Abstract: This paper presents an efficient algorithm for
optimization of radial distribution systems by a network
reconfiguration to balance feeder loads and eliminate overload
conditions. The system load-balancing index is used to determine the
loading conditions of the system and maximum system loading
capacity. The index value has to be minimum in the optimal network
reconfiguration of load balancing. A method based on Tabu search
algorithm, The Tabu search algorithm is employed to search for the
optimal network reconfiguration. The basic idea behind the search is
a move from a current solution to its neighborhood by effectively
utilizing a memory to provide an efficient search for optimality. It
presents low computational effort and is able to find good quality
configurations. Simulation results for a radial 69-bus system with
distributed generations and capacitors placement. The study results
show that the optimal on/off patterns of the switches can be identified
to give the best network reconfiguration involving balancing of
feeder loads while respecting all the constraints.
Abstract: In a pilot plant scale of a fluidized bed reactor, a
reduction reaction of sodium sulfate by natural gas has been
investigated. Natural gas is applied in this study as a reductant. Feed
density, feed mass flow rate, natural gas and air flow rate
(independent parameters)and temperature of bed and CO
concentration in inlet and outlet of reactor (dependent parameters)
were monitored and recorded at steady state. The residence time was
adjusted close to value of traditional reaction [1]. An artificial neural
network (ANN) was established to study dependency of yield and
carbon gradient on operating parameters. Resultant 97% accuracy of
applied ANN is a good prove that natural gas can be used as a
reducing agent. Predicted ANN model for relation between other
sources carbon gradient (accuracy 74%) indicates there is not a
meaningful relation between other sources carbon variation and
reduction process which means carbon in granule does not have
significant effect on the reaction yield.
Abstract: Developments in communication technologies
especially in wireless have enabled the progress of low-cost and lowpower
wireless sensor networks (WSNs). The features of such WSN
are holding minimal energy, weak computational capabilities,
wireless communication and an open-medium nature where sensors
are deployed. WSN is underpinned by application driven such as
military applications, the health sector, etc. Due to the intrinsic nature
of the network and application scenario, WSNs are vulnerable to
many attacks externally and internally. In this paper we have focused
on the types of internal attacks of WSNs based on OSI model and
discussed some security requirements, characterizers and challenges
of WSNs, by which to contribute to the WSN-s security research.
Abstract: Young patients suffering from Cerebral Palsy are
facing difficult choices concerning heavy surgeries. Diagnosis settled
by surgeons can be complex and on the other hand decision for
patient about getting or not such a surgery involves important
reflection effort. Proposed software combining prediction for
surgeries and post surgery kinematic values, and from 3D model
representing the patient is an innovative tool helpful for both patients
and medicine professionals. Beginning with analysis and
classification of kinematics values from Data Base extracted from
gait analysis in 3 separated clusters, it is possible to determine close
similarity between patients. Prediction surgery best adapted to
improve a patient gait is then determined by operating a suitable
preconditioned neural network. Finally, patient 3D modeling based
on kinematic values analysis, is animated thanks to post surgery
kinematic vectors characterizing the closest patient selected from
patients clustering.
Abstract: Segmentation of a color image composed of different
kinds of regions can be a hard problem, namely to compute for an
exact texture fields. The decision of the optimum number of
segmentation areas in an image when it contains similar and/or un
stationary texture fields. A novel neighborhood-based segmentation
approach is proposed. A genetic algorithm is used in the proposed
segment-pass optimization process. In this pass, an energy function,
which is defined based on Markov Random Fields, is minimized. In
this paper we use an adaptive threshold estimation method for image
thresholding in the wavelet domain based on the generalized
Gaussian distribution (GGD) modeling of sub band coefficients. This
method called Normal Shrink is computationally more efficient and
adaptive because the parameters required for estimating the threshold
depend on sub band data energy that used in the pre-stage of
segmentation. A quad tree is employed to implement the multi
resolution framework, which enables the use of different strategies at
different resolution levels, and hence, the computation can be
accelerated. The experimental results using the proposed
segmentation approach are very encouraging.
Abstract: Internet access is a vital part of the modern world and an important tool in the education of our children. It is present in schools, homes and even shopping malls. Mastering the use of the internet is likely to be an important skill for those entering the job markets of the future. An internet user can be anyone he or she wants to be in an online chat room, or play thrilling and challenging games against other players from all corners of the globe. It seems at present time (or near future) for many people relationships in the real world may be neglected as those in the virtual world increase in importance. Internet is provided a fast mode of transportation caused freedom from family bonds and mixing with different cultures and new communities. This research is an attempt to study effect of Internet on Social capital. For this purpose a survey technique on the sample size amounted 168 students of Payame Noor University of Kermanshah city in country of Iran were considered. Degree of social capital is moderate. With the help of the Multi-variable Regression, variables of Iranian message attractive, Interest to internet with effect of positive and variable Creating a cordial atmosphere with negative effect be significant.
