Abstract: A key issue in seismic risk analysis within the context
of Performance-Based Earthquake Engineering is the evaluation of
the expected seismic damage of structures under a specific
earthquake ground motion. The assessment of the seismic
performance strongly depends on the choice of the seismic Intensity
Measure (IM), which quantifies the characteristics of a ground
motion that are important to the nonlinear structural response. Several
conventional IMs of ground motion have been used to estimate their
damage potential to structures. Yet, none of them has been proved to
be able to predict adequately the seismic damage. Therefore,
alternative, scalar intensity measures, which take into account not
only ground motion characteristics but also structural information
have been proposed. Some of these IMs are based on integration of
spectral values over a range of periods, in an attempt to account for
the information that the shape of the acceleration, velocity or
displacement spectrum provides. The adequacy of a number of these
IMs in predicting the structural damage of 3D R/C buildings is
investigated in the present paper. The investigated IMs, some of
which are structure specific and some are non structure-specific, are
defined via integration of spectral values. To achieve this purpose
three symmetric in plan R/C buildings are studied. The buildings are
subjected to 59 bidirectional earthquake ground motions. The two
horizontal accelerograms of each ground motion are applied along
the structural axes. The response is determined by nonlinear time
history analysis. The structural damage is expressed in terms of the
maximum interstory drift as well as the overall structural damage
index. The values of the aforementioned seismic damage measures
are correlated with seven scalar ground motion IMs. The comparative
assessment of the results revealed that the structure-specific IMs
present higher correlation with the seismic damage of the three
buildings. However, the adequacy of the IMs for estimation of the
structural damage depends on the response parameter adopted.
Furthermore, it was confirmed that the widely used spectral
acceleration at the fundamental period of the structure is a good
indicator of the expected earthquake damage level.
Abstract: E-service quality plays a significant role to achieve
success or failure in any organization, offering services online. It will
increase the competition among the organizations, to attract the
customers on the basis of the quality of service provided by the
organization. Better e-service quality will enhance the relationship
with customers and their satisfaction. So the measurement of eservice
quality is very important but it is a complex process due to
the complex nature of services. Literature predicts that there is a lack
of universal definition of e-service quality. The e-service quality
measures in banking have great importance in achieving high
customer base. This paper proposes a conceptual model for
measuring e-service quality in Indian Banking Industry. Nine
dimensions reliability, ease of use, personalization, security and trust,
website aesthetic, responsiveness, contact and fulfillment had been
identified. The results of this paper may help to develop a proper
scale to measure the e-service quality in Indian Banking Industry,
which may assist to maintain and improve the performance and
effectiveness of e-service quality to retain customers.
Abstract: Predicting earthquakes is an important issue in the
study of geography. Accurate prediction of earthquakes can help
people to take effective measures to minimize the loss of personal
and economic damage, such as large casualties, destruction of
buildings and broken of traffic, occurred within a few seconds.
United States Geological Survey (USGS) science organization
provides reliable scientific information about Earthquake Existed
throughout history & the Preliminary database from the National
Center Earthquake Information (NEIC) show some useful factors to
predict an earthquake in a seismic area like Aleutian Arc in the U.S.
state of Alaska. The main advantage of this prediction method that it
does not require any assumption, it makes prediction according to the
future evolution of the object's time series. The article compares
between simulation data result from trained BP and RBF neural
network versus actual output result from the system calculations.
Therefore, this article focuses on analysis of data relating to real
earthquakes. Evaluation results show better accuracy and higher
speed by using radial basis functions (RBF) neural network.
