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arXiv 2024年

作者： Nauman, Ali Maashi, Mashael Alkahtani, Hend K. Al-Wesabi, Fahd N. Aljehane, Nojood O. Assiri, Mohammed Ibrahim, Sara Saadeldeen Khan, Wali Ullah The Department of Information and Communication Engineering Yeungnam University Korea Republic of The Department of Software Engineering College of Computer and Information Sciences King Saud University Po box 103786 Riyadh11543 Saudi Arabia The Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia The Department of Computer Science College of Science & Art at Mahayil King Khalid University Saudi Arabia The Department of Computer Science Faculty of Computers and Information Technology University of Tabuk Tabuk Saudi Arabia The Department of Computer Science College of Sciences and Humanities- Aflaj Prince Sattam bin Abdulaziz University Aflaj 16273 Saudi Arabia The Department of Computer and Self Development Preparatory Year Deanship Prince Sattam bin Abdulaziz University Al-Kharj Saudi Arabia University of Luxembourg Luxembourg

The increasing demand for massive connectivity and high data rates has made the efficient use of existing spectrum resources an increasingly challenging problem. Non-orthogonal multiple access (NOMA) is a potential solution for future heterogeneous networks (HetNets) due to its high capacity and spectrum efficiency. In this study, we analyze an uplink NOMA-enabled vehicular-aided HetNet, where multiple vehicular user equipment (VUEs) share the access link spectrum, and a high-altitude platform (HAP) communicates with roadside units (RSUs) through a backhaul communication link. We propose an improved algorithm for user association that selects VUEs for HAPs based on channel coefficient ratios and terrestrial VUEs based on a caching-state backhaul communication link. The joint optimization problems aim to maximize a utility function that considers VUE transmission rates and cross-tier interference while meeting the constraints of backhaul transmission rates and QoS requirements of each VUE. The joint resource allocation optimization problem consists of three sub-problems: bandwidth allocation, user association, and transmission power allocation. We derive a closed-form solution for bandwidth allocation and solve the transmission power allocation sub-problem iteratively using Taylor expansion to transform a non-convex term into a convex one. Our proposed three-stage iterative algorithm for resource allocation integrates all three sub-problems and is shown to be effective through simulation results. Specifically, the results demonstrate that our solution achieves performance improvements over existing approaches. Copyright © 2024, The Authors. All rights reserved.

关键词： Heterogeneous networks

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A Brief Review of Explainable Artificial Intelligence in Healthcare

arXiv

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arXiv 2023年

作者： Sadeghi, Zahra Alizadehsani, Roohallah Cifci, Mehmet Akif Kausar, Samina Rehman, Rizwan Mahanta, Priyakshi Bora, Pranjal Kumar Almasri, Ammar Alkhawaldeh, Rami S. Hussain, Sadiq Alatas, Bilal Shoeibi, Afshin Moosaei, Hossein Hladík, Milan Nahavandi, Saeid Pardalos, Panos M. Institute for Big Data Analytics Faculty of Computer Science Dalhousie University Canada Deakin University Geelong Australia The Institute of Computer Technology Tu Wien University Vienna1040 Austria University of Kotli Azad Jammu and Kashmir Azad Kashmir Kotli Pakistan Centre for Computer Science and Applications Dibrugarh University Assam India Department of Management Information Sys Al-Balqa Applied University Salt19117 Jordan Department of Computer Information Systems The University of Jordan Aqaba77110 Jordan Examination Branch Dibrugarh University Assam Dibrugarh India Department of Software Eng. Firat University Elazig23100 Turkey Data Science and Computational Intelligence Institute University of Granada Spain Department of Informatics Faculty of Science Jan Evangelista Purkyně University in Ústí nad Labem Czech Republic Department of Applied Mathematics School of Computer Science Faculty of Mathematics and Physics Charles University Prague Czech Republic Harvard Paulson School of Engineering and Applied Sciences Harvard University AllstonMA02134 United States Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida Gainesville32611 United States

XAI refers to the techniques and methods for building AI applications which assist end users to interpret output and predictions of AI models. Black box AI applications in high-stakes decision-making situations, such as medical domain have increased the demand for transparency and explainability since wrong predictions may have severe consequences. Model explainability and interpretability are vital successful deployment of AI models in healthcare practices. AI applications' underlying reasoning needs to be transparent to clinicians in order to gain their trust. This paper presents a systematic review of XAI aspects and challenges in the healthcare domain. The primary goals of this study are to review various XAI methods, their challenges, and related machine learning models in healthcare. The methods are discussed under six categories: Features-oriented methods, global methods, concept models, surrogate models, local pixel-based methods, and human-centric methods. Most importantly, the paper explores XAI role in healthcare problems to clarify its necessity in safety-critical applications. The paper intends to establish a comprehensive understanding of XAI-related applications in the healthcare field by reviewing the related experimental results. To facilitate future research for filling research gaps, the importance of XAI models from different viewpoints and their limitations are investigated. © 2023, CC BY-NC-ND.

