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Search Results: 1 - 10 of 584 matches for " Shahram Latifi "
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Cognitive Congestion Control for Data Portals with Variable Link Capacity  [PDF]
Ershad Sharifahmadian, Shahram Latifi
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2012, DOI: 10.4236/ijcns.2012.58058
Abstract: Network congestion, one of the challenging tasks in communication networks, leads to queuing delays, packet loss, or the blocking of new connections. In this study, a data portal is considered as an application-based network, and a cognitive method is proposed to deal with congestion in this kind of network. Unlike previous methods for congestion control, the proposed method is an effective approach for congestion control when the link capacity and information inquiries are unknown or variable. Using sufficient training samples and the current value of the network parameters, available bandwidth is adjusted to distribute the bandwidth among the active flows. The proposed cognitive method was tested under such situations as unexpected variations in link capacity and oscillatory behavior of the bandwidth. Based on simulation results, the proposed method is capable of adjusting the available bandwidth by tuning the queue length, and provides a stable queue in the network.
Decentralization of a Multi Data Source Distributed Processing System Using a Distributed Hash Table  [PDF]
Grzegorz Chmaj, Shahram Latifi
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2013, DOI: 10.4236/ijcns.2013.610047
Abstract: A distributed processing system (DPS) contains many autonomous nodes, which contribute their own computing power. DPS is considered a unified logical structure, operating in a distributed manner; the processing tasks are divided into fragments and assigned to various nodes for processing. That type of operation requires and involves a great deal of communication. We propose to use the decentralized approach, based on a distributed hash table, to reduce the communication overhead and remove the server unit, thus avoiding having a single point of failure in the system. This paper proposes a mathematical model and algorithms that are implemented in a dedicated experimental system. Using the decentralized approach, this study demonstrates the efficient operation of a decentralized system which results in a reduced energy emission.
Performance Assessment of MANET Routing Protocols  [PDF]
Bharath Chandra Mummadisetty, Astha Puri, Shahram Latifi
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2015, DOI: 10.4236/ijcns.2015.811041
Abstract: Mobile ad hoc networks use many different routing protocols to route data packets among nodes. Various routing protocols have been developed, and their usage depends on the application and network architecture. This study examined several different routing protocols, and evaluated the performance of three: the Ad Hoc On-Demand Distance Vector Protocol (AODV), the Destination-Sequenced Distance-Vector Routing (DSDV), and the Dynamic Source Routing (DSR). These three protocols were evaluated on a network with nodes ranging from 50 to 300, using performance metrics such as average delay, jitter, normal overhead, packet delivery ratio, and throughput. These performance metrics were measured by changing various parameters of the network: queue length, speed, and the number of source nodes. AODV performed well in high mobility and high density scenarios, whereas DSDV performed well when mobility and the node density were low. DSR performed well in low-mobility scenarios. All the simulations were performed in NS2 simulator.
A Hybrid Method for Compression of Solar Radiation Data Using Neural Networks  [PDF]
Bharath Chandra Mummadisetty, Astha Puri, Ershad Sharifahmadian, Shahram Latifi
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2015, DOI: 10.4236/ijcns.2015.86022
Abstract: The prediction of solar radiation is important for several applications in renewable energy research. There are a number of geographical variables which affect solar radiation prediction, the identification of these variables for accurate solar radiation prediction is very important. This paper presents a hybrid method for the compression of solar radiation using predictive analysis. The prediction of minute wise solar radiation is performed by using different models of Artificial Neural Networks (ANN), namely Multi-layer perceptron neural network (MLPNN), Cascade feed forward back propagation (CFNN) and Elman back propagation (ELMNN). Root mean square error (RMSE) is used to evaluate the prediction accuracy of the three ANN models used. The information and knowledge gained from the present study could improve the accuracy of analysis concerning climate studies and help in congestion control.
Energy Restrained Data Dissemination in Wireless Sensor Networks
Naoto Kimura,Vasu Jolly,Shahram Latifi
International Journal of Distributed Sensor Networks , 2006, DOI: 10.1080/15501320600642692
Abstract: Wireless sensor nodes can be mobile within a chosen area and communicate with neighboring nodes in the bounds of protocol limits. Since communications among all network components in sensor networks are wireless, a peer-to-peer protocol is employed between two nodes. Among many concerns about design of sensor networks are growing bandwidth demands, speed of information retrieval, and transporting bytes over the wireless networks to provide a quality service for the diverse requirements of the users, such as signal processing or multimedia applications. Although traditional routing protocols ignore power management issues for sensor networks, design and implementation of an efficient energy based routing is in the core interest. In this paper, we discuss the current power management protocols, and propose an energy restrained information dissemination scheme. Experimental analysis and comparison with related work show that using the proposed scheme we can save substantial energy as compared to the prior methods.
