Abstract: A novel design of two-wheeled robotic vehicle with moving payload is presented in this paper. A mathematical model describing the vehicle dynamics is derived and simulated in Matlab Simulink environment. Two control strategies were developed to stabilise the vehicle in the upright position. A robust Proportional- Integral-Derivative (PID) control strategy has been implemented and initially tested to measure the system performance, while the second control strategy is to use a hybrid fuzzy logic controller (FLC). The results are given on a comparative basis for the system performance in terms of disturbance rejection, control algorithms robustness as well as the control effort in terms of input torque.
Abstract: Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.
Abstract: Reliable information about tool temperature
distribution is of central importance in metal cutting. In this study,
tool-chip interface temperature was determined in cutting of ST37
steel workpiece by applying HSS as the cutting tool in dry turning.
Two different approaches were implemented for temperature
measuring: an embedded thermocouple (RTD) in to the cutting tool
and infrared (IR) camera. Comparisons are made between
experimental data and results of MSC.SuperForm and FLUENT
software.
An investigation of heat generation in cutting tool was performed
by varying cutting parameters at the stable cutting tool geometry and
results were saved in a computer; then the diagrams of tool
temperature vs. various cutting parameters were obtained. The
experimental results reveal that the main factors of the increasing
cutting temperature are cutting speed (V ), feed rate ( S ) and depth
of cut ( h ), respectively. It was also determined that simultaneously
change in cutting speed and feed rate has the maximum effect on
increasing cutting temperature.
Abstract: Using steelmaking slag as a raw material, aragonite superstructure product had been synthesized via an indirect CO2 mineral sequestration rout. It mainly involved two separate steps, in which the element of calcium is first selectively leached from steelmaking slag by a novel leaching media consisting of organic solvent Tributyl phosphate (TBP), acetic acid, and ultra-purity water, followed by enhanced carbonation in a separate step for aragonite superstructure production as well as efficiency recovery of leaching media. Based on the different leaching medium employed in the steelmaking slag leaching process, two typical products were collected from the enhanced carbonation step. The products were characterized by X-ray powder diffraction (XRD) and scanning electron microscopy (SEM), respectively. It reveals that the needle-like aragonite crystals self-organized into aragonite superstructure particles including aragonite microspheres as well as dumbbell-like spherical particles, can be obtained from the steelmaking slag with the purity over 99%.
Abstract: A common way to elude the signature-based Network Intrusion Detection System is based upon changing a recognizable attack to an unrecognizable one via the IDS. For example, in order to evade sign accommodation with intrusion detection system markers, a hacker spilt the payload packet into many small pieces or hides them within messages. In this paper we try to model the main fragmentation attack and create a new module in the intrusion detection architecture system which recognizes the main fragmentation attacks through verification of integrity checking of TCP packet in order to prevent elusion of the system and also to announce the necessary alert to the system administrator.
Abstract: The most reliable and accurate description of the actual behavior of a software system is its source code. However, not all questions about the system can be answered directly by resorting to this repository of information. What the reverse engineering methodology aims at is the extraction of abstract, goal-oriented “views" of the system, able to summarize relevant properties of the computation performed by the program. While concentrating on reverse engineering we had modeled the C++ files by designing the translator.
Abstract: A New features are extracted and compared to
improve the prediction of protein-protein interactions. The basic idea
is to select and use the best set of features from the Tensor matrices
that are produced by the frequency vectors of the protein sequences.
Three set of features are compared, the first set is based on the
indices that are the most common in the interacting proteins, the
second set is based on the indices that tend to be common in the
interacting and non-interacting proteins, and the third set is
constructed by using random indices. Moreover, three encoding
strategies are compared; that are based on the amino asides polarity,
structure, and chemical properties. The experimental results indicate
that the highest accuracy can be obtained by using random indices
with chemical properties encoding strategy and support vector
machine.
