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1st International Conference on Artificial Intelligence and its Applications, ICAIA 2023

作者： Ather, Danish Singh, Anupam Khan, Rubina Liyakat Vijay, Richa Singh, Ramveer Kumar, Raj Amity University in Tashkent Tashkent Uzbekistan Department of Computer Science and Engineering Graphic Era Hill University Dehradun India The Applied College Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Amity University Noida Uttar Pradesh Noida India Department of CSE Galgotias College of Engineering and Technology Greater Noida India Faridabad India

ISBN: (纸本)9783031843938

Concerns regarding the health and well-being of the old have been raised globally due to the elderly population’s rapid rise. In order to overcome these difficulties, this study introduces an Internet of Things (IoT)-based wearable health monitoring system for senior care. The suggested system combines a variety of sensors with wireless communication capabilities to continuously monitor the health and physical activities of elderly people. The central element for data collection, processing, and transmission is the Arduino platform, which is renowned for its simplicity and adaptability. In addition to an accelerometer for tracking movement and fall detection, the wearable gadget has sensors for assessing vital signs like heart rate, blood pressure, body temperature, and oxygen saturation. The Arduino board processes the data locally, and it is then wirelessly transferred to a centralized monitoring system using Wi-Fi or Bluetooth Low Energy (BLE) communication. Caretakers or medical experts can access the central monitoring system, which offers real-time visualization and analysis of the gathered data. It makes it possible to discover aberrant health situations early, to act quickly, and to perform remote monitoring. Additionally, the system may produce warnings and notifications in the event of crises, ensuring quick access to medical care. The suggested wearable health monitoring system built on Arduino has a number of benefits, including affordability, mobility, and simplicity of use. It gives elderly people the ability to preserve their independence while offering a safety net through ongoing health monitoring. Additionally, the system enables healthcare professionals to give individualized and timely interventions based on real-time health data and simplifies remote caregiving. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Electronic health record

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Trustworthy and Load-Balancing Routing Scheme for Satellite Services with Multi-Agent DRL

Trustworthy and Load-Balancing Routing Scheme for Satellite ...

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IEEE Conference on computer Communications Workshops, INFOCOM Wksps

作者： Jiaxin Song Ying Ju Lei Liu Qingqi Pei Celimuge Wu Mian Ahmad Jan Shahid Mumtaz School of Telecommunications Engineering Xidian University Xi'an China Graduate School of Informatics and Engineering the University of Electro-Communications Chofu Japan Department of Computer Science Abdul Wali Khan University Mardan Mardan Pakistan Department of Applied Informatics Silesian University of Technology Akademicka Poland Engineering Department Nottingham Trent University Nottingham UK

Massive computing tasks of various applications have been generated in 6G space-air-ground integrated networks, and need to be transmitted securely and reliably. Nevertheless, the mobility of satellites and the untrusted nodes bring new challenges to the routing scheme design in low earth orbit (LEO) satellite networks. To improve the system trust and elevate the service quality, this paper proposes a fully distributed trustworthy load-balancing routing scheme for satellite services with a multi-agent dueling double deep Q network (D3QN)-based learning algorithm. Our scheme organizes multiple agents to generate hop-by-hop routes and makes decisions based on the trust value of the nodes, which has good scalability to deploy on various satellite constellations and can meet the trust requirements of the services. Besides, we add a variable delay constraint into the load minimization objective to meet various delay-sensitive satellite quality of service (QoS) requirements. We demonstrate that the proposed scheme dramatically reduces the link queue utilization rate and enhances the system capability of handling delay-sensitive services. The packet loss rate of our scheme is 24% lower than that of the benchmark scheme when the system has 30% malicious nodes.

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Connection and operation of wind farms as part of electric power-supply systems through the example of Kaliningrad region

Connection and operation of wind farms as part of electric p...

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2020 International Conference on Germany and Russia: Ecosystems Without Borders, EcoSystConfKlgtu 2020

作者： Beley, V.F. Reshetnikov, G.A. Harzfeld, E. Department of Electrical Equipment of Ships and Electric Power Engineering Kaliningrad State Technical University Kaliningrad Russia Faculty of Electrical Engineering and Computer Science Hochschule Stralsund University of Applied Sciences Stralsund Germany

The issues of connecting wind power plants (WPP) to the power-supply system and their joint operation are currently gaining relevance due to the growth of their capacities and an abruptly variable pattern of its delivery to the grid. The paper presents the analysis of standards, recommendations and regulations related to connection and operation of WPPs as part of the power-supply system. The developed mathematical model of the Ushakovskaya WPP is used to analyze its main operating modes. Practical recommendations for changing the scheme of power generation of the plant at increased capacity are given with due regard to the standard requirements. © Published under licence by IOP Publishing Ltd.

关键词： Wind power

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Fog Computing Security Assessment for Device Authentication in the Internet of Things 22

Fog Computing Security Assessment for Device Authentication ...

