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Mobile Health Intervention System in Optimizing Healthcare Delivery for Cardiac Patients 5

Mobile Health Intervention System in Optimizing Healthcare D...

引用

5th International Conference on Advancements in Computing, ICAC 2023

作者： Prabashana, R.P.K. Nanayakkara, G.A.J.W. Wanniachchi, W.K.D.C. Arampath, S.B.A.M.B.S. Rajapaksha, Samantha Harshanath, S.M.B. Sri Lanka Institute of Information Technology Dept. of Computer Systems Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350358131

The advent of mobile health (mHealth) technologies has ushered in a new era in healthcare delivery, transforming the way cardiac patients receive medical care and support. This research paper explores the role of a mobile health intervention system in optimizing healthcare delivery for cardiac patients. The prevalence of heart attacks has necessitated innovative solutions to enhance patient outcomes and reduce the burden on healthcare systems. The proposed mHealth intervention system leverages the ubiquity of mobile devices to provide real-time monitoring, personalized interventions with environment prediction, and seamless communication between patients and healthcare providers. Through a comprehensive review of existing literature and empirical studies, this paper examines the impact of the mHealth intervention system on patient engagement, adherence to treatment plans, early detection of cardiac events, and overall quality of care. The integration of wearable device, CardioCare mobile application, and telemedicine platforms creates a holistic approach to cardiac care, empowering patients to actively participate in their health management and enabling healthcare professionals to make informed decisions. The potential benefits, challenges, and ethical considerations surrounding the implementation of this system are discussed. © 2023 IEEE.

关键词： Wearable technology

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Autonomous Social Amenity, Pothole Detection and Reporting

Autonomous Social Amenity, Pothole Detection and Reporting

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International Multidisciplinary Information Technology and engineering Conference (IMITEC)

作者： David Mosela Moses Olaifa Pius Owolawi Vusi Malele Dept. Computer Systems Engineering Tshwane University of Technology Tshwane South Africa Dept. of Computer Systems Engineering Tshwane University of Technology Tshwane South Africa

ISBN: (数字)9798350387988

ISBN: (纸本)9798350387995

Challenges faced by traffic management in many developing nations across the globe is a result of the poor quality of road infrastructure. Inadequate and defective road infrastructure are major contributors to this effect. A key element that poses significant risk to road safety and that leads to increased road management cost is the increasing number of potholes and inefficient detection and reporting approach. This study provides an in-dept. exploration of the latest developments in pothole detection systems and examines various methodologies and technologies used in these systems, emphasizing the importance of real-time monitoring for proactive road maintenance. In addition, we proposed a system that addresses the persistent challenge of road infrastructure degradation by adopting cutting-edge technologies, including computer vision, machine learning, and sensor networks (such as ultrasonic and GPIO systems) that are used to identify and assess potholes on road surfaces. To achieve the aim of the study, the system adopts the use of RasberryPi 4 Model B for pothole detection and YOLOv4 for image processing.

关键词： YOLO computer vision Roads Computational modeling Machine learning Hardware Acoustics Road safety Software tools Surface treatment

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Neural Network-Based Analysis of Forest Fire Aftermath in Class-Imbalanced Remote Sensing Earth Image Classification

Neural Network-Based Analysis of Forest Fire Aftermath in Cl...

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2024 Symposium on Beyond the Canopy: Technologies and Applications of Remote Sensing

作者： Hnatushenko, Viktoriia Hnatushenko, Volodymyr Soldatenko, Dmytro Dept. Information Technologies and Systems Ukrainian State University of Science and Technologies Dnipro Ukraine Dept. Information Technologies and Computer Engineering Dnipro University of Technology Dnipro Ukraine Institute of Photogrammetry and GeoInformation Leibniz Universität Hannover Germany

Today's agricultural sector is characterized by an important role of accurate mapping and monitoring of agriculture with the help of satellite imagery, which allows to optimize the use of resources, to plan crop areas and to forecast productivity. Classification of satellite images with unbalanced sample distribution is a critical problem in this regard. Traditional machine learning algorithms in particular have limitations in dealing with sample imbalance. In this paper, we proposed convolution neural networks for semantic segmentation, where sample imbalance is considered based on a particular loss function coupled with data augmentation. To illustrate our method, we use Sentinel-2 remote sensing (RS) images covering a number of regions in Ukraine, and then we create an image dataset of the region and for training and testing make data augmentation. The models with different architectural features were investigated. The results demonstrate that the proposed CNN has a higher classification accuracy than the ones discussed in the paper: the classification accuracy on the test dataset reached 96.7% with intersection-over-union values of up to 89.7%. This opens the way for further research in the direction of refining algorithms for classify satellite data with an imbalanced class structure. © Author(s) 2024.

