Abstract: In Mauritius, much emphasis is put on measures to
combat the high prevalence of non-communicable diseases (NCDs).
Health promotion campaigns for the adoption of healthy behaviors
and screening programs are done regularly by local authorities and
NCD surveys are carried out at intervals. However, the health
behaviors of the poor have not been investigated so far. This study
aims to give an insight on the perceptions of health status and
lifestyle health behaviors of poor people in Mauritius. A crosssectional
study among 83 persons benefiting from social aid in a
selected urban district was carried out. Results showed that 51.8% of
respondents perceived that they had good health status. 57.8% had no
known NCD whilst 25.3% had hypertension, followed by diabetes
(16.9%), asthma (9.6%) and heart disease (7.2%).They had low
smoking (10.8%) and alcohol consumption (6.0%) as well as high
physical activity prevalence (54.2%). These results were significantly
different from the NCD survey carried out in the general population.
Consumption of vegetables in the study was high. Overweight and
obesity trends were however similar to the NCD survey report 2009.
These findings contrast with other international studies showing poor
people having poor perceptions of health status and unhealthy
behavioral choices. Whether these positive health behaviors of poor
people in Mauritius arise out of choice or whether it is because the
alternative behavior is too costly remains to be investigated further.
Abstract: A brushless DC motor with integrated drive circuit for air management system is presented. Using magnetic equivalent circuit model a basic design of the motor is determined, and specific configurations are inspected thanks to finite element analysis. In order to reduce an unbalanced magnetic force in an axial direction, induced forces between a stator core and a permanent magnet are calculated with respect to the relative positions of them. For the high efficiency, and high power density, BLDC motor and drive are developed. Also vibration mode and eccentricity of a rotor are considered at the rated and maximum rotational speed Through the experimental results, a validity of the simulated one is confirmed.
Abstract: In Public Wireless LANs(PWLANs), user anonymity
is an essential issue. Recently, Juang et al. proposed an anonymous
authentication and key exchange protocol using smart cards in
PWLANs. They claimed that their proposed scheme provided identity
privacy, mutual authentication, and half-forward secrecy. In this paper,
we point out that Juang et al.'s protocol is vulnerable to the
stolen-verifier attack and does not satisfy user anonymity.
Abstract: It has formed an essential issue that Climate Change, composed of highly knowledge complexity, reveals its significant impact on human existence. Therefore, specific national policies, some of which present the educational aspects, have been published for overcoming the imperative problem. Accordingly, the study aims to analyze as well as integrate the relationship between Climate Change and environmental education and apply the perspective of concept map to represent the knowledge contents and structures of Climate Change; by doing so, knowledge contents of Climate Change could be represented in an even more comprehensive way and manipulated as the tool for environmental education. The method adapted for this study is knowledge conversion model compounded of the platform for experts and teachers, who were the participants for this study, to cooperate and combine each participant-s standpoints into a complete knowledge framework that is the foundation for structuring the concept map. The result of this research contains the important concepts, the precise propositions and the entire concept map for representing the robust concepts of Climate Change.
Abstract: In this work, we propose a hybrid heuristic in order to
solve the Team Orienteering Problem (TOP). Given a set of points (or
customers), each with associated score (profit or benefit), and a team
that has a fixed number of members, the problem to solve is to visit a
subset of points in order to maximize the total collected score. Each
member performs a tour starting at the start point, visiting distinct
customers and the tour terminates at the arrival point. In addition,
each point is visited at most once, and the total time in each tour
cannot be greater than a given value. The proposed heuristic combines
beam search and a local optimization strategy. The algorithm was
tested on several sets of instances and encouraging results were
obtained.
Abstract: Virtual environment induces simulator sickness effect
for some users. The purpose of this research is to compare the
simulation sickness relative with parallax affect in one-screen and
three-screen HoloStageTM system, measured by Simulation Sickness
Questionnaire (SSQ). The results show the subjects tested in
three-screen has less sickness than one-screen and effect from the
Oculomotor (O) more than from the Disorientation (D) and more than
from the Nausea (N) or represented in O>D>N.
