The Steiner tree is the underlying model for multicast communication. This paper presents a
novel ant colony algorithm guided by problem relaxation for unconstrained Steiner tree in static
wireless ad hoc networks. The framework of the proposed algorithm is based on ant colony
system (ACS). In the first step, the ants probabilistically construct the path from the source tothe terminal nodes. These paths are then merged together to generate a Steiner tree rooted at the source. The problem is relaxed to incorporate the structural information into the heuristic value for the selection of nodes. The effectiveness of the algorithm is tested on the benchmark problems of the OR-library. Simulation results show that our algorithm can find optimal Steiner tree with high success rate.
One of the important steps in routing is to find a feasible path based on the state information. In order to support real-time multimedia applications, the feasible path that satisfies one or more constraints has to be computed within a very short time. Therefore, the paper presents a genetic algorithm to solve the paths tree problem subject to cost constraints. The objective of the algorithm is to find the set of edges connecting all nodes such that the sum of the edge costs from the source (root) to each node is minimized. I.e. the path from the root to each node must be a minimum cost path connecting them. The algorithm has been applied on two sample networks, the first network with eight nodes, and the last one with eleven nodes to illustrate its efficiency.
Incorporating Kalman Filter in the Optimization of Quantum Neural Network Par...Waqas Tariq
Kalman filter have been used for the estimation of instantaneous states of linear dynamic systems. It is a good tool for inferring of missing information from noisy measurement. The quantum neural network is another approach to the merging of fuzzy logic with the neural network and that by the investment of quantum mechanics theory in building the structure of neural network. The gradient descent algorithm has been used, widely, in training the neural network, but the problem of local minima is one of the disadvantages of this algorithm. This paper presents an algorithm to train the quantum neural network by using the extended kalman filter.
Combining Neural Network and Firefly Algorithm to Predict Stock Price in Tehr...Editor IJCATR
In the present research, prediction of stock price index in Tehran stock exchange by using neural
networks and firefly algorithm in chaotic behavior of price index stock exchange are studied. Two data sets
are selected for neural network input. Various breaks of index and macro economic factors are considered
as independent variables. Also, firefly algorithm is used to [redict price index in next week. The results of
research show that combining neural networks and firefly optimization algorithm has better performance
than neural network to predict the price index. In addition, acceptable value of error-sequre means for
network error in test data show that there are chaotic mevements in behaviour of price index.
P REDICTION F OR S HORT -T ERM T RAFFIC F LOW B ASED O N O PTIMIZED W...ijcsit
Short term traffic forecasting has been a very impo
rtant consideration in many areas of transportation
research for more than 3 decades. Short-term traffi
c forecasting based on data driven methods is one o
f the
most dynamic and developing research arenas with en
ormous published literature. In order to improve
forecasting model accuracy of wavelet neural networ
k, an adaptive particle swarm optimization algorith
m
based on cloud theory was proposed, not only to hel
p improve search performance, but also speed up
individual optimizing ability. And the inertia weig
ht adaptively changes depending on X-conditional cl
oud
generator which has the stable tendency and randomn
ess property .Then the adaptive particle swarm
optimization algorithm based on cloud theory was us
ed to optimize the weights and thresholds of wavele
t
BP neural network, Instead of traditional gradient
descent method . At last, wavelet BP neural network
was
trained to search for the optimal solution. Based o
n above theory, an improved wavelet neural network
model based on modified particle swarm optimization
algorithm was proposed and the availability of the
modified prediction method was proved by predicting
the time series of real traffic flow. At last, the
computer simulations have shown that the nonlinear
fitting and accuracy of the modified prediction
methods are better than other prediction methods.
An enhanced fireworks algorithm to generate prime key for multiple users in f...journalBEEI
This work presents a new method to enhance the performance of fireworks algorithm to generate a prime key for multiple users. A threshold technique in image segmentation is used as one of the major steps. It is used processing the digital image. Some useful algorithms and methods for dividing and sharing an image, including measuring, recognizing, and recognizing, are common. In this research, we proposed a hybrid technique of fireworks and camel herd algorithms (HFCA), where Fireworks are based on 3-dimension (3D) logistic chaotic maps. Both, the Otsu method and the convolution technique are used in the pre-processing image for further analysis. The Otsu is employed to segment the image and find the threshold for each image, and convolution is used to extract the features of the used images. The sample of the images consists of two images of fingerprints taken from the Biometric System Lab (University of Bologna). The performance of the anticipated method is evaluated by using FVC2004 dataset. The results of the work enhanced algorithm, so quick response code (QRcode) is used to generate a stream key by using random text or number, which is a class of symmetric-key algorithm that operates on individual bits or bytes.
One of the important steps in routing is to find a feasible path based on the state information. In order to support real-time multimedia applications, the feasible path that satisfies one or more constraints has to be computed within a very short time. Therefore, the paper presents a genetic algorithm to solve the paths tree problem subject to cost constraints. The objective of the algorithm is to find the set of edges connecting all nodes such that the sum of the edge costs from the source (root) to each node is minimized. I.e. the path from the root to each node must be a minimum cost path connecting them. The algorithm has been applied on two sample networks, the first network with eight nodes, and the last one with eleven nodes to illustrate its efficiency.
Incorporating Kalman Filter in the Optimization of Quantum Neural Network Par...Waqas Tariq
Kalman filter have been used for the estimation of instantaneous states of linear dynamic systems. It is a good tool for inferring of missing information from noisy measurement. The quantum neural network is another approach to the merging of fuzzy logic with the neural network and that by the investment of quantum mechanics theory in building the structure of neural network. The gradient descent algorithm has been used, widely, in training the neural network, but the problem of local minima is one of the disadvantages of this algorithm. This paper presents an algorithm to train the quantum neural network by using the extended kalman filter.
Combining Neural Network and Firefly Algorithm to Predict Stock Price in Tehr...Editor IJCATR
In the present research, prediction of stock price index in Tehran stock exchange by using neural
networks and firefly algorithm in chaotic behavior of price index stock exchange are studied. Two data sets
are selected for neural network input. Various breaks of index and macro economic factors are considered
as independent variables. Also, firefly algorithm is used to [redict price index in next week. The results of
research show that combining neural networks and firefly optimization algorithm has better performance
than neural network to predict the price index. In addition, acceptable value of error-sequre means for
network error in test data show that there are chaotic mevements in behaviour of price index.
P REDICTION F OR S HORT -T ERM T RAFFIC F LOW B ASED O N O PTIMIZED W...ijcsit
Short term traffic forecasting has been a very impo
rtant consideration in many areas of transportation
research for more than 3 decades. Short-term traffi
c forecasting based on data driven methods is one o
f the
most dynamic and developing research arenas with en
ormous published literature. In order to improve
forecasting model accuracy of wavelet neural networ
k, an adaptive particle swarm optimization algorith
m
based on cloud theory was proposed, not only to hel
p improve search performance, but also speed up
individual optimizing ability. And the inertia weig
ht adaptively changes depending on X-conditional cl
oud
generator which has the stable tendency and randomn
ess property .Then the adaptive particle swarm
optimization algorithm based on cloud theory was us
ed to optimize the weights and thresholds of wavele
t
BP neural network, Instead of traditional gradient
descent method . At last, wavelet BP neural network
was
trained to search for the optimal solution. Based o
n above theory, an improved wavelet neural network
model based on modified particle swarm optimization
algorithm was proposed and the availability of the
modified prediction method was proved by predicting
the time series of real traffic flow. At last, the
computer simulations have shown that the nonlinear
fitting and accuracy of the modified prediction
methods are better than other prediction methods.
An enhanced fireworks algorithm to generate prime key for multiple users in f...journalBEEI
This work presents a new method to enhance the performance of fireworks algorithm to generate a prime key for multiple users. A threshold technique in image segmentation is used as one of the major steps. It is used processing the digital image. Some useful algorithms and methods for dividing and sharing an image, including measuring, recognizing, and recognizing, are common. In this research, we proposed a hybrid technique of fireworks and camel herd algorithms (HFCA), where Fireworks are based on 3-dimension (3D) logistic chaotic maps. Both, the Otsu method and the convolution technique are used in the pre-processing image for further analysis. The Otsu is employed to segment the image and find the threshold for each image, and convolution is used to extract the features of the used images. The sample of the images consists of two images of fingerprints taken from the Biometric System Lab (University of Bologna). The performance of the anticipated method is evaluated by using FVC2004 dataset. The results of the work enhanced algorithm, so quick response code (QRcode) is used to generate a stream key by using random text or number, which is a class of symmetric-key algorithm that operates on individual bits or bytes.
