Abstract: Factors affecting construction unit cost vary
depending on a country’s political, economic, social and
technological inclinations. Factors affecting construction costs have
been studied from various perspectives. Analysis of cost factors
requires an appreciation of a country’s practices. Identified cost
factors provide an indication of a country’s construction economic
strata. The purpose of this paper is to identify the essential factors
that affect unit cost estimation and their breakdown using artificial
neural networks. Twenty five (25) identified cost factors in road
construction were subjected to a questionnaire survey and employing
SPSS factor analysis the factors were reduced to eight. The 8 factors
were analysed using neural network (NN) to determine the
proportionate breakdown of the cost factors in a given construction
unit rate. NN predicted that political environment accounted 44% of
the unit rate followed by contractor capacity at 22% and financial
delays, project feasibility and overhead & profit each at 11%. Project
location, material availability and corruption perception index had
minimal impact on the unit cost from the training data provided.
Quantified cost factors can be incorporated in unit cost estimation
models (UCEM) to produce more accurate estimates. This can create
improvements in the cost estimation of infrastructure projects and
establish a benchmark standard to assist the process of alignment of
work practises and training of new staff, permitting the on-going
development of best practises in cost estimation to become more
effective.
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: 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: This paper provides a comparative study on the
performances of standard PID and adaptive PID controllers tested on
travel angle of a 3-Degree-of-Freedom (3-DOF) Quanser bench-top
helicopter. Quanser, a well-known manufacturer of educational
bench-top helicopter has developed Proportional Integration
Derivative (PID) controller with Linear Quadratic Regulator (LQR)
for all travel, pitch and yaw angle of the bench-top helicopter. The
performance of the PID controller is relatively good; however, its
performance could also be improved if the controller is combined
with adaptive element. The objective of this research is to design
adaptive PID controller and then compare the performances of the
adaptive PID with the standard PID. The controller design and test is
focused on travel angle control only. Adaptive method used in this
project is self-tuning controller, which controller’s parameters are
updated online. Two adaptive algorithms those are pole-placement
and deadbeat have been chosen as the method to achieve optimal
controller’s parameters. Performance comparisons have shown that
the adaptive (deadbeat) PID controller has produced more desirable
performance compared to standard PID and adaptive (poleplacement).
The adaptive (deadbeat) PID controller attained very fast
settling time (5 seconds) and very small percentage of overshoot (5%
to 7.5%) for 10° to 30° step change of travel angle.
Abstract: With a long history, dual-task has become one of the
most intriguing research fields regarding human brain functioning
and cognition. However, findings considering effects of taskinterrelations
are limited (especially, in combined motor and
cognitive tasks). Therefore, we aimed at developing a measurement
system in order to analyse interrelation effects of cognitive and motor
tasks. On the one hand, the present study demonstrates the
applicability of the measurement system and on the other hand first
results regarding a systematisation of different task combinations are
shown. Future investigations should combine imagine technologies
and this developed measurement system.
Abstract: Systems Engineering plays a key role during industrial
product development of complex technical systems. The need for
systems engineers in industry is growing. But there is a gap between
the industrial need and the academic education. Normally the
academic education is focused on the domain specific design,
implementation and testing of technical systems. Necessary systems
engineering expertise like knowledge about requirements analysis,
product cost estimation, management or social skills are poorly
taught. Thus there is the need of new academic concepts for teaching
systems engineering skills. This paper presents a project-orientated
training concept to prepare students from different technical degree
programs for systems engineering activities. The training concept has
been initially implemented and applied in the industrial engineering
master program of the University of Applied Sciences Offenburg.
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: 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: In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation,
style, illumination, and can suffer from perspective distortion.
Pre-processing is performed to make the characters scale and
rotation invariant. Since text degradations can not be appropriately
defined using well-known geometric transformations such
as translation, rotation, affine transformation and shearing, we
use the whole character black pixels as our feature vector.
Classification is performed with minimum distance classifier
using the maximum likelihood criterion, which delivers very
promising Character Recognition Rate (CRR) of 89%. We
achieve considerably higher Word Recognition Rate (WRR) of
99% when using lower level linguistic knowledge about product
words during the recognition process.
