Abstract: This article presents an alternative collapse capacity
intensity measure in the three elements form which is influenced by
the spectral ordinates at periods longer than that of the first mode
period at near and far source sites. A parameter, denoted by β, is
defined by which the spectral ordinate effects, up to the effective
period (2T1), on the intensity measure are taken into account. The
methodology permits to meet the hazard-levelled target extreme
event in the probabilistic and deterministic forms. A MATLAB code
is developed involving OpenSees to calculate the collapse capacities
of the 8 archetype RC structures having 2 to 20 stories for regression
process. The incremental dynamic analysis (IDA) method is used to
calculate the structure’s collapse values accounting for the element
stiffness and strength deterioration. The general near field set
presented by FEMA is used in a series of performing nonlinear
analyses. 8 linear relationships are developed for the 8structutres
leading to the correlation coefficient up to 0.93. A collapse capacity
near field prediction equation is developed taking into account the
results of regression processes obtained from the 8 structures. The
proposed prediction equation is validated against a set of actual near
field records leading to a good agreement. Implementation of the
proposed equation to the four archetype RC structures demonstrated
different collapse capacities at near field site compared to those of
FEMA. The reasons of differences are believed to be due to
accounting for the spectral shape effects.
Abstract: In this talk, we introduce a newly developed quantile
function model that can be used for estimating conditional
distributions of financial returns and for obtaining multi-step ahead
out-of-sample predictive distributions of financial returns. Since we
forecast the whole conditional distributions, any predictive quantity
of interest about the future financial returns can be obtained simply
as a by-product of the method. We also show an application of the
model to the daily closing prices of Dow Jones Industrial Average
(DJIA) series over the period from 2 January 2004 - 8 October 2010.
We obtained the predictive distributions up to 15 days ahead for
the DJIA returns, which were further compared with the actually
observed returns and those predicted from an AR-GARCH model.
The results show that the new model can capture the main features
of financial returns and provide a better fitted model together with
improved mean forecasts compared with conventional methods. We
hope this talk will help audience to see that this new model has the
potential to be very useful in practice.
Abstract: The knitted fabric suffers a deformation in its
dimensions due to stretching and tension factors, transverse and
longitudinal respectively, during the process in rectilinear knitting
machines so it performs a dry relaxation shrinkage procedure and
thermal action of prefixed to obtain stable conditions in the knitting.
This paper presents a dry relaxation shrinkage prediction of Bordeaux
fiber using a feed forward neural network and linear regression
models. Six operational alternatives of shrinkage were predicted. A
comparison of the results was performed finding neural network
models with higher levels of explanation of the variability and
prediction. The presence of different reposes is included. The models
were obtained through a neural toolbox of Matlab and Minitab
software with real data in a knitting company of Southern
Guanajuato. The results allow predicting dry relaxation shrinkage of
each alternative operation.
Abstract: This paper aims to determine Fundamental Natural
Frequency (FNF) of a structural composite floor system known as
Chromite. To achieve this purpose, FNFs of studied panels are
determined by development of Finite Element Models (FEMs) in
ABAQUS program. American Institute of Steel Construction (AISC)
code in Steel Design Guide Series 11 presents a fundamental formula
to calculate FNF of a steel framed floor system. This formula has
been used to verify results of the FEMs. The variability in the FNF of
the studied system under various parameters such as dimensions of
floor, boundary conditions, rigidity of main and secondary beams
around the floor, thickness of concrete slab, height of composite
joists, distance between composite joists, thickness of top and bottom
flanges of the open web steel joists, and adding tie beam
perpendicular on the composite joists, is determined. The results
show that changing in dimensions of the system, its boundary
conditions, rigidity of main beam, and also adding tie beam,
significant changes the FNF of the system up to 452.9%, 50.8%, -
52.2%, %52.6%, respectively. In addition, increasing thickness of
concrete slab increases the FNF of the system up to 10.8%.
Furthermore, the results demonstrate that variation in rigidity of
secondary beam, height of composite joist, and distance between
composite joists, and thickness of top and bottom flanges of open
web steel joists insignificant changes the FNF of the studied system
up to -0.02%, -3%, -6.1%, and 0.96%, respectively. Finally, the
results of this study help designer predict occurrence of resonance,
comfortableness, and design criteria of the studied system.