Abstract: The fault detection and diagnosis of complicated
production processes is one of essential tasks needed to run the process
safely with good final product quality. Unexpected events occurred in
the process may have a serious impact on the process. In this work,
triangular representation of process measurement data obtained in an
on-line basis is evaluated using simulation process. The effect of using
linear and nonlinear reduced spaces is also tested. Their diagnosis
performance was demonstrated using multivariate fault data. It has
shown that the nonlinear technique based diagnosis method produced
more reliable results and outperforms linear method. The use of
appropriate reduced space yielded better diagnosis performance. The
presented diagnosis framework is different from existing ones in that it
attempts to extract the fault pattern in the reduced space, not in the
original process variable space. The use of reduced model space helps
to mitigate the sensitivity of the fault pattern to noise.
Abstract: Modeling product configurations needs large amounts of knowledge about technical and marketing restrictions on the product. Previous attempts to automate product configurations concentrate on representations and management of the knowledge for specific domains in fixed and isolated computing environments. Since the knowledge about product configurations is subject to continuous change and hard to express, these attempts often failed to efficiently manage and exchange the knowledge in collaborative product development. In this paper, XML Topic Map (XTM) is introduced to represent and exchange the knowledge about product configurations in collaborative product development. A product configuration model based on XTM along with its merger and inference facilities enables configuration engineers in collaborative product development to manage and exchange their knowledge efficiently. A prototype implementation is also presented to demonstrate the proposed model can be applied to engineering information systems to exchange the product configuration knowledge.
Abstract: Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.
Abstract: Wheel-running type moving robot has the restriction
on the moving range caused by obstacles or stairs. Solving this
weakness, we studied the development of moving robot using airship.
Our airship robot moves by recognizing arrow marks on the path. To
have the airship robot recognize arrow marks, we used edge-based
template matching. To control propeller units, we used PID and PD
controller. The results of experiments demonstrated that the airship
robot can move along the marks and can go up and down the stairs. It is
shown the possibility that airship robot can become a robot which can
move at wide range facilities.
Abstract: Most file systems overwrite modified file data and
metadata in their original locations, while the Log-structured File
System (LFS) dynamically relocates them to other locations. We
design and implement the Evergreen file system that can select
between overwriting or relocation for each block of a file or metadata.
Therefore, the Evergreen file system can achieve superior write
performance by sequentializing write requests (similar to LFS-style
relocation) when space utilization is low and overwriting when
utilization is high. Another challenging issue is identifying
performance benefits of LFS-style relocation over overwriting on a
newly introduced SSD (Solid State Drive) which has only
Flash-memory chips and control circuits without mechanical parts.
Our experimental results measured on a SSD show that relocation
outperforms overwriting when space utilization is below 80% and vice
versa.
Abstract: For many chemical and biological processes, the understanding of the mixing phenomenon and flow behavior in a stirred tank is of major importance. A three-dimensional numerical study was performed using the software Fluent, to study the flow field in a stirred tank with a Rushton turbine. In this work, we first studied the flow generated in the tank with a Rushton turbine. Then, we studied the effect of the variation of turbine’s submergence on the thermodynamic quantities defining the flow field. For that, four submergences were considered, while maintaining the same rotational speed (N =250rpm). This work intends to optimize the aeration performances of a Rushton turbine in a stirred tank.
Abstract: Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Backpropagation gradient descent method was performed to train the ANFIS system. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in controlling the non linear system.
Abstract: The present paper deals with problems related to the
possibilities to use fractal systems to solve some important scientific
and practical problems connected with filtering and separation of
aqueous phases from organic ones. For this purpose a special
separator have been designed. The reactor was filled with a porous
material with fractal dimension, which is an integral part of the set
for filtration and separation of emulsions. As a model emulsion
hexadecan mixture with water in equal quantities (1:1) was used. We
examined the hydrodynamics of the separation of the emulsion at
different rates of submission of the entrance of the reactor.
