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5th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2023

作者： Tufekci, Zehra Erdemir, Gokhan Istinye University Department of Computer Engineering İstanbul Turkey University of Tennessee at Chattanooga Dep. of Engineering Management & Technology Tennessee United States

ISBN: (纸本)9798350337525

Interacting with their workspace, detecting obstacles, and real-time path planning in the field to reach the goal in the unknown environment are current working areas of mobile robotics. Working in an unknown environment with dynamic obstacles is a challenging topic for autonomous robots, which need to protect themselves from the dynamic obstacles they encounter, not damage the obstacle, and re-plan their path according to their new position. This study performed an experimental comparison of three different global planners for trajectory planning of mobile robots in an unknown environment with dynamic obstacles. Global Planner, Carrot Planner, and NavfnROS planners in the ROS package were used as global planners in two different mazes with dynamic obstacles. The durations from the start to the goal point in the two designed environments were determined for each global planner. © 2023 IEEE.

关键词： Motion planning

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Smart Healthy Schools: An IoT-enabled concept for multi-room dynamic air quality control

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Internet of Things and Cyber-Physical Systems 2024年第1期4卷 24-31页

作者： Zivelonghi, Alessandro Giuseppi, Alessandro Dep. of Applied Mathematical Science IIS "Calabrese-Levi" VR San Pietro in Cariano Italy PowerConsulting Studio San Pietro in Cariano Verona Italy Dept. of Computer Control and Management Engineering University of Rome "La Sapienza" Via Ariosto 25 Rome00185 Italy

Smart Healthy Schools (SHS) are a new paradigm in building engineering and infection risk control in school buildings where the disciplines of Indoor Air Quality (IAQ), IoT (Internet of Things) and Artificial Intelligence (AI) merge together. In the post-pandemic era, equipping schools with a network of smart IoT sensors has become critical to aspire for the optimal control of the IAQ and lowering the airborne infection risk of several pathogens, indirectly related to cumulated human emitted CO2 levels over time. Thermal energy waste in winter due to improved air renewal remains of major concern but can be well monitored within a SHS monitoring architecture thanks to the flexibility of the LoRaWAN protocol able to process also a large amount of energy and climatic data at room and building scale. In this work, we report the design of the AulaSicura platform, an IoT control system co-designed by the main author and Gizero Energie to implement the SHS paradigm via clearly visible (and audible) alarm signalling in existing and new school buildings. The cloud-based LoRa system is capable of continuous and simultaneous monitoring of a variety of sensors and IAQ parameters including indoor/oudoor temperatures, rel. humidities and human-emitted excess CO2. The multi-room monitoring concept of indoor-CO2 levels allows centralized control of natural ventilation levels in individual classrooms and can handle (quasi)-real-time data, relevant for data post-processing and future developments in (quasi)-real-rime assessment of IAQ and infection risk levels at single room scale. The sensor network is also extensible to up to one thousand of classrooms per LoRa-node allowing centralized control of entire school districts at an urban scale. Moreover, through Modbus-LoRa I/O converters, AulaSicura can also control the same amount of mechanical ventilation units per node either in pure or hybrid mechanical ventilation modes. © 2023 The Authors

关键词： Internet of things

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Fault-Tolerant FPGA-Based System for Mitigating SEUs in Configuration and User Bits

Fault-Tolerant FPGA-Based System for Mitigating SEUs in Conf...

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2024 International Conference on Microelectronics, ICM 2024

作者： Amer, O.T. Alkady, G.I. Mohamed, F.Y. Mahmoud, A.W. Amer, H.H. Daoud, R.M. Cairo University Communication & Computer Eng. Dep. Faculty of Engineering Cairo Egypt American University in Cairo Electronics & Communications Engineering Department Sead Group Cairo Egypt