Comparison Between Clustering Algorithms for Microarray Data AnalysisIOSR Journals
Currently, there are two techniques used for large-scale gene-expression profiling; microarray and
RNA-Sequence (RNA-Seq).This paper is intended to study and compare different clustering algorithms that used
in microarray data analysis. Microarray is a DNA molecules array which allows multiple hybridization
experiments to be carried out simultaneously and trace expression levels of thousands of genes. It is a highthroughput
technology for gene expression analysis and becomes an effective tool for biomedical research.
Microarray analysis aims to interpret the data produced from experiments on DNA, RNA, and protein
microarrays, which enable researchers to investigate the expression state of a large number of genes. Data
clustering represents the first and main process in microarray data analysis. The k-means, fuzzy c-mean, selforganizing
map, and hierarchical clustering algorithms are under investigation in this paper. These algorithms
are compared based on their clustering model.
α Nearness ant colony system with adaptive strategies for the traveling sales...ijfcstjournal
On account of ant colony algorithm easy to fall into local optimum, this paper presents an improved ant
colony optimization called α-AACS and reports its performance. At first, we provide an concise description
of the original ant colony system(ACS) and introduce α-nearness based on the minimum 1-tree for ACS’s
disadvantage, which better reflects the chances of a given link being a member of an optimal tour. Then, we
improve α-nearness by computing a lower bound and propose other adaptations for ACS. Finally, we
conduct a fair competition between our algorithm and others. The results clearly show that α-AACS has a
better global searching ability in finding the best solutions, which indicates that α-AACS is an effective
approach for solving the traveling salesman problem.
Behavior study of entropy in a digital image through an iterative algorithmijscmcj
Image segmentation is a critical step in computer vision tasks constituting an essential issue for pattern recognition and visual interpretation. In this paper, we study the behavior of entropy in digital images through an iterative algorithm of mean shift filtering. The order of a digital image in gray levels is defined. The behavior of Shannon entropy is analyzed and then compared, taking into account the number of iterations of our algorithm, with the maximum entropy that could be achieved under the same order. The use of equivalence classes it induced, which allow us to interpret entropy as a hyper-surface in real m dimensional space. The difference of the maximum entropy of order n and the entropy of the image is used to group the the iterations, in order to caractrizes the performance of the algorithm.
Here is my class on the multilayer perceptron where I look at the following:
1.- The entire backproagation algorithm based in the gradient descent
However, I am planning the tanning based in Kalman filters.
2.- The use of matrix computations to simplify the implementations.
I hope you enjoy it.
A Comparative Analysis of Feature Selection Methods for Clustering DNA SequencesCSCJournals
Large-scale analysis of genome sequences is in progress around the world, the major application of which is to establish the evolutionary relationship among the species using phylogenetic trees. Hierarchical agglomerative algorithms can be used to generate such phylogenetic trees given the distance matrix representing the dissimilarity among the species. ClustalW and Muscle are two general purpose programs that generates distance matrix from the input DNA or protein sequences. The limitation of these programs is that they are based on Smith-Waterman algorithm which uses dynamic programming for doing the pair-wise alignment. This is an extremely time consuming process and the existing systems may even fail to work for larger input data set. To overcome this limitation, we have used the frequency of codons usage as an approximation to find dissimilarity among species. The proposed technique further reduces the complexity by extracting only the significant features of the species from the mtDNA sequences using the techniques like frequent codons, codons with maximum range value or PCA technique. We have observed that the proposed system produces nearly accurate results in a significantly reduced running time.
An improved ant colony algorithm based onIJCI JOURNAL
This paper presents an improved chaotic ant colony system algorithm (ICACS) for solving combinatorial
optimization problems. The existing algorithms still have some imperfections, we use a combination of two
different operators to improve the performance of algorithm in this work. First, 3-opt local search is used
as a framework for the implementation of the ACS to improve the solution quality; Furthermore, chaos is
proposed in the work to modify the method of pheromone update to avoid the algorithm from dropping into
local optimum, thereby finding the favorable solutions. From the experimental results, we can conclude
that ICACS has much higher quality solutions than the original ACS, and can jump over the region of the
local optimum, and escape from the trap of a local optimum successfully and achieve the best solutions.
Therefore, it’s better and more effective algorithm for TSP.
In the classical model, the fundamental building block is represented by bits exists in two states a 0 or a 1. Computations are done by logic gates on the bits to produce other bits. By increasing the number of bits, the complexity of problem and the time of computation increases. A quantum algorithm is a sequence of operations on a register to transform it into a state which when measured yields the desired result. This paper provides introduction to quantum computation by developing qubit, quantum gate and quantum circuits.
COMPUTATIONAL PERFORMANCE OF QUANTUM PHASE ESTIMATION ALGORITHMcsitconf
A quantum computation problem is discussed in this paper. Many new features that make
quantum computation superior to classical computation can be attributed to quantum coherence
effect, which depends on the phase of quantum coherent state. Quantum Fourier transform
algorithm, the most commonly used algorithm, is introduced. And one of its most important
applications, phase estimation of quantum state based on quantum Fourier transform, is
presented in details. The flow of phase estimation algorithm and the quantum circuit model are
shown. And the error of the output phase value, as well as the probability of measurement, is
analysed. The probability distribution of the measuring result of phase value is presented and
the computational efficiency is discussed.
COMPUTATIONAL PERFORMANCE OF QUANTUM PHASE ESTIMATION ALGORITHMcscpconf
A quantum computation problem is discussed in this paper. Many new features that make quantum computation superior to classical computation can be attributed to quantum coherence
effect, which depends on the phase of quantum coherent state. Quantum Fourier transform algorithm, the most commonly used algorithm, is introduced. And one of its most important
applications, phase estimation of quantum state based on quantum Fourier transform, is presented in details. The flow of phase estimation algorithm and the quantum circuit model are
shown. And the error of the output phase value, as well as the probability of measurement, is analysed. The probability distribution of the measuring result of phase value is presented and the computational efficiency is discussed.
ENTROPY BASED ASSESSMENT OF HYDROMETRIC NETWORK USING NORMAL AND LOG-NORMAL D...mathsjournal
Establishment and maintenance of a hydrometric network in any geographical region is required for planning, design and management of water resources. Setting up and maintaining a hydrometric network is an evolutionary process, wherein a network is established early in the development of the geographical area; and the network reviewed and upgraded periodically to arrive at the optimum network. This paper presents the methodology adopted in assessing the hydrometric network using entropy theory adopting normal and log-normal probability distributions. The technique, involving computation of marginal and conditional entropy values, is applied to the upper Bhima basin up to Ujjani reservoir for illustrative purposes; and results presented. The derived optimum hydrometric network for the basin is evaluated based on WMO guidelines for minimum density of hydrometric network.
An Ant Algorithm for Solving QoS Multicast Routing ProblemCSCJournals
Abstract: Many applications require send information from a source to multiple destinations through a communication network. To support these applications, it is necessary to determine a multicast tree of minimal cost to connect the source node to the destination nodes subject to delay constraints. Based on the Ant System algorithm, we present an ant algorithm to find the multicast tree that minimizes the total cost. In the proposed algorithm, the k shortest paths from the source node to the destination nodes are used for genotype representation. The expermintal results show that the algorithm can find optimal solution quickly and has a good scalability.
Comparison Between Clustering Algorithms for Microarray Data AnalysisIOSR Journals
Currently, there are two techniques used for large-scale gene-expression profiling; microarray and
RNA-Sequence (RNA-Seq).This paper is intended to study and compare different clustering algorithms that used
in microarray data analysis. Microarray is a DNA molecules array which allows multiple hybridization
experiments to be carried out simultaneously and trace expression levels of thousands of genes. It is a highthroughput
technology for gene expression analysis and becomes an effective tool for biomedical research.
