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A Survey on Aerial Swarm Robotics

Soon-Jo Chung, Aditya Avinash Paranjape, Philip Dames, Shaojie Shen, Vijay Kumar
2018 IEEE Transactions on robotics  
Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional (3-D) space, and the dynamics of individual vehicles adds an extra layer of complexity.  ...  This technology depends on the clever and innovative application of theoretical tools from control and estimation.  ...  Hierarchical approaches are pervasive in both the machine learning and control fields for dealing with complexity and high dimensionality (e.g., hierarchical task networks (HTNs) [11] , hierarchical tree  ... 
doi:10.1109/tro.2018.2857475 fatcat:4blp42msbzakvmwlwyd3e57o2e

Forecasting Loss of Signal in Optical Networks with Machine Learning

Wenjie Du, David Cote, Chris Barber, Yan Liu
2021 Journal of Optical Communications and Networking  
Loss of Signal (LOS) represents a significant cost for operators of optical networks.  ...  before they occur, albeit at relatively low recall, with supervised machine learning (ML).  ...  Thanks to Paul Gosse, Dana Dennis and Yinqing Pei for expert guidance about Ciena equipment. Thanks to Mitacs for facilitating a fruitful collaboration between Concordia University and Ciena.  ... 
doi:10.1364/jocn.423667 fatcat:htipe3aw2fgzpizvkm4m7alizq

How Industry 4.0 Changes Business : A Commercial Perspective

Ayşe Göksu Özüdoğru, Esra Ergün, Djihane Ammari, Ali Görener
2018 International Journal of Commerce and Finance  
Commercial and industrial application examples of Industry 4.0 in different sectors and the possible implementation areas are defined based on countries and sectors.  ...  Finally, the commercial impacts of this new business model is given from the industrial and human perspectives.  ...  on commercial world based on the findings in research.  ... 
doaj:383fb6480e3e45e79e8c1b6bbfddf78e fatcat:xsv7zwr4vvdwhpbhcpif7zd23i

A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives

Irfan Ahmed, Hedi Khammari, Adnan Shahid, Ahmed Musa, Kwang Soon Kim, Eli De Poorter, Ingrid Moerman
2018 IEEE Communications Surveys and Tutorials  
We explore the suitability of hybrid beamforming methods, both, existing and proposed till first quarter of 2017, and identify the exciting future challenges in this domain.  ...  Index Terms-hybrid beamforming, mmWave, massive MIMO, HetNet, radio access network.  ...  Based on the received SINR, TI and BT exchange their roles and together learn their own optimal directions.  ... 
doi:10.1109/comst.2018.2843719 fatcat:v7kmfmaxrfeeti7hcwsjjf5fda

An Overview on Application of Machine Learning Techniques in Optical Networks [article]

Francesco Musumeci, Cristina Rottondi, Avishek Nag, Irene Macaluso, Darko Zibar, Marco Ruffini, Massimo Tornatore
2018 arXiv   pre-print
Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration  ...  The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years.  ...  Optics for Machine Learning (vs. Machine Learning for optics). Finally, an interesting, though speculative, area of future research is the application of ML to all-optical devices and networks.  ... 
arXiv:1803.07976v4 fatcat:rhzumocnrzfxpismbpkjejytfm

An Overview on Application of Machine Learning Techniques in Optical Networks

Francesco Musumeci, Cristina Rottondi, Avishek Nag, Irene Macaluso, Darko Zibar, Marco Ruffini, Massimo Tornatore
2018 IEEE Communications Surveys and Tutorials  
Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration  ...  The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years.  ...  Optics for Machine Learning (vs. Machine Learning for optics). Finally, an interesting, though speculative, area of future research is the application of ML to all-optical devices and networks.  ... 
doi:10.1109/comst.2018.2880039 fatcat:ql662vgph5hjdejxtl5yvdysom

Big data analytics for wireless and wired network design: A survey

Mohammed S. Hadi, Ahmed Q. Lawey, Taisir E.H. El-Gorashi, Jaafar M.H. Elmirghani
2018 Computer Networks  
In this paper, we conduct a survey on the role that big data analytics can play in the design of data communication networks.  ...  To the best of our knowledge, this is the first survey that addresses the use of big data analytics techniques for the design of a broad range of networks.  ...  Machine learning methods for cybersecurity intrusion detection The authors in [107] surveyed the topic of intrusion detection methods based on data mining and machine learning algorithms.  ... 
doi:10.1016/j.comnet.2018.01.016 fatcat:xqjwzzeww5c3bhyv3yrpuhsgye

D4.1 METRO-HAUL Control and Management Requirements and Framework

Ramon Casellas, Ricardo Martínez, Ricard Vilalta, Raül Muñoz, Michela Svaluto, Luis Velasco, Gabriel Junyent, Jaume Comellas, Marc Ruiz, Francisco Javier Moreno Muro, Miquel Garrich, Pablo Pavón (+18 others)
2018 Zenodo  
The COM is based on Software Defined Networking principles, with a centralized network control plane. This control plane is hierarchical, with an SDN control per technology domain.  ...  for the instantiation of NFV-based Network Services, understood in this context as interconnected Virtual Network Functions.  ...  Predictions are carried out by suitable algorithms based on machine learning.  ... 
doi:10.5281/zenodo.2586712 fatcat:db2lgebgy5c2tn3i3stsgvqzqu

