Abstract: This work aims to generalize the integer order Sallen-Key filters into the fractional-order domain. The analysis in the case of two different fractional-order elements introduced where the general transfer function becomes four terms which is unusual in the conventional case. In addition, the effect of the transfer function parameters on the filter poles and hence the stability is introduced and closed forms for the filter critical frequencies are driven. Finally, different examples for the fractional order Sallen-Key filter design are presented with circuit simulations using ADS where a great matching between the numerical and simulation results is obtained.
Abstract: In this paper, we present a comparative study of the
genetic algorithms and Hessian-s methods for optimal research of the
active powers in an electric network of power. The objective function
which is the performance index of production of electrical energy is
minimized by satisfying the constraints of the equality type and
inequality type initially by the Hessian-s methods and in the second
time by the genetic Algorithms. The results found by the application
of AG for the minimization of the electric production costs of power
are very encouraging. The algorithms seem to be an effective
technique to solve a great number of problems and which are in
constant evolution. Nevertheless it should be specified that the
traditional binary representation used for the genetic algorithms
creates problems of optimization of management of the large-sized
networks with high numerical precision.
Abstract: Learning the gradient of neuron's activity function
like the weight of links causes a new specification which is
flexibility. In flexible neural networks because of supervising and
controlling the operation of neurons, all the burden of the learning is
not dedicated to the weight of links, therefore in each period of
learning of each neuron, in fact the gradient of their activity function,
cooperate in order to achieve the goal of learning thus the number of
learning will be decreased considerably.
Furthermore, learning neurons parameters immunes them against
changing in their inputs and factors which cause such changing.
Likewise initial selecting of weights, type of activity function,
selecting the initial gradient of activity function and selecting a fixed
amount which is multiplied by gradient of error to calculate the
weight changes and gradient of activity function, has a direct affect
in convergence of network for learning.
Abstract: We have investigated statistical properties of the defect turbulence in 1D CGLE wherein many body interaction is involved between local depressing wave (LDW) and local standing wave (LSW). It is shown that the counting number fluctuation of LDW is subject to the sub-Poisson statistics (SUBP). The physical origin of the SUBP can be ascribed to pair extinction of LDWs based on the master equation approach. It is also shown that the probability density function (pdf) of inter-LDW distance can be identified by the hyper gamma distribution. Assuming a superstatistics of the exponential distribution (Poisson configuration), a plausible explanation is given. It is shown further that the pdf of amplitude of LDW has a fattail. The underlying mechanism of its fluctuation is examined by introducing a generalized fractional Poisson configuration.
Abstract: Papaya and banana bars were developed incorporating
inulin (IN) and fructooligosaccharides (FOS) (Liquid and Powder
form) in various proportions. The control bars were standardized
using 70% fruit pulp, 30% sugar, 0.3% citric acid while the treated
bars were standardized with 70% fruit pulp, 15% sugar, 15% of IN
and FOS and 0.3% citric acid. Among the various proportions tested,
papaya bars with 90% FOS (Powder) + 10% IN and banana bars with
90% FOS (liquid) + 10% IN were sensorially best accepted. The
study revealed that addition of IN and FOS improved the sensory
scores. The Physico-chemical and proximatecomposition analysis
revealed slight changes in brix°, total sugars, reducing sugars, nonreducing
sugars, moisture, protein, fat, vitamin C, ash, iron,
zinc, calcium and crude fibre between control and treated fruit bars.
Further the glycemic index of papaya bar was reduced from 65 to 54
when treated with FOS and IN.
Abstract: A reconfigurable manufacturing system (RMS) is an
advanced system designed at the outset for rapid changes in its hardware
and software components in order to quickly adjust its production
capacity and functionally. Among various operational decisions, this
study considers the scheduling problem that determines the input
sequence and schedule at the same time for a given set of parts. In
particular, we consider the practical constraints that the numbers of
pallets/fixtures are limited and hence a part can be released into the
system only when the fixture required for the part is available. To
solve the integrated input sequencing and scheduling problems, we
suggest a priority rule based approach in which the two sub-problems
are solved using a combination of priority rules. To show the effectiveness
of various rule combinations, a simulation experiment was
done on the data for a real RMS, and the test results are reported.
Abstract: This paper presents a customized deformable model
for the segmentation of abdominal and thoracic aortic aneurysms in
CTA datasets. An important challenge in reliably detecting aortic
aneurysm is the need to overcome problems associated with intensity
inhomogeneities and image noise. Level sets are part of an important
class of methods that utilize partial differential equations (PDEs) and
have been extensively applied in image segmentation. A Gaussian
kernel function in the level set formulation, which extracts the local
intensity information, aids the suppression of noise in the extracted
regions of interest and then guides the motion of the evolving contour
for the detection of weak boundaries. The speed of curve evolution
has been significantly improved with a resulting decrease in
segmentation time compared with previous implementations of level
sets. The results indicate the method is more effective than other
approaches in coping with intensity inhomogeneities.
