(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

Text Categorization (TC) remains as a potential application area for linear support vector machines (SVMs). Among the numerous linear SVM formulations, we bring forward linear PSVM together with recently proposed distributional clustering (DC) of words to realize its potential in TC realm. DC has been presented as an efficient alternative to conventionally used feature selection in TC. It has been shown that, DC together with linear SVM drastically brings down the dimensionality of text documents without any compromise in classification performance. In this paper we use linear PSVM and its extension Fuzzy PSVM (FPSVM) together with DC for TC. We present experimental results comparing PSVM/FPSVM with linear SVMlight and SVMlin on popular WebKB text corpus. Through numerous experiments on subsets of WebKB, we reveal the merits of PSVM and FPSVM over other linear SVMs. © Springer-Verlag Berlin Heidelberg 2009.

World University root node

Electrical Engineering

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Text categorization using fuzzy proximal svm and distributional clustering of words

One of the main issues of orthogonal frequency division multiplexing (OFDM) is the high peak-to-average power ratio (PAPR) of the transmitted signal which adversely affects the complexity of power amplifiers. The selected mapping (SLM) technique is one of the promising PAPR reduction techniques for OFDM. In this reported work, rows of normalised Riemann matrices are selected as phase sequence vectors for the SLM technique. MATLAB simulations show PAPR reduction of around 2.3dB using the proposed method compared with methods reported in the literature. © 2009 The Institution of Engineering and Technology.

Electronics Letters

SLM based PAPR reduction of OFDM signal using new phase sequence

Effect of laser flux density on the structural quality and optical properties of Zn0.6Cd0.4S thin films synthesized by ultraviolet pulsed laser deposition have been studied. The stoichiometric composition of this alloy was estimated using lattice constant calculated via XRD data. Surface morphology of the samples was examined using AFM. Optical properties were studied at room temperature by transmittance, absorbance, and photoluminescence measurements. Studies revealed that there is an improvement in the structural quality with increasing the laser flux density in some range. However, too high laser flux density could lead to the degradation in structural quality of thin film. It was observed from the PL data that with increase in laser flux density there is a decrease in the band gap. Transmission data shows a transmittance of more than 70% in the visible region. TEM investigation of the samples reveals that the particles are spherical in shape with average diameter of 15 nm. © 2009 Elsevier B.V. All rights reserved.

Thin Solid Films

Effect of laser flux density on ZnCdS thin films

In this paper, we have presented a new approach to predict pattern of the financial time series in stock market for next 10 days and compared it with the existing method of exact value prediction [2, 3, and 4]. The proposed pattern prediction technique performs better than value prediction. It has been shown that the average for pattern prediction is 58.7% while that for value prediction is 51.3%. Similarly, maximum for pattern and value prediction are 100% and 88.9% respectively. It is of more practical significance if one can predict an approximate pattern that can be expected in the financial time series in the near future rather than the exact value. This way one can know the periods when the stock will be at a high or at a low and use the information to buy or sell accordingly. We have used Support Vector Machine based prediction system as a basis for predicting pattern. MATLAB has been used for implementation. © Springer-Verlag Berlin Heidelberg 2009.

Computer Science and Engineering

Pattern prediction in stock market

Computing all-pairs distances in a graph is a fundamental problem of computer science but there has been a status quo with respect to the general problem of weighted directed graphs. In contrast, there has been a growing interest in the area of algorithms for approximate shortest paths leading to many interesting variations of the original problem. In this article, we trace some of the fundamental developments like spanners and distance oracles, their underlying constructions, as well as their applications to the approximate all-pairs shortest paths. © Springer-Verlag Berlin Heidelberg 2009.