ISBN: (纸本)9798350379396

This paper addresses two issues. First, in the context of factory automation, a low-cost fault-tolerant sensor system is proposed along with its FPGA-based voter. Second, the voter itself is designed to recover from failures affecting its own circuitry. The sensor system consists of one high-quality sensor used for measurement along with two functionally identical, but lower cost sensors used for monitoring purposes. A biased voter circuit is designed and implemented on the same Field Programmable Gate Array (FPGA) used to house the controller. It is shown that the voter can detect and recover from Single Event Upsets (SEUs) which often occur in the harsh factory environments. Both FPGA configuration and user bits are protected. It was shown that the proposed design requires less resources and power than some other designs presented in the literature. Focusing next on recovering from SEUs in both user and configuration FPGA bits, another use case is investigated, namely an I2C master;it is shown that the proposed design again requires less resources than some other commonly used techniques. Both proposed designs were implemented on the Xilinx Zynq-7000 (xc7z020clg400-1). © 2024 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Maximize Leader Election Algorithm Performance in Bi-Directional Ring Networks With Both Links Down Between Two Nodes 25

Maximize Leader Election Algorithm Performance in Bi-Directi...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Al Refai, Mohammed N. Fawareh, Hamed Aljawawdeh, Hamzeh Alshraiedeh, Fuad Sameh Al-Quraan, Mohammad Al-Odat, Hisham Ali Otoom, Ahmed Jamhawi, Zeyad M. Kanan, Mohammad Zarqa University Software Engineering Dep. Zarqa Jordan Zarqa University Zarqa Jordan Applied Science Private University Department of Cyber Security Amman Jordan Applied Science Private University Department of Computer Science Amman Jordan University of Business and Technelogy Dep. of Industry Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

The process of selecting a leader to avoid instability in distributed system network after leader failure is called Leader Election Algorithm (LEA). This process becomes more complicated when it faces intermittent or complete links disconnected. the network becomes a one-way behavior if both lines of communication between two points are disrupted and thus the network becomes very slow, especially in systems where time is a critical issue, and the process of communication between points becomes much slower if the network leader is next to the fault or close to it, so the criteria will be established to ensures that the system leader in the Bidirectional ring communication network is in a place that allows next leader to communicate with all points as quickly as possible, and this will be during the election *** research presents a solution for leader failure problem in bidirectional ring network. This research takes into account the existence of intermittent or disconnection links between nodes. It will produce three algorithms to determine a new leader in the network with maximum network performance. It uses the least probability of time steps and the number of messages needed to elect the new leader in bidirectional ring network with N communicated nodes. so that the system remains able to work and communicate with its best capacity during this problem with the number of message complexity O(N) in the worst case. The third scenario minimizes the value of proper leader ID IDCurrent/IDCurrent-idStepCount', and maximizes the value of proper leader place N - (N - nStepCount). © 2024 IEEE.

关键词： Artificial intelligence

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Partially isolated three-port converter for electric vehicle charging applications 25

Partially isolated three-port converter for electric vehicle...

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25th International Middle East Power System Conference, MEPCON 2024

作者： Galal, Omar Yasser Abdelsalam, Ibrahim Marei, Mostafa I. Ain Shams University Faculty of Engineering Electrical Power and Machines Department Cairo Egypt Arab Academy for Science Technology & Maritime Transport College of Engineering & Technology Electrical and Control Engineering Dep. Cairo Egypt

ISBN: (纸本)9798350379648

This proposal investigates an energy management control strategy for a single stage off-board electric vehicle charger. The charger topology is a three-port dc-dc-dc converter (TPC) of the partially isolated type. This converter links two dc sources at different voltage levels with common ground and an isolated output EV battery dc port. The TPC is primarily derived from the integration of an interleaved boost with the series resonant dual active bridge (DAB) topology. The phase shift combined with pulse width modulation (PSM+ PWM) technique is utilized to achieve flexible power management strategy among three ports. Operating principles of the converter are discussed with the aid of steady state waveforms. A PSCAD-based simulation program is used for assessing the dynamics of this control system and verifying its effectiveness for photovoltaic (PV) powered off-board electric vehicle charger applications. © 2024 IEEE.

