Abstract: In this paper, de Laval rotor system has been
characterized by a hinge model and its transient response numerically
treated for a dynamic solution. The effect of the ensuing non-linear
disturbances namely rub and breathing crack is numerically
simulated. Subsequently, three analysis methods: Orbit Analysis, Fast
Fourier Transform (FFT), and Wavelet Transform (WT) are
employed to extract features of the vibration signal of the faulty
system. An analysis of the system response orbits clearly indicates
the perturbations due to the rotor-to-stator contact. The sensitivities
of WT to the variation in system speed have been investigated by
Continuous Wavelet Transform (CWT). The analysis reveals that
features of crack, rubs and unbalance in vibration response can be
useful for condition monitoring. WT reveals its ability to detect nonlinear
signal, and obtained results provide a useful tool method for
detecting machinery faults.
Abstract: Since the advances in digital imaging technologies have led to
development of high quality digital devices, there are a lot of illegal copies
of copyrighted video content on the Internet. Also, unauthorized editing is
occurred frequently. Thus, we propose an editing prevention technique for
high-quality (HQ) video that can prevent these illegally edited copies from
spreading out. The proposed technique is applied spatial and temporal gradient
methods to improve the fidelity and detection performance. Also, the scheme
duplicates the embedding signal temporally to alleviate the signal reduction
caused by geometric and signal-processing distortions. Experimental results
show that the proposed scheme achieves better performance than previously
proposed schemes and it has high fidelity. The proposed scheme can be used
in unauthorized access prevention method of visual communication or traitor
tracking applications which need fast detection process to prevent illegally
edited video content from spreading out.
Abstract: In this paper, approach to incoherent signal detection
in multi-element antenna array are researched and modeled. Two
types of useful signals with unknown wavefront were considered:
first one, deterministic (Barker code), and second one, random
(Gaussian distribution). The derivation of the sufficient statistics took
into account the linearity of the antenna array. The performance
characteristics and detecting curves are modeled and compared for
different useful signals parameters and for different number of
elements of the antenna array. Results of researches in case of some
additional conditions can be applied to a digital communications
systems.
Abstract: This paper introduces a signal monitoring program
developed with a view to helping electrical engineering students get
familiar with sensors with digital output. Because the output of digital
sensors cannot be simply monitored by a measuring instrument such as
an oscilloscope, students tend to have a hard time dealing with digital
sensors. The monitoring program runs on a PC and communicates with
an MCU that reads the output of digital sensors via an asynchronous
communication interface. Receiving the sensor data from the MCU,
the monitoring program shows time and/or frequency domain plots of
the data in real time. In addition, the monitoring program provides a
serial terminal that enables the user to exchange text information with
the MCU while the received data is plotted. The user can easily
observe the output of digital sensors and configure the digital sensors
in real time, which helps students who do not have enough experiences
with digital sensors. Though the monitoring program was programmed
in the Matlab programming language, it runs without the Matlab since
it was compiled as a standalone executable.
Abstract: A seizure prediction method is proposed by extracting
global features using phase correlation between adjacent epochs for
detecting relative changes and local features using fluctuation/
deviation within an epoch for determining fine changes of different
EEG signals. A classifier and a regularization technique are applied
for the reduction of false alarms and improvement of the overall
prediction accuracy. The experiments show that the proposed method
outperforms the state-of-the-art methods and provides high prediction
accuracy (i.e., 97.70%) with low false alarm using EEG signals in
different brain locations from a benchmark data set.
Abstract: The power electronic components within Electric Vehicles (EV) need to operate in several important modes. Some modes directly influence safety, while others influence vehicle performance. Given the variety of functions and operational modes required of the power electronics, it needs to meet efficiency requirements to minimize power losses. Another challenge in the control and construction of such systems is the ability to support bidirectional power flow. This paper considers the construction, operation, and feasibility of available converters for electric vehicles with feasible configurations of electrical buses and loads. This paper describes logic and control signals for the converters for different operations conditions based on the efficiency and energy usage bases.
Abstract: This paper describes the development of a DNA-based
nanobiosensor to detect the dengue virus in mosquito using
electrically active magnetic (EAM) nanoparticles as concentrator and
electrochemical transducer. The biosensor detection encompasses
two sets of oligonucleotide probes that are specific to the dengue
virus: the detector probe labeled with the EAM nanoparticles and the
biotinylated capture probe. The DNA targets are double hybridized to
the detector and the capture probes and concentrated from
nonspecific DNA fragments by applying a magnetic field.
