Abstract: For over a decade, the Pulse Coupled Neural Network
(PCNN) based algorithms have been successfully used in image
interpretation applications including image segmentation. There are
several versions of the PCNN based image segmentation methods,
and the segmentation accuracy of all of them is very sensitive to the
values of the network parameters. Most methods treat PCNN
parameters like linking coefficient and primary firing threshold as
global parameters, and determine them by trial-and-error. The
automatic determination of appropriate values for linking coefficient,
and primary firing threshold is a challenging problem and deserves
further research. This paper presents a method for obtaining global as
well as local values for the linking coefficient and the primary firing
threshold for neurons directly from the image statistics. Extensive
simulation results show that the proposed approach achieves
excellent segmentation accuracy comparable to the best accuracy
obtainable by trial-and-error for a variety of images.
Abstract: The need to implement intelligent highways is much
more emphasized with the growth of vehicle production line as well as vehicle intelligence. The control of intelligent vehicles in order to
reduce human error and boost ease congestion is not accomplished solely by the aid of human resources. The present article is an attempt
to introduce an intelligent control system based on a single central computer. In this project, central computer, without utilizing Global
Positioning System (GPS), is capable of tracking all vehicles, crisis management and control, traffic guidance and recording traffic
crimes along the highway. By the help of RFID technology, vehicles
are connected to computerized systems, intelligent light poles and
other available hardware along the way. By the aid of Wimax
communicative technology, all components of the system are
virtually connected together through local and global networks
devised in them and the energy of the network is provided by the
solar cells installed on the intelligent light poles.
Abstract: This work presents a neural network model for the
clustering analysis of data based on Self Organizing Maps (SOM).
The model evolves during the training stage towards a hierarchical
structure according to the input requirements. The hierarchical structure
symbolizes a specialization tool that provides refinements of the
classification process. The structure behaves like a single map with
different resolutions depending on the region to analyze. The benefits
and performance of the algorithm are discussed in application to the
Iris dataset, a classical example for pattern recognition.
Abstract: A study on the performance of TCP Vegas versus
different TCP variants in homogeneous and heterogeneous wired
networks are performed via simulation experiment using network
simulator (ns-2). This performance evaluation prepared a comparison
medium for the performance evaluation of enhanced-TCP Vegas in
wired network and for wireless network. In homogeneous network,
the performance of TCP Tahoe, TCP Reno, TCP NewReno, TCP
Vegas and TCP SACK are analyzed. In heterogeneous network, the
performances of TCP Vegas against TCP variants are analyzed. TCP
Vegas outperforms other TCP variants in homogeneous wired
network. However, TCP Vegas achieves unfair throughput in
heterogeneous wired network.
Abstract: In this paper we investigate the influence of external
noise on the inference of network structures. The purpose of our
simulations is to gain insights in the experimental design of microarray
experiments to infer, e.g., transcription regulatory networks
from microarray experiments. Here external noise means, that the
dynamics of the system under investigation, e.g., temporal changes of
mRNA concentration, is affected by measurement errors. Additionally
to external noise another problem occurs in the context of microarray
experiments. Practically, it is not possible to monitor the mRNA
concentration over an arbitrary long time period as demanded by the
statistical methods used to learn the underlying network structure. For
this reason, we use only short time series to make our simulations
more biologically plausible.
Abstract: One approach to assess neural networks underlying the cognitive processes is to study Electroencephalography (EEG). It is relevant to detect various mental states and characterize the physiological changes that help to discriminate two situations. That is why an EEG (amplitude, synchrony) classification procedure is described, validated. The two situations are "eyes closed" and "eyes opened" in order to study the "alpha blocking response" phenomenon in the occipital area. The good classification rate between the two situations is 92.1 % (SD = 3.5%) The spatial distribution of a part of amplitude features that helps to discriminate the two situations are located in the occipital regions that permit to validate the localization method. Moreover amplitude features in frontal areas, "short distant" synchrony in frontal areas and "long distant" synchrony between frontal and occipital area also help to discriminate between the two situations. This procedure will be used for mental fatigue detection.
Abstract: In this document we studied more in detail the Performances of the vertical handover in the networks WLAN, WiMAX, UMTS before studying of it the Procedure of Handoff Vertical, the whole buckled by simulations putting forward the performances of the handover in the heterogeneous networks. The goal of Vertical Handover is to carry out several accesses in real-time in the heterogeneous networks. This makes it possible a user to use several networks (such as WLAN UMTS andWiMAX) in parallel, and the system to commutate automatically at another basic station, without disconnecting itself, as if there were no cut and with little loss of data as possible.