Abstract: This research is part of a broad program aimed at
advancing the science and technology involved in the rescue and
rehabilitation of oiled wildlife. One aspect of this research involves
the use of oil-sequestering magnetic particles for the removal of
contaminants from plumage – so-called “magnetic cleansing". This
treatment offers a number of advantages over conventional
detergent-based methods including portability - which offers the
possibility of providing a “quick clean" to the animal upon first
encounter in the field. This could be particularly advantageous
when the contaminant is toxic and/or corrosive and/or where there
is a delay in transporting the victim to a treatment centre. The
method could also be useful as part of a stabilization protocol when
large numbers of affected animals are awaiting treatment. This
presentation describes the design, development and testing of a
prototype field kit for providing a “quick clean" to contaminated
wildlife in the field.
Abstract: Fast forecasting of stock market prices is very important for
strategic planning. In this paper, a new approach for fast forecasting of
stock market prices is presented. Such algorithm uses new high speed
time delay neural networks (HSTDNNs). The operation of these
networks relies on performing cross correlation in the frequency
domain between the input data and the input weights of neural
networks. It is proved mathematically and practically that the number
of computation steps required for the presented HSTDNNs is less
than that needed by traditional time delay neural networks
(TTDNNs). Simulation results using MATLAB confirm the
theoretical computations.
Abstract: We consider optimal channel equalization for MIMO
(multi-input/multi-output) time-varying channels in the sense of
MMSE (minimum mean-squared-error), where the observation noise
can be non-stationary. We show that all ZF (zero-forcing) receivers
can be parameterized in an affine form which eliminates completely
the ISI (inter-symbol-interference), and optimal channel equalizers
can be designed through minimization of the MSE (mean-squarederror)
between the detected signals and the transmitted signals,
among all ZF receivers. We demonstrate that the optimal channel
equalizer is a modified Kalman filter, and show that under the AWGN
(additive white Gaussian noise) assumption, the proposed optimal
channel equalizer minimizes the BER (bit error rate) among all
possible ZF receivers. Our results are applicable to optimal channel
equalization for DWMT (discrete wavelet multitone), multirate transmultiplexers,
OFDM (orthogonal frequency division multiplexing),
and DS (direct sequence) CDMA (code division multiple access)
wireless data communication systems. A design algorithm for optimal
channel equalization is developed, and several simulation examples
are worked out to illustrate the proposed design algorithm.
Abstract: An enhanced particle swarm optimization algorithm
(PSO) is presented in this work to solve the non-convex OPF
problem that has both discrete and continuous optimization variables.
The objective functions considered are the conventional quadratic
function and the augmented quadratic function. The latter model
presents non-differentiable and non-convex regions that challenge
most gradient-based optimization algorithms. The optimization
variables to be optimized are the generator real power outputs and
voltage magnitudes, discrete transformer tap settings, and discrete
reactive power injections due to capacitor banks. The set of equality
constraints taken into account are the power flow equations while the
inequality ones are the limits of the real and reactive power of the
generators, voltage magnitude at each bus, transformer tap settings,
and capacitor banks reactive power injections. The proposed
algorithm combines PSO with Newton-Raphson algorithm to
minimize the fuel cost function. The IEEE 30-bus system with six
generating units is used to test the proposed algorithm. Several cases
were investigated to test and validate the consistency of detecting
optimal or near optimal solution for each objective. Results are
compared to solutions obtained using sequential quadratic
programming and Genetic Algorithms.
Abstract: In this paper, the finite-time stabilization of a class of multi-state time delay of fractional-order system is proposed. First, we define finite-time stability with the fractional-order system. Second, by using Generalized Gronwall's approach and the methods of the inequality, we get some conditions of finite-time stability for the fractional system with multi-state delay. Finally, a numerical example is given to illustrate the result.
Abstract: Machine-understandable data when strongly
interlinked constitutes the basis for the SemanticWeb. Annotating
web documents is one of the major techniques for creating metadata
on the Web. Annotating websitexs defines the containing data in a
form which is suitable for interpretation by machines. In this paper,
we present a better and improved approach than previous [1] to
annotate the texts of the websites depends on the knowledge base.
Abstract: The main purpose of this research was to analyze Socio-Cultural obstacles of disseminating of nanotechnology in Iran's agricultural section. One hundred twenty eight out of a total of 190 researchers with different levels of expertise in and familiarity with nanotechnology were randomly selected and questionnaires completed by them. Face validity have been done by expert's suggestion and correction, reliability by using Cronbakh-Alpha formula. The results of a factor analysis showed variation for different factors. For cultural factors 19/475 percent, for management 13/139 percent, information factor 11/277 percent, production factor 9/703 percent, social factor 9/267 percent, and for attitude factor it became 8/947 percent. Also results indicated that socio-cultural factors were the most important obstacle for nanotechnology dissemination in agricultural section in Iran.
