Abstract: The flexible follower response of a translating cam with
four different profiles for rise-dwell-fall-dwell (RDFD) motion is
investigated. The cycloidal displacement motion, the modified
sinusoidal acceleration motion, the modified trapezoidal acceleration
motion, and the 3-4-5 polynomial motion are employed to describe the
rise and the fall motions of the follower and the associated four kinds of
cam profiles are studied. Since the follower flexibility is considered,
the contact point of the roller and the cam is an unknown. Two
geometric constraints formulated to restrain the unknown position are
substituted into Hamilton-s principle with Lagrange multipliers.
Applying the assumed mode method, one can obtain the governing
equations of motion as non-linear differential-algebraic equations. The
equations are solved using Runge-Kutta method. Then, the responses of
the flexible follower undergoing the four different motions are
investigated in time domain and in frequency domain.
Abstract: This paper focuses attention on specific aspects of
entrepreneurial decisions relating to investment, both in the total
fixed investments and plant & machinery (separately). Demand and
financial factors, internal and external, are considered in the
investment analysis. Finally the influence of determinants of fixed
investment and investment plans are examined in Electric Power
industry in India.
Abstract: Nowadays increasingly the population makes use of
Information Technology (IT). As such, in recent year the Portuguese
government increased its focus on using the IT for improving
people-s life and began to develop a set of measures to enable the
modernization of the Public Administration, and so reducing the gap
between Public Administration and citizens.Thus the Portuguese
Government launched the Simplex Program. However these
SIMPLEX eGov measures, which have been implemented over the
years, present a serious challenge: how to forecast its impact on
existing Information Systems Architecture (ISA). Thus, this research
is focus in addressing the problem of automating the evaluation of the
actual impact of implementation an eGovSimplification and
Modernization measures in the Information Systems Architecture. To
realize the evaluation we proposes a Framework, which is supported
by some key concepts as: Quality Factors, ISA modeling,
Multicriteria Approach, Polarity Profile and Quality Metrics
Abstract: In this research, a 2-D computational analysis of
steady state free convection in a rectangular enclosure filled with an
electrically conducting fluid under Effect of Magnetic Field has been
performed. The governing equations (mass, momentum, and energy)
are formulated and solved by a finite volume method (FVM)
subjected to different boundary conditions. A parametric study has
been conducted to consider the influence of Grashof number (Gr),
Prantdl number (Pr) and the orientation of magnetic field on the flow
and heat transfer characteristics. It is observed that Nusselt number
(Nu) and heat flux will increase with increasing Grashof and Prandtl
numbers and decreasing the slope of the orientation of magnetic field.
Abstract: A dead leg is a typical subsea production system
component. CFD is required to model heat transfer within the dead
leg. Unfortunately its solution is time demanding and thus not
suitable for fast prediction or repeated simulations. Therefore there is
a need to create a thermal FEA model, mimicking the heat flows and
temperatures seen in CFD cool down simulations.
This paper describes the conventional way of tuning and a new
automated way using parametric model order reduction (PMOR)
together with an optimization algorithm. The tuned FE analyses
replicate the steady state CFD parameters within a maximum error in
heat flow of 6 % and 3 % using manual and PMOR method
respectively. During cool down, the relative error of the tuned FEA
models with respect to temperature is below 5% comparing to the
CFD. In addition, the PMOR method obtained the correct FEA setup
five times faster than the manually tuned FEA.
Abstract: Software project effort estimation is frequently seen
as complex and expensive for individual software engineers.
Software production is in a crisis. It suffers from excessive costs.
Software production is often out of control. It has been suggested that
software production is out of control because we do not measure.
You cannot control what you cannot measure. During last decade, a
number of researches on cost estimation have been conducted. The
metric-set selection has a vital role in software cost estimation
studies; its importance has been ignored especially in neural network
based studies. In this study we have explored the reasons of those
disappointing results and implemented different neural network
models using augmented new metrics. The results obtained are
compared with previous studies using traditional metrics. To be able
to make comparisons, two types of data have been used. The first
part of the data is taken from the Constructive Cost Model
(COCOMO'81) which is commonly used in previous studies and the
second part is collected according to new metrics in a leading
international company in Turkey. The accuracy of the selected
metrics and the data samples are verified using statistical techniques.
