Abstract: The paper involves a chain of activities from
synthesis, establishment of the methodology for characterization and
testing of novel protective materials through the pilot production and
application on model supports.
It summarizes the results regarding the development of the pilot
production protocol for newly developed self-cleaning materials. The
optimization of the production parameters was completed in order to
improve the most important functional properties (mineralogy
characteristics, particle size, self-cleaning properties and
photocatalytic activity) of the newly designed nanocomposite
material.
Abstract: This study investigates how AlGaAs/GaAs thin film
solar cells perform under varying global solar spectrum due to the
changes of environmental parameters such as the air mass and the
atmospheric turbidity. The solar irradiance striking the solar cell is
simulated using the spectral irradiance model SMARTS2 (Simple
Model of the Atmospheric Radiative Transfer of Sunshine) for clear
skies on the site of Setif (Algeria). The results show a reduction in the
short circuit current due to increasing atmospheric turbidity, it is
63.09% under global radiation. However increasing air mass leads to
a reduction in the short circuit current of 81.73%. The efficiency
decreases with increasing atmospheric turbidity and air mass.
Abstract: Near infrared (NIR) spectroscopy has always been of
great interest in the food and agriculture industries. The development
of prediction models has facilitated the estimation process in recent
years. In this study, 110 crude palm oil (CPO) samples were used to
build a free fatty acid (FFA) prediction model. 60% of the collected
data were used for training purposes and the remaining 40% used for
testing. The visible peaks on the NIR spectrum were at 1725 nm and
1760 nm, indicating the existence of the first overtone of C-H bands.
Principal component regression (PCR) was applied to the data in
order to build this mathematical prediction model. The optimal
number of principal components was 10. The results showed
R2=0.7147 for the training set and R2=0.6404 for the testing set.
Abstract: The star network is one of the promising
interconnection networks for future high speed parallel computers, it
is expected to be one of the future-generation networks. The star
network is both edge and vertex symmetry, it was shown to have
many gorgeous topological proprieties also it is owns hierarchical
structure framework. Although much of the research work has been
done on this promising network in literature, it still suffers from
having enough algorithms for load balancing problem. In this paper
we try to work on this issue by investigating and proposing an
efficient algorithm for load balancing problem for the star network.
The proposed algorithm is called Star Clustered Dimension Exchange
Method SCDEM to be implemented on the star network. The
proposed algorithm is based on the Clustered Dimension Exchange
Method (CDEM). The SCDEM algorithm is shown to be efficient in
redistributing the load balancing as evenly as possible among all
nodes of different factor networks.
Abstract: To develop AZ91D magnesium alloys with improved
properties, we have applied TiN and VN/TiN multilayer coatings
using DC magnetron sputter technique. Coating structure, surface
morphology, chemical bonding and corrosion resistance of coatings
were analyzed by x-ray diffraction (XRD), scanning electron
microscope (SEM), x-ray photoelectron spectroscopy (XPS), and
tafel extrapolation method, respectively. XPS analysis reveal that VN
overlayer reacts with oxygen at the VN/TiN interface and forms more
stable TiN layer. Morphological investigations and the corrosion
results show that VN/TiN multilayer thin film coatings are quite
effective to optimize the corrosion resistance of Mg alloys.
Abstract: The final step to complete the “Analytical Systems
Engineering Process” is the “Allocated Architecture” in which all
Functional Requirements (FRs) of an engineering system must be
allocated into their corresponding Physical Components (PCs). At
this step, any design for developing the system’s allocated
architecture in which no clear pattern of assigning the exclusive
“responsibility” of each PC for fulfilling the allocated FR(s) can be
found is considered a poor design that may cause difficulties in
determining the specific PC(s) which has (have) failed to satisfy a
given FR successfully. The present study utilizes the Axiomatic
Design method principles to mathematically address this problem and
establishes an “Axiomatic Model” as a solution for reaching good
alternatives for developing the allocated architecture. This study
proposes a “loss Function”, as a quantitative criterion to monetarily
compare non-ideal designs for developing the allocated architecture
and choose the one which imposes relatively lower cost to the
system’s stakeholders. For the case-study, we use the existing design
of U. S. electricity marketing subsystem, based on data provided by
the U.S. Energy Information Administration (EIA). The result for
2012 shows the symptoms of a poor design and ineffectiveness due to
coupling among the FRs of this subsystem.
