Abstract: The present paper attempts to investigate the
prediction of air entrainment rate and aeration efficiency of a free
overfall jets issuing from a triangular sharp crested weir by using
regression based modelling. The empirical equations, Support vector
machine (polynomial and radial basis function) models and the linear
regression techniques were applied on the triangular sharp crested
weirs relating the air entrainment rate and the aeration efficiency to
the input parameters namely drop height, discharge, and vertex angle.
It was observed that there exists a good agreement between the
measured values and the values obtained using empirical equations,
Support vector machine (Polynomial and rbf) models and the linear
regression techniques. The test results demonstrated that the SVM
based (Poly & rbf) model also provided acceptable prediction of the
measured values with reasonable accuracy along with empirical
equations and linear regression techniques in modelling the air
entrainment rate and the aeration efficiency of a free overfall jets
issuing from triangular sharp crested weir. Further sensitivity analysis
has also been performed to study the impact of input parameter on the
output in terms of air entrainment rate and aeration efficiency.
Abstract: In this study, an Artificial Neural Network (ANN)
analytical method has been developed for analyzing earthquake
performances of the Reinforced Concrete (RC) buildings. 66 RC
buildings with four to ten storeys were subjected to performance
analysis according to the parameters which are the existing material,
loading and geometrical characteristics of the buildings. The selected
parameters have been thought to be effective on the performance of
RC buildings. In the performance analyses stage of the study, level of
performance possible to be shown by these buildings in case of an
earthquake was determined on the basis of the 4-grade performance
levels specified in Turkish Earthquake Code-2007 (TEC-2007). After
obtaining the 4-grade performance level, selected 23 parameters of
each building have been matched with the performance level. In this
stage, ANN-based fast evaluation algorithm mentioned above made
an economic and rapid evaluation of four to ten storey RC buildings.
According to the study, the prediction accuracy of ANN has been
found about 74%.
Abstract: This paper presents a study on the effect of
second-order slip and jump on forced convection through a long
isothermally heated or cooled planar microchannel. The fully
developed solutions of thermal flow fields are analytically obtained on
the basis of the second-order Maxwell-Burnett slip and Smoluchowski
jump boundary conditions. Results reveal that the second-order term in
the Karniadakis slip boundary condition is found to contribute a
negative velocity slip and then to lead to a higher pressure drop as well
as a higher fluid temperature for the heated-wall case or to a lower
fluid temperature for the cooled-wall case. These findings are contrary
to predictions made by the Deissler model. In addition, the role of
second-order slip becomes more significant when the Knudsen
number increases.
Abstract: In this work, the plastic behaviour of cold-rolled zinc
coated dual-phase steel sheets DP600 and DP800 grades is firstly
investigated with the help of uniaxial, hydraulic bulge and Forming
Limit Curve (FLC) tests. The uniaxial tensile tests were performed in
three angular orientations with respect to the rolling direction to
evaluate the strain-hardening and plastic anisotropy. True stressstrain
curves at large strains were determined from hydraulic bulge
testing and fitted to a work-hardening equation. The limit strains are
defined at both localized necking and fracture conditions according to
Nakajima’s hemispherical punch procedure. Also, an elasto-plastic
localization model is proposed in order to predict strain and stress
based forming limit curves. The investigated dual-phase sheets
showed a good formability in the biaxial stretching and drawing FLC
regions. For both DP600 and DP800 sheets, the corresponding
numerical predictions overestimated and underestimated the
experimental limit strains in the biaxial stretching and drawing FLC
regions, respectively. This can be attributed to the restricted failure
necking condition adopted in the numerical model, which is not
suitable to describe the tensile and shear fracture mechanisms in
advanced high strength steels under equibiaxial and biaxial stretching
conditions.
