Networks

Mobile Communications Networks Mobile Communications Networks

Mobile Communications Networks − Evolving through Biologically-Inspired Technologies − Abbas Jamalipour, PhD; Fellow IEEE, Fellow IEAust IEEE Distinguished Lecturer Email: [email protected] October 2009 Contents Mobile Communications Networks and NGMN Why Bio-Inspired Networking? Bio-Inspired Defined Bio-Inspired Techniques in Communications New Elements Incorporating NGMN Closing

Advantages of Radial Basis Function Networks for Dynamic

5438 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 58, NO. 12, DECEMBER 2011 Advantages of Radial Basis Function Networks for Dynamic System Design Hao Yu, Student Member, IEEE, Tiantian Xie, Stanisław Paszczyñski, Senior Member, IEEE, and Bogdan M. Wilamowski, Fellow, IEEE Abstract—Radial basis function (RBF) networks have advantages

Siamese Networks for 1D Signal Identiﬁcation

Siamese Networks for 1D Signal Identiﬁcation Jan Schuetzke1, Alexander Benedix2, Ralf Mikut1, Markus Reischl1 1 Institute for Automation and Applied Informatics, KIT Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen E-Mail: [email protected] 2 Bruker AXS GmbH Oestliche Rheinbrückenstraße 49 76187 Karlsruhe E-Mail: [email protected] Abstract In material sciences, X-ray diffraction (XRD) or nuclear magnetic

ATM Networks: An Overview and Applications

ATM Networks: An Overview and Applications Raj Jain The Ohio State University Columbus, OH 43210 [email protected] http://www.cis.ohio-state.edu/~jain/ The Ohio State University 1 Raj Jain Overview q Trends: Why networking is critical? q What is ATM? q How and where can you use ATM? q What are

Software Systems through Complex Networks Science: Review

Software Systems through Complex Networks Science: Review, Analysis and Applications arXiv:1208.2518v1 [cs.SI] 13 Aug 2012 Lovro Šubelj University of Ljubljana Faculty of Computer and Information Science Tržaška cesta 25, SI-1000 Ljubljana, Slovenia [email protected] ABSTRACT Complex software systems are among most sophisticated human-made systems, yet only little is known

Survey of Important Issues in UAV Communications Networks

1 Survey of Important Issues in UAV Communication Networks Lav Gupta*, Senior Member IEEE, Raj Jain, Fellow, IEEE, and Gabor Vaszkun Abstract—Unmanned Aerial Vehicles (UAVs) have enormous potential in the public and civil domains. These are particularly useful in applications where human lives would otherwise be endangered.

Juniper Networks Product Quick Reference Guide

Juniper Networks Product Quick Reference Guide May 2006 Product Guide General Disclaimer Although Juniper Networks has attempted to provide accurate information in this Guide, Juniper Networks assumes no responsibility for the accuracy of the information. Juniper Networks may change the programs or products mentioned at any time without prior

Error Resilient Image Transport in Wireless Sensor Networks

Error Resilient Image Transport in Wireless Sensor Networks Huaming Wu, Alhussein A. Abouzeid ∗ Department of Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, 110 8th St. Troy, NY 12180 USA Abstract In this paper, we propose an “in-network” diversity combining scheme for image transport over wireless sensor networks. We

Reliable Wireless Data Transfer for Wireless Sensor Networks

Reliable Wireless Data Transfer for Wireless Sensor Networks Helen Chung, Reena Gupta Knight, Alex Liu, Evong Nham, Joshua Waldman Turned in for INFS612 on July 17, 2006 and Presented on July 19, 2006 George Mason University Fairfax, Virginia, USA Abstract Wireless Sensor Networks (WSN) are an emerging technology being used

CCNA 1: Introduction to Networks (CCNA Certification)

CCNA 1: Introduction to Networks (CCNA Certification) Training Course CCNA 1: Introduction to Networks (CCNA Certification) Course Language English Course Duration Total Number of hours : 60 hours Days: once a week Time: from 4:00PM to 8:00PM Course Objectives This course introduces the architecture, structure,

