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Search Results: 1 - 10 of 130501 matches for " V. Jeyakumar "
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Trust--Region Problems with Linear Inequality Constraints: Exact SDP Relaxation, Global Optimality and Robust Optimization
V. Jeyakumar,G. Li
Mathematics , 2013,
Abstract: The trust-region problem, which minimizes a nonconvex quadratic function over a ball, is a key subproblem in trust-region methods for solving nonlinear optimization problems. It enjoys many attractive properties such as an exact semi-definite linear programming relaxation (SDP relaxation) and strong duality. Unfortunately, such properties do not, in general, hold for an extended trust-region problem having extra linear constraints. This paper shows that two useful and powerful features of the classical trust-region problem continue to hold for an extended trust-region problem with linear inequality constraints under a new dimension condition. First, we establish that the class of extended trust-region problems has an exact SDP-relaxation, which holds without the Slater constraint qualification. This is achieved by proving that a system of quadratic and affine functions involved in the model satisfies a range-convexity whenever the dimension condition is fulfilled. Second, we show that the dimension condition together with the Slater condition ensures that a set of combined first and second-order Lagrange multiplier conditions is necessary and sufficient for global optimality of the extended trust-region problem and consequently for strong duality. Finally, we show that the dimension condition is easily satisfied for the extended trust-region model that arises from the reformulation of a robust least squares problem (LSP) as well as a robust second order cone programming model problem (SOCP) as an equivalent semi-definite linear programming problem. This leads us to conclude that, under mild assumptions, solving a robust (LSP) or (SOCP) under matrix-norm uncertainty or polyhedral uncertainty is equivalent to solving a SDP and so, their solutions can be validated in polynomial time.
Quadrant Based DIR in CWin Adaptation Mechanism for Multihop Wireless Network
V. Karthikeyan,V. J. Vijayalakshmi,P. Jeyakumar
Computer Science , 2013, DOI: 10.5121/ijci.2013.2404
Abstract: In Multihop Wireless Networks, traffic forwarding capability of each node varies according to its level of contention. Each node can yield its channel access opportunity to its neighbouring nodes, so that all the nodes can evenly share the channel and have similar forwarding capability. In this manner the wireless channel is utilize d effectively, which is achieved using Contention Window Adaptation Mechanism (CWAM). This mechanism achieves a higher end to - end throughout but consumes the network power to a higher level. So, a newly proposed algorithm Quadrant Based Directional Routing Protocol (Q-DIR) is implemented as a cross - layer with CWAM, to reduce the total network power consumption through limited flooding and also reduce the routing overheads, which eventually increases overall network throughput. This algorithm limits the broadcast region to a quadrant where the source node and the destination nodes are located. Implementation of the algorithm is done in Linux based NS-2 simulator.
Step and Search Control Method to Track the Maximum Power in Wind Energy Conversion Systems A Study
V. Karthikeyan,V. J. Vijayalakshmi,P. Jeyakumar
Computer Science , 2014,
Abstract: A simple step and search control strategy for extracting maximum output power from grid connected Variable Speed Wind Energy Conversion System (VSWECS) is implemented in this work. This system consists of a variable speed wind turbine coupled to a Permanent Magnet Synchronous Generator (PMSG) through a gear box, a DC-DC boost converter and a hysteresis current controlled Voltage Source Converter (VSC). The Maximum Power Point Tracking (MPPT) extracts maximum power from the wind turbine from cut-into rated wind velocity by sensing only by DC link power. This system can be connected to a micro-grid. Also it can be used for supplying an isolated local load by means of converting the output of Permanent Magnet Synchronous Generator (PMSG) to DC and then convert to AC by means of hysteresis current controlled Voltage Source Converter (VSI).
Ontology - Based Dynamic Business Process Customization
V. Karthikeyan,V. J. Vijayalakshmi,P. Jeyakumar
Computer Science , 2014,
Abstract: The interaction between business models is used in consumer centric manner instead of using a producer centric approach for customizing the business process in cloud environment. The knowledge based human semantic web is used for customizing the business process It introduces the Human Semantic Web as a conceptual interface, providing human-understandable semantics on top of the ordinary Semantic Web, which provides machine-readable semantics based on RDF in this mismatching is a major problem. To overcome this following technique automatic customization detection is an automated process of detecting possible elements or variables of a business process that needto be especially treated in order to suit the requirement of the other process. To the business processto be customized as the primary business process and those that it collaborates with as secondary business process or SBP Automatic customization enactment is an automated process of taking actions to perform the customization on the PBP according to the detected customization spots and the automatic reasoning on the customization conceptualization knowledge framework. The process of customizing businessprocesses by composite the web pages by using web service.
Separation Behavior of U(VI) and Th(IV) on a Mixed Ion Exchange Column Using 2,6-Pyridine Dicarboxylic Acid as a Complexing Agent and Determination of Trace Level Thorium in Uranium Matrix Employing High Performance Ion Chromatography  [PDF]
Vaibhavi V. Raut, S. P. Roy, M. K. Das, S. Jeyakumar, K. L. Ramakumar
International Journal of Analytical Mass Spectrometry and Chromatography (IJAMSC) , 2013, DOI: 10.4236/ijamsc.2013.11008

Retention behavior of U(VI) and Th(IV) as their 2, 6-pyridine dicarboxylic acid (PDCA) complexes on reversed phase and ion exchange (cation, anion and mixed ion exchange) columns was studied and based on the results, a simple ion chromatography method for the determination of trace level thorium in uranium oxide using 0.075mM 2, 6-pyridine dicarboxylic acid (PDCA) and 1M KNO3 in 1.2M HNO3 as eluent (flow rate 1 mL/min)was proposed. The advantage of the developed method is that the separation of uranium matrix is not required prior to the ion chromatographic determination of trace Th. Separation was carried out on a mixed ion exchange stationary phase and a 10?4 M arsenazo (III) solution was used as post column reagent for detecting the separated metal ions. The separation of Th from uranium using PDCA in the present investigation is attributed through cation exchange mechanism. A calibration plot was constructed by following the standard addition method over the concentration range of 0.25 to 10 ppm of Th in the presence of uranium matrix, which resulted in a linear regression coefficient of 0.9978. The precision of the method was better than 5% and the LOD for Th was found to be 0.1ppm (S/N=3). The method has been validated by comparing the results with the results obtained from ICP-MS analysis where the This separated from the uranium matrix. The proposed method is simple, rapid, accurate and cost effective compared to techniques like ICP-MS or ICP-AES and is suitable for the routine kind of analysis.

