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Emergency events detection based on integration of federated learning and active learning

International Journal of Information Technology (Singapore) 2023年第6期15卷 2863-2876页

作者： Alfalqi, Khalid Bellaiche, Martine Computer and Software Engineering Department Ecole Polytechnique Montreal Canada

Social media networks now make it easy to access, in real-time, massive amounts of information from all over the world. They are often the primary source of information for billions of people. In addition to other uses, social media platforms can be valuable to provide real-time information about emergency events and can help detect emergency situations. This can provide affected individuals with crucial information about imminent dangers, prompting them to take appropriate action and significantly influencing their decisions. The continuous flow of data generated during these emergencies requires efficient training and modeling. Deep learning can simplify this process and make it less reliant on feature extraction strategies. However, implementing deep learning-based solutions can be expensive and time-consuming due to the vast amounts of data involved. To address these limitations, in this paper, we employed and analyzed the effectiveness of utilizing Active Learning techniques along with Federated Learning for emergency events using a dataset garnered from the social media. After collecting images, we used a Federated Learning paradigm to split the data amongst different clients and used vision transformers as local models for each client. Furthermore, we used an ensemble approach to integrate the results from these strengthened local and global models in a novel way, demonstrating that the proposed setup yields an accuracy of 99%. The Logloss score reached 0.043, indicating the outstanding performance of our approach. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Active learning Emergency event detection Federated learning Object detection Snapchat Social networks Twitter Vision transformers ViT

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Systematic analysis of on-premise and cloud services

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International Journal of Cloud Computing 2024年第3期13卷 214-242页

作者： Ali, Asif Laghari, Asif Ali Kandhro, Irfan Ahmed Kumar, Kamlesh Younus, Salman Department of Computer Science Sindh Madressatul Islam University Karachi Pakistan Department of Software Engineering Sindh Madressatul Islam University Karachi Pakistan

There are two key distinctions between cloud and on-premise (OP) software, the cost for each varies and so does the level of control. As organisations explore to reduce costs, many data and rules are migrating to multiple clouds like GCP, AWS, AZURE, and so on. Cloud service providers provide the extensibility, resilience, and quickness that traditional OP deployments usually lose. This paper presents a comparative analysis of on-premise and cloud computing differs by outline, arrangement, administration, and devices for associations and clients. This comparison shows that cloud computing provides more flexible infrastructure and better service of data processing on-premise. In today’s enterprise IT world, there are many factors that a business must consider when deciding whether a cloud infrastructure is the right choice. As there are many mid-level organisations that I personally know which fails to adapt cloud solutions, instead rely on their proven legacy and on-premises applications and software to do business. Therefore, it is very challenging to decide for business, if either a cloud infrastructure is right choice or not. In this article, which have covered many areas and analyses of on-premise and cloud, which will help mid-level organisations to make the decision of choosing cloud solutions for their running business applications. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Cloud computing

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Traveling wave structures of some fourth-order nonlinear partial differential equations

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Journal of Ocean engineering and Science 2023年第2期8卷 124-132页

作者： Handenur Esen Neslihan Ozdemir Aydin Secer Mustafa Bayram Department of Mathematical Engineering Yildiz Technical UniversityIstanbul34220Turkey Department of Software Engineering Istanbul Gelisim UniversityIstanbulTurkey Department of Computer Engineering Biruni UniversityIstanbulTurkey

This study presents a large family of the traveling wave solutions to the two fourth-order nonlinear partial differential equations utilizing the Riccati-Bernoulli sub-ODE *** this method,utilizing a traveling wave transformation with the aid of the Riccati-Bernoulli equation,the fourth-order equation can be transformed into a set of algebraic *** the set of algebraic equations,we acquire the novel exact solutions of the integrable fourth-order equations presented in this research *** physical interpretation of the nonlinear models are also detailed through the exact solutions,which demonstrate the effectiveness of the presented *** Bäcklund transformation can produce an infinite sequence of solutions of the given two fourth-order nonlinear partial differential ***,3D graphs of some derived solutions in this paper are depicted through suitable parameter values.

关键词： Fourth-order equations Riccati-Bernoulli sub-ODE method Traveling wave solution Bäcklund transformation

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Integrating Blockchain and SDN for Centrality-Aware Virtual Multicast Tree Embedding 9

Integrating Blockchain and SDN for Centrality-Aware Virtual ...

