Abstract: The thermal conductivity of a fluid can be
significantly enhanced by dispersing nano-sized particles in it, and
the resultant fluid is termed as "nanofluid". A theoretical model for
estimating the thermal conductivity of a nanofluid has been proposed
here. It is based on the mechanism that evenly dispersed
nanoparticles within a nanofluid undergo Brownian motion in course
of which the nanoparticles repeatedly collide with the heat source.
During each collision a rapid heat transfer occurs owing to the solidsolid
contact. Molecular dynamics (MD) simulation of the collision
of nanoparticles with the heat source has shown that there is a pulselike
pick up of heat by the nanoparticles within 20-100 ps, the extent
of which depends not only on thermal conductivity of the
nanoparticles, but also on the elastic and other physical properties of
the nanoparticle. After the collision the nanoparticles undergo
Brownian motion in the base fluid and release the excess heat to the
surrounding base fluid within 2-10 ms. The Brownian motion and
associated temperature variation of the nanoparticles have been
modeled by stochastic analysis. Repeated occurrence of these events
by the suspended nanoparticles significantly contributes to the
characteristic thermal conductivity of the nanofluids, which has been
estimated by the present model for a ethylene glycol based nanofluid
containing Cu-nanoparticles of size ranging from 8 to 20 nm, with
Gaussian size distribution. The prediction of the present model has
shown a reasonable agreement with the experimental data available
in literature.
Abstract: Climate change confronts the built environment with
many new challenges in the form of more severe and frequent hydrometeorological
events. A series of strategies is proposed whereby the
various aspects of buildings and their sites can be made more resilient
to the effects of such events.
Abstract: Artificial Neural Network (ANN) can be trained using
back propagation (BP). It is the most widely used algorithm for
supervised learning with multi-layered feed-forward networks.
Efficient learning by the BP algorithm is required for many practical
applications. The BP algorithm calculates the weight changes of
artificial neural networks, and a common approach is to use a twoterm
algorithm consisting of a learning rate (LR) and a momentum
factor (MF). The major drawbacks of the two-term BP learning
algorithm are the problems of local minima and slow convergence
speeds, which limit the scope for real-time applications. Recently the
addition of an extra term, called a proportional factor (PF), to the
two-term BP algorithm was proposed. The third increases the speed
of the BP algorithm. However, the PF term also reduces the
convergence of the BP algorithm, and criteria for evaluating
convergence are required to facilitate the application of the three
terms BP algorithm. Although these two seem to be closely related,
as described later, we summarize various improvements to overcome
the drawbacks. Here we compare the different methods of
convergence of the new three-term BP algorithm.
Abstract: This study examines the credibility of the signaling as
explanation for IPO initial underpricing. Findings reveal the initial
underpricing and the long-term underperformance of IPOs in Taiwan.
However, we only find weak support for signaling as explanation of
IPO underpricing.
Abstract: The purpose of this study was to reduce patient
waiting times, improve system throughput and improve resources
utilization in radiology department. A discrete event simulation
model was developed using Arena simulation software to investigate
different alternatives to improve the overall system delivery based on
adding resource scenarios due to the linkage between patient waiting
times and resource availability. The study revealed that there is no
addition investment need to procure additional scanner but hospital
management deploy managerial tactics to enhance machine
utilization and reduce the long waiting time in the department.
Abstract: In this paper, effect of marginal quality groundwater
on yield of cotton crop and soil salinity was studied. In this
connection, three irrigation treatments each with four replications
were applied. These treatments were i) use of canal water (T1), ii) use
of marginal quality groundwater from tubewell (T2), and iii)
conjunctive use by mixing with the ratio of 1:1 of canal water and
marginal quality tubewell water (T3).
Water was applied to the crop cultivated in Kharif season 2011; its
quantity has been measured using cut-throat flume. Total 11 watering
each of 50 mm depth have been applied from 20th April to 20th July,
2011. Further, irrigations were stopped due to monsoon rainfall up to
crop harvesting.
Maximum crop yield (seed cotton) was observed under T1 which
was 1,517 kg/ha followed by T3 (mixed canal and tubewell water)
having 1009 kg/ha and T2 i.e. marginal quality groundwater having
709 kg/ha. This concludes that crop yield in T2 and T3 in comparison
to T1was reduced by about 53 and 30% respectively.
It has been observed that yield of cotton crop is below potential
limit for three treatments due to unexpected rainfall at the time of full
flowering season; thus the yield was adversely affected.