FiWi Access Networks

FiWi Access Networks The evolution of broadband access networks toward bimodal ﬁber-wireless (FiWi) access networks, described in this book, may be viewed as the endgame of broadband access. After discussing the economic impact of broadband access and current worldwide deployment statistics, all the major legacy wireline and wireless broadband access

Confidence in Protein Interaction Networks

Conﬁdence in Protein Interaction Networks Lyuba Ventsislavova Bozhilova Pembroke College University of Oxford A thesis submitted for the degree of Doctor of Philosophy Michaelmas Term 2019 Acknowledgements First and foremost, I would like to thank my supervisors, Charlotte Deane and Gesine Reinert, for their guidance. I have been incredibly

Handwritten Indic Character Recognition using Capsule Networks

Handwritten Indic Character Recognition using Capsule Networks Bodhisatwa Mandal∗,Suvam Dubey∗, Swarnendu Ghosh∗, RiteshSarkhel†, Nibaran Das∗ ∗Dept. of CSE, Jadavpur University, Kolkata, 700032, WB, India. {bodhisatwam,suvamdubey}@gmail.com, swarnendughosh.cse.rs,[email protected] †Dept. of CSE, Ohio State University, Columbus, OH 43210, USA [email protected] arXiv:1901.00166v1 [cs.CV] 1 Jan 2019 Abstract—Convolutional neural networks(CNNs) has become one

Numerical Analysis near Singularities in RBF Networks

Journal of Machine Learning Research 19 (2018) 1-39 Submitted 4/16; Revised 4/18; Published 8/18 Numerical Analysis near Singularities in RBF Networks Weili Guo [email protected] Haikun Wei [email protected] Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation Southeast

Climbing the Hills of Compiled Credal Networks

5th International Symposium on Imprecise Probability: Theories and Applications, Prague, Czech Republic, 2007 Climbing the Hills of Compiled Credal Networks Rolf Haenni Bern University of Applied Sciences, Switzerland [email protected] University of Bern, Switzerland [email protected] Abstract This paper introduces a new approximate inference algorithm for credal networks. The algorithm consists

Learning lessons from international community forestry networks

Learning Lessons from International Community Forestry Networks: Synthesis Report Marcus Colchester, Tejaswini Apte, Michel Laforge, Alois Mandondo & Neema Pathak March 2003 Learning Lessons from International Community Forestry Networks: Synthesis Report ___________________________________________________________________________ Acknowledgements: The authors would like to recognize the valuable contributions of very many people who made this

Secure Government Networks And Systems

Secure Government Networks And Systems With Forcepoint Global Government Solutions forcepoint.com Brochure Secure Government Networks And Systems With Forcepoint Global Government Solutions Table of Contents forcepoint.com/government 03 04 05 08 09 11 A Proven Leader in Defense-grade Security Integrated Solutions to Support the Mission

BOND: Unifying Mobile Networks with Named Data

University of California Los Angeles BOND: Unifying Mobile Networks with Named Data A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science by Michael Richard Meisel 2011 c Copyright by Michael Richard Meisel 2011 The dissertation of Michael Richard Meisel

Sensor Networks: Evolution, Opportunities, and Challenges

Sensor Networks: Evolution, Opportunities, and Challenges CHEE-YEE CHONG, MEMBER, IEEE AND SRIKANTA P. KUMAR, SENIOR MEMBER, IEEE Invited Paper Wireless microsensor networks have been identified as one of the most important technologies for the 21st century. This paper traces the history of research in sensor networks over the past

On the Structural Sensitivity of Deep Convolutional Networks

On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions Yusuke Tsuzuku1,2, Issei Sato1,2 1The University of Tokyo, 2RIKEN [email protected], [email protected] Abstract Data-agnostic quasi-imperceptible perturbations on inputs are known to degrade recognition accuracy of deep convolutional networks severely. This phenomenon is considered to be