iosr-JECE   Volume-10 ~ Issue-4 ~ July-August 2015

Abstract: The Practical Swarm Optimization (PSO) algorithms are required behavioral control to perform successful navigation. The role of communication with behavioral control is an important issue in swarm robotics. This paper presents how the leader and follower robots can change their mode of behavioral control by switching between centralization and decentralization processing methods with a new approach using implicit communication. The target of the robots is to reach the goal point, which is placed with IR beacon. The robots can avoid obstacles with the help of IR sensors (1 meter range) and communicates with RF Transceivers (2.4GHz).If there is no obstacle in between leader and follower, then follower continues to follow the leader as per centralization behavior mode.

[1]. Swarm Robotics: An Extensive Research Review Yogeswaran M. and Ponnambalam S. G. School of Engineering, Monash University, Sunway Campus. 46150 Petaling Jaya, Selangor, Malaysia.
[2]. Jung, D. & Zelinsky, A. (2000). Grounded Symbolic Communication between Heterogeneous Cooperating Robots, Autonomous Robots.
[3]. Dudek, G., Jenkin, M., Milios, E. & Wilkes, D. (1993). Taxonomy for Swarm Robots, Intelligent Robots and Systems‟ 93, IROS‟93. Proceedings of the 1993 IEEE/RSJ International Conference.
[4]. Chinnaaiah .M.C. "A novel approach in implementation of rendezvous behavioral control between FPGA robots" published in Advanced Robotics and Intelligent Systems (ARIS), 2014 International Conference. [5]. D‟Angelo, A. &Pagello, E. (2005). Making Collective Behaviors to Work Through Implicit Communication, Robotics and Automation, 2005.ICRA 2005. Proceedings of the 2005IEEE International Conference.
[6]. Lumelsky, V.; Mukhopadhyay, S.; Sun, K., "Sensor-Based Terrain Acquisition: a "Seed Spreader" Strategy," Intelligent Robots and Systems '89. The Autonomous Mobile Robots and Its Applications. IROS '89. Proceedings. IEEE/RSJ International Workshop on , vol., no., pp.62,67, 4-6 Sep 1989.

Abstract: This paper proposes an online system based on an intelligent method of a serial robot multi links. The suggested planning system is composed of multi links andindividual fuzzy units which control separately each manipulator joint. The purpose of this paperis to move the arm from a desired source to a desired destination. Simulation results show that the robot reaches the goal point successfullywith minimum error in terms of path planning.

Keywords: Cartesian space, path planning, fuzzy logic, robot manipulator, multi links.

[1]. Carl D, Crane III, Joseph D, (Eds). Kinematic Analysis of Robot Manipulators, Cambridge University Press, UK,USA, Australia,
2008.
[2]. Appin Knowledge Solutions, "Robotics: Appin Knowledge Solutions", Infinity Science Press Publications LCC, Hingham,
Massachusetts, New Delhi, 2007.
[3]. Cubero S. "Industrial robotics: Theory Modeling and Control" "P lV pro literature Verlag Robert Mayer-Scho lz, Germany.Ch 13,
pp. 379-380, 2007.
[4]. Siciliano B., Sciavicco L., Villani L., and Oriollo G., "Robotic: Modeling, Planning, and Control", Springer, Verland, London
limited, p.p. 104-106, 2010.
[5]. Cheung E., and Lumelsky V., "Proximity Sensing in Robot Manipulator Motion Planning: System and Implementation Issues",
IEEE Trans. Robotics and Automation, 1989, 5(6): 740–751. Downloaded from Iraqi Virtual science library at 8/2/2013.

