Abstract: Recent perceived climate variability raises concerns
with unprecedented hydrological phenomena and extremes.
Distribution and circulation of the waters of the Earth become
increasingly difficult to determine because of additional uncertainty
related to anthropogenic emissions. The world wide observed
changes in the large-scale hydrological cycle have been related to an
increase in the observed temperature over several decades. Although
the effect of change in climate on hydrology provides a general
picture of possible hydrological global change, new tools and
frameworks for modelling hydrological series with nonstationary
characteristics at finer scales, are required for assessing climate
change impacts. Of the downscaling techniques, dynamic
downscaling is usually based on the use of Regional Climate Models
(RCMs), which generate finer resolution output based on atmospheric
physics over a region using General Circulation Model (GCM) fields
as boundary conditions. However, RCMs are not expected to capture
the observed spatial precipitation extremes at a fine cell scale or at a
basin scale. Statistical downscaling derives a statistical or empirical
relationship between the variables simulated by the GCMs, called
predictors, and station-scale hydrologic variables, called predictands.
The main focus of the paper is on the need for using statistical
downscaling techniques for projection of local hydrometeorological
variables under climate change scenarios. The projections can be then
served as a means of input source to various hydrologic models to
obtain streamflow, evapotranspiration, soil moisture and other
hydrological variables of interest.
Abstract: The work proposes a decision support methodology
for the credit risk minimization in selection of investment projects.
The methodology provides two stages of projects’ evaluation.
Preliminary selection of projects with minor credit risks is made
using the Expertons Method. The second stage makes ranking of
chosen projects using the Possibilistic Discrimination Analysis
Method. The latter is a new modification of a well-known Method of
Fuzzy Discrimination Analysis.
Abstract: A generalized vortex lattice method for complex
lifting surfaces with flap and aileron deflection is formulated. The
method is not restricted by the linearized theory assumption and
accounts for all standard geometric lifting surface parameters:
camber, taper, sweep, washout, dihedral, in addition to flap and
aileron deflection. Thickness is not accounted for since the physical
lifting body is replaced by a lattice of panels located on the mean
camber surface. This panel lattice setup and the treatment of different
wake geometries is what distinguish the present work form the
overwhelming majority of previous solutions based on the vortex
lattice method. A MATLAB code implementing the proposed
formulation is developed and validated by comparing our results to
existing experimental and numerical ones and good agreement is
demonstrated. It is then used to study the accuracy of the widely used
classical vortex-lattice method. It is shown that the classical approach
gives good agreement in the clean configuration but is off by as much
as 30% when a flap or aileron deflection of 30° is imposed. This
discrepancy is mainly due the linearized theory assumption
associated with the conventional method. A comparison of the effect
of four different wake geometries on the values of aerodynamic
coefficients was also carried out and it is found that the choice of the
wake shape had very little effect on the results.
Abstract: Sudoku is a logic-based combinatorial puzzle game
which people in different ages enjoy playing it. The challenging and
addictive nature of this game has made it a ubiquitous game. Most
magazines, newspapers, puzzle books, etc. publish lots of Sudoku
puzzles every day. These puzzles often come in different levels of
difficulty so that all people, from beginner to expert, can play the
game and enjoy it. Generating puzzles with different levels of
difficulty is a major concern of Sudoku designers. There are several
works in the literature which propose ways of generating puzzles
having a desirable level of difficulty. In this paper, we propose a
method based on constraint satisfaction problems to evaluate the
difficulty of the Sudoku puzzles. Then we propose a hill climbing
method to generate puzzles with different levels of difficulty.
Whereas other methods are usually capable of generating puzzles
with only few number of difficulty levels, our method can be used to
generate puzzles with arbitrary number of different difficulty levels.
We test our method by generating puzzles with different levels of
difficulty and having a group of 15 people solve all the puzzles and
recording the time they spend for each puzzle.
Abstract: One of the major goals of Spoken Dialog Systems
(SDS) is to understand what the user utters.
In the SDS domain, the Spoken Language Understanding (SLU)
Module classifies user utterances by means of a pre-definite
conceptual knowledge. The SLU module is able to recognize only the
meaning previously included in its knowledge base. Due the vastity
of that knowledge, the information storing is a very expensive
process.
Updating and managing the knowledge base are time-consuming
and error-prone processes because of the rapidly growing number of
entities like proper nouns and domain-specific nouns. This paper
proposes a solution to the problem of Name Entity Recognition
(NER) applied to a SDS domain. The proposed solution attempts to
automatically recognize the meaning associated with an utterance by
using the PANKOW (Pattern based Annotation through Knowledge
On the Web) method at runtime.
The method being proposed extracts information from the Web to
increase the SLU knowledge module and reduces the development
effort. In particular, the Google Search Engine is used to extract
information from the Facebook social network.