Subsequently, the DNA sandwiched targets (EAM-detector probe–
DNA target–capture probe-biotin) are captured on streptavidin
modified screen printed carbon electrodes through the biotinylated
capture probes. Detection is achieved electrochemically by measuring
the oxidation–reduction signal of the EAM nanoparticles. Results
indicate that the biosensor is able to detect the redox signal of the
EAM nanoparticles at dengue DNA concentrations as low as 10
ng/μl.
Abstract: This study was aimed to measure effective transverse
relaxation rates (R2*) in the liver and muscle of normal New Zealand
White (NZW) rabbits. R2* relaxation rate has been widely used in
various hepatic diseases for iron overload by quantifying iron contents
in liver. R2* relaxation rate is defined as the reciprocal of T2*
relaxation time and mainly depends on the constituents of tissue.
Different tissues would have different R2* relaxation rates. The signal
intensity decay in Magnetic resonance imaging (MRI) may be
characterized by R2* relaxation rates. In this study, a 1.5T GE Signa
HDxt whole body MR scanner equipped with an 8-channel high
resolution knee coil was used to observe R2* values in NZW rabbit’s
liver and muscle. Eight healthy NZW rabbits weighted 2 ~ 2.5 kg were
recruited. After anesthesia using Zoletil 50 and Rompun 2% mixture,
the abdomen of rabbit was landmarked at the center of knee coil to
perform 3-plane localizer scan using fast spoiled gradient echo
(FSPGR) pulse sequence. Afterwards, multi-planar fast gradient echo
(MFGR) scans were performed with 8 various echo times (TEs) to
acquire images for R2* measurements. Regions of interest (ROIs) at
liver and muscle were measured using Advantage workstation.
Finally, the R2* was obtained by a linear regression of ln(sı) on TE.
The results showed that the longer the echo time, the smaller the signal
intensity. The R2* values of liver and muscle were 44.8 ± 10.9 s-1 and
37.4 ± 9.5 s-1, respectively. It implies that the iron concentration of
liver is higher than that of muscle. In conclusion, the more the iron
contents in tissue, the higher the R2*. The correlations between R2*
and iron content in NZW rabbits might be valuable for further
exploration.
Abstract: Chatter vibrations, occurring during cutting process,
cause vibration between the cutting tool and workpiece, which
deteriorates surface roughness and reduces tool life. The purpose of
this study is to investigate the influence of cutting parameters and
tool construction on surface roughness and vibration in turning of
aluminum alloy AA2024. A new design of cutting tool is proposed,
which is filled up with epoxy granite in order to improve damping
capacity of the tool. Experiments were performed at the lathe using
carbide cutting insert coated with TiC and two different cutting tools
made of AISI 5140 steel. Taguchi L9 orthogonal array was applied to
design of experiment and to optimize cutting conditions. By the help
of signal-to-noise ratio and analysis of variance the optimal cutting
condition and the effect of the cutting parameters on surface
roughness and vibration were determined. Effectiveness of Taguchi
method was verified by confirmation test. It was revealed that new
cutting tool with epoxy granite has reduced vibration and surface
roughness due to high damping properties of epoxy granite in
toolholder.
Abstract: Introduction: Whole-Body Vibration (WBV) uses
high frequency mechanical stimuli generated by a vibration plate and
transmitted through bone, muscle and connective tissues to the whole
body. Research has shown that long-term vibration-plate training
improves neuromuscular facilitation, especially in afferent neural
pathways, responsible for the conduction of vibration and
proprioceptive stimuli, muscle function, balance and proprioception.
Some researchers suggest that the vibration stimulus briefly inhibits
the conduction of afferent signals from proprioceptors and can
interfere with the maintenance of body balance. The aim of this study
was to evaluate the influence of a single set of exercises associated
with whole-body vibration on the joint position sense and body
balance. Material and methods: The study enrolled 55 people aged
19-24 years. These individuals were randomly divided into a test
group (30 persons) and a control group (25 persons). Both groups
performed the same set of exercises on a vibration plate. The
following vibration parameters: frequency of 20Hz and amplitude of
3mm, were used in the test group. The control group performed
exercises on the vibration plate while it was off. All participants were
instructed to perform six dynamic exercises lasting 30 seconds each
with a 60-second period of rest between them. The exercises involved
large muscle groups of the trunk, pelvis and lower limbs.
