Abstract: This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.
Abstract: As is needless to say; a majority of accidents, which occur, are due to drunk driving. As such, there is no effective mechanism to prevent this. Here we have designed an integrated system for the same purpose. Alcohol content in the driver-s body is detected by means of an infrared breath analyzer placed at the steering wheel. An infrared cell directs infrared energy through the sample and any unabsorbed energy at the other side is detected. The higher the concentration of ethanol, the more infrared absorption occurs (in much the same way that a sunglass lens absorbs visible light, alcohol absorbs infrared light). Thus the alcohol level of the driver is continuously monitored and calibrated on a scale. When it exceeds a particular limit the fuel supply is cutoff. If the device is removed also, the fuel supply will be automatically cut off or an alarm is sounded depending upon the requirement. This does not happen abruptly and special indicators are fixed at the back to avoid inconvenience to other drivers using the highway signals. Frame work for integration of sensors and control module in a scalable multi-agent system is provided .A SMS which contains the current GPS location of the vehicle is sent via a GSM module to the police control room to alert the police. The system is foolproof and the driver cannot tamper with it easily. Thus it provides an effective and cost effective solution for the problem of drunk driving in vehicles.
Abstract: In this paper, a class of impulsive BAM fuzzy cellular neural networks with time delays in the leakage terms is formulated and investigated. By establishing a delay differential inequality and M-matrix theory, some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with time delays in the leakage terms are obtained. In particular, a precise estimate of the exponential convergence rate is also provided, which depends on system parameters and impulsive perturbation intention. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.
Abstract: Single photon detectors have been fabricated NbN
nano wire. These detectors are fabricated from high quality, ultra
high vacuum sputtered NbN thin films on a sapphire substrate. In this
work a typical schematic of the nanowire Single Photon Detector
structure and then driving and measurement electronic circuit are
shown.
The response of superconducting nanowire single photon detectors
during a photo detection event, is modeled by a special electrical
circuits (two circuit).
Finally, current through the wire is calculated by solving
equations of models.
Abstract: Bioinformatics methods for predicting the T cell
coreceptor usage from the array of membrane protein of HIV-1 are
investigated. In this study, we aim to propose an effective prediction
method for dealing with the three-class classification problem of
CXCR4 (X4), CCR5 (R5) and CCR5/CXCR4 (R5X4). We made
efforts in investigating the coreceptor prediction problem as follows: 1)
proposing a feature set of informative physicochemical properties
which is cooperated with SVM to achieve high prediction test
accuracy of 81.48%, compared with the existing method with
accuracy of 70.00%; 2) establishing a large up-to-date data set by
increasing the size from 159 to 1225 sequences to verify the proposed
prediction method where the mean test accuracy is 88.59%, and 3)
analyzing the set of 14 informative physicochemical properties to
further understand the characteristics of HIV-1coreceptors.
Abstract: The aim of the study was to investigate the possible
use of commercial Computational Fluid Dynamics (CFD) software in
the design process of a domestic gas boiler. Because of the limited
computational resources some simplifications had to be made in
order to contribute to the design in a reasonable timescale.
The porous media model was used in order to simulate the
influence of the pressure drop characteristic of particular elements of
a heat transfer system on the water-flow distribution in the system.
Further, a combination of CFD analyses and spread sheet
calculations was used in order to solve the flow distribution problem.
Abstract: This paper presents a simple method for estimation of
additional load as a factor of the existing load that may be drawn
before reaching the point of line maximum loadability of radial
distribution system (RDS) with different realistic load models at
different substation voltages. The proposed method involves a simple
line loadability index (LLI) that gives a measure of the proximity of
the present state of a line in the distribution system. The LLI can use
to assess voltage instability and the line loading margin. The
proposed method also compares with the existing method of
maximum loadability index [10]. The simulation results show that the
LLI can identify not only the weakest line/branch causing system
instability but also the system voltage collapse point when it is near
one. This feature enables us to set an index threshold to monitor and
predict system stability on-line so that a proper action can be taken to
prevent the system from collapse. To demonstrate the validity of the
proposed algorithm, computer simulations are carried out on two bus
and 69 bus RDS.
