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Annual IEEE Systems Conference

作者： Mehran Jafari Gautier Bureau Marco Chiaramello Adrien Guironnet Patrick Panciatici Petros Aristidou Dept. of Electrical Eng. Computer Eng. & Informatics Cyprus University of Technology Limassol Cyprus Réseau de Transport d’ Électricité (RTE) France

ISBN: (数字)9798350358803

ISBN: (纸本)9798350358810

All modern electric power systems employ digital controllers to ensure their secure and optimized operation. The time-domain simulation of such systems requires the solution of a set of hybrid (both continuous and discrete variables) differential-algebraic equations. This is not an easy task, since the discontinuities introduced by the digital controllers lead to constant time-step reductions and an increased computational burden. A method that is able to effectively perform such simulations with no time step reduction is the interpolation-based method (IBM). In this paper, we extend the IBM into the decoupled interpolation-based method to increase the computational performance while maintaining the same high simulation accuracy. The performance and accuracy of the proposed methods is employed on several small and medium system models.

关键词： Accuracy Numerical simulation Control systems Mathematical models Software Trajectory Power systems

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Enhance Object Tracking on Augmented Reality Markerless using FAST Corner Detection 5

Enhance Object Tracking on Augmented Reality Markerless usin...

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5th IEEE International Conference on Information technology, Information Systems and Electrical Engineering, ICITISEE 2021

作者： Nurhadi Winanto, Eko Arip Saparudin Dinamika Bangsa University Faculty Of Engineering Sriwijaya University Dept. Of Informatics Engineering Indonesia University Of Technology Malaysia School Of Computing Malaysia Telkom University Faculty Of Computer Science Dept. Of Informatics Engineering Indonesia

ISBN: (纸本)9781665401968

Markerless-based is the method in Augmented Reality (AR) to augmentation 3D objects in the frame. One of the challenges in markerless AR is to extract features as input data training on markerless AR. One of algorithm for feature extraction of object target is FAST corner detection in image processing. This paper uses FAST corner detection for feature extraction on Augmented Reality Markerless based with the aim to improve performance of augmentation objects in AR. The User Defined Target and Extended Tracking are to improve convenience and reliability of the AR. The aim is can trace 3D objects even the 3D object invisible. The results show that maximum environment for the best augmentation is intensity in of 80-190 cd. © 2021 IEEE.

关键词： Augmented reality

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Implementing a Robust and Scalable Detect-and-Avoid Algorithm for UAV Navigation in ROS

Implementing a Robust and Scalable Detect-and-Avoid Algorith...

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International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Dimitrios Meimetis Ioannis Daramouskas Vaios Lappas Isidoros Perikos Vaggelis Kapoulas Michael Paraskevas Department of Aerospace Science & Technology NKUA Athens Greece Computer Technology Institute and Press “Diophantus” Patras Greece Applied Mechanics Lab UoP Patras Greece Computer Engineering and Informatics Department UoP Patras Greece Electrical and Computer Engineering Dept. Computer Technology Institute and Press “Diophantus” University of Peloponnese Patras Greece

ISBN: (数字)9798350368833

ISBN: (纸本)9798350368840

Unmanned aerial vehicles (UAVs) have garnered significant attention from the research community during the last decade, due to their diverse capabilities and potential applications. One of the most critical functions that drones must execute efficiently is navigation in real-world environments. This paper presents a decentralized approach for enabling unmanned aerial vehicles (UAVs) to navigate safely in unknown environments and avoid obstacles. Leveraging the Optimal Reciprocal Collision Avoidance (ORCA) algorithm, implemented in the Robot Operating System (ROS), our method facilitates conflict detection and resolution in 2D environments. Through simulations using ROS, Gazebo, and Iris drones, we validate the effectiveness of our approach in scenarios with initial trajectory conflicts. Our work addresses the pressing need for UAVs to autonomously plan and execute safe flights, laying the groundwork for enhanced UAV capabilities in various real-world applications. The simulation results demonstrate the efficiency and robustness of our approach.

关键词： Simulation Autonomous aerial vehicles Aircraft navigation Sensor systems Robustness Real-time systems Trajectory Safety Sensors Drones

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Increasing the RES hosting capacity of the Cyprus distribution system

Increasing the RES hosting capacity of the Cyprus distributi...

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CIRED 2024 Vienna Workshop

作者： Phivos Therapontos Rafail Konstantinou Charalambos A. Charalambous Petros Aristidou Distribution System Operator Electricity Authority of Cyprus Nicosia Cyprus University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus Dept. of Electrical & Computer Engineering & Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (数字)9781837241224

The Renewable Energy Sources (RES) penetration in the power system of Cyprus has dramatically increased over the last years. As a result, the system is already facing significant challenges limiting the RES hosting capacity of the Distribution Network (DN). The major limitation factors are network congestion and voltage security. In this paper, alternative solutions for increasing the RES hosting capacity in DNs are reviewed, and a methodology is introduced to evaluate their effectiveness. More specifically, different inverter settings and an advanced centralised voltage control from power transformers are used to mitigate voltage-related issues, while network reinforcements and upgrading the operating voltage are considered for further increase in hosting capacity. The solutions and evaluation methodology are tested using a real MV network of the Cyprus distribution system and the strategic plan of the Cyprus Distribution System Operator (DSO) for maximizing RES hosting capacity is outlined.