Measurements were carried out before and immediately after
exercise. Joint position sense (JPS) was measured in the knee joint
for the starting position at 45° in an open kinematic chain. JPS error
was measured using a digital inclinometer. Balance was assessed in a
standing position with both feet on the ground with the eyes open and
closed (each test lasting 30 sec). Balance was assessed using Matscan
with FootMat 7.0 SAM software. The surface of the ellipse of
confidence and front-back as well as right-left swing were measured
to assess balance. Statistical analysis was performed using Statistica
10.0 PL software. Results: There were no significant differences
between the groups, both before and after the exercise (p> 0.05). JPS
did not change in both the test (10.7° vs. 8.4°) and control groups
(9.0° vs. 8.4°). No significant differences were shown in any of the
test parameters during balance tests with the eyes open or closed in
both the test and control groups (p> 0.05). Conclusions: 1.
Deterioration in proprioception or balance was not observed
immediately after the vibration stimulus. This suggests that vibrationinduced
blockage of proprioceptive stimuli conduction can have only
a short-lasting effect that occurs only as long as a vibration stimulus
is present. 2. Short-term use of vibration in treatment does not impair
proprioception and seems to be safe for patients with proprioceptive
impairment. 3. These results need to be supplemented with an
assessment of proprioception during the application of vibration
stimuli. Additionally, the impact of vibration parameters used in the
exercises should be evaluated.
Abstract: Brain-Computer Interfaces (BCIs) measure brain
signals activity, intentionally and unintentionally induced by users,
and provides a communication channel without depending on the
brain’s normal peripheral nerves and muscles output pathway.
Feature Selection (FS) is a global optimization machine learning
problem that reduces features, removes irrelevant and noisy data
resulting in acceptable recognition accuracy. It is a vital step
affecting pattern recognition system performance. This study presents
a new Binary Particle Swarm Optimization (BPSO) based feature
selection algorithm. Multi-layer Perceptron Neural Network
(MLPNN) classifier with backpropagation training algorithm and
Levenberg-Marquardt training algorithm classify selected features.
Abstract: Wireless Sensor Networks (WSNs), which sense
environmental data with battery-powered nodes, require multi-hop
communication. This power-demanding task adds an extra workload
that is unfairly distributed across the network. As a result, nodes run
out of battery at different times: this requires an impractical
individual node maintenance scheme. Therefore we investigate a new
Cooperative Sensing approach that extends the WSN operational life
and allows a more practical network maintenance scheme (where all
nodes deplete their batteries almost at the same time). We propose a
novel cooperative algorithm that derives a piecewise representation
of the sensed signal while controlling approximation accuracy.
Simulations show that our algorithm increases WSN operational life
and spreads communication workload evenly. Results convey a
counterintuitive conclusion: distributing workload fairly amongst
nodes may not decrease the network power consumption and yet
extend the WSN operational life. This is achieved as our cooperative
approach decreases the workload of the most burdened cluster in the
network.
Abstract: In this paper, a novel Linear Feedback Shift Register
(LFSR) with Look Ahead Clock Gating (LACG) technique is
presented to reduce the power consumption in modern processors
and System-on-Chip. Clock gating is a predominant technique used
to reduce unwanted switching of clock signals. Several clock gating
techniques to reduce the dynamic power have been developed, of
which LACG is predominant. LACG computes the clock enabling
signals of each flip-flop (FF) one cycle ahead of time, based on the
present cycle data of the flip-flops on which it depends. It overcomes
the timing problems in the existing clock gating methods like datadriven
clock gating and Auto-Gated flip-flops (AGFF) by allotting a
full clock cycle for the determination of the clock enabling signals.
Further to reduce the power consumption in LACG technique, FFs
can be grouped so that they share a common clock enabling signal.
Simulation results show that the novel grouped LFSR with LACG
achieves 15.03% power savings than conventional LFSR with LACG
and 44.87% than data-driven clock gating.
Abstract: Cancer is still one of the serious diseases threatening
the lives of human beings. How to have an early diagnosis and
effective treatment for tumors is a very important issue. The animal
carcinoma model can provide a simulation tool for the studies of
pathogenesis, biological characteristics, and therapeutic effects.
Recently, drug delivery systems have been rapidly developed to
effectively improve the therapeutic effects. Liposome plays an
increasingly important role in clinical diagnosis and therapy for
delivering a pharmaceutic or contrast agent to the targeted sites.