A taxonomy and survey on Green Data Center Networks

Kashif Bilal, Saif Ur Rehman Malik, Osman Khalid, Abdul Hameed, Enrique Alvarez, Vidura Wijaysekara, Rizwana Irfan, Sarjan Shrestha, Debjyoti Dwivedy, Mazhar Ali, Usman Shahid Khan, Assad Abbas (+2 others)
2014 Future generations computer systems  
h i g h l i g h t s • We provide an overview of the research within Data Center Networks (DCNs). • We present the state-of-the-art energy efficiency techniques for a DCN. • The survey elaborates on the  ...  DCN architectures (electrical, optical, and hybrid). • We also focus on traffic management, characterization, and performance monitoring. • We present a comparative analysis of the aforementioned within  ...  The first packet of a flow (e.g., the SYN packet of a TCP flow) adaptively constructs the path towards the destination based on the queue-lengths of output ports.  ... 
doi:10.1016/j.future.2013.07.006 fatcat:f6btn5gljjetzphyg7w6lqa6jy

Comprehensive Survey of Evolutionary Morphological Soft Robotic Systems [article]

Reem J. Alattas, Sarosh Patel, Tarek M. Sobh
2017 arXiv   pre-print
This paper reviews the literature and discusses various aspects of evolutionary robotics including the application on morphological soft robots to allow self assembly, self reconfiguration, self repair  ...  Soft robotics have demonstrated the feasibility of evolutionary robotics for the synthesis of robots control and morphology.  ...  However, mainstream robots use machine learning to produce adaptive behaviour to simulate biological aspects, while neglecting the autonomous side of it.  ... 
arXiv:1702.02934v5 fatcat:6kfowwun55borprcdasfcidpdy

Frontiers of research and future directions in information and communication technology

Angel G. Jordan
2008 Technology in society  
Information and communication technology (ICT), characterized by continual innovation and rapid technological change, is having a tremendous impact on society.  ...  This paper deals with frontiers of research and trends in selected areas of ICT, including computer hardware, microelectronics, and semiconductor devices and materials-areas that are leading the innovations  ...  Other areas include: on-line learning, with connections between problems in machine learning, on-line algorithms, and optimization; astrostatistics, where the explosion of sky survey data has made non-parametric  ... 
doi:10.1016/j.techsoc.2008.05.002 fatcat:lmemejqecrfuhc7sxpex37eyoe

Smart Quantum Technologies using Photons [article]

Narayan Bhusal
2021 arXiv   pre-print
Similarly, in Chapter 2, I review the fundamental concepts of quantum optics and machine learning.  ...  In Chapter 1, I present a historical account of photon-based technologies.  ...  This is based on a convolutional neural network followed by a gradient descent optimizer [143, 83] .  ... 
arXiv:2103.07081v3 fatcat:73mx7nh6mza5zhk76iqw7c63tq

2022 Roadmap on Neuromorphic Computing and Engineering [article]

Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco, Abu Sebastian, Manuel Le Gallo, Andrea Redaelli, Stefan Slesazeck, Thomas Mikolajick, Sabina Spiga, Stephan Menzel, Ilia Valov, Gianluca Milano (+47 others)
2022 arXiv   pre-print
Modern computation based on the von Neumann architecture is today a mature cutting-edge science.  ...  Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically  ...  Acknowledgements Roadmap on Neuromorphic Computing and Engineering This work was partially based on results obtained from a project, JPNP16007, commissioned by the New Energy and Industrial Technology  ... 
arXiv:2105.05956v3 fatcat:pqir5infojfpvdzdwgmwdhsdi4

Eurolab-4-HPC Long-Term Vision on High-Performance Computing [article]

Theo Ungerer, Paul Carpenter
2018 arXiv   pre-print
This document presents the "EuroLab-4-HPC Long-Term Vision on High-Performance Computing" of August 2017, a road mapping effort within the EC CSA1 Eurolab-4-HPC that targets potential changes in hardware  ...  The proposal on research topics is derived from the report and discussions within the road mapping expert group.  ...  Deep learning is a machine learning technique inspired by the neural learning process of the human brain.  ... 
arXiv:1807.04521v1 fatcat:5neetrgubjhnvcajcktpkohrzq

Internet of Things 2.0: Concepts, Applications, and Future Directions

Ian Zhou, Imran Makhdoom, Negin Shariati, Muhammad Ahmad Raza, Rasool Keshavarz, Justin Lipman, Mehran Abolhasan, Abbas Jamalipour
2021 IEEE Access  
SONs provide machine learning-driven self-configuration, self-optimization, and self-healing functionalities [111] .  ...  TABLE 3 . 3 Machine Learning applications in self-optimization. [115] Applications Description Machine Learning Algorithm Backhaul Connection between user, base station and the core network.  ... 
doi:10.1109/access.2021.3078549 fatcat:g5jkc5p6tngpfonbhtsbcjipai
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