Abstract: Space exploration is a highly visible endeavour of
humankind to seek profound answers to questions about the origins
of our solar system, whether life exists beyond Earth, and how we
could live on other worlds. Different platforms have been utilized in
planetary exploration missions, such as orbiters, landers, rovers, and
penetrators.
Having low mass, good mechanical contact with the surface,
ability to acquire high quality scientific subsurface data, and ability to
be deployed in areas that may not be conducive to landers or rovers,
Penetrators provide an alternative and complimentary solution that
makes possible scientific exploration of hardly accessible sites (icy
areas, gully sites, highlands etc.).
The Canadian Space Agency (CSA) has put space exploration as
one of the pillars of its space program, and established ExCo program
to prepare Canada for future international planetary exploration.
ExCo sets surface mobility as its focus and priority, and invests
mainly in the development of rovers because of Canada's niche space
robotics technology. Meanwhile, CSA is also investigating how
micro-penetrators can help Canada to fulfill its scientific objectives
for planetary exploration.
This paper presents a review of the micro-penetrator technologies,
past missions, and lessons learned. It gives a detailed analysis of the
technical challenges of micro-penetrators, such as high impact
survivability, high precision guidance navigation and control, thermal
protection, communications, and etc. Then, a Canadian perspective of
a possible micro-penetrator mission is given, including Canadian
scientific objectives and priorities, potential instruments, and flight
opportunities.
Abstract: This paper presents a method for determining the
uniaxial tensile properties such as Young-s modulus, yield strength
and the flow behaviour of a material in a virtually non-destructive
manner. To achieve this, a new dumb-bell shaped miniature
specimen has been designed. This helps in avoiding the removal of
large size material samples from the in-service component for the
evaluation of current material properties. The proposed miniature
specimen has an advantage in finite element modelling with respect
to computational time and memory space. Test fixtures have been
developed to enable the tension tests on the miniature specimen in a
testing machine. The studies have been conducted in a chromium
(H11) steel and an aluminum alloy (AR66). The output from the
miniature test viz. load-elongation diagram is obtained and the finite
element simulation of the test is carried out using a 2D plane stress
analysis. The results are compared with the experimental results. It is
observed that the results from the finite element simulation
corroborate well with the miniature test results. The approach seems
to have potential to predict the mechanical properties of the
materials, which could be used in remaining life estimation of the
various in-service structures.
Abstract: This paper describes new computer vision algorithms
that have been developed to track moving objects as part of a
long-term study into the design of (semi-)autonomous vehicles. We
present the results of a study to exploit variable kernels for tracking in
video sequences. The basis of our work is the mean shift
object-tracking algorithm; for a moving target, it is usual to define a
rectangular target window in an initial frame, and then process the data
within that window to separate the tracked object from the background
by the mean shift segmentation algorithm. Rather than use the
standard, Epanechnikov kernel, we have used a kernel weighted by the
Chamfer distance transform to improve the accuracy of target
representation and localization, minimising the distance between the
two distributions in RGB color space using the Bhattacharyya
coefficient. Experimental results show the improved tracking
capability and versatility of the algorithm in comparison with results
using the standard kernel. These algorithms are incorporated as part of
a robot test-bed architecture which has been used to demonstrate their
effectiveness.
Abstract: This paper explores the knowledge and attitude of
women and men in decision making on pap smear screening. This
qualitative study recruited 52 respondents with 44 women and 8 men,
using the purposive sampling with snowballing technique through indepth
interviews. This study demonstrates several key findings:
Female respondents have better knowledge compared to male. Most
of the women perceived that pap smear screening is beneficial and
important, but to proceed with the test is still doubtful. Male
respondents were supportive in terms of sending their spouses to the
health facilities or give more freedom to their wives to choose and
making decision on their own health due to prominent reason that
women know best on their own health. It is expected that the results
from this study will provide useful guideline for healthcare providers
to prepare any action/intervention to provide an extensive education
to improve people-s knowledge and attitude towards pap smear.
Abstract: Support vector machines (SVMs) have shown
superior performance compared to other machine learning techniques,
especially in classification problems. Yet one limitation of SVMs is
the lack of an explanation capability which is crucial in some
applications, e.g. in the medical and security domains. In this paper, a
novel approach for eclectic rule-extraction from support vector
machines is presented. This approach utilizes the knowledge acquired
by the SVM and represented in its support vectors as well as the
parameters associated with them. The approach includes three stages;
training, propositional rule-extraction and rule quality evaluation.
Results from four different experiments have demonstrated the value
of the approach for extracting comprehensible rules of high accuracy
and fidelity.
