Abstract: In this paper, the effect of bolt clamping force on the fatigue behavior of bolted single lap joints of aluminum alloy 2024- T3 have been studied using numerical finite element method. To do so, a three dimensional model according to the bolted single lap joint has been created and numerical analysis has been carried out using finite element based package. Then the stress distribution and also the slip amplitudes have been calculated in the critical regions and the outcome have been compared with the available experimental fatigue tests results. The numerical results show that in low applied clamping force, the fatigue failure of the specimens occur around the stress concentration location (the bolted hole edge) due to the tensile stresses and thus fatigue crack propagation, but with increase of the clamping force, the fatigue life increases and the cracks nucleate and propagate far from the hole edge because of fretting fatigue. In other words, with the further increase of clamping force value of the joint, the fatigue life reduces due to occurrence of the fretting fatigue in the critical location where the slip amplitude is within its critical occurs earlier.
Abstract: This paper presents the design and implementation of CASTE, a Cloud-based automatic software test environment. We first present the architecture of CASTE, then the main packages and classes of it are described in detail. CASTE is built upon a private Infrastructure as a Service platform. Through concentrated resource management of virtualized testing environment and automatic execution control of test scripts, we get a better solution to the testing resource utilization and test automation problem. Experiments on CASTE give very appealing results.
Abstract: Real-time hand tracking is a challenging task in many
computer vision applications such as gesture recognition. This paper
proposes a robust method for hand tracking in a complex environment
using Mean-shift analysis and Kalman filter in conjunction with 3D
depth map. The depth information solve the overlapping problem
between hands and face, which is obtained by passive stereo measuring
based on cross correlation and the known calibration data of
the cameras. Mean-shift analysis uses the gradient of Bhattacharyya
coefficient as a similarity function to derive the candidate of the hand
that is most similar to a given hand target model. And then, Kalman
filter is used to estimate the position of the hand target. The results
of hand tracking, tested on various video sequences, are robust to
changes in shape as well as partial occlusion.
Abstract: In this paper we present, propose and examine
additional membership functions for the Smoothing Transition
Autoregressive (STAR) models. More specifically, we present the
tangent hyperbolic, Gaussian and Generalized bell functions.
Because Smoothing Transition Autoregressive (STAR) models
follow fuzzy logic approach, more fuzzy membership functions
should be tested. Furthermore, fuzzy rules can be incorporated or
other training or computational methods can be applied as the error
backpropagation or genetic algorithm instead to nonlinear squares.
We examine two macroeconomic variables of US economy, the
inflation rate and the 6-monthly treasury bills interest rates.
Abstract: In this work, we propose a hybrid heuristic in order to
solve the Team Orienteering Problem (TOP). Given a set of points (or
customers), each with associated score (profit or benefit), and a team
that has a fixed number of members, the problem to solve is to visit a
subset of points in order to maximize the total collected score. Each
member performs a tour starting at the start point, visiting distinct
customers and the tour terminates at the arrival point. In addition,
each point is visited at most once, and the total time in each tour
cannot be greater than a given value. The proposed heuristic combines
beam search and a local optimization strategy. The algorithm was
tested on several sets of instances and encouraging results were
obtained.
Abstract: Graph has become increasingly important in modeling
complicated structures and schemaless data such as proteins, chemical
compounds, and XML documents. Given a graph query, it is desirable
to retrieve graphs quickly from a large database via graph-based
indices. Different from the existing methods, our approach, called
VFM (Vertex to Frequent Feature Mapping), makes use of vertices
and decision features as the basic indexing feature. VFM constructs
two mappings between vertices and frequent features to answer graph
queries. The VFM approach not only provides an elegant solution to
the graph indexing problem, but also demonstrates how database
indexing and query processing can benefit from data mining,
especially frequent pattern mining. The results show that the proposed
method not only avoids the enumeration method of getting subgraphs
of query graph, but also effectively reduces the subgraph isomorphism
tests between the query graph and graphs in candidate answer set in
verification stage.
