Abstract: In this paper, we proposed an efficient data
compression strategy exploiting the multi-resolution characteristic of
the wavelet transform. We have developed a sensor node called
“Smart Sensor Node; SSN". The main goals of the SSN design are
lightweight, minimal power consumption, modular design and robust
circuitry. The SSN is made up of four basic components which are a
sensing unit, a processing unit, a transceiver unit and a power unit.
FiOStd evaluation board is chosen as the main controller of the SSN
for its low costs and high performance. The software coding of the
implementation was done using Simulink model and MATLAB
programming language. The experimental results show that the
proposed data compression technique yields recover signal with good
quality. This technique can be applied to compress the collected data
to reduce the data communication as well as the energy consumption
of the sensor and so the lifetime of sensor node can be extended.
Abstract: This paper describes a low-voltage and low-power
channel selection analog front end with continuous-time low pass
filters and highly linear programmable gain amplifier (PGA). The
filters were realized as balanced Gm-C biquadratic filters to achieve a
low current consumption. High linearity and a constant wide
bandwidth are achieved by using a new transconductance (Gm) cell.
The PGA has a voltage gain varying from 0 to 65dB, while
maintaining a constant bandwidth. A filter tuning circuit that requires
an accurate time base but no external components is presented.
With a 1-Vrms differential input and output, the filter achieves
-85dB THD and a 78dB signal-to-noise ratio. Both the filter and PGA
were implemented in a 0.18um 1P6M n-well CMOS process. They
consume 3.2mW from a 1.8V power supply and occupy an area of
0.19mm2.
Abstract: Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements.
Abstract: The hydraulic actuated excavator, being a non-linear
mobile machine, encounters many uncertainties. There are
uncertainties in the hydraulic system in addition to the uncertain
nature of the load. The simulation results obtained in this study show
that there is a need for intelligent control of such machines and in
particular interval type-2 fuzzy controller is most suitable for
minimizing the position error of a typical excavator-s bucket under
load variations. We consider the model parameter uncertainties such
as hydraulic fluid leakage and friction. These are uncertainties which
also depend up on the temperature and alter bulk modulus and
viscosity of the hydraulic fluid. Such uncertainties together with the
load variations cause chattering of the bucket position. The interval
type-2 fuzzy controller effectively eliminates the chattering and
manages to control the end-effecter (bucket) position with positional
error in the order of few millimeters.
Abstract: This paper presents a method for the optimal
allocation of Distributed generation in distribution systems. In this
paper, our aim would be optimal distributed generation allocation for
voltage profile improvement and loss reduction in distribution
network. Genetic Algorithm (GA) was used as the solving tool,
which referring two determined aim; the problem is defined and
objective function is introduced. Considering to fitness values
sensitivity in genetic algorithm process, there is needed to apply load
flow for decision-making. Load flow algorithm is combined
appropriately with GA, till access to acceptable results of this
operation. We used MATPOWER package for load flow algorithm
and composed it with our Genetic Algorithm. The suggested method
is programmed under MATLAB software and applied ETAP
software for evaluating of results correctness. It was implemented on
part of Tehran electricity distributing grid. The resulting operation of
this method on some testing system is illuminated improvement of
voltage profile and loss reduction indexes.
Abstract: During the year 1999, Serbia (ex Yugoslavia) and their northern province, Vojvodina, has been bombarded. Because of that general public believe is that this region was contaminated by depleted uranium and that there is a potential contaminant of agricultural products due to soil radioactivity. This paper presents the repeated analysis of agricultural soil samples in Vojvodina. The same investigation was carried out during the year 2001, and it was concluded that, based on the gamma-spectrometric analysis of 50 soil samples taken from the region of Vojvodina, there haven-t been registered any increase of radioactivity that could endanger the food production. We continue with the monitoring of this region. The comparison between those two sets of results is presented.
Abstract: The presented article deals with the description of a
numerical model of a corridor at a Central Interim Spent Fuel Storage
Facility (hereinafter CISFSF). The model takes into account the
effect of air flows on the temperature of stored waste. The
computational model was implemented in the ANSYS/CFX
programming environment in the form of a CFD task solution, which
was compared with an approximate analytical calculation. The article
includes a categorization of the individual alternatives for the
ventilation of such underground systems. The aim was to evaluate a
ventilation system for a CISFSF with regard to its stability and
capacity to provide sufficient ventilation for the removal of heat
produced by stored casks with spent nuclear fuel.