Abstract: The Multiple Intelligences theory characterizes human
intelligence as a multifaceted entity that exists in all human beings
with varying degrees. The most important contribution of this theory
to the field of English Language Teaching (ELT) is its role in
identifying individual differences and designing more learnercentered
programs. The present study aims at investigating the
relationship between different elements of multiple intelligence and
grammar scores. To this end, 63 female Iranian EFL learner selected
from among intermediate students participated in the study. The
instruments employed were a Nelson English language test, Michigan
Grammar Test, and Teele Inventory for Multiple Intelligences
(TIMI). The results of Pearson Product-Moment Correlation revealed
a significant positive correlation between grammatical accuracy and
linguistic as well as interpersonal intelligence. The results of
Stepwise Multiple Regression indicated that linguistic intelligence
contributed to the prediction of grammatical accuracy.
Abstract: Useful lifetime evaluation of chevron rubber spring
was very important in design procedure to assure the safety and
reliability. It is, therefore, necessary to establish a suitable criterion
for the replacement period of chevron rubber spring. In this study, we
performed characteristic analysis and useful lifetime prediction of
chevron rubber spring. Rubber material coefficient was obtained by
curve fittings of uniaxial tension equibiaxial tension and pure shear
test. Computer simulation was executed to predict and evaluate the
load capacity and stiffness for chevron rubber spring. In order to
useful lifetime prediction of rubber material, we carried out the
compression set with heat aging test in an oven at the temperature
ranging from 50°C to 100°C during a period 180 days. By using the
Arrhenius plot, several useful lifetime prediction equations for rubber
material was proposed.
Abstract: High frequency automotive interior noise above 500
Hz considerably affects automotive passenger comfort. To reduce this
noise, sound insulation material is often laminated on body panels or
interior trim panels. For a more effective noise reduction, the sound
reduction properties of this laminated structure need to be estimated.
We have developed a new calculate tool that can roughly calculate the
sound absorption and insulation properties of laminate structure and
handy for designers. In this report, the outline of this tool and an
analysis example applied to floor mat are introduced.
Abstract: This paper presents a methodology for probabilistic
assessment of bearing capacity and prediction of failure mechanism
of masonry vaults at the ultimate state with consideration of the
natural variability of Young’s modulus of stones. First, the
computation model is explained. The failure mode corresponds to the
four-hinge mechanism. Based on this consideration, the study of a
vault composed of 16 segments is presented. The Young’s modulus of
the segments is considered as random variable defined by a mean
value and a coefficient of variation. A relationship linking the vault
bearing capacity to the voussoirs modulus variation is proposed. The
most probable failure mechanisms, in addition to that observed in the
deterministic case, are identified for each variability level as well as
their probability of occurrence. The results show that the mechanism
observed in the deterministic case has decreasing probability of
occurrence in terms of variability, while the number of other
mechanisms and their probability of occurrence increases with the
coefficient of variation of Young’s modulus. This means that if a
significant change in the Young’s modulus of the segments is proven,
taking it into account in computations becomes mandatory, both for
determining the vault bearing capacity and for predicting its failure
mechanism.
Abstract: DNA analysis has been widely accepted as providing
valuable evidence concerning the identity of the source of biological
traces. Our work has showed that DNA samples can survive on
cartridges even after firing. The study also raised the possibility of
determining other information such as the age of the donor. Such
information may be invaluable in certain cases where spent cartridges
from automatic weapons are left behind at the scene of a crime. In
spite of the nature of touch evidence and exposure to high chamber
temperatures during shooting, we were still capable to retrieve
enough DNA for profile typing. In order to estimate age of
contributor, DNA methylation levels were analyzed using EpiTect
system for retrieved DNA. However, results were not conclusive, due
to low amount of input DNA.
Abstract: Geographical routing protocol requires node physical
location information to make forwarding decision. Geographical
routing uses location service or position service to obtain the position
of a node. The geographical information is a geographic coordinates
or can be obtained through reference points on some fixed coordinate
system. Link can be formed between two nodes. Link lifetime plays a
crucial role in MANET. Link lifetime represent how long the link is
stable without any failure between the nodes. Link failure may occur
due to mobility and because of link failure energy of nodes can be
drained. Thus this paper proposes survey about link lifetime
prediction using geographical information.