Abstract: Self-compacting concrete (SCC) developed in Japan
in the late 80s has enabled the construction industry to reduce
demand on the resources, improve the work condition and also
reduce the impact of environment by elimination of the need for
compaction. Fuzzy logic (FL) approaches has recently been used to
model some of the human activities in many areas of civil
engineering applications. Especially from these systems in the model
experimental studies, very good results have been obtained. In the
present study, a model for predicting compressive strength of SCC
containing various proportions of fly ash, as partial replacement of
cement has been developed by using Fuzzy Inference System (FIS).
For the purpose of building this model, a database of experimental
data were gathered from the literature and used for training and
testing the model. The used data as the inputs of fuzzy logic models
are arranged in a format of five parameters that cover the total binder
content, fly ash replacement percentage, water content,
superplasticizer and age of specimens. The training and testing results
in the fuzzy logic model have shown a strong potential for predicting
the compressive strength of SCC containing fly ash in the considered
range.
Abstract: Machining parameters are very important in
determining the surface quality of any material. In the past decade,
some new engineering materials were developed for the
manufacturing industry which created a need to conduct an
investigation on the impact of the said parameters on their surface
roughness. Polyurethane (PU) block is widely used in the automotive
industry to manufacture parts such as checking fixtures that are used
to verify the dimensional accuracy of automotive parts. In this paper,
the design of experiment (DOE) was used to investigate on the effect
of the milling parameters on the PU block. Furthermore, an analysis
of the machined surface chemical composition was done using
scanning electron microscope (SEM). It was found that the surface
roughness of the PU block is severely affected when PU undergoes a
flood machining process instead of a dry condition. In addition the
stepover and the silicon content were found to be the most significant
parameters that influence the surface quality of the PU block.
Abstract: Safety is one of the most important considerations
when buying a new car. While active safety aims at avoiding
accidents, passive safety systems such as airbags and seat belts
protect the occupant in case of an accident. In addition to legal
regulations, organizations like Euro NCAP provide consumers with
an independent assessment of the safety performance of cars and
drive the development of safety systems in automobile industry.
Those ratings are mainly based on injury assessment reference values
derived from physical parameters measured in dummies during a car
crash test.
The components and sub-systems of a safety system are designed
to achieve the required restraint performance. Sled tests and other
types of tests are then carried out by car makers and their suppliers
to confirm the protection level of the safety system. A Knowledge
Discovery in Databases (KDD) process is proposed in order to
minimize the number of tests. The KDD process is based on the
data emerging from sled tests according to Euro NCAP specifications.
About 30 parameters of the passive safety systems from different data
sources (crash data, dummy protocol) are first analysed together with
experts opinions. A procedure is proposed to manage missing data
and validated on real data sets. Finally, a procedure is developed to
estimate a set of rough initial parameters of the passive system before
testing aiming at reducing the number of tests.
Abstract: Bamboo is extensively used in construction industry.
Low durability of bamboo due to fungus infestation and termites
attack under storage puts certain constrains for it usage as modern
structural material. Looking at many chemical formulations for
bamboo treatment leading to severe harmful environment effects,
research on eco-friendly preservatives for bamboo treatment has been
initiated world-over. In the present studies, eco-friendly preservative
for bamboo treatment has been developed. To validate its application
for structural purposes, investigation of effect of treatment on
compressive strength has been investigated. Neemoil (25%)
integrated with copper naphthenate (0.3%) on dilution with kerosene
oil impregnated into bamboo culm at 2 bar pressure, has shown
weight loss of only 3.15% in soil block analysis method. The results
from compressive strength analysis using HEICO Automatic
Compression Testing Machine reveal that preservative treatment has
not altered the structural properties of bamboo culms. Compressive
strength of control (11.72 N/mm2) and above treated samples (11.71
N/mm2) was found to be comparable.
Abstract: Electricity spot prices are highly volatile under
optimal generation capacity scenarios due to factors such as nonstorability
of electricity, peak demand at certain periods, generator
outages, fuel uncertainty for renewable energy generators, huge
investments and time needed for generation capacity expansion etc.
As a result market participants are exposed to price and volume risk,
which has led to the development of risk management practices. This
paper provides an overview of risk management practices by market
participants in electricity markets using financial derivatives.
Abstract: Fuzzy inference method based approach to the
forming of modular intellectual system of assessment the quality of
communication services is proposed. Developed under this approach
the basic fuzzy estimation model takes into account the
recommendations of the International Telecommunication Union in
respect of the operation of packet switching networks based on IPprotocol.