Abstract: An efficient reintegration of the disabled people in the
family and society should be fulfilled; hence it is strongly needful to assist their diminished functions or to replace the totally lost
functions. Assistive technology helps in neutralizing the impairment.
Recent advancements in embedded systems have opened up a vast
area of research and development for affordable and portable assistive devices for the visually impaired. Granted there are many assistive devices on the market that are able to detect obstacles, and numerous research and development currently in process to
alleviate the cause, unfortunately the cost of devices, size of
devices, intrusiveness and higher learning curve prevents the visually impaired from taking advantage of available devices. This
project aims at the design and implementation of a detachable unit
which is robust, low cost and user friendly, thus, trying to
aggrandize the functionality of the existing white cane, to concede above-knee obstacle detection. The designed obstruction detector
uses ultrasound sensors for detecting the obstructions before direct contact. It bestows haptic feedback to the user in accordance with the position of the obstacle.
Abstract: In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment.
Abstract: This paper presents an evolutionary method for designing
electronic circuits and numerical methods associated with
monitoring systems. The instruments described here have been used
in studies of weather and climate changes due to global warming, and
also in medical patient supervision. Genetic Programming systems
have been used both for designing circuits and sensors, and also for
determining sensor parameters. The authors advance the thesis that
the software side of such a system should be written in computer
languages with a strong mathematical and logic background in order
to prevent software obsolescence, and achieve program correctness.
Abstract: The performance of the Optical Code Division Multiplexing/ Wavelength Division Multiplexing (WDM/OCDM) technique for Optical Packet Switch is investigated. The impact on the performance of the impairment due to both Multiple Access Interference and Beat noise is studied. The Packet Loss Probability due to output packet contentions is evaluated as a function of the main switch and traffic parameters when Gold coherent optical codes are adopted. The Packet Loss Probability of the OCDM/WDM switch can reach 10-9 when M=16 wavelengths, Gold code of length L=511 and only 24 wavelength converters are used in the switch.
Abstract: This paper presents a new compact analytical model of
the gate leakage current in high-k based nano scale MOSFET by
assuming a two-step inelastic trap-assisted tunneling (ITAT) process
as the conduction mechanism. This model is based on an inelastic
trap-assisted tunneling (ITAT) mechanism combined with a semiempirical
gate leakage current formulation in the BSIM 4 model. The
gate tunneling currents have been calculated as a function of gate
voltage for different gate dielectrics structures such as HfO2, Al2O3
and Si3N4 with EOT (equivalent oxide thickness) of 1.0 nm. The
proposed model is compared and contrasted with santaurus
simulation results to verify the accuracy of the model and excellent
agreement is found between the analytical and simulated data. It is
observed that proposed analytical model is suitable for different highk
gate dielectrics simply by adjusting two fitting parameters. It was
also shown that gate leakages reduced with the introduction of high-k
gate dielectric in place of SiO2.
Abstract: Utilizing echoic intension and distribution from different organs and local details of human body, ultrasonic image can catch important medical pathological changes, which unfortunately may be affected by ultrasonic speckle noise. A feature preserving ultrasonic image denoising and edge enhancement scheme is put forth, which includes two terms: anisotropic diffusion and edge enhancement, controlled by the optimum smoothing time. In this scheme, the anisotropic diffusion is governed by the local coordinate transformation and the first and the second order normal derivatives of the image, while the edge enhancement is done by the hyperbolic tangent function. Experiments on real ultrasonic images indicate effective preservation of edges, local details and ultrasonic echoic bright strips on denoising by our scheme.
Abstract: The software evolution control requires a deep
understanding of the changes and their impact on different system
heterogeneous artifacts. And an understanding of descriptive
knowledge of the developed software artifacts is a prerequisite
condition for the success of the evolutionary process.
The implementation of an evolutionary process is to make changes
more or less important to many heterogeneous software artifacts such
as source code, analysis and design models, unit testing, XML
deployment descriptors, user guides, and others. These changes can
be a source of degradation in functional, qualitative or behavioral
terms of modified software. Hence the need for a unified approach
for extraction and representation of different heterogeneous artifacts
in order to ensure a unified and detailed description of heterogeneous
software artifacts, exploitable by several software tools and allowing
to responsible for the evolution of carry out the reasoning change
concerned.
Abstract: Nowadays, more engineering systems are using some
kind of Artificial Intelligence (AI) for the development of their
processes. Some well-known AI techniques include artificial neural
nets, fuzzy inference systems, and neuro-fuzzy inference systems
among others. Furthermore, many decision-making applications base
their intelligent processes on Fuzzy Logic; due to the Fuzzy
Inference Systems (FIS) capability to deal with problems that are
based on user knowledge and experience. Also, knowing that users
have a wide variety of distinctiveness, and generally, provide
uncertain data, this information can be used and properly processed
by a FIS. To properly consider uncertainty and inexact system input
values, FIS normally use Membership Functions (MF) that represent
a degree of user satisfaction on certain conditions and/or constraints.
In order to define the parameters of the MFs, the knowledge from
experts in the field is very important. This knowledge defines the MF
shape to process the user inputs and through fuzzy reasoning and
inference mechanisms, the FIS can provide an “appropriate" output.
