Abstract: This paper analyses the heat transfer performance and
fluid flow using different nanofluids in a square enclosure. The
energy equation and Navier-Stokes equation are solved numerically
using finite volume scheme. The effect of volume fraction
concentration on the enhancement of heat transfer has been studied
icorporating the Brownian motion; the influence of effective thermal
conductivity on the enhancement was also investigated for a range of
volume fraction concentration. The velocity profile for different
Rayleigh number. Water-Cu, water AL2O3 and water-TiO2 were
tested.
Abstract: As the trend in automotive technology is fast moving
towards hybridization and electrification to curb emissions as well as
to improve the fuel efficiency, air-conditioning systems in passenger
cars have not caught up with this trend and still remain as the major
energy consumers amongst others. Adsorption based air-conditioning
systems, e.g. with silica-gel water pair, which are already in use for
residential and commercial applications, are now being considered as
a technology leap once proven feasible for the passenger cars. In this
paper we discuss a methodology, challenges and feasibility of
implementing an adsorption based air-conditioning system in a
passenger car utilizing the exhaust waste heat. We also propose an
optimized control strategy with interfaces to the engine control unit
of the vehicle for operating this system with reasonable efficiency
supported by our simulation and validation results in a prototype
vehicle, additionally comparing to existing implementations,
simulation based as well as experimental. Finally we discuss the
influence of start-stop and hybrid systems on the operation strategy of
the adsorption air-conditioning system.
Abstract: In wastewater treatment processes, aeration introduces
air into a liquid. In these systems, air is introduced by different
devices submerged in the wastewater. Smaller bubbles result in more
bubble surface area per unit of volume and higher oxygen transfer
efficiency. Jet pumps are devices that use air bubbles and are widely
used in wastewater treatment processes. The principle of jet pumps is
their ability to transfer energy of one fluid, called primary or motive,
into a secondary fluid or gas. These pumps have no moving parts and
are able to work in remote areas under extreme conditions. The
objective of this work is to study experimentally the characteristics of
the jet pump and the size of air bubbles in the laboratory water tank.
The effect of flow rate ratio on pump performance is investigated in
order to have a better understanding about pump behavior under
various conditions, in order to determine the efficiency of receiving
air bubbles different sizes. The experiments show that we should take
care when increasing the flow rate ratio while seeking to decrease
bubble size in the outlet flow. This study will help improve and
extend the use of the jet pump in many practical applications.
Abstract: A field study was conducted to evaluate the efficacy of
safflower plant for phytoremediation of contaminated soils. The
experiment was performed on an agricultural fields contaminated by
the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. Field
experiments with randomized complete block design with five
treatments (control, compost amendments added at 20 and 40 t/daa,
and vermicompost amendments added at 20 and 40 t/daa) were
carried out. The quality of safflower seeds and oil (heavy metals and
fatty acid composition) were determined. Tested organic amendments
significantly influenced the chemical composition of safflower seeds
and oil. The compost and vermicompost treatments significantly
reduced heavy metals concentration in safflower seeds and oils, but
the effect differed among them. Addition of vermicompost and
compost leads to an increase in the content of palmitic acid and
linoleic acid, and a decrease in the stearic and oleic acids compared
with the control. A significant increase in the quantity of saturated
acids was observed in the variants with 20 t/daa of compost and 20
t/daa of vermicompost (9.1 and 8.9% relative to the control).
Safflower is a plant which is tolerant to heavy metals and can be
successfully used in the phytoremediation of heavy metal
contaminated soils. The processing of seeds to oil and using the
obtained oil for nutritional purposes will greatly reduce the cost of
phytoremediation.
Abstract: Due to the continuous increment of the load demand,
identification of weaker buses, improvement of voltage profile and
power losses in the context of the voltage stability problems has
become one of the major concerns for the larger, complex,
interconnected power systems. The objective of this paper is to
review the impact of Flexible AC Transmission System (FACTS)
controller in Wind generators connected electrical network for
maintaining voltage stability. Wind energy could be the growing
renewable energy due to several advantages. The influence of wind
generators on power quality is a significant issue; non uniform power
production causes variations in system voltage and frequency.
Therefore, wind farm requires high reactive power compensation; the
advances in high power semiconducting devices have led to the
development of FACTS. The FACTS devices such as for example
SVC inject reactive power into the system which helps in maintaining
a better voltage profile. The performance is evaluated on an IEEE 14
bus system, two wind generators are connected at low voltage buses
to meet the increased load demand and SVC devices are integrated at
the buses with wind generators to keep voltage stability. Power
flows, nodal voltage magnitudes and angles of the power network are
obtained by iterative solutions using MIPOWER.
