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Deep Learning ResNet101 Deep Features of Portable Chest X-Ray Accurately Classify COVID-19 Lung Infection

computers, Materials & Continua 2023年第6期75卷 5213-5228页

作者： Sobia Nawaz Sidra Rasheed Wania Sami Lal Hussain Amjad Aldweesh Elsayed Tag eldin Umair Ahmad Salaria Mohammad Shahbaz Khan Basic Health Unit Sumra Lodhran59320Pakistan Basic Health Unit 20-G ChishtianBahawalnagar62300Pakistan Doctor’s Hospital Lahore54590Pakistan Department of Computer Science&IT Neelum CampusThe University of Azad Jammu and KashmirAthmuqam13230Azad KashmirPakistan Department of Computer Science&IT King Abdullah CampusThe University of Azad Jammu and KashmirMuzaffarabad13100Azad KashmirPakistan College of Computer science and information technology Shaqra UniversityShaqra15273Saudi Arabia Faculty of Engineering and Technology Future University in EgyptNew Cairo11835Egypt Department of Electrical Engineering University of Azad Jammu and KashmirChehla CampusMuzaffarabad13100Azad KashmirPakistan Department of Electrical Engineering Mirpur University of Science&TechnologyMirpurMuzaffarabad10250Azad KashmirPakistan Children’s National Hospital 111 Michigan AVE NWWashingtonDC20854USA

This study is designed to develop Artificial Intelligence(AI)based analysis tool that could accurately detect COVID-19 lung infections based on portable chest x-rays(CXRs).The frontline physicians and radiologists suffer from grand challenges for COVID-19 pandemic due to the suboptimal image quality and the large volume of *** this study,AI-based analysis tools were developed that can precisely classify COVID-19 lung *** available datasets of COVID-19(N=1525),non-COVID-19 normal(N=1525),viral pneumonia(N=1342)and bacterial pneumonia(N=2521)from the Italian Society of Medical and Interventional Radiology(SIRM),Radiopaedia,The Cancer Imaging Archive(TCIA)and Kaggle repositories were taken.A multi-approach utilizing deep learning ResNet101 with and without hyperparameters optimization was ***,the fea-tures extracted from the average pooling layer of ResNet101 were used as input to machine learning(ML)algorithms,which twice trained the learning *** ResNet101 with optimized parameters yielded improved performance to default *** extracted features from ResNet101 are fed to the k-nearest neighbor(KNN)and support vector machine(SVM)yielded the highest 3-class classification performance of 99.86%and 99.46%,*** results indicate that the proposed approach can be bet-ter utilized for improving the accuracy and diagnostic efficiency of *** proposed deep learning model has the potential to improve further the efficiency of the healthcare systems for proper diagnosis and prognosis of COVID-19 lung infection.

关键词： COVID-19 deep learning(DL) lung infection convolutional neural network(CNN)

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Deep Learning for Smart Grid Application: Addressing Data Scarcity Challenges and Enhancing Load Forecasting Efficiency

Deep Learning for Smart Grid Application: Addressing Data Sc...

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International Conference on Artificial Intelligence and Its Practical Applications in the Age of Digital Transformation, I2COMSAPP 2024

作者： Amalou, Ibtissam Mouhni, Naoual Abdali, Abdelmounim Jakimi, Abdeslam Tourad, Mohamedou Cheikh CISIEV FSTG University Cadi Ayyad Marrakech Morocco LAMIGEP EMSI Marrakech Marrakech Morocco GL-ISI Team Faculty of Science and Technology Errachidia Moulay Ismail University Meknes Morocco Scientific Computing Computer Science and Data Science Research Unit University of Nouakchott Nouakchott Mauritania

ISBN: (纸本)9783031714252

The surge in domestic electricity consumption necessitates innovative solutions for the integration of smart grids. Traditional automation methods prove insufficient for handling unforeseen challenges and sustainability issues, especially with the increasing adoption of renewable energy sources. This paper reviews the application of deep learning (DL) methods to smart grids. The research explores various DL approaches employed in smart grid data collection, such as generative adversarial networks, convolutional neural networks (CNNs), auto-encoders, restricted Boltzmann machines, and multilayer perceptron models. These techniques aim to refine features, detect electricity theft, and identify patterns related to false data injection attacks and energy consumption. Data scarcity emerges as a critical challenge impacting smart grid data management, affecting forecasting accuracy, operational insights, efficiency, and innovation. The study advocates for investments in advanced data collection technologies and taking advantage of machine learning techniques to optimize the use of available data. To demonstrate the impact of data scarcity on DL model efficiency, a Machine learning benchmark models are trained for energy consumption forecasting. Results reveal the significance of training models with sufficient data reaching a minimization of 3.1149 for validation mean squared error of one of the models (CNN_LSTM) by increasing the use of training data to 75% of the Individual household electric power consumption dataset, emphasizing the need to address data scarcity challenges for effective model training. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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Robust graph‐based localization for industrial Internet of things in the presence of flipping ambiguities

