Abstract: Network management techniques have long been of
interest to the networking research community. The queue size plays
a critical role for the network performance. The adequate size of the
queue maintains Quality of Service (QoS) requirements within
limited network capacity for as many users as possible. The
appropriate estimation of the queuing model parameters is crucial for
both initial size estimation and during the process of resource
allocation. The accurate resource allocation model for the
management system increases the network utilization. The present
paper demonstrates the results of empirical observation of memory
allocation for packet-based services.
Abstract: Developments in scientific and technical area cause to use new methods and techniques in education, as is the case in all fields. Especially, the internet contributes a variety of new methods to design virtual and real time laboratory applications in education. In this study, a real time virtual laboratory is designed and implemented for analog and digital communications laboratory experiments by using Lab VIEW program for Marmara University Electronics-Communication Department. In this application, students can access the virtual laboratory web site and perform their experiments without any limitation of time and location so as the students can observe the signals by changing the parameters of the experiment and evaluate the results.
Abstract: In 2002 an amendment to SOLAS opened for
lightweight material constructions in vessels if the same fire safety as
in steel constructions could be obtained. FISPAT (FIreSPread
Analysis Tool) is a computer application that simulates fire spread
and fault injection in cruise vessels and identifies fire sensitive areas.
It was developed to analyze cruise vessel designs and provides a
method to evaluate network layout and safety of cruise vessels. It
allows fast, reliable and deterministic exhaustive simulations and
presents the result in a graphical vessel model. By performing the
analysis iteratively while altering the cruise vessel design it can be
used along with fire chamber experiments to show that the
lightweight design can be as safe as a steel construction and that
SOLAS regulations are fulfilled.
Abstract: This research presented in this paper is an on-going
project of an application of neural network and fuzzy models to
evaluate the sociological factors which affect the educational
performance of the students in Sri Lanka. One of its major goals is to
prepare the grounds to device a counseling tool which helps these
students for a better performance at their examinations, especially at
their G.C.E O/L (General Certificate of Education-Ordinary Level)
examination. Closely related sociological factors are collected as raw
data and the noise of these data are filtered through the fuzzy
interface and the supervised neural network is being utilized to
recognize the performance patterns against the chosen social factors.
Abstract: While compressing text files is useful, compressing
still image files is almost a necessity. A typical image takes up much
more storage than a typical text message and without compression
images would be extremely clumsy to store and distribute. The
amount of information required to store pictures on modern
computers is quite large in relation to the amount of bandwidth
commonly available to transmit them over the Internet and
applications. Image compression addresses the problem of reducing
the amount of data required to represent a digital image. Performance
of any image compression method can be evaluated by measuring the
root-mean-square-error & peak signal to noise ratio. The method of
image compression that will be analyzed in this paper is based on the
lossy JPEG image compression technique, the most popular
compression technique for color images. JPEG compression is able to
greatly reduce file size with minimal image degradation by throwing
away the least “important" information. In JPEG, both color
components are downsampled simultaneously, but in this paper we
will compare the results when the compression is done by
downsampling the single chroma part. In this paper we will
demonstrate more compression ratio is achieved when the
chrominance blue is downsampled as compared to downsampling the
chrominance red in JPEG compression. But the peak signal to noise
ratio is more when the chrominance red is downsampled as compared
to downsampling the chrominance blue in JPEG compression. In
particular we will use the hats.jpg as a demonstration of JPEG
compression using low pass filter and demonstrate that the image is
compressed with barely any visual differences with both methods.
