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13th EASN International Conference on Innovation in Aviation and Space for Opening New Horizons

作者： Xenos, Michalis Mallas, Andreas Minas, Dimosthenis Computer Engineering and Informatics Department Patras University Rio Campus RioGR26500 Greece

This paper explores the potential of eye-tracking technology in adaptive human-machine interfaces for pilots in aviation. We argue that an interface able to adjust its layout and elements based on pilots' real-time eye-tracking data can prevent errors and enhance their performance. The study presents a literature review on the use of eye-tracking for various pilot cases, including flight simulator games, drone pilots, and cockpit pilots. Results in most cases showed that eye-tracking has been employed to improve interactions, enhance spatial awareness, guide pilots' gaze to relevant areas, and provide insights into pilots' information processing and task load. The paper discusses two sample cases demonstrating the potential of eye-tracking in adaptive human-machine interfaces. In the first case, during challenging drone simulations, eye-tracking identified areas where an adaptive human-machine interface could aid navigation and reduce cognitive load. In the second one, based on real drone flights, when signal loss incidents occurred, eye-tracking data showed that the interface should adapt to pilots' needs by providing critical information to help them to improve situational awareness. The paper concludes that eye-tracking technology has significant potential in adaptive human-machine interfaces for aviation, emphasising the importance of refining these technologies to meet pilots' specific needs and enhance flight safety. © Published under licence by IOP Publishing Ltd.

关键词： Eye tracking

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Classification of Arrhythmias 12-Lead ECG Signals Based on 1 Dimensional Convolutional Neural Networks

Classification of Arrhythmias 12-Lead ECG Signals Based on 1...

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2024 International Conference on Smart Computing, IoT and Machine Learning, SIML 2024

作者： Kurniawan, Arief Triwibowo, Bayu Aditya Fandiantoro, Dion Hayu Institut Teknologi Sepuluh Nopember Faculty of Intelligent Electrical and Informatics Technology Department of Computer Engineering Indonesia

ISBN: (纸本)9798350364101

Heart disease is the highest cause of death in the world. Arrhythmia is an abnormality in the rhythm of the heartbeat. The heart beats too fast, too slow, or irregularly. Arrhythmias are not always dangerous, e.g., someone who does excessive activity has a faster heart rate. Then, a diagnosis is needed to classify arrhythmias. One method used is ECG (Electrocardiogram) signal analysis. The ECG signal consists of P, QRS Complex, and T waves. The morphology of the QRS is used for arrhythmia classification. Currently, cardiologists analyze ECG signals by observing directly. This method is depending on the level of expertise of the cardiologist. Previous research classified arrhythmias based on the QRS morphology from a single ECG lead. As 12-lead ECG devices have now become standard in ECG examinations because abnormalities can be observed from multiple angles. This study proposes the classification of arrhythmias in 12-lead ECG signals based on the morphology of QRS complex waves using a deep learning 1-dimensional Convolutional Neural Network. The output of deep learning is the classification of arrhythmias into four classes, namely: Normal, Right Bundle Branch Block, Premature Ventricular Contraction, and Atrial Premature Beat. The outcome of the proposed system is that each QRS segment is used as input for deep learning, which can improve classification performance compared to the classification carried out by each lead. The experimental results show the method can be done well, with an average Accuracy, Precision, Sensitivity, and F1-Score were 98.8%, 99.2%, 99.2%, and 99.2%, respectively. © 2024 IEEE.

关键词： Convolutional neural networks

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Enabling LoRa energy awareness: A Multihop One-Hop Routing Protocol for Prolonging Network Lifetime 19

Enabling LoRa energy awareness: A Multihop One-Hop Routing P...