Abstract: Face authentication for access control is a face
membership authentication which passes the person of the incoming
face if he turns out to be one of an enrolled person based on face
recognition or rejects if not. Face membership authentication belongs
to the two class classification problem where SVM(Support Vector
Machine) has been successfully applied and shows better performance
compared to the conventional threshold-based classification. However,
most of previous SVMs have been trained using image feature vectors
extracted from face images of each class member(enrolled
class/unenrolled class) so that they are not robust to variations in
illuminations, poses, and facial expressions and much affected by
changes in member configuration of the enrolled class
In this paper, we propose an effective face membership
authentication method based on SVM using class discriminating
features which represent an incoming face image-s associability with
each class distinctively. These class discriminating features are weakly
related with image features so that they are less affected by variations
in illuminations, poses and facial expression.
Through experiments, it is shown that the proposed face
membership authentication method performs better than the threshold
rule-based or the conventional SVM-based authentication methods and
is relatively less affected by changes in member size and membership.
Abstract: In this paper we use classical linear stability theory
to investigate the effects of uniform internal heat generation on the
onset of Marangoni convection in a horizontal layer of fluid heated
from below. We use a analytical technique to obtain the close form
analytical expression for the onset of Marangoni convection when
the lower boundary is conducting with free-slip condition. We show
that the effect of increasing the internal heat generation is always to
destabilize the layer.
Abstract: Grobner basis calculation forms a key part of computational
commutative algebra and many other areas. One important
ramification of the theory of Grobner basis provides a means to solve
a system of non-linear equations. This is why it has become very
important in the areas where the solution of non-linear equations is
needed, for instance in algebraic cryptanalysis and coding theory. This
paper explores on a parallel-distributed implementation for Grobner
basis calculation over GF(2). For doing so Buchberger algorithm is
used. OpenMP and MPI-C language constructs have been used to
implement the scheme. Some relevant results have been furnished
to compare the performances between the standalone and hybrid
(parallel-distributed) implementation.
Abstract: In this work, we present a novel active learning approach
for learning a visual object detection system. Our system
is composed of an active learning mechanism as wrapper around
a sub-algorithm which implement an online boosting-based learning
object detector. In the core is a combination of a bootstrap procedure
and a semi automatic learning process based on the online boosting
procedure. The idea is to exploit the availability of classifier during
learning to automatically label training samples and increasingly
improves the classifier. This addresses the issue of reducing labeling
effort meanwhile obtain better performance. In addition, we propose
a verification process for further improvement of the classifier.
The idea is to allow re-update on seen data during learning for
stabilizing the detector. The main contribution of this empirical study
is a demonstration that active learning based on an online boosting
approach trained in this manner can achieve results comparable or
even outperform a framework trained in conventional manner using
much more labeling effort. Empirical experiments on challenging data
set for specific object deteciton problems show the effectiveness of
our approach.
Abstract: An application of Beta wavelet networks to
synthesize pass-high and pass-low wavelet filters is investigated in
this work. A Beta wavelet network is constructed using a parametric
function called Beta function in order to resolve some nonlinear
approximation problem. We combine the filter design theory with
wavelet network approximation to synthesize perfect filter
reconstruction. The order filter is given by the number of neurons in
the hidden layer of the neural network. In this paper we use only the
first derivative of Beta function to illustrate the proposed design
procedures and exhibit its performance.
Abstract: To determine the presence and location of faults in a transmission by the adaptation of protective distance relay based on the measurement of fixed settings as line impedance is achieved by several different techniques. Moreover, a fast, accurate and robust technique for real-time purposes is required for the modern power systems. The appliance of radial basis function neural network in transmission line protection is demonstrated in this paper. The method applies the power system via voltage and current signals to learn the hidden relationship presented in the input patterns. It is experiential that the proposed technique is competent to identify the particular fault direction more speedily. System simulations studied show that the proposed approach is able to distinguish the direction of a fault on a transmission line swiftly and correctly, therefore suitable for the real-time purposes.