However, salt deposition in soil profiles was not observed that is
due to leaching effect of heavy rainfall occurred during monsoon
season.
Abstract: In this study which has been conducted in Akçasu
Forest Range District of Devrek Forest Directorate; 3 methods (weed
control with labourer power, cover removal with Hitachi F20
Excavator, and weed control with agricultural equipment mounted on
a Ferguson 240S agriculture tractor) were utilized in weed control
efforts in regeneration of degraded oriental beech forests have been
compared. In this respect, 3 methods have been compared by
determining certain work hours and standard durations of unit areas
(1 hectare). For this purpose, evaluating the tasks made with human
and machine force from the aspects of duration, productivity and
costs, it has been aimed to determine the most productive method in
accordance with the actual ecological conditions of research field.
Within the scope of the study, the time studies have been conducted
for 3 methods used in weed control efforts. While carrying out those
studies, the performed implementations have been evaluated by
dividing them into business stages. Also, the actual data have been
used while calculating the cost accounts. In those calculations, the
latest formulas and equations which are also used in developed
countries have been utilized. The variance of analysis (ANOVA) was
used in order to determine whether there is any statistically
significant difference among obtained results, and the Duncan test
was used for grouping if there is significant difference. According to
the measurements and findings carried out within the scope of this
study, it has been found during living cover removal efforts in
regeneration efforts in demolished oriental beech forests that the
removal of weed layer in 1 hectare of field has taken 920 hours with
labourer force, 15.1 hours with excavator and 60 hours with an
equipment mounted on a tractor. On the other hand, it has been
determined that the cost of removal of living cover in unit area (1
hectare) was 3220.00 TL for labourer power, 1250 TL for excavator
and 1825 TL for equipment mounted on a tractor.
According to the obtained results, it has been found that the
utilization of excavator in weed control effort in regeneration of
degraded oriental beech regions under actual ecological conditions of
research field has been found to be more productive from both of
aspects of duration and costs. These determinations carried out
should be repeated in weed control efforts in degraded forest fields
with different ecological conditions, it is compulsory for finding the
most efficient weed control method. These findings will light the way
of technical staff of forestry directorate in determination of the most
effective and economic weed control method. Thus, the more actual
data will be used while preparing the weed control budgets, and there
will be significant contributions to national economy. Also the results of this and similar studies are very important for developing the policies for our forestry in short and long term.
Abstract: Liposome plays an important role in medical and
pharmaceutical science as e.g. nano scale drug carriers. Liposomes
are vesicles of varying size consisting of a spherical lipid bilayer and
an aqueous inner compartment. Magnet-driven liposome used for the
targeted delivery of drugs to organs and tissues. These liposome
preparations contain encapsulated drug components and finely
dispersed magnetic particles.
Liposomes are vesicles of varying size consisting of a spherical
lipid bilayer and an aqueous inner compartment that are generated in
vitro. These are useful in terms of biocompatibility, biodegradability,
and low toxicity, and can control biodistribution by changing the size,
lipid composition, and physical characteristics. Furthermore,
liposomes can entrap both hydrophobic and hydrophilic drugs and are
able to continuously release the entrapped substrate, thus being useful
drug carriers. Magnetic liposomes (MLs) are phospholipid vesicles
that encapsulate magneticor paramagnetic nanoparticles. They are
applied as contrast agents for magnetic resonance imaging (MRI).
The biological synthesis of nanoparticles using plant extracts plays
an important role in the field of nanotechnology. Green-synthesized
magnetite nanoparticles-protein hybrid has been produced by treating
Iron (III) / Iron (II) chloride with the leaf extract of Datura inoxia.
The phytochemicals present in the leaf extracts act as a reducing as
well stabilizing agents preventing agglomeration, which include
flavonoids, phenolic compounds, cardiac glycosides, proteins and
sugars.
The magnetite nanoparticles-protein hybrid has been trapped
inside the aqueous core of the liposome prepared by reversed phase
evaporation (REV) method using oleic and linoleic acid which has
been shown to be driven under magnetic field confirming the
formation magnetic liposome (ML). Chemical characterization of
stealth magnetic liposome has been performed by breaking the
liposome and release of magnetic nanoparticles. The presence iron
has been confirmed by colour complex formation with KSCN and
UV-Vis study using spectrophotometer Cary 60, Agilent.
This magnet driven liposome using nanoparticles-protein hybrid
can be a smart vesicles for the targeted drug delivery.
