(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

In this paper, QR-RLS based IIR adaptive channel TEQ(Time Domain Equalizer) to make the OFDM systems robust for delay spreads exceeding the CP(cyclic prefix) is presented. IIR based TEQ results in much shorter length equalizer compared to FIR based TEQ, at the same time guarantee for global convergence within the training period. The length of zeros of the proposed QR-IIR TEQ is restricted to CP. Givens rotation based QRD updation of TEQ coefficients results in computational advantage. The performance of the proposed method is then compared with conventional LMS and QR-FIR TEQ in terms of convergence, computational complexity and BER. The simulation results show that proposed QR-IIR method gives better results as compared to the aforementioned methods.

World University root node

Electrical Engineering

2007 3rd International Conference on Wireless Communication and Sensor Networks, WCSN

QR-RLS based adaptive channel shortening IIR-TEQ for OFDM wireless LAN

A new computationally efficient channel shortening technique, to make the OFDM systems robust for delay spreads exceeding the cyclic prefix is presented. The proposed technique gives same BER performance with shorter equalizer. The method is based on pole-zero modeling of the channel impulse response. This gives low computational complexity, both during initialization and data transmission. Moreover no delay search is required as compared with other methods. IEEE 802.11a is considered as underlying OFDM system. ©2007 IEEE.

IEEE Region 10 Annual International Conference, Proceedings/TENCON

A model based channel shortening technique for IEEE 802.11a OFDM system

Fulltext

International Journal of Neural Systems

Erratum: Neuro-fuzzy decision trees (International Journal of Neural Systems (2006) 16:1 (63-78))

A measure to evaluate functional dependency of crisp system output on crisp system input(s) proposed by Pawlak in the context of rough set theory, has been extended to the fuzzy input-output case by using fuzzy-rough hybrids. We have shown that the proposed measure covers Pawlak's measure as a limiting case.

Pattern Recognition Letters

On the extension of functional dependency degree from crisp to fuzzy partitions

This letter provides the theory and mathematical analysis in support of a recently proposed frequency modulated thermal wave imaging for nondestructive subsurface defect detection in solids. The authors illustrate how the technique simultaneously combines the advantages of both conventional pulse based thermography as well as modulated lock-in thermography. A specimen is heated for launching thermal waves into the sample, not at a single frequency (lock-in) or at all frequencies (pulse), but in a desired range of frequencies. While peak power requirement is reduced, phase images obtained retain known advantages. Experimental results from a carbon fiber reinforced plastic sample are presented in support. © 2006 American Institute of Physics.

Applied Physics Letters

Theory of frequency modulated thermal wave imaging for nondestructive subsurface defect detection

External Memory models, most notable being the I-O Model [3], capture the effects of memory hierarchy and aid in algorithm design. More than a decade of architectural advancements have led to new features not captured in the I-O model - most notably the prefetching capability. We propose a relatively simple Prefetch model that incorporates data prefetching in the traditional I-O models and show how to design algorithms that can attain close to peak memory bandwidth. Unlike (the inverse of) memory latency, the memory bandwidth is much closer to the processing speed, thereby, intelligent use of prefetching can considerably mitigate the I-O bottleneck. For some fundamental problems, our algorithms attain running times approaching that of the idealized Random Access Machines under reasonable assumptions. Our work also explains the significantly superior performance of the I-O efficient algorithms in systems that support prefetching compared to ones that do not. © 2006 Springer-Verlag.