Abstract: Aim of this work was to study the genetic basis for oil
accumulation in olive fruit via tracking DGAT2 (Diacylglycerol
acyltransferase type-2) gene in three Egyptian Origen Olive cultivars
namely Toffahi, Hamed and Maraki using molecular marker
techniques and bioinformatics tools. Results illustrate that, firstly:
specific genomic band of Maraki cultivars was identified as DGAT2
(Diacylglycerol acyltransferase type-2) and identical for this gene in
Olea europaea with 100% of similarity. Secondly, differential
genomic band of Maraki cultivars which produced from RAPD
fingerprinting technique reflected predicted distinguished sequence
which identified as DGAT2 (Diacylglycerol acyltransferase type-2)
in Fragaria vesca subsp. Vesca with 76% of sequential similarity.
Third and finally, specific genomic specific band of Hamed cultivars
was identified as two fragments, 1- Olea europaea cultivar Koroneiki
diacylglycerol acyltransferase type 2 mRNA, complete cds with two
matches regions with 99% or 2- Predicted: Fragaria vesca subsp.
vesca diacylglycerol O-acyltransferase 2-like (LOC101313050),
mRNA with 86 % of similarity.
Abstract: The knowledge of biodiesel density over large ranges
of temperature and pressure is important for predicting the behavior
of fuel injection and combustion systems in diesel engines, and for
the optimization of such systems. In this study, cottonseed oil was
transesterified into biodiesel and its density was measured at
temperatures between 288 K and 358 K and pressures between 0.1
MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg⋅m-
3. Experimental pressure-volume-temperature (pVT) cottonseed data
was used along with literature data relative to other 18 biodiesels, in
order to build a database used to test the correlation of density with
temperarure and pressure using the Goharshadi–Morsali–Abbaspour
equation of state (GMA EoS). To our knowledge, this is the first that
density measurements are presented for cottonseed biodiesel under
such high pressures, and the GMA EoS used to model biodiesel
density. The new tested EoS allowed correlations within 0.2 kg·m-3
corresponding to average relative deviations within 0.02%. The built
database was used to develop and test a new full predictive model
derived from the observed linear relation between density and degree
of unsaturation (DU), which depended from biodiesel FAMEs
profile. The average density deviation of this method was only about
3 kg.m-3 within the temperature and pressure limits of application.
These results represent appreciable improvements in the context of
density prediction at high pressure when compared with other
equations of state.
Abstract: The power converter that feeds high-frequency, highvoltage
transformers must be carefully designed due to parasitic
components, mainly the secondary winding capacitance and the
leakage inductance, that introduces resonances in relatively lowfrequency
range, next to the switching frequency. This paper
considers applications in which the load (resistive) has an
unpredictable behavior, changing from open to short-circuit condition
faster than the output voltage control loop could react. In this context,
to avoid overvoltage and over current situations, that could damage
the converter, the transformer or the load, it is necessary to find an
operation point that assure the desired output voltage in spite of the
load condition. This can done adjusting the frequency response of the
transformer adding an external inductance, together with selecting the
switching frequency to get stable output voltage independently of the
load.
Abstract: Series of laboratory tests were carried out to study the
extent of scour caused by a three-dimensional wall jets exiting from a
square cross-section nozzle and into a non-cohesive sand beds.
Previous observations have indicated that the effect of the tail water
depth was significant for densimetric Froude number greater than ten.
However, the present results indicate that the cut off value could be
lower depending on the value of grain size-to-nozzle width ratio.
Numbers of equations are drawn out for a better scaling of numerous
scour parameters. Also suggested the empirical prediction of scour to
predict the scour centre line profile and plan view of scour profile at
any particular time.
Abstract: Pavement surface unevenness plays a pivotal role on
roughness index of road which affects on riding comfort ability.
