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Ergodic Capacity Analysis of NOMA-Based Two-Way Relaying Systems

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TechRxiv

TechRxiv 2022年

作者： Khan, Wali Ullah Elhalawany, Basem M. da Costa, Daniel B. Ruby, Rukhsana Waqar, Omer Wu, Kaishun Electrical Engineering Department Faculty of Engineering at Shoubra Benha University Egypt AI & Telecom Research Center Technology Innovation Institute Masdar City Abu Dhabi9639 United Arab Emirates Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou64002 Taiwan SnT University of Luxembourg Luxembourg School of Computer Science and Software Engineering Shenzhen University Shenzhen China BC Canada

In this work, a non-orthogonal multiple access (NOMA) relying on a two-way relaying (TWR) approach is investigated to promote more efficient use of the available spectrum. Specifically, a NOMA-enabled half-duplex decode-and-forward relay node is used to simultaneously exchange data between two cellular users and a base station (BS), while assuming that the direct links between the two users and the BS are unavailable or negligible. In our analysis, the ergodic capacity is evaluated, in which high signal-to-noise ratio approximations, as well as upper bounds are derived owing to the intractability related to the exact analysis. The results reveal the superiority of the proposed TWR-NOMA scheme compared with the traditional one-way relaying (OWR-NOMA) scheme. Additionally, simulation results show that selecting a relay station (RS) closer to the BS can achieve a higher ergodic sum capacity for the system than selecting a far RS. © 2022, CC BY.

关键词： Spectrum efficiency

Awareness in robotics: An early perspective from the viewpoint of the EIC Pathfinder Challenge "Awareness Inside"

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arXiv 2024年

作者： Santina, Cosimo Della Corbato, Carlos Hernandez Sisman, Burak Leiva, Luis A. Arapakis, Ioannis Vakalellis, Michalis Vanderdonckt, Jean D’Haro, LuisFernando Manzi, Guido Becchio, Cristina Elamrani, Aïda Alirezaei, Mohsen Castellano, Ginevra Dimarogonas, Dimos V. Ghosh, Arabinda Haesaert, Sofie Soudjani, Sadegh Stroeve, Sybert Verschure, Paul Bacciu, Davide Deroy, Ophelia Bahrami, Bahador Gallicchio, Claudio Hauert, Sabine Sanz, Ricardo Lanillos, Pablo Iacca, Giovanni Sigg, Stephan Gasulla, Manel Steels, Luc Sierra, Carles Department of Cognitive Robotics Delft University of Technology Delft Netherlands Oberpfaffenhofen Germany Department of Computer Science University of Luxembourg Luxembourg 4 Telefónica I+D Spain AEGIS IT Research GmbH Germany Université catholique de Louvain Belgium Speech Technology and Machine Learning Group ETSI de Telecomunicación Universidad Politécnica de Madrid Madrid Spain Alien Venture Studio Alien Technology Transfer Rome Italy Hamburg Germany Institut Jean Nicod École Normale Supérieure Paris France Research Technology and Development Department Digital Industry Software Helmond Netherlands Department of Information Technology Uppsala University Uppsala Sweden Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Max Planck Institute for Software Systems Kaiserslautern Germany Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Amsterdam Netherlands Donders Centre for Neuroscience Radboud University Nijmegen Netherlands Computer Science Department University of Pisa Pisa Italy Faculty of Philosophy Philosophy of Science The Study of Religion Ludwig Maximilian University of Munich Munich Germany School of Engineering Mathematics and Technology University of Bristol Bristol United Kingdom Autonomous Systems Laboratory Universidad Politécnica de Madrid Spain Madrid Spain Department of Information Engineering and Computer Science University of Trento Trento Italy Department of Information and Communications Engineering Aalto University Espoo Finland Department of Electronic Engineering Universitat Politècnica de Catalunya Barcelona Spain Studio Stelluti Brussels Belgium Barcelona Spain

Consciousness has been historically a heavily debated topic in engineering, science, and philosophy. On the contrary, awareness had less success in raising the interest of scholars in the past. However, things are changing as more and more researchers are getting interested in answering questions concerning what awareness is and how it can be artificially generated. The landscape is rapidly evolving, with multiple voices and interpretations of the concept being conceived and techniques being developed. The goal of this paper is to summarize and discuss the ones among these voices that are connected with projects funded by the EIC Pathfinder Challenge called "Awareness Inside", a nonrecurring call for proposals within Horizon Europe that was designed specifically for fostering research on natural and synthetic awareness. In this perspective, we dedicate special attention to challenges and promises of applying synthetic awareness in robotics, as the development of mature techniques in this new field is expected to have a special impact on generating more capable and trustworthy embodied systems. © 2024, CC BY.