关键词： Semantic Segmentation

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A Novel Real-Time Redundant System For Aiding Drivers To Increase Their Attention Level 9

A Novel Real-Time Redundant System For Aiding Drivers To Inc...

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9th IEEE Smart World Congress, SWC 2023

作者： Sini, Jacopo Pugliese, Luigi D'Agostino, Pietro Violante, Massimo Groppo, Riccardo Politecnico di Torino Dept. of Control and Computer Engineering Turin Italy Sleep Advice Technologies S.r.l Turin Italy

ISBN: (纸本)9798350319804

Road accidents are a major concern worldwide. Research of technological solutions to improve road safety is an open topic, considering this issue from various perspectives. As widely reported in the literature, driver distraction is one of the most common causes of collisions. Even if vehicles are becoming safer and safer over the years, pedestrians and cyclists are still exposed to severe accidents. Major concerns about driver distraction is mobile phone use and drowsy driving. This paper proposes a virtual buddy designed to help drivers, thanks to warning sound messages, improve their attention level. The main idea is to recognize, thanks to different sources (video camera, physiological data, and interior environmental conditions) interpreted by a data-fusion algorithm, whenever there is a distracted or drowsy behavior, recalling the driver to the road. The effectiveness of the data-fusion algorithm in detecting dangerous conditions has been verified thanks to a driving simulator experimentally, obtaining no false negatives from distraction from drowsiness, a sensitivity of about 85% for the distraction caused by mobile phone usage or other activities different from focusing on driving. © 2023 IEEE.

关键词： Camera-based systems Image processing Neural Networks Physiological data Safety Sleep Vehicle Driving

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Multi-layer network modelling of genomic and transcriptomic data to investigate the response to checkpoint inhibitors in NSCLC

Multi-layer network modelling of genomic and transcriptomic ...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Mascolo, Davide Farina, Lorenzo Petti, Manuela Sapienza University of Rome Program in Data Science Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350337488

Recent innovations and developments in molecular biology and biotechnology have made it possible to acquire and store large omics datasets. In particular genomics, transcriptomics and the study of their relationship represent the key elements to understand how genotype influences phenotype. In this work we investigate the potential of multi-layer network modeling in integrating genomic and transcriptomic data of 152 advanced non-small cell lung cancer (NSCLC) patients treated with anti-PD-(L)1 therapy. For the transcriptomic layer, we performed differential expression and differential co-expression analyses in order to identify a subset of key genes in differentiating responder patients from non-responders. Adding to the genomic-transcriptomic model other three layers related to immune, myeloid and curated immunotherapy-based literature signatures we obtained a 5-layer Patient Similarity Network. The application of Similarity Network Fusion algorithm revealed a statistically significant stratification of patients (p-value ≤ 0.05) which allows the identification of two clusters characterized by patients responding and not responding to immunotherapy. © 2023 IEEE.

关键词： immunotherapy multi-layer network Network-based omics integration non-small cell lung cancer patient Stratification

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Unconventional Computing based on Four Wave Mixing in Highly Nonlinear Media

Unconventional Computing based on Four Wave Mixing in Highly...

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2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023

作者： Sozos, Kostas Deligiannidis, Stavros Mesaritakis, Charis Bogris, Adonis University of West Attica Dept. of Informatics and Computer Engineering. Aghiou Spiridonos Egaleo Athens12243 Greece University of the Aegean Dept. of Information and Communication Systems Engineering Palama 2 Karlovassi Samos83200 Greece

ISBN: (纸本)9798350345995

Nowadays, photonic analog computing in the form of neuromorphic photonics or photonic neural networks has resulted in powerful hardware platforms that accelerate difficult tasks with marginal power consumption. Although linear transformations are efficiently carried out in the optical domain, nonlinear transformations are also of paramount importance. Here, we propose four wave mixing (FWM) process as an elegant solution for the generation of diverse nonlinear higher order products of an original signal. On one hand, these products can act as activation functions in different types of neural networks, either recurrent neural networks (RNNs) and reservoir computers or in any other type of brain-inspired frameworks. On the other hand, the same products can form the basis for polynomial regression which is a very powerful technique used in machine learning in different tasks i.e. for the prediction of COVID-19 transmission [1]. © 2023 IEEE.