关键词： Decision making

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Diff-Reg: Diffusion Model in Doubly Stochastic Matrix Space for Registration Problem

arXiv

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arXiv 2024年

作者： Wu, Qianliang Jiang, Haobo Luo, Lei Li, Jun Ding, Yaqing Xie, Jin Yang, Jian PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China School of Intelligence Science and Technology Nanjing University Suzhou China Visual Recognition Group Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic National University of Singapore Singapore

Establishing reliable correspondences is essential for 3D and 2D-3D registration tasks. Existing methods commonly leverage geometric or semantic point features to generate potential correspondences. However, these features may face challenges such as large deformation, scale inconsistency, and ambiguous matching problems (e.g., symmetry). Additionally, many previous methods, which rely on single-pass prediction, may struggle with local minima in complex scenarios. To mitigate these challenges, we introduce a diffusion matching model for robust correspondence construction. Our approach treats correspondence estimation as a denoising diffusion process within the doubly stochastic matrix space, which gradually denoises (refines) a doubly stochastic matching matrix to the ground-truth one for high-quality correspondence estimation. It involves a forward diffusion process that gradually introduces Gaussian noise into the ground truth matching matrix and a reverse denoising process that iteratively refines the noisy one. In particular, we deploy a lightweight denoising strategy during the inference phase. Specifically, once points/image features are extracted and fixed, we utilize them to conduct multiple-pass denoising predictions in the reverse sampling process. Evaluation of our method on both 3D and 2D-3D registration tasks confirms its effectiveness. The code is available at https://***/wuqianliang/Diff-Reg. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Educational use of a microwave electromagnetic analysis of 3-D planar structures

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computer Applications in engineering Education 1993年第3期1卷 243-243页

作者： Rautio, J.C. Sonnet Software Inc. Suite 203 135 Old Cove Road Liverpool NY 13090 Dr. James C. Rautio:founded Sonnet Software a developer of 3-D planar electromagnetic microwave software in 1983 with support from the David Sarnoff Research Center Hewlett Packard General Electric and Syracuse University. He has served as a visiting member of the faculty at Syracuse University and as an adjunct faculty member at Cornell University teaching microwave and computer courses as well as pursuing research in electromagnetics. Dr. Rautio previously worked in General Electric's Space Division and Electronics Laboratory. He designed microwave circuits including filters for a Landsat receiver and various GaAs microwave integrated circuits. He also developed microwave and millimeter wave automated measurement equipment and wrote a large microwave circuit analysis program. Dr. Rautio holds a BS in Electrical Engineering from Cornell University an MS in Systems Engineering from the University of Pennsylvania and a PhD in Electrical Engineering from Syracuse University

The use of an electromagnetic analysis of 3-D planar structures is described with respect to the educational requirements of students from the college freshman level through the graduate level. The analysis is intended primarily for microwave use; however, there is also significant potential interest from the student of high speed digital design. The analysis is used for passive planar circuits with any number of layers. The third dimension is represented by vias. A mature graphical user interface is provided allowing rapid capture of structure geometry, color visualization, and animation of the resulting current distributions. The software is also explicitly designed to work in conjunction with popular circuit theory based microwave software and with SPICE.

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A Preliminary Study of Optimizing Back Pain Medicinal Cupping Points Disease via Graph Colouring

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Journal of Physics: Conference Series 2019年第1期1366卷

作者： Nurfatihah Mohamad Hanafi Yuhani Yusof Mohd Sham Mohamad Muhamad Faiz Abu Bakar Mohd Adhha Ibrahim Centre for Mathematical Sciences Universiti Malaysia Pahang 26300 Pahang Faculty of Computer Systems & Software Engineering Universiti Malaysia Pahang 26300 Pahang Pusat Bekam Al-Yakin Kuantan Pahang

Medical cupping is an ancient method that is still used by many people. It is an alternative method in healing process for much type of diseases by using special cups on the specific points of the skin to create suction. Every disease has their specific cupping points. As a habit, practitioners will cup based on patient request or complaint, where it give effect to the cost and time. Thus, the aim of this paper is to study the effective ways on finding the optimum number of cupping points for back pain disease through graph colouring. In addition, a formulation in C# language is given too in validating the graph model result. The finding shows that the optimum number of back pain medicinal cupping points is two.

