Abstract: This paper presents ageing experiments controlled by the evolution of junction parameters. The deterioration of the device is related to high injection effects which modified the transport mechanisms in the space charge region of the junction. Physical phenomena linked to the degradation of junction parameters that affect the devices reliability are reported and discussed. We have used the method based on numerical analysis of experimental current-voltage characteristic of the junction, in order to extract the electrical parameters. The simultaneous follow-up of the evolutions of the series resistance and of the transition voltage allow us to introduce a new parameter for reliability evaluation.
Abstract: We proposed a technique to identify road traffic
congestion levels from velocity of mobile sensors with high accuracy
and consistent with motorists- judgments. The data collection utilized
a GPS device, a webcam, and an opinion survey. Human perceptions
were used to rate the traffic congestion levels into three levels: light,
heavy, and jam. Then the ratings and velocity were fed into a
decision tree learning model (J48). We successfully extracted vehicle
movement patterns to feed into the learning model using a sliding
windows technique. The parameters capturing the vehicle moving
patterns and the windows size were heuristically optimized. The
model achieved accuracy as high as 99.68%. By implementing the
model on the existing traffic report systems, the reports will cover
comprehensive areas. The proposed method can be applied to any
parts of the world.
Abstract: This paper presents a Particle Swarm Optimization
(PSO) method for determining the optimal parameters of a first-order
controller for TCP/AQM system. The model TCP/AQM is described
by a second-order system with time delay. First, the analytical
approach, based on the D-decomposition method and Lemma of
Kharitonov, is used to determine the stabilizing regions of a firstorder
controller. Second, the optimal parameters of the controller are
obtained by the PSO algorithm. Finally, the proposed method is
implemented in the Network Simulator NS-2 and compared with the
PI controller.
Abstract: Quality control charts are very effective in detecting
out of control signals but when a control chart signals an out of
control condition of the process mean, searching for a special cause
in the vicinity of the signal time would not always lead to prompt
identification of the source(s) of the out of control condition as the
change point in the process parameter(s) is usually different from the
signal time. It is very important to manufacturer to determine at what
point and which parameters in the past caused the signal. Early
warning of process change would expedite the search for the special
causes and enhance quality at lower cost. In this paper the quality
variables under investigation are assumed to follow a multivariate
normal distribution with known means and variance-covariance
matrix and the process means after one step change remain at the new
level until the special cause is being identified and removed, also it is
supposed that only one variable could be changed at the same time.
This research applies artificial neural network (ANN) to identify the
time the change occurred and the parameter which caused the change
or shift. The performance of the approach was assessed through a
computer simulation experiment. The results show that neural
network performs effectively and equally well for the whole shift
magnitude which has been considered.
Abstract: The purpose of this paper is to perform a multidisciplinary design and analysis (MDA) of honeycomb panels used in the satellites structural design. All the analysis is based on clamped-free boundary conditions. In the present work, detailed finite element models for honeycomb panels are developed and analysed. Experimental tests were carried out on a honeycomb specimen of which the goal is to compare the previous modal analysis made by the finite element method as well as the existing equivalent approaches. The obtained results show a good agreement between the finite element analysis, equivalent and tests results; the difference in the first two frequencies is less than 4% and less than 10% for the third frequency. The results of the equivalent model presented in this analysis are obtained with a good accuracy. Moreover, investigations carried out in this research relate to the honeycomb plate modal analysis under several aspects including the structural geometrical variation by studying the various influences of the dimension parameters on the modal frequency, the variation of core and skin material of the honeycomb. The various results obtained in this paper are promising and show that the geometry parameters and the type of material have an effect on the value of the honeycomb plate modal frequency.
Abstract: This paper deals with the localization of the wideband sources. We develop a new approach for estimating the wide band sources parameters. This method is based on the high order statistics of the recorded data in order to eliminate the Gaussian components from the signals received on the various hydrophones.In fact the noise of sea bottom is regarded as being Gaussian. Thanks to the coherent signal subspace algorithm based on the cumulant matrix of the received data instead of the cross-spectral matrix the wideband correlated sources are perfectly located in the very noisy environment. We demonstrate the performance of the proposed algorithm on the real data recorded during an underwater acoustics experiments.
Abstract: This paper presents a useful sub-pixel image
registration method using line segments and a sub-pixel edge detector.
In this approach, straight line segments are first extracted from gray
images at the pixel level before applying the sub-pixel edge detector.
Next, all sub-pixel line edges are mapped onto the orientation-distance
parameter space to solve for line correspondence between images.
Finally, the registration parameters with sub-pixel accuracy are
analytically solved via two linear least-square problems. The present
approach can be applied to various fields where fast registration with
sub-pixel accuracy is required. To illustrate, the present approach is
applied to the inspection of printed circuits on a flat panel. Numerical
example shows that the present approach is effective and accurate
when target images contain a sufficient number of line segments,
which is true in many industrial problems.