Abstract: In the current study we present a system that is
capable to deliver proxy based differentiated service. It will help the
carrier service node to sell a prepaid service to clients and limit the
use to a particular mobile device or devices for a certain time. The
system includes software and hardware architecture for a mobile
device with moderate computational power, and a secure protocol for
communication between it and its carrier service node. On the
carrier service node a proxy runs on a centralized server to be
capable of implementing cryptographic algorithms, while the mobile
device contains a simple embedded processor capable of executing
simple algorithms. One prerequisite is needed for the system to run
efficiently that is a presence of Global Trusted Verification Authority
(GTVA) which is equivalent to certifying authority in IP networks.
This system appears to be of great interest for many commercial
transactions, business to business electronic and mobile commerce,
and military applications.
Abstract: It is expected that ubiquitous era will come soon. A ubiquitous environment has features like peer-to-peer and nomadic environments. Such features can be represented by peer-to-peer systems and mobile ad-hoc networks (MANETs). The features of P2P systems and MANETs are similar, appealing for implementing P2P systems in MANET environment. It has been shown that, however, the performance of the P2P systems designed for wired networks do not perform satisfactorily in mobile ad-hoc environment. Subsequently, this paper proposes a method to improve P2P performance using cross-layer design and the goodness of a node as a peer. The proposed method uses routing metric as well as P2P metric to choose favorable peers to connect. It also utilizes proactive approach for distributing peer information. According to the simulation results, the proposed method provides higher query success rate, shorter query response time and less energy consumption by constructing an efficient overlay network.
Abstract: All the geophysical phenomena including river
networks and flow time series are fractal events inherently and fractal
patterns can be investigated through their behaviors. A non-linear
system like a river basin can well be analyzed by a non-linear
measure such as the fractal analysis. A bilateral study is held on the
fractal properties of the river network and the river flow time series.
A moving window technique is utilized to scan the fractal properties
of them. Results depict both events follow the same strategy
regarding to the fractal properties. Both the river network and the
time series fractal dimension tend to saturate in a distinct value.
Abstract: Several wireless networks security standards have been proposed and widely implemented in both business and home environments in order to protect the network from unauthorized access. However, the implementation of such standards is usually achieved by network administrators without even knowing the standards- weaknesses and strengths. The intention of this paper is to evaluate and analyze the impact over the network-s security due to the implementation of the wireless networks security standards WEP, WPA and WLAN 802.1X.
Abstract: Due to insufficient frequency band and tremendous growth of the mobile users, complex computation is needed for the use of resources. Long distance communication began with the introduction of telegraphs and simple coded pulses, which were used to transmit short messages. Since then numerous advances have rendered reliable transfer of information both easier and quicker. Wireless network refers to any type of computer network that is wireless, and is commonly associated with a telecommunications network whose interconnections between nodes is implemented without the use of wires. Wireless network can be broadly categorized in infrastructure network and infrastructure less network. Infrastructure network is one in which we have a base station to serve the mobile users and in the infrastructure less network is one in which no infrastructure is available to serve the mobile users this kind of networks are also known as mobile Adhoc networks. In this paper we have simulated the result for different scenarios with protocols like AODV and DSR; we simulated the result for throughput, delay and receiving traffic in the given scenario.
Abstract: In this paper, we proposed a method to design a
model-following adaptive controller for linear/nonlinear plants.
Radial basis function neural networks (RBF-NNs), which are known
for their stable learning capability and fast training, are used to
identify linear/nonlinear plants. Simulation results show that the
proposed method is effective in controlling both linear and nonlinear
plants with disturbance in the plant input.
Abstract: The Influence Diagrams (IDs) is a kind of Probabilistic Belief Networks for graphic modeling. The usage of IDs can improve the communication among field experts, modelers, and decision makers, by showing the issue frame discussed from a high-level point of view. This paper enhances the Time-Sliced Influence Diagrams (TSIDs, or called Dynamic IDs) based formalism from a Discrete Event Systems Modeling and Simulation (DES M&S) perspective, for Exploring Analysis (EA) modeling. The enhancements enable a modeler to specify times occurred of endogenous events dynamically with stochastic sampling as model running and to describe the inter- influences among them with variable nodes in a dynamic situation that the existing TSIDs fails to capture. The new class of model is named Dynamic-Stochastic Influence Diagrams (DSIDs). The paper includes a description of the modeling formalism and the hiberarchy simulators implementing its simulation algorithm, and shows a case study to illustrate its enhancements.