Microarray analysis aims to interpret the data produced from experiments on DNA, RNA, and protein
microarrays, which enable researchers to investigate the expression state of a large number of genes. Data
clustering represents the first and main process in microarray data analysis. The k-means, fuzzy c-mean, selforganizing
map, and hierarchical clustering algorithms are under investigation in this paper. These algorithms
are compared based on their clustering model.
α Nearness ant colony system with adaptive strategies for the traveling sales...ijfcstjournal
On account of ant colony algorithm easy to fall into local optimum, this paper presents an improved ant
colony optimization called α-AACS and reports its performance. At first, we provide an concise description
of the original ant colony system(ACS) and introduce α-nearness based on the minimum 1-tree for ACS’s
disadvantage, which better reflects the chances of a given link being a member of an optimal tour. Then, we
improve α-nearness by computing a lower bound and propose other adaptations for ACS. Finally, we
conduct a fair competition between our algorithm and others. The results clearly show that α-AACS has a
better global searching ability in finding the best solutions, which indicates that α-AACS is an effective
approach for solving the traveling salesman problem.
Behavior study of entropy in a digital image through an iterative algorithmijscmcj
Image segmentation is a critical step in computer vision tasks constituting an essential issue for pattern recognition and visual interpretation. In this paper, we study the behavior of entropy in digital images through an iterative algorithm of mean shift filtering. The order of a digital image in gray levels is defined. The behavior of Shannon entropy is analyzed and then compared, taking into account the number of iterations of our algorithm, with the maximum entropy that could be achieved under the same order. The use of equivalence classes it induced, which allow us to interpret entropy as a hyper-surface in real m dimensional space. The difference of the maximum entropy of order n and the entropy of the image is used to group the the iterations, in order to caractrizes the performance of the algorithm.
Here is my class on the multilayer perceptron where I look at the following:
1.- The entire backproagation algorithm based in the gradient descent
However, I am planning the tanning based in Kalman filters.
2.- The use of matrix computations to simplify the implementations.
I hope you enjoy it.
A Comparative Analysis of Feature Selection Methods for Clustering DNA SequencesCSCJournals
Large-scale analysis of genome sequences is in progress around the world, the major application of which is to establish the evolutionary relationship among the species using phylogenetic trees. Hierarchical agglomerative algorithms can be used to generate such phylogenetic trees given the distance matrix representing the dissimilarity among the species. ClustalW and Muscle are two general purpose programs that generates distance matrix from the input DNA or protein sequences. The limitation of these programs is that they are based on Smith-Waterman algorithm which uses dynamic programming for doing the pair-wise alignment. This is an extremely time consuming process and the existing systems may even fail to work for larger input data set. To overcome this limitation, we have used the frequency of codons usage as an approximation to find dissimilarity among species. The proposed technique further reduces the complexity by extracting only the significant features of the species from the mtDNA sequences using the techniques like frequent codons, codons with maximum range value or PCA technique. We have observed that the proposed system produces nearly accurate results in a significantly reduced running time.
An improved ant colony algorithm based onIJCI JOURNAL
This paper presents an improved chaotic ant colony system algorithm (ICACS) for solving combinatorial
optimization problems. The existing algorithms still have some imperfections, we use a combination of two
different operators to improve the performance of algorithm in this work. First, 3-opt local search is used
as a framework for the implementation of the ACS to improve the solution quality; Furthermore, chaos is
proposed in the work to modify the method of pheromone update to avoid the algorithm from dropping into
local optimum, thereby finding the favorable solutions. From the experimental results, we can conclude
that ICACS has much higher quality solutions than the original ACS, and can jump over the region of the
local optimum, and escape from the trap of a local optimum successfully and achieve the best solutions.
Therefore, it’s better and more effective algorithm for TSP.
In the classical model, the fundamental building block is represented by bits exists in two states a 0 or a 1. Computations are done by logic gates on the bits to produce other bits. By increasing the number of bits, the complexity of problem and the time of computation increases. A quantum algorithm is a sequence of operations on a register to transform it into a state which when measured yields the desired result. This paper provides introduction to quantum computation by developing qubit, quantum gate and quantum circuits.
COMPUTATIONAL PERFORMANCE OF QUANTUM PHASE ESTIMATION ALGORITHMcsitconf
A quantum computation problem is discussed in this paper. Many new features that make
quantum computation superior to classical computation can be attributed to quantum coherence
effect, which depends on the phase of quantum coherent state. Quantum Fourier transform
algorithm, the most commonly used algorithm, is introduced. And one of its most important
applications, phase estimation of quantum state based on quantum Fourier transform, is
presented in details. The flow of phase estimation algorithm and the quantum circuit model are
shown. And the error of the output phase value, as well as the probability of measurement, is
analysed. The probability distribution of the measuring result of phase value is presented and
the computational efficiency is discussed.
COMPUTATIONAL PERFORMANCE OF QUANTUM PHASE ESTIMATION ALGORITHMcscpconf
A quantum computation problem is discussed in this paper. Many new features that make quantum computation superior to classical computation can be attributed to quantum coherence
effect, which depends on the phase of quantum coherent state. Quantum Fourier transform algorithm, the most commonly used algorithm, is introduced. And one of its most important
applications, phase estimation of quantum state based on quantum Fourier transform, is presented in details. The flow of phase estimation algorithm and the quantum circuit model are
shown. And the error of the output phase value, as well as the probability of measurement, is analysed. The probability distribution of the measuring result of phase value is presented and the computational efficiency is discussed.
ENTROPY BASED ASSESSMENT OF HYDROMETRIC NETWORK USING NORMAL AND LOG-NORMAL D...mathsjournal
Establishment and maintenance of a hydrometric network in any geographical region is required for planning, design and management of water resources. Setting up and maintaining a hydrometric network is an evolutionary process, wherein a network is established early in the development of the geographical area; and the network reviewed and upgraded periodically to arrive at the optimum network. This paper presents the methodology adopted in assessing the hydrometric network using entropy theory adopting normal and log-normal probability distributions. The technique, involving computation of marginal and conditional entropy values, is applied to the upper Bhima basin up to Ujjani reservoir for illustrative purposes; and results presented. The derived optimum hydrometric network for the basin is evaluated based on WMO guidelines for minimum density of hydrometric network.
An Ant Algorithm for Solving QoS Multicast Routing ProblemCSCJournals
Abstract: Many applications require send information from a source to multiple destinations through a communication network. To support these applications, it is necessary to determine a multicast tree of minimal cost to connect the source node to the destination nodes subject to delay constraints. Based on the Ant System algorithm, we present an ant algorithm to find the multicast tree that minimizes the total cost. In the proposed algorithm, the k shortest paths from the source node to the destination nodes are used for genotype representation. The expermintal results show that the algorithm can find optimal solution quickly and has a good scalability.
FAULT TOLERANT ROUTING ALGORITHM IN OCTAGON-CELL INTERCONNECTED NETWORK FOR H...IJCNCJournal
Octagon-Cell interconnected network can be viewed as an undirected graph, in which vertices and edges
can be compared with processors and bidirectional communication links respectively between the
processing elements. It has attractive features like small diameter and better bisection width and constant
node degree. It is analyzed to arrive at fault-tolerant communication. A fault tolerant communication
scheme for this network is described in this paper. Here an efficient routing scheme has been described
which routes the horizontal moving messages from source node to the destination node in presence of faulty
nodes / link failure along the path. In this algorithm when a message is received by an intermediate node, it
will consider itself a new source node.
nternational Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region IJECEIAES
This paper presents data an Ant colony optimization (ACO) based data hiding technique. ACO is used to detect complex region of cover image and afterward, least significant bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. ACO is an algorithm developed inspired by the inborn manners of ant species. The ant leaves pheromone on the ground for searching food and provisions. The proposed ACO-based data hiding in complex region establishes an array of pheromone, also called pheromone matrix, which represents the complex region in sequence at each pixel position of the cover image. The pheromone matrix is developed according to the movements of ants, determined by local differences of the image element’s intensity. The least significant bits of complex region pixels are substituted with message bits, to hide secret information. The experimental results, provided, show the significance of the performance of the proposed method.
