Abstract: A mathematical model of the additional effects of the
liquid in the hydrodynamic gap is presented in the paper. An
incompressible viscous fluid is considered. Based on computational
modeling are determined the matrices of mass, stiffness and damping.
The mathematical model is experimentally verified.
Abstract: In the Hierarchical Temporal Memory (HTM) paradigm
the effect of overlap between inputs on the activation of columns in
the spatial pooler is studied. Numerical results suggest that similar
inputs are represented by similar sets of columns and dissimilar inputs
are represented by dissimilar sets of columns. It is shown that the
spatial pooler produces these results under certain conditions for
the connectivity and proximal thresholds. Following the discussion
of the initialization of parameters for the thresholds, corresponding
qualitative arguments about the learning dynamics of the spatial
pooler are discussed.
Abstract: An efficient remanufacturing network lead to an
efficient design of sustainable manufacturing enterprise. In
remanufacturing network, products are collected from the customer
zone, disassembled and remanufactured at a suitable remanufacturing
facility. In this respect, another issue to consider is how the returned
product to be remanufactured, in other words, what is the best layout
for such facility. In order to achieve a sustainable manufacturing
system, Cellular Manufacturing System (CMS) designs are highly
recommended, CMSs combine high throughput rates of line layouts
with the flexibility offered by functional layouts (job shop).
Introducing the CMS while designing a remanufacturing network will
benefit the utilization of such a network. This paper presents and
analyzes a comprehensive mathematical model for the design of
Dynamic Cellular Remanufacturing Systems (DCRSs). In this paper,
the proposed model is the first one to date that considers CMS and
remanufacturing system simultaneously. The proposed DCRS model
considers several manufacturing attributes such as multi period
production planning, dynamic system reconfiguration, duplicate
machines, machine capacity, available time for workers, worker
assignments, and machine procurement, where the demand is totally
satisfied from a returned product. A numerical example is presented
to illustrate the proposed model.
Abstract: The article presents two mathematical models of the
interaction between a rotating shaft and an incompressible fluid. The
mathematical model includes both the journal bearings and the
axially traversed hydrodynamic sealing gaps of hydraulic machines.
A method is shown for the identification of additional effects of the
fluid acting on the rotor of the machine, both for a linear and a nonlinear
model. The interaction is expressed by matrices of mass,
stiffness and damping.
Abstract: In the past few years, the amount of malicious software
increased exponentially and, therefore, machine learning algorithms
became instrumental in identifying clean and malware files through
(semi)-automated classification. When working with very large
datasets, the major challenge is to reach both a very high malware
detection rate and a very low false positive rate. Another challenge
is to minimize the time needed for the machine learning algorithm to
do so. This paper presents a comparative study between different
machine learning techniques such as linear classifiers, ensembles,
decision trees or various hybrids thereof. The training dataset consists
of approximately 2 million clean files and 200.000 infected files,
which is a realistic quantitative mixture. The paper investigates the
above mentioned methods with respect to both their performance
(detection rate and false positive rate) and their practicability.
Abstract: DC motors have been widely used in the past
centuries which are proudly known as the workhorse of industrial
systems until the invention of the AC induction motors which makes
a huge revolution in industries. Since then, the use of DC machines
has been decreased due to enormous factors such as reliability,
robustness and complexity but it lost its fame due to the losses. In this
paper a new methodology is proposed to construct a DC motor
through the simulation in LabVIEW to get an idea about its real time
performances, if a change in parameter might have bigger
improvement in losses and reliability.