Abstract: The continuity in the electric supply of the electric installations is becoming one of the main requirements of the electric supply network (generation, transmission, and distribution of the electric energy). The achievement of this requirement depends from one side on the structure of the electric network and on the other side on the avaibility of the reserve source provided to maintain the supply in case of failure of the principal one. The avaibility of supply does not only depends on the reliability parameters of the both sources (principal and reserve) but it also depends on the reliability of the circuit breaker which plays the role of interlocking the reserve source in case of failure of the principal one. In addition, the principal source being under operation, its control can be ideal and sure, however, for the reserve source being in stop, a preventive maintenances which proceed on time intervals (periodicity) and for well defined lengths of time are envisaged, so that this source will always available in case of the principal source failure. The choice of the periodicity of preventive maintenance of the source of reserve influences directly the reliability of the electric feeder system In this work and on the basis of the semi- markovian's processes, the influence of the time of interlocking the reserve source upon the reliability of an industrial electric network is studied and is given the optimal time of interlocking the reserve source in case of failure the principal one, also the influence of the periodicity of the preventive maintenance of the source of reserve is studied and is given the optimal periodicity.
Abstract: This paper presents Genetic Algorithm (GA) based
approach for the allocation of FACTS (Flexible AC Transmission
System) devices for the improvement of Power transfer capacity in an
interconnected Power System. The GA based approach is applied on
IEEE 30 BUS System. The system is reactively loaded starting from
base to 200% of base load. FACTS devices are installed in the
different locations of the power system and system performance is
noticed with and without FACTS devices. First, the locations, where
the FACTS devices to be placed is determined by calculating active
and reactive power flows in the lines. Genetic Algorithm is then
applied to find the amount of magnitudes of the FACTS devices. This
approach of GA based placement of FACTS devices is tremendous
beneficial both in terms of performance and economy is clearly
observed from the result obtained.
Abstract: The Aggregate Production Plan (APP) is a schedule of
the organization-s overall operations over a planning horizon to
satisfy demand while minimizing costs. It is the baseline for any
further planning and formulating the master production scheduling,
resources, capacity and raw material planning. This paper presents a
methodology to model the Aggregate Production Planning problem,
which is combinatorial in nature, when optimized with Genetic
Algorithms. This is done considering a multitude of constraints of
contradictory nature and the optimization criterion – overall cost,
made up of costs with production, work force, inventory, and
subcontracting. A case study of substantial size, used to develop the
model, is presented, along with the genetic operators.
Abstract: A framework to estimate the state of dynamically
varying environment where data are generated from heterogeneous
sources possessing partial knowledge about the environment is presented.
This is entirely derived within Dempster-Shafer and Evidence
Filtering frameworks. The belief about the current state is expressed
as belief and plausibility functions. An addition to Single Input
Single Output Evidence Filter, Multiple Input Single Output Evidence
Filtering approach is introduced. Variety of applications such as
situational estimation of an emergency environment can be developed
within the framework successfully. Fire propagation scenario is used
to justify the proposed framework, simulation results are presented.
Abstract: Recent advances in wireless sensor networks have led
to many routing methods designed for energy-efficiency in wireless
sensor networks. Despite that many routing methods have been
proposed in USN, a single routing method cannot be energy-efficient
if the environment of the ubiquitous sensor network varies. We present
the controlling network access to various hosts and the services they
offer, rather than on securing them one by one with a network security
model. When ubiquitous sensor networks are deployed in hostile
environments, an adversary may compromise some sensor nodes and
use them to inject false sensing reports. False reports can lead to not
only false alarms but also the depletion of limited energy resource in
battery powered networks. The interleaved hop-by-hop authentication
scheme detects such false reports through interleaved authentication.
This paper presents a LMDD (Low energy method for data delivery)
algorithm that provides energy-efficiency by dynamically changing
protocols installed at the sensor nodes. The algorithm changes
protocols based on the output of the fuzzy logic which is the fitness
level of the protocols for the environment.