Comfort ability refers to the degree of protection offered to vehicle
occupants from uneven elements in the road surface. So, it is
preferable to have a lower roughness index value for a better riding
quality of road users. Roughness is generally defined as an
expression of irregularities in the pavement surface which can be
measured using different equipments like MERLIN, Bump integrator,
Profilometer etc. Among them Bump Integrator is quite simple and
less time consuming in case of long road sections. A case study is
conducted on low volume roads in West District in Tripura to
determine roughness index (RI) using Bump Integrator at the
standard speed of 32 km/h. But it becomes too tough to maintain the
requisite standard speed throughout the road section. The speed of
Bump Integrator (BI) has to lower or higher in some distinctive
situations. So, it becomes necessary to convert these roughness index
values of other speeds to the standard speed of 32 km/h. This paper
highlights on that roughness index conversional model. Using SPSS
(Statistical Package of Social Sciences) software a generalized
equation is derived among the RI value at standard speed of 32 km/h
and RI value at other speed conditions.
Abstract: Present study is aimed on the cutting process of circular
cross-section rods where the fracture is used to separate one rod
into two pieces. Incorporating the phenomenological ductile fracture
model into the explicit formulation of finite element method, the
process can be analyzed without the necessity of realizing too many
real experiments which could be expensive in case of repetitive
testing in different conditions. In the present paper, the steel AISI
1045 was examined and the tensile tests of smooth and notched
cylindrical bars were conducted together with biaxial testing of the
notched tube specimens to calibrate material constants of selected
phenomenological ductile fracture models. These were implemented
into the Abaqus/Explicit through user subroutine VUMAT and used
for cutting process simulation. As the calibration process is based
on variables which cannot be obtained directly from experiments,
numerical simulations of fracture tests are inevitable part of the
calibration. Finally, experiments regarding the cutting process were
carried out and predictive capability of selected fracture models is
discussed. Concluding remarks then make the summary of gained
experience both with the calibration and application of particular
ductile fracture criteria.
Abstract: The substantial similarity of fatigue mechanism in a
new test rig for rolling contact fatigue (RCF) has been investigated. A
new reduced-scale test rig is designed to perform controlled RCF
tests in wheel-rail materials. The fatigue mechanism of the rig is
evaluated in this study using a combined finite element-fatigue
prediction approach. The influences of loading conditions on fatigue
crack initiation have been studied. Furthermore, the effects of some
artificial defects (squat-shape) on fatigue lives are examined. To
simulate the vehicle-track interaction by means of the test rig, a threedimensional
finite element (FE) model is built up. The nonlinear
material behaviour of the rail steel is modelled in the contact
interface. The results of FE simulations are combined with the critical
plane concept to determine the material points with the greatest
possibility of fatigue failure. Based on the stress-strain responses, by
employing of previously postulated criteria for fatigue crack initiation
(plastic shakedown and ratchetting), fatigue life analysis is carried
out. The results are reported for various loading conditions and
different defect sizes. Afterward, the cyclic mechanism of the test rig
is evaluated from the operational viewpoint. The results of fatigue
life predictions are compared with the expected number of cycles of
the test rig by its cyclic nature. Finally, the estimative duration of the
experiments until fatigue crack initiation is roughly determined.
Abstract: This work presents a Computational Fluid Dynamics
(CFD) simulation of a butterfly valve used to control the flow of
combustible gas mixture in an industrial process setting.The work
uses CFD simulation to analyze the flow characteristics in the
vicinity of the valve, including the pressure distributions and
Frequency spectrum of the pressure pulsations downstream the valves
and the vortex shedding allow predicting the torque fluctuations
acting on the valve shaft and the possibility of generating mechanical
vibration and resonance.These fluctuations are due to aerodynamic
torque resulting from fluid turbulence and vortex shedding in the
valve vicinity.
The valve analyzed is located in a pipeline between two opposing
90o elbows, which exposes the valve and the surrounding structure to
the turbulence generated upstream and downstream the elbows at
either end of the pipe.CFD simulations show that the best location for
the valve from a vibration point of view is in the middle of the pipe
joining the elbows.