Abstract: This paper deals with the theoretical and numerical
investigation of magneto hydrodynamic boundary layer flow of a
nanofluid past a wedge shaped wick in heat pipe used for the cooling
of electronic components and different type of machines. To
incorporate the effect of nanoparticle diameter, concentration of
nanoparticles in the pure fluid, nanothermal layer formed around the
nanoparticle and Brownian motion of nanoparticles etc., appropriate
models are used for the effective thermal and physical properties of
nanofluids. To model the rotation of nanoparticles inside the base
fluid, microfluidics theory is used. In this investigation ethylene
glycol (EG) based nanofluids, are taken into account. The non-linear
equations governing the flow and heat transfer are solved by using a
very effective particle swarm optimization technique along with
Runge-Kutta method. The values of heat transfer coefficient are
found for different parameters involved in the formulation viz.
nanoparticle concentration, nanoparticle size, magnetic field and
wedge angle etc. It is found that, the wedge angle, presence of
magnetic field, nanoparticle size and nanoparticle concentration etc.
have prominent effects on fluid flow and heat transfer characteristics
for the considered configuration.
Abstract: The number of persons with implanted cardiac
pacemakers (PM) has increased in Western countries. The aim of this
paper is to investigate the possible situations where persons with a
PM may be exposed to extremely low frequency (ELF) electric (EF)
and magnetic fields (MF) that may disturb their PM. Based on our
earlier studies, it is possible to find such high public exposure to EFs
only in some places near 400 kV power lines, where an EF may
disturb a PM in unipolar mode. Such EFs cannot be found near 110
kV power lines. Disturbing MFs can be found near welding
machines. However, we do not have measurement data from welding.
Based on literature and earlier studies at Tampere University of
Technology, it is difficult to find public EF or MF exposure that is
high enough to interfere with PMs.
Abstract: Fixed-geometry hydrodynamic journal bearings are
one of the best supporting systems for several applications of rotating
machinery. Cylindrical journal bearings present excellent loadcarrying
capacity and low manufacturing costs, but they are subjected
to the oil-film instability at high speeds. An attempt of overcoming
this instability problem has been the development of non-circular
journal bearings. This work deals with an analysis of oil-lubricated
elliptical journal bearings using the finite element method. Steadystate
and dynamic performance characteristics of elliptical bearings
are rendered by zeroth- and first-order lubrication equations obtained
through a linearized perturbation method applied on the classical
Reynolds equation. Four-node isoparametric rectangular finite
elements are employed to model the bearing thin film flow. Curves of
elliptical bearing load capacity and dynamic force coefficients are
rendered at several operating conditions. The results presented in this
work demonstrate the influence of the bearing ellipticity on its
performance at different loading conditions.
Abstract: This paper introduces a proposal scheme for an
Intelligent System applied to Pedagogical Advising using Case-Based
Reasoning, to find consolidated solutions before used for the new
problems, making easier the task of advising students to the
pedagogical staff. We do intend, through this work, introduce the
motivation behind the choices for this system structure, justifying the
development of an incremental and smart web system who learns
bests solutions for new cases when it’s used, showing technics and
technology.
Abstract: The thermal control in many systems is widely
accomplished applying mixed convection process due to its low cost,
reliability and easy maintenance. Typical applications include the
aircraft electronic equipment, rotating-disc heat exchangers, turbo
machinery, and nuclear reactors, etc. Natural convection in an inclined
square enclosure heated via wall heater has been studied numerically.
Finite volume method is used for solving momentum and energy
equations in the form of stream function–vorticity. The right and left
walls are kept at a constant temperature, while the other parts are
adiabatic. The range of the inclination angle covers a whole revolution.
The method is validated for a vertical cavity. A general power law
dependence of the Nusselt number with respect to the Rayleigh
number with the coefficient and exponent as functions of the
inclination angle is presented. For a fixed Rayleigh number, the
inclination angle increases or decreases is found.
Abstract: Chemical vapor deposition (CVD) diamond coated
cutting tool has excellent cutting performance, it is the most ideal tool
for the processing of nonferrous metals and alloys, composites,
nonmetallic materials and other difficult-to-machine materials
efficiently and accurately. Depositing CVD diamond coating on the
cemented carbide with high cobalt content can improve its toughness
and strength, therefore, it is very important to research on the
preparation technology and cutting properties of CVD diamond coated
cemented carbide cutting tool with high cobalt content. The
preparation technology of boron-doped diamond (BDD) coating has
been studied and the coated drills were prepared. BDD coating were
deposited on the drills by using the optimized parameters and the SEM
results show that there are no cracks or collapses in the coating.