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CAAI Transactions on Intelligence technology 2023年第4期8卷 1140-1149页

作者： Mian Imtiaz ul Haq Ruhul Amin Khalil Muhannad Almutiry Ahmad Sawalmeh Tanveer Ahmad Nasir Saeed Faculty of Electrical Engineering Swedish College of Engineering and TechnologyWah CanttPakistan Department of Electrical Engineering Faculty of Electrical and Computer EngineeringUniversity of Engineering and TechnologyPeshawarPakistan Department of Electrical Engineering Remote Sensing UnitNorthern Border UniversityArarSaudi Arabia Data Science and Artificial Intelligence Department‐College of Science and Information Technology Irbid National UniversityIrbadJordan Innovation Education and Research Center for On‐Device AI Software(Bk21) Department of Computer Science and EngineeringChungnam National UniversityDaejeonRepublic of Korea Department of Electrical and Communication Engineering United Arab Emirates University(UAEU)Al AinUnited Arab Emirates

Localisation of machines in harsh Industrial Internet of Things(IIoT)environment is necessary for various ***,a novel localisation algorithm is proposed for noisy range measurements in IIoT *** position of an unknown machine device in the network is estimated using the relative distances between blind machines(BMs)and anchor machines(AMs).Moreover,a more practical and challenging scenario with the erroneous position of AM is considered,which brings additional uncertainty to the final position ***,the AMs selection algorithm for the localisation of BMs in the IIoT network is *** those AMs will participate in the localisation process,which increases the accuracy of the final location ***,the closed‐form expression of the proposed greedy successive anchorization process is derived,which prevents possible local convergence,reduces computation,and achieves Cramér‐Rao lower bound accuracy for white Gaussian measurement *** results are compared with the state‐of‐the‐art and verified through numerous simulations.

关键词： Cramér‐Rao lower bound greedy successive anchorization industrial internet of things localization

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Non-Consensus Opinion Model with Byzantine Nodes 12

Non-Consensus Opinion Model with Byzantine Nodes

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12th International Workshop on Resilient Networks Design and Modeling, RNDM 2022

作者： Liu, Xinhan Achterberg, Massimo A. Kooij, Robert E. Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft Netherlands Unit Ict Tno Netherlands

ISBN: (数字)9781665486774

ISBN: (纸本)9781665486774

pinion dynamics models study how the interaction among people influences the opinion formation process. In most opinion dynamics models, only one opinion can exist in the steady state, which is different from the real-life opinion formation process. In 2009, Shao et at. introduced a Non-Consensus Opinion (NCO) model, which allows different opinions to coexist in the steady state. This paper extends the NCO model by introducing a special type of nodes, namely Byzantine nodes, to play the role of dishonest people. We perform simulations on three different network models: small-scale graphs, Erdős-Rényi random graphs and scale-free networks. We find a new steady state for the NCO model: the cyclic steady state. The cyclic behavior of the NCO and Byzantine NCO model is discussed, including a method to generate networks with extremely long cycle lengths. Other properties of the Byzantine NCO model, such as the probability of cyclic behavior and the final opinion distribution, are also studied. We find that the introduction of Byzantine nodes generally steers towards a more balanced steady state and increases the probability of cyclic behavior. The latter is particularly problematic in communication systems, where the large cycle lengths may cause a very slow consensus process and thus stalling future communications. © 2022 IEEE.