Random Keying Technique for Security in Wireless Sensor Networks Based on Mem...ijcsta
Wireless Sensor Networks (WSNs) are often prone to risk of security attacks and vulnerabilities. This is because of
the less human intervention in their operations. Hence, novel security mechanisms and techniques are of a prime
importance in these types of networks. In this context, we propose a unique security scheme, which coalesce the
random keying technique with memetics. The application of these kinds of bio-inspired computation in WSNs
provides robust security in the network with the obtained results supporting the security concerns of the network.
AN OPTIMIZED HYBRID APPROACH FOR PATH FINDINGijfcstjournal
Path finding algorithm addresses problem of finding shortest path from source to destination avoiding
obstacles. There exist various search algorithms namely A*, Dijkstra's and ant colony optimization. Unlike
most path finding algorithms which require destination co-ordinates to compute path, the proposed
algorithm comprises of a new method which finds path using backtracking without requiring destination
co-ordinates. Moreover, in existing path finding algorithm, the number of iterations required to find path is
large. Hence, to overcome this, an algorithm is proposed which reduces number of iterations required to
traverse the path. The proposed algorithm is hybrid of backtracking and a new technique(modified 8-
neighbor approach). The proposed algorithm can become essential part in location based, network, gaming
applications. grid traversal, navigation, gaming applications, mobile robot and Artificial Intelligence.
Path finding algorithm addresses problem of finding shortest path from source to destination avoiding
obstacles. There exist various search algorithms namely A*, Dijkstra's and ant colony optimization. Unlike
most path finding algorithms which require destination co-ordinates to compute path, the proposed
algorithm comprises of a new method which finds path using backtracking without requiring destination
co-ordinates. Moreover, in existing path finding algorithm, the number of iterations required to find path is
large. Hence, to overcome this, an algorithm is proposed which reduces number of iterations required to
traverse the path. The proposed algorithm is hybrid of backtracking and a new technique(modified 8-
neighbor approach). The proposed algorithm can become essential part in location based, network, gaming
applications. grid traversal, navigation, gaming applications, mobile robot and Artificial Intelligence.
Ant Colony Optimization Based Energy Efficient on-Demand Multipath Routing Sc...ijsrd.com
Reliable transmission has become one of the major aspects of a wireless sensor network. The current paper provides an Ant Colony Optimization based method for providing multi path routes. These routes are provided on-demand, hence they can be used in any dynamic system. The advantage of this system is that it can provide near optimal results within the stipulated time.
Ant Colony Optimization for Optimal Low-Pass State Variable Filter Sizing IJECEIAES
In analog filter design, discrete components values such as resistors (R) and capacitors (C) are selected from the series following constant values chosen. Exhaustive search on all possible combinations for an optimized design is not feasible. In this paper, we present an application of the Ant Colony Optimization technique (ACO) in order to selected optimal values of resistors and capacitors from different manufactured series to satisfy the filter design criteria. Three variants of the Ant Colony Optimization are applied, namely, the AS (Ant System), the MMAS (Min-Max AS) and the ACS (Ant Colony System), for the optimal sizing of the Low-Pass State Variable Filter. SPICE simulations are used to validate the obtained results/performances which are compared with already published works.
Chaotic Secure Communication Using Iterated Filtering Method P. Karthik -Assistant Professor,
D. Gokul Prashanth -UG Scholar,
T. Gokul - UG Scholar,
Department of Electronics and Communication Engineering,
SNS College of Engineering, Coimbatore, India.
An efficient ant optimized multipath routing in wireless sensor networkEditor Jacotech
Today, the Wireless Sensor Network is increasingly gaining popularity and importance. It is the more interesting and stimulating area of research. Now, the WSN is applied in object tracking and environmental monitoring applications. This paper presents the self-optimized model of multipath routing algorithm for WSN which considers definite parameters like delay, throughput level and loss and generates the outcomes that maximizes data throughput rate and minimizes delay and loss. This algorithm is based on ANT optimization technique that will bring out an optimal and organized route for WSN and is also to avoid congestion in WSN, the algorithm incorporate multipath capability..
Chaotic ANT System Optimization for Path Planning of the Mobile Robotscseij
This paper presents an improved ant system algorithm for path planning of the mobile robot under the complicated environment. To solve the drawback of the traditional ant colony system algorithm (ACS), which usually falls into the local optimum, we propose an improved ant colony system algorithm (IACS) based on chaos. Simulation experiments show that chaotic ant colony algorithm not only enhances the global search capability, but also has more effective than the traditional algorithm.
ANALYSIS OF LAND SURFACE DEFORMATION GRADIENT BY DINSAR cscpconf
The progressive development of Synthetic Aperture Radar (SAR) systems diversify the exploitation of the generated images by these systems in different applications of geoscience. Detection and monitoring surface deformations, procreated by various phenomena had benefited from this evolution and had been realized by interferometry (InSAR) and differential interferometry (DInSAR) techniques. Nevertheless, spatial and temporal decorrelations of the interferometric couples used, limit strongly the precision of analysis results by these techniques. In this context, we propose, in this work, a methodological approach of surface deformation detection and analysis by differential interferograms to show the limits of this technique according to noise quality and level. The detectability model is generated from the deformation signatures, by simulating a linear fault merged to the images couples of ERS1 / ERS2 sensors acquired in a region of the Algerian south.
4D AUTOMATIC LIP-READING FOR SPEAKER'S FACE IDENTIFCATIONcscpconf
A novel based a trajectory-guided, concatenating approach for synthesizing high-quality image real sample renders video is proposed . The lips reading automated is seeking for modeled the closest real image sample sequence preserve in the library under the data video to the HMM predicted trajectory. The object trajectory is modeled obtained by projecting the face patterns into an KDA feature space is estimated. The approach for speaker's face identification by using synthesise the identity surface of a subject face from a small sample of patterns which sparsely each the view sphere. An KDA algorithm use to the Lip-reading image is discrimination, after that work consisted of in the low dimensional for the fundamental lip features vector is reduced by using the 2D-DCT.The mouth of the set area dimensionality is ordered by a normally reduction base on the PCA to obtain the Eigen lips approach, their proposed approach by[33]. The subjective performance results of the cost function under the automatic lips reading modeled , which wasn’t illustrate the superior performance of the
method.
MOVING FROM WATERFALL TO AGILE PROCESS IN SOFTWARE ENGINEERING CAPSTONE PROJE...cscpconf
Universities offer software engineering capstone course to simulate a real world-working environment in which students can work in a team for a fixed period to deliver a quality product. The objective of the paper is to report on our experience in moving from Waterfall process to Agile process in conducting the software engineering capstone project. We present the capstone course designs for both Waterfall driven and Agile driven methodologies that highlight the structure, deliverables and assessment plans.To evaluate the improvement, we conducted a survey for two different sections taught by two different instructors to evaluate students’ experience in moving from traditional Waterfall model to Agile like process. Twentyeight students filled the survey. The survey consisted of eight multiple-choice questions and an open-ended question to collect feedback from students. The survey results show that students were able to attain hands one experience, which simulate a real world-working environment. The results also show that the Agile approach helped students to have overall better design and avoid mistakes they have made in the initial design completed in of the first phase of the capstone project. In addition, they were able to decide on their team capabilities, training needs and thus learn the required technologies earlier which is reflected on the final product quality
PROMOTING STUDENT ENGAGEMENT USING SOCIAL MEDIA TECHNOLOGIEScscpconf
Using social media in education provides learners with an informal way for communication. Informal communication tends to remove barriers and hence promotes student engagement. This paper presents our experience in using three different social media technologies in teaching software project management course. We conducted different surveys at the end of every semester to evaluate students’ satisfaction and engagement. Results show that using social media enhances students’ engagement and satisfaction. However, familiarity with the tool is an important factor for student satisfaction.
A SURVEY ON QUESTION ANSWERING SYSTEMS: THE ADVANCES OF FUZZY LOGICcscpconf
In real world computing environment with using a computer to answer questions has been a human dream since the beginning of the digital era, Question-answering systems are referred to as intelligent systems, that can be used to provide responses for the questions being asked by the user based on certain facts or rules stored in the knowledge base it can generate answers of questions asked in natural , and the first main idea of fuzzy logic was to working on the problem of computer understanding of natural language, so this survey paper provides an overview on what Question-Answering is and its system architecture and the possible relationship and
different with fuzzy logic, as well as the previous related research with respect to approaches that were followed. At the end, the survey provides an analytical discussion of the proposed QA models, along or combined with fuzzy logic and their main contributions and limitations.