Abstract: This paper includes a concise record of data windows along with their significant performance parameters from which the different windows can be compared. Windows impact on many attributes of a signal processor which includes detectability , resolution, dynamic range, confidence and ease of implementation. Various Computer Aided Design tools are available for this purpose. The Filter Design and Analysis tool available with MATLAB provides a method to design. In a signal when we compute the frequency content,
usually we tend to pick a limited-duration snapshot which results in errors because the signal actually lasts for
a longer time. Windowing is a way to reduce these errors, though it cannot eliminate them completely. The
problem identified in this paper is to allow performance comparisons between different FIR windows; mainly
Hamming, Hann and Blackman window; based on some major parameters.
Keywords - FIR windows , MATLAB Signal processing ,Window function

[1] Fredric J Harris, On the use of Windows for Harmonic Analysis with the Discrete Fourier Transform,
Proceedings of the IEEE,
Vol 66 ,No.1 , Jan 1978.
[2] Sonika Gupta, Aman Panghal Performance Analysis of FIR Filter Design by Using Rectangular,
Hanning and Hamming Windows Methods,IJARCSSE, Vol-2,Issue-6,Jun2012,pp273-278
[3] Manira Khatun, Implement a new Window function and Design FIR filters by using this new window,
IJECS,Volume-3,Issue-3, March 2014, pp4087-4090.

Abstract: A printed rectangular patch antenna (RPA) with a multiple rectangular shape slots with a rectangular ground plane has been proposed. Four rectangles of dimensions 7.3mm x 1mm is arranged in such a manner to achieve a bandwidth of 200 MHz having a centre frequency of 3.498GHz. This antenna is fabricated on the glass epoxy (FR4 lossy) of dielectric substrate with relative permittivity (€r) of 4.3, thickness of 1.6 mm. Simulated Return loss of -41.7dB is achieved with a good antenna gain. Other parameters such as bandwidth, antenna gain, VSWR are also analysed with different values of ground plane length and feed gap. The simulation and measurement results show that the designed antenna is capable of operating over the 3.399–3.599GHz frequency band. The proposed antenna finds application in Wi-Max which works around 3.5GHz.

Keywords : RPA (Rectangular patch antenna), Rectangular slot, Wi-Max, S – Band Applications.

[1]. Mahdi Moosazadeh and Sergey Kharkovsky, "Compact and Small Planar Monopole AntennaWith Symmetrical L- and U-Shaped Slots for WLAN/WiMAX Applications", IEEE antennas and wireless propagation letters, vol. 13, 2014.
[2]. CA Balanis, Antenna Theory Analysis and Design (John Wiley & Sons Inc, 2nd edition, 1997).
[3]. S. Muzahir Abbas, Istaqlal Ahmed, Hamza Nawaz, Ilyas Saleem, "Meandered Corner Planar Monopole Antenna for UWB Applications", Scientific & Academic Publishing, Vol. 2, No. 3, 2012.
[4]. Jyoti Ranjan Panda, Rakesh Singh Kshetrimayum, "Parametric Study of Printed Rectangular Monopole Antennas", International Journal of Recent Trends in Engineering, Vol. 1, No. 3, 2009.
[5]. N. Suresh Babu, "Design of Compact Printed Rectangular Monopole Antenna and U Shaped Monopole Antenna for L-Band and S-Band Applications", International Journal of Electronics Signal and System, Vol. 1, No. 3, 2012.

Abstract: In this paper, a novel compact frequency-reconfigurable monopole antenna with switchable symmetric slot structure is presented. The frequency-reconfigurable capability of the antenna is achieved by using a switchable slotted structure on the ground plane. The designed antenna has a simple structure and compact size of 40X40 mm . The antenna, which supports most applicable frequency bands above 2 GHz The UWB monopole antenna can be reconfigured by using a slotted structure placed on the ground plane.The antenna is further modified with a symmetric slot structure.By placing slot on the patch makes this antenna to avoid a particular band of frequency.

[1]. S. Yang, C. Zhang, H. K. Pan, A. E. Fathy, and V. K. Nair, ―Frequencyreconfigurable antennas for multiradio wireless platforms,‖ IEEE Microw. Mag., vol. 10, no. 1, pp. 66–83, Feb. 2009.
[2]. FCC Spectrum Policy Task Force, Washington, DC, ―Report of the Spectrum Efficiency Working Group,‖ Tech. Rep., 2002.
[3]. T. Wu,R.L.Li, S. Y. Eom, S. S.Myoung, K. Lim, J. Laskar, S. I. Jeon, and M. M. Tentzeris, ―Switchable quad-band antennas for cognitive radio base station applications,‖ IEEE Trans. Antennas Propag., vol. 58, no. 5, pp. 1468–1476, May 2010.
[4]. A. F. Sheta and S. F. Mahmoud, ―A widely tunable compact patch antenna,‖ IEEE Antennas Wireless Propag. Lett., vol. 7, pp. 40–42, 2008.
[5]. T. Y. Han and C. T. Huang, ―Reconfigurable monopolar patch antenna,‖ Electron. Lett., vol. 46, no. 3, pp. 199–200, Feb. 2010.