Cutting tests with the prepared drills against the silumin and aluminum
base printed circuit board (PCB) have been studied. The results show
that the wear amount of the coated drill is small and the machined
surface has a better precision. The coating does not come off during
the test, which shows good adhesion and cutting performance of the
drill.
Abstract: The capability of CNC gantry milling machines in
manufacturing long components has caused the expanded use of such
machines. On the other hand, the machines’ gantry rigidity can
reduce under severe loads or vibration during operation. Indeed, the
quality of machining is dependent on the machine’s dynamic
behavior throughout the operating process. For this reason, these
types of machines have always been used widely and are not
efficient. Therefore, they can usually be employed for rough
machining and may not produce adequate surface finishing. In this
paper, a CNC gantry milling machine with the potential to produce
good surface finish has been designed and analyzed. The lowest
natural frequency of this machine is 202 Hz corresponding to 12000
rpm at all motion amplitudes with a full range of suitable frequency
responses. Meanwhile, the maximum deformation under dead loads
for the gantry machine is 0.565*m, indicating that this machine tool
is capable of producing higher product quality.
Abstract: Power Regeneration in Refrigeration Plant concept
has been analyzed and has been shown to be capable of saving about
25% power in Cryogenic Plants with the Power Regeneration System
(PRS) running under nominal conditions. The innovative component
Compressor Expander Group (CEG) based on turbomachinery has
been designed and built modifying CETT compressor and expander,
both selected for optimum plant performance. Experiments have
shown the good response of the turbomachines to run with R404a as
working fluid. Power saving up to 12% under PRS derated conditions
(50% loading) has been demonstrated. Such experiments allowed
predicting a power saving up to 25% under CEG full load.
Abstract: Customer churn prediction is one of the most useful
areas of study in customer analytics. Due to the enormous amount
of data available for such predictions, machine learning and data
mining have been heavily used in this domain. There exist many
machine learning algorithms directly applicable for the problem of
customer churn prediction, and here, we attempt to experiment on
a novel approach by using a cognitive learning based technique in
an attempt to improve the results obtained by using a combination
of supervised learning methods, with cognitive unsupervised learning
methods.
Abstract: Over the past four decades, the fatigue behavior of
nickel-based alloys has been widely studied. However, in recent
years, significant advances in the fabrication process leading to grain
size reduction have been made in order to improve fatigue properties
of aircraft turbine discs. Indeed, a change in particle size affects the
initiation mode of fatigue cracks as well as the fatigue life of the
material. The present study aims to investigate the fatigue behavior of
a newly developed nickel-based superalloy under biaxial-planar
loading. Low Cycle Fatigue (LCF) tests are performed at different
stress ratios so as to study the influence of the multiaxial stress state
on the fatigue life of the material. Full-field displacement and strain
measurements as well as crack initiation detection are obtained using
Digital Image Correlation (DIC) techniques. The aim of this
presentation is first to provide an in-depth description of both the
experimental set-up and protocol: the multiaxial testing machine, the
specific design of the cruciform specimen and performances of the
DIC code are introduced. Second, results for sixteen specimens
related to different load ratios are presented. Crack detection, strain
amplitude and number of cycles to crack initiation vs. triaxial stress
ratio for each loading case are given. Third, from fractographic
investigations by scanning electron microscopy it is found that the
mechanism of fatigue crack initiation does not depend on the triaxial
stress ratio and that most fatigue cracks initiate from subsurface
carbides.