关键词： DAB Electric vehicle interleaved boost Off-board charger resonant converter three-port dc-dc converter

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Fine-Tuning Pre-Trained Models for Automated Analysis of Ophthalmic Imaging in Diagnosing Eye Diseases 24

Fine-Tuning Pre-Trained Models for Automated Analysis of Oph...

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24th International Arab Conference on Information Technology, ACIT 2023

作者： Al Mamlook, Rabia Emhamed Nasayreh, Ahmad Gharaibeh, Hasan Aljaidi, Mohammad Al-Na'amneh, Qais Alzu'bi, Dalia Bzizi, Hanin Abdeltawab, Abdelrahman Trine University Dep. of Business Administration Indiana United States University Zawia Department of Industrial Engineering Tripoli Libya Yarmouk University Dep. Computer Science Irbid Jordan Zarqa University Dep. of Computer Science Zarqa Jordan Applied Science Private University Dep. of Cyber Security Amman Jordan Concordia University Dep. Information and Systems Engineering Montreal Canada Western Michigan University Dep of Biomedical Science KalamazooMI49008 United States Bani Sweif University Faculty of Pharmacy Bani Suwayf Egypt

ISBN: (纸本)9798350384307

This paper searches into the convergence of such ad-vanced techniques with architectures like DenseNet201, VGG16, InceptionResNetV2, and NasNetMobile. Our focus centers on harnessing deep learning capabilities for the precise detection of eye ailments. Preliminary findings spotlight a notable uplift in diagnostic precision. Among the tested algorithms, the Nas-NetMobile architecture emerged superior, boasting an impressive accuracy rate of 92% on the chosen dataset. Through this work, we extend a significant advancement in the realm of automated eye disease diagnosis, potentially equipping medical professionals with sharper, swifter diagnostic tools. The outcomes presented herein could play a seminal role in sculpting more sophisticated and precise diagnostic approaches within ophthalmology. © 2023 IEEE.

关键词： Deep Learning Eye Disease Fine Tuning Transfer Learning

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PV Grid Forecasting Analysis using Artificial Neural Network

PV Grid Forecasting Analysis using Artificial Neural Network

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International Middle-East Power System Conference, MEPCON

作者： Mohamed R. Aboelmagd Ali Selim Mamdouh Abdel-Akher Department of Electrical Engineering Faculty of Engineering Aswan University Aswan Egypt Department of Control and Computer Engineering Dep. Almaaqal University Basra Iraq

ISBN: (数字)9798350379648

ISBN: (纸本)9798350379655

In addition to its use in building and agriculture, global solar irradiance is one of the most critical aspects in designing and considering any solar station's volume. Because the Iraqi metrological organization and seismology lack exact information regarding irradiance, this project aims to use historical global data, develop numerical analysis using artificial neural networks, and forecast hourly irradiance. The test is run over Basra to determine references to their nearest places. The learning technique in this study is a forward neural network (FNN) and time series neural network. Their comparison dep.nds on seven input variables: temperature, wind speed, wind direction, sunshine duration, and date. One of the most essential integrated and impactful events for managing the system of new and renewable energy sources in the power grid is accurate solar energy forecasting. The study offers a valuable method for forecasting solar energy generation using neural networks. It is difficult to apply neural networks to anticipate PV power generation because of the unpredictability of variations in the weather; unlike traditional mathematical models, which struggle to handle complicated nonlinear interactions and provide poor predictions, neural network approaches achieve superior prediction performance. The suggested forecasting model based on neural networks provides a practical means of raising the accuracy of PV generation estimation

关键词： Renewable energy sources Accuracy Wind speed Time series analysis Production Artificial neural networks Power system stability Mathematical models Forecasting Wind forecasting

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Comparative Analysis of ML Algorithms for Fraud Detection

Comparative Analysis of ML Algorithms for Fraud Detection

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Smart Information Systems and Technologies (SIST), IEEE International Conference on