New example of integrable nonlinear coupled equations with exact asymptotic singular solution in the context of laser-plasma interaction
A. Latifi
Physics , 2015,
Abstract: A new set of nonlinear coupled equations is derived in the context of small amplitude limit of the general wave equations in a fluid type warm electrons/cold ions plasma irradiated by a continuous laser beam. This limit is proved to be integrable by means of the spectral transform theory with singular dispersion relation. An exact asymptotic solution is obtained. This model accounts for a nonlinear mode coupling of the electrostatic waves with the ion sound wave, and is shown to be unstable and does not propagate any stable small amplitude solution. This instability is understood as a continuous secular transfer of energy from the electrostatic wave to the ion sound wave through the ponderomotive force. The exact mechanism of this transfer is exposed. The dynamics of this energy transfer results in a singular asymptotic behavior of the ion sound wave which explains the low penetration of the incident laser beam.
Homogeneous geodesics in homogeneous Finsler spaces
Dariush Latifi
Mathematics , 2007, DOI: 10.1016/j.geomphys.2006.11.004
Abstract: In this paper, we study homogeneous geodesics in homogeneous Finsler spaces. We first give a simple criterion that characterizes geodesic vectors. We show that the geodesics on a Lie group, relative to a bi-invariant Finsler metric, are the cosets of the one-parameter subgroups. The existence of infinitely many homogeneous geodesics on compact semi-simple Lie group is established. We introduce the notion of naturally reductive homogeneous Finsler space. As a special case, we study homogeneous geodesics in homogeneous Randers spaces. Finally, we study some curvature properties of homogeneous geodesics. In particular, we prove that the S-curvature vanishes along the homogeneous geodesics.
Homogeneous geodesics of left invariant Finsler metrics
Dariush Latifi
Mathematics , 2007,
Abstract: In this paper, we study the set of homogeneous geodesics of a leftinvariant Finsler metric on Lie groups. We first give a simple criterion that characterizes geodesic vectors. As an application, we study some geometric properties of bi-invariant Finsler metrics on Lie groups. In particular a necessary and sufficient condition that left-invariant Randers metrics are of Berwald type is given. Finally a correspondence of homogeneous geodesics to critical points of restricted Finsler metrics is given. Then results concerning the existence homogeneous geodesics are obtained.
On Point-Based Haptic Rendering  [PDF]
Shi Wen, Shahram Payandeh
Engineering (ENG) , 2013, DOI: 10.4236/eng.2013.55A003
Abstract: Haptic rendering is referred to as an approach for complementing graphical model of the virtual object with mechanics- based properties. As a result, when the user interacts with the virtual object through a haptic device, the object can graphically deflect or deform following laws of mechanics. In addition, the user is able to feel the resulting interaction force when interacting with the virtual object. This paper presents a study of defining the levels-of-detail (LOD) in point-based computational mechanics for haptic rendering of objects. The approach uses the description of object as a set of sampled points. In comparison with the finite element method (FEM), point-based approach does not rely on any predefined mesh representation and depends on the point representation of the volume of the object. Different from solving the governing equations of motion representing the entire object based on pre-defined mesh representation which is used in FEM, in point-based modeling approach, the number of points involved in the computation of displacement/deformation can be adaptively defined during the solution cycle. This frame work can offer the implementation of the notion for levels-of-detail techniques for which can be used to tune the haptic rendering environment for in- creased realism and computational efficiency. This paper presents some initial experimental studies in implementing LOD in such environment.

Preana: Game Theory Based Prediction with Reinforcement Learning  [PDF]
Zahra Eftekhari, Shahram Rahimi
Natural Science (NS) , 2014, DOI: 10.4236/ns.2014.613099
Abstract:

In this article, we have developed a game theory based prediction tool, named Preana, based on a promising model developed by Professor Bruce Beuno de Mesquita. The first part of this work is dedicated to exploration of the specifics of Mesquita’s algorithm and reproduction of the factors and features that have not been revealed in literature. In addition, we have developed a learning mechanism to model the players’ reasoning ability when it comes to taking risks. Preana can predict the outcome of any issue with multiple steak-holders who have conflicting interests in economic, business, and political sciences. We have utilized game theory, expected utility theory, Median voter theory, probability distribution and reinforcement learning. We were able to reproduce Mesquita’s reported results and have included two case studies from his publications and compared his results to that of Preana. We have also applied Preana on Irans 2013 presidential election to verify the accuracy of the prediction made by Preana.

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