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: Social networking is one of the most successful and popular tools to emerge from the Web 2.0 era. However, the increased interconnectivity and access to peoples- personal lives and information has created a plethora of opportunities for the nefarious side of human nature to manifest. This paper categorizes and describes the major types of anti-social behavior and criminal activity that can arise through undisciplined use and/or misuse of social media. We specifically address identity theft, misrepresentation of information posted, cyber bullying, children and social networking, and social networking in the work place. Recommendations are provided for how to reduce the risk of being the victim of a crime or engaging in embarrassing behavior that could irrevocably harm one-s reputation either professionally or personally. We also discuss what responsibilities social networking companies have to protect their users and also what law enforcement and policy makers can do to help alleviate the problems.
Abstract: In this paper parametric analytical studies have been carried out to examine the intrinsic flow physics pertaining to the liftoff time of solid propellant rockets. Idealized inert simulators of solid rockets are selected for numerical studies to examining the preignition chamber dynamics. Detailed diagnostic investigations have been carried out using an unsteady two-dimensional k-omega turbulence model. We conjectured from the numerical results that the altered variations of the igniter jet impingement angle, turbulence level, time and location of the first ignition, flame spread characteristics, the overall chamber dynamics including the boundary layer growth history are having bearing on the time for nozzle flow chocking for establishing the required thrust for the rocket liftoff. We concluded that the altered flow choking time of strap-on motors with the pre-determined identical ignition time at the lift off phase will lead to the malfunctioning of the rocket. We also concluded that, in the light of the space debris, an error in predicting the liftoff time can lead to an unfavorable launch window amounts the satellite injection errors and/or the mission failures.
Abstract: A theory for optimal filtering of infinite sets of random
signals is presented. There are several new distinctive features of the
proposed approach. First, a single optimal filter for processing any
signal from a given infinite signal set is provided. Second, the filter is
presented in the special form of a sum with p terms where each term
is represented as a combination of three operations. Each operation
is a special stage of the filtering aimed at facilitating the associated
numerical work. Third, an iterative scheme is implemented into the
filter structure to provide an improvement in the filter performance at
each step of the scheme. The final step of the scheme concerns signal
compression and decompression. This step is based on the solution of
a new rank-constrained matrix approximation problem. The solution
to the matrix problem is described in this paper. A rigorous error
analysis is given for the new filter.
Abstract: Longitudinal data typically have the characteristics of
changes over time, nonlinear growth patterns, between-subjects
variability, and the within errors exhibiting heteroscedasticity and
dependence. The data exploration is more complicated than that of
cross-sectional data. The purpose of this paper is to organize/integrate
of various visual-graphical techniques to explore longitudinal data.
From the application of the proposed methods, investigators can
answer the research questions include characterizing or describing the
growth patterns at both group and individual level, identifying the time
points where important changes occur and unusual subjects, selecting
suitable statistical models, and suggesting possible within-error
variance.
Abstract: Bus networks design is an important problem in
public transportation. The main step to this design, is determining the
number of required terminals and their locations. This is an especial
type of facility location problem, a large scale combinatorial
optimization problem that requires a long time to be solved.
The genetic algorithm (GA) is a search and optimization technique
which works based on evolutionary principle of natural
chromosomes. Specifically, the evolution of chromosomes due to the
action of crossover, mutation and natural selection of chromosomes
based on Darwin's survival-of-the-fittest principle, are all artificially
simulated to constitute a robust search and optimization procedure.
In this paper, we first state the problem as a mixed integer
programming (MIP) problem. Then we design a new crossover and
mutation for bus terminal location problem (BTLP). We tested the
different parameters of genetic algorithm (for a sample problem) and
obtained the optimal parameters for solving BTLP with numerical try
and error.
Abstract: In a previously developed fast vortex method, the
diffusion of the vortex sheet induced at the solid wall by the no-slip
boundary conditions was modeled according to the approximation
solution of Koumoutsakos and converted into discrete blobs in the
vicinity of the wall. This scheme had been successfully applied to a
simulation of the flow induced with an impulsively initiated circular
cylinder. In this work, further modifications on this vortex method are
attempted, including replacing the approximation solution by the
boundary-element-method solution, incorporating a new algorithm for
handling the over-weak vortex blobs, and diffusing the vortex sheet
circulation in a new way suitable for high-curvature solid bodies. The
accuracy is thus largely improved. The predictions of lift and drag
coefficients for a uniform flow past a NASA airfoil agree well with the
existing literature.
Abstract: One of the key research issues in wireless sensor networks (WSNs) is how to efficiently deploy sensors to cover an area. In this paper, we present a Fishnet Based Dispatch Scheme (FiBDS) with energy aware mobility and interest based sensing angle. We propose two algorithms, one is FiBDS centralized algorithm and another is FiBDS distributed algorithm. The centralized algorithm is designed specifically for the non-time critical applications, commonly known as non real-time applications while the distributed algorithm is designed specifically for the time critical applications, commonly known as real-time applications. The proposed dispatch scheme works in a phase-selection manner. In this in each phase a specific constraint is dealt with according to the specified priority and then moved onto the next phase and at the end of each only the best suited nodes for the phase are chosen. Simulation results are presented to verify their effectiveness.
