iosr-JECE   Volume-2 ~ Issue-6

Abstract:In this paper Electromagnetic Band Gap structure with microstrip antenna has been proposed. Many small and compact periodic EBGs have been investigated to design the antenna. Simulation is done on the HFSS software tool. The antenna is designed on the 21x31mm FR4 substrate with the dielectric constant of 4.4. The designed antenna is designed to resonate at 8GHz frequency. The designed antenna is having the peak return loss of 49.87dB at 7.7GHz frequency with the bandwidth of 4.7GHz from 5.3GHz to 10GHz, thus has the wide range of applications in ultra wideband communication.
Keywords– EBG, microstrip antenna, patch antenna, UWB, wideband antenna.

[[1]. Y. Fu and N. Yuan, "Elimination of scan blindness in phased array of microstrip patches using electromagnetic bandgap materials," IEEE Antennas Wireless Propag. Lett., vol. 3, pp. 64–65, 2004.
[2]. J. S. Colburn and Y. Rahmat-Samii, "Patch antennas on externally perforated high dielectric constant substrates," IEEE Trans. Antennas Propag., vol. 47, no. 12, pp. 1785–1794, Dec. 1999.
[3]. Pirhadi, A., M. Hakkak, and F. Keshmiri, "Bandwidth enhancement of the probe fed microstrip antenna using frequency selective surface as electromagnetic bandgap superstrate," Progress In Electromagnetics Research, PIER 61, 215–230, 2006.
[4]. Pirhadi, A., F. Keshmiri, and M. Hakkak, "Design of dualband low profile high directive EBG resonator antenna, using single layer frequency selective surface superstrate," IEEE APS/USNC/URSI Int. Symp., Albuquerque, New Mexico, USA, July 9–14, 2006.
[5]. Lee, Y. J., J. Yeo, R. Mittra, and W. S. Park, "Application of electromagnetic bandgap (EBG) superstrates with controllable defects for a class of patch antennas as spatial angular filters," IEEE Trans. Antennas and Propag., Vol. AP-53, No. 1, 224–234, Jan. 2005.
[6]. G. Cakir and L. Sevgi, "Design of a novel microstrip electromagnetic band-gap (EBG) structure," Microw. Opt.Technol Lett., vol. 46, pp. 399–401, 2005.
[7]. F. Yang and Y. Rahmat-Samii, "Microstrip antennas integrated with electromagnetic band-gap (EBG) structures: A low mutual coupling design for array applications," IEEE Trans. Antennas Propag., vol. 51, no. 10, pp. 2936–2946, Oct. 2003.
[8]. Ansoft Corporation, HFSS 14.

Abstract: This work proposes MARA, a joint method for automatic rate selection and route quality evaluation in Wireless Mesh Networks. This method targets at avoiding the problem of inaccurate link quality estimates, common to main existing proposals of multi-hop wireless routing metrics. In this proposal, the statistics collected by the routing protocol are used by the rate adaptation algorithm to compute the best rate for each wireless link. This coordinated decision aims at providing better routing and rate choices. Simulation results indicate that MARA leads to an overall improvement in network performance.

Key Words:Wireless Mesh Networks, Routing Metrics, Rate Adaptation Algorithms.

[1] M. E. M. Campista, D. G. Passos, P. M. Esposito, I. M. Moraes,C. V. N. de Albuquerque, D. Muchaluat-Saade, M. G. Rubinstein, L. H.M. K. Costa, and O. C. M. B. Duarte, "Routing metrics and protocolsfor wireless mesh networks," IEEE Network, vol. 22, no. 1, pp. 6–12,Jan./Feb. 2008.
[2] K. Ramachandran, H. Kremo, M. Gruteser, P. Spasojevic, and I. Seskar,"Scalability analysis of rate adaptation techniques in congested IEEE802.11 networks: An orbit testbed comparative study," in WoWMoM2007, Jun. 2007, pp. 1–12.
[3] J. P. Pavon and S. Choi, "Link adaptation strategy for IEEE 802.11WLAN via received signal strength measurement," in ICC '03, vol. 2, 2003, pp. 1108–1113.
[4] C. E. Koksal and H. Balakrishnan, "Quality-aware routing metrics fortime-varying wireless mesh networks," IEEE Journal on Selected Areas in Communications, vol. 24, no. 11, pp. 1984–1994, Nov. 2006.
[5] R. Draves, J. Padhye, and B. Zill, "Routing in multi-radio, multi-hop wireless mesh networks," in ACM International Conference on MobileComputing and Networking (MobiCom), Sept. 2004, pp. 114–128.
[6] Special Interest research Group on NETworking (SIGNET). (2008, Jun.) dei80211mr: a new 802.11 implementation for ns 2. [Online]. Available: http://www.dei.unipd.it/wdyn/?IDsezione=5090