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22nd IEEE International Conference on High Performance Computing and Communications, 18th IEEE International Conference on Smart City and 6th IEEE International Conference on Data science and Systems, HPCC-SmartCity-DSS 2020

作者： Al Harbi, Saud Halabi, Talal Bellaiche, Martine Polytechnique Montreal Department of Computer Engineering Quebec Canada University of Winnipeg Department of Applied Computer Science Manitoba Canada Polytechnique Montreal Department of Computer Engineering Quebec Canada

ISBN: (纸本)9781728176499

The Fog is an emergent computing architecture that will support the mobility and geographic distribution of Internet of Things (IoT) nodes and deliver context-Aware applications with low latency to end-users. It forms an intermediate layer between IoT devices and the Cloud. However, Fog computing brings many requirements that increase the cost of security management. It inherits the security and trust issues of Cloud and acquires some of the vulnerable features of IoT that threaten data and application confidentiality, integrity, and availability. Several existing solutions address some of the security challenges following adequate adaptation, but others require new and innovative mechanisms. These reflect the need for a Fog architecture that provides secure access, efficient authentication, reliable and secure communication, and trust establishment among IoT devices and Fog nodes. The Fog might be more convenient to deploy decentralized authentication solutions for IoT than the Cloud if appropriately designed. In this short survey, we highlight the Fog security challenges related to IoT security requirements and architectural design. We conduct a comparative study of existing Fog architectures then perform a critical analysis of different authentication schemes in Fog computing, which confirms some of the fundamental requirements for effective authentication of IoT devices based on the Fog, such as decentralization, less resource consumption, and low latency. © 2020 IEEE.

关键词： Fog

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Machine Learning Information Retrieval and Summarisation to Support Systematic Review on Outcomes Based Contracting

arXiv

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arXiv 2024年

作者： Bilal, Iman Munire Fang, Zheng Arana-Catania, Miguel van Lier, Felix-Anselm Velarde, Juliana Outes Bregazzi, Harry Carter, Eleanor Airoldi, Mara Procter, Rob Department of Computer Science University of Warwick and Alan Turing Institute for Data Science and AI Coventry United Kingdom Faculty of Engineering and Applied Sciences Cranfield University United Kingdom Government Outcomes Lab Blavatnik School of Government University of Oxford Oxford United Kingdom

As academic literature proliferates, traditional review methods are increasingly challenged by the sheer volume and diversity of available research. This article presents a study that aims to address these challenges by enhancing the efficiency and scope of systematic reviews in the social sciences through advanced machine learning (ML) and natural language processing (NLP) tools. In particular, we focus on automating stages within the systematic reviewing process that are time-intensive and repetitive for human annotators and which lend themselves to immediate scalability through tools such as information retrieval and summarisation guided by expert advice. The article concludes with a summary of lessons learnt regarding the integrated approach towards systematic reviews and future directions for improvement, including explainability. © 2024, CC BY.

关键词： Adversarial machine learning

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Modeling of Measurement Error in Financial Returns Data

arXiv

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arXiv 2024年

作者： Jasra, Ajay Maama, Mohamed Mijatović, Aleksandar School of Data Science The Chinese University of Hong Kong Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Statistics University of Warwick United Kingdom

In this paper we consider the modeling of measurement error for fund returns data. In particular, given access to a time-series of discretely observed log-returns and the associated maximum over the observation period, we develop a stochastic model which models the true log-returns and maximum via a Lévy process and the data as a measurement error there-of. The main technical difficulty of trying to infer this model, for instance Bayesian parameter estimation, is that the joint transition density of the return and maximum is seldom known, nor can it be simulated exactly. Based upon the novel stick breaking representation of [12] we provide an approximation of the model. We develop a Markov chain Monte Carlo (MCMC) algorithm to sample from the Bayesian posterior of the approximated posterior and then extend this to a multilevel MCMC method which can reduce the computational cost to approximate posterior expectations, relative to ordinary MCMC. We implement our methodology on several applications including for real data. Copyright © 2024, The Authors. All rights reserved.

关键词： Markov chains

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Mental Health Stigma: Strategies for Destigmatization in Healthcare Settings

Mental Health Stigma: Strategies for Destigmatization in Hea...

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Electrical Electronics and Computing Technologies (ICEECT), International Conference on

作者： Aishwarya Verma Krishna Tanaya Panda Vandana Sharma Hrudaya Kumar Tripathy Mahmoud Ahmad Al-Khasawneh Ahmed Alkhayyat Kalinga Institute of Industrial Technology India Computer Science Department CHRIST University India School of Computing Skyline University College University City Sharjah Sharjah UAE Applied Science Research Center Applied Science Private University Amman Jordan Jadara University Research Center Jadara University Jordan College of Technical Engineering The Islamic University Najaf Iraq

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

Mental illness is one of the most common disabilities in the world. The term "mental illness stigma" describes harmful practices and misconceptions that lead to a detrimental effect on the mental health, motivation, and self-worth of those who suffer from mental illnesses. Health care services are important for treating and reducing the negative stigma of mental health, as they are areas where patients seek relief and support. The study aims to investigate the causes and how to reduce them. Explores ways to disrupt the health care environment, specifically the RESHAPE program, which focuses on the concept of "critical". This review paper looks at 8-10 papers on mental health and stigma and how stigma will be reduced. The results show that a large number of doctors and students are stigmatized, negatively affecting the lives of people affected by mental illness. RESHAPE, KAP, and IBH therapies are also effective ways to minimize mental health stigma. This intervention aims to educate public health workers, promote social cohesion, and integrate treatment into primary health care, improving treatment into primary health care, improving treatment quality and patient outcomes. The study draws attention to the importance of stigma reduction efforts in the long term in health education and practice emphasis.