Abstract: Three dimensional non-Interlaced carbon fibre
reinforced silicon carbide (3-D-Cf/SiC) composites with pyrocarbon
interphase were fabricated using isothermal chemical vapor
infiltration (ICVI) combined with polymer impregnation pyrolysis
(PIP) process. Polysilazane (PSZ) is used as a preceramic polymer to
obtain silicon carbide matrix. Thermo gravimetric analysis (TGA),
Infrared spectroscopic analysis (IR) and X-ray diffraction (XRD)
analysis were carried out on PSZ pyrolysed at different temperatures
to understand the pyrolysis and obtaining the optimum pyrolysing
condition to yield β-SiC phase. The density of the composites was
1.94 g cm-3 after the 3-D carbon preform was SiC infiltrated for 280 h
with one intermediate polysilazane pre-ceramic PIP process.
Mechanical properties of the composite materials were investigated
under tensile, flexural, shear and impact loading. The values of
tensile strength were 200 MPa at room temperature (RT) and 195
MPa at 500°C in air. The average RT flexural strength was 243 MPa.
The lower flexural strength of these composites is because of the
porosity. The fracture toughness obtained from single edge notched
beam (SENB) technique was 39 MPa.m1/2. The work of fracture
obtained from the load-displacement curve of SENB test was 22.8
kJ.m-2. The composites exhibited excellent impact resistance and the
dynamic fracture toughness of 44.8 kJ.m-2 is achieved as determined
from instrumented Charpy impact test. The shear strength of the
composite was 93 MPa, which is significantly higher compared 2-D
Cf/SiC composites. Microstructure evaluation of fracture surfaces
revealed the signatures of fracture processes and showed good
support for the higher toughness obtained.
Abstract: This study aimed at designing and developing a
mechanical force gauge for the square watermelon mold for the first
time. It also tried to introduce the square watermelon characteristics
and its production limitations. The mechanical force gauge
performance and the product itself were also described. There are
three main designable gauge models: a. hydraulic gauge, b. strain
gauge, and c. mechanical gauge. The advantage of the hydraulic
model is that it instantly displays the pressure and thus the force
exerted by the melon. However, considering the inability to measure
forces at all directions, complicated development, high cost, possible
hydraulic fluid leak into the fruit chamber and the possible influence
of increased ambient temperature on the fluid pressure, the
development of this gauge was overruled. The second choice was to
calculate pressure using the direct force a strain gauge. The main
advantage of these strain gauges over spring types is their high
precision in measurements; but with regard to the lack of conformity
of strain gauge working range with water melon growth, calculations
were faced with problems. Finally the mechanical pressure gauge has
advantages, including the ability to measured forces and pressures on
the mold surface during melon growth; the ability to display the peak
forces; the ability to produce melon growth graph thanks to its
continuous force measurements; the conformity of its manufacturing
materials with the required physical conditions of melon growth; high
air conditioning capability; the ability to permit sunlight reaches the
melon rind (no yellowish skin and quality loss); fast and
straightforward calibration; no damages to the product during
assembling and disassembling; visual check capability of the product
within the mold; applicable to all growth environments (field,
greenhouses, etc.); simple process; low costs and so forth.
Abstract: This paper is concerned with the stability problem
with two additive time-varying delay components. By choosing one
augmented Lyapunov-Krasovskii functional, using some new zero
equalities, and combining linear matrix inequalities (LMI)
techniques, two new sufficient criteria ensuring the global stability
asymptotic stability of DNNs is obtained. These stability criteria are
present in terms of linear matrix inequalities and can be easily
checked. Finally, some examples are showed to demonstrate the
effectiveness and less conservatism of the proposed method.
Abstract: The growth of wireless devices affects the availability
of limited frequencies or spectrum bands as it has been known that
spectrum bands are a natural resource that cannot be added.
Meanwhile, the licensed frequencies are idle most of the time.
Cognitive radio is one of the solutions to solve those problems.
Cognitive radio is a promising technology that allows the unlicensed
users known as secondary users (SUs) to access licensed bands
without making interference to licensed users or primary users (PUs).
As cloud computing has become popular in recent years, cognitive
radio networks (CRNs) can be integrated with cloud platform. One of
the important issues in CRNs is security. It becomes a problem since
CRNs use radio frequencies as a medium for transmitting and CRNs
share the same issues with wireless communication systems. Another
critical issue in CRNs is performance. Security has adverse effect to
performance and there are trade-offs between them. The goal of this
paper is to investigate the performance related to security trade-off in
CRNs with supporting cloud platforms. Furthermore, Queuing
Network Models with preemptive resume and preemptive repeat
identical priority are applied in this project to measure the impact of
security to performance in CRNs with or without cloud platform. The
generalized exponential (GE) type distribution is used to reflect the
bursty inter-arrival and service times at the servers. The results show
that the best performance is obtained when security is disabled and
cloud platform is enabled.
