Abstract: Image registration is the process of establishing point
by point correspondence between images obtained from a same
scene. This process is very useful in remote sensing, medicine,
cartography, computer vision, etc. Then, the task of registration is to
place the data into a common reference frame by estimating the
transformations between the data sets. In this work, we develop a
rigid point registration method based on the application of genetic
algorithms and Hausdorff distance. First, we extract the feature points
from both images based on the algorithm of global and local
curvature corner. After refining the feature points, we use Hausdorff
distance as similarity measure between the two data sets and for
optimizing the search space we use genetic algorithms to achieve
high computation speed for its inertial parallel. The results show the
efficiency of this method for registration of satellite images.
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: The adsorption of bovine serum albumin (BSA), immunoglobulin G (IgG) and fibrinogen (Fgn) on fluorinated selfassembled monolayers have been studied using time of flight secondary ion mass spectrometry (ToF-SIMS) and Spectroscopic Ellipsometry (SE). The objective of the work has to establish the utility of ToF-SIMS for the determination of the amount of protein adsorbed on the surface. Quantification of surface adsorbed proteins was carried out using SE and a good correlation between ToF-SIMS results and SE was achieved. The surface distribution of proteins were also analysed using Atomic Force Microscopy (AFM). We show that the surface distribution of proteins strongly affect the ToFSIMS results.
Abstract: In this paper, backstepping method (BM) is proposed for a single-link flexible mechanical manipulator. In each step of this method a positive value is obtained. Selections of the gain factor values are very important because controller will have different behavior for each different set of values. Improper selection of these gains can lead to instability of the system. In order to choose proper values for gains BELBIC method has been used in this work. Finally, to prove the efficiency of this method, the obtained results of proposed model are compared with robust controller one. Results show that the combination of backstepping and BELBIC that is presented here, can stabilized the system with higher speed, shorter settling time and lower overshoot in than robust controller.
Abstract: This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for vectored thrust aerial vehicle (VTAV). With the SA strategy, we proposed a flight control procedure to address the dynamics variation and performance requirement difference of flight trajectory for an unmanned helicopter model with vectored thrust configuration. This control strategy for chosen model of VTAV has been verified by simulation of take-off and forward maneuvers using software package Simulink and demonstrated good performance for fast stabilization of motors, consequently, fast SA with economy in energy can be asserted during search-and-rescue operations.
Abstract: In this study, the static behavior of super elliptical Winkler plate is analyzed by applying the double side approach method. The lack of information about super elliptical Winkler plates is the motivation of this study and we use the double side approach method to solve this problem because of its superior ability on efficiently treating problems with complex boundary shape. The double side approach method has the advantages of high accuracy, easy calculation procedure and less calculation load required. Most important of all, it can give the error bound of the approximate solution. The numerical results not only show that the double side approach method works well on this problem but also provide us the knowledge of static behavior of super elliptical Winkler plate in practical use.
Abstract: Thermite welding is mainly used in world. The
reasons why the thermite welding method is widely used are
that the equipment has good mobility and total working time
of that is shorter than that of the enclosed arc welding method
on site. Moreover, the operating skill, which required for
thermite welding, is less than that of for enclosed arc welding.
In the present research work, heat treatment and combined
'expulsion and heat treatment' techniques were used improve
the mechanical properties and weldment structure. The
specimens were cut in the transverse direction from expulsion
with Heat treated and heat treated Thermite Welded rails.
Specimens were prepared according to AWS standard and
subjected to tensile test, Impact test and hardness and their
results were tabulated. Microstructural analysis was carried
out with the help of SEM. Then analyze to effect of heat
treated and 'expulsion with heat treated' with the properties of
their thermite welded rails. Compare the mechanical and
microstructural properties of thermite welded rails between
heat expulsion with heat treated and heat treated. Mechanical
and microstructural response expulsion with heat treated
thermite welded rail is higher value as compared to heat
treatment.
Abstract: Steganography is the process of hiding one file inside another such that others can neither identify the meaning of the embedded object, nor even recognize its existence. Current trends favor using digital image files as the cover file to hide another digital file that contains the secret message or information. One of the most common methods of implementation is Least Significant Bit Insertion, in which the least significant bit of every byte is altered to form the bit-string representing the embedded file. Altering the LSB will only cause minor changes in color, and thus is usually not noticeable to the human eye. While this technique works well for 24-bit color image files, steganography has not been as successful when using an 8-bit color image file, due to limitations in color variations and the use of a colormap. This paper presents the results of research investigating the combination of image compression and steganography. The technique developed starts with a 24-bit color bitmap file, then compresses the file by organizing and optimizing an 8-bit colormap. After the process of compression, a text message is hidden in the final, compressed image. Results indicate that the final technique has potential of being useful in the steganographic world.
Abstract: A gradient learning method to regulate the trajectories
of some nonlinear chaotic systems is proposed. The method is
motivated by the gradient descent learning algorithms for neural
networks. It is based on two systems: dynamic optimization system
and system for finding sensitivities. Numerical results of several
examples are presented, which convincingly illustrate the efficiency
of the method.
Abstract: When faced with stochastic networks with an uncertain
duration for their activities, the securing of network completion time
becomes problematical, not only because of the non-identical pdf of
duration for each node, but also because of the interdependence of
network paths. As evidenced by Adlakha & Kulkarni [1], many
methods and algorithms have been put forward in attempt to resolve
this issue, but most have encountered this same large-size network
problem. Therefore, in this research, we focus on network reduction
through a Series/Parallel combined mechanism. Our suggested
algorithm, named the Activity Network Reduction Algorithm
(ANRA), can efficiently transfer a large-size network into an S/P
Irreducible Network (SPIN). SPIN can enhance stochastic network
analysis, as well as serve as the judgment of symmetry for the Graph
Theory.
