Abstract: Heat transfer due to forced convection of copper water
based nanofluid has been predicted by Artificial Neural network
(ANN). The present nanofluid is formed by mixing copper
nanoparticles in water and the volume fractions are considered here
are 0% to 15% and the Reynolds number are kept constant at 100.
The back propagation algorithm is used to train the network. The
present ANN is trained by the input and output data which has been
obtained from the numerical simulation, performed in finite volume
based Computational Fluid Dynamics (CFD) commercial software
Ansys Fluent. The numerical simulation based results are compared
with the back propagation based ANN results. It is found that the
forced convection heat transfer of water based nanofluid can be
predicted correctly by ANN. It is also observed that the back
propagation ANN can predict the heat transfer characteristics of
nanofluid very quickly compared to standard CFD method.
Abstract: Thousands of organisations store important and
confidential information related to them, their customers, and their
business partners in databases all across the world. The stored data
ranges from less sensitive (e.g. first name, last name, date of birth) to
more sensitive data (e.g. password, pin code, and credit card
information). Losing data, disclosing confidential information or
even changing the value of data are the severe damages that
Structured Query Language injection (SQLi) attack can cause on a
given database. It is a code injection technique where malicious SQL
statements are inserted into a given SQL database by simply using a
web browser. In this paper, we propose an effective pattern
recognition neural network model for detection and classification of
SQLi attacks. The proposed model is built from three main elements
of: a Uniform Resource Locator (URL) generator in order to generate
thousands of malicious and benign URLs, a URL classifier in order
to: 1) classify each generated URL to either a benign URL or a
malicious URL and 2) classify the malicious URLs into different
SQLi attack categories, and a NN model in order to: 1) detect either a
given URL is a malicious URL or a benign URL and 2) identify the
type of SQLi attack for each malicious URL. The model is first
trained and then evaluated by employing thousands of benign and
malicious URLs. The results of the experiments are presented in
order to demonstrate the effectiveness of the proposed approach.
Abstract: The purpose of the paper is to estimate the US small
wind turbines market potential and forecast the small wind turbines
sales in the US. The forecasting method is based on the application of
the Bass model and the generalized Bass model of innovations
diffusion under replacement purchases. In the work an exponential
distribution is used for modeling of replacement purchases. Only one
parameter of such distribution is determined by average lifetime of
small wind turbines. The identification of the model parameters is
based on nonlinear regression analysis on the basis of the annual
sales statistics which has been published by the American Wind
Energy Association (AWEA) since 2001 up to 2012. The estimation
of the US average market potential of small wind turbines (for
adoption purchases) without account of price changes is 57080
(confidence interval from 49294 to 64866 at P = 0.95) under average
lifetime of wind turbines 15 years, and 62402 (confidence interval
from 54154 to 70648 at P = 0.95) under average lifetime of wind
turbines 20 years. In the first case the explained variance is 90,7%,
while in the second - 91,8%. The effect of the wind turbines price
changes on their sales was estimated using generalized Bass model.
This required a price forecast. To do this, the polynomial regression
function, which is based on the Berkeley Lab statistics, was used. The
estimation of the US average market potential of small wind turbines
(for adoption purchases) in that case is 42542 (confidence interval
from 32863 to 52221 at P = 0.95) under average lifetime of wind
turbines 15 years, and 47426 (confidence interval from 36092 to
58760 at P = 0.95) under average lifetime of wind turbines 20 years.
In the first case the explained variance is 95,3%, while in the second
– 95,3%.
Abstract: Sol-enhanced Zn-Ni-Al2O3 nanocomposite coatings
were electroplated on mild steel by our newly developed solenhanced
electroplating method. In this method, transparent Al2O3 sol
was added into the acidic Zn-Ni bath to produced Zn-Ni-Al2O3nanocomposite
coatings. The chemical composition, microstructure and
mechanical properties of the composite and alloy coatings deposited
at two different agitation speed were investigated. The structure of all
coatings was single γ-Ni5Zn21 phase. The composite coatings possess
refined crystals with higher microhardness compared to Zn-Ni alloy
coatings. The wear resistance of Zn-Ni coatings was improved
significantly by incorporation of alumina nano particles into the
coatings. Higher agitation speed provided more uniform coatings
with smaller grain sized and slightly higher microhardness.
Considering composite coatings, high agitation speeds may facilitate
co-deposition of alumina in the coatings.