Abstract: The challenge in the swing-up problem of double
inverted pendulum on a cart (DIPC) is to design a controller that
bring all DIPC's states, especially the joint angles of the two links,
into the region of attraction of the desired equilibrium. This paper
proposes a new method to swing-up DIPC based on a series of restto-
rest maneuvers of the first link about its vertically upright
configuration while holding the cart fixed at the origin. The rest-torest
maneuvers are designed such that each one results in a net gain
in energy of the second link. This results in swing-up of DIPC-s
configuration to the region of attraction of the desired equilibrium. A
three-step algorithm is provided for swing-up control followed by the
stabilization step. Simulation results with a comparison to an
experimental work done in the literature are presented to demonstrate
the efficacy of the approach.
Abstract: This paper proposes a system to extract images from web pages and then detect the skin color regions of these images. As part of the proposed system, using BandObject control, we built a Tool bar named 'Filter Tool Bar (FTB)' by modifying the Pavel Zolnikov implementation. The Yahoo! Team provides us with the Yahoo! SDK API, which also supports image search and is really useful. In the proposed system, we introduced three new methods for extracting images from the web pages (after loading the web page by using the proposed FTB, before loading the web page physically from the localhost, and before loading the web page from any server). These methods overcome the drawback of the regular expressions method for extracting images suggested by Ilan Assayag. The second part of the proposed system is concerned with the detection of the skin color regions of the extracted images. So, we studied two famous skin color detection techniques. The first technique is based on the RGB color space and the second technique is based on YUV and YIQ color spaces. We modified the second technique to overcome the failure of detecting complex image's background by using the saturation parameter to obtain an accurate skin detection results. The performance evaluation of the efficiency of the proposed system in extracting images before and after loading the web page from localhost or any server in terms of the number of extracted images is presented. Finally, the results of comparing the two skin detection techniques in terms of the number of pixels detected are presented.
Abstract: An image compression method has been developed
using fuzzy edge image utilizing the basic Block Truncation Coding
(BTC) algorithm. The fuzzy edge image has been validated with
classical edge detectors on the basis of the results of the well-known
Canny edge detector prior to applying to the proposed method. The
bit plane generated by the conventional BTC method is replaced with
the fuzzy bit plane generated by the logical OR operation between
the fuzzy edge image and the corresponding conventional BTC bit
plane. The input image is encoded with the block mean and standard
deviation and the fuzzy bit plane. The proposed method has been
tested with test images of 8 bits/pixel and size 512×512 and found to
be superior with better Peak Signal to Noise Ratio (PSNR) when
compared to the conventional BTC, and adaptive bit plane selection
BTC (ABTC) methods. The raggedness and jagged appearance, and
the ringing artifacts at sharp edges are greatly reduced in
reconstructed images by the proposed method with the fuzzy bit
plane.
Abstract: An important technique in stability theory for
differential equations is known as the direct method of Lyapunov. In
this work we deal global stability properties of Leptospirosis
transmission model by age group in Thailand. First we consider the
data from Division of Epidemiology Ministry of Public Health,
Thailand between 1997-2011. Then we construct the mathematical
model for leptospirosis transmission by eight age groups. The
Lyapunov functions are used for our model which takes the forms of
an Ordinary Differential Equation system. The globally
asymptotically for equilibrium states are analyzed.
Abstract: In this paper, we propose a new method to describe fractal shapes using parametric l-systems. First we introduce scaling factors in the production rules of the parametric l-systems grammars. Then we decorticate these grammars with scaling factors using turtle algebra to show the mathematical relation between l-systems and iterated function systems (IFS). We demonstrate that with specific values of the scaling factors, we find the exact relationship established by Prusinkiewicz and Hammel between l-systems and IFS.