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19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

作者： Katsidimas, Ioannis Manolopoulos, Alexandros-Ioannis Nikoletseas, Sotiris University of Patras Department of Computer Engineering and Informatics Patras Greece University of Athens Department of Physics National and Kapodistrian Athens Greece University of Patras and Computer Technology Institute and Press Diophantus Department of Computer Engineering and Informatics Patras Greece

ISBN: (纸本)9798350346497

IoT applications often rely on battery-powered nodes that may be challenging to recharge, making energy efficiency a crucial concern. In this context, routing protocols play a vital role as they dictate the paths data packets take between nodes, directly influencing the energy consumption of IoT networks. Energy-aware routing protocols have been proposed to address this issue, with the aim of optimizing energy consumption by selecting paths that minimize the energy required for data transmission and reception. These protocols employ various strategies, such as distance-based, traffic-based, and hybrid schemes, to achieve energy efficiency in IoT networks. LoRaWAnprotocol has been adopted for various IoT applications with requirements in low-power and extended coverage. Over the recent years attempts have been made to replace the typical star topology employed by LoRa with multihop solutions, in an effort to further increase its capabilities. In this paper, we present a multihop algorithm that is based on an energy-balanced routing scheme adopted by LoRa nodes to increase energy efficiency and network lifetime. Multiple one-hop routes are configured for critical nodes and a different route is selected in each transmission. Additionally, critical nodes adjust their Spreading Factor and Transmission Power according to the distance of intermediate nodes. Simulation testing results verify the improved performance of our algorithm over the direct link approach. © 2023 IEEE.

关键词： Energy efficiency

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A proposed brain tumor detection algorithm using Multi wavelet Transform (MWT)

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Materials Today: Proceedings 2022年 65卷 2731-2737页

作者： Mahmoud Al-Jawher, Waleed A. Awad, Sarah H. Uruk University Department of computer engineering Iraq Iraqi Commission for computers and informatics Iraq

Magnetic resonance imaging)MRI) is a technological development in the medical field. It is used to give images of the human body with high accuracy and good quality, facilitating the process of identifying and classifying diseases in the human body. One of the diseases that are diagnosed using MRI is a brain tumor, MRI which helps in the early diagnosis of the tumor, and helps the doctor to diagnose and identify the tumor and thus make the fastest medical decision. This paper used to identification and extraction of brain tumors from magnetic resonance images based on Multi Wavelet Transform (MWT) and image processing techniques. This project Multi Wavelet Transform (MWT) used in preprocessing stage to enhance the input image and denoising. Thresholding based is used for segmentation methods, classification of brain tumor is done using Statistical Classification Methods to classify the input MRI of brain into normal or abnormal. Firstly the location of tumor was presented & next its area computed. © 2022

关键词： Magnetic resonance imaging

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Impact of Fast Frequency Response on Renewable Energy Source Curtailment and Load Shedding

Impact of Fast Frequency Response on Renewable Energy Source...

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CIRED 2024 Vienna Workshop

作者： Panagi, Savvas Lazari, Antonis Koutsoloukas, Vrahimis Aristidou, Petros Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Transmission System Operator of Cyprus Cyprus

ISBN: (纸本)9781837242672

System operators in low-inertia power systems often have to curtail renewable energy sources (RES) and employ strict under-frequency load shedding (UFLS) schemes to ensure frequency security after an event leading to loss of generation. This approach limits the maximum RES penetration in a system and results to the loss of load. To tackle these problems, fast frequency response (FFR) schemes can be used to limit the frequency Nadir after a disturbance and decrease the need for RES curtailments and UFLS. This article provides insights on the interaction between the Kinetic Energy (KE), Frequency Containment Reserves (FCR), and Nadir after a disturbance, which are the driving mechanisms leading to RES curtailment. Then, it analyses the impact of FFR on the Nadir and its ability to alleviate RES curtailment problems. The low-inertia, islanded, Cyprus dynamic model is used to quantify the results and showcase the impact on a real system. © The Institution of engineering & Technology 2024.