Abstract: The present study is an attempt to provide a relatively
comprehensive preview of the Iranian English translators’ perception
on Machine Translation. Furthermore, the study tries to shed light on
the status of implementation of Machine Translation among the
Iranian English Translators. To reach the aforementioned objectives,
the Localization Industry Standards Association’s questioner for
measuring perceptions with regard to the adoption of a technology
innovation was adapted and used to investigate the perception and
implementation of Machine Translation applications by the Iranian
English language translators. The participants of the study were 224
last-year undergraduate Iranian students of English translation at 10
universities across the country. The study revealed a very low level of
adoption and a very high level of willingness to get familiar with and
learn about Machine Translation, as well as a positive perception of
and attitude toward Machine Translation by the Iranian English
translators.
Abstract: Robotic surgery is used to enhance minimally invasive
surgical procedure. It provides greater degree of freedom for surgical
tools but lacks of haptic feedback system to provide sense of touch to
the surgeon. Surgical robots work on master-slave operation, where
user is a master and robotic arms are the slaves. Current, surgical
robots provide precise control of the surgical tools, but heavily rely
on visual feedback, which sometimes cause damage to the inner
organs. The goal of this research was to design and develop a realtime
Simulink based robotic system to study force feedback
mechanism during instrument-object interaction. Setup includes three
VelmexXSlide assembly (XYZ Stage) for three dimensional
movement, an end effector assembly for forceps, electronic circuit for
four strain gages, two Novint Falcon 3D gaming controllers,
microcontroller board with linear actuators, MATLAB and Simulink
toolboxes. Strain gages were calibrated using Imada Digital Force
Gauge device and tested with a hard-core wire to measure
instrument-object interaction in the range of 0-35N. Designed
Simulink model successfully acquires 3D coordinates from two
Novint Falcon controllers and transfer coordinates to the XYZ stage
and forceps. Simulink model also reads strain gages signal through
10-bit analog to digital converter resolution of a microcontroller
assembly in real time, converts voltage into force and feedback the
output signals to the Novint Falcon controller for force feedback
mechanism. Experimental setup allows user to change forward
kinematics algorithms to achieve the best-desired movement of the
XYZ stage and forceps. This project combines haptic technology
with surgical robot to provide sense of touch to the user controlling
forceps through machine-computer interface.
Abstract: In this paper, we used data mining to extract
biomedical knowledge. In general, complex biomedical data
collected in studies of populations are treated by statistical methods,
although they are robust, they are not sufficient in themselves to
harness the potential wealth of data. For that you used in step two
learning algorithms: the Decision Trees and Support Vector Machine
(SVM). These supervised classification methods are used to make the
diagnosis of thyroid disease. In this context, we propose to promote
the study and use of symbolic data mining techniques.
Abstract: Electroencephalogram (EEG) is a noninvasive
technique that registers signals originating from the firing of neurons
in the brain. The Emotiv EEG Neuroheadset is a consumer product
comprised of 14 EEG channels and was used to record the reactions
of the neurons within the brain to two forms of stimuli in 10
participants. These stimuli consisted of auditory and visual formats
that provided directions of ‘right’ or ‘left.’ Participants were
instructed to raise their right or left arm in accordance with the
instruction given. A scenario in OpenViBE was generated to both
stimulate the participants while recording their data. In OpenViBE,
the Graz Motor BCI Stimulator algorithm was configured to govern
the duration and number of visual stimuli. Utilizing EEGLAB under
the cross platform MATLAB®, the electrodes most stimulated during
the study were defined. Data outputs from EEGLAB were analyzed
using IBM SPSS Statistics® Version 20. This aided in determining
the electrodes to use in the development of a brain-machine interface
(BMI) using real-time EEG signals from the Emotiv EEG
Neuroheadset. Signal processing and feature extraction were
accomplished via the Simulink® signal processing toolbox. An
Arduino™ Duemilanove microcontroller was used to link the Emotiv
EEG Neuroheadset and the right and left Mecha TE™ Hands.