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9th International Conference on computer Science and engineering, UBMK 2024

作者： Ayaz, Furkan Guler, Evrim Karakus, Murat Hanbay, Davut Bartin University Department of Computer Engineering Bartin Turkey Ankara University Department of Software Engineering Ankara Turkey

ISBN: (纸本)9798350365887

Recent innovations in network virtualization have made it possible to support multiple tenants, or 'virtual net-works;' on a single physical infrastructure. This is feasible due to the decoupling of network services from the actual hardware design. The intricate NP-Hard problem known as Virtual Network Embedding (VNE) requires the simultaneous avail-ability of certain network resources (e.g., bandwidth, computing capacity) and the mapping of virtual network components (e.g., virtual nodes and links) onto an existing Substrate Network (SN). In contrast to the classic VNE problem, which is centered on unicast communication, this research aims to efficiently map Virtual Networks (VNs) with one-to-many (multicast) interactions onto an SN using Virtual Multicast Trees (VMTs). To embed VMTs onto a shared SN, we provide a Centrality-Aware Blockchain Infrastructure for Virtual Multicast Tree Embedding (CBI-VMTE). This approach uses a blockchain-based centrality-aware path-finding mechanism. The goal of the CBI-VMTE architecture is to satisfy the processing needs of virtual nodes while minimizing the SN's use of network resources, especially bandwidth. In a wide range of network topologies, including NSFNET, US Backbone, Random-14, and Random-24-nodes, our approach outperforms dynamic node ranking and traditional greedy-based VMTE approaches in terms of bandwidth efficiency. © 2024 IEEE.

关键词： Trees (mathematics)

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Cross comparison of COVID-19 fake news detection machine learning models 17

Cross comparison of COVID-19 fake news detection machine lea...

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17th International Conference on Open Source Systems and Technologies, ICOSST 2023

作者： Qadees, Muhammad Hannan, Abdul Islamabad Department of Computer & Software Engineering Pakistan

ISBN: (纸本)9798350381320

The quick advancement of technology in internet communication and social media platforms eased several problems during the COVID-19 outbreak. It was, however, used to spread untruths and misinformation regarding the illness and the immunization. In this study, it is examined whether machine-learning algorithms (Naive Bayesian, Random Forest, Logistic Regression, Decision Tree, and Support Vector Machine, as well as Gradient Boost, Bagging, AdaBoost, Stochastic Gradient Descent, and Multi-layer Perceptron) can automatically classify and point out fake news text about the COVID-19 pandemic posted on social media platforms. The 'COVID19-FNIR DATASET' was used to train, test, and fine-Tune machine learning models in order to predict the sentiment class of each fake news item on COVID-19. The results were assessed using a variety of evaluation metrics (confusion matrix, classification rate, true positives rate, etc.). The findings collected demonstrate an extremely high level of accuracy when compared to other models. © 2023 IEEE.

关键词： COVID-19

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Penetration Testing Operating Systems: Exploiting Vulnerabilities

Penetration Testing Operating Systems: Exploiting Vulnerabil...

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2024 IEEE International Conference on Communications, Computing, Cybersecurity and Informatics, CCCI 2024

作者： Gardner, Evan Singh, Gurmeet Qu, Weihao Software Engineering Monmouth University Department of Computer Science United States

ISBN: (纸本)9798350349832

The safeguarding of critical data stored on devices such as phones, computers, and tablets against unauthorized access has emerged as a central concern in modern society. Along with the increasing reliance on these devices for both productivity and personal affairs, the protection of the vast collections of sensitive information becomes crucial. Information safety against unauthorized access is a critical area in cybersecurity which is addressed through the discipline of penetration testing. This practice involves security researchers simulating adversarial attacks to evaluate the defenses of various technological systems, including web applications, operating systems, and networks, with the goal of protecting sensitive data from malicious actors. This research specifically focuses on the study of penetration testing operating systems without requiring login credentials, employing techniques such as command combinations in languages like BASH within the terminal to gain access to administrative accounts. Our further studies explore the performance of emulating keystrokes when these command combinations are used in conjunction with penetration testing devices, such as a USB Rubber Ducky, focusing on optimizing speed and efficiency. This research uncovers significant security vulnerabilities that, if exploited, could result in severe consequences not only for individual devices but also for entire networks and critical infrastructures, including core businesses, healthcare systems, schools, and government agencies. By identifying and mitigating these vulnerabilities, we contribute to strengthening security protocols, such as implementing system administration enhancements that prevent unauthorized access to the root terminal. In this way, our work bolsters efforts to protect digital systems against evolving cyber threats, ensuring the safety and integrity of both individual and collective digital operations. © 2024 IEEE.

关键词： Critical infrastructures

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Resilient Electricity Network Recovery Operation Following Seismic Events

Resilient Electricity Network Recovery Operation Following S...

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2025 IEEE PES Grid Edge Technologies Conference and Exposition, Grid Edge 2025

作者： Arif, Shaila Nair, Nirmal-Kumar C. The University of Auckland Department of Electrical Computer and Software Engineering Auckland New Zealand

ISBN: (纸本)9798350352528

Seismic events, globally, are known to impact electricity networks, causing disruptions in the provision of energy and affecting the recovery well-being of communities. Contingency analysis is an established method for understanding network vulnerability, evaluating possible failure situations, and developing specific measures to minimize, which enhance the security of supply. However, current N-1 approaches often fail to effectively handle the dynamic and evolving natures of highimpact natural disturbances. This paper presents modelling based approach illustrated using scenario-based simulations to illustrate network recovery operational planning using contingency analysis. In this study, the N-2 contingency analysis is performed and solutions are proposed to improve the system resilience using the IEEE 39 bus. The identification of potentially viable credible islands is a major contribution of this work. © 2025 IEEE.

