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29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024

作者： Melo, Eduardo Pinto, Rui Tavares, Pedro University of Porto Dept. of Electrical and Computer Engineering Faculty of Engineering Porto Portugal Faculty of Engineering University of Porto Systec Arise Porto Portugal Sarkkis Robotics Porto Portugal

ISBN: (纸本)9798350361230

The rapid growth of the robotics field is driven by increasing demand for enhanced performance, characterized by high reliability and repeatability capabilities. As industries strive to maintain elevated quality performance throughout their production pipelines, the complexity of the challenges they face grows in tandem. This complexity extends to processing algorithms, needing greater computational power for faster and more effective solutions. In this context, emerging technologies such as Cloud Computing present promising opportunities to augment planning tasks in robotics. This literature review explores the intersection of robotics and Cloud Computing, investigating how leveraging cloud resources can enhance planning performance in response to evolving industry demands. © 2024 IEEE.

关键词： Cloud platforms

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Control Aspects in Programming by Demonstation for Robotic Deep- Micro- Hole Drilling 32

Control Aspects in Programming by Demonstation for Robotic D...

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32nd Mediterranean Conference on Control and Automation, MED 2024

作者： Maric, Bruno Petric, Frano Orsag, Matko University of Zagreb LARICS Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing Zagreb10000 Croatia

ISBN: (纸本)9798350395440

This paper explores control aspects in a collab-orative robotic system designed to replicate human operators' drilling skills in deep- micro- hole tasks, focusing on the glass-container mould industry. To replicate human performance, we develop a single-DOF Impedance-based drill controller for a standard industrial position-controlled robot, enhancing safe and smooth interactions between the drill bit and the mould. To address high feed rates observed in worker demonstrations and prevent bit breaks, we focus on minimizing non-axial motion during drilling on an off-the-shelf available industrial manipulator KUKA KR 10. This involves analyzing the impact of joint dynamics on drill motion and designing a control system for the robot's low-level control to achieve axial drill motion. We show that the proposed joint control system that takes into account relationship between joint and tool dynamics outperforms available robot low-level control in minimizing non-axial motion, leading to the robot being able to outperform the human in deep- micro- hole drilling. © 2024 IEEE.

关键词： Molds

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Texture Features-Based Machine Learning for Classification of Cervical Cell Microscopic Images 1

Texture Features-Based Machine Learning for Classification o...

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1st International Conference of Adisutjipto on Aerospace electrical engineering and Informatics, ICAAEEI 2024

作者： Jusman, Yessi Rahmawati, Maryza Intan Sulaiman, Siti Noraini Universitas Muhammadiyah Yogyakarta Faculty of Engineering Center of Artificial Intelligence and Robotics Studies Department of Electrical Engineering Yogyakarta Indonesia Universiti Malaysia Perlis Faculty of Electrical Engineering and Technology Department of Mechatronic Engineering Perlis Malaysia College of Engineering Universiti Teknologi Mara Electrical Engineering Studies Penang Malaysia

ISBN: (纸本)9798331507930

Machine learning has been developed in biomedical science as a clinical decision-support technique. It can automatically recognize patterns in a given dataset to perform predictions and data classification. It has been widely applied to detect abnormalities in various diseases by leveraging texture-based features. This study utilized a Histogram of Oriented Gradients (HOG) as a feature extraction method and a Support Vector Machine (SVM) for classification in detecting the level of cancer abnormalities in cervical cells. The dataset of cervical cell microscopic images consisted of 972 images for training and 108 for testing. Among the models used, the Medium Gaussian SVM achieved the best performance, with a training accuracy of 73.3% and the fastest training time of 4.123 seconds. Whereas, the best performance matrix of testing results achieved 81.10% of accuracy. These results highlight the potential of the proposed method in improving cervical cancer detection through automated and efficient classification techniques. © 2024 IEEE.

关键词： Adversarial machine learning

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Evaluation of Image Enhancement Techniques for Improving Skin Cancer Image Processing

Evaluation of Image Enhancement Techniques for Improving Ski...

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2024 International Conference on Information Technology and Computing, ICITCOM 2024

作者： Jusman, Yessi Tyassari, Wikan Husnaa, Aafiyah Namyra, Dhea Hanafi, Muhammad Ali Nur, Firmansyah Olga Pangestu, Jihan Center of Artificial Intelligence and Robotics Studies Universitas Muhammadiyah Yogyakarta D.I. Department of Electrical Engineering Yogyakarta Indonesia Faculty of Electrical Engineering and Technology Arau02600 Malaysia Universitas Muhammadiyah Yogyakarta D.I. Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350379839

Skin cancer is a noncontagious but dangerous disease characterized by its ferocity and speed to spread to other parts of the body, causing death for the sufferers. Indonesia is a tropical climate country with extremely high sun exposure, which is a significant contributing factor to the development of skin malignancy. Melanoma is the most common skin cancer in Indonesia, reaching 1,609 cases in 2020. Manual detection of skin cancer relies heavily on the skills of observers, raising the possibility of errors. This study utilized three classes of skin cancer: melanoma, nevus, and seborrheic keratosis. Two kinds of noise were employed: Salt and Pepper and Gaussian. The results of the noisy images underwent processing to determine the most effective filter for all noise types. The Gaussian filter depicted better performance in reducing noise, especially Salt and Pepper noise. However, both the average filter and the Gaussian filter exhibited similar performance in reducing Gaussian noise. © 2024 IEEE.