Liposome can be absorbed and excreted by the human body, and is
well known that no harm to the human body. This study aimed to
compare the therapeutic effects between encapsulated (doxorubicin
liposomal, Lipodox) and un-encapsulated (doxorubicin, Dox)
anti-tumor drugs using magnetic resonance imaging (MRI).
Twenty-four New Zealand rabbits implanted with VX2 carcinoma at
left thighs were classified into three groups: control group (untreated),
Dox-treated group, and LipoDox-treated group, 8 rabbits for each
group. MRI scans were performed three days after tumor implantation.
A 1.5T GE Signa HDxt whole body MRI scanner with a high
resolution knee coil was used in this study. After a 3-plane localizer
scan was performed, three-dimensional (3D) fast spin echo (FSE)
T2-weighted Images (T2WI) was used for tumor volumetric
quantification. Afterwards, two-dimensional (2D) spoiled gradient
recalled echo (SPGR) dynamic contrast-enhanced (DCE) MRI was
used for tumor perfusion evaluation. DCE-MRI was designed to
acquire four baseline images, followed by contrast agent Gd-DOTA
injection through the ear vein of rabbit. A series of 32 images were
acquired to observe the signals change over time in the tumor and
muscle. The MRI scanning was scheduled on a weekly basis for a
period of four weeks to observe the tumor progression longitudinally.
The Dox and LipoDox treatments were prescribed 3 times in the first
week immediately after the first MRI scan; i.e. 3 days after VX2 tumor
implantation. ImageJ was used to quantitate tumor volume and time
course signal enhancement on DCE images. The changes of tumor size
showed that the growth of VX2 tumors was effectively inhibited for
both LipoDox-treated and Dox-treated groups. Furthermore, the tumor
volume of LipoDox-treated group was significantly lower than that of
Dox-treated group, which implies that LipoDox has better therapeutic effect than Dox. The signal intensity of LipoDox-treated group is
significantly lower than that of the other two groups, which implies
that targeted therapeutic drug remained in the tumor tissue. This study
provides a radiation-free and non-invasive MRI method for
therapeutic monitoring of targeted liposome on an animal tumor
model.
Abstract: The relationship dependence between RSS and distance
in an enclosed environment is an important consideration because it is
a factor that can influence the reliability of any localization algorithm
founded on RSS. Several algorithms effectively reduce the variance of
RSS to improve localization or accuracy performance. Our proposed
algorithm essentially avoids this pitfall and consequently, its high
adaptability in the face of erratic radio signal. Using 3 anchors in
close proximity of each other, we are able to establish that RSS can be
used as reliable indicator for localization with an acceptable degree of
accuracy. Inherent in this concept, is the ability for each prospective
anchor to validate (guarantee) the position or the proximity of the
other 2 anchors involved in the localization and vice versa. This
procedure ensures that the uncertainties of radio signals due to
multipath effects in enclosed environments are minimized. A major
driver of this idea is the implicit topological relationship among
sensors due to raw radio signal strength. The algorithm is an area
based algorithm; however, it does not trade accuracy for precision
(i.e the size of the returned area).
Abstract: Multiple Input Multiple Output (MIMO) systems are
wireless systems with multiple antenna elements at both ends of the
link. Wireless communication systems demand high data rate and
spectral efficiency with increased reliability. MIMO systems have
been popular techniques to achieve these goals because increased
data rate is possible through spatial multiplexing scheme and
diversity. Spatial Multiplexing (SM) is used to achieve higher
possible throughput than diversity. In this paper, we propose a Zero-
Forcing (ZF) detection using a combination of Ordered Successive
Interference Cancellation (OSIC) and Zero Forcing using
Interference Cancellation (ZF-IC). The proposed method used an
OSIC based on Signal to Noise Ratio (SNR) ordering to get the
estimation of last symbol, then the estimated last symbol is
considered to be an input to the ZF-IC. We analyze the Bit Error Rate
(BER) performance of the proposed MIMO system over Rayleigh
Fading Channel, using Binary Phase Shift Keying (BPSK)
modulation scheme. The results show better performance than the
previous methods.
Abstract: Current study established for EEG signal analysis in
patients with language disorder. Language disorder can be defined as
meaningful delay in the use or understanding of spoken or written
language. The disorder can include the content or meaning of
language, its form, or its use. Here we applied Z-score, power
spectrum, and coherence methods to discriminate the language
disorder data from healthy ones. Power spectrum of each channel in
alpha, beta, gamma, delta, and theta frequency bands was measured.
In addition, intra hemispheric Z-score obtained by scoring algorithm.
