Abstract: Ramadan requires individuals to abstain from food and fluid intake between sunrise and sunset; physiological considerations predict that poorer mood, physical performance and mental performance will result. In addition, any difficulties will be worsened because preparations for fasting and recovery from it often mean that nocturnal sleep is decreased in length, and this independently affects mood and performance.
A difficulty of interpretation in many studies is that the observed changes could be due to fasting but also to the decreased length of sleep and altered food and fluid intakes before and after the daytime fasting. These factors were separated in this study, which took place over three separate days and compared the effects of different durations of fasting (4, 8 or 16h) upon a wide variety of measures (including subjective and objective assessments of performance, body composition, dehydration and responses to a short bout of exercise) - but with an unchanged amount of nocturnal sleep, controlled supper the previous evening, controlled intakes at breakfast and daytime naps not being allowed. Many of the negative effects of fasting observed in previous studies were present in this experiment also. These findings indicate that fasting was responsible for many of the changes previously observed, though some effect of sleep loss, particularly if occurring on successive days (as would occur in Ramadan) cannot be excluded.
Abstract: Since injection engines have a considerable portion, in
consumption of energy and environmental pollution, using an
alternative source of energy with lower pollutant effects in this
regard is necessary.
Biodiesel fuel is a suitable alternative for gasoline in diesel
engines.
In this research the property of biodiesel, the function and the
pollution effects of diesel engine, when using 100% biodiesel, using
100% gasoline and mixing ratio of both fuels for comparing them,
have been investigated.
The researches have shown, using biodiesel fuel in prevalent
diesel engine, will reduce the pollutants such as Co, half burned
carbohydrate and suspended particles and a little increase in
oxidation will achieve while power consumption, particularly fuel
and thermal efficiency of diesel fuel has the same.
Abstract: Numerical analysis for the aerodynamic characteristics
of the WIG (wing-in ground effect) craft with highly cambered and
aspect ratio of one is performed to predict the ground effect for the
case of with- and without- lower-extension endplate. The analysis is
included varying angles of attack from 0 to10 deg. and ground
clearances from 5% of chord to 50%. Due to the ground effect, the lift
by rising in pressure on the lower surface is increased and the
influence of wing-tip vortices is decreased. These two significant
effects improve the lift-drag ratio. On the other hand, the endplate
prevents the high-pressure air escaping from the air cushion at the
wing tip and causes to increase the lift and lift-drag ratio further. It is
found from the visualization of computation results that two wing-tip
vortices are generated from each surface of the wing tip and their
strength are weak and diminished rapidly. Irodov-s criteria are also
evaluated to investigate the static height stability. The comparison of
Irodov-s criteria shows that the endplate improves the deviation of the
static height stability with respect to pitch angles and heights. As the
results, the endplate can improve the aerodynamic characteristics and
static height stability of wings in ground effect, simultaneously.
Abstract: Rapid urbanization, industrialization and population
growth have led to an increase in number of automobiles that cause
air pollution. It is estimated that road traffic contributes 60% of air
pollution in urban areas. A case by case assessment is required to
predict the air quality in urban situations, so as to evolve certain
traffic management measures to maintain the air quality levels with
in the tolerable limits. Calicut city in the state of Kerala, India has
been chosen as the study area. Carbon Monoxide (CO) concentration
was monitored at 15 links in Calicut city and air quality performance
was evaluated over each link. The CO pollutant concentration values
were compared with the National Ambient Air Quality Standards
(NAAQS), and the CO values were predicted by using CALINE4 and
IITLS and Linear regression models. The study has revealed that
linear regression model performs better than the CALINE4 and
IITLS models. The possible association between CO pollutant
concentration and traffic parameters like traffic flow, type of vehicle,
and traffic stream speed was also evaluated.
Abstract: In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.
Abstract: Documents clustering become an essential technology
with the popularity of the Internet. That also means that fast and
high-quality document clustering technique play core topics. Text
clustering or shortly clustering is about discovering semantically
related groups in an unstructured collection of documents. Clustering
has been very popular for a long time because it provides unique
ways of digesting and generalizing large amounts of information.