DYNAMIC PHONE WARPING – A METHOD TO MEASURE THE DISTANCE BETWEEN PRONUNCIATIONS cscpconf
Human beings generate different speech waveforms while speaking the same word at different times. Also, different human beings have different accents and generate significantly varying speech waveforms for the same word. There is a need to measure the distances between various words which facilitate preparation of pronunciation dictionaries. A new algorithm called Dynamic Phone Warping (DPW) is presented in this paper. It uses dynamic programming technique for global alignment and shortest distance measurements. The DPW algorithm can be used to enhance the pronunciation dictionaries of the well-known languages like English or to build pronunciation dictionaries to the less known sparse languages. The precision measurement experiments show 88.9% accuracy.
INTELLIGENT ELECTRONIC ASSESSMENT FOR SUBJECTIVE EXAMS cscpconf
In education, the use of electronic (E) examination systems is not a novel idea, as Eexamination systems have been used to conduct objective assessments for the last few years. This research deals with randomly designed E-examinations and proposes an E-assessment system that can be used for subjective questions. This system assesses answers to subjective questions by finding a matching ratio for the keywords in instructor and student answers. The matching ratio is achieved based on semantic and document similarity. The assessment system is composed of four modules: preprocessing, keyword expansion, matching, and grading. A survey and case study were used in the research design to validate the proposed system. The examination assessment system will help instructors to save time, costs, and resources, while increasing efficiency and improving the productivity of exam setting and assessments.
TWO DISCRETE BINARY VERSIONS OF AFRICAN BUFFALO OPTIMIZATION METAHEURISTICcscpconf
African Buffalo Optimization (ABO) is one of the most recent swarms intelligence based metaheuristics. ABO algorithm is inspired by the buffalo’s behavior and lifestyle. Unfortunately, the standard ABO algorithm is proposed only for continuous optimization problems. In this paper, the authors propose two discrete binary ABO algorithms to deal with binary optimization problems. In the first version (called SBABO) they use the sigmoid function and probability model to generate binary solutions. In the second version (called LBABO) they use some logical operator to operate the binary solutions. Computational results on two knapsack problems (KP and MKP) instances show the effectiveness of the proposed algorithm and their ability to achieve good and promising solutions.
DETECTION OF ALGORITHMICALLY GENERATED MALICIOUS DOMAINcscpconf
In recent years, many malware writers have relied on Dynamic Domain Name Services (DDNS) to maintain their Command and Control (C&C) network infrastructure to ensure a persistence presence on a compromised host. Amongst the various DDNS techniques, Domain Generation Algorithm (DGA) is often perceived as the most difficult to detect using traditional methods. This paper presents an approach for detecting DGA using frequency analysis of the character distribution and the weighted scores of the domain names. The approach’s feasibility is demonstrated using a range of legitimate domains and a number of malicious algorithmicallygenerated domain names. Findings from this study show that domain names made up of English characters “a-z” achieving a weighted score of < 45 are often associated with DGA. When a weighted score of < 45 is applied to the Alexa one million list of domain names, only 15% of the domain names were treated as non-human generated.
GLOBAL MUSIC ASSET ASSURANCE DIGITAL CURRENCY: A DRM SOLUTION FOR STREAMING C...cscpconf
The amount of piracy in the streaming digital content in general and the music industry in specific is posing a real challenge to digital content owners. This paper presents a DRM solution to monetizing, tracking and controlling online streaming content cross platforms for IP enabled devices. The paper benefits from the current advances in Blockchain and cryptocurrencies. Specifically, the paper presents a Global Music Asset Assurance (GoMAA) digital currency and presents the iMediaStreams Blockchain to enable the secure dissemination and tracking of the streamed content. The proposed solution provides the data owner the ability to control the flow of information even after it has been released by creating a secure, selfinstalled, cross platform reader located on the digital content file header. The proposed system provides the content owners’ options to manage their digital information (audio, video, speech, etc.), including the tracking of the most consumed segments, once it is release. The system benefits from token distribution between the content owner (Music Bands), the content distributer (Online Radio Stations) and the content consumer(Fans) on the system blockchain.
IMPORTANCE OF VERB SUFFIX MAPPING IN DISCOURSE TRANSLATION SYSTEMcscpconf
This paper discusses the importance of verb suffix mapping in Discourse translation system. In
discourse translation, the crucial step is Anaphora resolution and generation. In Anaphora
resolution, cohesion links like pronouns are identified between portions of text. These binders
make the text cohesive by referring to nouns appearing in the previous sentences or nouns
appearing in sentences after them. In Machine Translation systems, to convert the source
language sentences into meaningful target language sentences the verb suffixes should be
changed as per the cohesion links identified. This step of translation process is emphasized in
the present paper. Specifically, the discussion is on how the verbs change according to the
subjects and anaphors. To explain the concept, English is used as the source language (SL) and
an Indian language Telugu is used as Target language (TL)
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...cscpconf
In this paper, based on the definition of conformable fractional derivative, the functional
variable method (FVM) is proposed to seek the exact traveling wave solutions of two higherdimensional
space-time fractional KdV-type equations in mathematical physics, namely the
(3+1)-dimensional space–time fractional Zakharov-Kuznetsov (ZK) equation and the (2+1)-
dimensional space–time fractional Generalized Zakharov-Kuznetsov-Benjamin-Bona-Mahony
(GZK-BBM) equation. Some new solutions are procured and depicted. These solutions, which
contain kink-shaped, singular kink, bell-shaped soliton, singular soliton and periodic wave
solutions, have many potential applications in mathematical physics and engineering. The
simplicity and reliability of the proposed method is verified.
AUTOMATED PENETRATION TESTING: AN OVERVIEWcscpconf
The using of information technology resources is rapidly increasing in organizations,
businesses, and even governments, that led to arise various attacks, and vulnerabilities in the
field. All resources make it a must to do frequently a penetration test (PT) for the environment
and see what can the attacker gain and what is the current environment's vulnerabilities. This
paper reviews some of the automated penetration testing techniques and presents its
enhancement over the traditional manual approaches. To the best of our knowledge, it is the
first research that takes into consideration the concept of penetration testing and the standards
in the area.This research tackles the comparison between the manual and automated
penetration testing, the main tools used in penetration testing. Additionally, compares between
some methodologies used to build an automated penetration testing platform.
CLASSIFICATION OF ALZHEIMER USING fMRI DATA AND BRAIN NETWORKcscpconf
Since the mid of 1990s, functional connectivity study using fMRI (fcMRI) has drawn increasing
attention of neuroscientists and computer scientists, since it opens a new window to explore
functional network of human brain with relatively high resolution. BOLD technique provides
almost accurate state of brain. Past researches prove that neuro diseases damage the brain
network interaction, protein- protein interaction and gene-gene interaction. A number of
neurological research paper also analyse the relationship among damaged part. By
computational method especially machine learning technique we can show such classifications.
In this paper we used OASIS fMRI dataset affected with Alzheimer’s disease and normal
patient’s dataset. After proper processing the fMRI data we use the processed data to form
classifier models using SVM (Support Vector Machine), KNN (K- nearest neighbour) & Naïve
Bayes. We also compare the accuracy of our proposed method with existing methods. In future,
we will other combinations of methods for better accuracy.
VALIDATION METHOD OF FUZZY ASSOCIATION RULES BASED ON FUZZY FORMAL CONCEPT AN...cscpconf
In order to treat and analyze real datasets, fuzzy association rules have been proposed. Several
algorithms have been introduced to extract these rules. However, these algorithms suffer from
the problems of utility, redundancy and large number of extracted fuzzy association rules. The
expert will then be confronted with this huge amount of fuzzy association rules. The task of
validation becomes fastidious. In order to solve these problems, we propose a new validation
method. Our method is based on three steps. (i) We extract a generic base of non redundant
fuzzy association rules by applying EFAR-PN algorithm based on fuzzy formal concept analysis.