Obtained results showed high Z-score and power spectrum in
posterior regions. Therefore, we can conclude that peoples with
language disorder have high brain activity in frontal region of brain
in comparison with healthy peoples. Results showed that high coherence correlates with irregularities
in the ERP and is often found during complex task, whereas low
coherence is often found in pathological conditions. The results of the
Z-score analysis of the brain dynamics showed higher Z-score peak
frequency in delta, theta and beta sub bands of Language Disorder
patients. In this analysis there were activity signs in both hemispheres
and the left-dominant hemisphere was more active than the right.
Abstract: An analytical 4-DOF nonlinear model of a de Laval
rotor-stator system based on Energy Principles has been used
theoretically and experimentally to investigate fault symptoms in a
rotating system. The faults, namely rotor-stator-rub, crack and
unbalance are modeled as excitations on the rotor shaft. Mayes
steering function is used to simulate the breathing behaviour of the
crack. The fault analysis technique is based on waveform signal,
orbits and Fast Fourier Transform (FFT) derived from simulated and
real measured signals. Simulated and experimental results manifest
considerable mutual resemblance of elliptic-shaped orbits and FFT
for a same range of test data.
Abstract: Nonlinear evolution of broadband ultrasonic pulses
passed through the rock specimens is studied using the apparatus
“GEOSCAN-02M”. Ultrasonic pulses are excited by the pulses of Qswitched
Nd:YAG laser with the time duration of 10 ns and with the
energy of 260 mJ. This energy can be reduced to 20 mJ by some light
filters. The laser beam radius did not exceed 5 mm. As a result of the
absorption of the laser pulse in the special material – the optoacoustic
generator–the pulses of longitudinal ultrasonic waves are excited with
the time duration of 100 ns and with the maximum pressure
amplitude of 10 MPa. The immersion technique is used to measure
the parameters of these ultrasonic pulses passed through a specimen,
the immersion liquid is distilled water. The reference pulse passed
through the cell with water has the compression and the rarefaction
phases. The amplitude of the rarefaction phase is five times lower
than that of the compression phase. The spectral range of the
reference pulse reaches 10 MHz. The cubic-shaped specimens of the
Karelian gabbro are studied with the rib length 3 cm. The ultimate
strength of the specimens by the uniaxial compression is (300±10)
MPa. As the reference pulse passes through the area of the specimen
without cracks the compression phase decreases and the rarefaction
one increases due to diffraction and scattering of ultrasound, so the
ratio of these phases becomes 2.3:1. After preloading some horizontal
cracks appear in the specimens. Their location is found by one-sided
scanning of the specimen using the backward mode detection of the
ultrasonic pulses reflected from the structure defects. Using the
computer processing of these signals the images are obtained of the
cross-sections of the specimens with cracks. By the increase of the
reference pulse amplitude from 0.1 MPa to 5 MPa the nonlinear
transformation of the ultrasonic pulse passed through the specimen
with horizontal cracks results in the decrease by 2.5 times of the
amplitude of the rarefaction phase and in the increase of its duration
by 2.1 times. By the increase of the reference pulse amplitude from 5
MPa to 10 MPa the time splitting of the phases is observed for the
bipolar pulse passed through the specimen. The compression and
rarefaction phases propagate with different velocities. These features
of the powerful broadband ultrasonic pulses passed through the rock
specimens can be described by the hysteresis model of Preisach-
Mayergoyz and can be used for the location of cracks in the optically
opaque materials.
Abstract: Heart is the most important part in the body of living
organisms. It affects and is affected by any factor in the body.
Therefore, it is a good detector for all conditions in the body. Heart
signal is a non-stationary signal; thus, it is utmost important to study
the variability of heart signal. The Heart Rate Variability (HRV) has
attracted considerable attention in psychology, medicine and has
become important dependent measure in psychophysiology and
behavioral medicine. The standards of measurements, physiological
interpretation and clinical use for HRV that are most often used were
described in many researcher papers, however, remain complex
issues are fraught with pitfalls. This paper presents one of the nonlinear
techniques to analyze HRV. It discusses many points like, what
Poincaré plot is and how Poincaré plot works; also, Poincaré plot's
merits especially in HRV. Besides, it discusses the limitation of
Poincaré cause of standard deviation SD1, SD2 and how to overcome
this limitation by using complex correlation measure (CCM). The
CCM is most sensitive to changes in temporal structure of the
Poincaré plot as compared toSD1 and SD2.