(SoE) School of Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

This paper designs a novel fuzzy attributes and competition based bidding strategy (FAC-Bid), in which the final best bid is calculated on the basis of the assessment of multiple attributes of the goods and the competition for the goods in the market. The assessment of attributes adapts the fuzzy sets technique to handle uncertainty of the bidding process. The bidding strategy also uses and determines competition in the market (based on the two factors i.e. no. of the bidders participating and the total time elapsed for an auction) using Mamdani's Direct Method. Then the final price of the best bid will be determined based on the assessed attributes and the competition in the market using fuzzy reasoning technique.

World University root node

Computer Science and Engineering

ICEIS 2010 - Proceedings of the 12th International Conference on Enterprise Information Systems

Using fuzzy set approach in multi-attribute automated auctions

A digital repository is a digital archive for depositing and providing access to digital contents. It harvests metadata for providing an access framework of digital content to multiple users. In existing systems, query and retrieval is done on centralized basis and do not consider semantics of the query. Since the repositories are distributed, distinct and autonomous, there is a need for a framework which is capable of providing an efficient integrated and semantically enriched query retrieval mechanism over multiple repositories. We have proposed and implemented a multi-agent based framework for querying multiple disjoint repositories that is equipped with well defined semantic web technologies such as ontology [7, 8]. The system has been implemented using Jena framework for semantic web, Jade for agents and Java Swing for user interfaces. © 2010 IEEE.

2010 International Conference on Machine and Web Intelligence, ICMWI 2010 - Proceedings

Multi-agent based architecture for querying disjoint data repositories

Web services provide a promising solution to an age old need of fast and flexible information sharing among people and businesses. One of the key research issues in web services is selection of most pertinent web services. Selection of web service has become a tedious job because of the increasing number of service providers providing services with similar functionality. Therefore, a framework for selection and discovery of web service that can meet the non-functional requirements is needed. In this work, we have developed a selection tool (WSS-NFP) for web services which can rank services based on their non functional properties such as performance, delay etc. We have used soft computing techniques for selection and discovery of web services based on non functional properties. These properties are fuzzy in nature. A tool is developed and implemented that is generic in nature and can be customized for any application domain. As a core of this tool, it consists of Fuzzy System for ranking web services and Neural Network for fine tuning the membership functions for linguistic terms. Appropriate and fine tuned membership functions help in minimizing the output error measure and maximizing the performance index of the proposed tool. This tool is basically a Neuro-Fuzzy system for ranking web services of any domain. © 2010 IEEE.

WSS-NFP: Tool for web service selection based on non-functional properties using soft computing

Zn1-xCdxS Nanoparticles with varying Cd concentration were synthesized via co-precipitation technique at 280 K. Despite the analogous size, the nanoparticles with different Cd content exhibit composition-dependent absorption resulting from the distinguished band gap. Due to size effect Zn1-xCdxS nanoparticles, self activated PL band shifted to higher energies compared to the absorption band of bulk counterpart. Origin of the PL emission bands are investigated via fluorescence lifetime measurement. Decay time constant is found in nano second regime and is attributed to the spatial confinement of photo generated electron-hole pairs. © 2010 Bentham Science Publishers Ltd.

Electrical Engineering

Current Nanoscience

Optical properties of Zn1-xCdxS nanoparticles in the quantum confinement regime

The basic component of an electromagnetic levitation systems are inductance and resistance of the actuator, input DC link voltage, mass of the payload, air-gap between the pole face of the magnet and ferromagnetic guide-way, controller parameters etc. All these parameters are supposed to get change in real life situation. Electromagnetic levitation system (EMLS) is inherently unstable and strongly nonlinear in nature. In most cases a classical controller has been designed for the linear model around an operating point for maintaining overall closed-loop stability. In this work, a cascade lead compensation control scheme utilizing inner current loop and outer position loop has been designed and implemented for stabilization of a single magnet based single axis levitation system. The prototype has been successfully tested and stable levitation has been demonstrated at the desired operating gap. The performances of the linear controller with the change in different parameters have been studied experimentally. The dynamic performance of the controller has been tested by applying different disturbance inputs (square wave, sinusoidal etc.) with increasing magnitudes and frequencies. The parameters of the designed controller also get varied during experimentation. So a sensitivity study of the controller for an EMLS is also important. © JES 2010.