Abstract: The optimal control problem for the viscoelastic melt
spinning process has not been reported yet in the literature. In this
study, an optimal control problem for a mathematical model of a
viscoelastic melt spinning process is considered. Maxwell-Oldroyd
model is used to describe the rheology of the polymeric material, the
fiber is made of. The extrusion velocity of the polymer at the spinneret
as well as the velocity and the temperature of the quench air and the
fiber length serve as control variables. A constrained optimization
problem is derived and the first–order optimality system is set up
to obtain the adjoint equations. Numerical solutions are carried out
using a steepest descent algorithm. A computer program in MATLAB
is developed for simulations.
Abstract: To identify an endothelial cell-specific promoter suitable for vascular-specific targeting, we tested five promoters in vitro--Tie2SE, Tie2LE, ICAM2, Flt-1 and vWF--for promoter activity and specificity in endothelial cells, smooth muscle cells and non-vascular resident cells as well as tissues. These promoters, except for vWF, exhibited good endothelial activity and specificity in vitro. In a syngenic heart transplantation model, the ICAM2 promoter was variably functional in coronary endothelial cells of donor hearts. Thus, the ICAM2, Flt-1, Tie2SE and Tie2LE promoters hold promise for endothelial-specific targeting, but in vitro expression may not predict in vivo expression.
Abstract: Recently there has been a growing interest in the field
of bio-mimetic robots that resemble the behaviors of an insect or an
aquatic animal, among many others. One of various bio-mimetic robot
applications is to explore pipelines, spotting any troubled areas or
malfunctions and reporting its data. Moreover, the robot is able to
prepare for and react to any abnormal routes in the pipeline. Special
types of mobile robots are necessary for the pipeline monitoring tasks.
In order to move effectively along a pipeline, the robot-s movement
will resemble that of insects or crawling animals. When situated in
massive pipelines with complex routes, the robot places fixed sensors
in several important spots in order to complete its monitoring. This
monitoring task is to prevent a major system failure by preemptively
recognizing any minor or partial malfunctions. Areas uncovered by
fixed sensors are usually impossible to provide real-time observation
and examination, and thus are dependent on periodical offline
monitoring. This paper proposes a monitoring system that is able to
monitor the entire area of pipelines–with and without fixed
sensors–by using the bio-mimetic robot.
Abstract: In this paper, we present a simple circuit for
Manchester decoding and without using any complicated or
programmable devices. This circuit can decode 90kbps of transmitted
encoded data; however, greater than this transmission rate can be
decoded if high speed devices were used. We also present a new
method for extracting the embedded clock from Manchester data in
order to use it for serial-to-parallel conversion. All of our
experimental measurements have been done using simulation.
Abstract: The so-called all-pass filter circuits are commonly
used in the field of signal processing, control and measurement.
Being connected to capacitive loads, these circuits tend to loose their
stability; therefore the elaborate analysis of their dynamic behavior is
necessary. The compensation methods intending to increase the
stability of such circuits are discussed in this paper, including the socalled
lead-lag compensation technique being treated in detail. For
the dynamic modeling, a two-port network model of the all-pass filter
is being derived. The results of the model analysis show, that
effective lead-lag compensation can be achieved, alone by the
optimization of the circuit parameters; therefore the application of
additional electric components are not needed to fulfill the stability
requirement.
Abstract: A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for SI applications. However, due to the structure of its filter bank, it captures vocal tract characteristics more effectively in the lower frequency regions. This paper proposes a new set of features using a complementary filter bank structure which improves distinguishability of speaker specific cues present in the higher frequency zone. Unlike high level features that are difficult to extract, the proposed feature set involves little computational burden during the extraction process. When combined with MFCC via a parallel implementation of speaker models, the proposed feature set outperforms baseline MFCC significantly. This proposition is validated by experiments conducted on two different kinds of public databases namely YOHO (microphone speech) and POLYCOST (telephone speech) with Gaussian Mixture Models (GMM) as a Classifier for various model orders.