Abstract: In many communication and signal processing
systems, it is highly desirable to implement an efficient narrow-band
filter that decimate or interpolate the incoming signals. This paper
presents hardware efficient compensated CIC filter over a narrow
band frequency that increases the speed of down sampling by using
multiplierless decimation filters with polyphase FIR filter structure.
The proposed work analyzed the performance of compensated CIC
filter on the bases of the improvement of frequency response with
reduced hardware complexity in terms of no. of adders and
multipliers and produces the filtered results without any alterations.
CIC compensator filter demonstrated that by using compensation
with CIC filter improve the frequency response in passed of interest
26.57% with the reduction in hardware complexity 12.25%
multiplications per input sample (MPIS) and 23.4% additions per
input sample (APIS) w.r.t. FIR filter respectively.
Abstract: The purposes of this study were to design and find
users’ satisfaction after using the decision support system for tourism
northern part of Thailand, which can provide tourists touristic
information and plan their personal voyage. Such information can be
retrieved systematically based on personal budget and provinces. The
samples of this study were five experts and users 30 persons white
collars in Bangkok. This decision support system was designed via
ASP.NET. Its database was developed by using MySQL, for
administrators are able to effectively manage the database. The
application outcome revealed that the innovation works properly as
sought in objectives. Specialists and white collars in Bangkok have
evaluated the decision support system; the result was satisfactorily
positive.
Abstract: In order to evaluate the performance of a unified power
flow controller (UPFC), mathematical models for steady state and
dynamic analysis are to be developed. The steady state model is
mainly concerned with the incorporation of the UPFC in load flow
studies. Several load flow models for UPFC have been introduced
in literature, and one of the most reliable models is the decoupled
UPFC model. In spite of UPFC decoupled load flow model simplicity,
it is more robust compared to other UPFC load flow models and it
contains unique capabilities. Some shortcoming such as additional
set of nonlinear equations are to be solved separately after the load
flow solution is obtained. The aim of this study is to investigate the
different control strategies that can be realized in the decoupled load
flow model (individual control and combined control), and the impact
of the location of the UPFC in the network on its control parameters.
Abstract: This work presents the modelling and simulation of
saponification of ethyl acetate in the presence of sodium hydroxide in
a plug flow reactor using Aspen Plus simulation software. Plug flow
reactors are widely used in the industry due to the non-mixing
property. The use of plug flow reactors becomes significant when
there is a need for continuous large scale reaction or fast reaction.
Plug flow reactors have a high volumetric unit conversion as the
occurrence for side reactions is minimum. In this research Aspen Plus
V8.0 has been successfully used to simulate the plug flow reactor. In
order to simulate the process as accurately as possible HYSYS Peng-
Robinson EOS package was used as the property method. The results
obtained from the simulation were verified by the experiment carried
out in the EDIBON plug flow reactor module. The correlation
coefficient (r2) was 0.98 and it proved that simulation results
satisfactorily fit for the experimental model. The developed model
can be used as a guide for understanding the reaction kinetics of a
plug flow reactor.
Abstract: Lead (Pb) poisoning is one of the most common and
preventable environmental health problems. There are different
sources of environmental pollution with lead as lead alkyl additives
in petrol and manufacturing processes. Pb in the atmosphere can be
deposited in urban soils, and may then be re-suspended to re-enter the
atmosphere. This could increase human exposure to Pb and cause
long-term health effects. Thus, monitoring Pb pollution is considered
one of the major tasks in controlling pollution. Scalp hair can be
utilized for the determination of lead (Pb) concentration. It provides a
lasting record of metal intakes of weeks or even months, and for most
metals, their accumulation in hair reflects their accumulation in the
whole body. This work was conducted to investigate the
concentration of lead in male scalp hair of Cairo (residential-traffic
and residential-industrial) and rural residents after twenty years of
phasing out of leaded gasoline. Results indicated that the mean
concentration of lead in hair of residential-traffic (9.7552 μg/g ±0.71)
and residential-industrial (12.3288 μg/g ±1.13) was significantly
higher than that in rural residents (4.7327 μg/g ±0.67). The mean
concentration of lead in hair of resident’s industrial areas was the
highest among Cairo residents and not the traffic areas as it was
before phasing out of leaded gasoline. Twenty years of phasing out of
leaded gasoline in Cairo has greatly improved the lead pollution
among residents of traffic areas, but industrial areas residents were
still suffering from lead pollution, which needs more efforts to
control the sources of lead pollution.