(ii) we categorize extracted rules into groups and (iii) we evaluate the relevance of these rules
using structural equation model.
PROBABILITY BASED CLUSTER EXPANSION OVERSAMPLING TECHNIQUE FOR IMBALANCED DATAcscpconf
In many applications of data mining, class imbalance is noticed when examples in one class are
overrepresented. Traditional classifiers result in poor accuracy of the minority class due to the
class imbalance. Further, the presence of within class imbalance where classes are composed of
multiple sub-concepts with different number of examples also affect the performance of
classifier. In this paper, we propose an oversampling technique that handles between class and
within class imbalance simultaneously and also takes into consideration the generalization
ability in data space. The proposed method is based on two steps- performing Model Based
Clustering with respect to classes to identify the sub-concepts; and then computing the
separating hyperplane based on equal posterior probability between the classes. The proposed
method is tested on 10 publicly available data sets and the result shows that the proposed
method is statistically superior to other existing oversampling methods.
CHARACTER AND IMAGE RECOGNITION FOR DATA CATALOGING IN ECOLOGICAL RESEARCHcscpconf
Data collection is an essential, but manpower intensive procedure in ecological research. An
algorithm was developed by the author which incorporated two important computer vision
techniques to automate data cataloging for butterfly measurements. Optical Character
Recognition is used for character recognition and Contour Detection is used for imageprocessing.
Proper pre-processing is first done on the images to improve accuracy. Although
there are limitations to Tesseract’s detection of certain fonts, overall, it can successfully identify
words of basic fonts. Contour detection is an advanced technique that can be utilized to
measure an image. Shapes and mathematical calculations are crucial in determining the precise
location of the points on which to draw the body and forewing lines of the butterfly. Overall,
92% accuracy were achieved by the program for the set of butterflies measured.
SOCIAL MEDIA ANALYTICS FOR SENTIMENT ANALYSIS AND EVENT DETECTION IN SMART CI...cscpconf
Smart cities utilize Internet of Things (IoT) devices and sensors to enhance the quality of the city
services including energy, transportation, health, and much more. They generate massive
volumes of structured and unstructured data on a daily basis. Also, social networks, such as
Twitter, Facebook, and Google+, are becoming a new source of real-time information in smart
cities. Social network users are acting as social sensors. These datasets so large and complex
are difficult to manage with conventional data management tools and methods. To become
valuable, this massive amount of data, known as 'big data,' needs to be processed and
comprehended to hold the promise of supporting a broad range of urban and smart cities
functions, including among others transportation, water, and energy consumption, pollution
surveillance, and smart city governance. In this work, we investigate how social media analytics
help to analyze smart city data collected from various social media sources, such as Twitter and
Facebook, to detect various events taking place in a smart city and identify the importance of
events and concerns of citizens regarding some events. A case scenario analyses the opinions of
users concerning the traffic in three largest cities in the UAE
SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGEcscpconf
The anonymity of social networks makes it attractive for hate speech to mask their criminal
activities online posing a challenge to the world and in particular Ethiopia. With this everincreasing
volume of social media data, hate speech identification becomes a challenge in
aggravating conflict between citizens of nations. The high rate of production, has become
difficult to collect, store and analyze such big data using traditional detection methods. This
paper proposed the application of apache spark in hate speech detection to reduce the
challenges. Authors developed an apache spark based model to classify Amharic Facebook
posts and comments into hate and not hate. Authors employed Random forest and Naïve Bayes
for learning and Word2Vec and TF-IDF for feature selection. Tested by 10-fold crossvalidation,
the model based on word2vec embedding performed best with 79.83%accuracy. The
proposed method achieve a promising result with unique feature of spark for big data.
GENERAL REGRESSION NEURAL NETWORK BASED POS TAGGING FOR NEPALI TEXTcscpconf
This article presents Part of Speech tagging for Nepali text using General Regression Neural
Network (GRNN). The corpus is divided into two parts viz. training and testing. The network is
trained and validated on both training and testing data. It is observed that 96.13% words are
correctly being tagged on training set whereas 74.38% words are tagged correctly on testing
data set using GRNN. The result is compared with the traditional Viterbi algorithm based on
Hidden Markov Model. Viterbi algorithm yields 97.2% and 40% classification accuracies on
training and testing data sets respectively. GRNN based POS Tagger is more consistent than the
traditional Viterbi decoding technique.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
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2. 310 Computer Science & Information Technology (CS & IT)
second phase, the algorithm iteratively adds an entire path to the partially constructed tree rather
than edges to form the tree. The probability of node selection is influenced by both pheromone
and heuristic information. We utilize the structural information provided by problem relaxation to
guide the decision of ants for node transition.
The ant algorithm described Singh et. al. is based on ant system (AS). Each ant starts its journey
from the terminal node. The ants merge when one ant collides with other ant or it steps into the
route of the other ant. In [5], collision detection mechanism is incorporated as there is a
possibility of the collision of the ants. But our algorithm does not require any such mechanism.
In DCACS [3], is based on Prims algorithm in the framework of ant colony system (ACS). The
algorithm is applied on a distance complete graph (DCG). The ant starts with a randomly chosen
terminal node. The ant probabilistically builds the solution after which the both the actual and the
virtual edges are subjected to pheromone updation.
The rest of the paper is organized as follows. Section 2 discusses the Ant Colony Optimization
(ACO) metaheuristics. Section 3 describes the proposed algorithm in detail along with the
formulation. Section 4 presents the results, followed by conclusion in section 5.
2. ANT COLONY OPTIMIZATION (ACO) METAHEURISTICS
ACO was proposed by [6] and is a population based stochastic optimization technique. It is
inspired by the foraging behaviour of ants and is based on stigmergic learning. In this, a
population of artificial agents (ants) work collectively to generate the shortest path from the
source to the destination. The solution is built step by step going through several probabilistic
decisions which depends on (i) long term joint population memory (pheromone) and (ii) some
additional information about the problem (heuristic information). After the solution has been
constructed by the ants, some pheromone is deposited on the edges of the path which is biased
towards better solution i.e. more pheromone is deposited on the edges of good solutions.
Gradually, the concentration of pheromone on the edges corresponding to good solutions builds
up evolving a global optimum solution. The exploitation of the pheromone value on the edges of
the good solution may lead to premature convergence. To facilitate the exploration of the entire
search space, pheromone trail evaporation is also incorporated in ACO. [12] gives an overview of
the recent developments in ACO. Convergence proofs for ACO can be found in [7]. For better
results and faster convergence, ACO are usually combined with local search algorithms. In this
paper, we use problem relaxation to gain insights into the structural information of the problem.
2.1 Problem Relaxation
The minimum spanning tree (MST) with edge cost is essentially a Steiner tree without Steiner
nodes. The Steiner tree heuristics are based on MST heuristics [8][9]. The approximate Steiner
tree is obtained in two steps (i) generate the MST of the network and (ii) prune the MST. The
distributed versions of the classical MST algorithm – Prim and Kruskal are used to obtain the
Steiner tree using this method. There are two disadvantages of this technique (i) the
computational cost is high since all the nodes are involved in the execution of MST algorithm and
(ii) the result obtained is suboptimal.
The approach proposed in this paper uses problem relaxation to gain insights into the structure of
the Steiner tree. The edges contained in MST are very likely to be part of the Steiner tree. The
paper incorporates this information into the heuristic value of the ants. Thus, the transition
probability of the ants is guided by the edge information provided by MST.
3. Computer Science & Information Technology (CS & IT) 311
3. PROPOSED ALGORITHM
The proposed algorithm applies ant colony optimization to obtain Steiner tree for multicast
routing. The algorithm is initialized by placing each ant on the terminal node. The algorithm
consists of two phases (i) Forward set initialization and (ii) Merge path.
Forward Set Initialization: In this phase, each ant starts from the terminal node and builds a
shortest path from the terminal node to the source node. The node transition probability depends
on pheromone and the heuristic information. Since the input graph is not complete, it is possible
that the set N of the entire available alternative that go out from the node v lead to already
visited nodes. In this case, the ant is relocated to a node within its own tabu list such that it is
nearest to a node in the tabu list of any other ant.