关键词： Complex networks

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NeuroMark PET: Replicable positron emission tomography ICA templates for florbetapir and florbetaben radioligands 46

NeuroMark PET: Replicable positron emission tomography ICA t...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Eierud, Cyrus Fu, Zening Petropoulos, Helen Bohsali, Anastasia Iraji, Armin Ganz, Melanie Pernet, Cyril Calhoun, Vince TReNDS Center Georgia State University Georgia Institute of Technology Emory University AtlantaGA United States University of Copenhagen Department of Computer Science Copenhagen Denmark Rigshospitalet Neurobiology Research Unit Copenhagen Denmark

ISBN: (纸本)9798350371499

Positron emission tomography (PET) tracer binding may not be aligned with commonly used parcellations of neocortex [1]. Independent component analysis (ICA) can capture coactivated regions among participants that might serve as robust templates from a data-driven perspective. NeuroMark is a framework combining pre-defined templates with spatially constrained ICA, capturing a wide range of brain markers across imaging modalities [2],[3]. Here, we build NeuroMark PET beta-amyloid templates for the 18F-florbetapir (FBP) and the 18F-florbetaben (FBB) radioligands, aiming to provide reliable spatial priors for future PET studies using ICA. Measuring the spatial similarities using correlation, the templates for the NeuroMark FBP and FBB templates matched strongly (ρ > 0.4) for 18 components. In a final step, the NeuroMark FBP template is applied on both FBB and FBP radioligands, showing that the age correlate profile across the FBB and FBP radioligands are statistically similar (p © 2024 IEEE.

关键词： Positrons

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On the periodic motions of a one-degree-of-freedom oscillator

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SeMA Journal 2024年第3期81卷 479-494页

作者： Kooij, Robert Zegeling, André Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands Unit ICT Strategy and Policy TNO (Netherlands Organisation for Applied Scientific Research) The Hague Netherlands College of Mathematics and Statistics Guangxi Normal University Guilin China

We present a mechanical model for an oscillator with one degree of freedom under the influence of a flowing medium. Under fairly general conditions we show that the ensuing differential equation has at most two limit cycles and we give examples where exactly two limit cycles will occur. The implications of this result are that it is possible for a system of this kind to exhibit galloping even when the so-called Den Hartog criterion of local instability is not satisfied. © 2023, The Author(s).

关键词： 34C15 34C25 34C29 73K70 Galloping Limit cycles Liénard system Wind-induced vibrations

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Guest Editorial Special Issue on Neuromorphic Devices and Circuits for Next-Generation Flexible Electronics in IEEE Journal on Flexible Electronics

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2024年第1期3卷 2-3页

作者： Liu, Fengyuan Goswami, Sreetosh Pan, Lijia Wang, Yanzhi Fondazione Bruno Kessler Microsystems Technology Unit Center for Sensors and Devices Trento38123 Italy Northeastern University Bendable Electronics and Sustainable Technologies Group Electrical and Computer Engineering Department BostonMA02120 United States Indian Institute of Science Centre for Nano Science and Engineering Bengaluru560012 India Nanjing University School of Electronic Engineering Nanjing210023 China Northeastern University Electrical and Computer Engineering Department BostonMA02120 United States

It is fascinating how our body receives an immense amount of sensory information through numerous receptors distributed throughout the body and efficiently integrates it to make decisions for daily activities, while maintaining extremely low energy consumption and cognitive load. This bioinspired sensory information processing paradigm offers unparalleled advantages over traditional von Neumann architectures due to its exceptional energy efficiency, fault tolerance, and adaptability. While previous efforts in this area have mainly focused on the development of biomimetic sensors, it is equally important to create a computing architecture that can process sensory data locally before transmitting it to a higher level. The strategy of offloading computation at the edge can significantly reduce data latency, saving transmission bandwidth and relieving the burden of computation at a higher level, just like the way our peripheral nervous system complements the central nervous system.

关键词： Special issues and sections Neuromorphic engineering Receptor (biochemistry) Flexible electronics

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Infinitely Many Weak Solutions for a Neumann Problem Involving p(·)-Kirchhoff Triharmonic Operator

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International Journal of Applied and Computational Mathematics 2024年第5期10卷 1-17页

作者： Ahmed, Ahmed Elemine Vall, Mohamed Saad Bouh Research Unit Geometry Algebra Analysis and Applications Mathematics and Computer Sciences Department Faculty of Science and Technology University of Nouakchott Nouakchott Mauritania Research Unity: Modelling and Scientific Calculus Department of Mathematics Professional University Institute University of Nouakchott Nouakchott Mauritania

The following problem with Neumann boundary conditions is the subject of our study in this paper (Formula presented.) Where Ω is a bounded domain in RN with smooth boundary ∂Ω, N≥4. Employing a technical approach b... 详细信息

The following problem with Neumann boundary conditions is the subject of our study in this paper (Formula presented.) Where Ω is a bounded domain in R^N with smooth boundary ∂Ω, N≥4. Employing a technical approach based on B. Ricceri’s critical points theorem and the theory of variable exponent Sobolev spaces, we establish conditions that guarantee the existence of a multitude of weak solutions for the problem featuring the p(·)-Kirchhoff triharmonic operator. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2024.