Abstract: Multiprocessor task scheduling is a NP-hard problem and Genetic Algorithm (GA) has been revealed as an excellent technique for finding an optimal solution. In the past, several methods have been considered for the solution of this problem based on GAs. But, all these methods consider single criteria and in the present work, minimization of the bi-criteria multiprocessor task scheduling problem has been considered which includes weighted sum of makespan & total completion time. Efficiency and effectiveness of genetic algorithm can be achieved by optimization of its different parameters such as crossover, mutation, crossover probability, selection function etc. The effects of GA parameters on minimization of bi-criteria fitness function and subsequent setting of parameters have been accomplished by central composite design (CCD) approach of response surface methodology (RSM) of Design of Experiments. The experiments have been performed with different levels of GA parameters and analysis of variance has been performed for significant parameters for minimisation of makespan and total completion time simultaneously.
Abstract: In this paper, the requirement for Coke quality
prediction, its role in Blast furnaces, and the model output is
explained. By applying method of Artificial Neural Networking
(ANN) using back propagation (BP) algorithm, prediction model has
been developed to predict CSR. Important blast furnace functions
such as permeability, heat exchanging, melting, and reducing
capacity are mostly connected to coke quality. Coke quality is further
dependent upon coal characterization and coke making process
parameters. The ANN model developed is a useful tool for process
experts to adjust the control parameters in case of coke quality
deviations. The model also makes it possible to predict CSR for new
coal blends which are yet to be used in Coke Plant. Input data to the
model was structured into 3 modules, for tenure of past 2 years and
the incremental models thus developed assists in identifying the
group causing the deviation of CSR.
Abstract: A novel sponge submerged membrane bioreactor
(SSMBR) was developed to effectively remove organics and
nutrients from wastewater. Sponge is introduced within the SSMBR
as a medium for the attached growth of biomass. This paper evaluates
the effects of new and acclimatized sponges for dissolved organic
carbon (DOC) removal from wastewater at different mixed liquor
suspended solids- (MLSS) concentration of the sludge. It was
observed in a series of experimental studies that the acclimatized
sponge performed better than the new sponge whilst the optimum
DOC removal could be achieved at 10g/L of MLSS with the
acclimatized sponge. Moreover, the paper analyses the relationships
between the MLSSsponge/MLSSsludge and the DOC removal efficiency
of SSMBR. The results showed a non-linear relationship between the
biomass parameters of the sponge and the sludge, and the DOC
removal efficiency of SSMBR. A second-order polynomial function
could reasonably represent these relationships.
Abstract: In this study, the numerical solution of unsteady flow
between two concentric rotating spheres with suction and blowing at
their boundaries is presented. The spheres are rotating about a
common axis of rotation while their angular velocities are constant.
The Navier-Stokes equations are solved by employing the finite
difference method and implicit scheme. The resulting flow patterns
are presented for various values of the flow parameters including
rotational Reynolds number Re , and a blowing/suction Reynolds
number Rew . Viscous torques at the inner and the outer spheres are
calculated, too. It is seen that increasing the amount of suction and
blowing decrease the size of eddies generated in the annulus.
Abstract: Validation of an automation system is an important issue. The goal is to check if the system under investigation, modeled by a Petri net, never enters the undesired states. Usually, tools dedicated to Petri nets such as DESIGN/CPN are used to make reachability analysis. The biggest problem with this approach is that it is impossible to generate the full occurence graph of the system because it is too large. In this paper, we show how computational methods such as temporal logic model checking and Groebner bases can be used to verify the correctness of the design of an automation system. We report our experimental results with two automation systems: the Automated Guided Vehicle (AGV) system and the traffic light system. Validation of these two systems ranged from 10 to 30 seconds on a PC depending on the optimizing parameters.
Abstract: Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.
Abstract: The paper focuses on the enhanced stiffness modeling
of robotic manipulators by taking into account influence of the external force/torque acting upon the end point. It implements the
virtual joint technique that describes the compliance of manipulator elements by a set of localized six-dimensional springs separated by
rigid links and perfect joints. In contrast to the conventional
formulation, which is valid for the unloaded mode and small
displacements, the proposed approach implicitly assumes that the loading leads to the non-negligible changes of the manipulator posture and corresponding amendment of the Jacobian. The
developed numerical technique allows computing the static
equilibrium and relevant force/torque reaction of the manipulator for
any given displacement of the end-effector. This enables designer
detecting essentially nonlinear effects in elastic behavior of
manipulator, similar to the buckling of beam elements. It is also proposed the linearization procedure that is based on the inversion of
the dedicated matrix composed of the stiffness parameters of the
virtual springs and the Jacobians/Hessians of the active and passive
joints. The developed technique is illustrated by an application example that deals with the stiffness analysis of a parallel
manipulator of the Orthoglide family
Abstract: Web usage mining algorithms have been widely
utilized for modeling user web navigation behavior. In this study we
advance a model for mining of user-s navigation pattern. The model
makes user model based on expectation-maximization (EM)
algorithm.An EM algorithm is used in statistics for finding maximum
likelihood estimates of parameters in probabilistic models, where the
model depends on unobserved latent variables. The experimental
results represent that by decreasing the number of clusters, the log
likelihood converges toward lower values and probability of the
largest cluster will be decreased while the number of the clusters
increases in each treatment.