To implement the main features and functions of the fuzzy
control system of quality telecommunication services it is used
multilayer feedforward neural network.
Abstract: Metal matrix composites (MMCs) attract considerable
attention as a result from its ability in providing a high strength, high
modulus, high toughness, high impact properties, improving wear
resistance and providing good corrosion resistance compared to
unreinforced alloy. Aluminium Silicon (Al/Si) alloy MMC has been
widely used in various industrial sectors such as in transportation,
domestic equipment, aerospace, military, construction, etc.
Aluminium silicon alloy is an MMC that had been reinforced with
aluminium nitrate (AlN) particle and become a new generation
material use in automotive and aerospace sector. The AlN is one of
the advance material that have a bright prospect in future since it has
features such as lightweight, high strength, high hardness and
stiffness quality. However, the high degree of ceramic particle
reinforcement and the irregular nature of the particles along the
matrix material that contribute to its low density is the main problem
which leads to difficulties in machining process. This paper examined
the tool wear when milling AlSi/AlN Metal Matrix Composite using
a TiB2 (Titanium diboride) coated carbide cutting tool. The volume
of the AlN reinforced particle was 10% and milling process was
carried out under dry cutting condition. The TiB2 coated carbide
insert parameters used were at the cutting speed of (230, 300 and
370m/min, feed rate of 0.8, Depth of Cut (DoC) at 0.4m). The
Sometech SV-35 video microscope system used to quantify of the
tool wear. The result shown that tool life span increasing with the
cutting speeds at (370m/min, feed rate of 0.8mm/tooth and DoC at
0.4mm) which constituted an optimum condition for longer tool life
lasted until 123.2 mins. Meanwhile, at medium cutting speed which
at 300m/m, feed rate of 0.8mm/tooth and depth of cut at 0.4mm we
found that tool life span lasted until 119.86 mins while at low cutting
speed it lasted in 119.66 mins. High cutting speed will give the best
parameter in cutting AlSi/AlN MMCs material. The result will help
manufacturers in machining process of AlSi/AlN MMCs materials.
Abstract: Red blood cells (RBC) are the most common types of
blood cells and are the most intensively studied in cell biology. The
lack of RBCs is a condition in which the amount of hemoglobin level
is lower than normal and is referred to as “anemia”. Abnormalities in
RBCs will affect the exchange of oxygen. This paper presents a
comparative study for various techniques for classifying the RBCs as
normal or abnormal (anemic) using WEKA. WEKA is an open
source consists of different machine learning algorithms for data
mining applications. The algorithms tested are Radial Basis Function
neural network, Support vector machine, and K-Nearest Neighbors
algorithm. Two sets of combined features were utilized for
classification of blood cells images. The first set, exclusively consist
of geometrical features, was used to identify whether the tested blood
cell has a spherical shape or non-spherical cells. While the second
set, consist mainly of textural features was used to recognize the
types of the spherical cells. We have provided an evaluation based on
applying these classification methods to our RBCs image dataset
which were obtained from Serdang Hospital - Malaysia, and
measuring the accuracy of test results. The best achieved
classification rates are 97%, 98%, and 79% for Support vector
machines, Radial Basis Function neural network, and K-Nearest
Neighbors algorithm respectively.
Abstract: The classroom of the 21st century is an ever changing
forum for new and innovative thoughts and ideas. With increasing
technology and opportunity, students have rapid access to
information that only decades ago would have taken weeks to obtain.
Unfortunately, new techniques and technology are not the cure for
the fundamental problems that have plagued the classroom ever since
education was established. Class size has been an issue long debated
in academia. While it is difficult to pin point an exact number, it is
clear that in this case more does not mean better. By looking into the
success and pitfalls of classroom size the true advantages of smaller
classes will become clear. Previously, one class was comprised of 50
students. Being seventeen and eighteen- year- old students,
sometimes it was quite difficult for them to stay focused. To help
them understand and gain much knowledge, a researcher introduced
“The Theory of Multiple Intelligence” and this, in fact, enabled
students to learn according to their own learning preferences no
matter how they were being taught. In this lesson, the researcher
designed a cycle of learning activities involving all intelligences so
that everyone had equal opportunities to learn.
Abstract: Solar air heater is a type of heat exchanger which
transforms solar radiation into heat energy. The thermal performance
of conventional solar air heater has been found to be poor because of
the low convective heat transfer coefficient from the absorber plate to
the air. It is attributed to the formation of a very thin boundary layer
at the absorber plate surface commonly known as viscous sub-layer.
