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Location-Verification and Network Planning via Machine Learning Approaches
[article]
2019
arXiv
pre-print
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In-region location verification (IRLV) in wireless networks is the problem of deciding if user equipment (UE) is transmitting from inside or outside a specific physical region (e.g., a safe room). ...
We propose a solution based on machine learning (ML) implemented by a neural network (NN) trained with the channel features (in particular, noisy attenuation values) collected by the APs for various positions ...
We propose a machine learning (ML) approach where i) channel measurements are collected by trusted nodes both inside and outside the region of interest (ROI), ii) a machine is trained to take decisions ...
arXiv:1811.06729v2
fatcat:ibmgqjjagjd5bd5pmt3ygleaxi
Artificial intelligence in image-guided radiotherapy: a review of treatment target localization
2021
Quantitative Imaging in Medicine and Surgery
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Modern conformal beam delivery techniques require image-guidance to ensure the prescribed dose to be delivered as planned. ...
The benefits, limitations and some important trends in research and development of the AI-based IGRT techniques are also discussed. ...
Different from the classical machine learning algorithms, deep learning-based approaches are considered as "blackboxes" and lack good interpretability. ...
doi:10.21037/qims-21-199
pmid:34888196
pmcid:PMC8611462
fatcat:kk4mvoxmjbf3bfo4t3tlqh4gw4
Machine Learning and Model Checking Join Forces (Dagstuhl Seminar 18121)
2018
Dagstuhl Reports
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This report documents the program and the outcomes of Dagstuhl Seminar 18121 "Machine Learning and Model Checking Join Forces". ...
This Dagstuhl Seminar brought together researchers working in the fields of machine learning and model checking. ...
Extremal-probability states, end components, and essential states are all special cases of the equivalence relation induced by the NWR. ...
doi:10.4230/dagrep.8.3.74
dblp:journals/dagstuhl-reports/JansenKKK18
fatcat:225qaztsujhgxpclahyf4wm7qe
Kinship Verification using Color Features and Extreme Learning Machine
2018
2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP)
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To mitigate this problem, we propose a new approach to kinship verification based on color features and extreme learning machines (ELM). ...
The proposed methods so far are not robust enough to predict the kin between persons via facial appearance only. ...
ACKNOWLEDGMENT This work was partially funded by China Scholarship Council and Academy of Finland. ...
doi:10.1109/siprocess.2018.8600423
fatcat:43kzcljehzcl7dnmmempbgasa4
IEEE Access Special Section Editorial: Real-Time Machine Learning Applications in Mobile Robotics
2021
IEEE Access
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The gesture recognition is done via a leap motion device and two separate machine learning architectures to evaluate kinematic hand data on the fly. ...
, USA, which is one of the pioneer players in robust planning and learning under uncertainty with an emphasis on the multiagent system. ...
doi:10.1109/access.2021.3090135
fatcat:5ukmcr2sqnbpvni2fkmnscslz4
Contents
[chapter]
2021
Digital Health
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142
9.4.1 From classical feature extraction to
automatic feature learning
142
9.4.2 Feature learning via convolutional
neural networks
142
9.4.3 Learning temporal representations
via long short-term ...
and random forests
138
9.2.2 Support vector machines
139
9.2.3 Neural networks
140
9.3 Machine learning pipeline for wearable
sensor data analysis
140
9.4 Deep learning on wearable sensor data ...
doi:10.1016/b978-0-12-818914-6.00031-4
fatcat:lul57btdr5ertbqcj2a5x6tgme
ActivFORMS: active formal models for self-adaptation
2014
Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems - SEAMS 2014
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A common approach to realize self-adaptation is with a MAPE-K feedback loop that consists of four adaptation components: Monitor, Analyze, Plan, and Execute. ...
., does the execute component execute the plan correctly?). ...
The monitor, analyze, plan, and execute automata can interact directly via channels, or indirectly via reading and writing data in the knowledge. ...
doi:10.1145/2593929.2593944
dblp:conf/icse/IftikharW14a
fatcat:3qntqhimybgt7pouo2wswiffti
A two-step machine learning approach to statistical post-processing of weather forecasts for power generation
[article]
2022
arXiv
pre-print
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We propose a general two-step machine learning-based approach to calibrating ensemble weather forecasts, where in the first step improved point forecasts are generated, which are then together with various ...