Hybrid Approaches to Image Coding: A Review
Rehna. V. J,Jeyakumar. M. K
Mathematics , 2012,
Abstract: Nowadays, the digital world is most focused on storage space and speed. With the growing demand for better bandwidth utilization, efficient image data compression techniques have emerged as an important factor for image data transmission and storage. To date, different approaches to image compression have been developed like the classical predictive coding, popular transform coding and vector quantization. Several second generation coding schemes or the segmentation based schemes are also gaining popularity. Practically efficient compression systems based on hybrid coding which combines the advantages of different traditional methods of image coding have also been developed over the years. In this paper, different hybrid approaches to image compression are discussed. Hybrid coding of images, in this context, deals with combining two or more traditional approaches to enhance the individual methods and achieve better-quality reconstructed images with higher compression ratio. Literature on hybrid techniques of image coding over the past years is also reviewed. An attempt is made to highlight the neuro-wavelet approach for enhancing coding efficiency.
Convergence of the Lasserre Hierarchy of SDP Relaxations for Convex Polynomial Programs without Compactness
V. Jeyakumar,T. S. Pham,G. Li
Mathematics , 2013,
Abstract: The Lasserre hierarchy of semidefinite programming (SDP) relaxations is an effective scheme for finding computationally feasible SDP approximations of polynomial optimization over compact semi-algebraic sets. In this paper, we show that, for convex polynomial optimization, the Lasserre hierarchy with a slightly extended quadratic module always converges asymptotically even in the face of non-compact semi-algebraic feasible sets. We do this by exploiting a coercivity property of convex polynomials that are bounded below. We further establish that the positive definiteness of the Hessian of the associated Lagrangian at a saddle-point (rather than the objective function at each minimizer) guarantees finite convergence of the hierarchy. We obtain finite convergence by first establishing a new sum-of-squares polynomial representation of convex polynomials over convex semi-algebraic sets under a saddle-point condition. We finally prove that the existence of a saddle-point of the Lagrangian for a convex polynomial program is also necessary for the hierarchy to have finite convergence.
SDP Duals without Duality Gaps for a Class of Convex Minimax Programs
V. Jeyakumar,J. Vicente-Perez
Mathematics , 2013, DOI: 10.1007/s10957-013-0496-0
Abstract: In this paper we introduce a new dual program, which is representable as a semi-definite linear programming problem, for a primal convex minimax programming model problem and show that there is no duality gap between the primal and the dual whenever the functions involved are SOS-convex polynomials. Under a suitable constraint qualification, we derive strong duality results for this class of minimax problems. Consequently, we present applications of our results to robust SOS-convex programming problems under data uncertainty and to minimax fractional programming problems with SOS-convex polynomials. We obtain these results by first establishing sum of squares polynomial representations of non-negativity of a convex max function over a system of SOS-convex constraints. The new class of SOS-convex polynomials is an important subclass of convex polynomials and it includes convex quadratic functions and separable convex polynomials. The SOS-convexity of polynomials can numerically be checked by solving semi-definite programming problems whereas numerically verifying convexity of polynomials is generally very hard.
An Energy Efficient Neighbour Node Discovery Method for Wireless Sensor Networks
V. Karthikeyan,A. Vinod,P. Jeyakumar
Computer Science , 2014,
Abstract: The discovery of neighbouring nodes in multihop wireless networks has become a key challenge. Due to tribulations in communication, synchronization loss between nodes, disparity in transmission power etc, the connectivity of nodes will always experience disruptions. On the other hand, the energy utilization by the nodes also became critical . In this paper, we propose a new method for neighbour discovery in wireless sensor networks (WSNs) which pays an eminent consideration for energy utilization and QoS parameters like latency, throughput, error rate etc. In the proposed method, the network routing is enhanced using AOMDV protocol which can accurately discover the neighbour nodes and power management with HMAC protocol which reduces the energy utilization significantly. A complete analysis is being performed to estimate how the Q o S metrics varies in various scenarios of power consumption in wireless networks.
An Efficient Method for Face Recognition System In Various Assorted Conditions
V. Karthikeyan,K. Vijayalakshmi,P. Jeyakumar
Computer Science , 2014,
Abstract: In the beginning stage, face verification is done using easy method of geometric algorithm models, but the verification route has now developed into a scientific progress of complicated geometric representation and identical procedure. In recent years the technologies have boosted face recognition system into the healthy focus. Researchers currently undergoing strong research on finding face recognition system for wider area information taken under hysterical elucidation dissimilarity. The proposed face recognition system consists of a narrative expositionindiscreet preprocessing method, a hybrid Fourier-based facial feature extraction and a score fusion scheme. We have verified the face recognition in different lightening conditions (day or night) and at different locations (indoor or outdoor). Preprocessing, Image detection, Feature- extraction and Face recognition are the methods used for face verification system. This paper focuses mainly on the issue of toughness to lighting variations. The proposed system has obtained an average of 88.1% verification rate on Two-Dimensional images under different lightening conditions.
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