Abstract: Over the last few decades, oilfield service rolling
equipment has significantly increased in weight, primarily because of
emissions regulations, which require larger/heavier engines, larger
cooling systems, and emissions after-treatment systems, in some
cases, etc. Larger engines cause more vibration and shock loads,
leading to failure of electronics and control systems.
If the vibrating frequency of the engine matches the system
frequency, high resonance is observed on structural parts and mounts.
One such existing automated control equipment system comprising
wire rope mounts used for mounting computers was designed
approximately 12 years ago. This includes the use of an industrialgrade
computer to control the system operation. The original
computer had a smaller, lighter enclosure. After a few years, a newer
computer version was introduced, which was 10 lbm heavier. Some
failures of internal computer parts have been documented for cases in
which the old mounts were used. Because of the added weight, there
is a possibility of having the two brackets impact each other under
off-road conditions, which causes a high shock input to the computer
parts. This added failure mode requires validating the existing mount
design to suit the new heavy-weight computer.
This paper discusses the modal finite element method (FEM)
analysis and experimental modal analysis conducted to study the
effects of vibration on the wire rope mounts and the computer. The
existing mount was modelled in ANSYS software, and resultant
mode shapes and frequencies were obtained. The experimental modal
analysis was conducted, and actual frequency responses were
observed and recorded.
Results clearly revealed that at resonance frequency, the brackets
were colliding and potentially causing damage to computer parts. To
solve this issue, spring mounts of different stiffness were modeled in
ANSYS software, and the resonant frequency was determined.
Increasing the stiffness of the system increased the resonant
frequency zone away from the frequency window at which the engine
showed heavy vibrations or resonance. After multiple iterations in
ANSYS software, the stiffness of the spring mount was finalized,
which was again experimentally validated.
Abstract: Many wireless sensor network applications require
K-coverage of the monitored area. In this paper, we propose a
scalable harmony search based algorithm in terms of execution
time, K-Coverage Enhancement Algorithm (KCEA), it attempts to
enhance initial coverage, and achieve the required K-coverage degree
for a specific application efficiently. Simulation results show that
the proposed algorithm achieves coverage improvement of 5.34%
compared to K-Coverage Rate Deployment (K-CRD), which achieves
1.31% when deploying one additional sensor. Moreover, the proposed
algorithm is more time efficient.
Abstract: Nowadays social media information, such as news,
links, images, or VDOs, is shared extensively. However, the
effectiveness of disseminating information through social media
lacks in quality: less fact checking, more biases, and several rumors.
Many researchers have investigated about credibility on Twitter, but
there is no the research report about credibility information on
Facebook. This paper proposes features for measuring credibility on
Facebook information. We developed the system for credibility on
Facebook. First, we have developed FB credibility evaluator for
measuring credibility of each post by manual human’s labelling. We
then collected the training data for creating a model using Support
Vector Machine (SVM). Secondly, we developed a chrome extension
of FB credibility for Facebook users to evaluate the credibility of
each post. Based on the usage analysis of our FB credibility chrome
extension, about 81% of users’ responses agree with suggested
credibility automatically computed by the proposed system.
Abstract: The recommended limit for cadmium concentration in
potable water is less than 0.005 mg/L. A continuous biosorption
process using indigenous red seaweed, Gracilaria corticata, was
performed to remove cadmium from the potable water. The process
was conducted under fixed conditions and the breakthrough curves
were achieved for three consecutive sorption-desorption cycles. A
modeling based on Artificial Neural Network (ANN) was employed
to fit the experimental breakthrough data. In addition, a simplified
semi empirical model, Thomas, was employed for this purpose. It
was found that ANN well described the experimental data (R2>0.99)
while the Thomas prediction were a bit less successful with R2>0.97.
The adjusted design parameters using the nonlinear form of Thomas
model was in a good agreement with the experimentally obtained
ones. The results approve the capability of ANN to predict the
cadmium concentration in potable water.
Abstract: The problematic of gender and socioeconomic status
biased differences in academic motivation patterns is discussed.
Gender identity is understood according to symbolic interactionism
perspective: as a result of reflected appraisals, social comparisons,
self-attributions, and identifications, shaped by social environment
and family context. The effects of socioeconomic status on academic
motivation are conceptualized according to Bourdieu’s habitus
concept, reflecting the role of unconscious and internalized cultural
signals, proper to low and high socioeconomic status family contexts.