Abstract: Fabrication and efficiency enhancement of non-mercury, high efficiency and green field emission lamps using carbon nano-materials such as carbon nanotubes as cathode field emitters was studied. Phosphor was coated on the ITO glass or metal substrates as the anode. The luminescence efficiency enhancement was carried out by upgrading the uniform of the emitters, improving electron and thermal conductivity of the phosphor and the optimization of the design of different cathode/anode configurations. After evaluation of the aforementioned parameters, the luminescence efficiency of the field emission lamps was raised.
Abstract: This paper examines many mathematical methods for
molding the hourly price forward curve (HPFC); the model will be
constructed by numerous regression methods, like polynomial
regression, radial basic function neural networks & a furrier series.
Examination the models goodness of fit will be done by means of
statistical & graphical tools. The criteria for choosing the model will
depend on minimize the Root Mean Squared Error (RMSE), using the
correlation analysis approach for the regression analysis the optimal
model will be distinct, which are robust against model
misspecification. Learning & supervision technique employed to
determine the form of the optimal parameters corresponding to each
measure of overall loss. By using all the numerical methods that
mentioned previously; the explicit expressions for the optimal model
derived and the optimal designs will be implemented.
Abstract: The structural stability of the model of a nonelectroneutral current sheath is investigated. The stationary model of a current sheath represents the system of four connected nonlinear differential first-order equations and thus they should manifest structural instability property, i.e. sensitivity to the infinitesimal changes of parameters and starting conditions. Domains of existence of the solutions of current sheath type are found. Those solutions of the current sheath type are realized only in some regions of sevendimensional space of parameters of the problem. The phase volume of those regions is small in comparison with the whole phase volume of the definition range of those parameters. It is shown that the offered model of a nonelectroneutral current sheath is applicable for theoretical interpretation of the bifurcational current sheaths observed in the magnetosphere.
Abstract: Falls are the primary cause of accidents in people over
the age of 65, and frequently lead to serious injuries. Since the early
detection of falls is an important step to alert and protect the aging
population, a variety of research on detecting falls was carried out
including the use of accelerators, gyroscopes and tilt sensors. In
exiting studies, falls were detected using an accelerometer with
errors. In this study, the proposed method for detecting falls was to
use two accelerometers to reject wrong falls detection. As falls are
accompanied by the acceleration of gravity and rotational motion, the
falls in this study were detected by using the z-axial acceleration
differences between two sites. The falls were detected by calculating
the difference between the analyses of accelerometers placed on two
different positions on the chest of the subject. The parameters of the
maximum difference of accelerations (diff_Z) and the integration of
accelerations in a defined region (Sum_diff_Z) were used to form the
fall detection algorithm. The falls and the activities of daily living
(ADL) could be distinguished by using the proposed parameters
without errors in spite of the impact and the change in the positions
of the accelerometers. By comparing each of the axial accelerations,
the directions of falls and the condition of the subject afterwards
could be determined.In this study, by using two accelerometers
without errors attached to two sites to detect falls, the usefulness of
the proposed fall detection algorithm parameters, diff_Z and
Sum_diff_Z, were confirmed.
Abstract: Solidification cracking and hydrogen cracking are some defects generated in the fusion welding of ultrahigh carbon steels. However, friction stir welding (FSW) of such steels, being a solid-state technique, has been demonstrated to alleviate such problems encountered in traditional welding. FSW include different process parameters that must be carefully defined prior processing. These parameters included but not restricted to: tool feed, tool RPM, tool geometry, tool tilt angle. These parameters form a key factor behind avoiding warm holes and voids behind the tool and in achieving a defect-free weld. More importantly, these parameters directly affect the microstructure of the weld and hence the final mechanical properties of weld. For that, 3D finite element (FE) thermo-mechanical model was developed using DEFORM 3D to simulate FSW of carbon steel. At points of interest in the joint, tracking is done for history of critical state variables such as temperature, stresses, and strain rates. Typical results found include the ability to simulate different weld zones. Simulations predictions were successfully compared to experimental FSW tests. It is believed that such a numerical model can be used to optimize FSW processing parameters to favor desirable defect free weld with better mechanical properties.