关键词： computers Reviews Education Medical treatment Mental health Medical services Media Public healthcare

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Hybrid CNN-GRU Framework with Integrated Pre-trained Language Transformer for SMS Phishing Detection 21

Hybrid CNN-GRU Framework with Integrated Pre-trained Languag...

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Proceedings of the 5th International Conference on Future Networks and Distributed Systems

作者： Rubaiath E Ulfath Hamed Alqahtani Mohammad Hammoudeh Iqbal H. Sarker Department of Computer Science and Engineering Chittagong University of Engineering & Technology Bangladesh King Khalid University Saudi Arabia Department of Computing & Math Manchester Metropolitan University United Kingdom

ISBN: (纸本)9781450387347

Smartphones are prone to SMS phishing due to the rapid growth in the availability of smart mobile technologies driven by Internet connections. Also, detecting phishing SMS is a challenging task due to the unstructured nature of SMS text data with non-linear complex correlations. In this concern, considering the recent advancements in the domain of cybersecurity, we have proposed a hybrid deep learning framework that extracts robust features from SMS texts followed by an automatic detection of Phishing SMS. Due to combining the potential capability of individual models into one hybrid framework, it has outperformed various other individual machine learning and deep learning models. The proposed Phishing Detection framework is an effective hybrid combination of pretrained transformer model, MPNet (Masked and Permuted Language Modeling), with supervised ConvNets (CNN) and Bi-directional Gated Recurrent Units (GRU). It is intended to successfully detect unstructured short phishing text messages that contain complex patterns.

关键词： AI

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AI-Driven VANETs for IoT-Enabled Transportation Systems 1st

AI-Driven VANETs for IoT-Enabled Transportation Systems

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1st International Conference on Artificial Intelligence and its Applications, ICAIA 2023

作者： Singh, Ramveer Kumar, Raj Singh, Anupam Vijay, Richa Khan, Rubina Liyakat Ather, Danish Department of CSE Galgotias College of Engineering and Technology Greater Noida India Faridabad India Department of Computer Science and Engineering Graphic Era Hill University Dehradun India Amity University Uttar Pradesh Noida India The Applied College Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Amity University in Tashkent Tashkent Uzbekistan

ISBN: (纸本)9783031843938

This paper presents an innovative approach to address traffic congestion and safety challenges in smart cities by leveraging Artificial Intelligence (AI)-driven Vehicular Ad-Hoc Networks (VANETs) within IoT-enabled transportation systems. The integration of AI algorithms, such as machine learning and deep learning, enables seamless communication among connected vehicles and IoT infrastructure. Real-time data analysis facilitates effective traffic flow control, congestion detection, and accident prediction at the same instance security and privacy concerns are addressed through robust solutions. The current work showcases simulations and case studies, highlighting significant improvements in traffic efficiency, reduced travel time, and enhanced transportation safety. The study emphasizes the transformative potential of AI-driven VANETs in creating intelligent transportation systems for future smart cities, fostering more sustainable and liveable urban environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Vehicular ad hoc networks

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A Riemannian ADMM

arXiv

引用

arXiv 2022年

作者： Li, Jiaxiang Ma, Shiqian Srivastava, Tejes Department of Electrical and Computer Engineering University of Minnesota United States Computational Applied Mathematics and Operations Research Rice University United States Department of Computer Science University of Chicago United States

We consider a class of Riemannian optimization problems where the objective is the sum of a smooth function and a nonsmooth function, considered in the ambient space. This class of problems finds important applications in machine learning and statistics such as the sparse principal component analysis, sparse spectral clustering, and orthogonal dictionary learning. We propose a Riemannian alternating direction method of multipliers (ADMM) to solve this class of problems. Our algorithm adopts easily computable steps in each iteration. The iteration complexity of the proposed algorithm for obtaining an ϵ-stationary point is analyzed under mild assumptions. Existing ADMM for solving nonconvex problems either does not allow nonconvex constraint set, or does not allow nonsmooth objective function. Our algorithm is the first ADMM type algorithm that minimizes a nonsmooth objective over manifold – a particular nonconvex set. Numerical experiments are conducted to demonstrate the advantage of the proposed *** Codes 90C30 Copyright © 2022, The Authors. All rights reserved.

关键词： Principal component analysis

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