关键词： Electric load shedding

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Occupant-Centric Proactive Control Methodology for IEQ 18

Occupant-Centric Proactive Control Methodology for IEQ

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18th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Kakoulli, Christina Kyriacou, Alexis Michaelides, Michalis Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Lelantus Innovations Ltd Nicosia Cyprus

ISBN: (纸本)9798331306816

Indoor Environmental Quality (IEQ) is undeniably a crucial factor that affects the occupants’ overall health and well-being. However, there is a significant lack of available actionable and measurable real-time metrics for the impact of IEQ on occupants, restricting potential control solutions and the validation of their effectiveness. Even more, occupant-centric and energy concerned automatic control solutions with direct aim to decrease or even prevent any negative effects of poor IEQ on occupants are required for creating sustainable built environments. In this work, we propose a novel framework for an occupant-centric proactive air-purification and ventilation control methodology (PPV). The method utilizes state-space models along with what-if scenarios to generate the potential solution space. A multi-objective optimization extracts the optimal solution in terms of air-purification and ventilation operation points, while minimizing various computed IEQ impact metrics in terms of the occupants’ health, comfort and virus transmissibility risk, and also considering the energy expenditure. © 2024 18th Conference of the International Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - Conference Program and Proceedings. All rights reserved.

关键词： Indoor air pollution

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Factors Influencing Participation in Data Crowdsourcing: A Systematic Literature Review 8

Factors Influencing Participation in Data Crowdsourcing: A S...

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8th International Conference on informatics and Computing, ICIC 2023

作者： Panjaitan, Re. Miracle Setiawan, Budi Darma Brawijaya University Faculty of Computer Science Department of Informatics Engineering Malang Indonesia

ISBN: (纸本)9798350342604

Crowdsourcing is becoming a trending concept used by many organizations, without being limited to a particular field. As of 2018, crowdsourcing was used by 85% of the largest worldwide companies. This trend of crowdsourcing would be increasing as it offers numerous advantages to companies in achieving their goals, such as the capability of obtaining data and information from the crowd. The crowd-provided data and information contain the essence of human ingenuity, which enables companies to do problem-solving with a human-centered approach. The more contributors participate, the more likely the crowdsourcing program will succeed. Several studies give different lists of factors that influence the participation rate of the crowd. However, there's a lack of discussion about the factors and it leads to a situation where organizations need to examine many factors when developing a crowdsourcing platform to get great crowd engagement. Therefore, this study conducted a Systematic Literature Review (SLR) to perform screening and analysis of preceding research systematically. The factors in each of these literatures are generated by considering the case of the study or the region of the people related to the research. This diversity helps identify the factors influencing contributor participation in data crowdsourcing from research all over the world. A study reflecting on these research findings would help answer research questions thoroughly. This study found that there are 19 factors that positively influence contributor participation in data crowdsourcing out of 26 factors found in the 16 selected documents. © 2023 IEEE.

关键词： Crowdsourcing

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A novel medical image data protection scheme for smart healthcare system

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 821-836页

作者： Mujeeb Ur Rehman Arslan Shafique Muhammad Shahbaz Khan Maha Driss Wadii Boulila Yazeed Yasin Ghadi Suresh Babu Changalasetty Majed Alhaisoni Jawad Ahmad School of Computer Science and Informatics Cyber Technology InstituteDe Montfort UniversityLeicesterUK Department of Biomedical Engineering University of GlasgowGlasgowUK School of Computing Engineering and the Built EnvironmentEdinburgh Napier UniversityEdinburghUK Robotics and Internet‐of‐Things Laboratory Prince Sultan UniversityRiyadhSaudi Arabia Department of Computer Science Al Ain UniversityAl AinUnited Arab Emirates Department of Computer Engineering College of Computer Science King Khalid UniversityAbhaSaudi Arabia Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The Internet of Multimedia Things(IoMT)refers to a network of interconnected multimedia devices that communicate with each other over the ***,smart healthcare has emerged as a significant application of the IoMT,particularly in the context of knowledge‐based learning *** healthcare systems leverage knowledge‐based learning to become more context‐aware,adaptable,and auditable while maintain-ing the ability to learn from historical *** smart healthcare systems,devices capture images,such as X‐rays,Magnetic Resonance *** security and integrity of these images are crucial for the databases used in knowledge‐based learning systems to foster structured decision‐making and enhance the learning abilities of ***,in knowledge‐driven systems,the storage and transmission of HD medical images exert a burden on the limited bandwidth of the communication channel,leading to data trans-mission *** address the security and latency concerns,this paper presents a lightweight medical image encryption scheme utilising bit‐plane decomposition and chaos *** results of the experiment yield entropy,energy,and correlation values of 7.999,0.0156,and 0.0001,*** validates the effectiveness of the encryption system proposed in this paper,which offers high‐quality encryption,a large key space,key sensitivity,and resistance to statistical attacks.