Abstract: Different services based on different switching
techniques in wireless networks leads to drastic changes in the
properties of network traffic. Because of these diversities in services,
network traffic is expected to undergo qualitative and quantitative
variations. Hence, assumption of traffic characteristics and the
prediction of network events become more complex for the wireless
networks. In this paper, the traffic characteristics have been studied
by collecting traces from the mobile switching centre (MSC). The
traces include initiation and termination time, originating node, home
station id, foreign station id. Traffic parameters namely, call interarrival
and holding times were estimated statistically. The results
show that call inter-arrival and distribution time in this wireless
network is heavy-tailed and follow gamma distributions. They are
asymptotically long-range dependent. It is also found that the call
holding times are best fitted with lognormal distribution. Based on
these observations, an analytical model for performance estimation is
also proposed.
Abstract: This study discovers a novel framework of individual
level technology adoption known as I-P (Individual- Privacy) towards
health information application in Smart National Identity Card. Many
countries introduced smart national identity card (SNIC) with various
applications such as health information application embedded inside
it. However, the degree to which citizens accept and use some of the
embedded applications in smart national identity remains unknown to
many governments and application providers as well. Moreover, the
factors of trust, perceived risk, Privacy concern and perceived
credibility need to be incorporated into more comprehensive models
such as extended Unified Theory of Acceptance and Use of
Technology known as UTAUT2. UTAUT2 is a mainly widespread
and leading theory up to now. This research identifies factors
affecting the citizens’ behavioural intention to use health information
application embedded in SNIC and extends better understanding on
the relevant factors that the government and the application providers
would need to consider in predicting citizens’ new technology
acceptance in the future. We propose a conceptual framework by
combining the UTAUT2 and Privacy Calculus Model constructs and
also adding perceived credibility as a new variable. The proposed
framework may provide assistance to any government planning,
decision, and policy makers involving e-government projects.
Empirical study may be conducted in the future to provide proof and
empirically validate this I-P framework.
Abstract: Fuzzy systems have been successfully used for
exchange rate forecasting. However, fuzzy system is very confusing
and complex to be designed by an expert, as there is a large set of
parameters (fuzzy knowledge base) that must be selected, it is not a
simple task to select the appropriate fuzzy knowledge base for an
exchange rate forecasting. The researchers often look the effect of
fuzzy knowledge base on the performances of fuzzy system
forecasting. This paper proposes a genetic fuzzy predictor to forecast
the future value of daily US Dollar/Euro exchange rate time’s series.
A range of methodologies based on a set of fuzzy predictor’s which
allow the forecasting of the same time series, but with a different
fuzzy partition. Each fuzzy predictor is built from two stages, where
each stage is performed by a real genetic algorithm.
Abstract: A relationship between face and signature biometrics
is established in this paper. A new approach is developed to predict
faces from signatures by using artificial intelligence. A multilayer
perceptron (MLP) neural network is used to generate face details
from features extracted from signatures, here face is the physical
biometric and signatures is the behavioural biometric. The new
method establishes a relationship between the two biometrics and
regenerates a visible face image from the signature features.
Furthermore, the performance efficiencies of our new technique are
demonstrated in terms of minimum error rates compared to published
work.
Abstract: Characterization of the engineering behavior of
unsaturated soil is dependent on the soil-water characteristic curve
(SWCC), a graphical representation of the relationship between water
content or degree of saturation and soil suction. A reasonable
description of the SWCC is thus important for the accurate prediction
of unsaturated soil parameters. The measurement procedures for
determining the SWCC, however, are difficult, expensive, and timeconsuming.
During the past few decades, researchers have laid a
major focus on developing empirical equations for predicting the
SWCC, with a large number of empirical models suggested. One of
the most crucial questions is how precisely existing equations can
represent the SWCC. As different models have different ranges of
capability, it is essential to evaluate the precision of the SWCC
models used for each particular soil type for better SWCC estimation.