Abstract: The work reported through this paper is an
experimental work conducted on High Performance Concrete (HPC)
with super plasticizer with the aim to develop some models suitable
for prediction of compressive strength of HPC mixes. In this study,
the effect of varying proportions of fly ash (0% to 50% @ 10%
increment) on compressive strength of high performance concrete has
been evaluated. The mix designs studied were M30, M40 and M50 to
compare the effect of fly ash addition on the properties of these
concrete mixes. In all eighteen concrete mixes that have been
designed, three were conventional concretes for three grades under
discussion and fifteen were HPC with fly ash with varying
percentages of fly ash. The concrete mix designing has been done in
accordance with Indian standard recommended guidelines. All the
concrete mixes have been studied in terms of compressive strength at
7 days, 28 days, 90 days, and 365 days. All the materials used have
been kept same throughout the study to get a perfect comparison of
values of results. The models for compressive strength prediction
have been developed using Linear Regression method (LR), Artificial
Neural Network (ANN) and Leave-One-Out Validation (LOOV)
methods.
Abstract: Different countries have introduced different schemes
and policies to counter global warming. The rationale behind the
proposed policies and the potential barriers to successful
implementation of the policies adopted by the countries were
analyzed and estimated based on different models. It is argued that
these models enhance the transparency and provide a better
understanding to the policy makers. However, these models are
underpinned with several structural and baseline assumptions. These
assumptions, modeling features and future prediction of emission
reductions and other implication such as cost and benefits of a
transition to a low-carbon economy and its economy wide impacts
were discussed. On the other hand, there are potential barriers in the
form political, financial, and cultural and many others that pose a
threat to the mitigation options.
Abstract: Predicting earnings management is vital for the capital
market participants, financial analysts and managers. The aim of this
research is attempting to respond to this query: Is there a significant
difference between the regression model and neural networks’
models in predicting earnings management, and which one leads to a
superior prediction of it? In approaching this question, a Linear
Regression (LR) model was compared with two neural networks
including Multi-Layer Perceptron (MLP), and Generalized
Regression Neural Network (GRNN). The population of this study
includes 94 listed companies in Tehran Stock Exchange (TSE)
market from 2003 to 2011. After the results of all models were
acquired, ANOVA was exerted to test the hypotheses. In general, the
summary of statistical results showed that the precision of GRNN did
not exhibit a significant difference in comparison with MLP. In
addition, the mean square error of the MLP and GRNN showed a
significant difference with the multi variable LR model. These
findings support the notion of nonlinear behavior of the earnings
management. Therefore, it is more appropriate for capital market
participants to analyze earnings management based upon neural
networks techniques, and not to adopt linear regression models.
Abstract: The paper aims to evaluate the effect of online
advertising on consumer purchase behavior in Malaysian
organizations. The paper has potential to extend and refine theory. A
survey was distributed among Students of UTM university during the
winter 2014 and 160 responses were collected. Regression analysis
was used to test the hypothesized relationships of the model. Result
shows that the predictors (cost saving factor, convenience factor and
customized product or services) have positive impact on intention to
continue seeking online advertising.
Abstract: This work explores the inter-region investment
behaviors of Integrated Circuit (IC) design industry from Taiwan to
China using the amount of foreign direct investment (FDI). According
to the mutual dependence among different IC design industrial
locations, Lotka-Volterra model is utilized to explore the FDI
interactions between South and East China. Effects of inter-regional
collaborations on FDI flows into China are considered. The analysis
results show that FDIs into South China for IC design industry
significantly inspire the subsequent FDIs into East China, while FDIs
into East China for Taiwan’s IC design industry significantly hinder
the subsequent FDIs into South China. Because the supply chain along
IC industry includes upstream IC design, midstream manufacturing, as
well as downstream packing and testing enterprises, IC design industry
has to cooperate with IC manufacturing, packaging and testing
industries in the same area to form a strong IC industrial cluster.
Taiwan’s IC design industry implement the largest FDI amount into
East China and the second largest FDI amount into South China
among the four regions: North, East, Mid-West and South China. If IC
design houses undertake more FDIs in South China, those in East
China are urged to incrementally implement more FDIs into East
China to maintain the competitive advantages of the IC supply chain in
East China. On the other hand, as the FDIs in East China rise, the FDIs
in South China will successively decline since capitals have
concentrated in East China. In addition, this investigation proves that
the prediction of Lotka-Volterra model in FDI trends is accurate
because the industrial interactions between the two regions are
included. Finally, this work confirms that the FDI flows cannot reach a
stable equilibrium point, so the FDI inflows into East and South China
will expand in the future.
Abstract: Chatter vibrations and process instabilities are the
most important factors limiting the productivity of the milling
process. Chatter can leads to damage of the tool, the part or the
machine tool. Therefore, the estimation and prediction of the process
stability is very important. The process stability depends on the
spindle speed, the depth of cut and the width of cut. In milling, the
process conditions are defined in the NC-program. While the spindle
speed is directly coded in the NC-program, the depth and width of cut
are unknown. This paper presents a new simulation based approach
for the prediction of the depth and width of cut of a milling process.