Abstract: During recent years wind turbine technology has
undergone rapid developments. Growth in size and the optimization
of wind turbines has enabled wind energy to become increasingly
competitive with conventional energy sources. As a result today-s
wind turbines participate actively in the power production of several
countries around the world. These developments raise a number of
challenges to be dealt with now and in the future. The penetration of
wind energy in the grid raises questions about the compatibility of the
wind turbine power production with the grid. In particular, the
contribution to grid stability, power quality and behavior during fault
situations plays therefore as important a role as the reliability. In the
present work, we addressed two fault situations that have shown their
influence on the generator and the behavior of the wind over the
defects which are briefly discussed based on simulation results.
Abstract: In this study, the contact problem of a layered composite which consists of two materials with different elastic constants and heights resting on two rigid flat supports with sharp edges is considered. The effect of gravity is neglected. While friction between the layers is taken into account, it is assumed that there is no friction between the supports and the layered composite so that only compressive tractions can be transmitted across the interface. The layered composite is subjected to a uniform clamping pressure over a finite portion of its top surface. The problem is reduced to a singular integral equation in which the contact pressure is the unknown function. The singular integral equation is evaluated numerically and the results for various dimensionless quantities are presented in graphical forms.
Abstract: In this paper, a multi-agent robot system is presented. The system consists of four robots. The developed robots are able to automatically enter and patrol a harmful environment, such as the building infected with virus or the factory with leaking hazardous gas. Further, every robot is able to perform obstacle avoidance and search for the victims. Several operation modes are designed: remote control, obstacle avoidance, automatic searching, and so on.
Abstract: An integrated Artificial Neural Network- Particle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world-s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World-s population, Gross domestic product (GDP), oil trade movement and natural gas trade movement are used as socio-economic indicators in this study. For each socio-economic indicator, a feed-forward back propagation artificial neural network is trained and projected for future time domain. STEP 2: in the second step, global electricity consumption is projected based on the oil, natural gas, coal and primary energy consumption using PSO. global electricity consumption is forecasted up to year 2040.
Abstract: Video Mosaicing is the stitching of selected frames of
a video by estimating the camera motion between the frames and
thereby registering successive frames of the video to arrive at the
mosaic. Different techniques have been proposed in the literature for
video mosaicing. Despite of the large number of papers dealing with
techniques to generate mosaic, only a few authors have investigated
conditions under which these techniques generate good estimate of
motion parameters. In this paper, these techniques are studied under
different videos, and the reasons for failures are found. We propose
algorithms with incorporation of outlier removal algorithms for better
estimation of motion parameters.
Abstract: In this paper we illuminate a frequency domain based
classification method for video scenes. Videos from certain topical
areas often contain activities with repeating movements. Sports
videos, home improvement videos, or videos showing mechanical
motion are some example areas. Assessing main and side frequencies
of each repeating movement gives rise to the motion type. We
obtain the frequency domain by transforming spatio-temporal motion
trajectories. Further on we explain how to compute frequency features
for video clips and how to use them for classifying. The focus of
the experimental phase is on transforms utilized for our system.
By comparing various transforms, experiments show the optimal
transform for a motion frequency based approach.
Abstract: Ethanol has been known for a long time, being
perhaps the oldest product obtained through traditional biotechnology
fermentation. Agriculture waste as substrate in fermentation is vastly
discussed as alternative to replace edible food and utilization of
organic material. Pineapple peel, highly potential source as substrate
is a by-product of the pineapple processing industry. Bio-ethanol
from pineapple (Ananas comosus) peel extract was carried out by
controlling fermentation without any treatment. Saccharomyces
ellipsoides was used as inoculum in this fermentation process as it is
naturally found at the pineapple skin. In this study, the capability of
Response Surface Methodology (RSM) for optimization of ethanol
production from pineapple peel extract using Saccharomyces
ellipsoideus in batch fermentation process was investigated. Effect of
five test variables in a defined range of inoculum concentration 6-
14% (v/v), pH (4.0-6.0), sugar concentration (14-22°Brix),
temperature (24-32°C) and time of incubation (30-54 hrs) on the
ethanol production were evaluated. Data obtained from experiment
were analyzed with RSM of MINITAB Software (Version 15)
whereby optimum ethanol concentration of 8.637% (v/v) was
determined. The optimum condition of 14% (v/v) inoculum
concentration, pH 6, 22°Brix, 26°C and 30hours of incubation. The
significant regression equation or model at the 5% level with
correlation value of 99.96% was also obtained.
Abstract: The article investigates how 14- to 15- year-olds build informal conceptions of inferential statistics as they engage in a modelling process and build their own computer simulations with dynamic statistical software. This study proposes four primary phases of informal inferential reasoning for the students in the statistical modeling and simulation process. Findings show shifts in the conceptual structures across the four phases and point to the potential of all of these phases for fostering the development of students- robust knowledge of the logic of inference when using computer based simulations to model and investigate statistical questions.
