Abstract: Petri Net being one of the most useful graphical tools for modelling complex asynchronous systems, we have used Petri Net to model multi-track railway level crossing system. The roadway has been augmented with four half-size barriers. For better control, a three stage control mechanism has been introduced to ensure that no road-vehicle is trapped on the level crossing. Timed Petri Net is used to include the temporal nature of the signalling system. Safeness analysis has also been included in the discussion section.
Abstract: Open and distance learning is a fairly new concept in
Malawi. The major public provider, the Malawi College of Distance
Education, rolled out its activities only about 40 years ago. Over the
years, the demand for distance education has tremendously increased.
The present government has displayed positive political will to uplift
ODL as outlined in the Malawi Growth and Development Strategy as
well as the National Education Sector Plan. A growing national
interest in education coupled with political stability and a booming
ICT industry also raise hope for success. However, a fragile economy
with a GNI per capita of -US$ 200 over the last decade, poor public
funding, erratic power supply and lack of expertise put strain on
efforts towards the promotion of ODL initiatives. Despite the
challenges, the nation appears determined to go flat out and explore
all possible avenues that could revolutionise education access and
equity through ODL.
Abstract: One astonishing capability of humans is to recognize thousands of different objects visually, and to learn the semantic association between those objects and words referring to them. This work is an attempt to build a computational model of such capacity,simulating the process by which infants learn how to recognize objects and words through exposure to visual stimuli and vocal sounds.One of the main fact shaping the brain of a newborn is that lights and colors come from entities of the world. Gradually the visual system learn which light sensations belong to same entities, despite large changes in appearance. This experience is common between humans and several other mammals, like non-human primates. But humans only can recognize a huge variety of objects, most manufactured by himself, and make use of sounds to identify and categorize them. The aim of this model is to reproduce these processes in a biologically plausible way, by reconstructing the essential hierarchy of cortical circuits on the visual and auditory neural paths.
Abstract: This paper presents a Reliability-Based Topology
Optimization (RBTO) based on Evolutionary Structural Optimization
(ESO). An actual design involves uncertain conditions such as
material property, operational load and dimensional variation.
Deterministic Topology Optimization (DTO) is obtained without
considering of the uncertainties related to the uncertainty parameters.
However, RBTO involves evaluation of probabilistic constraints,
which can be done in two different ways, the reliability index
approach (RIA) and the performance measure approach (PMA). Limit
state function is approximated using Monte Carlo Simulation and
Central Composite Design for reliability analysis. ESO, one of the
topology optimization techniques, is adopted for topology
optimization. Numerical examples are presented to compare the DTO
with RBTO.
Abstract: For several high speed networks, providing resilience against failures is an essential requirement. The main feature for designing next generation optical networks is protecting and restoring high capacity WDM networks from the failures. Quick detection, identification and restoration make networks more strong and consistent even though the failures cannot be avoided. Hence, it is necessary to develop fast, efficient and dependable fault localization or detection mechanisms. In this paper we propose a new fault localization algorithm for WDM networks which can identify the location of a failure on a failed lightpath. Our algorithm detects the failed connection and then attempts to reroute data stream through an alternate path. In addition to this, we develop an algorithm to analyze the information of the alarms generated by the components of an optical network, in the presence of a fault. It uses the alarm correlation in order to reduce the list of suspected components shown to the network operators. By our simulation results, we show that our proposed algorithms achieve less blocking probability and delay while getting higher throughput.
Abstract: Environmental micro-organisms include a large number of taxa and some species that are generally considered nonpathogenic, but can represent a risk in certain conditions, especially for elderly people and immunocompromised individuals. Chemotaxonomic identification techniques are powerful tools for environmental micro-organisms, and cellular fatty acid methyl esters (FAME) content is a powerful fingerprinting identification technique. A system based on an unsupervised artificial neural network (ANN) was set up using the fatty acid profiles of standard bacterial strains, obtained by gas-chromatography, used as learning data. We analysed 45 certified strains belonging to Acinetobacter, Aeromonas, Alcaligenes, Aquaspirillum, Arthrobacter, Bacillus, Brevundimonas, Enterobacter, Flavobacterium, Micrococcus, Pseudomonas, Serratia, Shewanella and Vibrio genera. A set of 79 bacteria isolated from a drinking water line (AMGA, the major water supply system in Genoa) were used as an example for identification compared to standard MIDI method. The resulting ANN output map was found to be a very powerful tool to identify these fresh isolates.