关键词： Robotics

Feature selection based on min-redundancy and max-consistency

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Advances in Computational Intelligence 2021年第1期2卷 1-11页

作者： Guo, Yanting Hu, Meng Tsang, Eric C. C. Chen, Degang Xu, Weihua College of Computer Science and Software Engineering Shenzhen University Shenzhen China Faculty of Information Technology Macau University of Science and Technology Taipa China Department of Mathematics and Physics North China Electric Power University Beijing China College of Artificial Intelligence Southwest University Chongqing China

Feature selection can effectively eliminate irrelevant or redundant features without changing features semantics, so as to improve the performance of learning and reduce the training time. In most of the existing feature selection methods based on rough sets, eliminating the redundant features between features and decisions, and deleting the redundant features between features are performed separately. This will greatly increase the search time of feature subset. To quickly remove redundant features, we define a series of feature evaluation functions that consider both the consistency between features and decisions, and redundancy between features, then propose a novel feature selection method based on min-redundancy and max-consistency. Firstly, we define the consistency of features with respect to decisions and the redundancy between features from neighborhood information granules. Then we propose a combined criterion to measure the importance of features and design a feature selection algorithm based on minimal-redundancy-maximal-consistency (mRMC). Finally, on UCI data sets, mRMC is compared with three other popular feature selection algorithms based on neighborhood idea, from classification accuracy, the number of selected features and running time. The experimental comparison shows that mRMC can quickly delete redundant features and select useful features while ensuring classification accuracy.

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Quantum computing for corrosion-resistant materials and anti-corrosive coatings design

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arXiv 2024年

作者： Nguyen, Nam Watts, Thomas W. Link, Benjamin Williams, Kristen S. Sanders, Yuval R. Elman, Samuel J. Kieferova, Maria Bremner, Michael J. Morrell, Kaitlyn J. Elenewski, Justin Isaacs, Eric B. Johnson, Samuel D. Mathieson, Luke Obenland, Kevin M. Otten, Matthew Sundareswara, Rashmi Holmes, Adam Boeing Research & Technology United States HRL Laboratories LLC MalibuCA United States Centre for Quantum Software and Information School of Computer Science Faculty of Engineering & Information Technology University of Technology SydneyNSW2007 Australia Centre for Quantum Computation and Communication Technology University of Technology SydneyNSW2007 Australia MIT Lincoln Laboratory LexingtonMA United States Department of Physics University of Wisconsin - Madison MadisonWI United States

Recent estimates indicate that the U.S. Department of Defense spends over $20 billion USD annually on corrosion-related maintenance. This expenditure is accompanied by a substantial loss in asset readiness, ranging from 10% to 30%. Moreover, the global costs associated with corrosion damage have been estimated at an astonishing $2.5 trillion USD per year, or approximately 3.4% of global GDP in 2016. This project aims to describe how quantum computers might be leveraged to fundamentally change the way material-environment interactions are modeled for material discovery, selection, and design. This project also seeks to understand the plausibility and utility of replacing portions of classical computing workflows with algorithms optimized for quantum computing hardware. The utility of quantum computers is explored through the lens of two industrially relevant problems: (1) characterizing magnesium alloy corrosion properties in aqueous environments and (2) identifying stable niobium-rich alloys with corrosion resistance at temperatures above 1500K. This paper presents an end-to-end analysis of the complexity of both classical and quantum algorithms used in application workflows. Resource estimates are produced using a custom software package, pyLIQTR, based on the qubitized Quantum Phase Estimation (QPE) algorithm. Estimates for the two aforementioned applications show that industrially-relevant computational models that have the potential to deliver commercial utility require quantum computers with thousands to hundreds of thousands of logical qubits and the ability to execute 1013 to 1019 T-gates. These estimates represent an upper bound and motivate continued research into improved quantum algorithms and resource reduction techniques. © 2024, CC BY.

关键词： Corrosion resistance

Corrections to “An Ensemble Hybrid Framework: A Comparative Analysis of Metaheuristic Algorithms for Ensemble Hybrid CNN Features for Plants Disease Classification”

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IEEE Access 2025年 13卷 31659-31659页

作者： Khaoula Taji Ali Sohail Tariq Shahzad Bilal Shoaib Khan Muhammad Adnan Khan Khmaies Ouahada Electronic Systems Information Processing Mechanics and Energy Laboratory Kenitra Faculty of Sciences Ibn Tofail University Kenitra Morocco Department of Computer Science Minhaj University Lahore Lahore Pakistan Department of Electrical and Electronic Engineering Science University of Johannesburg Johannesburg South Africa Department of Computer Science Green International University Lahore Pakistan Department of Software Faculty of Artificial Intelligence and Software Gachon University Seongnam-si Republic of Korea

Presents corrections to the paper, Corrections to “An Ensemble Hybrid Framework: A Comparative Analysis of Metaheuristic Algorithms for Ensemble Hybrid CNN Features for Plants Disease Classification”.

关键词： Plant diseases Metaheuristics

New Moments Based Fuzzy Similarity Measure for Text Detection in Distorted Social Media Images 5th

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New Moments Based Fuzzy Similarity Measure for Text Detectio...