Abstract: Matrix metalloproteinase-3 (MMP3) is key member
of the MMP family, and is known to be present in coronary
atherosclerotic. Several studies have demonstrated that MMP-3
5A/6A polymorphism modify each transcriptional activity in allele
specific manner. We hypothesized that this polymorphism may play
a role as risk factor for development of coronary stenosis. The aim of
our study was to estimate MMP-3 (5A/6A) gene polymorphism on
interindividual variability in risk for coronary stenosis in an Iranian
population.DNA was extracted from white blood cells and genotypes
were obtained from coronary stenosis cases (n=95) and controls
(n=100) by PCR (polymerase chain reaction) and restriction
fragment length polymorphism techniques. Significant differences
between cases and controls were observed for MMP3 genotype
frequencies (X2=199.305, p< 0.001); the 6A allele was less
frequently seen in the control group, compared to the disease group
(85.79 vs. 78%, 6A/6A+5A/6A vs. 5A/5A, P≤0.001). These data
imply the involvement of -1612 5A/6A polymorphism in coronary
stenosis, and suggest that probably the 6A/6A MMP-3 genotype is a
genetic susceptibility factor for coronary stenosis.
Abstract: Sociological models (e.g., social network analysis, small-group dynamic and gang models) have historically been used to predict the behavior of terrorist groups. However, they may not be the most appropriate method for understanding the behavior of terrorist organizations because the models were not initially intended to incorporate violent behavior of its subjects. Rather, models that incorporate life and death competition between subjects, i.e., models utilized by scientists to examine the behavior of wildlife populations, may provide a more accurate analysis. This paper suggests the use of biological models to attain a more robust method for understanding the behavior of terrorist organizations as compared to traditional methods. This study also describes how a biological population model incorporating predator-prey behavior factors can predict terrorist organizational recruitment behavior for the purpose of understanding the factors that govern the growth and decline of terrorist organizations. The Lotka-Volterra, a biological model that is based on a predator-prey relationship, is applied to a highly suggestive case study, that of the Irish Republican Army. This case study illuminates how a biological model can be utilized to understand the actions of a terrorist organization.
Abstract: Dynamic Causal Modeling (DCM) functional
Magnetic Resonance Imaging (fMRI) is a promising technique to
study the connectivity among brain regions and effects of stimuli
through modeling neuronal interactions from time-series
neuroimaging. The aim of this study is to study characteristics of a
mirror neuron system (MNS) in elderly group (age: 60-70 years old).
Twenty volunteers were MRI scanned with visual stimuli to study a
functional brain network. DCM was employed to determine the
mechanism of mirror neuron effects. The results revealed major
activated areas including precentral gyrus, inferior parietal lobule,
inferior occipital gyrus, and supplementary motor area. When visual
stimuli were presented, the feed-forward connectivity from visual
area to conjunction area was increased and forwarded to motor area.
Moreover, the connectivity from the conjunction areas to premotor
area was also increased. Such findings can be useful for future
diagnostic process for elderly with diseases such as Parkinson-s and
Alzheimer-s.
Abstract: This paper considers the problem of finding low cost
chip set for a minimum cost partitioning of a large logic circuits. Chip
sets are selected from a given library. Each chip in the library has a
different price, area, and I/O pin. We propose a low cost chip set
selection algorithm. Inputs to the algorithm are a netlist and a chip
information in the library. Output is a list of chip sets satisfied with
area and maximum partitioning number and it is sorted by cost. The
algorithm finds the sorted list of chip sets from minimum cost to
maximum cost. We used MCNC benchmark circuits for experiments.
The experimental results show that all of chip sets found satisfy the
multiple partitioning constraints.