关键词： Battery storage

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DRL-based Trajectory Planning and Sensor Task Scheduling for Edge Robotics 10

DRL-based Trajectory Planning and Sensor Task Scheduling for...

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10th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Bouhoula, Sirine Avgeris, Marios Leivadeas, Aris Lambadaris, Ioannis Department of Software and IT Engineering Montréal Canada Carleton University Department of Systems and Computer Engineering Ottawa Canada

ISBN: (纸本)9798350373011

Mobile Edge Computing (MEC) and Edge Robotics have recently emerged as transformative technologies, revolutionizing industries by enabling real-time processing, decision-making, and automation at the network edge. However, the dynamicity induced by the system's conditions and specifically the mobility poses a challenge for optimally deciding where to execute a given computational task. As a response, we develop an intelligent algorithm for dynamic sensor task offloading tailored to the unique requirements of MEC-enabled robotic environments. Specifically, we first introduce the environmental dynamics including a sensor task's end-to-end delay and the robots' mobility and energy consumption and provide mathematical formulations to model these dynamics. Then, we mathematically formulate the optimization problem and its MDP counterpart and we propose a Deep Reinforcement Learning (DRL)-based computational offloading strategy to jointly optimize Quality of Service (QoS) and energy consumption through robot trajectory planning and fine-grained task allocation. Through hand-picked representative simulation scenarios, we demonstrate the superiority of our proposed mechanism in enhancing the overall system performance, specifically in optimizing task execution, reducing energy consumption, and mitigating transmission delays, compared to various baseline approaches. © 2024 IEEE.

关键词： Computation offloading

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Spatial Correlation Module for Classification of Multi-Label Ocular Diseases Using Color Fundus Images

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computers, Materials & Continua 2023年第7期76卷 133-150页

作者： Ali Haider Khan Hassaan Malik Wajeeha Khalil Sayyid Kamran Hussain Tayyaba Anees Muzammil Hussain Department of Software Engineering Faculty of Computer SciencesLahore Garrison UniversityLahorePakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Department of Computer Science&Information Technology University of Engineering and Technology(UET)PeshawarPakistan Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan

To prevent irreversible damage to one’s eyesight,ocular diseases(ODs)need to be recognized and treated *** fundus imaging(CFI)is a screening technology that is both effective and *** to CFIs,the early stages of the disease are characterized by a paucity of observable symptoms,which necessitates the prompt creation of automated and robust diagnostic *** traditional research focuses on image-level diagnostics that attend to the left and right eyes in isolation without making use of pertinent correlation data between the two sets of *** addition,they usually only target one or a few different kinds of eye diseases at the same *** this study,we design a patient-level multi-label OD(PLML_ODs)classification model that is based on a spatial correlation network(SCNet).This model takes into consideration the relevance of patient-level diagnosis combining bilateral eyes and multi-label ODs ***_ODs is made up of three parts:a backbone convolutional neural network(CNN)for feature extraction i.e.,DenseNet-169,a SCNet for feature correlation,and a classifier for the development of classification *** DenseNet-169 is responsible for retrieving two separate sets of attributes,one from each of the left and right *** then,the SCNet will record the correlations between the two feature sets on a pixel-by-pixel *** the attributes have been analyzed,they are integrated to provide a representation at the patient *** the whole process of ODs categorization,the patient-level representation will be *** efficacy of the PLML_ODs is examined using a soft margin loss on a dataset that is readily accessible to the public,and the results reveal that the classification performance is significantly improved when compared to several baseline approaches.

关键词： Ocular disease multi-label spatial correlation CNN eye disease

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Digital Twin-Assisted Robust and Adaptive Resource Slicing in LEO Satellite Networks

Digital Twin-Assisted Robust and Adaptive Resource Slicing i...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： He, Mingcheng Wu, Huaqing Zhou, Conghao Hu, Shisheng Tang, Zhixuan Zhuang, Weihua University of Waterloo Department of Electrical and Computer Engineering Canada University of Calgary Department of Electrical and Software Engineering Canada

ISBN: (纸本)9798350351255

Resource slicing in low Earth orbit satellite networks (LSN) is essential to support diversified services. In this paper, we investigate a resource slicing problem in LSN to reserve resources in satellites to achieve efficient resource provisioning. To address the challenges of non-stationary service demands, inaccurate prediction, and satellite mobility, we propose an adaptive digital twin (DT)-assisted resource slicing scheme for robust and adaptive resource management in LSN. Specifically, a slice DT, being able to capture the service demand prediction uncertainty through collected service demand data, is constructed to enhance the robustness of resource slicing decisions for dynamic service demands. In addition, the constructed DT can emulate resource slicing decisions for evaluating their performance, enabling adaptive slicing decision updates to efficiently reserve resources in LSN. Simulation results demonstrate that the proposed scheme outperforms benchmark methods, achieving low service demand violations with efficient resource consumption. © 2024 IEEE.

关键词： Resource allocation

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