Since families differ by various socioeconomic features, the
hypothesis about possible impact of parents’ socioeconomic status on
their children’s academic motivation interfering with gender
socialization effects is held. The survey, aiming to seize gender
differences in academic motivation and self-recorded improvementoriented
efforts as a result of socialization processes operating in the
families of low and high socioeconomic status, was designed. The
results of Lithuanian higher education students’ survey are presented
and discussed.
Abstract: Nowadays, Photovoltaic-PV Farms/ Parks and large
PV-Smart Grid Interface Schemes are emerging and commonly
utilized in Renewable Energy distributed generation. However, PVhybrid-
Dc-Ac Schemes using interface power electronic converters
usually has negative impact on power quality and stabilization of
modern electrical network under load excursions and network fault
conditions in smart grid. Consequently, robust FACTS based
interface schemes are required to ensure efficient energy utilization
and stabilization of bus voltages as well as limiting switching/fault
onrush current condition. FACTS devices are also used in smart grid-
Battery Interface and Storage Schemes with PV-Battery Storage
hybrid systems as an elegant alternative to renewable energy
utilization with backup battery storage for electric utility energy and
demand side management to provide needed energy and power
capacity under heavy load conditions. The paper presents a robust
interface PV-Li-Ion Battery Storage Interface Scheme for
Distribution/Utilization Low Voltage Interface using FACTS
stabilization enhancement and dynamic maximum PV power tracking
controllers.
Digital simulation and validation of the proposed scheme is done
using MATLAB/Simulink software environment for Low Voltage-
Distribution/Utilization system feeding a hybrid Linear-Motorized
inrush and nonlinear type loads from a DC-AC Interface VSC-6-
pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion
Storage Battery.
Abstract: In this work, neural networks methods MLP type were
applied to a database from an array of six sensors for the detection of
three toxic gases. The choice of the number of hidden layers and the
weight values are influential on the convergence of the learning
algorithm. We proposed, in this article, a mathematical formula to
determine the optimal number of hidden layers and good weight
values based on the method of back propagation of errors. The results
of this modeling have improved discrimination of these gases and
optimized the computation time. The model presented here has
proven to be an effective application for the fast identification of
toxic gases.
Abstract: Container handling problems at container terminals
are NP-hard problems. This paper presents an approach using
discrete-event simulation modeling to optimize solution for storage
space allocation problem, taking into account all various interrelated
container terminal handling activities. The proposed approach is
applied on a real case study data of container terminal at Alexandria
port. The computational results show the effectiveness of the
proposed model for optimization of storage space allocation in
container terminal where 54% reduction in containers handling time
in port is achieved.
Abstract: The exact theoretical expression describing the
probability distribution of nonlinear sea-surface elevations derived
from the second-order narrowband model has a cumbersome form
that requires numerical computations, not well-disposed to theoretical
or practical applications. Here, the same narrowband model is reexamined
to develop a simpler closed-form approximation suitable
for theoretical and practical applications. The salient features of the
approximate form are explored, and its relative validity is verified
with comparisons to other readily available approximations, and
oceanic data.
Abstract: Taking the design tolerance into account, this paper
presents a novel efficient approach to generate iso-scallop tool path for
five-axis strip machining with a barrel cutter. The cutter location is
first determined on the scallop surface instead of the design surface,
and then the cutter is adjusted to locate the optimal tool position based
on the differential rotation of the tool axis and satisfies the design
tolerance simultaneously. The machining strip width and error are
calculated with the aid of the grazing curve of the cutter. Based on the
proposed tool positioning algorithm, the tool paths are generated by
keeping the scallop height formed by adjacent tool paths constant. An
example is conducted to confirm the validity of the proposed method.
Abstract: The paper focus on robotic telepresence system build
around humanoid robot operated with controller-less Wizard of Oz
technique. Proposed solution gives possibility to quick start acting as
a operator with short, if any, initial training.
Abstract: The use of eXtensible Markup Language (XML) in
web, business and scientific databases lead to the development of
methods, techniques and systems to manage and analyze XML data.
Semi-structured documents suffer due to its heterogeneity and
dimensionality. XML structure and content mining represent
convergence for research in semi-structured data and text mining. As
the information available on the internet grows drastically, extracting
knowledge from XML documents becomes a harder task. Certainly,
documents are often so large that the data set returned as answer to a
query may also be very big to convey the required information. To
improve the query answering, a Semantic Tree Based Association
Rule (STAR) mining method is proposed. This method provides
intentional information by considering the structure, content and the
semantics of the content. The method is applied on Reuter’s dataset
and the results show that the proposed method outperforms well.