It is expected that better estimation of SWCC would be achieved via
a thorough statistical analysis of its distribution within a particular
soil class. With this in view, a statistical analysis was conducted in
order to evaluate the reliability of the SWCC prediction models
against laboratory measurement. Optimization techniques were used
to obtain the best-fit of the model parameters in four forms of SWCC
equation, using laboratory data for relatively coarse-textured (i.e.,
sandy) soil. The four most prominent SWCCs were evaluated and
computed for each sample. The result shows that the Brooks and
Corey model is the most consistent in describing the SWCC for sand
soil type. The Brooks and Corey model prediction also exhibit
compatibility with samples ranging from low to high soil water
content in which subjected to the samples that evaluated in this study.
Abstract: In this paper, we present a comparative assessment of
Space Vector Pulse Width Modulation (SVPWM) and Model
Predictive Control (MPC) for two-level three phase (2L-3P) Voltage
Source Inverter (VSI). VSI with associated system is subjected to
both control techniques and the results are compared.
Matlab/Simulink was used to model, simulate and validate the
control schemes. Findings of this study show that MPC is superior to
SVPWM in terms of total harmonic distortion (THD) and
implementation.
Abstract: This study aimed at investigating whether the
functional brain networks constructed using the initial EEG (obtained
when patients first visited hospital) can be correlated with the
progression of cognitive decline calculated as the changes of
mini-mental state examination (MMSE) scores between the latest and
initial examinations. We integrated the time–frequency cross mutual
information (TFCMI) method to estimate the EEG functional
connectivity between cortical regions, and the network analysis based
on graph theory to investigate the organization of functional networks
in aMCI. Our finding suggested that higher integrated functional
network with sufficient connection strengths, dense connection
between local regions, and high network efficiency in processing
information at the initial stage may result in a better prognosis of the
subsequent cognitive functions for aMCI. In conclusion, the functional
connectivity can be a useful biomarker to assist in prediction of
cognitive declines in aMCI.
Abstract: The effect of trucks on the level of service is
determined by considering passenger car equivalents (PCE) of trucks.
The current version of Highway Capacity Manual (HCM) uses a
single PCE value for all tucks combined. However, the composition
of truck traffic varies from location to location; therefore, a single
PCE value for all trucks may not correctly represent the impact of
truck traffic at specific locations. Consequently, present study
developed separate PCE values for single-unit and combination
trucks to replace the single value provided in the HCM on different
freeways. Site specific PCE values, were developed using concept of
spatial lagging headways (that is the distance between rear bumpers
of two vehicles in a traffic stream) measured from field traffic data.
The study used data from four locations on a single urban freeway
and three different rural freeways in Indiana. Three-stage-leastsquares
(3SLS) regression techniques were used to generate models
that predicted lagging headways for passenger cars, single unit trucks
(SUT), and combination trucks (CT). The estimated PCE values for
single-unit and combination truck for basic urban freeways (level
terrain) were: 1.35 and 1.60, respectively. For rural freeways the
estimated PCE values for single-unit and combination truck were:
1.30 and 1.45, respectively. As expected, traffic variables such as
vehicle flow rates and speed have significant impacts on vehicle
headways. Study results revealed that the use of separate PCE values
for different truck classes can have significant influence on the LOS
estimation.
Abstract: OEE has been used in many industries as measure of
performance. However due to limitations of original OEE, it has been
modified by various researchers. OEE for mining application is
special version of classic equation, carries these limitation over. In
this paper it has been aimed to modify the OEE for mining
application by introducing the weights to the elements of it and
termed as Mine Production index (MPi). As a special application of
new index MPishovel has been developed by authors. This can be used
for evaluating the shovel effectiveness. Based on analysis, utilization
followed by performance and availability were ranked in this order.
To check the applicability of this index, a case study was done on
four electrical and one hydraulic shovel in a Swedish mine. The
results shows that MPishovel can evaluate production effectiveness of
shovels and can determine effectiveness values in optimistic view
compared to OEE. MPi with calculation not only give the
effectiveness but also can predict which elements should be focused
for improving the productivity.