关键词： 35D30 35J20 35J55 35J60 35J65 Generalized Lebesgue-Sobolev spaces Kirchhoff type equation Nonlinear elliptic systems p(·)-triharmonic operator Ricceri’s variational principle Weak solutions to PDEs

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Exploring Children’s Strategies in Response to Robot’s Advice During a Group Task with iCub and Nao 16th

Exploring Children’s Strategies in Response to Robot’s A...

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16th International Conference on Social Robotics, ICSR + AI 2024

作者： Pusceddu, Giulia Sangineto, Mariapia Cocchella, Francesca Bogliolo, Michela Belgiovine, Giulia Lastrico, Linda Casadio, Maura Rea, Francesco Gena, Cristina Sciutti, Alessandra Robotics Brain and Cognitive Science Department Italian Institute of Technology Genoa Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy Department of Computer Science University of Turin Turin Italy Cognitive Architecture for Collaborative Technologies Unit Italian Institute of Technology Genoa Italy Scuola di Robotica Genoa Italy

ISBN: (纸本)9789819635184

This study investigates children’s trust in two humanoid robots, Nao and iCub, through a cooperative game designed to elicit spontaneous behaviors and group dynamics. We investigate whether participants change their choices after hearing advice from a robot, considering rounds where the advice is correct or incorrect, with the robot apologizing for its mistakes. Results reveal that, in most cases, participants prefer not to change their moves after the robot’s advice. Additionally, after the robots made mistakes, participants are less likely to actively follow their advice and more likely to reject it. No significant differences in strategies among the iCub and Nao samples are evidenced. Furthermore, we examine the influence of group dynamics, identifying "Proactive Players" who consistently initiated moves. A significant association between the strategies of this player and their teammates is found, suggesting potential influence. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Decoding the future: exploring and comparing ABE standards for cloud, IoT, blockchain security applications

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Multimedia Tools and Applications 2025年第13期84卷 12299-12327页

作者： Singamaneni, Kranthi Kumar Yadav, Kusum Aledaily, Arwa N. Viriyasitavat, Wattana Dhiman, Gaurav Kaur, Amandeep Department of Computer Engineering and Technology Chaitanya Bharathi Institute of Technology T.S Gandipet Hyderabad500075 India College of Computer Science and Engineering University of Ha’il Hail Saudi Arabia Business Information Technology Division Department of Statistics Faculty of Commerce and Accountancy Chulalongkorn University Bangkok Thailand School of Sciences and Emerging Technologies Jagat Guru Nanak Dev Punjab State Open University Patiala India Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon Chitkara Centre for Research and Development Chitkara University Himachal Pradesh 173212 India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Division of Research and Development Lovely Professional University Phagwara India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India MEU Research Unit Middle East University Amman Jordan

Data security poses a significant challenge in cloud computing, the Internet of Things (IoT), and blockchain applications. Attribute-Based Encryption (ABE) has emerged as a promising cryptographic solution for secure data sharing and access management in these contexts. This research article focuses on enhancing security in cloud, IoT, and blockchain applications through a comprehensive examination and comparison of various ABE standards. The study begins with an in-depth literature review on ABE requirements, offering insights into the evolving landscape, challenges, and trends. This review serves as the foundation for the research, which aims to compare ABE standards based on cryptographic techniques, encryption/decryption processes, and access control rules, considering criteria like flexibility, efficiency, scalability, and security. Statistical analyses complement the comparative study, generating empirical data on ABE standard performance. Key metrics, including key size, storage overhead, encryption/decryption time, and computational complexity, are considered to identify trends and draw meaningful conclusions. The research also explores use cases for different ABE models within blockchain, IoT, and cloud computing applications, pinpointing scenarios where specific ABE models excel. The study contributes to advancing access control and secure data-sharing technologies in specified domains, aiding researchers, practitioners, and developers in selecting the most appropriate encryption method. By systematically outlining advantages and disadvantages of various Cipher Text ABE standards, the research facilitates informed decision-making. Additionally, practical use cases ensure alignment between ABE models and the distinctive traits and requirements of each domain, expanding the toolset for enhancing data security in blockchain, IoT, and cloud computing applications. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springe

关键词： Internet of things

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