Abstract: Roof top rainwater harvesting (RWH) has been
carried out worldwide to provide an inexpensive source of water for
many people. This research aims at evaluating the potential of roof
top rain water harvesting as a resource in Jordan. For the purpose of
this work, two case studies at Al-Jubiha and Shafa-Badran districts in
Amman city were selected. All existing rooftops in both districts
were identified by digitizing 2012 satellite images of the two districts
using Google earth and ArcGIS tools. Rational method was used to
estimate the potential volume of rainwater that can be harvested from
the digitized rooftops. Results indicated that 1.17 and 0.526 MCM/yr
can be harvested in Al-Jubiha and Shafa-Badran districts,
respectively. This study should increase the attention to the
importance of implementing RWH technique in Jordanian residences
as a viable alternative for ensuring a continued source of non-potable
water.
Abstract: The emergence of the Semantic Web technology
increases day by day due to the rapid growth of multiple web pages.
Many standard formats are available to store the semantic web data.
The most popular format is the Resource Description Framework
(RDF). Querying large RDF graphs becomes a tedious procedure
with a vast increase in the amount of data. The problem of query
optimization becomes an issue in querying large RDF graphs.
Choosing the best query plan reduces the amount of query execution
time. To address this problem, nature inspired algorithms can be used
as an alternative to the traditional query optimization techniques. In
this research, the optimal query plan is generated by the proposed
SAPSO algorithm which is a hybrid of Simulated Annealing (SA)
and Particle Swarm Optimization (PSO) algorithms. The proposed
SAPSO algorithm has the ability to find the local optimistic result
and it avoids the problem of local minimum. Experiments were
performed on different datasets by changing the number of predicates
and the amount of data. The proposed algorithm gives improved
results compared to existing algorithms in terms of query execution
time.
Abstract: In this paper, GSM signal strength was measured in
order to detect the type of the signal fading phenomenon using onedimensional
multilevel wavelet residual method and neural network
clustering to determine the average GSM signal strength received in
the study area. The wavelet residual method predicted that the GSM
signal experienced slow fading and attenuated with MSE of 3.875dB.
The neural network clustering revealed that mostly -75dB, -85dB and
-95dB were received. This means that the signal strength received in
the study is a weak signal.
Abstract: Disasters are quite experienced in our days. They are
caused by floods, landslides, and building fires that is the main
objective of this study. To cope with these unexpected events,
precautions must be taken to protect human lives. The emphasis on
disposal work focuses on the resolution of the evacuation problem in
case of no-notice disaster. The problem of evacuation is listed as a
dynamic network flow problem. Particularly, we model the
evacuation problem as an earliest arrival flow problem with load
dependent transit time. This problem is classified as NP-Hard. Our
challenge here is to propose a metaheuristic solution for solving the
evacuation problem. We define our objective as the maximization of
evacuees during earliest periods of a time horizon T. The objective
provides the evacuation of persons as soon as possible. We
performed an experimental study on emergency evacuation from the
tunisian children’s hospital. This work prompts us to look for
evacuation plans corresponding to several situations where the
network dynamically changes.
Abstract: ‘Steganalysis’ is one of the challenging and attractive interests for the researchers with the development of information hiding techniques. It is the procedure to detect the hidden information from the stego created by known steganographic algorithm. In this paper, a novel feature based image steganalysis technique is proposed. Various statistical moments have been used along with some similarity metric. The proposed steganalysis technique has been designed based on transformation in four wavelet domains, which include Haar, Daubechies, Symlets and Biorthogonal. Each domain is being subjected to various classifiers, namely K-nearest-neighbor, K* Classifier, Locally weighted learning, Naive Bayes classifier, Neural networks, Decision trees and Support vector machines. The experiments are performed on a large set of pictures which are available freely in image database. The system also predicts the different message length definitions.
Abstract: Artificial Neural Networks (ANN) trained using backpropagation
(BP) algorithm are commonly used for modeling
material behavior associated with non-linear, complex or unknown
interactions among the material constituents. Despite multidisciplinary
applications of back-propagation neural networks
(BPNN), the BP algorithm possesses the inherent drawback of
getting trapped in local minima and slowly converging to a global
optimum. The paper present a hybrid artificial neural networks and
genetic algorithm approach for modeling slump of ready mix
concrete based on its design mix constituents. Genetic algorithms
(GA) global search is employed for evolving the initial weights and
biases for training of neural networks, which are further fine tuned
using the BP algorithm. The study showed that, hybrid ANN-GA
model provided consistent predictions in comparison to commonly
used BPNN model. In comparison to BPNN model, the hybrid ANNGA
model was able to reach the desired performance goal quickly.
Apart from the modeling slump of ready mix concrete, the synaptic
weights of neural networks were harnessed for analyzing the relative
importance of concrete design mix constituents on the slump value.
The sand and water constituents of the concrete design mix were
found to exhibit maximum importance on the concrete slump value.