Approximating shortest paths in graphs

Extracting meaningful patterns from voluminous amount of biological data is a very big challenge. Motifs are biological patterns of great interest to biologists. There are different versions of the Motif Finding Problem. In this paper we concentrate on the Planted (l, d) Motif Search Problem. There have been numerous algorithms designed to solve this problem. Many instances of the Planted (l, d) Motif Problem have been identified as challenging instances. The algorithm proposed here is an extension of PMS3 [1]. It uses a very simple approach and solves challenging instances ((21, 8), for example) that have not been reported solved before in the literature. We also propose a new algorithm PMS3p. We expect PMS3p to be significantly faster than PMS3. © 2009 IEEE.

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings

A simple algorithm for (l, d) motif search

C axis oriented AlN films were deposited on silicon substrate by radio frequency reactive magnetron sputtering. Subsequently the films were annealed in a horizontal furnace at temperatures ranging from 400 to 800°C for 30 min in nitrogen ambient. The change in the morphological properties with annealing temperatures was investigated using X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy and atomic force microscopy techniques. Morphological studies revealed that the annealing increased surface roughness and grain size. In addition, Al-N bond density along with the crystallinity of the deposited films was improved with annealing. The electrical properties, namely the insulator charge density (Qin) and the interface electronic state density (Dit), were estimated by the capacitance-voltage (C-V) measurements. It was found that the Qin increased, but the Dit decreased with annealing temperature. Lower leakage current with improved resistivity and dielectric behaviour was also observed with annealing. © 2009 Institute of Materials, Minerals and Mining.

Materials Science and Technology

Impact of post-deposition annealing on surface, bulk and interface properties of RF sputtered AlN films

In this paper, constrained controller design is proposed for a class of nonlinear discrete-time uncertain system having matched type system uncertainties, using the solution of HJB (Hamilton-Jaccobi-Bellman) equation. The discrete-time HJB equation is formulated using a suitable nonquadratic term in the performance functional to tackle constraints on the control input. Based on the non-quadratic functional, a greedy HDP algorithm is used to obtain the constrained robust-optimal controller. The constrained robust controller requires knowledge of the upper bound of system uncertainties. For facilitating the implementation of the iterative algorithm, two neural networks are used to approximate the value function and to compute the optimal control policy, respectively. Their weights have been tuned using least squares method. Proposed algorithm has been applied on a nonlinear discrete-time system with matched uncertainties. © 2009 AACC.

Proceedings of the American Control Conference

Constrained controller design for a class of nonlinear discrete-time uncertain systems

Orthogonal Frequency Division Multiplexing (OFDM) is seen as one of the most promising solution to broadband wireless communications. Its performance depends on the channel state information (CSI) which can be estimated using different channel estimation algorithms. This paper proposes a Set Member Feasibility (SMF) formulation to govern the updating of the adaptive-filter coefficients. Here, twodimensional Set-Membership Normalized LMS (2D-SM-NLMS) algorithm is proposed. The 2D-RLS adaptive channel estimation algorithm is also simulated for comparison. Matlab simulations show that 2D-SM-NLMS and 2D-RLS algorithms have similar Bit Error Rate (BER) performance. But the proposed algorithm has computational complexity of O(N) which is less than that of conventional 2D-RLS algorithm having order O(N2) while compromising on the convergence speed.

Proceedings of INDICON 2009 - An IEEE India Council Conference

Two-dimensional set membership normalized least mean square adaptive channel estimation for OFDM systems

This paper presents Orthogonal Frequency Division Multiplexing (OFDM) based two-way relaying scheme to communicate between two nodes S1 and S2 via MIMO Relay Station (RS) in a frequency selective environment. This scheme relies on two-hop relaying approach which uses two orthogonal channel resources to transmit and receive a signal. This scheme requires the channel state information (CSI) only at RS. Spatial filtering is implemented at the RS for transmit and receive processing which is evaluated using zero forcing (ZF) and minimum mean squared error (MMSE) criterion. MATLAB simulations are conducted to evaluate the validity of the algorithm using both criterions in presence of frequency selective environment. The simulation results depict that the algorithm under defined conditions performs better in a frequency selective fading environment with the use of OFDM. Also, the BER performance evaluated through spatial filtering done using MMSE is found to be better than its ZF counterpart. © 2009 IEEE.