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

arXiv

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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

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A Brief Review of Explainable Artificial Intelligence in Healthcare

SSRN

引用

SSRN 2023年

作者： Sadeghi, Zahra Alizadehsani, Roohallah Cifci, Mehmet Akif Kausar, Samina Rehman, Rizwan Mahanta, Priyakshi Bora, Pranjal Kumar Almasri, Ammar Alkhawaldeh, Rami S. Hussain, Sadiq Alatas, Bilal Shoeibi, Afshin Moosaei, Hossein Hladík, Milan Nahavandi, Saeid Pardalo, Panos M. Institute for Big Data Analytics Faculty of Computer Science Dalhousie University Canada Deakin University Geelong Australia The Institute of Computer Technology Tu Wien University Vienna1040 Austria University of Kotli Azad Jammu and Kashmir Azad Kashmir Kotli Pakistan Centre for Computer Science and Applications Dibrugarh University Assam India Department of Management Information Sys Al-Balqa Applied University Salt19117 Jordan Department of Computer Information Systems The University of Jordan Aqaba77110 Jordan Examination Branch Dibrugarh University Assam Dibrugarh India Department of Software Eng. Firat University Elazig23100 Turkey Data Science and Computational Intelligence Institute University of Granada Spain Department of Informatics Faculty of Science Jan Evangelista Purkyně University in Ústí nad Labem Czech Republic Department of Applied Mathematics School of Computer Science Faculty of Mathematics and Physics Charles University Prague Czech Republic Harvard Paulson School of Engineering and Applied Sciences Harvard University AllstonMA02134 United States Swinburne University of Technology HawthornVIC3122 Australia Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida Gainesville32611 United States

关键词： Decision making

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Corrigendum to “Identification of significant features and data mining techniques in predicting heart disease” [Telematics Informatics 36 (2019) 82–93]

引用

Telematics and Informatics 2022年 70卷

作者： Mohammad Shafenoor Amin Yin Kia Chiam Kasturi Dewi Varathan Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya 50603 Kuala Lumpur Malaysia BRAC University 66 Mohakhali Dhaka 1212 Bangladesh Department of Information Systems Faculty of Computer Science and Information Technology University of Malaya 50603 Kuala Lumpur Malaysia

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Quantum-optimal Frequency Estimation of Stochastic AC Fields

arXiv

引用

arXiv 2024年

作者： Dey, Anirban Mouradian, Sara Lupo, Cosmo Huang, Zixin School of Mathematical and Physical Sciences Macquarie University NSW2109 Australia ARC Centre of Excellence for Engineered Quantum Systems Macquarie University NSW2109 Australia Department of Electrical and Computer Engineering University of Washington 98195 United States Dipartimento Interateneo di Fisica Politecnico di Bari Bari70126 Italy Dipartimento Interateneo di Fisica Università di Bari Bari70126 Italy INFN Sezione di Bari Bari70126 Italy Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia

Classically, measurement bandwidth limits the achievable frequency resolution of stochastic time-dependent fields. We frame the problem of frequency measurement as the estimation of the noise parameter of a dephasing quantum channel. Using this framework, we find an exact upper bound for estimating frequency centroids and separations. In particular, given two closely separated frequencies with separation ωr, the quantum Fisher information (QFI) upper bound is approximately 2/ωr2, inversely proportional to the separation parameter. We show that this is achievable with a superposition of Dicke states, and show that GHZ states improve precision over unentangled states, achieving Heisenberg scaling in the low-bandwidth limit. This work established a robust framework for stochastic AC signal sensing and can be extended to an arbitrary number of frequencies. Copyright © 2024, The Authors. All rights reserved.

关键词： Bandwidth

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Short-time simulation of quantum dynamics by Pauli measurements

arXiv

引用

arXiv 2024年

作者： Faehrmann, Paul K. Eisert, Jens Kieferová, Mária Kueng, Richard Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute for Integrated Circuits and Quantum Computing Johannes Kepler University Linz Austria Helmholtz-Zentrum Berlin für Materialien und Energie Hahn-Meitner-Platz 1 Berlin14109 Germany Fraunhofer Heinrich Hertz Institute Berlin10587 Germany Centre for Quantum Software and Information School of Computer Science Faculty of Engineering & Information Technology University of Technology SydneyNSW2007 Australia

Simulating the dynamics of complex quantum systems is a central application of quantum devices. Here, we propose leveraging the power of measurements to simulate short-time quantum dynamics of physically prepared quantum states in classical post-processing using a truncated Taylor series approach. While limited to short simulation times, our hybrid quantum-classical method is equipped with rigorous error bounds. It is extendable to estimate low-order Taylor approximations of smooth, time-dependent functions of tractable linear combinations of measurable operators. These insights can be made use of in the context of Hamiltonian learning and device verification, short-time imaginary time evolution, or the application of intractable operations to sub-universal quantum simulators in classical post-processing. © 2024, CC BY.

关键词： Hamiltonians

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