Abstract: This interdisciplinary research aims to distinguish universal scale-free and field-like fundamental principles of selforganization observable across many disciplines like computer science, neuroscience, microbiology, social science, etc. Based on these universal principles we provide basic premises and postulates for designing holistic social simulation models. We also introduce pervasive information field (PIF) concept, which serves as a simulation media for contextual information storage, dynamic distribution and organization in social complex networks. PIF concept specifically is targeted for field-like uncoupled and indirect interactions among social agents capable of affecting and perceiving broadcasted contextual information. Proposed approach is expressive enough to represent contextual broadcasted information in a form locally accessible and immediately usable by network agents. This paper gives some prospective vision how system-s resources (tangible and intangible) could be simulated as oscillating processes immersed in the all pervasive information field.
Abstract: Hydrogen diffusion is the main problem for corrosion fatigue in corrosive environment. In order to analyze the phenomenon, it is needed to understand their behaviors specially the hydrogen behavior during the diffusion. So, Hydrogen embrittlement and prediction its behavior as a main corrosive part of the fractions, needed to solve combinations of different equations mathematically. The main point to obtain the equation, having knowledge about the source of causing diffusion and running the atoms into materials, called driving force. This is produced by either gradient of electrical or chemical potential. In this work, we consider the gradient of chemical potential to obtain the property equation. In diffusion of atoms, some of them may be trapped but, it could be ignorable in some conditions. According to the phenomenon of hydrogen embrittlement, the thermodynamic and chemical properties of hydrogen are considered to justify and relate them to fracture mechanics. It is very important to get a stress intensity factor by using fugacity as a property of hydrogen or other gases. Although, the diffusive behavior and embrittlement event are common and the same for other gases but, for making it more clear, we describe it for hydrogen. This considering on the definite gas and describing it helps us to understand better the importance of this relation.
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: Internet is one of the major sources of information for
the person belonging to almost all the fields of life. Major language
that is used to publish information on internet is language. This thing
becomes a problem in a country like Pakistan, where Urdu is the
national language. Only 10% of Pakistan mass can understand
English. The reason is millions of people are deprived of precious
information available on internet. This paper presents a system for
translation from English to Urdu. A module LESSA is used that uses
a rule based algorithm to read the input text in English language,
understand it and translate it into Urdu language. The designed
approach was further incorporated to translate the complete website
from English language o Urdu language. An option appears in the
browser to translate the webpage in a new window. The designed
system will help the millions of users of internet to get benefit of the
internet and approach the latest information and knowledge posted
daily on internet.
Abstract: New ways of working- refers to non-traditional work practices, settings and locations with information and communication technologies (ICT) to supplement or replace traditional ways of working. It questions the contemporary work practices and settings still very much used in knowledge-intensive organizations today. In this study new ways of working is seen to consist of two elements: work environment (incl. physical, virtual and social) and work practices. This study aims to gather the scattered information together and deepen the understanding on new ways of working. Moreover, the objective is to provide some evidence of the unclear productivity impacts of new ways of working using case study approach.
Abstract: In this research, STNEP is being studied considering network adequacy and limitation of investment cost by decimal codification genetic algorithm (DCGA). The goal is obtaining the maximum of network adequacy with lowest expansion cost for a specific investment. Finally, the proposed idea is applied to the Garvers 6-bus network. The results show that considering the network adequacy for solution of STNEP problem is caused that among of expansion plans for a determined investment, configuration which has relatively lower expansion cost and higher adequacy is proposed by GA based method. Finally, with respect to the curve of adequacy versus expansion cost it can be said that more optimal configurations for expansion of network are obtained with lower investment costs.
Abstract: Short-Term Load Forecasting (STLF) plays an important role for the economic and secure operation of power systems. In this paper, Continuous Genetic Algorithm (CGA) is employed to evolve the optimum large neural networks structure and connecting weights for one-day ahead electric load forecasting problem. This study describes the process of developing three layer feed-forward large neural networks for load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. We find good performance for the large neural networks. The proposed methodology gives lower percent errors all the time. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.
Abstract: This work presents a numerical simulation of the interaction of an incident shock wave propagates from the left to the right with a cone placed in a tube at shock. The Mathematical model is based on a non stationary, viscous and axisymmetric flow. The Discretization of the Navier-stokes equations is carried out by the finite volume method in the integral form along with the Flux Vector Splitting method of Van Leer. Here, adequate combination of time stepping parameter, CFL coefficient and mesh size level is selected to ensure numerical convergence. The numerical simulation considers a shock tube filled with air. The incident shock wave propagates to the right with a determined Mach number and crosses the cone by leaving behind it a stationary detached shock wave in front of the nose cone. This type of interaction is observed according to the time of flow.
Abstract: This paper presents a predictive model of sensor readings for mobile robot. The model predicts sensor readings for given time horizon based on current sensor readings and velocities of wheels assumed for this horizon. Similar models for such anticipation have been proposed in the literature. The novelty of the model presented in the paper comes from the fact that its structure takes into account physical phenomena and is not just a black box, for example a neural network. From this point of view it may be regarded as a semi-phenomenological model. The model is developed for the Khepera robot, but after certain modifications, it may be applied for any robot with distance sensors such as infrared or ultrasonic sensors.