关键词： data analysis medical image processing security

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Goalpost Detection and Recognition on Robot Soccer ERSOW Using SSD MobileNet-V2 FPNlite 25

Goalpost Detection and Recognition on Robot Soccer ERSOW Usi...

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25th International Electronics Symposium, IES 2023

作者： Supriyadi, Ujang Bachtiar, Mochamad Mobed Wibowo, Iwan Kurnianto Politeknik Elektronika Negeri Surabaya Department of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350314731

In the Indonesian Robot Contest, EEPIS Robot Soccer on Wheeled (ERSOW) plays soccer on wheels. Based on the rules, the victory of a team is taken from the highest score of the robot in scoring goals against the goalpost. However, it's not as simple as it may be thought to score goals against the goalpost. The robot has to maneuver during the game without stopping, causing the robot's position data generated by the odometry and IMU sensors to experience an accumulation of errors. The goal position data, which will be a reference for the robot's kick against the goalpost, will be impacted by the accumulated errors. This paper presents a goalpost detection system that can be used on robots. Deep Learning Neural Network (DNN) is used by the detecting system to teach itself the crucial visual characteristics of the goalpost in order to make detections. The deep learning model makes use of the Single Snapshot Detector (SSD) MobileNet V2 FPNLite 640x640. An individual image dataset of the goal point from the omnidirectional cameras. SSD MobileNetV2 FPNLite 640x640 model with 1% classification loss, 0.1% localization loss, 9% total loss and confidence score is 96-100%. The accuracy of goalpost detection and recognition is 93% with the frame rate average is 49 FPS. © 2023 IEEE.

关键词： Robots

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Simulation-based Beamforming Optimization in Moving Drones 15

Simulation-based Beamforming Optimization in Moving Drones

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15th IFIP Wireless and Mobile Networking Conference, WMNC 2024

作者： Bouras, Christos Diasakos, Damianos Kokkinos, Vasileios Prodromos, Nikolaos Gkamas, Apostolos Pouyioutas, Philippos University of Patras Computer Engineering and Informatics Department Patras Greece University of Ioannina Department of Chemistry Ioannina Greece University of Nicosia Computer Science Department Nicosia Cyprus

ISBN: (纸本)9783903176683

The integration of drone technology with 5G networks presents novel opportunities for enhancing wireless communication systems. This paper explores the application of beamforming optimization techniques in dynamic environments, specifically focusing on moving drones in a simulated environment based on the DeepMIMO O1 scenario. By leveraging the unique properties of the O1 drone setup of DeepMIMO simulation environment, which simulates realistic urban mobility patterns at millimeter-wave (mmWave) frequencies, we propose a novel beamforming algorithm designed to optimize the signal quality and stability in highly mobile aerial networks. Key performance metrics used in this study include Signal-to-Noise Ratio (SNR), battery consumption, and power consumption of both the drones and the base station. Our findings indicate that the adaptive beamforming algorithm not only enhances the SNR and reduces power consumption but also optimizes battery usage compared to conventional beamforming methods. This study enhances the understanding of mmWave beamforming dynamics in aerial scenarios but also lays the groundwork for future advancements in drone-based communication networks. © 2024 IFIP.

关键词： 5G mobile communication systems

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