Abstract: Durian is the flagship fruit of Mindanao and there is
an abundance of several cultivars with many confusing identities/
names.
The project was conducted to develop procedure for reliable and
rapid detection and sorting of durian planting materials. Moreover, it
is also aimed to establish specific genetic or DNA markers for routine
testing and authentication of durian cultivars in question.
The project developed molecular procedures for routine testing.
SSR primers were also screened and identified for their utility in
discriminating durian cultivars collected.
Results of the study showed the following accomplishments:
1. Twenty (29) SSR primers were selected and identified based on
their ability to discriminate durian cultivars,
2. Optimized and established standard procedure for identification
and authentication of Durian cultivars
3. Genetic profile of durian is now available at Biotech Unit
Our results demonstrate the relevance of using molecular
techniques in evaluating and identifying durian clones. The most
polymorphic primers tested in this study could be useful tools for
detecting variation even at the early stage of the plant especially for
commercial purposes. The process developed combines the efficiency
of the microsatellites development process with the optimization of
non-radioactive detection process resulting in a user-friendly protocol
that can be performed in two (2) weeks and easily incorporated into
laboratories about to start microsatellite development projects. This
can be of great importance to extend microsatellite analyses to other
crop species where minimal genetic information is currently
available. With this, the University can now be a service laboratory
for routine testing and authentication of durian clones.
Abstract: Many factors influence the educational outcome of
students. Some of these have been studied by researchers with many
emphasizing the role of students, schools, governments, peer groups
and so on. More often than not, some of these factors influencing the
academic achievement of the students have been traced back to
parents and family; being the primary platform on which learning not
only begins but is nurtured, encouraged and developed which later
transforms to the performance of the students. This study not only
explores parental and related factors that predict academic
achievement through the review of relevant literatures but also,
investigates the influence of parental background on the academic
achievement of senior secondary school students in Ibadan North
Local Government Area of Oyo State, Nigeria. As one of the criteria
of the quality of education, students’ academic achievement was
investigated because it is most often cited as an indicator of school
effectiveness by school authorities and educationists. The data
collection was done through interviews and use of well-structured
questionnaires administered to one hundred students (100) within the
target local government. This was statistically analysed and the result
showed that parents’ attitudes towards their children’s education had
significant effect(s) on students’ self-reporting of academic
achievement. However, such factors as parental education and socioeconomic
background had no significant relationship with the
students’ self-reporting of academic achievement.
Abstract: Edge is variation of brightness in an image. Edge
detection is useful in many application areas such as finding forests,
rivers from a satellite image, detecting broken bone in a medical
image etc. The paper discusses about finding edge of multiple aerial
images in parallel. The proposed work tested on 38 images 37
colored and one monochrome image. The time taken to process N
images in parallel is equivalent to time taken to process 1 image in
sequential. Message Passing Interface (MPI) and Open Computing
Language (OpenCL) is used to achieve task and pixel level
parallelism respectively.
Abstract: All current experimental methods for determination of
stress intensity factors are based on the assumption that the state of
stress near the crack tip is plane stress. Therefore, these methods rely
on strain and displacement measurements made outside the near
crack tip region affected by the three-dimensional effects or by
process zone. In this paper, we develop and validate an experimental
procedure for the evaluation of stress intensity factors from the
measurements of the out-of-plane displacements in the surface area
controlled by 3D effects. The evaluation of stress intensity factors is
possible when the process zone is sufficiently small, and the
displacement field generated by the 3D effects is fully encapsulated
by K-dominance region.
Abstract: A simple adaptive voice activity detector (VAD) is
implemented using Gabor and gammatone atomic decomposition of
speech for high Gaussian noise environments. Matching pursuit is
used for atomic decomposition, and is shown to achieve optimal
speech detection capability at high data compression rates for low
signal to noise ratios. The most active dictionary elements found by
matching pursuit are used for the signal reconstruction so that the
algorithm adapts to the individual speakers dominant time-frequency
characteristics. Speech has a high peak to average ratio enabling
matching pursuit greedy heuristic of highest inner products to isolate
high energy speech components in high noise environments. Gabor
and gammatone atoms are both investigated with identical
logarithmically spaced center frequencies, and similar bandwidths.
The algorithm performs equally well for both Gabor and gammatone
atoms with no significant statistical differences. The algorithm
achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR
and 98% accuracy at a 20dB SNR using 30d B SNR as a reference
for voice activity.
