both vapour pressure and liquid heat
capacity.
Abstract: In order to define a new model of Tunisian foot
sizes and for building the most comfortable shoes, Tunisian
industrialists must be able to offer for their customers products able
to put on and adjust the majority of the target population concerned.
Moreover, the use of models of shoes, mainly from others
country, causes a mismatch between the foot and comfort of the
Tunisian shoes.
But every foot is unique; these models become uncomfortable for
the Tunisian foot. We have a set of measures produced from a
3D scan of the feet of a diverse population (women, men ...) and we
try to analyze this data to define a model of foot specific to the
Tunisian footwear design.
In this paper we propose tow new approaches to modeling a new
foot sizes model. We used, indeed, the neural networks, and specially
the Kohonen network.
Next, we combine neural networks with the concept of half-foot
size to improve the models already found. Finally, it was necessary to
compare the results obtained by applying each approach and we
decide what-s the best approach that give us the most model of foot
improving more comfortable shoes.
Abstract: Effect of viscosity of media on kinetic parameters of the coupled enzyme system NADH:FMN-oxidoreductase–luciferase was investigated with addition of organic solvents (glycerol and sucrose), because bioluminescent enzyme systems based on bacterial luciferases offer a unique and general tool for analysis of the many analytes and enzymes in the environment, research and clinical laboratories and other fields. The possibility of stabilization and increase of activity of the coupled enzyme system NADH:FMN-oxidoreductase–luciferase activity in vicious aqueous-organic mixtures have been shown.
Abstract: Modern manufacturing facilities are large scale,
highly complex, and operate with large number of variables under
closed loop control. Early and accurate fault detection and diagnosis
for these plants can minimise down time, increase the safety of plant
operations, and reduce manufacturing costs. Fault detection and
isolation is more complex particularly in the case of the faulty analog
control systems. Analog control systems are not equipped with
monitoring function where the process parameters are continually
visualised. In this situation, It is very difficult to find the relationship
between the fault importance and its consequences on the product
failure. We consider in this paper an approach to fault detection and
analysis of its effect on the production quality using an adaptive
centring and scaling in the pickling process in cold rolling. The fault
appeared on one of the power unit driving a rotary machine, this
machine can not track a reference speed given by another machine.
The length of metal loop is then in continuous oscillation, this affects
the product quality. Using a computerised data acquisition system,
the main machine parameters have been monitored. The fault has
been detected and isolated on basis of analysis of monitored data.
Normal and faulty situation have been obtained by an artificial neural
network (ANN) model which is implemented to simulate the normal
and faulty status of rotary machine. Correlation between the product
quality defined by an index and the residual is used to quality
classification.
Abstract: The motorway segment between Tangier and Oued
R’mel has experienced, since the beginning of building works,
significant instability and landslides linked to a number of geological,
hydrogeological and geothermic factors affecting the different
formations.
The landslides observed are not fully understood, despite many
studies conducted on this segment. This study aims at producing new
methods to better explain the phenomena behind the landslides,
taking into account the geotechnical and geothermic contexts. This
analysis builds up on previous studies and geotechnical data collected
in the field.
The final body of data collected shall be processed through the
Plaxis software for a better and customizable view of the landslide
problems in the area, which will help tofind solutions and stabilize
land in the area.
Abstract: Future astronomical projects on large space x-ray
imaging telescopes require novel substrates and technologies for the
construction of their reflecting mirrors. The mirrors must be
lightweight and precisely shaped to achieve large collecting area with
high angular resolution. The new materials and technologies must be
cost-effective. Currently, the most promising materials are glass or
silicon foils. We focused on precise shaping these foils by thermal
forming process. We studied free and forced slumping in the
temperature region of hot plastic deformation and compared the
shapes obtained by the different slumping processes. We measured
the shapes and the surface quality of the foils. In the experiments, we
varied both heat-treatment temperature and time following our
experiment design. The obtained data and relations we can use for
modeling and optimizing the thermal forming procedure.
Abstract: The tray/multi-tray distillation process is a topic that
has been investigated to great detail over the last decade by many
teams such as Jubran et al. [1], Adhikari et al. [2], Mowla et al. [3],
Shatat et al. [4] and Fath [5] to name a few. A significant amount of
work and effort was spent focusing on modeling and/simulation of
specific distillation hardware designs. In this work, we have focused
our efforts on investigating and gathering experimental data on
several engineering and design variables to quantify their influence
on the yield of the multi-tray distillation process. Our goals are to
generate experimental performance data to bridge some existing gaps
in the design, engineering, optimization and theoretical modeling
aspects of the multi-tray distillation process.
Abstract: This paper deals with a novel approach of power
transformers diagnostics. This approach identifies the exact location
and the range of a fault in the transformer and helps to reduce
operation costs related to handling of the faulty transformer, its
disassembly and repair. The advantage of the approach is a
possibility to simulate healthy transformer and also all faults, which
can occur in transformer during its operation without its
disassembling, which is very expensive in practice. The approach is
based on creating frequency dependent impedance of the transformer
by sweep frequency response analysis measurements and by 3D FE
parametrical modeling of the fault in the transformer. The parameters
of the 3D FE model are the position and the range of the axial short
circuit. Then, by comparing the frequency dependent impedances of
the parametrical models with the measured ones, the location and the
range of the fault is identified. The approach was tested on a real
transformer and showed high coincidence between the real fault and
the simulated one.
Abstract: In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasi-stationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.
Abstract: The distressing flood scenarios that occur in
recent years at the surrounding areas of Sarawak River have
left damages of properties and indirectly caused disruptions of
productive activities. This study is meant to reconstruct a 100-year
flood event that took place in this river basin. Sarawak River Subbasin
was chosen and modeled using the one-dimensional
hydrodynamic modeling approach using InfoWorks River Simulation
(RS), in combination with Geographical Information System (GIS).
This produces the hydraulic response of the river and its floodplains
in extreme flooding conditions. With different parameters introduced
to the model, correlations of observed and simulated data are
between 79% – 87%. Using the best calibrated model, flood
mitigation structures are imposed along the sub-basin. Analysis is
done based on the model simulation results. Result shows that the
proposed retention ponds constructed along the sub-basin provide the
most efficient reduction of flood by 34.18%.