Abstract: Extracting and determining chlorophyll pigments
(chlorophyll a and b) in green leaves are the procedures based on the
solvent extraction of pigments in samples using N,Ndimethylformamide
as the extractant. In this study, two species of
soluble inorganic selenium forms, selenite (SeIV) and selenate (SeVI)
at different concentrations were investigated on maize plants that
were growing in nutrient solutions during 2 weeks and at the end of
the experiment, amounts of chlorophyll a and b for first and second
leaves of maize were measured. In accordance with the results we
observed that our regarded Se concentrations in both forms of SeIV
and SeVI were not effective on maize plants’ chlorophyll a and b
significantly although high level of 3 mg.kg-1 SeIV had negative affect
on growth of the samples that had been treated by it but about SeVI
samples we did not observe this state and our different considered
SeVI concentrations were not toxic for maize plants.
Abstract: This paper presents a numerical investigation of two
horizontally mounted four-lobed swirl pipes in terms of swirl
induction effectiveness into flows passing through them. The swirl
flows induced by the two swirl pipes have the potential to improve
the efficiency of Clean-In-Place procedures in a closed processing
system by local intensification of hydrodynamic impact on the
internal pipe surface. Pressure losses, swirl development within the
two swirl pipe, swirl induction effectiveness, swirl decay and wall
shear stress variation downstream of two swirl pipes are analyzed and
compared. It was found that a shorter length of swirl inducing pipe
used in joint with transition pipes is more effective in swirl induction
than when a longer one is used, in that it has a less constraint to the
induced swirl and results in slightly higher swirl intensity just
downstream of it with the expense of a smaller pressure loss. The
wall shear stress downstream of the shorter swirl pipe is also slightly
larger than that downstream of the longer swirl pipe due to the
slightly higher swirl intensity induced by the shorter swirl pipe. The
advantage of the shorter swirl pipe in terms of swirl induction is more
significant in flows with a larger Reynolds Number.
Abstract: Aim of this work is to determine the theoretical and
experimental properties of filament wound glass fiber/epoxy resin
composite pipes with different winding design subjected under
bending. For determination of bending strength of composite samples
three point bending tests were conducted. Good correlation between
theoretical and experimental results has been obtained, where sample
No4 has shown the highest value of bending strength. All samples
have demonstrated matrix cracking and fiber failure followed by
layers delamination during testing. Also, it was found that smaller
winding angles lead to an increase in bending stress. From presented
results good merger between glass fibers and epoxy resin was
confirmed by SEM analysis.
Abstract: In this study, firstly democratic thoughts which
directly or indirectly affect economic development and/or the
interaction between authoritarian regimes and the economic
development and the direction and channels of this interaction were
studied and then the study tried to determine how democracy affects
economic development. It was concluded that the positive
contributions of democracy to economic development were more
determinant than the effects that were either negative or restrictive in
terms of development. When compared to autocracy, since
democracy is more successful in managing social conflicts, ensuring
political stability and preventing social disasters such as famine, it
contributes more to economic development. Democracy also
facilitates delegation of authority, provides a stable investment
environment and accelerates mobilization of resources in accordance
with economic growth/development. Democracy leads to an increase
in human capital accumulation and increases the growth rate through
reducing income inequality. It can be said that democratic regimes
are the most appropriate ones in terms of increasing economic
performance and supporting economic development through their
strong institutional structures and the assurance they will ensure in
property rights.
Abstract: Non-crimp 3D orthogonal fabric composite is one of
the textile-based composite materials that are rapidly developing
light-weight engineering materials. The present paper focuses on
geometric and micromechanical modeling of non-crimp 3D
orthogonal carbon fabric and composites reinforced with it for
aerospace applications. In this research meso-finite element (FE)
modeling employs for stress analysis in different load conditions.
Since mechanical testing of expensive textile carbon composites with
specific application isn't affordable, simulation composite in a virtual
environment is a helpful way to investigate its mechanical properties
in different conditions.
Abstract: Background: Worldwide, at least 2.8 million people
die each year as a result of being overweight or obese, and 35.8
million (2.3%) of global DALYs are caused by overweight or
obesity. Obesity is acknowledged as one of the burning public
health problems reducing life expectancy and quality of life. The
body composition analysis of the university population is essential
in assessing the nutritional status, as well as the risk of developing
diseases associated with abnormal body fat content so as to make
nutritional recommendations. Objectives: The main aim was to
determine the prevalence of obesity and overweight in University
students using Anthropometric analysis and BIA methods. Material
and Methods: In this cross-sectional study, 283 university students
participated. The body composition analysis was undertaken by
using mainly: i) Anthropometric Measurement: Height, Weight,
BMI, waist circumference, hip circumference and skin fold
thickness, ii) Bio-electrical impedance was used for analysis of
body fat mass, fat percent and visceral fat which was measured by
Tanita SC-330P Professional Body Composition Analyzer. The
data so collected were compiled in MS Excel and analyzed for
males and females using SPSS 16. Results and Discussion: The
mean age of the male (n= 153) studied subjects was 25.37 ±2.39
years and females (n=130) was 22.53 ±2.31. The data of BIA
revealed very high mean fat per cent of the female subjects i.e.