However, both wind and photovoltaic energy sources are highly volatile making planning difficult for grid operators, so accurate forecasts of the corresponding weather variables are essential for reliable ...
The authors thank Gabriella Szépszó and Mihály Szűcs from the HMS for providing the AROME-EPS data. ...
arXiv:2207.07589v1
fatcat:m62aj5uk2nbtlbupkg2dqbttg4
Machine Learning and Location Verification in Vehicular Networks
[article]
2019
arXiv
pre-print
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Location information will play a very important role in emerging wireless networks such as Intelligent Transportation Systems, 5G, and the Internet of Things. ...
In recent years, a number of information-theoretic Location Verification Systems (LVSs) have been formulated in attempts to optimally verify the location information supplied by network users. ...
The authors acknowledge support by the University of New South Wales, Australia, and Macquarie University, Australia. ...
arXiv:1904.05610v2
fatcat:sip657pl4javlfliup4ix6ib2m
Editorial Special Issue on AI Innovations in Intelligent Transportation Systems
2022
IEEE transactions on intelligent transportation systems (Print)
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In [A25] , Chandra et al. present an approach that leverages machine learning to predict, the behaviors of human drivers. ...
In [A15] , Wu et al. presented a novel augmented machine learning approach to improve the prediction accuracy of multiscenario real-time train delays, including regular and irregular train delays. ...
doi:10.1109/tits.2022.3152067
fatcat:w5qyxfyp7zfzjckdkhsmddvzwm
Planning and Decision-Making for Autonomous Vehicles
2018
Annual Review of Control Robotics and Autonomous Systems
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In this survey, we emphasize recent approaches for integrated perception and planning and for behavior-aware planning, many of which rely on machine learning. ...
Furthermore, new paradigms, such as interactive planning and end-to-end learning, open up questions regarding safety and reliability that need to be addressed. ...
MOTION PLANNING AND CONTROL We first review traditional methods for vehicle control and motion planning in intelligent vehicles. ...
doi:10.1146/annurev-control-060117-105157
fatcat:hgrhw76idbbdrct742bbhnsqem
Wireless Personal Communications: Machine Learning for Big Data Processing in Mobile Internet
2018
Wireless personal communications
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The seventh paper, entitled ''Machine Learning Based Resource Utilization and Preestimation for Network on Chip (NoC) Communication'' by Adesh Kumar et al., presents the use of machine learning techniques ...
To solve the optimization problem, the authors employ machine learning based methods to locate the possibly global optimal solution. ...
doi:10.1007/s11277-018-5916-x
fatcat:r6ik6co7pjabhoc5jczn3ecy6e
Mapping New Informal Settlements using Machine Learning and Time Series Satellite Images: An Application in the Venezuelan Migration Crisis
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:2008.13583v2 fatcat:7vnoaedhc5ed3fzxfyepuar534Other Versions
To address this problem, we propose a novel approach for rapidly and cost-effectively locating new and emerging informal settlements using machine learning and publicly accessible Sentinel-2 time-series ...
Finally, we emphasize the importance of post-classification verification and present a two-step validation approach consisting of (1) remote validation using Google Earth and (2) on-the-ground validation ...
natural materials); a disorganized and unstructured layout; and a lack of a nearby structured road network, signifying the absence of proper urban planning. ...
arXiv:2008.13583v3
fatcat:peguy4wapzd7rbp5kczf7mkura
2021 Index IEEE Transactions on Automation Science and Engineering Vol. 18
2021
IEEE Transactions on Automation Science and Engineering
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The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. ...
., +, TASE April 2021 405-413 Energy Efficiency Modeling for Configuration-Dependent Machining via Machine Learning: A Comparative Study. ...
doi:10.1109/tase.2021.3120615
fatcat:ybfn4kfdvjfipbty7z3mocjjci
A Systematic Measurement of Street Quality through Multi-Sourced Urban Data: A Human-Oriented Analysis
2019
International Journal of Environmental Research and Public Health
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images extraction with supervised machine learning, and accessibility metrics using network science. ...
They are combined as a collection of new urban data and research techniques, including location-based service (LBS) positioning data, points of interest (PoIs), elements and visual quality of street-view ...
We also thank Ziyi Tang and Erjie Hu for assistance in data preparation and siddharth khakhar for language improvement to the manuscript. ...
doi:10.3390/ijerph16101782
pmid:31137538
pmcid:PMC6571925
fatcat:k2hblvao65dxlh2becj3bqr3fe
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