Abstract: This research details a Computational Fluid Dynamics (CFD) approach to model fluid flow in a journal bearing with 8 equispaced semi-circular axial grooves. Water is used as the lubricant and is fed from one end of the bearing to the other, under pressure. The geometry of the bearing is modeled using a commercially available modeling software GAMBIT and the flow analysis is performed using a dedicated CFD analysis software FLUENT. The pressure distribution in the bearing clearance is obtained from FLUENT for various whirl ratios and is used to calculate the hydrodynamic force components in the radial and tangential direction of the bearing. These values along with the various whirl speeds can be used to do a regression analysis to determine the stiffness and damping coefficients. The values obtained are then compared with the stiffness and damping coefficients of a 3 Axial groove water lubricated journal bearing and those obtained from a FORTRAN code for a similar bearing.
Abstract: The utility of expert system generators has been
widely recognized in many applications. Several generators based on
concept of the paradigm object, have been recently proposed. The
generator of oriented object expert system (GSEOO) offers
languages that are often complex and difficult to use. We propose in
this paper an extension of the expert system generator, JESS, which
permits a friendly use of this expert system. The new tool, called
VISUAL JESS, bring two main improvements to JESS. The first
improvement concerns the easiness of its utilization while giving
back transparency to the syntax and semantic aspects of the JESS
programming language. The second improvement permits an easy
access and modification of the JESS knowledge basis. The
implementation of VISUAL JESS is made so that it is extensible and
portable.
Abstract: Herein, the organic semiconductor methyl orange
(MO), is investigated for the first time for its electronic applications.
For this purpose, Al/MO/n-Si heterojunction is fabricated through
economical cheap and simple “drop casting” technique. The currentvoltage
(I-V) measurements of the device are made at room
temperature under dark conditions. The I-V characteristics of
Al/MO/n-Si junction exhibits asymmetrical and rectifying behavior
that confirms the formation of diode. The diode parameters such as
rectification ratio (RR), turn on voltage (Vturn on), reverse saturation
current (I0), ideality factor (n), barrier height ( b
f ), series resistance
(Rs) and shunt resistance (Rsh) are determined from I-V curves using
Schottky equations. These values of these parameters are also
extracted and verified by applying Cheung’s functions. The
conduction mechanisms are explained from the forward bias I-V
characteristics using the power law.
Abstract: The purpose of this paper is to demonstrate the ability
of a genetic programming (GP) algorithm to evolve a team of data
classification models. The GP algorithm used in this work is
“multigene" in nature, i.e. there are multiple tree structures (genes)
that are used to represent team members. Each team member assigns
a data sample to one of a fixed set of output classes. A majority vote,
determined using the mode (highest occurrence) of classes predicted
by the individual genes, is used to determine the final class
prediction. The algorithm is tested on a binary classification problem.
For the case study investigated, compact classification models are
obtained with comparable accuracy to alternative approaches.
Abstract: This paper investigates the development of weld zone
in Resistance Spot Welding (RSW) which focuses on weld nugget and Heat Affected Zone (HAZ). The effects of four factors namely
weld current, weld time, electrode force and hold time were studied using a general 24 factorial design augmented by five centre points. The results of the analysis showed that all selected factors except
hold time exhibit significant effect on weld nugget radius and HAZ size. Optimization of the welding parameters (weld current, weld
time and electrode force) to normalize weld nugget and to minimize
HAZ size was then conducted using Central Composite Design (CCD) in Response Surface Methodology (RSM) and the optimum
parameters were determined. A regression model for radius of weld nugget and HAZ size was developed and its adequacy was evaluated.
The experimental results obtained under optimum operating conditions were then compared with the predicted values and were
found to agree satisfactorily with each other
Abstract: Heat source addition to the axisymmetric supersonic
inlet may improve the performance parameters, which will increase
the inlet efficiency. In this investigation the heat has been added to
the flow field at some distance ahead of an axisymmetric inlet by
adding an imaginary thermal source upstream of cowl lip. The effect
of heat addition on the drag coefficient, mass flow rate and the
overall efficiency of the inlet have been investigated. The results
show that heat addition causes flow separation, hence to prevent this
phenomena, roughness has been added on the spike surface.