Abstract: Recommender Systems act as personalized decision
guides, aiding users in decisions on matters related to personal taste.
Most previous research on Recommender Systems has focused on the
statistical accuracy of the algorithms driving the systems, with no
emphasis on the trustworthiness of the user. RS depends on
information provided by different users to gather its knowledge. We
believe, if a large group of users provide wrong information it will
not be possible for the RS to arrive in an accurate conclusion. The
system described in this paper introduce the concept of Testing the
knowledge of user to filter out these “bad users".
This paper emphasizes on the mechanism used to provide robust
and effective recommendation.
Abstract: In this paper, a simulated annealing algorithm has been developed to optimize machining parameters in turning operation on cylindrical workpieces. The turning operation usually includes several passes of rough machining and a final pass of finishing. Seven different constraints are considered in a non-linear model where the goal is to achieve minimum total cost. The weighted total cost consists of machining cost, tool cost and tool replacement cost. The computational results clearly show that the proposed optimization procedure has considerably improved total operation cost by optimally determining machining parameters.
Abstract: The aim of this contribution is to present a new
approach in modeling the electrical activity of the human heart. A
recurrent artificial neural network is being used in order to exhibit a
subset of the dynamics of the electrical behavior of the human heart.
The proposed model can also be used, when integrated, as a
diagnostic tool of the human heart system.
What makes this approach unique is the fact that every model is
being developed from physiological measurements of an individual.
This kind of approach is very difficult to apply successfully in many
modeling problems, because of the complexity and entropy of the
free variables describing the complex system. Differences between
the modeled variables and the variables of an individual, measured at
specific moments, can be used for diagnostic purposes. The sensor
fusion used in order to optimize the utilization of biomedical sensors
is another point that this paper focuses on. Sensor fusion has been
known for its advantages in applications such as control and
diagnostics of mechanical and chemical processes.
Abstract: Proteomics is one of the largest areas of research for
bioinformatics and medical science. An ambitious goal of proteomics
is to elucidate the structure, interactions and functions of all proteins
within cells and organisms. Predicting Protein-Protein Interaction
(PPI) is one of the crucial and decisive problems in current research.
Genomic data offer a great opportunity and at the same time a lot of
challenges for the identification of these interactions. Many methods
have already been proposed in this regard. In case of in-silico
identification, most of the methods require both positive and negative
examples of protein interaction and the perfection of these examples
are very much crucial for the final prediction accuracy. Positive
examples are relatively easy to obtain from well known databases. But
the generation of negative examples is not a trivial task. Current PPI
identification methods generate negative examples based on some
assumptions, which are likely to affect their prediction accuracy.
Hence, if more reliable negative examples are used, the PPI prediction
methods may achieve even more accuracy. Focusing on this issue, a
graph based negative example generation method is proposed, which
is simple and more accurate than the existing approaches. An
interaction graph of the protein sequences is created. The basic
assumption is that the longer the shortest path between two
protein-sequences in the interaction graph, the less is the possibility of
their interaction. A well established PPI detection algorithm is
employed with our negative examples and in most cases it increases
the accuracy more than 10% in comparison with the negative pair
selection method in that paper.
Abstract: To provide a better understanding of fair share policies supported by current production schedulers and their impact on scheduling performance, A relative fair share policy supported in four well-known production job schedulers is evaluated in this study. The experimental results show that fair share indeed reduces heavy-demand users from dominating the system resources. However, the detailed per-user performance analysis show that some types of users may suffer unfairness under fair share, possibly due to priority mechanisms used by the current production schedulers. These users typically are not heavy-demands users but they have mixture of jobs that do not spread out.
Abstract: Following the laser ablation studies leading to a
theory of nuclei confinement by a Debye layer mechanism, we
present here numerical evaluations for the known stable nuclei where
the Coulomb repulsion is included as a rather minor component
especially for lager nuclei. In this research paper the required
physical conditions for the formation and stability of nuclei
particularly endothermic nuclei with mass number greater than to
which is an open astrophysical question have been investigated.