Abstract: Drying is a phenomenon that accompanies the
hardening of hydraulic materials. This study is concerned the
modelling of drying shrinkage of the hydraulic materials and the
prediction of the rate of spontaneous deformations of hydraulic
materials during hardening. The model developed takes consideration
of the main factors affecting drying shrinkage. There was agreement
between drying shrinkage predicted by the developed model and
experimental results. In last we show that developed model describe
the evolution of the drying shrinkage of high performances concretes
correctly.
Abstract: Particle size distribution, the most important
characteristics of aerosols, is obtained through electrical
characterization techniques. The dynamics of charged nanoparticles
under the influence of electric field in Electrical Mobility
Spectrometer (EMS) reveals the size distribution of these particles.
The accuracy of this measurement is influenced by flow conditions,
geometry, electric field and particle charging process, therefore by
the transfer function (transfer matrix) of the instrument. In this work,
a wire-cylinder corona charger was designed and the combined fielddiffusion
charging process of injected poly-disperse aerosol particles
was numerically simulated as a prerequisite for the study of a
multichannel EMS. The result, a cloud of particles with no uniform
charge distribution, was introduced to the EMS. The flow pattern and
electric field in the EMS were simulated using Computational Fluid
Dynamics (CFD) to obtain particle trajectories in the device and
therefore to calculate the reported signal by each electrometer.
According to the output signals (resulted from bombardment of
particles and transferring their charges as currents), we proposed a
modification to the size of detecting rings (which are connected to
electrometers) in order to evaluate particle size distributions more
accurately. Based on the capability of the system to transfer
information contents about size distribution of the injected particles,
we proposed a benchmark for the assessment of optimality of the
design. This method applies the concept of Von Neumann entropy
and borrows the definition of entropy from information theory
(Shannon entropy) to measure optimality. Entropy, according to the
Shannon entropy, is the ''average amount of information contained in
an event, sample or character extracted from a data stream''.
Evaluating the responses (signals) which were obtained via various
configurations of detecting rings, the best configuration which gave
the best predictions about the size distributions of injected particles,
was the modified configuration. It was also the one that had the
maximum amount of entropy. A reasonable consistency was also
observed between the accuracy of the predictions and the entropy
content of each configuration. In this method, entropy is extracted
from the transfer matrix of the instrument for each configuration.
Ultimately, various clouds of particles were introduced to the
simulations and predicted size distributions were compared to the
exact size distributions.
Abstract: Voting algorithms are extensively used to make
decisions in fault tolerant systems where each redundant module
gives inconsistent outputs. Popular voting algorithms include
majority voting, weighted voting, and inexact majority voters. Each
of these techniques suffers from scenarios where agreements do not
exist for the given voter inputs. This has been successfully overcome
in literature using fuzzy theory. Our previous work concentrated on a
neuro-fuzzy algorithm where training using the neuro system
substantially improved the prediction result of the voting system.
Weight training of Neural Network is sub-optimal. This study
proposes to optimize the weights of the Neural Network using
Artificial Bee Colony algorithm. Experimental results show the
proposed system improves the decision making of the voting
algorithms.
Abstract: Human beings have the ability to make logical
decisions. Although human decision - making is often optimal, it is
insufficient when huge amount of data is to be classified. Medical
dataset is a vital ingredient used in predicting patient’s health
condition. In other to have the best prediction, there calls for most
suitable machine learning algorithms. This work compared the
performance of Artificial Neural Network (ANN) and Decision Tree
Algorithms (DTA) as regards to some performance metrics using
diabetes data. WEKA software was used for the implementation of
the algorithms. Multilayer Perceptron (MLP) and Radial Basis
Function (RBF) were the two algorithms used for ANN, while
RegTree and LADTree algorithms were the DTA models used. From
the results obtained, DTA performed better than ANN. The Root
Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is
0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206
respectively.
Abstract: This study utilizes a frequency domain approach over
the period of 1996 to 2013 to examine the causal relationship between
governance and economic growth in ten Asian countries, which have
different levels of democracy; classified as “Free”, “Partly Free”, and
“Not Free” countries. The empirical results show that there is no
Granger causality running from governance to economic growth in
“Not Free” countries and “Partly Free” countries with the exception of
Singapore. As for “Free” countries such as South Korea and Taiwan,
there is a one-way causality running from governance to economic
growth. The findings of this study indicate that policy makers in South
Korea, Taiwan, and Singapore could use governance index to improve
their predictions of the future economic growth.