The prediction is based on a material removal simulation with an
analytically represented tool shape and a multi-dexel approach for the
workpiece. The new calculation method allows the direct estimation
of the depth and width of cut, which are the influencing parameters of
the process stability, instead of the removed volume as existing
approaches do. The knowledge can be used to predict the stability of
new, unknown parts. Moreover with an additional vibration sensor,
the stability lobe diagram of a milling process can be estimated and
improved based on the estimated depth and width of cut.
Abstract: This paper presents the results of a Finite Element
based vibration analysis of a solar powered Unmanned Aerial
Vehicle (UAV). The purpose of this paper was to quantify the free
vibration, forced vibration response due to differing point inputs in
order to predict the relative response magnitudes and frequencies at
various wing locations of vibration induced power generators
(magnet in coil) excited by gust and/or control surface pulse-decays
used to help power the flight of the electric UAV. A Fluid Structure
Interaction (FSI) study was performed in order to ascertain pertinent
design stresses and deflections as well as aerodynamic parameters of
the UAV airfoil. The 10 ft span airfoil is modeled using Mylar as the
primary material. Results show that the free mode in bending is 4.8
Hz while the first forced bending mode is on range of 16.2 to 16.7 Hz
depending on the location of excitation. The free torsional bending
mode is 28.3 Hz, and the first forced torsional mode is range of 26.4
to 27.8 Hz, depending on the location of excitation. The FSI results
predict the coefficients of aerodynamic drag and lift of 0.0052 and
0.077, respectively, which matches hand-calculations used to validate
the Finite Element based results. FSI based maximum von Mises
stresses and deflections were found to be 0.282 MPa and 3.4 mm,
respectively. Dynamic pressures on the airfoil range from 1.04 to
1.23 kPa corresponding to velocity magnitudes in range of 22 to 66
m/s.
Abstract: During welding or flame cutting of metals, the
prediction of heat affected zone (HAZ) is critical. There is need to
develop a simple mathematical model to calculate the temperature
variation in HAZ and derivative analysis can be used for this purpose.
This study presents analytical solution for heat transfer through
conduction in mild steel plate. The homogeneous and nonhomogeneous
boundary conditions are single variables. The full field
analytical solutions of temperature measurement, subjected to local
heating source, are derived first by method of separation of variables
followed with the experimental visualization using infrared imaging.
Based on the present work, it is suggested that appropriate heat input
characteristics controls the temperature distribution in and around
HAZ.
Abstract: The purpose of this paper is to examine the effects and
relationship of stress and social support towards the quality of life
among flood victims in Malaysia. A total of 764 respondents took
part in the survey via convenience sampling. The Depression,
Anxiety and Stress scale (DASS) was utilized to measure stress while
The Multidimensional Scale of Perceived Social Support was used to
measure social support. To measure quality of life, the combination
of WHO Quality of Life – BREF (WHOQOL-BREF) and The Impact
of Event Scale – Revised (IES-R) were utilized. The findings of this
study indicate that there were significant correlations between
variables in the study. The findings showed a significant negative
relation between stress and quality of life; and significant positive
correlations between support from family as well as support from
friends with quality of life. Stress and support from family were
found to be significant predictors that influence the quality of life
among flood victims.
Abstract: Due to the interference effects, the intrinsic
aerodynamic parameters obtained from the individual component
testing are always fundamentally different than those obtained for
complete model testing. Consideration and limitation for such testing
need to be taken into account in any design work related to the
component buildup method. In this paper, the scaled model of a
straight rectangular canard of a hybrid buoyant aircraft is tested at 50
m/s in IIUM-LSWT (Low Speed Wind Tunnel). Model and its
attachment with the balance are kept rigid to have results free from
the aeroelastic distortion. Based on the velocity profile of the test
section’s floor; the height of the model is kept equal to the
corresponding boundary layer displacement. Balance measurements
provide valuable but limited information of overall aerodynamic
behavior of the model. Zero lift coefficient is obtained at -2.2o and
the corresponding drag coefficient was found to be less than that at
zero angle of attack. As a part of the validation of low fidelity tool,
plot of lift coefficient plot was verified by the experimental data and
except the value of zero lift coefficients, the overall trend has under
predicted the lift coefficient. Based on this comparative study, a
correction factor of 1.36 is proposed for lift curve slope obtained
from the panel method.