30.3±6.5 per cent whereas mean fat per cent of the male subjects
was 15.60±6.02 per cent indicating a normal body fat range. The
findings showed high visceral fat of both males (12.92±3.02) and
females (16.86±4.98). BMI, BF% and WHR were higher among
females, and BMI was higher among males. The most evident
correlation was verified between BF% and WHR for female
students (r=0.902; p
Abstract: This paper introduces symbiotic organism search (SOS)
for solving capacitated vehicle routing problem (CVRP). SOS is a new
approach in metaheuristics fields and never been used to solve discrete
problems. A sophisticated decoding method to deal with a discrete
problem setting in CVRP is applied using the basic symbiotic
organism search (SOS) framework. The performance of the algorithm
was evaluated on a set of benchmark instances and compared results
with best known solution. The computational results show that the
proposed algorithm can produce good solution as a preliminary
testing. These results indicated that the proposed SOS can be applied
as an alternative to solve the capacitated vehicle routing problem.
Abstract: Experimental studies to investigate the depth of the
scour conducted at a side-weir intersection located at the 1800 curved
flume which located Hydraulic Laboratory of Yıldız Technical
University, Istanbul, Turkey. Side weirs were located at the middle of
the straight part of the main channel. Three different lengths (25, 40
and 50 cm) and three different weir crest height (7, 10 and 12 cm) of
the side weir placed on the side weir station. There is no scour when
the material is only kaolin. Therefore, the cohesive bed was prepared
by properly mixing clay material (kaolin) with 31% sand in all
experiments. Following 24h consolidation time, in order to observe
the effect of flow intensity on the scour depth, experiments were
carried out for five different upstream Froude numbers in the range of
0.33-0.81.
As a result of this study the relation between scour depth and
upstream flow intensity as a function of time have been established.
The longitudinal velocities decreased along the side weir; towards the
downstream due to overflow over the side-weirs. At the beginning,
the scour depth increases rapidly with time and then asymptotically
approached constant values in all experiments for all side weir
dimensions as in non-cohesive sediment. Thus, the scour depth
reached equilibrium conditions. Time to equilibrium depends on the
approach flow intensity and the dimensions of side weirs. For
different heights of the weir crest, dimensionless scour depths
increased with increasing upstream Froude number. Equilibrium
scour depths which formed 7 cm side-weir crest height were obtained
higher than that of the 12 cm side-weir crest height. This means when
side-weir crest height increased equilibrium scour depths decreased.
Although the upstream side of the scour hole is almost vertical, the
downstream side of the hole is inclined.
Abstract: Chitosan functionalized Fe3O4-Au core shell
nanoparticles have been prepared using a two-step wet chemical
approach using NaBH4 as reducing agent for formation of Au in
ethylene glycol. X-ray diffraction studies shows individual phases of
Fe3O4 and Au in the as prepared samples with crystallite size of 5.9
and 11.4 nm respectively. The functionalization of the core-shell
nanostructure with Chitosan has been confirmed using Fourier
transform infrared spectroscopy along with signatures of octahedral
and tetrahedral sites of Fe3O4 below 600cm-1. Mössbauer
spectroscopy shows decrease in particle-particle interaction in
presence of Au shell (72% sextet) than pure oleic coated Fe3O4
nanoparticles (88% sextet) at room temperature. At 80K, oleic acid
coated Fe3O4 shows only sextets whereas the Chitosan functionalized
Fe3O4 and Chitosan functionalized Fe3O4@Au core shell show
presence of 5 and 11% doublet, respectively.
Abstract: This study aimed to investigate the magnetic resonance
(MR) signal enhancement ratio (ER) of contrast-enhanced MR
angiography (CE-MRA) in normal rats with gadobenate dimeglumine
(Gd-BOPTA) using a clinical 3T scanner and an extremity coil. The
relaxivities of Gd-BOPTA with saline only and with 4.5% human
serum albumin (HSA) were also measured. Compared with
Gadolinium diethylenetriaminepentaacetic acid (Gd-DTPA),
Gd-BOPTA had higher relaxivities. The maximum ER of aorta (ERa),
kidney, liver and muscle with Gd-BOPTA were higher than those with
Gd-DTPA. The maximum ERa appeared at 1.2 min and decayed to half
at 10 min after Gd-BOPTA injection. This information is helpful for
the design of CE-MRA study of rats.
Abstract: This research study aims to present a retrospective
study about speech recognition systems and artificial intelligence.
Speech recognition has become one of the widely used technologies,
as it offers great opportunity to interact and communicate with
automated machines. Precisely, it can be affirmed that speech
recognition facilitates its users and helps them to perform their daily
routine tasks, in a more convenient and effective manner. This
research intends to present the illustration of recent technological
advancements, which are associated with artificial intelligence.