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

Algorithmic ramifications of prefetching in memory hierarchy

Many experimental and theoretical studies have been performed on single and multi-wall nanotubes. In particular, deformation modes and overall tube stiffness have been examined. This problem will be even more challenging in the case of nanocomposites in which carbon nanotubes are dispersed randomly in a polymeric (i.e. polystyrene, epoxy etc.) matrix. A critical issue for nanotechnology is the ability to understand, model and simulate the behavior of the small structures and to make the connection between structure properties and functions. Most nanosystems are too small for direct measurements but too large to be described by current rigorous first principles in theoretical and computational methods. They exhibit too many statistical ensembles. The vital role of molecular modeling in this field is to enable engineering design at the component and systems level and to set objectives that could guide laboratory efforts of the physical implications. An important component in molecular mechanics calculations of the nanostructure of materials is the description of the forces between individual atoms which are characterized by a force field. In this paper, the stiffness matrix of a single wall carbon nanotube (SWCNT) of (7, 0) chirality is calculated using molecular dynamics simulation under various combinations of loads. Both the magnitude and direction of load are varied on SWCNT and its composites. When dispersed in the polymeric matrix, it was observed that SWCNTs tend to cluster in bundles. Bundles of 7, 9 and 19 SWCNT (7, 0) are modeled using molecular dynamics and the stiffness matrix is calculated for all the three cases. The polymeric matrix is simulated and its mechanical properties are calculated. SWCNT-polymer nanocomposite is then modeled using a single wall carbon nanotube embedded in a polymeric matrix. Also, the mechanical properties of the interface for the same nanocomposite are calculated. In this case, the density of the SWCNT-polymer nanocomposite in the vicinity of SWCNT is maintained to match the experimentally observed density of the same kind of nanocomposite.

Civil Engineering

American Society for Composites - 21st Technical Conference of the American Society for Composites 2006

Molecular dynamics simulation of SWCNT - Polymer nanocomposite and its constituents

A little explored relationship between the structural and electrical properties of radio frequency sputtered AlN films is studied as a function of nitrogen concentration. It is found that the grain growth mechanism is responsible for an improvement of structural properties and a degradation of electrical properties. © 2006 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Scripta Materialia

Influence of nitrogen concentration on grain growth, structural and electrical properties of sputtered aluminum nitride films

Over the years many researchers have contributed to develop an understanding of moisture absorption behavior of different fiber reinforced composite systems under the influence of various internal factors (fiber volume fraction, fiber orientation, size of fiber reinforcement, moisture absorption nature of fiber and type of fiber etc.) and external factors (relative humidity, temperature of environment and the state of stress experienced by composites etc). In the present research the extent of degradation in flexural properties as a function of amount of absorbed moisture present in pultruded composite material is studied. Further, these results were compared with the effects of water and air freeze thaw on flexural properties of pre-conditioned (150 °F, 24 hours) and non-conditioned samples with and without prior absorbed moisture. For this study, one freeze thaw cycle was comprised of 8 hours of freezing and 16 hours of thawing. This ensured the complete freezing and thawing of the composite material during freeze thaw cycling. A set of samples with and without absorbed moisture were also subjected to room temperature aging. Statistical analysis of results obtained after water and air freeze thaw and room temperature aging was performed in accordance with MIL Handbook - 17. Results of this study indicate that the effect of amount of absorbed moisture on flexural strength is much greater than that of freeze thaw in water or air. However, as a result of drying during room temperature aging, samples with absorbed moisture are able to regain a significant portion of their flexural strength, which was lost due to ingress of moisture. Samples with higher moisture content (0.96%) also regain their strength as a result of drying in a vacuum oven.

Effects of complete freeze thaw on the flexural properties of e-glass/polymer pultruded composite

Automatic filtering of information has become increasingly important in recent years due to large availability of electronic information. We present an approach for optimization of Information Retrieval System (IRS) by genetic algorithm and fuzzy sets in an adaptive filtering process. From the observed user preferences regarding documents in the sets retrieved, the system learns from the user's information needs. An interest profile is created that represents the needs as learned from the observed preferences in the user's area of interest. The proposed system will act as an offline information-filtering agent. The documents have been already downloaded from the Internet using google. The system generates a recommendation based on adaptive filtering using a set of keywords extracted from all documents evaluated by user. The process starts with the initial set of documents retrieved as the answer to user's initial query in the area of interest. The preferences given by the user are learned through explicit feedback on retrieved documents. The agent filters and ranks the retrieved information according to user's preferences using Genetic Algorithm (GA) and Fuzzy Set Theory. The system has been implemented using Java on Windows 98. © 2006 Taylor & Francis Group, LLC.