Prakash G.,KS Rangasamy College of Technology |
ICECT 2011 - 2011 3rd International Conference on Electronics Computer Technology | Year: 2011
The IEEE 802.11e WLAN defines a MAC Protocol to support real-time application. In this paper, we propose an analytical model for performance evaluation of IEEE 802.11e EDCA scheme under non-saturation condition and channel error rate. The analytical model is suitable for both basic access and RTS/CTS access mechanisms. We develop an expression for the nonsaturation throughput as a function of the number of stations, packet sizes and BER. We validate the accuracy of our analysis with simulation expression. Using this model, the contention factors can be arranged appropriately to accomplish specific quality-of-service (QoS) requirements. © 2011 IEEE.
Kar A.,IIIT |
Studies in Computational Intelligence | Year: 2014
The structure of an adaptive time varying linear filter largely depends on its tap-length and the delay units connected to it. The no of taps is one of the most important structural parameters of the liner adaptive filter. Determining the system order or length is not a trivial task. Fixing the tap-length at a fixed value sometimes results in unavoidable issues with the adaptive design like insufficient modeling and adaptation noise. On the other hand a dynamic tap-length adaptation algorithm automatically finds the optimum order of the adaptive filter to have a tradeoff between the convergence and steady state error. It is always difficult to get satisfactory performance in high noise environment employing an adaptive filter for any identification problem. High noise decreases the Signal to noise ratio and sometimes creates wandering issues. In this chapter an improved pseudo-fractional tap-length selection algorithm has been proposed and analyzed to find out the optimum tap-length which best balances the complexity and steady state performance specifically in high noise environment. A steady-state performance analysis has been presented to formulate the steady state tap-length in correspondence with the proposed algorithm. Simulations and results are provided to observe the analysis and to make a comparison with the existing tap-length learning methods. © Springer International Publishing Switzerland 2014.
Sarkar B.K.,B.I.T. |
Sana S.S.,Bhangar Mahavidyalaya C.U. |
Chaudhuri K.,Jadavpur University
Applied Soft Computing Journal | Year: 2012
Individual classifiers predict unknown objects. Although, these are usually domain specific, and lack the property of scaling up prediction while handling data sets with huge size and high-dimensionality or imbalance class distribution. This article introduces an accuracy-based learning system called DTGA (decision tree and genetic algorithm) that aims to improve prediction accuracy over any classification problem irrespective to domain, size, dimensionality and class distribution. More specifically, the proposed system consists of two rule inducing phases. In the first phase, a base classifier, C4.5 (a decision tree based rule inducer) is used to produce rules from training data set, whereas GA (genetic algorithm) in the next phase refines them with the aim to provide more accurate and high-performance rules for prediction. The system has been compared with competent non-GA based systems: neural network, Naïve Bayes, rule-based classifier using rough set theory and C4.5 (i.e., the base classifier of DTGA), on a number of benchmark datasets collected from UCI (University of California at Irvine) machine learning repository. Empirical results demonstrate that the proposed hybrid approach provides marked improvement in a number of cases. © 2011 Elsevier B.V. All rights reserved.
Islam A.,BIT |
2012 Annual IEEE India Conference, INDICON 2012 | Year: 2012
Due to increase in Vt (threshold voltage) variation caused by global and local process variations in ultrashort-channel devices, CMOS-based 6T SRAM cell and its variants cannot be operated at voltage lower than 600 mV. Therefore, this paper presents a FinFET-based 8T SRAM cell to mitigate impact of process variation. In this work, various design metrics are assessed and compared with MOSFET-based RD8T SRAM cell. The proposed design offers 4.35× and 1.86× improvements in TRA (read access time) and TWA (write access time) respectively compared to RD8T. It proves its robustness against process variations by featuring narrower spread in TRA distribution (6.95×) and TWA distribution (5.04×) compared with RD8T. These improvements are achieved at the expense of 11.65× higher read power and 13.75× higher write power. However, proposed bitcell exhibits 3.64× narrower spread in read power and 1.94× narrower spread in write power. Our bitcell achieves 6% improvement in RSNM compared with RD8T at the cost of reduction in WSNM (write static noise margin). However, it is still RSNM limited and is more balanced in terms of RSNM and WSNM. © 2012 IEEE.
Jayabharata Reddy M.,NIT |
International Journal of Energy Technology and Policy | Year: 2011
This paper presents a modular approach for detection, classification and location of transmission line faults using wavelet transform along with intelligent techniques. By using wavelet Multiresolution Analysis (MRA), summation of detail coefficients is extracted for three-phase fault currents. These detail coefficients constitute the edifice for classification and location of faults. The classification of different types of faults is done using Fuzzy Inference System (FIS). The algorithm proceeds with classification of arcing and non-arcing faults, and then locates the fault on the transmission line using Modular Artificial Neural Networks (MANNs). The results indicate that such a modular approach can be used for supporting high-speed protective relaying systems during both arcing and non-arcing faults. Copyright © 2011 Inderscience Enterprises Ltd.
