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19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022

作者： Hichri, Amal Hajji, Mansour Mansouri, Majdi Bouzrara, Kais Nounou, Hazem Nounou, Mohamed Higher Institute of Applied Sciences and Technology of Kasserine Kasserine Tunisia Electrical and Computer Engineering Program Texas A&m University at Qatar Doha23874 Qatar Prince Sultan University Department of Mathematics and Sciences Riyadh11586 Saudi Arabia Signal Processing and Image National Engineering School of Monastir Research Laboratory of Automation 5019 Tunisia Chemical Engineering Program Texas A&m University at Qatar Doha23874 Qatar

ISBN: (数字)9781665471084

ISBN: (纸本)9781665471084

Photovoltaic (PV) system fault diagnosis is crucial because it helps PV system operators reduce energy and income losses. It also decreases the risk of fire and electric shock from PV system failures. Thus, the implementation of fault diagnosis tool is required. The most well-known techniques are machine learning models. Although these techniques provided well in terms of diagnosis and classification accuracy, they rely on manual feature extraction, which is time consuming, expensive, and requires diagnostic skill. Manual feature extraction is a problem that has to be addressed. This paper therefore presents a PV system fault diagnosis techniques that can automatically extract features from raw data in order to classify PV system faults. The implemented methods include long short-term memory (LSTM) bidirectional long short-term memory (BiLSTM) networks, which are deep learning based algorithms. Finally, the presented fault diagnosis approaches showed a good diagnosis performances when applied to an emulated GCPV system. © 2022 IEEE.

关键词： Failure analysis

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A Hybrid BCI for Robotic Device Navigation

A Hybrid BCI for Robotic Device Navigation

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Annual Conference on Information Sciences and Systems (CISS)

作者： Yih-Choung Yu Hayden Fisher Angela Busheska Lily Thompson Lisa Gabel Dept. of Electrical and Computer Engineering Lafayette College Easton PA USA Children’s Hospital of Philadelphia Philadelphia PA USA Neuroscience Program Lafayette College Easton PA USA Dept. of Psychology & Neuroscience Program Lafayette College Easton PA USA

Applications of brain-computer interface (BCI) systems have grown in importance for assisting individuals with severe motor disabilities in navigating our increasingly technologically dependent society. With applications such as electric wheelchairs and advanced prosthetics in mind, the goal of this research is to develop a system that enables the use of electroencephalographic (EEG) and electromyographic (EMG) signals to control the movement of a robot. An EEG cap was used to obtain occipital alpha power density, frontal muscular artifacts, and sensorimotor mu rhythms, which were then sent back to a PC via Bluetooth for further processing. Signal-processing algorithms and models were developed and implemented to determine the user’s mental activity and send signals to the external physical device. The preliminary results from the pilot experiments were very promising. The algorithms will be implemented for real-time signal processing and tested with a BCI-controlled robotic device.

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A critical review of the integration of renewable energy sources with various technologies

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Protection and Control of Modern Power Systems 2021年第1期6卷 37-54页

作者： Erdiwansyah Mahidin H.Husin Nasaruddin M.Zaki Muhibbuddin Doctoral Program School of EngineeringUniversitas Syiah KualaBanda Aceh23111Indonesia Faculty of Engineering Universitas Serambi MekkahBanda Aceh23245Indonesia Department of Chemical Engineering Universitas Syiah KualaBanda Aceh23111Indonesia Department of Electrical and Computer Engineering Universitas Syiah KualaBanda Aceh23111Indonesia Department of Mechanical and Industrial Engineering Universitas Syiah KualaBanda Aceh23111Indonesia

Wind power, solar power and water power are technologies that can be used as the main sources of renewable energy so that the target of decarbonisation in the energy sector can be achieved. However, when compared with conventional power plants, they have a significant difference. The share of renewable energy has made a difference and posed various challenges, especially in the power generation system. The reliability of the power system can achieve the decarbonization target but this objective often collides with several challenges and failures, such that they make achievement of the target very vulnerable, Even so, the challenges and technological solutions are still very rarely discussed in the literature. This study carried out specific investigations on various technological solutions and challenges, especially in the power system domain. The results of the review of the solution matrix and the interrelated technological challenges are the most important parts to be developed in the future. Developing a matrix with various renewable technology solutions can help solve RE challenges. The potential of the developed technological solutions is expected to be able to help and prioritize them especially cost-effective energy. In addition, technology solutions that are identified in groups can help reduce certain challenges. The categories developed in this study are used to assist in determining the specific needs and increasing transparency of the renewable energy integration process in the future.

关键词： Integration RE Energy source Technology system energy Power system Variable RE

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Traffic-Aware Beacon Interval for Position-Based Protocols in VANETs

Traffic-Aware Beacon Interval for Position-Based Protocols i...