Abstract: In this study concept of experimental design is
successfully applied for the determination of optimum condition to
produce PP/SWCNT (Polypropylene/Single wall carbon nanotube)
nanocomposite. Central composite design as one of experimental
design techniques is employed for the optimization and statistical
determination of the significant factors influencing on the tensile
modulus and yield stress as mechanical properties of this
nanocomposite. The significant factors are SWCNT weight fraction
and acid treatment time for functionalizing the nanoparticles.
Optimum conditions are in 0.7 % of SWCNT weight fraction and 210
min as acid treatment time for 1112.75 ± 28 MPa as maximum tensile
modulus and in 216 min and 0.65 % as acid treatment time and
SWCNT weight fraction respectively for 40.26 ± 0.3 MPa as
maximum yield stress. Also after setting new experiments for test
these optimum conditions, found excelent agreement with predicted
values.
Abstract: In this paper, we propose a supervised method for
color image classification based on a multilevel sigmoidal neural
network (MSNN) model. In this method, images are classified into
five categories, i.e., “Car", “Building", “Mountain", “Farm" and
“Coast". This classification is performed without any segmentation
processes. To verify the learning capabilities of the proposed method,
we compare our MSNN model with the traditional Sigmoidal Neural
Network (SNN) model. Results of comparison have shown that the
MSNN model performs better than the traditional SNN model in the
context of training run time and classification rate. Both color
moments and multi-level wavelets decomposition technique are used
to extract features from images. The proposed method has been
tested on a variety of real and synthetic images.
Abstract: Virtual environment induces simulator sickness effect
for some users. The purpose of this research is to compare the
simulation sickness relative with parallax affect in one-screen and
three-screen HoloStageTM system, measured by Simulation Sickness
Questionnaire (SSQ). The results show the subjects tested in
three-screen has less sickness than one-screen and effect from the
Oculomotor (O) more than from the Disorientation (D) and more than
from the Nausea (N) or represented in O>D>N.
Abstract: This paper presents a systematic approach for the
design of power system stabilizer using genetic algorithm and
investigates the robustness of the GA based PSS. The proposed
approach employs GA search for optimal setting of PSS parameters.
The performance of the proposed GPSS under small and large
disturbances, loading conditions and system parameters is tested.
The eigenvalue analysis and nonlinear simulation results show the
effectiveness of the GPSS to damp out the system oscillations. It is
found tat the dynamic performance with the GPSS shows improved
results, over conventionally tuned PSS over a wide range of
operating conditions.
Abstract: In this paper a new embedded Singly Diagonally
Implicit Runge-Kutta Nystrom fourth order in fifth order method for
solving special second order initial value problems is derived. A
standard set of test problems are tested upon and comparisons on the
numerical results are made when the same set of test problems are
reduced to first order systems and solved using the existing
embedded diagonally implicit Runge-Kutta method. The results
suggests the superiority of the new method.
Abstract: En bloc assumes modeling all phases of the orthostatic test with the only one mathematical model, which allows the complex parametric view of orthostatic response. The work presents the implementation of a mathematical model for processing of the measurements of systolic, diastolic blood pressure and heart rate performed on volunteers during orthostatic test. The original assumption of model hypothesis that every postural change means only one Stressor, did not complying with the measurements of physiological circulation factor-time profiles. Results of the identification support the hypothesis that second postural change of orthostatic test causes induced Stressors, with the observation of a physiological regulation mechanism. Maximal demonstrations are on the heart rate and diastolic blood pressure-time profile, minimal are for the measurements of the systolic blood pressure. Presented study gives a new view on orthostatic test with impact on clinical practice.
Abstract: Nanostructured materials have attracted many
researchers due to their outstanding mechanical and physical
properties. For example, carbon nanotubes (CNTs) or carbon
nanofibres (CNFs) are considered to be attractive reinforcement
materials for light weight and high strength metal matrix composites.
These composites are being projected for use in structural
applications for their high specific strength as well as functional
materials for their exciting thermal and electrical characteristics. The
critical issues of CNT-reinforced MMCs include processing
techniques, nanotube dispersion, interface, strengthening mechanisms
and mechanical properties. One of the major obstacles to the effective
use of carbon nanotubes as reinforcements in metal matrix
composites is their agglomeration and poor distribution/dispersion
within the metallic matrix. In order to tap into the advantages of the
properties of CNTs (or CNFs) in composites, the high dispersion of
CNTs (or CNFs) and strong interfacial bonding are the key issues
which are still challenging. Processing techniques used for synthesis
of the composites have been studied with an objective to achieve
homogeneous distribution of carbon nanotubes in the matrix.