Pal M.,National Institute of Technology Kurukshetra |
Singh N.K.,BIT |
Tiwari N.K.,National Institute of Technology Kurukshetra
Engineering Applications of Artificial Intelligence | Year: 2011
This paper investigates the potential of support vector machines based regression approach to model the local scour around bridge piers using field data. A dataset of consisting of 232 pier scour measurements taken from BSDMS were used for this analysis. Results obtained by using radial basis function and polynomial kernel based Support vector regression were compared with four empirical relation as well as with a backpropagation neural network and generalized regression neural network. A total of 154 data were used for training different algorithms whereas remaining 78 data were used to test the created model. A coefficient of determination value of 0.897 (root mean square error=0.356) was achieved by radial basis kernel based support vector regression in comparison to 0.880 and 0.835 (root mean square error=0.388 and 0.438) by backpropagation neural and generalized regression neural network. Comparisons of results with four predictive equations suggest an improved performance by support vector regression. Results with dimensionless data using all three algorithms suggest a better performance by dimensional data with this dataset. Sensitivity analysis suggests the importance of depth of flow and pier width in predicting the scour depth when using support vector regression based modeling approach. © 2010 Elsevier Ltd. All rights reserved.
Tiwari A.,BIT |
Mandal A.,NIFFT |
Materials Today: Proceedings | Year: 2015
Objective: of thework is to achieve best optimal combination of various input parameter for radial over-cut (ROC) in electrochemical machining for EN 19 tool steel with copper electrodeapplyingtaguchitechnique. The electrolytic concentration, voltage, feed rate and inter electrode gap are considered as input process parameters for electro-chemical machining. Optimal combination of selected input parameters utilized in order to achieve the minimum overcut effects for better accuracy of shape features. The experiments were undertaken as per taguchiL27 orthogonal array (OA) with three levels for each machining parameter. The Design of Experiments of L27 orthogonal array was tabulated with the aid of Minitab software version 16. The impact of each machining process parameterswere predicted by performing ANOVA at 95% level of significance. This paper also stress on the development of mathematical model by using regression analysis, second order response equation obtained between the controllable variables and parametric interactions for overcut as response. From the obtained results, it wasobserved thatvoltage and concentrationwere the most dominating criteria for minimization of overcut. © 2015.
Verma N.,BIT |
Procedia Engineering | Year: 2016
Value stream mapping is an effective tool of lean manufacturing to reduce the wastage in any process by segregating value added and non-value added activities. The present work uses the concept of value stream mapping and developed energy value stream mapping to address the non productive energy consuming processes. This paper focuses on achieving Green Manufacturing as overall productivity which has already reached an acceptable value. The main problem identified is that there is a void when it has been looked for a tool to achieve Lean Manufacturing along with Green manufacturing. It deals with the development of a method that allows a first quick, easy and comprehensive analysis of energy and material flows within the production processes. The paper concludes with discussing improvements in the processes. © 2016 The Authors. Published by Elsevier Ltd.
Prakash G.,k-Technology |
Journal of Computer Science | Year: 2011
Problem statement: The IEEE 802.11e EDCA protocol with different access Categories (ACs) supporting for Quality-of-Service (QoS). Due to internal or external packet collision, the Contention Window (CW) of the station increases the channel idle time under high Bit Error Rate (BER). Approach: In this study, we propose an analytical model for performance evaluation of IEEE 802.11e EDCA scheme under non-saturation condition and error prone channel. The new markov chain model have decrease the channel idle time in IEEE 802.11 EDCA and considerably increases the throughput for minimum number of station. Results: We develop an expression for the nonsaturation throughput as a function of the number of stations, packet sizes and BER. Conclusion: We validate the accuracy of our analysis with simulation expression. Using this model, the contention factors can be set appropriately to attain particular Quality-of-Service (QoS) requirements. © 2011 Science Publications.
Priya A.,BIT |
Sinha E.,BIT |
Solid State Sciences | Year: 2013
In this paper, Barium Strontium Tungstate (Ba1-xSr x)WO4 crystals with (x = 0; 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 and 1.0) were prepared by standard wet milling ceramic preparation method. These crystals were structurally characterized by X-ray diffraction (XRD), Fourier transform Raman (FT-Raman) and Fourier transform infrared (FT-IR) spectroscopic techniques. The shape, growth and average crystal size distribution of these crystals were investigated by a scanning electron microscope (SEM). Their optical properties were investigated by ultraviolet visible (UV-vis) absorption and photoluminescence (PL) measurements. XRD patterns, Rietveld refinements data, FT-Raman and FT-IR spectroscopies indicate that all the crystals present a scheelite-type tetragonal structure without deleterious phases. FT-Raman spectra exhibited 6 Raman active modes in range from 100 to 1000 cm-1, while the FT-IR spectra presented 2 infrared active modes in range from 500 to 1000 cm-1. SEM micrographs showed well sintered BaWO4 grains, while the substitution of Sr induced modifications in the shape and reduction in the grain size. UV-vis absorption measurements evidenced an increase in the values of the optical band gap (from 4.36 to 4.53 eV) with the increase of Sr into BaWO4 lattice. Dielectric constant, temperature coefficient of resonant frequency (τf), quality factors were measured with Hakki-Coleman technique. The value of τf found -43.68 ppm/ C for BaWO4 which increased to -21.40 ppm/ C for the SrWO4. © 2013 Elsevier Masson SAS. All rights reserved.