Abstract: Margin-Based Principle has been proposed for a long
time, it has been proved that this principle could reduce the
structural risk and improve the performance in both theoretical
and practical aspects. Meanwhile, feed-forward neural network is
a traditional classifier, which is very hot at present with a deeper
architecture. However, the training algorithm of feed-forward neural
network is developed and generated from Widrow-Hoff Principle that
means to minimize the squared error. In this paper, we propose
a new training algorithm for feed-forward neural networks based
on Margin-Based Principle, which could effectively promote the
accuracy and generalization ability of neural network classifiers
with less labelled samples and flexible network. We have conducted
experiments on four UCI open datasets and achieved good results
as expected. In conclusion, our model could handle more sparse
labelled and more high-dimension dataset in a high accuracy while
modification from old ANN method to our method is easy and almost
free of work.
Abstract: In this paper the problem of the application of
temporal reasoning and case-based reasoning in intelligent decision
support systems is considered. The method of case-based reasoning
with temporal dependences for the solution of problems of real-time
diagnostics and forecasting in intelligent decision support systems is
described. This paper demonstrates how the temporal case-based
reasoning system can be used in intelligent decision support systems
of the car access control. This work was supported by RFBR.
Abstract: The problems arising from unbalanced data sets
generally appear in real world applications. Due to unequal class
distribution, many researchers have found that the performance of
existing classifiers tends to be biased towards the majority class. The
k-nearest neighbors’ nonparametric discriminant analysis is a method
that was proposed for classifying unbalanced classes with good
performance. In this study, the methods of discriminant analysis are
of interest in investigating misclassification error rates for classimbalanced
data of three diabetes risk groups. The purpose of this
study was to compare the classification performance between
parametric discriminant analysis and nonparametric discriminant
analysis in a three-class classification of class-imbalanced data of
diabetes risk groups. Data from a project maintaining healthy
conditions for 599 employees of a government hospital in Bangkok
were obtained for the classification problem. The employees were
divided into three diabetes risk groups: non-risk (90%), risk (5%),
and diabetic (5%). The original data including the variables of
diabetes risk group, age, gender, blood glucose, and BMI were
analyzed and bootstrapped for 50 and 100 samples, 599 observations
per sample, for additional estimation of the misclassification error
rate. Each data set was explored for the departure of multivariate
normality and the equality of covariance matrices of the three risk
groups. Both the original data and the bootstrap samples showed nonnormality
and unequal covariance matrices. The parametric linear
discriminant function, quadratic discriminant function, and the
nonparametric k-nearest neighbors’ discriminant function were
performed over 50 and 100 bootstrap samples and applied to the
original data. Searching the optimal classification rule, the choices of
prior probabilities were set up for both equal proportions (0.33: 0.33:
0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10)
and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples
indicated that the k-nearest neighbors approach when k=3 or k=4 and
the defined prior probabilities of non-risk: risk: diabetic as 0.90:
0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of
misclassification. The k-nearest neighbors approach would be
suggested for classifying a three-class-imbalanced data of diabetes
risk groups.
Abstract: In this work, we explore the capability of the mean
shift algorithm as a powerful preprocessing tool for improving the
quality of spatial data, acquired from airborne scanners, from densely
built urban areas. On one hand, high resolution image data corrupted
by noise caused by lossy compression techniques are appropriately
smoothed while at the same time preserving the optical edges and, on
the other, low resolution LiDAR data in the form of normalized
Digital Surface Map (nDSM) is upsampled through the joint mean
shift algorithm. Experiments on both the edge-preserving smoothing
and upsampling capabilities using synthetic RGB-z data show that the
mean shift algorithm is superior to bilateral filtering as well as to
other classical smoothing and upsampling algorithms. Application of
the proposed methodology for 3D reconstruction of buildings of a
pilot region of Athens, Greece results in a significant visual
improvement of the 3D building block model.
Abstract: The relationship between the state and the religion is
different based on the fact that how powerful is the religion faith in a
state and of the influences that affected the views of the constitution
drafters according to the constitutional system they were based to
draft their constitution. This paper aims at providing, through a
comparative methodology, how it is regulated by the constitution the
relationship between the state and the religion. The object of this
study are the constitutions of Italy as a nation with catholic religious
tradition, Greece as a nation with orthodox religion tradition, and
Turkey as a nation which represents Muslim religion, while Albania
as a nation known for its religious plurality. In particular, the analysis
will be focused on the secular or religious principle provided in the
constitution of each respective state. This comparative overview
intends to discern which of the states analyzed is more tolerant and
fully respects the freedom of religion. It results that most of the states
subject of this study, despite their religious tradition have chosen the
secular principle in their constitutions, but the religious freedom is
differently guaranteed.