Recent researches have revealed the fact that speech recognition is
found to be the utmost issue, which affects the decoding of speech. In
order to overcome these issues, different statistical models were
developed by the researchers. Some of the most prominent statistical
models include acoustic model (AM), language model (LM), lexicon
model, and hidden Markov models (HMM). The research will help in
understanding all of these statistical models of speech recognition.
Researchers have also formulated different decoding methods, which
are being utilized for realistic decoding tasks and constrained
artificial languages. These decoding methods include pattern
recognition, acoustic phonetic, and artificial intelligence. It has been
recognized that artificial intelligence is the most efficient and reliable
methods, which are being used in speech recognition.
Abstract: Many water desalination technologies have been
developed but in general they are energy intensive and have high cost
and adverse environmental impact. Recently, adsorption technology
for water desalination has been investigated showing the potential of
using low temperature waste heat (50-85oC) thus reducing energy
consumption and CO2 emissions. This work mathematically
compares the performance of an adsorption cycle that produces two
useful effects namely, fresh water and cooling using two different
adsorbents, silica-gel and an advanced zeolite material AQSOA-ZO2,
produced by Mitsubishi plastics. It was found that at low chilled
water temperatures, typically below 20oC, the AQSOA-Z02 is more
efficient than silica-gel as the cycle can produce 5.8 m3 of fresh water
per day and 50.1 Rton of cooling per tonne of AQSOA-ZO2. Above
20oC silica-gel is still better as the cycle production reaches 8.4 m3
per day and 62.4 Rton per tonne of silica-gel. These results show the
potential of using the AQSOA-Z02 at low chilled water temperature
for water desalination and cooling applications.
Abstract: Al6061 alloy base matrix, reinforced with particles of
silicon carbide (10 wt %) and Graphite powder (1wt%), known as
hybrid composites have been fabricated by liquid metallurgy route
(stir casting technique) and optimized at different parameters like
applied load, sliding speed and sliding distance by taguchi method. A
plan of experiment generated through taguchi technique was used to
perform experiments based on L27 orthogonal array. The developed
ANOVA and regression equations are used to find the optimum
coefficient of friction and wear under the influence of applied load,
sliding speed and sliding distance. On the basis of “smaller the best”
the dry sliding wear resistance was analysed and finally confirmation
tests were carried out to verify the experimental results.
Abstract: This research paper presents highly optimized barrel
shifter at 22nm Hi K metal gate strained Si technology node. This
barrel shifter is having a unique combination of static and dynamic
body bias which gives lowest power delay product. This power delay
product is compared with the same circuit at same technology node
with static forward biasing at ‘supply/2’ and also with normal reverse
substrate biasing and still found to be the lowest. The power delay
product of this barrel sifter is .39362X10-17J and is lowered by
approximately 78% to reference proposed barrel shifter at 32nm bulk
CMOS technology. Power delay product of barrel shifter at 22nm Hi
K Metal gate technology with normal reverse substrate bias is
2.97186933X10-17J and can be compared with this design’s PDP of
.39362X10-17J. This design uses both static and dynamic substrate
biasing and also has approximately 96% lower power delay product
compared to only forward body biased at half of supply voltage. The
NMOS model used are predictive technology models of Arizona state
university and the simulations to be carried out using HSPICE
simulator.
Abstract: This paper investigates and compares the community
support for tourism development between two groups of minority
ethnic descendants in Malacca, Malaysia, namely the Baba-Nyonya
and Portuguese. A descriptive research design using a quantitative
method with self-reported and self-administered questionnaires
through across-sectional approach was applied. Through the
descriptive and inferential statistics, some significantly useful
insights pertaining to the issue investigated were obtained. The
research outcomes indicate that the sense of community is somewhat
more effective in small communities in terms of togetherness,
closeness and a sense of belonging compared to the slightly bigger
minority group. In addition, the sense of community attributes
through membership, influence, integration and shared emotional
connections contributes to community participation in tourism
development regardless of which ethnic group one belongs to.
Abstract: Quantitative analyses of whisker movements provide a
means to study functional recovery and regeneration of mouse facial
nerve after an injury. However, accurate tracking of the mouse whisker
movement is challenging. Most methods for whisker tracking require
manual intervention, e.g. fixing the head of the mouse during a study.
Here we describe a semi-automated image processing method, which
is applied to high-speed video recordings of free-moving mice to track
the whisker movements. We first track the head movement of a mouse
by delineating the lower head contour frame-by-frame that allows for
detection of the location and orientation of the head. Then, a region of
interest is identified for each frame; the subsequent application of a
mask and the Hough transform detects the selected whiskers on each
side of the head. Our approach is used to examine the functional
recovery of damaged facial nerves in mice over a course of 21 days.