Abstract: The dynamic spectrum allocation solutions such as
cognitive radio networks have been proposed as a key technology to
exploit the frequency segments that are spectrally underutilized.
Cognitive radio users work as secondary users who need to
constantly and rapidly sense the presence of primary users or
licensees to utilize their frequency bands if they are inactive. Short
sensing cycles should be run by the secondary users to achieve
higher throughput rates as well as to provide low level of interference
to the primary users by immediately vacating their channels once
they have been detected. In this paper, the throughput-sensing time
relationship in local and cooperative spectrum sensing has been
investigated under two distinct scenarios, namely, constant primary
user protection (CPUP) and constant secondary user spectrum
usability (CSUSU) scenarios. The simulation results show that the
design of sensing slot duration is very critical and depends on the
number of cooperating users under CPUP scenario whereas under
CSUSU, cooperating more users has no effect if the sensing time
used exceeds 5% of the total frame duration.
Abstract: Over the years, many implementations have been
proposed for solving IA networks. These implementations are
concerned with finding a solution efficiently. The primary goal of
our implementation is simplicity and ease of use.
We present an IA network implementation based on finite domain
non-binary CSPs, and constraint logic programming. The
implementation has a GUI which permits the drawing of arbitrary IA
networks. We then show how the implementation can be extended to
find all the solutions to an IA network. One application of finding all
the solutions, is solving probabilistic IA networks.
Abstract: Interactions among proteins are the basis of various
life events. So, it is important to recognize and research protein
interaction sites. A control set that contains 149 protein molecules
were used here. Then 10 features were extracted and 4 sample sets
that contained 9 sliding windows were made according to features.
These 4 sample sets were calculated by Radial Basis Functional neutral
networks which were optimized by Particle Swarm Optimization
respectively. Then 4 groups of results were obtained. Finally, these 4
groups of results were integrated by decision fusion (DF) and Genetic
Algorithm based Selected Ensemble (GASEN). A better accuracy was
got by DF and GASEN. So, the integrated methods were proved to
be effective.
Abstract: The aim of this paper is to propose a mathematical
model to determine invariant sets, set covering, orbits and, in
particular, attractors in the set of tourism variables. Analysis was
carried out based on a pre-designed algorithm and applying our
interpretation of chaos theory developed in the context of General
Systems Theory. This article sets out the causal relationships
associated with tourist flows in order to enable the formulation of
appropriate strategies. Our results can be applied to numerous cases.
For example, in the analysis of tourist flows, these findings can be
used to determine whether the behaviour of certain groups affects that
of other groups and to analyse tourist behaviour in terms of the most
relevant variables. Unlike statistical analyses that merely provide
information on current data, our method uses orbit analysis to
forecast, if attractors are found, the behaviour of tourist variables in
the immediate future.
Abstract: End milling process is one of the common metal
cutting operations used for machining parts in manufacturing
industry. It is usually performed at the final stage in manufacturing a
product and surface roughness of the produced job plays an
important role. In general, the surface roughness affects wear
resistance, ductility, tensile, fatigue strength, etc., for machined parts
and cannot be neglected in design. In the present work an
experimental investigation of end milling of aluminium alloy with
carbide tool is carried out and the effect of different cutting
parameters on the response are studied with three-dimensional
surface plots. An artificial neural network (ANN) is used to establish
the relationship between the surface roughness and the input cutting
parameters (i.e., spindle speed, feed, and depth of cut). The Matlab
ANN toolbox works on feed forward back propagation algorithm is
used for modeling purpose. 3-12-1 network structure having
minimum average prediction error found as best network architecture
for predicting surface roughness value. The network predicts surface
roughness for unseen data and found that the result/prediction is
better. For desired surface finish of the component to be produced
there are many different combination of cutting parameters are
available. The optimum cutting parameter for obtaining desired
surface finish, to maximize tool life is predicted. The methodology is
demonstrated, number of problems are solved and algorithm is coded
in Matlab®.