Using the Debye layer mechanism, nuclear surface energy, Fermi
energy and coulomb repulsion energy it is possible to find conditions
under which the process of nucleation is permitted in early universe.
Our numerical calculations indicate that about 200 second after the
big bang at temperature of about 100 KeV and subrelativistic region
with nucleon density nearly equal to normal nuclear density namely,
10cm all endothermic and exothermic nuclei have been
formed.
Abstract: Technology transfer of renewable energy technologies is very often unsuccessful in the developing world. Aside from challenges that have social, economic, financial, institutional and environmental dimensions, technology transfer has generally been misunderstood, and largely seen as mere delivery of high tech equipment from developed to developing countries or within the developing world from R&D institutions to society. Technology transfer entails much more, including, but not limited to: entire systems and their component parts, know-how, goods and services, equipment, and organisational and managerial procedures. Means to facilitate the successful transfer of energy technologies, including the sharing of lessons are subsequently extremely important for developing countries as they grapple with increasing energy needs to sustain adequate economic growth and development. Improving the success of technology transfer is an ongoing process as more projects are implemented, new problems are encountered and new lessons are learnt. Renewable energy is also critical to improve the quality of lives of the majority of people in developing countries. In rural areas energy is primarily traditional biomass. The consumption activities typically occur in an inefficient manner, thus working against the notion of sustainable development. This paper explores the implementation of technology transfer in the developing world (sub-Saharan Africa). The focus is necessarily on RETs since most rural energy initiatives are RETs-based. Additionally, it aims to highlight some lessons drawn from the cited RE projects and identifies notable differences where energy technology transfer was judged to be successful. This is done through a literature review based on a selection of documented case studies which are judged against the definition provided for technology transfer. This paper also puts forth research recommendations that might contribute to improved technology transfer in the developing world. Key findings of this paper include: Technology transfer cannot be complete without satisfying pre-conditions such as: affordability, maintenance (and associated plans), knowledge and skills transfer, appropriate know how, ownership and commitment, ability to adapt technology, sound business principles such as financial viability and sustainability, project management, relevance and many others. It is also shown that lessons are learnt in both successful and unsuccessful projects.
Abstract: The aim of this paper is to provide a better
understanding of the implementation of Project Management
practices by UiTM contractors to ensure project success. A
questionnaire survey was administered to 120 UiTM contractors in
Malaysia. The purpose of this method was to gather information on
the contractors- project background and project management skills. It
was found that all of the contractors had basic knowledge and
understanding of project management skills. It is suggested that a
reasonable project plan and an appropriate organizational structure
are influential factors for project success. It is recommended that the
contractors need to have an effective program of work and up to date
information system are emphasized.
Abstract: An inflation–extension test with human vena cava
inferior was performed with the aim to fit a material model. The vein
was modeled as a thick–walled tube loaded by internal pressure and
axial force. The material was assumed to be an incompressible
hyperelastic fiber reinforced continuum. Fibers are supposed to be
arranged in two families of anti–symmetric helices. Considered
anisotropy corresponds to local orthotropy. Used strain energy
density function was based on a concept of limiting strain
extensibility. The pressurization was comprised by four pre–cycles
under physiological venous loading (0 – 4kPa) and four cycles under
nonphysiological loading (0 – 21kPa). Each overloading cycle was
performed with different value of axial weight. Overloading data
were used in regression analysis to fit material model. Considered
model did not fit experimental data so good. Especially predictions
of axial force failed. It was hypothesized that due to
nonphysiological values of loading pressure and different values of
axial weight the material was not preconditioned enough and some
damage occurred inside the wall. A limiting fiber extensibility
parameter Jm was assumed to be in relation to supposed damage.
Each of overloading cycles was fitted separately with different values
of Jm. Other parameters were held the same. This approach turned out
to be successful. Variable value of Jm can describe changes in the
axial force – axial stretch response and satisfy pressure – radius
dependence simultaneously.