However, heat addition reduces the drag coefficient and the inlet
mass flow rate considerably. Furthermore, the effects of position,
size, and shape on the inlet performance were studied. It is found that
the thermal source deflects the flow streamlines. By improper
location of the thermal source, the optimum condition has been
obtained. For the optimum condition, the drag coefficient is
considerably reduced and the inlet mass flow rate and its efficiency
have been increased slightly. The optimum shape of the heat source
is obtained too.
Abstract: Mammals are known to use Interaural Intensity Difference (IID) to determine azimuthal position of high frequency sounds. In the Lateral Superior Olive (LSO) neurons have firing behaviours which vary systematicaly with IID. Those neurons receive excitatory inputs from the ipsilateral ear and inhibitory inputs from the contralateral one. The IID sensitivity of a LSO neuron is thought to be due to delay differences between both ears, delays due to different synaptic delays and to intensity-dependent delays. In this paper we model the auditory pathway until the LSO. Inputs to LSO neurons are at first numerous and differ in their relative delays. Spike Timing-Dependent Plasticity is then used to prune those connections. We compare the pruned neuron responses with physiological data and analyse the relationship between IID-s of teacher stimuli and IID sensitivities of trained LSO neurons.
Abstract: This paper details the application of a genetic
programming framework for induction of useful classification rules
from a database of income statements, balance sheets, and cash flow
statements for North American public companies. Potentially
interesting classification rules are discovered. Anomalies in the
discovery process merit further investigation of the application of
genetic programming to the dataset for the problem domain.
Abstract: In the present study, 49 Hybrid (Catla catla ♂ x
Labeo rohita ♀) were sampled from Al-Raheem Fish Hatchery,
Village Ali Pure Shamali, Jhang Road, 18 Km from Muzaffar Garh
using a cast net and Live fishes were transported to research
laboratory. Mean percentage for water found 79.13 %, ash 6.58 %, fat
2.22 % and protein content 12.06 % in whole wet body weight. It was
observed that body constituents were found increasing in the same
proportion with an increase in body weight while significant
proportional increase was observed with total length. However,
condition factor remained insignificant (P>0.05) with body
constituents.
Abstract: Distance visualization of large datasets often takes the direction of remote viewing and zooming techniques of stored static images. However, the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop computers. Additionally, the visualization techniques such as Isosurface depend on the available resources of the running machine and the size of datasets. Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. On top of that, different output devices and different network bandwidth between the visualization pipeline components often result output suitable for one machine and not suitable for another. In this paper we investigate how the grid services could be used to support remote visualization of large datasets and to break the constraint of physical co-location of the resources by applying the grid computing technologies. We show our grid enabled architecture to visualize large medical datasets (circa 5 million polygons) for remote interactive visualization on modest resources clients.
Abstract: This paper introduces a technique of distortion
estimation in image watermarking using Genetic Programming (GP).
The distortion is estimated by considering the problem of obtaining a
distorted watermarked signal from the original watermarked signal as
a function regression problem. This function regression problem is
solved using GP, where the original watermarked signal is
considered as an independent variable. GP-based distortion
estimation scheme is checked for Gaussian attack and Jpeg
compression attack. We have used Gaussian attacks of different
strengths by changing the standard deviation. JPEG compression
attack is also varied by adding various distortions. Experimental
results demonstrate that the proposed technique is able to detect the
watermark even in the case of strong distortions and is more robust
against attacks.
Abstract: Autism spectrum disorder is characterized by
abnormalities in social communication, language abilities and
repetitive behaviors. The present study focused on some grammatical
deficits in autistic children. We evaluated the impairment of correct
use of different Persian verb tenses in autistic children-s speech. Two
standardized Language Test were administered then gathered data
were analyzed. The main result of this study was significant
difference between the mean scores of correct responses to present
tense in comparison with past tense in Persian language. This study
demonstrated that tense is severely impaired in autistic children-s
speech. Our findings indicated those autistic children-s production of
simple present/ past tense opposition to be better than production of
future and past periphrastic forms (past perfect, present perfect, past
progressive).
Abstract: This study introduces a new method for detecting,
sorting, and localizing spikes from multiunit EEG recordings. The
method combines the wavelet transform, which localizes distinctive
spike features, with Super-Paramagnetic Clustering (SPC) algorithm,
which allows automatic classification of the data without assumptions
such as low variance or Gaussian distributions. Moreover, the method
is capable of setting amplitude thresholds for spike detection. The
method makes use of several real EEG data sets, and accordingly the
spikes are detected, clustered and their times were detected.