Abstract: Numerical investigations were conducted to study the
influence of flexural reinforcement ratio on the diagonal cracking
strength and ultimate shear strength of reinforced concrete (RC)
beams without stirrups. Three-dimensional nonlinear finite element
analyses (FEAs) of the beams with flexural reinforcement ratios
ranging from 0.58% to 2.20% subjected to a mid-span concentrated
load were carried out. It is observed that the load-deflection and loadstrain
curves obtained from the numerical analyses agree with those
obtained from the experiments. It is concluded that flexural
reinforcement ratio has a significant effect on the shear strength and
deflection capacity of RC beams without stirrups. The predictions of
diagonal cracking strength and ultimate shear strength of beams
obtained by using the equations defined by a number of codes and
researchers are compared with each other and with the experimental
values.
Abstract: Accurate forecasting of fresh produce demand is one
the challenges faced by Small Medium Enterprise (SME)
wholesalers. This paper is an attempt to understand the cause for the
high level of variability such as weather, holidays etc., in demand of
SME wholesalers. Therefore, understanding the significance of
unidentified factors may improve the forecasting accuracy. This
paper presents the current literature on the factors used to predict
demand and the existing forecasting techniques of short shelf life
products. It then investigates a variety of internal and external
possible factors, some of which is not used by other researchers in the
demand prediction process. The results presented in this paper are
further analysed using a number of techniques to minimize noise in
the data. For the analysis past sales data (January 2009 to May 2014)
from a UK based SME wholesaler is used and the results presented
are limited to product ‘Milk’ focused on café’s in derby. The
correlation analysis is done to check the dependencies of variability
factor on the actual demand. Further PCA analysis is done to
understand the significance of factors identified using correlation.
The PCA results suggest that the cloud cover, weather summary and
temperature are the most significant factors that can be used in
forecasting the demand. The correlation of the above three factors
increased relative to monthly and becomes more stable compared to
the weekly and daily demand.
Abstract: Several parameters are established in order to measure
biodiesel quality. One of them is the iodine value, which is an
important parameter that measures the total unsaturation within a
mixture of fatty acids. Limitation of unsaturated fatty acids is
necessary since warming of higher quantity of these ones ends in
either formation of deposits inside the motor or damage of lubricant.
Determination of iodine value by official procedure tends to be very
laborious, with high costs and toxicity of the reagents, this study uses
artificial neural network (ANN) in order to predict the iodine value
property as an alternative to these problems. The methodology of
development of networks used 13 esters of fatty acids in the input
with convergence algorithms of back propagation of back
propagation type were optimized in order to get an architecture of
prediction of iodine value. This study allowed us to demonstrate the
neural networks’ ability to learn the correlation between biodiesel
quality properties, in this caseiodine value, and the molecular
structures that make it up. The model developed in the study reached
a correlation coefficient (R) of 0.99 for both network validation and
network simulation, with Levenberg-Maquardt algorithm.
Abstract: This paper presents a rheological model for producing
shape-memory thermoplastic polymers. Shape-memory occurs as a
result of internal rearrangement of the structural elements of a
polymer. A non-linear viscoelastic model was developed that allows
qualitative and quantitative prediction of the stress-strain behavior of
shape-memory polymers during heating. This research was done to
develop a technique to determine the maximum possible change in
size of shape-memory products during heating. The rheological
model used in this work was particularly suitable for defining process
parameters and constructive parameters of the processing equipment.
Abstract: 3-roller conical bending process is widely used in the
industries for manufacturing of conical sections and shells. It
involves static as well dynamic bending stages. Analytical models for
prediction of bending force during static as well as dynamic bending
stage are available in the literature. In this paper bending forces
required for static bending stage and dynamic bending stages have
been compared using the analytical models. It is concluded that force
required for dynamic bending is very less as compared to the bending
force required during the static bending stage.