Abstract: This paper presents the study of induced currents and
temperature distribution in gear heated by induction process using 2D
finite element (FE) model. The model is developed by coupling
Maxwell and heat transfer equations into a multi-physics model. The
obtained results allow comparing the medium frequency (MF) and
high frequency (HF) cases and the effect of machine parameters on
the evolution of induced currents and temperature during heating.
The sensitivity study of the temperature profile is conducted and the
case hardness is predicted using the final temperature profile. These
results are validated using tests and give a good understanding of
phenomena during heating process.
Abstract: Animation is simply defined as the sequencing of a
series of static images to generate the illusion of movement. Most
people believe that actual drawings or creation of the individual
images is the animation, when in actuality it is the arrangement of
those static images that conveys the motion. To become an animator,
it is often assumed that needed the ability to quickly design
masterpiece after masterpiece. Although some semblance of artistic
skill is a necessity for the job, the real key to becoming a great
animator is in the comprehension of timing. This paper will use a
combination of sprite animation, frame animation, and some other
techniques to cause a group of multi-colored static images to slither
around in the bounded area. In addition to slithering, the images
will also change the color of different parts of their body, much like
the real world creatures that have this amazing ability to change the
colors on their bodies do. This paper was implemented by using
Java 2 Standard Edition (J2SE).
It is both time-consuming and expensive to create animations,
regardless if they are created by hand or by using motion-capture
equipment. If the animators could reuse old animations and even
blend different animations together, a lot of work would be saved in
the process. The main objective of this paper is to examine a method
for blending several animations together in real time. This paper
presents and analyses a solution using Weighted Skeleton
Animation (WSA) resulting in limited CPU time and memory waste
as well as saving time for the animators. The idea presented is
described in detail and implemented. In this paper, text animation,
vertex animation, sprite part animation and whole sprite animation
were tested.
In this research paper, the resolution, smoothness and movement
of animated images will be carried out from the parameters, which
will be obtained from the experimental research of implementing
this paper.
Abstract: Synchronization is a difficult problem in CDMA
satellite communications. Due to the influence of additive noise and
fading in the mobile channel, it is not easy to keep up with the
attenuation and offset. This paper considers a recently proposed
approach to solve the problem of synchronization chaotic Chen
system in CDMA satellite communication in the presence of constant
attenuation and offset. An analytic algorithm that provides closed
form channel and carrier offset estimates is presented. The principle
of this approach is based on adding a compensation block before the
receiver to compensate the distortion of the imperfect channel by
using genetic algorithm.
The resultants presented, show that the receiver is able to recover
rapidly the synchronization with the transmitter.
Abstract: One of the main image representations in Mathematical Morphology is the 3D Shape Decomposition Representation, useful for Image Compression and Representation,and Pattern Recognition. The 3D Morphological Shape Decomposition representation can be generalized a number of times,to extend the scope of its algebraic characteristics as much as possible. With these generalizations, the Morphological Shape Decomposition 's role to serve as an efficient image decomposition tool is extended to grayscale images.This work follows the above line, and further develops it. Anew evolutionary branch is added to the 3D Morphological Shape Decomposition's development, by the introduction of a 3D Multi Structuring Element Morphological Shape Decomposition, which permits 3D Morphological Shape Decomposition of 3D binary images (grayscale images) into "multiparameter" families of elements. At the beginning, 3D Morphological Shape Decomposition representations are based only on "1 parameter" families of elements for image decomposition.This paper addresses the gray scale inter frame interpolation by means of mathematical morphology. The new interframe interpolation method is based on generalized morphological 3D Shape Decomposition. This article will present the theoretical background of the morphological interframe interpolation, deduce the new representation and show some application examples.Computer simulations could illustrate results.
Abstract: In general the images used for compression are of
different types like dark image, high intensity image etc. When these
images are compressed using Counter Propagation Neural Network,
it takes longer time to converge. The reason for this is that the given
image may contain a number of distinct gray levels with narrow
difference with their neighborhood pixels. If the gray levels of the
pixels in an image and their neighbors are mapped in such a way that
the difference in the gray levels of the neighbor with the pixel is
minimum, then compression ratio as well as the convergence of the
network can be improved. To achieve this, a Cumulative Distribution
Function is estimated for the image and it is used to map the image
pixels. When the mapped image pixels are used the Counter
Propagation Neural Network yield high compression ratio as well as
it converges quickly.
Abstract: A real-time tracking system was built to track performers on an interactive stage. Using an ordinary, up to date, desktop workstation, the performers- silhouette was segmented from the background and parameterized by calculating the normalized central image moments. In the stage system, the silhouette moments were then sent to a parallel workstation, which used them to generate corresponding 3D virtual geometry and projected the generated graphic back onto the stage.