One of the issues of clustering is to extract proper feature (concept)
of a problem domain. The existing clustering technology mainly
focuses on term weight calculation. To achieve more accurate
document clustering, more informative features including concept
weight are important. Feature Selection is important for clustering
process because some of the irrelevant or redundant feature may
misguide the clustering results. To counteract this issue, the proposed
system presents the concept weight for text clustering system
developed based on a k-means algorithm in accordance with the
principles of ontology so that the important of words of a cluster can
be identified by the weight values. To a certain extent, it has resolved
the semantic problem in specific areas.
Abstract: When reconstructing a scenario, it is necessary to
know the structure of the elements present on the scene to have an
interpretation. In this work we link 3D scenes reconstruction to
evolutionary algorithms through the vision stereo theory. We
consider vision stereo as a method that provides the reconstruction of
a scene using only a couple of images of the scene and performing
some computation. Through several images of a scene, captured from
different positions, vision stereo can give us an idea about the threedimensional
characteristics of the world. Vision stereo usually
requires of two cameras, making an analogy to the mammalian vision
system. In this work we employ only a camera, which is translated
along a path, capturing images every certain distance. As we can not
perform all computations required for an exhaustive reconstruction,
we employ an evolutionary algorithm to partially reconstruct the
scene in real time. The algorithm employed is the fly algorithm,
which employ “flies" to reconstruct the principal characteristics of
the world following certain evolutionary rules.
Abstract: This paper reviews the objectives, methods and results of previous studies on biodrying of solid waste in several countries. Biodrying of solid waste is a novel technology in developing countries such as in Malaysia where high moisture content in organic waste makes the segregation process for recycling purposes complicated and diminishes the calorific value for the use of fuel source. In addition, the high moisture content also encourages the breeding of vectors and disease-bearing animals. From the laboratory results, the average moisture content of organic waste, paper, plastics and metals are 58.17%, 37.93%, 29.79% and 1.03% respectively for UKM campus. Biodrying of solid waste is a simple method of waste treatment as well as a cost-efficient technology to dry the solid waste. The process depends on temperature monitoring and air flow control along with the natural biodegradable process of organic waste. This review shows that the biodrying of solid waste method has high potential in treatment and recycling of solid waste, be useful for biodrying study and implementation in Malaysia.
Abstract: A cross sectional survey design was used to collect
data from 370 diabetic patients. Two instruments were used in
obtaining data; in-depth interview guide and researchers- developed
questionnaire. Fisher's exact test was used to investigate association
between the identified factors and nonadherence. Factors identified
were: socio-demographic factors such as: gender, age, marital status,
educational level and occupation; psychosocial obstacles such as:
non-affordability of prescribed diet, frustration due to the restriction,
limited spousal support, feelings of deprivation, feeling that
temptation is inevitable, difficulty in adhering in social gatherings
and difficulty in revealing to host that one is diabetic; health care
providers obstacles were: poor attitude of health workers, irregular
diabetes education in clinics , limited number of nutrition education
sessions/ inability of the patients to estimate the desired quantity of
food, no reminder post cards or phone calls about upcoming patient
appointments and delayed start of appointment / time wasting in
clinics.
Abstract: In the past years, the world has witnessed significant work in the field of Manufacturing. Special efforts have been made in the implementation of new technologies, management and control systems, among many others which have all evolved the field. Closely following all this, due to the scope of new projects and the need of turning the existing flexible ideas into more autonomous and intelligent ones, i.e.: moving toward a more intelligent manufacturing, the present paper emerges with the main aim of contributing to the analysis and a few customization issues of a new iCIM 3000 system at the IPSAM. In this process, special emphasis in made on the material flow problem. For this, besides offering a description and analysis of the system and its main parts, also some tips on how to define other possible alternative material flow scenarios and a partial analysis of the combinatorial nature of the problem are offered as well. All this is done with the intentions of relating it with the use of simulation tools, for which these have been briefly addressed with a special focus on the Witness simulation package. For a better comprehension, the previous elements are supported by a few figures and expressions which would help obtaining necessary data. Such data and others will be used in the future, when simulating the scenarios in the search of the best material flow configurations.