Abstract: Restructured electricity markets may provide
opportunities for producers to exercise market power maintaining
prices in excess of competitive levels. In this paper an oligopolistic
market is presented that all Generation Companies (GenCos) bid in a
Cournot model. Genetic algorithm (GA) is applied to obtain
generation scheduling of each GenCo as well as hourly market
clearing prices (MCP). In order to consider network constraints a
multiperiod framework is presented to simulate market clearing
mechanism in which the behaviors of market participants are
modelled through piecewise block curves. A mixed integer linear
programming (MILP) is employed to solve the problem. Impacts of
market clearing process on participants- characteristic and final
market prices are presented. Consequently, a novel multi-objective
model is addressed for security constrained optimal bidding strategy
of GenCos. The capability of price-maker GenCos to alter MCP is
evaluated through introducing an effective-supply curve. In addition,
the impact of exercising market power on the variation of market
characteristics as well as GenCos scheduling is studied.
Abstract: This paper numerically investigates the effects of input
speed on the overall dynamic characteristics of a multi-body system
with differently located revolute clearance joints without friction. A
typical planar slider-crank mechanism is used as a demonstration case
in which the effects of the input speed on the dynamic performance
of the mechanism with a revolute clearance joint between the crank
and connecting rod, and between the connecting rod and slider are
separately investigated with comprehensive observations numerically
presented. It is observed that, changing the driving speed of a multibody
system makes the behavior of the system to change from
either periodic to chaotic, or chaotic to periodic depending on which
joint has clearance. The location of the clearance revolute joint and
the operating speed of a multi-body system play a crucial role in
predicting accurately the dynamic responses of the system. Therefore
the dynamic behavior of one clearance revolute joint cannot be used
as a general case for a mechanical system.
Abstract: The Ministry of Defense (MoD) spends hundreds of
millions of dollars on software to support its infrastructure, operate
its weapons and provide command, control, communications,
computing, intelligence, surveillance, and reconnaissance (C4ISR)
functions. These and other all new advanced systems have a common
critical component is information technology. Defense and
Aerospace environment is continuously striving to keep up with
increasingly sophisticated Information Technology (IT) in order to
remain effective in today-s dynamic and unpredictable threat
environment. This makes it one of the largest and fastest growing
expenses of Defense. Hundreds of millions of dollars spent a year on
IT projects. But, too many of those millions are wasted on costly
mistakes. Systems that do not work properly, new components that
are not compatible with old once, trendily new applications that do
not really satisfy defense needs or lost though poorly managed
contracts.
This paper investigates and compiles the effective strategies that
aim to end exasperation with low returns and high cost of
Information Technology Acquisition for defense; it tries to show how
to maximize value while reducing time and expenditure.
Abstract: Alumina matrix composites with addition of hexagonal boron nitride (hBN), acting as solid lubricant, were produced. Main purpose of solid lubricants is to dispose the necessity of using cooling lubricants in machining process. Hot pressing was used as a consolidating process for Al2O3-x%wt.hBN (x=1/ 2,5/ 5 /7,5 /10) composites. Properties of sinters such as relative density, hardness, Young-s modulus and fracture toughness were examined. Obtained samples characterize by high relative density. Hardness and fracture toughness values allow the use of alumina – hBN composites for machining steels even in hardened condition. However it was observed that high weight content of hBN can negatively influence the mechanical properties of composites.
Abstract: Manufacturing components of fiber-reinforced
thermoplastics requires three steps: heating the matrix, forming and
consolidation of the composite and terminal cooling the matrix. For
the heating process a pre-determined temperature distribution through
the layers and the thickness of the pre-consolidated sheets is
recommended to enable forming mechanism. Thus, a design for the
heating process for forming composites with thermoplastic matrices
is necessary. To obtain a constant temperature through thickness and
width of the sheet, the heating process was analyzed by the help of
the finite element method. The simulation models were validated by
experiments with resistance thermometers as well as with an infrared
camera. Based on the finite element simulation, heating methods for
infrared radiators have been developed. Using the numeric
simulation many iteration loops are required to determine the process
parameters. Hence, the initiation of a model for calculating relevant
process parameters started applying regression functions.