Abstract: Image segmentation is a very emerging and important area due to a large number of real life applications. Bag-of-features (BoFs) model is the one of the most successful algorithm used for the image classification. BoF methods are based on order-less collections of quantized local image descriptors; they discard spatial information and are therefore conceptually and computationally simpler than many alternative methods.Bag-of-features algorithm is used for the feature extraction from the image. BoFs model has several advantages like,scalability,simplicity, and generality. But BoFs have some disadvantages too and some of them are Time and Accuracy of the image classification process.

[1]. G. Csurka, C. Dance, L. Fan, J. Willamowski, and C. Bray, "Visual Categorization with Bags of Keypoints," in Proc. Workshop Statist. Learn. Comput. Vis., Eur. Con. Comput. Vis., 2004, pp. 1-22.
[2]. M. Marszalek and C. Schmid, "Spatial weighting for bag-of-features," in Proc. Comput. Vis. Pattern Recognit., 2006, pp. 2118-2125.
[3]. E. Nowak, F. Jurie, and B. Triggs, "Sampling strategies for bag-of features image classification," in Proc. Comput. Vis. Pattern Recognit.,2006, pp. 490–503.
[4]. G. Csurka, C. Dance, L. Fan, J. Williamowski, and C. Bray, "VisualCategorization with Bags of Keypoints,"Proc. ECCV WorkshopStatistical Learning in Computer Vision,pp. 59-74, 2004
[5]. R. Fergus, L. Fei-Fei, P. Perona, and A. Zisserman, "LearningObject Categories from Google‟s Image Search,"Proc. 10th IEEEInt‟l Conf. Computer Vision,vol. 2, pp. 1816-1823, 2005.

Abstract: The requirement for elevated data-rate multimedia wireless communication has been increasing rapidly. As standards are addressing higher capacity wireless links to meet increasing demands, as well as the consumption of device power is also increasing rapidly. A wireless sensor network has many inimitable characteristics such as intensive node deployment, higher unreliability of sensor nodes, asymmetrical data transmission, computation and stern power.

1]. A.Sivagami,S.Malarkkann,S.Sandiya,R.Ramakrishnan,"Analysis of Residual Energy and SNR of DSR/AODV/RPAR Protocols in Wireless Multimedia Sensor Networks",Advances in natural and applied sciences, vol.8,no.16, pp.66-74,Nov. 2014.
[2]. Sung-Keun Lee,.et al,' "An Energy Efficient QoS-aware Routing Algorithm for Wireless Multimedia Sensor Networks", International Journal of Multimedia and Ubiquitous Engineering, vol.9,no.2, 2014.
[3]. Shruti Prabha Shaktawat and O.P Sharma, "Node Deployment Models and their Performance Parameters for Wireless Sensor Network: A Perspective", International Journal of Computer App (0975 – 8887), Vol. 88 , No.9, Feb 2014
[4]. Junho Park,et al,''Disjointed Multipath Routing for Real-Time Data in Wireless Multimedia Sensor Networks'',International Journal of Distributed Sensor Networks,vol.14,2014.
[5]. S. Ponlatha and R. S. Sabeenian, "Comparison of Video Compression Standards", International Journal of Computer and Electrical Engineering, Vol. 5, No. 6, Dec 2013.

Abstract: In cognitive radio network, improvement in the spectrum efficiency is achieved by employing the cognitive radios that act as secondary users to opportunistically access the under-utilized frequency bands. Spectrum sensing, as a key technology in cognitive radio networks is used to detect the signals from licensed primary radios to avoid harmful interference. However, due to fading, individual cognitive radios may not be able to reliably detect the existence of a primary radio. To mitigate such effects, cooperative sensing is proposed while satisfying a constraint on the detection performance. This paper presents the mathematical derivation for the optimal number of cooperating cognitive radios under two scenarios: energy efficient and a throughput optimization setup.