Abstract: Eco-driving allows the driver to optimize his/her behaviour in order to achieve several types of benefits: reducing pollution emissions, increasing road safety, and fuel saving. One of the main rules for adopting eco-driving is to anticipate the traffic events by avoiding strong acceleration or braking and maintaining a steady speed when possible. Therefore, drivers have to comply with speed limits and time headway. The present study explored the role of three types of motivation and social norms in predicting French drivers- intentions to comply with speed limits and time headway as eco-driving practices as well as examine the variations according to gender and age. 1234 drivers with ages between 18 and 75 years old filled in a questionnaire which was presented as part of an online survey aiming to better understand the drivers- road habits. It included items assessing: a) behavioural intentions to comply with speed limits and time headway according to three types of motivation: reducing pollution emissions, increasing road safety, and fuel saving, b) subjective and descriptive social norms regarding the intention to comply with speed limits and time headway, and c) sociodemographical variables. Drivers expressed their intention to frequently comply with speed limits and time headway in the following 6 months; however, they showed more intention to comply with speed limits as compared to time headway regardless of the type of motivation. The subjective injunctive norms were significantly more important in predicting drivers- intentions to comply with speed limits and time headway as compared to the descriptive norms. In addition, the most frequently reported type of motivation for complying with speed limits and time headway was increasing road safety followed by fuel saving and reducing pollution emissions, hence underlining a low motivation to practice eco-driving. Practical implications of the results are discussed.
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: This article presents a short discussion on
optimum neighborhood size selection in a spherical selforganizing
feature map (SOFM). A majority of the literature
on the SOFMs have addressed the issue of selecting optimal
learning parameters in the case of Cartesian topology SOFMs.
However, the use of a Spherical SOFM suggested that the
learning aspects of Cartesian topology SOFM are not directly
translated. This article presents an approach on how to
estimate the neighborhood size of a spherical SOFM based on
the data. It adopts the L-curve criterion, previously suggested
for choosing the regularization parameter on problems of
linear equations where their right-hand-side is contaminated
with noise. Simulation results are presented on two artificial
4D data sets of the coupled Hénon-Ikeda map.
Abstract: Decision making preferences to certain criteria
usually focus on positive degrees without considering the negative
degrees. However, in real life situation, evaluation becomes more
comprehensive if negative degrees are considered concurrently.
Preference is expected to be more effective when considering both
positive and negative degrees of preference to evaluate the best
selection. Therefore, the aim of this paper is to propose the
conflicting bifuzzy preference relations in group decision making by
utilization of a novel score function. The conflicting bifuzzy
preference relation is obtained by introducing some modifications on
intuitionistic fuzzy preference relations. Releasing the intuitionistic
condition by taking into account positive and negative degrees
simultaneously and utilizing the novel score function are the main
modifications to establish the proposed preference model. The
proposed model is tested with a numerical example and proved to be
simple and practical. The four-step decision model shows the
efficiency of obtaining preference in group decision making.
Abstract: Students often adopt routine practicing as learning
strategy for mathematics. The reason is they are often bound and
trained to solving conventional-typed questions in Mathematics in
high school. This will be problematic if students further consolidate
this practice in university. Therefore, the Department of Mathematics
emphasized and integrated the Discovery-enriched approach in the
undergraduate curriculum. This paper presents the details of
implementing the Discovery-enriched Curriculum by providing
adequate platform for project-learning, expertise for guidance and
internship opportunities for students majoring in Mathematics. The
Department also provided project-learning opportunities to
mathematics courses targeted for students majoring in other science or
engineering disciplines. The outcome is promising: the research
ability and problem solving skills of students are enhanced.
Abstract: Having a very many number of pipelines all over the
country, Iran is one of the countries consists of various ecosystems
with variable degrees of fragility and robusticity as well as
geographical conditions. This study presents a state-of-the-art method
to estimate environmental risks of pipelines by recommending
rational equations including FES, URAS, SRS, RRS, DRS, LURS
and IRS as well as FRS to calculate the risks. This study was carried
out by a relative semi-quantitative approach based on land uses and
HVAs (High-Value Areas). GIS as a tool was used to create proper
maps regarding the environmental risks, land uses and distances. The
main logic for using the formulas was the distance-based approaches
and ESI as well as intersections. Summarizing the results of the
study, a risk geographical map based on the ESIs and final risk score
(FRS) was created. The study results showed that the most sensitive
and so of high risk area would be an area comprising of mangrove
forests located in the pipeline neighborhood. Also, salty lands were
the most robust land use units in the case of pipeline failure
circumstances. Besides, using a state-of-the-art method, it showed
that mapping the risks of pipelines out with the applied method is of
more reliability and convenience as well as relative
comprehensiveness in comparison to present non-holistic methods for
assessing the environmental risks of pipelines. The focus of the
present study is “assessment" than that of “management". It is
suggested that new policies are to be implemented to reduce the
negative effects of the pipeline that has not yet been constructed
completely