Abstract: The efficient use of available licensed spectrum is
becoming more and more critical with increasing demand and usage
of the radio spectrum. This paper shows how the use of spectrum as
well as dynamic spectrum management can be effectively managed
and spectrum allocation schemes in the wireless communication
systems be implemented and used, in future. This paper would be an
attempt towards better utilization of the spectrum. This research will
focus on the decision-making process mainly, with an
assumption that the radio environment has already been sensed and
the QoS requirements for the application have been specified either
by the sensed radio environment or by the secondary user itself. We
identify and study the characteristic parameters of Cognitive Radio
and use Genetic Algorithm for spectrum allocation. Performance
evaluation is done using MATLAB toolboxes.
Abstract: WiMAX and Wi-Fi are considered as the promising
broadband access solutions for wireless MAN’s and LANs,
respectively. In the recent works WiMAX is considered suitable as a
backhaul service to connect multiple dispersed Wi-Fi ‘hotspots’.
Hence a new integrated WiMAX/Wi-Fi architecture has been
proposed in literatures. In this paper the performance of an integrated
WiMAX/Wi-Fi network has been investigated by streaming a video
conference application. The difference in performance between the
two protocols is compared with respect to video conferencing. The
Heterogeneous network was simulated in the OPNET simulator.
Abstract: An optimal control of Reverse Osmosis (RO) plant is
studied in this paper utilizing the auto tuning concept in conjunction
with PID controller. A control scheme composing an auto tuning
stochastic technique based on an improved Genetic Algorithm (GA) is
proposed. For better evaluation of the process in GA, objective
function defined newly in sense of root mean square error has been
used. Also in order to achieve better performance of GA, more
pureness and longer period of random number generation in operation
are sought. The main improvement is made by replacing the uniform
distribution random number generator in conventional GA technique
to newly designed hybrid random generator composed of Cauchy
distribution and linear congruential generator, which provides
independent and different random numbers at each individual steps in
Genetic operation. The performance of newly proposed GA tuned
controller is compared with those of conventional ones via simulation.
Abstract: With the increasing spread of computers and the internet among culturally, linguistically and geographically diverse communities, issues of internationalization and localization and becoming increasingly important. For some of the issues such as different scales for length and temperature, there is a well-developed measurement theory. For others such as date formats no such theory will be possible. This paper fills a gap by developing a measurement theory for a class of scales previously overlooked, based on discrete and interval-valued scales such as spanner and shoe sizes. The paper gives a theoretical foundation for a class of data representation problems.
Abstract: Simultaneous determination of multicomponents of phenol, resorcinol and catechol with a chemometric technique a PCranking artificial neural network (PCranking-ANN) algorithm is reported in this study. Based on the data correlation coefficient method, 3 representative PCs are selected from the scores of original UV spectral data (35 PCs) as the original input patterns for ANN to build a neural network model. The results obtained by iterating 8000 .The RMSEP for phenol, resorcinol and catechol with PCranking- ANN were 0.6680, 0.0766 and 0.1033, respectively. Calibration matrices were 0.50-21.0, 0.50-15.1 and 0.50-20.0 μg ml-1 for phenol, resorcinol and catechol, respectively. The proposed method was successfully applied for the determination of phenol, resorcinol and catechol in synthetic and water samples.
Abstract: As the network based technologies become
omnipresent, demands to secure networks/systems against threat
increase. One of the effective ways to achieve higher security is
through the use of intrusion detection systems (IDS), which are a
software tool to detect anomalous in the computer or network. In this
paper, an IDS has been developed using an improved machine
learning based algorithm, Locally Linear Neuro Fuzzy Model
(LLNF) for classification whereas this model is originally used for
system identification. A key technical challenge in IDS and LLNF
learning is the curse of high dimensionality. Therefore a feature
selection phase is proposed which is applicable to any IDS. While
investigating the use of three feature selection algorithms, in this
model, it is shown that adding feature selection phase reduces
computational complexity of our model. Feature selection algorithms
require the use of a feature goodness measure. The use of both a
linear and a non-linear measure - linear correlation coefficient and
mutual information- is investigated respectively
Abstract: This paper presents a software quality support tool, a
Java source code evaluator and a code profiler based on
computational intelligence techniques. It is Java prototype software
developed by AI Group [1] from the Research Laboratories at
Universidad de Palermo: an Intelligent Java Analyzer (in Spanish:
Analizador Java Inteligente, AJI). It represents a new approach to
evaluate and identify inaccurate source code usage and transitively,
the software product itself.
The aim of this project is to provide the software development
industry with a new tool to increase software quality by extending
the value of source code metrics through computational intelligence.