Thermal efficiency of solar air heater can be improved by providing
the artificial roughness on absorber plate is the most efficient
technique. In this paper an attempt is made to provide artificial
roughness by incorporating inclined multiple V-ribs in the underside
of the absorber plate. 60˚V – ribs are arranged inclined to the
direction of air flow. Performance of collector estimated theoretically
and experimentally. Results of the investigation reveal that thermal
efficiency of collector with multiple V-ribs increased by 14%.
Abstract: In this work, we propose and analyze a model of
Phytoplankton-Zooplankton interaction with harvesting considering
that some species are exploited commercially for food. Criteria for
local stability, instability and global stability are derived and some
threshold harvesting levels are explored to maintain the population
at an appropriate equilibrium level even if the species are exploited
continuously.Further,biological and bionomic equilibria of the system
are obtained and an optimal harvesting policy is also analysed using
the Pantryagin’s Maximum Principle.Finally analytical findings are
also supported by some numerical simulations.
Abstract: Lead being a toxic heavy metal that mankind is
exposed to the highest levels of this metal from environmental
pollutants. A total of 180 Male scalp hair samples were collected
from different environments in Greater Cairo (GC), i.e. industrial,
heavy traffic and rural areas (60 samples from each) having different
activities during the period of, 1/5/2010 to 1/11/2012. Hair samples
were collected during five stages. Data proved that the concentration
of lead in male industrial areas of Cairo ranged between 6.2847 to
19.0432 μg/g, with mean value of 12.3288 μg/g. On the other hand,
lead content of hair samples of residential-traffic areas ranged
between 2.8634 to 16.3311 μg/g with mean value of 9.7552 μg/g.
While lead concentration on the hair of the male residents living in
rural area ranged between 1.0499-9.0402μg/g with mean value of
4.7327 μg/g. The Pb concentration in scalp hair of Cairo residents of
residential-traffic and rural traffic areas was observed to follow the
same pattern. The pattern was that of decrease concentration of
summer and its increase in winter. Then, there was a marked increase
in Pb concentration of summer 2012, and this increase was
significant. These were obviously seen for the residential-traffic and
rural areas residents. Pb pollution in residents of industrial areas
showed the same seasonal pattern, but there was marked to decrease
in Pb concentration of summer 2012, and this decrease was
significant. Lead pollution in residents of GC was serious. It is worth
noting that the atmosphere is still contaminated by lead despite a
decade of using unleaded gasoline. Strong seasonal variation in
higher Pb concentration on winter than in summer was found. Major
contributions to the pollution with Pb could include industry
emissions, motor vehicle emissions and long transported dust from
outside Cairo. More attention should be paid to the reduction of Pb
content of the urban aerosol and to the Pb pollution health.
Abstract: Several of the practical industrial control processes are
multivariable processes. Due to the relation amid the variables
(interaction), delay in the loops, it is very intricate to design a
controller directly for these processes. So first, the interaction of the
variables is analyzed using Relative Normalized Gain Array
(RNGA), which considers the time constant, static gain and delay
time of the processes. Based on the effect of RNGA, relative gain
array (RGA) and NI, the pair (control configuration) of variables to
be controlled by decentralized control is selected. The equivalent
transfer function (ETF) of the process model is estimated as first
order process with delay using the corresponding elements in the
Relative gain array and Relative average residence time array
(RARTA) of the processes. Secondly, a decentralized Proportional-
Integral (PI) controller is designed for each ETF simply using
frequency response specifications. Finally, the performance and
robustness of the algorithm is comparing with existing related
approaches to validate the effectiveness of the projected algorithm.
Abstract: Image spam is a kind of email spam where the spam
text is embedded with an image. It is a new spamming technique
being used by spammers to send their messages to bulk of internet
users. Spam email has become a big problem in the lives of internet
users, causing time consumption and economic losses. The main
objective of this paper is to detect the image spam by using histogram
properties of an image. Though there are many techniques to
automatically detect and avoid this problem, spammers employing
new tricks to bypass those techniques, as a result those techniques are
inefficient to detect the spam mails. In this paper we have proposed a
new method to detect the image spam. Here the image features are
extracted by using RGB histogram, HSV histogram and combination
of both RGB and HSV histogram. Based on the optimized image
feature set classification is done by using k- Nearest Neighbor(k-NN)
algorithm. Experimental result shows that our method has achieved
better accuracy. From the result it is known that combination of RGB
and HSV histogram with k-NN algorithm gives the best accuracy in
spam detection.