The model presented here is based on Multi-Layer Perceptron
(MLP). Another difficulty associated with the cost estimation studies
is the fact that the data collection requires time and care. To make a
more thorough use of the samples collected, k-fold, cross validation
method is also implemented. It is concluded that, as long as an
accurate and quantifiable set of metrics are defined and measured
correctly, neural networks can be applied in software cost estimation
studies with success
Abstract: The influence of eccentric discharge of stored solids in
squat silos has been highly valued by many researchers. However,
calculation method of lateral pressure under eccentric flowing still
needs to be deeply studied. In particular, the lateral pressure
distribution on vertical wall could not be accurately recognized
mainly because of its asymmetry. In order to build mechanical model
of lateral pressure, flow channel and flow pattern of stored solids in
squat silo are studied. In this passage, based on Janssen-s theory, the
method for calculating lateral static pressure in squat silos after
eccentric discharge is proposed. Calculative formulae are deduced for
each of three possible cases. This method is also focusing on
unsymmetrical distribution characteristic of silo wall normal
pressure. Finite element model is used to analysis and compare the
results of lateral pressure and the numerical results illustrate the
practicability of the theoretical method.
Abstract: The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.
Abstract: In order to guarantee secure communication for wireless sensor networks (WSNs), many user authentication schemes have successfully drawn researchers- attention and been studied widely. In 2012, He et al. proposed a robust biometric-based user authentication scheme for WSNs. However, this paper demonstrates that He et al.-s scheme has some drawbacks: poor reparability problem, user impersonation attack, and sensor node impersonate attack.
Abstract: In this paper we proposed comparison of four content based objective metrics with results of subjective tests from 80 video sequences. We also include two objective metrics VQM and SSIM to our comparison to serve as “reference” objective metrics because their pros and cons have already been published. Each of the video sequence was preprocessed by the region recognition algorithm and then the particular objective video quality metric were calculated i.e. mutual information, angular distance, moment of angle and normalized cross-correlation measure. The Pearson coefficient was calculated to express metrics relationship to accuracy of the model and the Spearman rank order correlation coefficient to represent the metrics relationship to monotonicity. The results show that model with the mutual information as objective metric provides best result and it is suitable for evaluating quality of video sequences.
Abstract: In the present article, nonlinear vibration analysis of
single layer graphene sheets is presented and the effect of small
length scale is investigated. Using the Hamilton's principle, the three
coupled nonlinear equations of motion are obtained based on the von
Karman geometrical model and Eringen theory of nonlocal
continuum. The solutions of Free nonlinear vibration, based on a one
term mode shape, are found for both simply supported and clamped
graphene sheets. A complete analysis of graphene sheets with
movable as well as immovable in-plane conditions is also carried out.
The results obtained herein are compared with those available in the
literature for classical isotropic rectangular plates and excellent
agreement is seen. Also, the nonlinear effects are presented as
functions of geometric properties and small scale parameter.
Abstract: Symbolic dynamics studies dynamical systems on the basis of the symbol sequences obtained for a suitable partition of the state space. This approach exploits the property that system dynamics reduce to a shift operation in symbol space. This shift operator is a chaotic mapping. In this article we show that in the symbol space exist other chaotic mappings.
Abstract: This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.
Abstract: Study of fire and explosion is very important mainly
in oil and gas industries due to several accidents which have been
reported in the past and present. In this work, we have investigated
the flammability of bio oil vapour mixtures. This mixture may
contribute to fire during the storage and transportation process. Bio
oil sample derived from Palm Kernell shell was analysed using Gas
Chromatography Mass Spectrometry (GC-MS) to examine the
composition of the sample. Mole fractions of 12 selected
components in the liquid phase were obtained from the GC-FID data
and used to calculate mole fractions of components in the gas phase
via modified Raoult-s law. Lower Flammability Limits (LFLs) and
Upper Flammability Limits (UFLs) for individual components were
obtained from published literature. However, stoichiometric
concentration method was used to calculate the flammability limits
of some components which their flammability limit values are not
available in the literature. The LFL and UFL values for the mixture
were calculated using the Le Chatelier equation. The LFLmix and
UFLmix values were used to construct a flammability diagram and
subsequently used to determine the flammability of the mixture. The
findings of this study can be used to propose suitable inherently
safer method to prevent the flammable mixture from occurring and
to minimizing the loss of properties, business, and life due to fire
accidents in bio oil productions.