Modified mechanical alloying (ball milling) techniques have emerged
as promising routes for the fabrication of carbon nanotube (CNT)
reinforced metal matrix composites. In order to obtain a
homogeneous product, good control of the milling process, in
particular control of the ball movement, is essential. The control of
the ball motion during the milling leads to a reduction in grinding
energy and a more homogeneous product. Also, the critical inner
diameter of the milling container at a particular rotational speed can
be calculated. In the present work, we use conventional and modified
mechanical alloying to generate a homogenous distribution of 2 wt.
% CNT within Al powders. 99% purity Aluminium powder (Acros,
200mesh) was used along with two different types of multiwall
carbon nanotube (MWCNTs) having different aspect ratios to
produce Al-CNT composites. The composite powders were processed
into bulk material by compaction, and sintering using a cylindrical
compaction and tube furnace. Field Emission Scanning electron
microscopy (FESEM), X-Ray diffraction (XRD), Raman
spectroscopy and Vickers macro hardness tester were used to
evaluate CNT dispersion, powder morphology, CNT damage, phase
analysis, mechanical properties and crystal size determination.
Despite the success of ball milling in dispersing CNTs in Al powder,
it is often accompanied with considerable strain hardening of the Al
powder, which may have implications on the final properties of the
composite. The results show that particle size and morphology vary
with milling time. Also, by using the mixing process and sonication
before mechanical alloying and modified ball mill, dispersion of the
CNTs in Al matrix improves.
Abstract: The fault detection and diagnosis of complicated
production processes is one of essential tasks needed to run the process
safely with good final product quality. Unexpected events occurred in
the process may have a serious impact on the process. In this work,
triangular representation of process measurement data obtained in an
on-line basis is evaluated using simulation process. The effect of using
linear and nonlinear reduced spaces is also tested. Their diagnosis
performance was demonstrated using multivariate fault data. It has
shown that the nonlinear technique based diagnosis method produced
more reliable results and outperforms linear method. The use of
appropriate reduced space yielded better diagnosis performance. The
presented diagnosis framework is different from existing ones in that it
attempts to extract the fault pattern in the reduced space, not in the
original process variable space. The use of reduced model space helps
to mitigate the sensitivity of the fault pattern to noise.
Abstract: MultiProtocol Label Switching (MPLS) is an
emerging technology that aims to address many of the existing issues
associated with packet forwarding in today-s Internetworking
environment. It provides a method of forwarding packets at a high
rate of speed by combining the speed and performance of Layer 2
with the scalability and IP intelligence of Layer 3. In a traditional IP
(Internet Protocol) routing network, a router analyzes the destination
IP address contained in the packet header. The router independently
determines the next hop for the packet using the destination IP
address and the interior gateway protocol. This process is repeated at
each hop to deliver the packet to its final destination. In contrast, in
the MPLS forwarding paradigm routers on the edge of the network
(label edge routers) attach labels to packets based on the forwarding
Equivalence class (FEC). Packets are then forwarded through the
MPLS domain, based on their associated FECs , through swapping
the labels by routers in the core of the network called label switch
routers. The act of simply swapping the label instead of referencing
the IP header of the packet in the routing table at each hop provides
a more efficient manner of forwarding packets, which in turn allows
the opportunity for traffic to be forwarded at tremendous speeds and
to have granular control over the path taken by a packet. This paper
deals with the process of MPLS forwarding mechanism,
implementation of MPLS datapath , and test results showing the
performance comparison of MPLS and IP routing. The discussion
will focus primarily on MPLS IP packet networks – by far the
most common application of MPLS today.
