Abstract: This paper presents the exergy analysis of a
desalination unit using humidification-dehumidification process.
Here, this unit is considered as a thermal system with three main
components, which are the heating unit by using a solar collector, the
evaporator or the humidifier, and the condenser or the dehumidifier.
In these components the exergy is a measure of the quality or grade
of energy and it can be destroyed in them. According to the second
law of thermodynamics this destroyed part is due to irreversibilities
which must be determined to obtain the exergetic efficiency of the
system.
In the current paper a computer program has been developed using
visual basic to determine the exergy destruction and the exergetic
efficiencies of the components of the desalination unit at variable
operation conditions such as feed water temperature, outlet air
temperature, air to feed water mass ratio and salinity, in addition to
cooling water mass flow rate and inlet temperature, as well as
quantity of solar irradiance.
The results obtained indicate that the exergy efficiency of the
humidifier increases by increasing the mass ratio and decreasing the
outlet air temperature. In the other hand the exergy efficiency of the
condenser increases with the increase of this ratio and also with the
increase of the outlet air temperature.
Abstract: In this paper, experimental testing and numerical analysis were used to investigate the effect of tube thickness on the face bending for concrete filled hollow sections connected to other structural members using Extended Hollobolts. Six samples were tested experimentally by applying pull-out load on the bolts. These samples were designed to fail by column face bending. The main variable in all tests is the column face thickness. Finite element analyses were also performed using ABAQUS 6.11 to extend the experimental results and to quantify the effect of column face thickness. Results show that, the column face thickness has a clear impact on the connection strength and stiffness. However, the amount of improvement in the connection stiffness by changing the column face thickness from 5mm to 6.3mm seems to be higher than that when increasing it from 6.3mm to 8mm. The displacement at which the bolts start pulling-out from their holes increased with the use of thinner column face due to the high flexibility of the section. At the ultimate strength, the yielding of the column face propagated to the column corner and there was no yielding in its walls. After the ultimate resistance is reached, the propagation of the yielding was mainly in the column face with a miner yielding in the walls.
Abstract: The hydraulic actuated excavator, being a non-linear
mobile machine, encounters many uncertainties. There are
uncertainties in the hydraulic system in addition to the uncertain
nature of the load. The simulation results obtained in this study show
that there is a need for intelligent control of such machines and in
particular interval type-2 fuzzy controller is most suitable for
minimizing the position error of a typical excavator-s bucket under
load variations. We consider the model parameter uncertainties such
as hydraulic fluid leakage and friction. These are uncertainties which
also depend up on the temperature and alter bulk modulus and
viscosity of the hydraulic fluid. Such uncertainties together with the
load variations cause chattering of the bucket position. The interval
type-2 fuzzy controller effectively eliminates the chattering and
manages to control the end-effecter (bucket) position with positional
error in the order of few millimeters.
Abstract: This study introduces a new method for detecting,
sorting, and localizing spikes from multiunit EEG recordings. The
method combines the wavelet transform, which localizes distinctive
spike features, with Super-Paramagnetic Clustering (SPC) algorithm,
which allows automatic classification of the data without assumptions
such as low variance or Gaussian distributions. Moreover, the method
is capable of setting amplitude thresholds for spike detection. The
method makes use of several real EEG data sets, and accordingly the
spikes are detected, clustered and their times were detected.
Abstract: Global Software Development (GSD) projects are
passing through different boundaries of a company, country and even
in other continents where time zone differs between both sites.
Beside many benefits of such development, research declared plenty
of negative impacts on these GSD projects. It is important to
understand problems which may lie during the execution of GSD
project with different time zones. This research project discussed and
provided different issues related to time delays in GSD projects. In
this paper, authors investigated some of the time delay factors which
usually lie in GSD projects with different time zones. This
investigation is done through systematic review of literature.
Furthermore, the practices to overcome these delay factors which
have already been reported in literature and GSD organizations are
also explored through literature survey and case studies.
Abstract: The complexity of today-s software systems makes
collaborative development necessary to accomplish tasks.
Frameworks are necessary to allow developers perform their tasks
independently yet collaboratively. Similarity detection is one of the
major issues to consider when developing such frameworks. It allows
developers to mine existing repositories when developing their own
views of a software artifact, and it is necessary for identifying the
correspondences between the views to allow merging them and
checking their consistency. Due to the importance of the
requirements specification stage in software development, this paper
proposes a framework for collaborative development of Object-
Oriented formal specifications along with a similarity detection
approach to support the creation, merging and consistency checking
of specifications. The paper also explores the impact of using
additional concepts on improving the matching results. Finally, the
proposed approach is empirically evaluated.