Merge Path: In this phase, we merge the path to obtain the minimum cost Steiner tree. Given a
terminal it we first find all the nodes in the path iP from the source to the destination it that are
already in the existing tree. The path iP can be joined to the tree at any of these points. The node
that joins the subpath at the minimum cost is selected as the point of attachment.
2.1. Ant Colony Based Tree Construction
In this section, we describe the search behaviour of ant to build a tree. The algorithm is as
follows:
Step 1: Initialization
The multicast group consist of a source node s, and a set of terminal nodes { }mtttT ,......,, 21= .
Let || Tn = be the number of group members. The number of ants antnum is equal to n. The
pheromone value on the link is initialized to a constant 0τ . The iteration is set to a constant MAX.
Each ant maintains its own tabu list to record the list of nodes already visited. This avoids the ant
revisiting the same node again and forming a cycle. The ants are placed at each destination node
it where 1≤ i ≤ n that needs to be connected and the tabu list of the ant is initialized with it.
Step 2 : State transition probability
The ant m at node i, probabilistically determines the next node j based on the state transition rule
given below:
≤
= ∉
on)(explorati
ion)(exploitat,][][maxarg 0,,)(
otherwiseJ
qqif
j kikimtabuk
βα
ητ
(1)
where
• ki,τ is a positive real quantity of the pheromone value associated with the edge connecting
node i and k where k is a set of feasible nodes in the neighbourhood of node i. The pheromone
value ki,τ represents the accumulated knowledge about the goodness of the edge and indicates
how useful it is to move to a feasible node j from the current node i.
4. 312 Computer Science & Information Technology (CS & IT)
• ki,η is the heuristic function which represents the desirability of choosing a feasible node j
from current node i. The heuristic value for ant m is defined as:
m
i
ijm
ji
jic ψγ
η
.),(
1
,
+
Ω+
= (2)
where γ is a constant and m
iψ is the minimum cost path from node i to all the vertices in the
tabu list of other ants. This causes the current ant m merge into the path of other ants as
quickly as possible to form the tree. ijΩ is 1 if the edge is included in MST, 0 otherwise.
• Parameter βα and weigh the relative importance of pheromone value and the heuristic
function.
• q is a random number chosen with a uniform probability in [0,1] and 0q is a parameter such
that 10 0 ≤≤ q . If q is smaller than 0q , the ant will choose the next unvisited node with the
maximum product of pheromone and heuristic value (exploitation step). Otherwise, the next
node j is chosen as given by (3) with a probability distribution (exploration step)
∉
= ∑∉
otherwise0
if
][][
][][
),( ,,
,,
m
tabuk
kiki
jiji
m
tabuj
jip
m
βα
βα
ητ
ητ
(3)
The next node j is determined stochastically but the process favours the minimum cost edges
having high amount of trail.
Step 3: Pheromone updation rule
The updating of the trail intensity on the edges is defined as follows.
ji,,, )1( τρτρτ ∆+−= jiji (4)
where ρ is a constant, called the trail evaporation rate. The increment in updating is given by the
following formula.
∈
=∆
otherwise0
),(if
)(,
t
tji
Eji
Sc
Q
τ
where )( tSc is the cost of the current tree tS , tE is the edge set of the current tree and Q is a
constant that matches the tree cost.
The high level description of the proposed algorithm is shown in Fig. 1. The notation used in the
algorithm are given as follows
1. JoinPath ( )uSP ii ,, 1− : joins the path iP to the existing tree 1−iS at point u to return the
current Steiner tree iS .
5. Computer Science & Information Technology (CS & IT) 313
2. FindCommonNode ( )1, −ii SP : Given an existing tree 1−iS and iP be the path from the source
to the destination it . The function returns a sequence of nodes in path iP that are already a part
of the existing tree 1−iS .
3. Subpath_Cost ( )itu, : the function returns the cost of the subpath from the common node u to
the selected destination it .
4. Shortest_Subpath ( )itu, : The function returns the subpath ip that joins the destination it to
the tree iS at a tree node u .
Fig. 1. Ant Colony Based Algorithm for Steiner Tree
Main procedure
Input : A connected graph ),,( cEVG = , terminal set T and a source s
Output : A minimal cost Steiner tree S
1. /* Initialization phase */
Place the ant on each node in the terminal set T and put the node into its
tabu-list
Compute the MST of G
2. /* Main Algorithm */
while loop < MAX do
ConstructSteinerTree (G, T, s)
Update the trail intensity on every edge (i,j) by (4)
Update the current best solution
loop++
Return the current best solution
6. 314 Computer Science & Information Technology (CS & IT)
Fig. 2. ConstructSteinerTree subprocedure
Procedure ConstructSteinerTree (G, T, s)
Input : A connected graph ),( EVG = and a terminal set T and a source s
Output : A Steiner tree S
1. /* Phase 1 : Construction of the initial forwarding path from the destination it to the source */
for m=1 to antnum
currentnode=Tm
while currentnode!= s do
determine the nextnode j based on (1)
if nextnode !=φ
currentnode=nextnode
else
relocate(m)
end-if
Add the edge ( )ji, into the path mP of ant m
end-while
end-for
2. /* Merge Path */
11 PS =
for i=2 to n
mincost=inf;
Z = FindCommonPoint ( )1, −ii SP
if Z >0
for each u in Z do
cost = Subpath_Cost( )itu,
if mincost > cost
mincost=cost
ip = Shortest_Subpath ( )itu,
end-if
end-for
iS =JoinPath ( )uSP ii ,, 1−
else
iS =JoinPath ( )sSP ii ,, 1−
end-if
end-for
3. Prune (T) /* Prune the tree to obtain the minimal Steiner tree */
7. Computer Science & Information Technology (CS & IT) 315
3. RESULTS
The effectiveness of the proposed algorithm is tested using MATLAB simulations. The problem
set B from the OR-library is used as the data set [10]. The parameters of ant colony is set
empirically as 1=α , 4=β , 1.0=ρ , 9.00 =q , 100=Q . The trail on all edges is initialized
to a very small value 0τ at the beginning of the algorithm. The maximum iteration is set as 500.
The stopping criterion of our algorithm is either the maximum iteration or a fixed number of
generations without improvement in the solution. Such a number is fixed as 100. Initially the
movement of ants is primarily based on the heuristic information but subsequently the pheromone
information is also used to build the solution. The simulation scenario for B01 is shown in Fig. 3.
The nodes are randomly placed in an area of 50 x 50 m2
. The obtained results are tabulated in
Table 1. The results of the proposed algorithm are compared with the ant based algorithm
reported in [5] using a fixed sequence approach for selection. The results suggest that the
proposed algorithm is able to find the optimal results with high success rate.
Table 1: Results for B-Test Data
Graph Data Results
Test
Data
Set
V E T Ant
Algo
[5]
Proposed Algo
Best Value
Proposed Algo
Average Value
B01 50 63 9 82 82 82
B02 50 63 13 83 83 83
B03 50 63 25 138 138 140
B06 50 100 25 - 122 125
B08 75 94 19 110 104 104
B09 75 94 38 230 225 226
B11 75 150 19 103 88 88
B12 75 150 38 - 176 179
B14 100 125 25 242 235 236
B15 100 125 50 350 320 321
B16 100 200 17 145 127 132
[-] results not available in [5]
8. 316 Computer Science & Information Technology (CS & IT)
Fig 3. The simulation scenario for B01 test data set
4. CONCLUSION
The paper proposed a novel ant colony based algorithm for unconstrained Steiner tree in wireless
ad hoc networks. The proposed ant based algorithm uses problem relaxation to incorporate the
structural information into the heuristic value for node transition. The algorithm was tested on the
standard test data set of the OR-library. The results suggest that the proposed algorithm is able to
find the optimal results with high success rate. The future work is to further enhance the
algorithm for constrained Steiner tree in wireless ad hoc networks and also extend it for dynamic
multicast groups.
REFERENCES
[1] M. R. Garey and D.S. Johnson, “ Computers and Intractability : A Guide to the Theory of NP
Completeness”, W. M. Freeman, 1979.