Abstract: In the current context of globalization, a large number of companies sought to develop as a group in order to reach to other markets or meet the necessary criteria for listing on a stock exchange. The issue of consolidated financial statements prepared by a parent, an investor or a venture and the financial reporting standards guiding them therefore becomes even more important. The aim of our paper is to expose this issue in a consistent manner, first by summarizing the international accounting and financial reporting standards applicable before the 1st of January 2013 and considering the role of the crisis in shaping the standard setting process, and secondly by analyzing the newly issued/modified standards and main changes being brought
Abstract: In this paper we introduce an ultra low power CMOS
LC oscillator and analyze a method to design a low power low phase
noise complementary CMOS LC oscillator. A 1.8GHz oscillator is
designed based on this analysis. The circuit has power supply equal
to 1.1 V and dissipates 0.17 mW power. The oscillator is also
optimized for low phase noise behavior. The oscillator phase noise is
-126.2 dBc/Hz and -144.4 dBc/Hz at 1 MHz and 8 MHz offset
respectively.
Abstract: The structural interpretation of a part of eastern Potwar
(Missa Keswal) has been carried out with available seismological,
seismic and well data. Seismological data contains both the source
parameters and fault plane solution (FPS) parameters and seismic data
contains ten seismic lines that were re-interpreted by using well data.
Structural interpretation depicts two broad types of fault sets namely,
thrust and back thrust faults. These faults together give rise to pop up
structures in the study area and also responsible for many structural
traps and seismicity. Seismic interpretation includes time and depth
contour maps of Chorgali Formation while seismological interpretation
includes focal mechanism solution (FMS), depth, frequency,
magnitude bar graphs and renewal of Seismotectonic map. The Focal
Mechanism Solutions (FMS) that surrounds the study area are
correlated with the different geological and structural maps of the area
for the determination of the nature of subsurface faults. Results of
structural interpretation from both seismic and seismological data
show good correlation. It is hoped that the present work will help in
better understanding of the variations in the subsurface structure and
can be a useful tool for earthquake prediction, planning of oil field and
reservoir monitoring.
Abstract: The length of a given rational B'ezier curve is
efficiently estimated. Since a rational B'ezier function is nonlinear,
it is usually impossible to evaluate its length exactly. The
length is approximated by using subdivision and the accuracy
of the approximation n is investigated. In order to improve
the efficiency, adaptivity is used with some length estimator.
A rigorous theoretical analysis of the rate of convergence of
n to is given. The required number of subdivisions to
attain a prescribed accuracy is also analyzed. An application
to CAD parametrization is briefly described. Numerical results
are reported to supplement the theory.
Abstract: The paper describes a knowledge based system for
analysis of microscopic wear particles. Wear particles contained in
lubricating oil carry important information concerning machine
condition, in particular the state of wear. Experts (Tribologists) in the
field extract this information to monitor the operation of the machine
and ensure safety, efficiency, quality, productivity, and economy of
operation. This procedure is not always objective and it can also be
expensive. The aim is to classify these particles according to their
morphological attributes of size, shape, edge detail, thickness ratio,
color, and texture, and by using this classification thereby predict
wear failure modes in engines and other machinery. The attribute
knowledge links human expertise to the devised Knowledge Based
Wear Particle Analysis System (KBWPAS). The system provides an
automated and systematic approach to wear particle identification
which is linked directly to wear processes and modes that occur in
machinery. This brings consistency in wear judgment prediction
which leads to standardization and also less dependence on
Tribologists.
Abstract: Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.
Abstract: Wireless sensor network can be applied to both abominable
and military environments. A primary goal in the design of
wireless sensor networks is lifetime maximization, constrained by
the energy capacity of batteries. One well-known method to reduce
energy consumption in such networks is data aggregation. Providing
efcient data aggregation while preserving data privacy is a challenging
problem in wireless sensor networks research. In this paper,
we present privacy-preserving data aggregation scheme for additive
aggregation functions. The Cluster-based Private Data Aggregation
(CPDA)leverages clustering protocol and algebraic properties of
polynomials. It has the advantage of incurring less communication
overhead. The goal of our work is to bridge the gap between
collaborative data collection by wireless sensor networks and data
privacy. We present simulation results of our schemes and compare
their performance to a typical data aggregation scheme TAG, where
no data privacy protection is provided. Results show the efficacy and
efficiency of our schemes.
Abstract: In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.