关键词： Salt and pepper noise

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General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action

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engineering 2024年第2期33卷 63-76页

作者： Heye Huang Yicong Liu Jinxin Liu Qisong Yang Jianqiang Wang David Abbink Arkady Zgonnikov School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China Department of Cognitive Robotics Faculty of MechanicalMaritime and Materials Engineering(3mE)Delft University of TechnologyDelft 2628Netherlands Department of Software Technology Faculty of Electrical EngineeringMathematics and Computer ScienceDelft University of TechnologyDelft 2628Netherlands Xi’an Institute of High-Technology Xi’an 710051China

This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and ***,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road *** coordinates are then transformed to achieve the curvature continuity of the generated *** the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate ***,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and *** simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic ***,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.

关键词： Autonomous vehicle Trajectory planning Multi-performance objectives Principle of least action

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Remote Monitoring and Control for a Lab-Scaled Valve Control System 10

Remote Monitoring and Control for a Lab-Scaled Valve Control...

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10th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2024

作者： Ali, Abdul Malik Bin Mohd Sahlan, Shafishuhaza Yunus, Mohd Amri Md. Rosli, Khairul Ijlal Gen, Ng Zi Manaf, Mohamad Shukri Abdul Electrical Electronic & Automation Section Kedah 0900 Malaysia Universiti Teknologi Malaysia Centre for Artificial Intelligence and Robotics Faculty of Electrical Engineering Johor Malaysia Universiti Teknologi Malaysia Faculty of Electrical Engineering Johor Malaysia ZEC Engineering Sdn. Bhd. Johor Bahru Malaysia

ISBN: (纸本)9798350365283

In this paper, an automated control valve system utilizing the Panasonic Programmable Logic Controller (PLC) AFPSWC is developed. Panasonic Control Web Creator software is used to develop the Supervisory Control and Data Acquisition (SCADA) system for remote control and monitoring purposes. To increase the efficiency of the operator, a user-friendly Human Machine Interface (HMI) is developed for the system. The lab-scaled control valve system consists of a supply tank, a reservoir tank, a control valve with a positioner, water level sensors, flow rate sensor and motor pump. The water level in the reservoir tank will be controlled by regulating the percentage of the control valve opening. The parameters such as incoming water flow rate, water levels in the supply tank and reservoir tank, incoming and outgoing motor frequencies and percentage of valve opening will be analysed. The communication protocol, Ethernet/IP is used to set up communication between the PLC and devices for remote monitoring and control purposes. The customized HMI can monitor the physical parameters in real time, while the predetermined water volume and motor pump frequencies can be controlled remotely. With the implementation of the remote monitoring system, the efficiency of the system is 97.6%. © 2024 IEEE.

关键词： Remote control

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Remote Automated Control and Monitoring Water Distribution System Utilizing A 3-Way Valve Logic on ThingsBoard Platform 10

Remote Automated Control and Monitoring Water Distribution S...

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10th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2024

作者： Sahlan, Shafishuhaza Nik Nazaruddin, Nik Muhammad Adib Hakimy Yunus, Mohd Amri Md. Rosli, Khairul Ijlal Jamali, Annisa Manaf, Mohamad Shukri Abdul Universiti Teknologi Malaysia Centre for Artificial Intelligence and Robotics Faculty of Electrical Engineering Johor Malaysia Universiti Teknologi Malaysia Faculty of Electrical Engineering Johor Malaysia ZEC Engineering Sdn. Bhd. Johor Bahru Malaysia Universiti Malaysia Sarawak Faculty of Engineering Sarawak Kota Samarahan Malaysia

ISBN: (纸本)9798350365283

In this paper, an automated Lab-scaled Valve control system for Water Distribution System (WDS) that mimics real-world conditions is presented. The system utilises ThingsBoard software as the Supervisory Control and Data Acquisition (SCADA) system and PANASONIC Programmable Logic Controller (PLC) FP7 CPS31 as the master controller. The lab-scaled system consists of reservoir tank, supply tank, variable speed drives (VSD), flow rate sensors, and level sensors. Meanwhile ThingsBoard software provides an intuitive monitoring purposes and by using the application of Node-RED, it can develop an alternative Human Machine Interface (HMI) for remote control. By modifying the motor speed, which is managed by the VSD, the automated algorithm in the PLC makes use of sensor relationships to regulate the water level in the distribution reservoir tank. For water flow rate in pipes, the incoming flow rate is analysed in relation to the height of the reservoir tank. As a result, an automated control system that is capable of remote monitoring, controlling, and gathering data for the lab-scale WDS is successfully developed. © 2024 IEEE.