Abstract: In recent years, the compression of date (Phoenix
dactylifera L.) fruit powders (DP) to obtain date tablets (DT) has
been suggested as a promising form of valorization of non
commercial valuable date fruit (DF) varieties. To further improve
and characterize DT, the present study aims to investigate the
influence of the DP particle size and compression force on some
physical properties of DT. The results show that independently of
particle size, the hardness (y) of tablets increases with the increase of
the compression force (x) following a logarithmic law (y = a ln (bx)
where a and b are the constants of model). Further, a full factorial
design (FFD) at two levels, applied to investigate the erosion %,
reveals that the effects of time and particle size are the same in
absolute value and they are beyond the effect of the compression.
Regarding the disintegration time, the obtained results also by means
of a FFD show that the effect of the compression force exceeds 4
times that of the DP particle size. As final stage, the color parameters
in the CIELab system of DT immediately after their obtaining are
differently influenced by the size of the initial powder.
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: Endowed of renewable energy sources (RES) are the
advantages of ASEAN, but they are using a low amount of RES only
to generate electricity because their primary energy sources are fossil
and coal. The cost of purchasing fossil and coal is cheaper now, but it
might be expensive soon, as it will be depleted sooner and after.
ASEAN showed that the RES are convenient to be implemented.
Some country in ASEAN has huge renewable energy sources
potential and use. The primary aim of this project is to assist ASEAN
countries in preparing the renewable energy and to guide the policies
for RES in the more upright direction. The Green-Y model will help
ASEAN government to study and forecast the economic concept,
including feed-in tariff.
Abstract: Securing the confidential data transferred via wireless
network remains a challenging problem. It is paramount to ensure
that data are accessible only by the legitimate users rather than by the
attackers. One of the most serious threats to organization is jamming,
which disrupts the communication between any two pairs of nodes.
Therefore, designing an attack-defending scheme without any packet
loss in data transmission is an important challenge. In this paper,
Dependence based Malicious Route Defending DMRD Scheme has
been proposed in multi path routing environment to prevent jamming
attack. The key idea is to defend the malicious route to ensure
perspicuous transmission. This scheme develops a two layered
architecture and it operates in two different steps. In the first step,
possible routes are captured and their agent dependence values are
marked using triple agents. In the second step, the dependence values
are compared by performing comparator filtering to detect malicious
route as well as to identify a reliable route for secured data
transmission. By simulation studies, it is observed that the proposed
scheme significantly identifies malicious route by attaining lower
delay time and route discovery time; it also achieves higher
throughput.
Abstract: The focal aspire of e-Government (eGovt) is to offer
citizen-centered service delivery. Accordingly, the citizenry
consumes services from multiple government agencies through
national portal. Thus, eGovt is an enterprise with the primary
business motive of transparent, efficient and effective public services
to its citizenry and its logical structure is the eGovernment Enterprise
Architecture (eGEA). Since eGovt is IT oriented multifaceted
service-centric system, EA doesn’t do much on an automated
enterprise other than the business artifacts. Service-Oriented
Architecture (SOA) manifestation led some governments to pertain
this in their eGovts, but it limits the source of business artifacts. The
concurrent use of EA and SOA in eGovt executes interoperability and
integration and leads to Service-Oriented e-Government Enterprise
(SOeGE). Consequently, agile eGovt system becomes a reality. As an
IT perspective eGovt comprises of centralized public service artifacts
with the existing application logics belong to various departments at
central, state and local level. The eGovt is renovating to SOeGE by
apply the Service-Orientation (SO) principles in the entire system.
This paper explores IT perspective of SOeGE in India which
encompasses the public service models and illustrated with a case
study the Passport service of India.
Abstract: Real time image and video processing is a demand in
many computer vision applications, e.g. video surveillance, traffic
management and medical imaging. The processing of those video
applications requires high computational power. Thus, the optimal
solution is the collaboration of CPU and hardware accelerators. In
this paper, a Canny edge detection hardware accelerator is proposed.
Edge detection is one of the basic building blocks of video and image
processing applications. It is a common block in the pre-processing
phase of image and video processing pipeline. Our presented
approach targets offloading the Canny edge detection algorithm from
processing system (PS) to programmable logic (PL) taking the
advantage of High Level Synthesis (HLS) tool flow to accelerate the
implementation on Zynq platform. The resulting implementation
enables up to a 100x performance improvement through hardware
acceleration. The CPU utilization drops down and the frame rate
jumps to 60 fps of 1080p full HD input video stream.