作者： Gulnara Abitova Miras Abalkanov Dep. of Eletrical Engineering and Computer Science Dep. of Computer Engineering State University of New York Astana IT University Binghamton NY USA Dep. of Eletrical Engineering and Computer Science Dep. of Computer Engineering State University of New York Astana IT University Astana Kazakhstan Department of Computer Engineeering Astana IT University Astana Kazakhstan

ISBN: (数字)9798350374865

ISBN: (纸本)9798350374872

The challenge of credit card fraud presents a significant threat to both consumers and financial institutions alike, leading to substantial economic detriment. In response, this research applies various machine learning strategies to sift through transactional data for the identification of fraudulent activities. Specifically, we employ logistic regression, decision trees, and random forest algorithms to analyze a compiled dataset of genuine and deceptive transactions. This dataset undergoes segmentation into training and testing phases, allowing for a comprehensive assessment of each algorithm's effectiveness. The determination of accuracy scores across these phases serves as a metric for model evaluation. The findings lay down an essential groundwork for ongoing exploration into leveraging machine learning for the mitigation of credit card fraud. The integration of these analytical models promises to bolster the fraud detection capabilities of both financial entities and individual cardholders, significantly reducing the incidence of financial loss.

关键词： Training Logistic regression Machine learning algorithms Accuracy Sensitivity Credit cards Fraud

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A Proposed Approach for Risk Planning and Management 25

A Proposed Approach for Risk Planning and Management

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Al Refai, Mohammed N. Al-Smadi, Yazan Al-Momani, Adai Jamhawi, Zeyad M. Otoom, Ahmed Ali Atoum, Issa Yaseen, Ahid Ababneh, Jafar Kanan, Mohammad Zarqa University Software Engineering Dep. Zarqa Jordan Zarqa University Department of Computer Science Zarqa Jordan Applied Science Private University Department of Computer Science Amman Jordan Applied Science Private University Department of Cyber Security Amman Jordan Philadelphia University Faculty of Information Technology Software Engineering Department Jordan Zarqa University Department of Cyber Security Zarqa Jordan University of Business and Technelogy Dep. of Industry Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

Project Risk management is the process of identifying, evaluating, avoiding, or reducing risks. Where there is no software project without risks existence are natural in the context of project planning and management. This study focuses on proposing an enhanced risk management approach where testing phases were added to make the risk management process more effective by proposing solutions to many mistakes and challenges that occur through dealing with risks. The proposed approach focuses on dealing with risks that cannot be easily defined, more accurate risk evaluation, planning, and managing risk coordinated with a contingency plan. © 2024 IEEE.

关键词： Project management

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A Three-Phase Interleaved AC-DC Converter Based Electric-Vehicle Off-Board Battery Charger Station 6

A Three-Phase Interleaved AC-DC Converter Based Electric-Veh...

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6th International Youth Conference on Radio Electronics, Electrical and Power engineering, REEPE 2024

作者： Alajmi, Bader N. Abdelsalam, Ibrahim Marei, Mostafa I. Ahmed, Nabil A. Electrical Engineering Technology Department College of Technological Studies Shuwaikh Kuwait College of Engineering Technology. Arab Academy for Science Technology Maritime Transport Electrical and Control Engineering Dep. Cairo Egypt Faculty of Engineering Ain Shams University Electrical Power and Machines Department Cairo Egypt

ISBN: (纸本)9798350382891

This paper presents a universal off-board charger for electrical vehicles (EVs), that can charge different categories of EVs, from light low-voltage EVs to heavy high-voltage EVs. The proposed off-board battery charger is based on an interleaved AC-DC converter such that each supply phase is connected to an interleaved buck-boost converter through an isolating transformer followed by a bridge rectifier. To ensure of stable operation of the proposed charger, the control strategy contains three flowed control loops. The outer loop is to regulate the charger output voltage. While the middle-cascaded loop is for battery charging current control, the last control loop is used to ensure that the grid current is sinusoidal at the unity power factor. The performance of the off-board battery charger and its capability to operate as a level '3' charger with a wide voltage range is tested using PSCAD/EMTDC simulation software. © 2024 IEEE.

关键词： Charging (batteries)

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