关键词： Recurrent neural networks

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A Multicore Implementation of an AUTOSAR-based XCP Module 12

A Multicore Implementation of an AUTOSAR-based XCP Module

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12th Mediterranean Conference on Embedded Computing, MECO 2023

作者： Osama, Mahmoud Hammad, Sherif Elhady, Nancy E. El-Kharashi, M. Watheq Ain Shams University Faculty of Engineering Dept. of Computer & Systems Eng. Cairo Egypt Garraio CEO Cairo Egypt Ain Shams University Faculty of Engineering Dept. of Mechatronics Eng. Cairo Egypt

ISBN: (纸本)9798350322910

The automotive industry depends on computers to control and monitor vehicles behaviour. The Universal Measurement and Calibration Protocol (XCP) connects calibration systems to electronic control units (ECUs). Nowadays, AUTOSAR-based XCP for single core ECUs is widely used in automotive industry. As the demand for computing power is rapidly increasing in the automotive domain, car manufacturers are gradually introducing multi-core ECUs in their electronic architectures. Multi-core ECUs provide high level of parallelism. This research work aims to deliver a multi-core implementation of an AUTOSAR-based XCP module, as it is important to have an efficient process of measurement and calibration on multi-core targets. The paper results are ensuring data consistency on the application level, avoiding race conditions between writer core and reader core which might result in processing rubbish data, and decreasing data dependency between cores. © 2023 IEEE.

关键词： Automotive industry

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Pursuit-Evasion on a Sphere and When It Can Be Considered Flat 63

Pursuit-Evasion on a Sphere and When It Can Be Considered Fl...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Milutinovic, Dejan Moll, Alexander Von Manyam, Satyanarayana G. Casbeer, David W. Weintraub, Isaac E. Pachter, Meir Electrical and Computer Engineering Dept. University of California Santa Cruz Santa CruzCA United States Control Science Center Aerospace Systems Directorate Air Force Research Laboratory DaytonOH45435 United States Dcs Corporation DaytonOH United States Air Force Institute of Technology Wright-Patterson Afb Dept. of Electrical Engineering OH United States

ISBN: (纸本)9798350316339

In planar pursuit-evasion differential games considering a faster pursuer and slower evader, the interception points resulting from equilibrium strategies lie on the Apollonius circle. This property is instrumental for leveraging geometric approaches for solving multiple pursuit-evasion scenarios in the plane. Here, we study a pursuit-evasion differential game on a sphere and generalize the planar Apollonius set to the spherical domain. We find that the interception point from the equilibrium strategies can leave the Apollonius set boundary and present a condition to keep the intercept point on the boundary. This condition allows for generalizing planar pursuitevasion strategies to the sphere. © 2024 IEEE.

关键词： Spheres

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Stealthy Attack Detection of controlled ramp meters in freeway networks 63

Stealthy Attack Detection of controlled ramp meters in freew...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Menelaou, Charalambos Zhang, Kangkang Timotheou, Stelios Panayiotou, Christos G. Parisini, Thomas University of Cyprus Kios CoE Dept. of Electrical and Computer Engineering Cyprus Imperial College London Dept. of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy

ISBN: (纸本)9798350316339

The increasing reliance on intelligent transportation systems (ITS) for traffic management has simultaneously heightened the potential for cybersecurity threats. Malicious cyber attacks on such systems can lead to operational inefficiencies, heightened congestion, and compromised safety. This work introduces a stealthy integrity attack tailored for ramp metered freeway systems. The attack model is conceptualized as a closed-loop dynamical system, formulated as an optimization problem based on the Cell Transmission Model. This work further proposes a distributed detection mechanism designed to identify attack residuals, which, by incorporating an adaptive threshold scheme, can detect the presence of an attack. To demonstrate the efficacy of our detection scheme, we present a scenario illustrating its application in freeway road networks. © 2024 IEEE.

关键词： Cyber attacks

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Enhancing Connectivity in Remote Regions using Adaptive and Resilient UAV-Based Wireless Networks

Enhancing Connectivity in Remote Regions using Adaptive and ...

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IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Andrés García–Lopez Diego Ramos–Ramos Santiago García–Gil José Gómez–delaHiz Juan Manuel Murillo Jaime Galán–Jiménez Dept. of Computer Systems and Telematics Engineering University of Extremadura Spain

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

The annual growth of Internet adoption still leaves around 2 billion people in remote areas without connectivity, cutting them off from vital services such as healthcare and distance education. This paper proposes an energy-efficient solution leveraging Unmanned Aerial Vehicles (UAVs) based network architectures to dynamically adapt to hardware failures or battery depletion. By incorporating the Software-Defined Networking (SDN) paradigm for real-time network management, this approach ensures swift adaptability to changing environmental conditions. Consequently, the UAV-based network can deliver Internet of Things (IoT) applications to users, significantly improving the quality of life for rural populations. Simulations conducted in realistic scenarios demonstrate a success rate of over 90% in handling user requests across various situations.

关键词： Adaptation models Wireless networks Autonomous aerial vehicles Energy efficiency Real-time systems Hardware Batteries Internet of Things Vehicle dynamics Software defined networking

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