Abstract: In this paper we examine the use of global texture analysis based approaches for the purpose of Persian font recognition in machine-printed document images. Most existing methods for font recognition make use of local typographical features and connected component analysis. However derivation of such features is not an easy task. Gabor filters are appropriate tools for texture analysis and are motivated by human visual system. Here we consider document images as textures and use Gabor filter responses for identifying the fonts. The method is content independent and involves no local feature analysis. Two different classifiers Weighted Euclidean Distance and SVM are used for the purpose of classification. Experiments on seven different type faces and four font styles show average accuracy of 85% with WED and 82% with SVM classifier over typefaces
Abstract: The main goal of this paper is to establish a
methodology for testing and optimizing GPRS performance over
Libya GSM network as well as to propose a suitable optimization
technique to improve performance. Some measurements of
download, upload, throughput, round-trip time, reliability, handover,
security enhancement and packet loss over a GPRS access network
were carried out. Measured values are compared to the theoretical
values that could be calculated beforehand. This data should be
processed and delivered by the server across the wireless network to
the client. The client on the fly takes those pieces of the data and
process immediately. Also, we illustrate the results by describing the
main parameters that affect the quality of service. Finally, Libya-s
two mobile operators, Libyana Mobile Phone and Al-Madar al-
Jadeed Company are selected as a case study to validate our
methodology.
Abstract: The paper describes the evaluation of quality of
control for cases of controlled non-minimal phase plants. Control
circuits containing non-minimal phase plants have different
properties, they manifest reversed reaction at the beginning of unit
step response. For these types of plants are developed special
criterion of quality of control, which considers the difference and can
be helpful for synthesis of optimal controller tuning. All results are
clearly presented using Matlab/Simulink models.
Abstract: Positron emission particle tracking (PEPT) is a
technique in which a single radioactive tracer particle can be
accurately tracked as it moves. A limitation of PET is that in order to
reconstruct a tomographic image it is necessary to acquire a large
volume of data (millions of events), so it is difficult to study rapidly
changing systems. By considering this fact, PEPT is a very fast
process compared with PET.
In PEPT detecting both photons defines a line and the annihilation
is assumed to have occurred somewhere along this line. The location
of the tracer can be determined to within a few mm from coincident
detection of a small number of pairs of back-to-back gamma rays and
using triangulation. This can be achieved many times per second and
the track of a moving particle can be reliably followed. This
technique was invented at the University of Birmingham [1].
The attempt in PEPT is not to form an image of the tracer particle
but simply to determine its location with time. If this tracer is
followed for a long enough period within a closed, circulating system
it explores all possible types of motion.
The application of PEPT to industrial process systems carried out
at the University of Birmingham is categorized in two subjects: the
behaviour of granular materials and viscous fluids. Granular
materials are processed in industry for example in the manufacture of
pharmaceuticals, ceramics, food, polymers and PEPT has been used
in a number of ways to study the behaviour of these systems [2].
PEPT allows the possibility of tracking a single particle within the
bed [3]. Also PEPT has been used for studying systems such as: fluid
flow, viscous fluids in mixers [4], using a neutrally-buoyant tracer
particle [5].
Abstract: Automatic detection of bleeding is of practical
importance since capsule endoscopy produces an extremely large
number of images. Algorithm development of bleeding detection in
the digestive tract is difficult due to different contrasts among the
images, food dregs, secretion and others. In this study, were assigned
weighting factors derived from the independent features of the
contrast and brightness between bleeding and normality. Spectral
analysis based on weighting factors was fast and accurate. Results
were a sensitivity of 87% and a specificity of 90% when the accuracy
was determined for each pixel out of 42 endoscope images.
Abstract: Social, culture and artistic status of a society in
various historical eras is affected by numerous, and sometimes
imposed, factors that better understanding requires analysis of such
conditions. Throughout history Iran has been involved with
determining and significant events that examining each of these
events can improve the understanding of social conditions of this
country in the intended time. Mongolian conquest of Iran is one of
most significant events in the history of Iran with consequences that
never left Iranian societies. During this tragic invasion and
subsequent devastating wars, which led to establishment of Ilkhanate
dynasty, numerous cultural and artistic changes occurred both in
Mongolian conquerors and Iranian society. This study examines these
changes with a glimpse towards art and architecture as important part
of cultural aspects and social communication.
Abstract: Feature and model selection are in the center of
attention of many researches because of their impact on classifiers-
performance. Both selections are usually performed separately but
recent developments suggest using a combined GA-SVM approach to
perform them simultaneously. This approach improves the
performance of the classifier identifying the best subset of variables
and the optimal parameters- values. Although GA-SVM is an
effective method it is computationally expensive, thus a rough
method can be considered. The paper investigates a joined approach
of Genetic Algorithm and kernel matrix criteria to perform
simultaneously feature and model selection for SVM classification
problem. The purpose of this research is to improve the classification
performance of SVM through an efficient approach, the Kernel
Matrix Genetic Algorithm method (KMGA).