关键词： Programmable logic controllers

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Data augmentation and denoising of computed tomography scan images in training deep learning models for rapid COVID-19 detection

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International Journal of Business Intelligence and Data Mining 2024年第2期24卷 203-216页

作者： Mubarak, Auwalu Saleh Serte, Sertan Al-Turjman, Fadi Ameen, Zubaida Sa'Id Artificial Intelligence Engineering Department AI and Robotics Institute Near East University Mersin10 Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Mersin10 Turkey Department of Electrical and Electronics Engineering Near East University Mersin10 Turkey

The deadly respiratory disease corona virus-2 (COVID-19) which was declared a pandemic by the World Health Organization (WHO) has resulted in over a million deaths around the world within less than a year. With the rapid spread of the virus, the currently adopted COVID-19 test by the WHO is the reverse transcription polymerase chain reaction (RT-PCR) test, which is expensive, time-consuming and not accessed by underdeveloped countries. Computed tomography (CT) scan images that were used in profiling suspected COVID-19 patients can serve as an alternative to the RT PCR test method. In this study, two different pre-Trained deep learning models ResNet-50 and ResNet-101 were trained to classify positive COVID-19 scan images. The best model which was trained on the augmented CT scan images achieved an accuracy of 98.3%, a sensitivity of 0.984, specificity of 0.983. © 2024 Inderscience Enterprises Ltd.. All rights reserved.

关键词： COVID-19

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Magnetic Flux Servoing for Precise Localization Based on Gradient Tensor Contractions 19

Magnetic Flux Servoing for Precise Localization Based on Gra...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Martinovic, Dean Orsag, Matko University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Zagreb10000 Croatia

ISBN: (纸本)9798350320695

This paper focuses on bridge inspections performed by intelligent unmanned aerial vehicles (UAV). For this, small data loggers are placed by the UAVs at the bridge, which have to be removed later. In our previous work we presented the magnetic localization method SRIOD, which not only detects the center of the data logger but also its orientation. In this work we proof SRIOD in a real application and let a robotic arm locate a magnetic target. The hardware involved is presented including the control strategy for the robot. The motions of the robot and the magnetic target are captured with 12 Optitrack cameras in order to validate the localization quality. © 2023 IEEE.

关键词： Antennas

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Parameterization of Circuit Breakers for HVDC Transmission Line Between Egypt and the Kingdom of Saudi Arabia Toward Restriking Voltage

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IEEE Access 2024年 12卷 18259-18269页

作者： Eliyan, Tamer Elsisi, Mahmoud Alghaythi, Mamdouh L. Alshammari, Meshari S. Wadie, Fady Benha University Faculty of Engineering at Shoubra Department of Electrical Engineering Cairo 11629 Egypt Higher Institute of Engineering at El-Shorouk City Alshorouk Academy Department of Electrical Power and Machines Engineering Cairo 11837 Egypt National Kaohsiung University of Science and Technology Department of Electrical Engineering Kaohsiung 807618 Taiwan Jouf University College of Engineering Department of Electrical Engineering Sakaka 72388 Saudi Arabia Egyptian Russian University Faculty of Engineering Mechatronics and Robotics Engineering Department Badr City 11829 Egypt

The high voltage direct current (HVDC) transmission lines represent the prospective way for long-distance transmission between countries, remote areas, and offshore wind farms to decrease power loss. However, the HVDC protection systems have many challenges against any system issue, such as maintenance and short circuits. Thus, the vital role played by high voltage direct current circuit breaker CB has made it the center of attention in HVDC protection systems. The main challenge in HVDC CB is the lack of naturally exiting current zero that allows the breaker to extinguish the arc during the opening process. Thus, a commutation L-C circuit is required to inject an oscillating current and enforce a zero-crossing. Nevertheless, the L-C branch is affected directly by the arcing time, the transient recovery voltage (TRV), and the rate of rise of recovery voltage (RRRV). This paper investigates the parametric uncertainties of L-C and SF6 mechanical interrupters, including cooling power and arc time constant upon TRV and RRRV, based on Mayr's black-box model. Furthermore, a part of 3000 MVA, 500 kV HVDC transmission line between Egypt and the Kingdom of Saudi Arabia is used as a testing system employing ATP/EMTP software package to demonstrate the effect of CB's parameters variations. The results indicate that the capacitance represents the major parameter having a direct impact on TRV and RRRV. In essence, the proper parameterization of the CB is highly required in the design process of HVDC CB to enhance the decision-making and ensure that the L-C is capable of reducing arcing time and TRV simultaneously. © 2013 IEEE.

关键词： arcing time black-box arc model circuit breakers HVDC protection systems RRRV Transmission lines TRV

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