Abstract: Lately, significant work in the area of Intelligent
Manufacturing has become public and mainly applied within the
frame of industrial purposes. Special efforts have been made in the
implementation of new technologies, management and control
systems, among many others which have all evolved the field. Aware
of all this and due to the scope of new projects and the need of
turning the existing flexible ideas into more autonomous and
intelligent ones, i.e.: Intelligent Manufacturing, the present paper
emerges with the main aim of contributing to the design and analysis
of the material flow in either systems, cells or work stations under
this new “intelligent" denomination. For this, besides offering a
conceptual basis in some of the key points to be taken into account
and some general principles to consider in the design and analysis of
the material flow, also some tips on how to define other possible
alternative material flow scenarios and a classification of the states a
system, cell or workstation are offered as well. All this is done with
the intentions of relating it with the use of simulation tools, for which
these have been briefly addressed with a special focus on the Witness
simulation package. For a better comprehension, the previous
elements are supported by a detailed layout, other figures and a few
expressions which could help obtaining necessary data. Such data and
others will be used in the future, when simulating the scenarios in the
search of the best material flow configurations.
Abstract: In this paper we present semantic assistant agent
(SAA), an open source digital library agent which takes user query
for finding information in the digital library and takes resources-
metadata and stores it semantically. SAA uses Semantic Web to
improve browsing and searching for resources in digital library. All
metadata stored in the library are available in RDF format for
querying and processing by SemanSreach which is a part of SAA
architecture. The architecture includes a generic RDF-based model
that represents relationships among objects and their components.
Queries against these relationships are supported by an RDF triple
store.
Abstract: Appropriate description of business processes through
standard notations has become one of the most important assets for
organizations. Organizations must therefore deal with quality faults
in business process models such as the lack of understandability and
modifiability. These quality faults may be exacerbated if business
process models are mined by reverse engineering, e.g., from existing
information systems that support those business processes. Hence,
business process refactoring is often used, which change the internal
structure of business processes whilst its external behavior is
preserved. This paper aims to choose the most appropriate set of
refactoring operators through the quality assessment concerning
understandability and modifiability. These quality features are
assessed through well-proven measures proposed in the literature.
Additionally, a set of measure thresholds are heuristically established
for applying the most promising refactoring operators, i.e., those that
achieve the highest quality improvement according to the selected
measures in each case.
Abstract: Group-III nitride material as particularly AlxGa1-xN is
one of promising optoelectronic materials to require for shortwavelength
devices. To achieve the high-quality AlxGa1-xN films for
a high performance of such devices, AlN-nucleation layers are the
important factor. To improve the AlN-nucleation layers with a
variation of Ga-addition, XRD measurements were conducted to
analyze the crystalline quality of the subsequent Al0.1Ga0.9N with the
minimum ω-FWHMs of (0002) and (10-10) reflections of 425 arcsec
and 750 arcsec, respectively. SEM and AFM measurements were
performed to observe the surface morphology and TEM
measurements to identify the microstructures and orientations.
Results showed that the optimized Ga-atoms in the Al(Ga)Nnucleation
layers improved the surface diffusion to form moreuniform
crystallites in structure and size, better alignment of each
crystallite, and better homogeneity of island distribution. This, hence,
improves the orientation of epilayers on the Si-surface and finally
improves the crystalline quality and reduces the residual strain of
subsequent Al0.1Ga0.9N layers.
Abstract: The back propagation algorithm calculates the weight
changes of artificial neural networks, and a common approach is to
use a training algorithm consisting of a learning rate and a
momentum factor. The major drawbacks of above learning algorithm
are the problems of local minima and slow convergence speeds. The
addition of an extra term, called a proportional factor reduces the
convergence of the back propagation algorithm. We have applied the
three term back propagation to multiplicative neural network
learning. The algorithm is tested on XOR and parity problem and
compared with the standard back propagation training algorithm.