However an important issue immediately arises: How can it be
assured that the obtained output is the optimum solution? How can it
be guaranteed that each MF has an optimum shape? A viable solution
to these questions is through the MFs parameter optimization. In this
Paper a novel parameter optimization process is presented. The
process for FIS parameter optimization consists of the five simple
steps that can be easily realized off-line. Here the proposed process
of FIS parameter optimization it is demonstrated by its
implementation on an Intelligent Interface section dealing with the
on-line customization / personalization of internet portals applied to
E-commerce.
Abstract: In this paper a study on the vibration of thin
cylindrical shells with ring supports and made of functionally
graded materials (FGMs) composed of stainless steel and
nickel is presented. Material properties vary along the
thickness direction of the shell according to volume fraction
power law. The cylindrical shells have ring supports which are
arbitrarily placed along the shell and impose zero lateral
deflections. The study is carried out based on third order shear
deformation shell theory (T.S.D.T). The analysis is carried out
using Hamilton-s principle. The governing equations of motion of
FGM cylindrical shells are derived based on shear deformation
theory. Results are presented on the frequency characteristics,
influence of ring support position and the influence of boundary
conditions. The present analysis is validated by comparing results
with those available in the literature.
Abstract: Ascorbic acid (AA), commonly known as vitamin C, is essential for normal functioning of the body and maintenance of metabolic integrity. Among its various roles are as an antioxidant, a cofactor in collagen formation and other reactions, as well as reducing physical stress and maintenance of the immune system. Recent collaborative research between the Australian Defence Science and Technology Organisation (DSTO) in Scottsdale, Tasmania and RMIT University has sought to overcome the problems arising from the inherent instability of ascorbic acid during processing and storage of foods. The recent work has demonstrated the potential of microencapsulation by spray drying as a means to enhance retention. The purpose of this current study has been focused upon the influence of spray drying conditions on the properties of encapsulated ascorbic acid. The process was carried out according to a central composite design. Independent variables were: inlet temperature (80-120° C) and feed flow rate (7-14 mL/minute). Process yield, ascorbic acid loss, moisture content, water activity and particle size distribution were analysed as responses. The results have demonstrated the potential of microencapsulation by spray drying as a means to enhance retention. Vitamin retention, moisture content, water activity and process yield were influenced positively by inlet air temperature and negatively by feed flow rate.
Abstract: Defect prevention is the most vital but habitually
neglected facet of software quality assurance in any project. If
functional at all stages of software development, it can condense the
time, overheads and wherewithal entailed to engineer a high quality
product. The key challenge of an IT industry is to engineer a
software product with minimum post deployment defects.
This effort is an analysis based on data obtained for five selected
projects from leading software companies of varying software
production competence. The main aim of this paper is to provide
information on various methods and practices supporting defect
detection and prevention leading to thriving software generation. The
defect prevention technique unearths 99% of defects. Inspection is
found to be an essential technique in generating ideal software
generation in factories through enhanced methodologies of abetted
and unaided inspection schedules. On an average 13 % to 15% of
inspection and 25% - 30% of testing out of whole project effort time
is required for 99% - 99.75% of defect elimination.
A comparison of the end results for the five selected projects
between the companies is also brought about throwing light on the
possibility of a particular company to position itself with an
appropriate complementary ratio of inspection testing.
Abstract: An adaptive dynamic cerebellar model articulation
controller (DCMAC) neural network used for solving the prediction
and identification problem is proposed in this paper. The proposed
DCMAC has superior capability to the conventional cerebellar model
articulation controller (CMAC) neural network in efficient learning
mechanism, guaranteed system stability and dynamic response. The
recurrent network is embedded in the DCMAC by adding feedback
connections in the association memory space so that the DCMAC
captures the dynamic response, where the feedback units act as
memory elements. The dynamic gradient descent method is adopted to
adjust DCMAC parameters on-line. Moreover, the analytical method
based on a Lyapunov function is proposed to determine the
learning-rates of DCMAC so that the variable optimal learning-rates
are derived to achieve most rapid convergence of identifying error.
Finally, the adaptive DCMAC is applied in two computer simulations.
Simulation results show that accurate identifying response and
superior dynamic performance can be obtained because of the
powerful on-line learning capability of the proposed DCMAC.
Abstract: In this paper, we present a non-blind technique of
adding the watermark to the Fourier spectral components of audio
signal in a way such that the modified amplitude does not exceed the
maximum amplitude spread (MAS). This MAS is due to individual
Discrete fourier transform (DFT) coefficients in that particular frame,
which is derived from the Energy Spreading function given by
Schroeder. Using this technique one can store double the information
within a given frame length i.e. overriding the watermark on the
host of equal length with least perceptual distortion. The watermark
is uniformly floating on the DFT components of original signal.
This helps in detecting any intentional manipulations done on the
watermarked audio. Also, the scheme is found robust to various signal
processing attacks like presence of multiple watermarks, Additive
white gaussian noise (AWGN) and mp3 compression.