5th Asian Conference on Pattern Recognition, ACPR 2019

作者： Roy, Soumyadip Shivakumara, Palaiahnakote Pal, Umapada Lu, Tong Blumenstein, Michael Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia National Key Lab for Novel Software Technology Nanjing University Nanjing China Faculty of Engineering and Information Technology University of Technology Sydney Australia

ISBN: (纸本)9783030414030

A trend towards capturing or filming images using cellphone and sharing images on social media is a part and parcel of day to day activities of humans. When an image is forwarded several times in social media it may be distorted a lot due to several different devices. This work deals with text detection from such distorted images. In this work, we consider images pass through three mobile devices on WhatsApp social media, which results in four images (including the original image) Unlike the existing methods that aim at developing new ways, we utilize the results detected by the existing ones to improve performances. The proposed method extracts Hu moments and fuzzy logic from detected texts of images. The similarity between text detection results given by three existing text detection methods is studied for determining the best pair of texts. The same similarity estimation is then used in a novel way to remove extra background or non-texts and restoring missing text information. Experimental results on own dataset and benchmark datasets of natural scene images, namely, MSRA-TD500, ICDAR2017-MLT, Total-Text, CTW1500 dataset and COCO datasets, show that the proposed method outperforms the existing methods. © Springer Nature Switzerland AG 2020.

关键词： Fuzzy logic

Augmented shortcuts for vision transformers

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arXiv 2021年

作者： Tang, Yehui Han, Kai Xu, Chang Xiao, An Deng, Yiping Xu, Chao Wang, Yunhe Dept. of Machine Intelligence Peking University Noah's Ark Lab Huawei Technologies Central Software Institution Huawei Technologies School of Computer Science Faculty of Engineering University of Sydney

Transformer models have achieved great progress on computer vision tasks recently. The rapid development of vision transformers is mainly contributed by their high representation ability for extracting informative features from input images. However, the mainstream transformer models are designed with deep architectures, and the feature diversity will be continuously reduced as the depth increases, i.e., feature collapse. In this paper, we theoretically analyze the feature collapse phenomenon and study the relationship between shortcuts and feature diversity in these transformer models. Then, we present an augmented shortcut scheme, which inserts additional paths with learnable parameters in parallel on the original shortcuts. To save the computational costs, we further explore an efficient approach that uses the block-circulant projection to implement augmented shortcuts. Extensive experiments conducted on benchmark datasets demonstrate the effectiveness of the proposed method, which brings about 1% accuracy increase of the state-of-the-art visual transformers without obviously increasing their parameters and FLOPs. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

Local-photon model of the momentum of light

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arXiv 2024年

作者： Waite, Gabriel Hodgson, Daniel Lang, Ben Alapatt, Varghese Beige, Almut The School of Physics and Astronomy University of Leeds LeedsLS2 9JT United Kingdom Centre for Quantum Computation and Communication Technology Australia Centre for Quantum Software and Information School of Computer Science Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia The School of Physics and Astronomy University of Nottingham NottinghamNG7 2RD United Kingdom Universitat de València Paterna Spain

Recently we introduced a local photon approach for modelling the quantised electromagnetic field in position space. Using this approach, we define the momentum of light in this paper as in quantum mechanics as the generator for spatial translation. Afterwards, we analyse the momentum dynamics of photonic wave packets which transition from air into a denser dielectric medium. Our analysis shines new light onto the Abraham-Minkowski controversy which highlights the intricacies involved in the characterisation of the momentum of the electromagnetic field. Although our results align with Minkowski’s theory and with the definition of the canonical momentum of light in quantum electrodynamics, there are also some crucial differences. © 2024, CC BY.

关键词： Momentum

AUTOMATIC GENERATION OF A LARGE DICTIONARY WITH CONCRETENESS/ABSTRACTNESS RATINGS BASED ON A SMALL HUMAN DICTIONARY

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arXiv 2022年

作者： Ivanov, Vladimir Solovyev, Valery Faculty of Computer Science and Software Engineering Innopolis University 1 Universitetskaya st. Republic of Tatarstan Innopolis420500 Russia Linguistic Research and Education Center Research Laboratory 'Intellectual Technologies of Text Management' Kazan Federal University 2 Tatarstan Street Republic of Tatarstan Kazan420021 Russia

Concrete/abstract words are used in a growing number of psychological and neurophysiological research. For a few languages, large dictionaries have been created manually. This is a very time-consuming and costly process. To generate large high-quality dictionaries of concrete/abstract words automatically one needs extrapolating the expert assessments obtained on smaller samples. The research question that arises is how small such samples should be to do a good enough extrapolation. In this paper, we present a method for automatic ranking concreteness of words and propose an approach to significantly decrease amount of expert assessment. The method has been evaluated on a large test set for English. The quality of the constructed dictionaries is comparable to the expert ones. The correlation between predicted and expert ratings is higher comparing to the state-of-the-art methods. © 2022, CC BY-NC-ND.

关键词： Extrapolation