Abstract: This paper introduces a novel approach to estimate the
clique potentials of Gibbs Markov random field (GMRF) models
using the Support Vector Machines (SVM) algorithm and the Mean
Field (MF) theory. The proposed approach is based on modeling the
potential function associated with each clique shape of the GMRF
model as a Gaussian-shaped kernel. In turn, the energy function of
the GMRF will be in the form of a weighted sum of Gaussian
kernels. This formulation of the GMRF model urges the use of the
SVM with the Mean Field theory applied for its learning for
estimating the energy function. The approach has been tested on
synthetic texture images and is shown to provide satisfactory results
in retrieving the synthesizing parameters.
Abstract: The localized corrosion behavior of laser surface
melted 304L austenitic stainless steel was studied by
potentiodynamic polarization test. The extent of improvement in
corrosion resistance was governed by the preferred orientation and
the percentage of delta ferrite present on the surface of the laser
melted sample. It was established by orientation imaging microscopy
that the highest pitting potential value was obtained when grains were
oriented in the most close- packed [101] direction compared to the
random distribution of the base metal and other laser surface melted
samples oriented in [001] direction. The sample with lower
percentage of ferrite had good pitting resistance.
Abstract: The proof of concept experiments were conducted to
determine the feasibility of using small amounts of Dissolved
Sulphur (DS) from the gaseous phase to precipitate platinum ions in
chloride media. Two sets of precipitation experiments were
performed in which the source of sulphur atoms was either a
thiosulphate solution (Na2S2O3) or a sulphur dioxide gas (SO2). In
liquid-liquid (L-L) system, complete precipitation of Pt was achieved
at small dosages of Na2S2O3 (0.01 – 1.0 M) in a time interval of 3-5
minutes. On the basis of this result, gas absorption tests were carried
out mainly to achieve sulphur solubility equivalent to 0.018 M. The
idea that huge amounts of precious metals could be recovered
selectively from their dilute solutions by utilizing the waste SO2
streams at low pressure seemed attractive from the economic and
environmental point of views. Therefore, mass transfer characteristics
of SO2 gas associated with reactive absorption across the gas-liquid
(G-L) interface were evaluated under different conditions of pressure
(0.5 – 2 bar), solution temperature ranges from 20 – 50 oC and acid
strength (1 – 4 M, HCl). This paper concludes with information about
selective precipitation of Pt in the presence of cations (Fe2+, Co2+,
and Cr3+) in a CSTR and recommendation to scale up laboratory data
to industrial pilot scale operations.
Abstract: Abu Dhabi is one of the fastest developed cities in the region. On top of all the current and future environmental challenges, Abu Dhabi aims to be among the top governments in the world in sustainable development. Abu Dhabi plans to create an attractive, livable and sustainable managed urban environment in which all necessary services and infrastructure are provided in a sustainable and timely manner. Abu Dhabi is engaged in a difficult challenge to develop credible environmental indicators that would assess the ambitious environmental targets. The aim of those indicators is to provide reliable guidance to decision makers and the public concerning key factors that determine the state of urban environment and identify major areas for policy intervention. In order to ensure sustainable development in UAE in general, and of Abu Dhabi City in particular, relevant and contextual environmental indicators need to be carefully considered. These indicators provide a gauge at a national government scale of how close countries are to establish environmental policy goals. The environment indicators assist city decision-making in such areas as identification of significant environmental aspects and observation of environmental performance trends. Those can help to find ways of reducing environmental pollution and in improving eco-efficiency. This paper outlines recent strategies implemented in Abu Dhabi that aims to improve the sustainable performance of the city-s built environment. The paper explores the variety of current and possible indicators at different levels and their roles in the development of the city.
Abstract: This paper examines predictability in stock return in
developed and emergingmarkets by testing long memory in stock
returns using wavelet approach. Wavelet-based maximum likelihood
estimator of the fractional integration estimator is superior to the
conventional Hurst exponent and Geweke and Porter-Hudak
estimator in terms of asymptotic properties and mean squared error.
We use 4-year moving windows to estimate the fractional integration
parameter. Evidence suggests that stock return may not be predictable
indeveloped countries of the Asia-Pacificregion. However,
predictability of stock return insome developing countries in this
region such as Indonesia, Malaysia and Philippines may not be ruled
out. Stock return in the Thailand stock market appears to be not
predictable after the political crisis in 2008.