Abstract:Biometric identification systems, which use physical features to check a person's identity, ensures much greater security than password and number systems. Multibiometric system is being increasingly deployed in much large scale application because they provide lower error rate, large population coverage compared to unibiometric. In this paper, multibiometric identification system aim to fuse iris n fingerprint traits. During enrollment stage system generate iris n fingerprint template separately n stored in database. Approach for fingerprint recognition is to extract minutiae from fingerprint images. It makes possible to achieve highly robust fingerprint recognition for low-quality fingerprints. During iris recognition images are segmented, normalized and features are extract by using Log-Gabor filter. Finally matching is done with help of hamming-distance. Once both iris n fingerprint template are match separately scores are combined by using sum rule-based score level fusion which increase the recognition rate. Thus improve system accuracy and dependability.
Keywords- biometric, minutiae extraction, Log-Gabor filter, sum-rule based score level fusion, identification system

[1] K. Nandakumar and A. K. Jain, ―Multibiometric based on feature-level fusion,‖ in Proc. IEEE 2nd Int. Conf. on information, and Security,vol.7,no.1, Feb.2012.
[2] Norman Poh, Josef Kittler ―A Unified Framework for Biometric Expert Fusion Incorporating Quality Measures,‖ IEEE Transactions on pattern analysis and machine intelligence, VOL. 34, NO. 1, January 2012
[3] A.Gunatilaka and Brian A., ―Feature level and decision level fusion of noncoincidently sampled sensor for land mine detection,‖ in
Proc. IEEE 2nd Int. Conf. on information, and Security,vol.7,no.1, Feb.2012.
[4] A. Nagar, S. Rane, and A. Vetro, ―Privacy and security of features extracted from minutiae aggregates,‖ in Proc. IEEE Int. Conf.
Acoustics, Speech and Signal Processing, Dallas, TX, Mar. 2010, pp. 524–531.
[5] T. Ignatenko and F. M. J. Willems, ―Biometric systems: Privacy and secrecy aspects,‖ IEEE Trans. Inf. Forensics Security, vol 4,
no. 4, pp. 956–973, Dec. 2009.
[6] R. Snelick, U. Uludag, A. Mink, M. Indovina, A. Jain, Large-scale evaluation of multimodal biometric authentication using state-ofthe- art systems, IEEE Trans- actions on Pattern Analysis and Machine Intelligence 27 (3) (2005) 450–455.
[7] K. Veeramachaneni, L. A. Osadciw, and P. K. Varshney, ―An adaptive multimodal biometric management algorithm,‖ IEEE Trans.
Syst., ManCybern. C, Appl. Rev., vol. 35, no. 3, pp. 344–356, Aug. 2005.
[8] M. Vatsa, R. Singh, and A. Noore, ―Improving iris recognition performance using segmentation, quality enhancement, match score
fusion, and indexing,‖ IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 38, no. 4, pp. 1021–1035, Aug. 2008.
[9] K. Miyazawa, K. Ito, T. Aoki, K. Kobayashi, and H. Nakajima, ―An effective approach for iris recognition using phase-based image matching,‖ IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 10, pp. 1741–1756,Oct. 2008.
[10] W. W. Boles and B. Boashash, ―A human identification technique using images of the iris and wavelet transform,‖ IEEE Trans.
Signal Process.,vol. 46, no. 4, pp. 1185–1188, Apr. 1998.