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A Dynamic Security Assessment Tool for Modern Power Systems with Massive RES Penetration

A Dynamic Security Assessment Tool for Modern Power Systems ...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Phivos Therapontos Charalambos A. Charalambous Petros Aristidou Distribution System Operator Electricity Authority of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Dept. of Electrical & Computer Engineering & Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

Modern power systems are facing significant challenges due to the massive penetration of renewable energy sources (RES). Recently, issues related to frequency security, system strength, and excessive fault levels have been experienced in some power systems. Classical dynamic security assessment (DSA) tools have not been developed to identify and analyze these new challenges that are critical in low-inertia grids. In this paper, a DSA tool has been developed that evaluates frequency security, system strength, and maximum fault levels to allow for secure system planning and operation. Furthermore, to increase the accuracy of the DSA tool, inverter-based resources’ (IBRs’) protections and capabilities have been incorporated in the DSA tool. A real-time operation and an operational planning application of the DSA tool are showcased using the islanded Cyprus Power System.

关键词： Renewable energy sources Adaptation models Accuracy Power system dynamics Real-time systems Planning Security Protection Faces

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Normal Vector Direction-based 3D LiDAR Point Cloud Planar Surface Removal for Object Cluster Minimization in Human Activity Monitoring System

Normal Vector Direction-based 3D LiDAR Point Cloud Planar Su...

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IEEE Instrumentation and Measurement technology Conference

作者： Nova Eka Budiyanta Eko Mulyanto Yuniarno Tsuyoshi Usagawa Mauridhi Hery Purnomo Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Computer Science and Electrical Engineering Graduate School of Science and Technology Kumamoto University Kumamoto Japan Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember University Center of Excellence on Artificial Intelligence for Healthcare and Society (UCE AIHeS) Surabaya Indonesia

The use of 3-Dimensional Light Detection and Ranging (3D LiDAR) point cloud as the alternative data to reduce privacy exposure in monitoring systems has been carried out in several studies. Unfortunately, various challenges in using point clouds intersect with the amount of data and computational costs. Several studies attempted to optimize the point cloud processing approach by segmenting the ground plane to get the object clusters separated. However, many unnecessary points can still burden the computation process. Since the ground plane mainly represents the horizontal planar plane on the x, y axis, this study tried to reduce the points on the vertical planar plane on the x, z and y, z axes with the x, y horizontal planar plane as well based on the surface normal vector direction of each point. The proposed approach has successfully reduced the raw point cloud by 79.29% removing the point cloud that indicates the planar surface of the three axes while maintaining the essential object of the monitoring system on the KITTI raw dataset. Therefore, the object cluster can be minimized, supporting the computational costs for further research in human activity monitoring systems.

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Wital: A COTS WiFi Devices Based Vital Signs Monitoring System Using NLOS Sensing Model

arXiv

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arXiv 2023年

作者： Zhang, Xiang Gu, Yu Yan, Huan Wang, Yantong Dong, Mianxiong Ota, Kaoru Ren, Fuji Ji, Yusheng The School of Computer and Information Hefei University of Technology China I+ Lab School of Computer Science and Engineering University of Electronic Science and Technology of China China The Dept. of Sciences and Informatics Muroran Institute of Technology Japan The National Institute of Informatics Tokyo101-8430 Japan

Vital sign (breathing and heartbeat) monitoring is essential for patient care and sleep disease prevention. Most current solutions are based on wearable sensors or cameras;however, the former could affect sleep quality, while the latter often present privacy concerns. To address these shortcomings, we propose Wital, a contactless vital sign monitoring system based on low-cost and widespread commercial off-the-shelf (COTS) Wi-Fi devices. There are two challenges that need to be overcome. First, the torso deformations caused by breathing/heartbeats are weak. How can such deformations be effectively captured? Second, movements such as turning over affect the accuracy of vital sign monitoring. How can such detrimental effects be avoided? For the former, we propose a non-line-of-sight (NLOS) sensing model for modeling the relationship between the energy ratio of line-of-sight (LOS) to NLOS signals and the vital sign monitoring capability using Ricean K theory and use this model to guide the system construction to better capture the deformations caused by breathing/heartbeats. For the latter, we propose a motion segmentation method based on motion regularity detection that accurately distinguishes respiration from other motions, and we remove periods that include movements such as turning over to eliminate detrimental effects. We have implemented and validated Wital on low-cost COTS devices. The experimental results demonstrate the effectiveness of Wital in monitoring vital signs. © 2023, CC BY.

