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: In this study, attempt has been made to investigate the
relationship specifically the causal relation between fund unit prices
of Islamic equity unit trust fund which measure by fund NAV and the
selected macro-economic variables of Malaysian economy by using
VECM causality test and Granger causality test. Monthly data has
been used from Jan, 2006 to Dec, 2012 for all the variables. The
findings of the study showed that industrial production index,
political election and financial crisis are the only variables having
unidirectional causal relationship with fund unit price. However the
global oil price is having bidirectional causality with fund NAV.
Thus, it is concluded that the equity unit trust fund industry in
Malaysia is an inefficient market with respect to the industrial
production index, global oil prices, political election and financial
crisis. However the market is approaching towards informational
efficiency at least with respect to four macroeconomic variables,
treasury bill rate, money supply, foreign exchange rate, and
corruption index.
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: 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: 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: 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: The paper examines the interaction between the
environmental taxation, size of government spending on
environmental protection and greenhouse gas emissions and gross
inland energy consumption. The aim is to analyze the effects of
environmental taxation and government spending on environmental
protection as an environmental policy instruments on greenhouse gas
emissions and gross inland energy consumption in the EU15. The
empirical study is performed using a VAR approach with the
application of aggregated data of EU15 over the period 1995 to 2012.
The results provide the evidence that the reactions of greenhouse gas
emission and gross inland energy consumption to the shocks of
environmental policy instruments are strong, mainly in the short term
and decay to zero after about 8 years. Further, the reactions of the
environmental policy instruments to the shocks of greenhouse gas
emission and gross inland energy consumption are also strong in the
short term, however with the deferred effects. In addition, the results
show that government spending on environmental protection together
with gross inland energy consumption has stronger effect on
greenhouse gas emissions than environmental taxes in EU15 over the
examined period.
Abstract: TiO2 thin films have been prepared by the sol-gel dipcoating
technique in order to elaborate antireflective thin films for
monocrystalline silicon (mono-Si). The titanium isopropoxyde was
chosen as a precursor with hydrochloric acid as a catalyser for
preparing a stable solution. The optical properties have been tailored
with varying the solution concentration, the withdrawn speed, and the
heat-treatment. We showed that using a TiO2 single layer with 64.5
nm in thickness, heat-treated at 450°C or 300°C reduces the mono-Si
reflection at a level lower than 3% over the broadband spectral
domains [669-834] nm and [786-1006] nm respectively. Those latter
performances are similar to the ones obtained with double layers of
low and high refractive index glasses respectively.
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: In this paper a new design of a broadband microwave
power limiter is presented and validated into simulation by using
ADS software (Advanced Design System) from Agilent technologies.
The final circuit is built on microstrip lines by using identical Zero
Bias Schottky diodes. The power limiter is designed by Associating 3
stages Schottky diodes. The obtained simulation results permit to
validate this circuit with a threshold input power level of 0 dBm until
a maximum input power of 30 dBm.
Abstract: The globalization of markets, the need to develop
competitive advantages and core competencies, among other things,
lead organizations to increasingly cross borders to operate in other
countries. The expatriation of professionals who go to work in
another country besides their own becomes increasingly common. In
order to generate data about this issue, research was conducted
concerning the perception of expatriate employees concerning
expatriation success. The research method used was case study
through a qualitative approach. This research was done through
interviews with five India expatriates and five China expatriates,
interview with expatriate department heads and analysis of company
documents. It was found that there are differences between the
organizational perception and perception of expatriates of what
constitutes mission success. The paper also provides suggestions for
further research and suggestions for future expatriates.
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 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.
Abstract: The IEEE 802.22 working group aims to drive the
Digital Video Broadcasting-Terrestrial (DVB-T) bands for data
communication to the rural area without interfering the TV broadcast.
In this paper, we arrive at a closed-form expression for average
detection probability of Fusion center (FC) with multiple antenna
over the κ − μ fading channel model. We consider a centralized
cooperative multiple antenna network for reporting. The DVB-T
samples forwarded by the secondary user (SU) were combined using
Maximum ratio combiner at FC, an energy detection is performed
to make the decision. The fading effects of the channel degrades
the detection probability of the FC, a generalized independent and
identically distributed (IID) κ − μ and an additive white Gaussian
noise (AWGN) channel is considered for reporting and sensing
respectively. The proposed system performance is verified through
simulation results.
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.
Abstract: Learning through creation of contextual games is a
very promising approach when undertaking interdisciplinary and
international group projects. During 2013 and 2014 the authors
organized two intensive student projects. The two projects were in
different countries and different conditions. Between them, the two
projects involved 68 students and 12 mentors from five EU countries
and from various academic disciplines. In this paper we share our
experience of these two projects and we suggest approaches that can
be utilized to strengthen the chances of succeeding in short (12-15
days long) intensive student projects.
Abstract: Software Architecture is the basic structure of
software that states the development and advancement of a software
system. Software architecture is also considered as a significant tool
for the construction of high quality software systems. A clean design
leads to the control, value and beauty of software resulting in its
longer life while a bad design is the cause of architectural erosion
where a software evolution completely fails. This paper discusses the
occurrence of software architecture erosion and presents a set of
methods for the detection, declaration and prevention of architecture
erosion. The causes and symptoms of architecture erosion are
observed with the examples of prescriptive and descriptive
architectures and the practices used to stop this erosion are also
discussed by considering different types of software erosion and their
affects. Consequently finding and devising the most suitable
approach for fighting software architecture erosion and in some way
reducing its affect is evaluated and tested on different scenarios.
Abstract: We present a trigonometric scheme to approximate a
circular arc with its two end points and two end tangents/unit
tangents. A rational cubic trigonometric Bézier curve is constructed
whose end control points are defined by the end points of the circular
arc. Weight functions and the remaining control points of the cubic
trigonometric Bézier curve are estimated by variational approach to
reproduce a circular arc. The radius error is calculated and found less
than the existing techniques.
Abstract: Near infrared (NIR) spectroscopy has always been of
great interest in the food and agriculture industries. The development
of prediction models has facilitated the estimation process in recent
years. In this study, 110 crude palm oil (CPO) samples were used to
build a free fatty acid (FFA) prediction model. 60% of the collected
data were used for training purposes and the remaining 40% used for
testing. The visible peaks on the NIR spectrum were at 1725 nm and
1760 nm, indicating the existence of the first overtone of C-H bands.
Principal component regression (PCR) was applied to the data in
order to build this mathematical prediction model. The optimal
number of principal components was 10. The results showed
R2=0.7147 for the training set and R2=0.6404 for the testing set.