[1]. Subhedar, Mansi, and GajananBirajdar. "Spectrum sensing techniques in cognitive radio networks: a survey." International Journal of Next-Generation Networks 3.2 (2011): 37-51.
[2]. Tulika Mehta, Naresh Kumar, Surender S Saini, "Comparison of Spectrum Sensing Techniques in Cognitive Radio Networks", IJECT Vol. 4, Issue Spl - , April - June 2013.
[3]. P. K. Varshney, "Distributed Detection and Data Fusion", Springer-Verlag,1996.
[4]. R. Viswanathan and P. K. Varshney, "Distributed detection with multiplesensors," Proc. IEEE, vol. 85, pp. 5463, Jan. 1997.

Abstract: DAB (digital audio broadcasting) is a radio system which is depends on EUREKA-147 project. This project was designed by the Members of European Broadcasting Union (EBU). DAB System depends on wireless communication. DAB channel estimation was designed by the OFDM technology that reduces co-channel interference and multipath fading. In this paper we have analyzed bit error rate performance v/s signal to noise ratio (BER v/s SNR).for DAB modes we done block coding with the help of MATLAB Simulink tool. In this paper we use 16-QAM modulation technique and reed-Solomon convolution coding.

[1]. A. J Bower, "DIGITAL RADIO--The Eureka 147 DAB System," Electronic Engineering BBC, April 1998.
[2]. R P Singh and S D Sapre, Communication Systems, 2nd ed.: Tata McGraw-Hill Education Pvt. Ltd., 2007.
[3]. Kai-Sheng Yang, Chao-Tang Yu Yu-Pin Chang, "Improved Channel Codec Implementation and Performance Analysis of OFDM based DAB Systems," in IWCMC 2006 - Proceedings of the 2006 International Wireless Communications and Mobile Computing Conference, 84 2006, pp. 997-1001.
[4]. Brian Chen and Carl-Erik W. Sundberg, "An Integrated Error Correction and Detection System for Digital Audio Broadcasting," in IEEE Transactions On Broadcasting, vol. vol. 46, March 2000, pp. 68-78.
[5]. Lukas M. Gaetzi and Malcolm O. J. Hawks ford, "Performance prediction of DAB modulation and transmission using Matlab modeling," in IEEE International Symposium on Consumer Electronics – Proceedings, 2004, pp. 272-277.

Abstract: The introduction of mobile communication has changed how people behave and their demand for connectivity is anywhere and anytime. This demand is driven by the fact that essential services have moved from mere telecommunication to very crucial services like money transfer services, e-learning and medical services. However, terrorism threats, vandalism, environmental disasters and general failures are also on the increase and these threaten the availability of mobile services anytime and everywhere. It is thus critical that measures are taken to ensure availability of service amid these threats. Cell zooming promises to provide a self-healing solution that would ensure the demand for service is anytime and anywhere is sustained. This paper investigates the application of cell zooming in outage compensation. Cell zooming is achieved by adjusting the input power to the transmitter or the height of the transmitter.

[1]. I. Poole. Radio-electronics.com. [Online
[2]. R. Litjens. (November 16, 2012) Self-Management in Cellular Networks.
[3]. Nokia Siemens Networks, "Self-Organizing Network (SON)," White Paper, 2009.
[4]. 3GPP , "Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN), Overall Description, Stage 2, Release 8," 3GPP , TS 36.300 v. 8.8.0, 2009.
[5]. 3GPP LTE, "Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Self-configuring and self-optimizing network (SON) use cases and solutions," Sophia Antipolis Cedex - FRANCE, 2010.
[6]. 3GPP, "Self-configuring and self-optimizing network (SON) use cases and solutions," 3GPP, TS 36.902, 2008.

Abstract: In this paper Self similar solutions for one dimensional flow of plane shock wave propagating into an uniform atmosphere with variable density and pressure, are obtained where the uniform atmosphere assumed to be at rest.

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