关键词： Wireless local area networks (WLAN)

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CRISP - DM Process in Smart Building Management

CRISP - DM Process in Smart Building Management

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International Conf on Electrical and Electronic Engineering (ICEEE)

作者： Mahir Dursun Moldir Sabyrzhan Dept. of Electrical and Electronics Engineering Faculty of Technology Gazi University Ankara Türkiye Department of Computer Science Graduate School of Informatics Gazi University Ankara Türkiye

ISBN: (数字)9798350362541

ISBN: (纸本)9798350362558

Smart Buildings are buildings that integrate and combine intelligence, management, control, materials, and construction as a single system to meet all the needs of the building, such as comfort, energy efficiency, and durability. In universities, laboratories are used less frequently than other facilities and classrooms. Courses and students may change in the same classroom, and the period of use of such classrooms is much more extended than in laboratories. However, classrooms may only be used for classes during long breaks or for short periods of non-use between exams. In addition, there is no provision for when the heating system will start to heat up before classes or when it will be turned off after classes. By planning heating and lightning, energy and costs will be saved. This paper presents data acquisition methods for preparing a dataset to create a machine learning (ML) model to save energy loss in university laboratories. The developed model will predict energy consumption in classrooms and laboratories based on weather conditions. The study is being conducted in two stages. The first stage describes how to collect data using electronic devices such as Internet of Things (IoT) controllers of Smart Building Management Systems. The second stage gave possibilities for data analysis and preparation using the phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM).

关键词： Heating systems Smart buildings Laboratories Energy conservation Decision making Process control Data models Planning Internet of Things Data mining

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Medical Knowledge-Guided Deep Learning for Mammographic Breast Density Classification

Medical Knowledge-Guided Deep Learning for Mammographic Brea...

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Medical Imaging 2023: computer-Aided Diagnosis

作者： Gao, Long Liu, Chang Arefan, Dooman Panigrahy, Ashok Zuley, Margarita L. Wu, Shandong Dept. of Radiology University of Pittsburgh PittsburghPA15213 United States Dept. of Bioengineering University of Pittsburgh PittsburghPA15213 United States Dept. of Biomedical Informatics University of Pittsburgh PittsburghPA15213 United States Intelligent Systems Program University of Pittsburgh PittsburghPA15213 United States College of Computer National University of Defense Technology Changsha410073 China Magee-Womens Hospital University of Pittsburgh Medical Center PittsburghPA15213 United States

ISBN: (纸本)9781510660359

Classification of Breast Imaging Reporting and Data System (BI-RADS) breast density categories generally reflects the amount of dense/fibroglandular tissue in the breast. Studies have consistently shown that breast with higher density has a higher risk of developing breast cancer compared to breast with lower density. In this paper, we propose a novel end-to-end method, namely, Medical Knowledge-guided Deep Learning (MKDL), for breast mammogram density classification. The principle behind MKDL lies in the fact that many breast image density classification tasks are partly or largely based on certain pre-known image features, such as image contrast and brightness. These pre-known features can be computationally represented and then leveraged as prior knowledge to facilitate more effective model learning and thus boost the classification performance. We designed specific knowledge-based transformations for breast density classification and showed that our model outperformed several state-of-the-art models. © 2023 SPIE.

关键词： Classification (of information)

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Comparative Analysis of Robotic Arm Efficiency: Evaluating PID and Fuzzy-PID Control using Printed Mechanical Structure and ESP8266 Integration

Comparative Analysis of Robotic Arm Efficiency: Evaluating P...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Padma Nyoman Crisnapati I Made Darma Susila I Komang Agus Ady Aryanto Jaturapith Krohkaew Ricky Aurelius Nurtanto Diaz I Made Suandana Astika Pande Department of Information Systems Faculty of Informatics and Computers Institute Technology and Business STIKOM Bali Denpasar Indonesia Department of Computer Systems Faculty of Informatics and Computers Institute Technology and Business STIKOM Bali Denpasar Indonesia Dept. of Big Data Management and Analytics Faculty of Science and Technology Rajamangala University of Technology Thanyaburi Thanyaburi Thailand

ISBN: (数字)9798331539603

ISBN: (纸本)9798331539610

This study investigates the comparative effectiveness of manual PID tuning versus Fuzzy-PID control in enhancing the performance of a robot arm with two degrees of freedom (2-DOF). The experimental approach involves conducting two scenarios: manual tuning of PID parameters in Scenario 1 and utilizing a fuzzy algorithm for PID parameter tuning in Scenario 2. The novelty of this research lies in the new 3D mechanical design of the 2-DOF robot arm and the utilization of the ESP8266 microcontroller for implementing Fuzzy-PID control. Performance evaluation is conducted using Root Mean Square Error (RMSE) and Root Mean Square Percentage Error (RMSPE) calculations. The results reveal that Fuzzy-PID control significantly reduces errors compared to manual PID tuning, with lower RMSE and RMSPE values indicating more precise and stable control. These findings underscore the potential of integrating fuzzy logic with PID control to enhance system adaptability and flexibility. Additionally, the ESP8266 is capable of handling the computations required for fuzzy-PID control while being cost-effective.

关键词： Fuzzy logic PI control Microcontrollers 2-DOF Manuals Manipulators Three-dimensional printing PD control Root mean square Tuning

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