Abstract: The purpose of this research was to investigate the
creep behaviour of the heterogeneous Timber-UHPFRC beams. New
developments have been done to further improve the structural
performance, such as strengthening of the timber (glulam) beam by
bonding composite material combine with an ultra-high performance
fibre reinforced concrete (UHPFRC) internally reinforced with or
without carbon fibre reinforced polymer (CFRP) bars. However, in
the design of wooden structures, in addition to the criteria of
strengthening and stiffness, deformability due to the creep of wood,
especially in horizontal elements, is also a design criterion. Glulam,
UHPFRC and CFRP may be an interesting composite mix to respond
to the issue of creep behaviour of composite structures made of
different materials with different rheological properties. In this paper,
we describe an experimental and analytical investigation of the creep
performance of the glulam-UHPFRC-CFRP beams assembled by
bonding. The experimental investigations creep behaviour was
conducted for different environments: in- and outside under constant
loading for approximately a year. The measured results are compared
with numerical ones obtained by an analytical model. This model was
developed to predict the creep response of the glulam-UHPFRCCFRP
beams based on the creep characteristics of the individual
components. The results show that heterogeneous glulam-UHPFRC
beams provide an improvement in both the strengthening and
stiffness, and can also effectively reduce the creep deflection of
wooden beams.
Abstract: Healthcare safety has been perceived important. It is
essential to prevent troubles in healthcare processes for healthcare
safety. Trouble prevention is based on trouble prediction using
accumulated knowledge on processes, troubles, and countermeasures.
However, information on troubles has not been accumulated in
hospitals in the appropriate structure, and it has not been utilized
effectively to prevent troubles. In the previous study, however a
detailed knowledge acquisition process for trouble prediction was
proposed, the knowledgebase for countermeasures was not involved.
In this paper, we aim to propose the structure of the knowledgebase for
countermeasures, in the knowledge acquisition process for trouble
prediction in healthcare process. We first design the structure of
countermeasures and propose the knowledge representation form on
countermeasures. Then, we evaluate the validity of the proposal, by
applying it into an actual hospital.
Abstract: The current study aims to highlight the loading
characteristics impact on the time evolution (focusing particularly on
long term effects) of the deformation of realized reinforced concrete
beams. Namely the tension stiffening code provisions (i.e. within
Eurocode 2) are reviewed with a clear intention to reassess their
operational value and predicting capacity. In what follows the
experimental programme adopted along with some preliminary
findings and numerical modeling attempts are presented. For a range of long slender reinforced concrete simply supported
beams (4200 mm) constant static sustained and repeated cyclic
loadings were applied mapping the time evolution of deformation.
All experiments were carried out at the Heavy Structures Lab of the
University of Leeds. During tests the mid-span deflection, creep
coefficient and shrinkage strains were monitored for duration of 90
days. The obtained results are set against the values predicted by
Eurocode 2 and the tools within an FE commercial package (i.e.
Midas FEA) to yield that existing knowledge and practise is at times
over-conservative.
Abstract: Tamil handwritten document is taken as a key source
of data to identify the writer. Tamil is a classical language which has
247 characters include compound characters, consonants, vowels and
special character. Most characters of Tamil are multifaceted in
nature. Handwriting is a unique feature of an individual. Writer may
change their handwritings according to their frame of mind and this
place a risky challenge in identifying the writer. A new
discriminative model with pooled features of handwriting is proposed
and implemented using support vector machine. It has been reported
on 100% of prediction accuracy by RBF and polynomial kernel based
classification model.
Abstract: When high strength reinforced concrete is exposed to
high temperature due to a fire, deteriorations occur such as loss in
strength and elastic modulus, cracking and spalling of the concrete.
Therefore, it is important to understand risk of structural safety in
building structures by studying structural behaviors and rehabilitation
of fire damaged high strength concrete structures. This paper aims at
investigating rehabilitation effect on fire damaged high strength
concrete beams using experimental and analytical methods. In the
experiments, flexural specimens with high strength concrete are
exposed to high temperatures according to ISO 834 standard time
temperature curve. From four-point loading test, results show that
maximum loads of the rehabilitated beams are similar to or higher than
those of the non-fire damaged RC beam. In addition, structural
analyses are performed using ABAQUS 6.10-3 with same conditions
as experiments to provide accurate predictions on structural and
mechanical behaviors of rehabilitated RC beams. The parameters are
the fire cover thickness and strengths of repairing mortar. Analytical
results show good rehabilitation effects, when the results predicted
from the rehabilitated models are compared to structural behaviors of
the non-damaged RC beams. In this study, fire damaged high strength concrete beams are
rehabilitated using polymeric cement mortar. The predictions from the
finite element (FE) models show good agreements with the
experimental results and the modeling approaches can be used to
investigate applicability of various rehabilitation methods for further
study.
Abstract: Tamil handwritten document is taken as a key source of data to identify the writer. Tamil is a classical language which has 247 characters include compound characters, consonants, vowels and special character. Most characters of Tamil are multifaceted in nature. Handwriting is a unique feature of an individual. Writer may change their handwritings according to their frame of mind and this place a risky challenge in identifying the writer. A new discriminative model with pooled features of handwriting is proposed and implemented using support vector machine. It has been reported on 100% of prediction accuracy by RBF and polynomial kernel based classification model.