Abstract: The field of biomedical materials plays an imperative
requisite and a critical role in manufacturing a variety of biological
artificial replacements in a modern world. Recently, titanium (Ti)
materials are being used as biomaterials because of their superior
corrosion resistance and tremendous specific strength, free- allergic
problems and the greatest biocompatibility compared to other
competing biomaterials such as stainless steel, Co-Cr alloys,
ceramics, polymers, and composite materials. However, regardless of
these excellent performance properties, Implantable Ti materials have
poor shear strength and wear resistance which limited their
applications as biomaterials. Even though the wear properties of Ti
alloys has revealed some improvements, the crucial effectiveness of
biomedical Ti alloys as wear components requires a comprehensive
deep understanding of the wear reasons, mechanisms, and techniques
that can be used to improve wear behavior. This review examines
current information on the effect of thermal and thermomechanical
processing of implantable Ti materials on the long-term prosthetic
requirement which related with wear behavior. This paper focuses
mainly on the evolution, evaluation and development of effective
microstructural features that can improve wear properties of bio
grade Ti materials using thermal and thermomechanical treatments.
Abstract: Concrete performance is strongly affected by the
particle packing degree since it determines the distribution of the
cementitious component and the interaction of mineral particles. By
using packing theory designers will be able to select optimal
aggregate materials for preparing concrete with low cement content,
which is beneficial from the point of cost. Optimum particle packing
implies minimizing porosity and thereby reducing the amount of
cement paste needed to fill the voids between the aggregate particles,
taking also the rheology of the concrete into consideration. For
reaching good fluidity superplasticizers are required. The results from
pilot tests at Luleå University of Technology (LTU) show various
forms of the proposed theoretical models, and the empirical approach
taken in the study seems to provide a safer basis for developing new,
improved packing models.
Abstract: The primary cause of Total Hip Replacement (THR)
failure for younger patients is aseptic loosening. This complication is
twice more likely to happen in acetabular cup than in femoral stem.
Excessive micromotion between bone and implant will cause
loosening and it depends in patient activities, age and bone. In this
project, the effects of different metal back design of press fit on
osseointegration of the acetabular cup are carried out. Commercial
acetabular cup designs, namely Spiked, Superfix and Quadrafix are
modelled and analyzed using commercial finite element software.
The diameter of acetabular cup is based on the diameter of acetabular
rim to make sure the component fit to the acetabular cavity. A new
design of acetabular cup are proposed and analyzed to get better
osseointegration between the bones and implant interface. Results
shows that the proposed acetabular cup designs are more stable
compared to other designs with respect to stress and displacement
aspects.
Abstract: Heart failure is the most common reason of death
nowadays, but if the medical help is given directly, the patient-s life
may be saved in many cases. Numerous heart diseases can be
detected by means of analyzing electrocardiograms (ECG). Artificial
Neural Networks (ANN) are computer-based expert systems that
have proved to be useful in pattern recognition tasks. ANN can be
used in different phases of the decision-making process, from
classification to diagnostic procedures. This work concentrates on a
review followed by a novel method.
The purpose of the review is to assess the evidence of healthcare
benefits involving the application of artificial neural networks to the
clinical functions of diagnosis, prognosis and survival analysis, in
ECG signals. The developed method is based on a compound neural
network (CNN), to classify ECGs as normal or carrying an
AtrioVentricular heart Block (AVB). This method uses three
different feed forward multilayer neural networks. A single output
unit encodes the probability of AVB occurrences. A value between 0
and 0.1 is the desired output for a normal ECG; a value between 0.1
and 1 would infer an occurrence of an AVB. The results show that
this compound network has a good performance in detecting AVBs,
with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy
value is 87.9%.
Abstract: Algae-based fuel are considered a promising sources
of clean energy, and because it has many advantages over traditional
biofuel, research and business ventures have driven into developing
and producing Algal-biofuel. But its production stages create a cost
structure that it is not competitive with traditional fuels. Therefore,
cost becomes the main obstacle in commercial production purpose.
However, the present research which aims at using cost structure
model, and designed MS-Dose program, to investigate the a mount of
production cost and determined the parameter had great effect on it,
second to measured the amount of contribution rate of algae in
process the pollution by capturing Co2 from air . The result generated
from the model shows that the production cost of biomass is between
$0.137 /kg for 100 ha and $0.132 /kg for 500 ha which was less than
cost of other studies, while gallon costs between $3.4 - 3.5, more
than traditional sources of oil about $1 ,which regarded as a rate of
contribution of algal in capturing CO2 from air.
Abstract: Urban road network traffic has become one of the
most studied research topics in the last decades. This is mainly due to
the enlargement of the cities and the growing number of motor
vehicles traveling in this road network. One of the most sensitive
problems is to verify if the network is congestion-free. Another
related problem is the automatic reconfiguration of the network
without building new roads to alleviate congestions. These problems
require an accurate model of the traffic to determine the steady state
of the system. An alternative is to simulate the traffic to see if there
are congestions and when and where they occur. One key issue is to
find an adequate model for road intersections. Once the model
established, either a large scale model is built or the intersection is
represented by its performance measures and simulation for analysis.
In both cases, it is important to seek the queueing model to represent
the road intersection. In this paper, we propose to model the road
intersection as a BCMP queueing network and we compare this
analytical model against a simulation model for validation.