Journal of Electrical Systems

Performance study of the controller of an attraction type levitation system under parametric change

Multiclass support vector machine (SVM) methods are well studied in recent literature. Comparison studies on UCI/statlog multiclass datasets suggest using one-against-one method for multiclass SVM classification. However, in unilabel (multiclass) text categorization with SVMs, no comparison studies exist with one-against-one and other methods, e.g. one-against-all and several well-known improvements to these approaches. In this paper, we bridge this gap by performing empirical comparison of standard one-against-all and one-against-one, together with three improvements to these standard approaches for unilabel text categorization with SVM as base binary learner. We performed all our experiments on three standard text corpuses using two types of document representation. Outcome of our experiments partly support Rifkin and Klautau's (2004) statement that, for small scale unilabel text categorization tasks, if parameters of the classifiers are well tuned, one-against-all will have better performance than one-against-one and other methods. © 2010 Elsevier B.V. All rights reserved.

Pattern Recognition Letters

A comparison study on multiple binary-class SVM methods for unilabel text categorization

This letter proposes Inverse QR two-dimensional Recursive Least Square (IQR-2D-RLS) adaptive channel estimation for Orthogonal. Frequency Division Multiplexing (OFDM) systems (using Givens Rotations and Householder Transformations). It is more stable numerically than 2D-RLS algorithm. MATLAB simulations show that BER performance of IQR-2D-RLS algorithm is similar to that of 2D-RLS algorithm. Copyright © 2010 The Institute of Electronics, Information and Communication Engineers.

IEICE Transactions on Communications

Inverse QR 2D-RLS adaptive channel estimation for OFDM systems

In this study, an optimal control algorithm based on Hamilton-Jacobi- Bellman (HJB) equation, for the bounded robust controller design for finite-time-horizon nonlinear systems, is proposed. The HJB equation formulated using a suitable nonquadratic term in the performance functional to take care of magnitude constraints on the control input. Utilising the direct method of Lyapunov stability, we have proved the optimality of the controller with respect to a cost functional, that includes penalty on the control effort and the maximum bound on system uncertainty. The bounded controller requires the knowledge of the upper bound of system uncertainty. In the proposed algorithm, neural network is used to approximate the time-varying solution of HJB equation using least squares method. Proposed algorithm has been applied on the nonlinear system with matched and unmatched system uncertainties. Necessary theoretical and simulation results are presented to validate proposed algorithm. © 2009 The Institution of Engineering and Technology.

IET Control Theory and Applications

Fixed final time optimal control approach for bounded robust controller design using Hamilton-Jacobi-Bellman solution

In this paper we formulate a least squares version of the recently proposed twin support vector machine (TSVM) for binary classification. This formulation leads to extremely simple and fast algorithm for generating binary classifiers based on two non-parallel hyperplanes. Here we attempt to solve two modified primal problems of TSVM, instead of two dual problems usually solved. We show that the solution of the two modified primal problems reduces to solving just two systems of linear equations as opposed to solving two quadratic programming problems along with two systems of linear equations in TSVM. Classification using nonlinear kernel also leads to systems of linear equations. Our experiments on publicly available datasets indicate that the proposed least squares TSVM has comparable classification accuracy to that of TSVM but with considerably lesser computational time. Since linear least squares TSVM can easily handle large datasets, we further went on to investigate its efficiency for text categorization applications. Computational results demonstrate the effectiveness of the proposed method over linear proximal SVM on all the text corpuses considered. © 2008 Elsevier Ltd. All rights reserved.

Expert Systems with Applications

Least squares twin support vector machines for pattern classification

In this paper we present a novel shape descriptor based on shape context, which in combination with hierarchical distance based hashing is used for word and graphical pattern based document image indexing and retrieval. The shape descriptor represents the relative arrangement of points sampled on the boundary of the shape of object. We also demonstrate the applicability of the novel shape descriptor for classification of characters and symbols. For indexing, we provide a new formulation for distance based hierarchical locality sensitive hashing. Experiments have yielded promising results. © 2009 IEEE.