Abstract: Fischer-Tropsch synthesis is one of the most
important catalytic reactions that convert the synthetic gas to light
and heavy hydrocarbons. One of the main issues is selecting the type
of reactor. The slurry bubble reactor is suitable choice for Fischer-
Tropsch synthesis because of its good qualification to transfer heat
and mass, high durability of catalyst, low cost maintenance and
repair. The more common catalysts for Fischer-Tropsch synthesis are
Iron-based and Cobalt-based catalysts, the advantage of these
catalysts on each other depends on which type of hydrocarbons we
desire to produce. In this study, Fischer-Tropsch synthesis is modeled
with Iron and Cobalt catalysts in a slurry bubble reactor considering
mass and momentum balance and the hydrodynamic relations effect
on the reactor behavior. Profiles of reactant conversion and reactant
concentration in gas and liquid phases were determined as the
functions of residence time in the reactor. The effects of temperature,
pressure, liquid velocity, reactor diameter, catalyst diameter, gasliquid
and liquid-solid mass transfer coefficients and kinetic
coefficients on the reactant conversion have been studied. With 5%
increase of liquid velocity (with Iron catalyst), H2 conversions
increase about 6% and CO conversion increase about 4%, With 8%
increase of liquid velocity (with Cobalt catalyst), H2 conversions
increase about 26% and CO conversion increase about 4%. With
20% increase of gas-liquid mass transfer coefficient (with Iron
catalyst), H2 conversions increase about 12% and CO conversion
increase about 10% and with Cobalt catalyst H2 conversions increase
about 10% and CO conversion increase about 6%. Results show that
the process is sensitive to gas-liquid mass transfer coefficient and
optimum condition operation occurs in maximum possible liquid
velocity. This velocity must be more than minimum fluidization
velocity and less than terminal velocity in such a way that avoid
catalysts particles from leaving the fluidized bed.
Abstract: The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.
Abstract: The broadcast problem including the plan design is
considered. The data are inserted and numbered at predefined order
into customized size relations. The server ability to create a full,
regular Broadcast Plan (RBP) with single and multiple channels after
some data transformations is examined. The Regular Geometric
Algorithm (RGA) prepares a RBP and enables the users to catch their
items avoiding energy waste of their devices. Moreover, the
Grouping Dimensioning Algorithm (GDA) based on integrated
relations can guarantee the discrimination of services with a
minimum number of channels. This last property among the selfmonitoring,
self-organizing, can be offered by servers today
providing also channel availability and less energy consumption by
using smaller number of channels. Simulation results are provided.
Abstract: Transcription factors are a group of proteins that
helps for interpreting the genetic information in DNA.
Protein-protein interactions play a major role in the execution
of key biological functions of a cell. These interactions are
represented in the form of a graph with nodes and edges.
Studies have showed that some nodes have high degree of
connectivity and such nodes, known as hub nodes, are the
inevitable parts of the network. In the present paper a method
is proposed to identify hub transcription factor proteins using
sequence information. On a complete data set of transcription
factor proteins available from the APID database, the
proposed method showed an accuracy of 77%, sensitivity of
79% and specificity of 76%.
Abstract: The objective of this research is to calculate the
optimal inventory lot-sizing for each supplier and minimize the total
inventory cost which includes joint purchase cost of the products,
transaction cost for the suppliers, and holding cost for remaining
inventory. Genetic algorithms (GAs) are applied to the multi-product
and multi-period inventory lot-sizing problems with supplier
selection under storage space. Also a maximum storage space for the
decision maker in each period is considered. The decision maker
needs to determine what products to order in what quantities with
which suppliers in which periods. It is assumed that demand of
multiple products is known over a planning horizon. The problem is
formulated as a mixed integer programming and is solved with the
GAs. The detailed computation results are presented.
Abstract: This paper aims to explain the project carried out at
the University of Cordoba, specifically at the High Polytechnic
School in collaboration with two other organizations belonging to the
Andalusian Ministry of Innovation, Science and Business:
Andalusian Innovation and Development Agency (IDEA agency) [1]
and the Territorial Net of Entrepreneurship Support (in Spanish Red
Territorial de Apoyo al Emprendedor) [11].
The project is being developed in several stages of which only the
first one has already been completed. However, several important
preliminary results derive from it, based mainly in the description of
the nature of entrepreneurship in the field of university education and
its impact on student-s competency as recommended by the European
Higher Education Area. Some problems holding back the correct
future development will also be shown as derived from the specific
context of application of the project.