Abstract: An accurate and proficient artificial neural network
(ANN) based genetic algorithm (GA) is developed for predicting of
nanofluids viscosity. A genetic algorithm (GA) is used to optimize
the neural network parameters for minimizing the error between the
predictive viscosity and the experimental one. The experimental
viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15
to 343.15 K and volume fraction up to 15% were used from
literature. The result of this study reveals that GA-NN model is
outperform to the conventional neural nets in predicting the viscosity
of nanofluids with mean absolute relative error of 1.22% and 1.77%
for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results
of this work have also been compared with others models. The
findings of this work demonstrate that the GA-NN model is an
effective method for prediction viscosity of nanofluids and have
better accuracy and simplicity compared with the others models.
Abstract: The belief K-modes method (BKM) approach is a new
clustering technique handling uncertainty in the attribute values of
objects in both the cluster construction task and the classification one.
Like the standard version of this method, the BKM results depend on
the chosen initial modes. So, one selection method of initial modes
is developed, in this paper, aiming at improving the performances of
the BKM approach. Experiments with several sets of real data show
that by considered the developed selection initial modes method, the
clustering algorithm produces more accurate results.
Abstract: Due to the stringent legislation for emission of diesel
engines and also increasing demand on fuel consumption, the
importance of detailed 3D simulation of fuel injection, mixing and
combustion have been increased in the recent years. In the present
work, FIRE code has been used to study the detailed modeling of
spray and mixture formation in a Caterpillar heavy-duty diesel
engine. The paper provides an overview of the submodels
implemented, which account for liquid spray atomization, droplet
secondary break-up, droplet collision, impingement, turbulent
dispersion and evaporation. The simulation was performed from
intake valve closing (IVC) to exhaust valve opening (EVO). The
predicted in-cylinder pressure is validated by comparing with
existing experimental data. A good agreement between the predicted
and experimental values ensures the accuracy of the numerical
predictions collected with the present work. Predictions of engine
emissions were also performed and a good quantitative agreement
between measured and predicted NOx and soot emission data were
obtained with the use of the present Zeldowich mechanism and
Hiroyasu model. In addition, the results reported in this paper
illustrate that the numerical simulation can be one of the most
powerful and beneficial tools for the internal combustion engine
design, optimization and performance analysis.
Abstract: This paper is a continuation of our daily energy peak load forecasting approach using our modified network which is part of the recurrent networks family and is called feed forward and feed back multi context artificial neural network (FFFB-MCANN). The inputs to the network were exogenous variables such as the previous and current change in the weather components, the previous and current status of the day and endogenous variables such as the past change in the loads. Endogenous variable such as the current change in the loads were used on the network output. Experiment shows that using endogenous and exogenous variables as inputs to the FFFBMCANN rather than either exogenous or endogenous variables as inputs to the same network produces better results. Experiments show that using the change in variables such as weather components and the change in the past load as inputs to the FFFB-MCANN rather than the absolute values for the weather components and past load as inputs to the same network has a dramatic impact and produce better accuracy.
Abstract: Short Message Service (SMS) has grown in
popularity over the years and it has become a common way of
communication, it is a service provided through General System
for Mobile Communications (GSM) that allows users to send text
messages to others.
SMS is usually used to transport unclassified information, but
with the rise of mobile commerce it has become a popular tool for
transmitting sensitive information between the business and its
clients. By default SMS does not guarantee confidentiality and
integrity to the message content.
In the mobile communication systems, security (encryption)
offered by the network operator only applies on the wireless link.
Data delivered through the mobile core network may not be
protected. Existing end-to-end security mechanisms are provided
at application level and typically based on public key
cryptosystem.
The main concern in a public-key setting is the authenticity of
the public key; this issue can be resolved by identity-based (IDbased)
cryptography where the public key of a user can be derived
from public information that uniquely identifies the user.
This paper presents an encryption mechanism based on the IDbased
scheme using Elliptic curves to provide end-to-end security
for SMS. This mechanism has been implemented over the standard
SMS network architecture and the encryption overhead has been
estimated and compared with RSA scheme. This study indicates
that the ID-based mechanism has advantages over the RSA
mechanism in key distribution and scalability of increasing
security level for mobile service.