Abstract: Access Management is the proactive management of
vehicular access points to land parcels adjacent to all manner of
roadways. Good access management promotes safe and efficient use
of the transportation network. This study attempts to utilize archived
data from the University Technology of Malaysia on-campus area to
assess the accuracy with which access management display some
benefits. Results show that usage of access management reduces
delay and fewer crashes. Clustered development can improve
walking, cycling and transit travel, reduce parking requirements and
improve emergency responses. Effective Access Management
planning can also reduce total roadway facility costs by reducing the
number of driveways and intersections. At the end after presenting
recommendations some of the travel impact, and benefits that
can be derived if these suggestions are implemented have
been summarized with the related comments.
Abstract: This study examines knowledge management in the public organizations in Iran. The purpose of this article is to provide a conceptual framework for application of knowledge management in public organizations. The study indicates that an increasing tendency for implementation of knowledge management in organizations is emerging. Nonetheless knowledge management in public organizations is toddler and little has been done to bring the subject to use in the public sector. The globalization of change and popularization of some values like participation, citizen-orientation and knowledge-orientation in the new theories of public administration requires that the knowledge management is considered and attend to in the public sector. This study holds that a knowledge management framework for public organizations is different from this in the public sector, because public sector is stakeholder-dependent while the private is shareholder-dependent. Based on the research, we provide a conceptual model. The model proposed involves three factors: Organizational, knowledge citizens and contextual factors. The study results indicate these factors affect on knowledge management in public organizations in Iran.
Abstract: To judge whether the memristor can be interpreted as
the fourth fundamental circuit element, we propose a variable-relation
criterion of fundamental circuit elements. According to the criterion,
we investigate the nature of three fundamental circuit elements and the
memristor. From the perspective of variables relation, the memristor
builds a direct relation between the voltage across it and the current
through it, instead of a direct relation between the magnetic flux and
the charge. Thus, it is better to characterize the memristor and the
resistor as two special cases of the same fundamental circuit element,
which is the memristive system in Chua-s new framework. Finally, the
definition of memristor is refined according to the difference between
the magnetic flux and the flux linkage.
Abstract: Re-entrant scheduling is an important search problem
with many constraints in the flow shop. In the literature, a number of
approaches have been investigated from exact methods to
meta-heuristics. This paper presents a genetic algorithm that encodes
the problem as multi-level chromosomes to reflect the dependent
relationship of the re-entrant possibility and resource consumption.
The novel encoding way conserves the intact information of the data
and fastens the convergence to the near optimal solutions. To test the
effectiveness of the method, it has been applied to the
resource-constrained re-entrant flow shop scheduling problem.
Computational results show that the proposed GA performs better than
the simulated annealing algorithm in the measure of the makespan
Abstract: The purpose of this study is to investigate the capacity
of natural Turkish zeolite for NH4-N removal from landfill leachate.
The effects of modification and initial concentration on the removal
of NH4-N from leachate were also investigated. The kinetics of
adsorption of NH4-N has been discussed using three kinetic models,
i.e., the pseudo-second order model, the Elovich equation, the
intraparticle diffuion model. Kinetic parameters and correlation
coefficients were determined. Equilibrium isotherms for the
adsorption of NH4-N were analyzed by Langmuir, Freundlich and
Tempkin isotherm models. Langmuir isotherm model was found to
best represent the data for NH4-N.
Abstract: Collaborative networked learning (hereafter CNL)
was first proposed by Charles Findley in his work “Collaborative
networked learning: online facilitation and software support" as part
of instructional learning for the future of the knowledge worker. His
premise was that through electronic dialogue learners and experts
could interactively communicate within a contextual framework to
resolve problems, and/or to improve product or process knowledge.
Collaborative learning has always been the forefront of educational
technology and pedagogical research, but not in the mainstream of
operations management. As a result, there is a large disparity in the
study of CNL, and little is known about the antecedents of network
collaboration and sharing of information among diverse employees in
the manufacturing environment. This paper presents a model to
bridge the gap between theory and practice. The objective is that
manufacturing organizations will be able to accelerate organizational
learning and sharing of information through various collaborative
Abstract: The objective of this paper is to develop a neural
network-based residual generator to detect the fault in the actuators
for a specific communication satellite in its attitude control system
(ACS). First, a dynamic multilayer perceptron network with dynamic
neurons is used, those neurons correspond a second order linear
Infinite Impulse Response (IIR) filter and a nonlinear activation
function with adjustable parameters. Second, the parameters from the
network are adjusted to minimize a performance index specified by
the output estimated error, with the given input-output data collected
from the specific ACS. Then, the proposed dynamic neural network
is trained and applied for detecting the faults injected to the wheel,
which is the main actuator in the normal mode for the communication
satellite. Then the performance and capabilities of the proposed
network were tested and compared with a conventional model-based
observer residual, showing the differences between these two
methods, and indicating the benefit of the proposed algorithm to
know the real status of the momentum wheel. Finally, the application
of the methods in a satellite ground station is discussed.