[2] F. Hwang and D. Richards, “ Steiner Tree Problems”, Networks, vol 22, pp 55-89, 1992
[3] X. Hu, J. Zhang and L. Zhang, “Swarm Intelligence Inspired Multicast Routing : An Ant Colony
Optimization Approach”, LNCS, pp. 51-60, 2009.
[4] L. Luyet, S. Varone and N. Zufferey, “An Ant Algorithm for Steiner Tree Problem in Graphs”,
LNCS, pp. 42-51, 2007
[5] G. Singh, S. Das, S. Shekhar and S. Pujar, “Ant Colony Algorithms for Steiner Trees: An Application
to Routing in Sensor Networks”, Book Chapter in Recent Developments in Biologically Inspired
Computing, IGI global publishing, pp. 181-206, 2005
[6] M. Dorigo, G. Caro and L. Gambardella, “ Ant Algorithms for Discrete Optimization”, Artificial Life,
vol 5(2), pp. 137-192, 1999.
[7] T. Stuetzle and M. Dorigo, “ A Short Convergence Proof for a class of ACO Algorithms” IEEE
Transactions on Evolutionary Computation, vol 6(4), pp. 358-365, 2002
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Simulation Scenarion for B01 Test Set
9. Computer Science & Information Technology (CS & IT) 317
[8] L. Kuo, G. Markowsky and L. Berman, “A fast algorithm for steiner trees”, Acta Informatica, vol 15,
pp. 141-145, 1981.
[9] H. Takahashi and Matsuyama, “An Approximate solution for Steiner Tree problem in Graphs”, Math
Japonica, vol 24(6), pp. 573-577, 1980
[10] J. Beasley: “OR-Library-Distributing Test Problem by electronic mail” Journal of Operational
Research Society, vol 41, pp. 1061-0172, 1990.
[11] A. Haghighat et. al., “GA Based heuristic Algorithms for Bandwidth Delay Constrained Least Cost
Multicast Routing”, Computer Communications, vol 27(1), pp. 111-127, 2004
[12] M. Dorigo and T. Stutzle, “Ant Colony Optimization”, MIT Press, 2004
![David C. Wyld, et al. (Eds): CCSEA, SEA, CLOUD, DKMP, CS & IT 05, pp. 309–317, 2012.
© CS & IT-CSCP 2012 DOI : 10.5121/csit.2012.2231
A NOVEL ANT COLONY ALGORITHM FOR MULTICAST
ROUTING IN WIRELESS AD HOC NETWORKS
Sunita Prasad1
, Zaheeruddin2
and D. K. Lobiyal3
,
1
Center for Development of Advanced Computing, India
2
Department of Electrical Engineering, JMI, Delhi, India
3
School of Computer and System Sciences, JNU, Delhi, India
ABSTRACT
The Steiner tree is the underlying model for multicast communication. This paper presents a
novel ant colony algorithm guided by problem relaxation for unconstrained Steiner tree in static
wireless ad hoc networks. The framework of the proposed algorithm is based on ant colony
system (ACS). In the first step, the ants probabilistically construct the path from the source to
the terminal nodes. These paths are then merged together to generate a Steiner tree rooted at
the source. The problem is relaxed to incorporate the structural information into the heuristic
value for the selection of nodes. The effectiveness of the algorithm is tested on the benchmark
problems of the OR-library. Simulation results show that our algorithm can find optimal Steiner
tree with high success rate.
KEYWORDS
Multicast routing, Steiner Tree, Wireless Ad Hoc Networks, Ant Colony Optimization (ACO)
1. INTRODUCTION
The rapid developments in multimedia applications like video/audio conferencing and distance
education require multicast communication. In multicast communication, the message is sent
concurrently to all members of the multicast group. The multicast routing problem intends to find
a minimum cost routing tree which is rooted at the source and links all the destinations. The
underlying model for multicast routing is Steiner tree. Given a undirected graph ),,( cEVG =
consisting of V as the node set and E as the edge set and a positive edge cost +
→ REc : . A
subset of terminal nodes VT ⊆ is also defined, the objective is to find a Steiner tree S which is
a subnetwork of G such that (i) there is a path between every pair of terminals T and (ii) total
cost )(∑∈Se
i
i
ec is minimized where Eei ⊆ . The vertices TV in S are called Steiner nodes.
Steiner tree is a well known NP-hard combinatorial optimization problem [1][2]. For most NP-
hard problems, the performance of deterministic algorithm is not satisfactory due to high
computational time required for even small instances. Metaheuristics such as Genetic Algorithm
(GA) [11] and the Ant colony Optimization (ACO) [3][4][5] has been applied to solve the Steiner
tree problem. In this paper, we present a novel ant colony algorithm based on problem relaxation
for unconstrained multicast routing. The framework of the proposed algorithm is based on ant
colony system [6]. Each ant is initially placed at the terminal node. In the first phase of the
algorithm, each ant builds a complete path from the destination node to the source node. In the](https://image.slidesharecdn.com/csit2231-180131090137/85/A-NOVEL-ANT-COLONY-ALGORITHM-FOR-MULTICAST-ROUTING-IN-WIRELESS-AD-HOC-NETWORKS-1-320.jpg)
![310 Computer Science & Information Technology (CS & IT)
second phase, the algorithm iteratively adds an entire path to the partially constructed tree rather
than edges to form the tree. The probability of node selection is influenced by both pheromone
and heuristic information. We utilize the structural information provided by problem relaxation to
guide the decision of ants for node transition.
The ant algorithm described Singh et. al. is based on ant system (AS). Each ant starts its journey
from the terminal node. The ants merge when one ant collides with other ant or it steps into the
route of the other ant. In [5], collision detection mechanism is incorporated as there is a
possibility of the collision of the ants. But our algorithm does not require any such mechanism.
In DCACS [3], is based on Prims algorithm in the framework of ant colony system (ACS). The
algorithm is applied on a distance complete graph (DCG). The ant starts with a randomly chosen
terminal node. The ant probabilistically builds the solution after which the both the actual and the
virtual edges are subjected to pheromone updation.
The rest of the paper is organized as follows. Section 2 discusses the Ant Colony Optimization
(ACO) metaheuristics. Section 3 describes the proposed algorithm in detail along with the
formulation. Section 4 presents the results, followed by conclusion in section 5.
2. ANT COLONY OPTIMIZATION (ACO) METAHEURISTICS
ACO was proposed by [6] and is a population based stochastic optimization technique. It is
inspired by the foraging behaviour of ants and is based on stigmergic learning. In this, a
population of artificial agents (ants) work collectively to generate the shortest path from the
source to the destination. The solution is built step by step going through several probabilistic
decisions which depends on (i) long term joint population memory (pheromone) and (ii) some
additional information about the problem (heuristic information). After the solution has been
constructed by the ants, some pheromone is deposited on the edges of the path which is biased
towards better solution i.e. more pheromone is deposited on the edges of good solutions.
Gradually, the concentration of pheromone on the edges corresponding to good solutions builds
up evolving a global optimum solution. The exploitation of the pheromone value on the edges of
the good solution may lead to premature convergence. To facilitate the exploration of the entire
search space, pheromone trail evaporation is also incorporated in ACO. [12] gives an overview of
the recent developments in ACO. Convergence proofs for ACO can be found in [7]. For better
results and faster convergence, ACO are usually combined with local search algorithms. In this
paper, we use problem relaxation to gain insights into the structural information of the problem.
2.1 Problem Relaxation
The minimum spanning tree (MST) with edge cost is essentially a Steiner tree without Steiner
nodes. The Steiner tree heuristics are based on MST heuristics [8][9]. The approximate Steiner
tree is obtained in two steps (i) generate the MST of the network and (ii) prune the MST. The
distributed versions of the classical MST algorithm – Prim and Kruskal are used to obtain the
Steiner tree using this method. There are two disadvantages of this technique (i) the
computational cost is high since all the nodes are involved in the execution of MST algorithm and
(ii) the result obtained is suboptimal.
The approach proposed in this paper uses problem relaxation to gain insights into the structure of
the Steiner tree. The edges contained in MST are very likely to be part of the Steiner tree. The
paper incorporates this information into the heuristic value of the ants. Thus, the transition
probability of the ants is guided by the edge information provided by MST.](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)