Abstract: Today, building automation is advancing from simple
monitoring and control tasks of lightning and heating towards more
and more complex applications that require a dynamic perception
and interpretation of different scenes occurring in a building. Current
approaches cannot handle these newly upcoming demands. In this
article, a bionically inspired approach for multimodal, dynamic scene
perception and interpretation is presented, which is based on neuroscientific
and neuro-psychological research findings about the perceptual
system of the human brain. This approach bases on data from diverse
sensory modalities being processed in a so-called neuro-symbolic
network. With its parallel structure and with its basic elements being
information processing and storing units at the same time, a very
efficient method for scene perception is provided overcoming the
problems and bottlenecks of classical dynamic scene interpretation
systems.
Abstract: Prediction of fault-prone modules provides one way to
support software quality engineering. Clustering is used to determine
the intrinsic grouping in a set of unlabeled data. Among various
clustering techniques available in literature K-Means clustering
approach is most widely being used. This paper introduces K-Means
based Clustering approach for software finding the fault proneness of
the Object-Oriented systems. The contribution of this paper is that it
has used Metric values of JEdit open source software for generation
of the rules for the categorization of software modules in the
categories of Faulty and non faulty modules and thereafter
empirically validation is performed. The results are measured in
terms of accuracy of prediction, probability of Detection and
Probability of False Alarms.
Abstract: A numerical investigation of surface heat transfer
characteristics of turbulent air flows in different parallel plate
grooved channels is performed using CFD code. The results are
obtained for Reynolds number ranging from 10,000 to 30,000 and for
arc-shaped and rectangular grooved channels. The influence of
different geometric parameters of dimples as well as the number of
them and the geometric and thermophysical properties of channel
walls are studied. It is found that there exists an optimum value for
depth of dimples in which the largest wall heat flux can be achieved.
Also, the results show a critical value for the ratio of wall thermal
conductivity to the one of fluid in which the dependence of wall heat
flux to this ratio almost vanishes. In most cases examined, heat
transfer enhancement is larger for arc-shaped grooved channels than
rectangular ones.
Abstract: Image retrieval is a topic where scientific interest is currently high. The important steps associated with image retrieval system are the extraction of discriminative features and a feasible similarity metric for retrieving the database images that are similar in content with the search image. Gabor filtering is a widely adopted technique for feature extraction from the texture images. The recently proposed sparsity promoting l1-norm minimization technique finds the sparsest solution of an under-determined system of linear equations. In the present paper, the l1-norm minimization technique as a similarity metric is used in image retrieval. It is demonstrated through simulation results that the l1-norm minimization technique provides a promising alternative to existing similarity metrics. In particular, the cases where the l1-norm minimization technique works better than the Euclidean distance metric are singled out.
Abstract: In this paper, we study a new modified Novikov equation for its classical and nonclassical symmetries and use the symmetries to reduce it to a nonlinear ordinary differential equation (ODE). With the aid of solutions of the nonlinear ODE by using the modified (G/G)-expansion method proposed recently, multiple exact traveling wave solutions are obtained and the traveling wave solutions are expressed by the hyperbolic functions, trigonometric functions and rational functions.
Abstract: Dynamic shear test on simulated phantom can be used
to validate magnetic resonance elastography (MRE) measurements.
Phantom gel has been usually utilized for the cell culture of cartilage
and soft tissue and also been used for mechanical property
characterization using imaging systems. The viscoelastic property of
the phantom would be important for dynamic experiments and
analyses. In this study, An axisymmetric FE model is presented for
determining the dynamic shear behaviour of brain simulated phantom
using ABAQUS. The main objective of this study was to investigate
the effect of excitation frequencies and boundary conditions on shear
modulus and shear viscosity in viscoelastic media.