Abstract: Microscopic simulation tool kits allow for
consideration of the two processes of railway operations and the
previous timetable production. Block occupation conflicts on both
process levels are often solved by using defined train priorities. These
conflict resolutions (dispatching decisions) generate reactionary
delays to the involved trains. The sum of reactionary delays is
commonly used to evaluate the quality of railway operations, which
describes the timetable robustness. It is either compared to an
acceptable train performance or the delays are appraised
economically by linear monetary functions. It is impossible to
adequately evaluate dispatching decisions without a well-founded
objective function. This paper presents a new approach for the
evaluation of dispatching decisions. The approach uses mode choice
models and considers the behaviour of the end-customers. These
models evaluate the reactionary delays in more detail and consider
other competing modes of transport. The new approach pursues the
coupling of a microscopic model of railway operations with the
macroscopic choice mode model. At first, it will be implemented for
railway operations process but it can also be used for timetable
production. The evaluation considers the possibility for the customer
to interchange to other transport modes. The new approach starts to
look at rail and road, but it can also be extended to air travel. The
result of mode choice models is the modal split. The reactions by the
end-customers have an impact on the revenue of the train operating
companies. Different purposes of travel have different payment
reserves and tolerances towards late running. Aside from changes to
revenues, longer journey times can also generate additional costs.
The costs are either time- or track-specific and arise from required
changes to rolling stock or train crew cycles. Only the variable values
are summarised in the contribution margin, which is the base for the
monetary evaluation of delays. The contribution margin is calculated
for different possible solutions to the same conflict. The conflict
resolution is optimised until the monetary loss becomes minimal. The
iterative process therefore determines an optimum conflict resolution
by monitoring the change to the contribution margin. Furthermore, a
monetary value of each dispatching decision can also be derived.
Abstract: In more complex systems, such as automotive
gearbox, a rigorous treatment of the data is necessary because there
are several moving parts (gears, bearings, shafts, etc.), and in this
way, there are several possible sources of errors and also noise. The
basic objective of this work is the detection of damage in automotive
gearbox. The detection methods used are the wavelet method, the
bispectrum; advanced filtering techniques (selective filtering) of
vibrational signals and mathematical morphology. Gearbox vibration
tests were performed (gearboxes in good condition and with defects)
of a production line of a large vehicle assembler. The vibration
signals are obtained using five accelerometers in different positions
of the sample. The results obtained using the kurtosis, bispectrum,
wavelet and mathematical morphology showed that it is possible to
identify the existence of defects in automotive gearboxes.
Abstract: Evolutionary optimization methods such as genetic
algorithms have been used extensively for the construction site layout
problem. More recently, ant colony optimization algorithms, which
are evolutionary methods based on the foraging behavior of ants,
have been successfully applied to benchmark combinatorial
optimization problems. This paper proposes a formulation of the site
layout problem in terms of a sequencing problem that is suitable for
solution using an ant colony optimization algorithm.
In the construction industry, site layout is a very important
planning problem. The objective of site layout is to position
temporary facilities both geographically and at the correct time such
that the construction work can be performed satisfactorily with
minimal costs and improved safety and working environment. During
the last decade, evolutionary methods such as genetic algorithms
have been used extensively for the construction site layout problem.
This paper proposes an ant colony optimization model for
construction site layout. A simple case study for a highway project is
utilized to illustrate the application of the model.
Abstract: In this work, two fermentations at different
temperatures (25 and 30ºC), with cell recycling, were accomplished
to produce ethanol, using a mix of commercial substrates, xylose
(70%) and glucose (30%), as organic source for Scheffersomyces
stipitis. Five consecutive fermentations of 80 g L-1 (1º, 2º and 3º
recycles), 96 g L-1 (4º recycle) and 120 g L-1 (5º recycle)reduced
sugars led to a final maximum ethanol concentration of 17.2 and 34.5
g L-1, at 25 and 30ºC, respectively. Glucose was the preferred
substrate; moreover xylose startup degradation was initiated after a
remaining glucose presence in the medium. Results showed that yeast
acid treatment, performed before each cycle, provided improvements
on cell viability, accompanied by ethanol productivity of 2.16 g L-1 h-
1 at 30ºC. A maximum 36% of xylose was retained in the
fermentation medium and after five-cycle fermentation an ethanol
yield of 0.43 g ethanol/g sugars was observed. S. stipitis fermentation
capacity and tolerance showed better results at 30ºC with 83.4% of
theoretical yield referenced on initial biomass.
Abstract: In this paper we propose a novel methodology for
extracting a road network and its nodes from satellite images of
Algeria country.
This developed technique is a progress of our previous research
works. It is founded on the information theory and the mathematical
morphology; the information theory and the mathematical
morphology are combined together to extract and link the road
segments to form a road network and its nodes.
We therefore have to define objects as sets of pixels and to study
the shape of these objects and the relations that exist between them.
In this approach, geometric and radiometric features of roads are
integrated by a cost function and a set of selected points of a crossing
road. Its performances were tested on satellite images of Algeria
country.