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IEEE Latin-American Conference on Communications, LATINCOM

作者： Alvaro T. Amaya Alexandre A. P. Pohl Mauro S. Fonseca Ricardo Lüders Graduate Program in Electrical and Computer Engineering (CPGEI) Universidade Tecnológica Federal do Paraná (UTFPR) Curitiba Brazil

Position-based protocols in vehicular ad-hoc networks (VANETs) depend on the transmission of periodic beacon messages to keep the nodes informed about the current position of their neighbors. However, an excessive load of beacons can drastically deteriorate the network performance. This work presents a novel adaptive vehicular traffic-aware strategy to compute the beacon interval in a position-based protocol. The strategy relies on three mobility factors: vehicular density, the mean difference of speed among neighbors, and the spatial distribution of neighbors. Its effectiveness is proven through extensive simulations in an urban mobility scenario using the packet delivery ratio, the average end-to-end delay, overhead, and processing time as the performance metrics. The results show that our approach maintains a high delivery ratio and low End-To-End delay, overhead, and processing time regardless of the density of the surrounding vehicular traffic. The results also show that our method uses the available beacon interval range more efficiently than another traffic-aware approach.

关键词： Measurement Adaptation models Graphical models Computational modeling Collaboration Routing protocols Delays

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State of The Art: Fragility Function of electrical Power System

State of The Art: Fragility Function of Electrical Power Sys...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Elvy Sahnur Nasution Syahrial Syahrial Ira Devi Sara Yuwaldi Away Doctoral Program Postgraduate School of Engineering Universitas Syiah Kuala Universitas Muhammadiyah Sumatera Utara Banda Aceh Indonesia Dept. Electrical and computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia

Natural disasters, particularly earthquakes, can cause the electric power system to collapse, which can be brought on by one of the infrastructure breakdowns in the power system. Damaged power system can cause losses to electricity providers, electricity users, so it is necessary to understand the vulnerability of electric power system assets to earthquakes. The research fragility function presents the concept of fragility function in power system of the entire power system, showed fragility of power plant, transmission line, tower transmission, transformers, generator, and substation. Substation is more fragile than the others because substation consist of circuit breaker and disconnecting switch the most fragile asset. In addition, this paper also presents how to creating the fragility function and several solutions to increase the resilience of the electric power system to earthquakes.

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Convergence of Bi-Virus Epidemic Models with Non-Linear Rates on Networks - A Monotone Dynamical Systems Approach

arXiv

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arXiv 2022年

作者： Doshi, Vishwaraj Mallick, Shailaja Eun, Do Young The Operations Research Graduate Program The Department of Computer Science The Department of Electrical and Computer Engineering North Carolina State University RaleighNC United States

We study convergence properties of competing epidemic models of the Susceptible-Infected-Susceptible (SIS) type. The SIS epidemic model has seen widespread popularity in modelling the spreading dynamics of contagions such as viruses, infectious diseases, or even rumors/opinions over contact networks (graphs). We analyze the case of two such viruses spreading on overlaid graphs, with non-linear rates of infection spread and recovery. We call this the non-linear bi-virus model and, building upon recent results, obtain precise conditions for global convergence of the solutions to a trichotomy of possible outcomes: a virus-free state, a single-virus state, and to a coexistence state. Our techniques are based on the theory of monotone dynamical systems (MDS), in contrast to Lyapunov based techniques that have only seen partial success in determining convergence properties in the setting of competing epidemics. We demonstrate how the existing works have been unsuccessful in characterizing a large subset of the model parameter space for bi-virus epidemics, including all scenarios leading to coexistence of the epidemics. To the best of our knowledge, our results are the first in providing complete convergence analysis for the bi-virus system with nonlinear infection and recovery rates on general graphs. © 2022, CC BY.

关键词： Viruses

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Additive manufacturing for multimodal photoacoustic ophthalmoscopy

Additive manufacturing for multimodal photoacoustic ophthalm...

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Photons Plus Ultrasound: Imaging and Sensing 2023

作者： Haindl, Richard Bellemo, Valentina Rajendran, Praveenbalaji Tan, Bingyao Liu, Mengyang Leitgeb, Rainer Drexler, Wolfgang Schmetterer, Leopold Pramanik, Manojit School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University 62 Nanyang Drive Singapore Singapore Centre for Medical Physics and Biomedical Engineering Medical University of Vienna Währinger Gürtel 18-20/4L Vienna Austria Program Nanyang Technological University Singapore Singapore Singapore Eye Research Institute Singapore National Eye Centre Singapore Singapore Department of Electrical and Computer Engineering Iowa State University AmesIA United States

ISBN: (纸本)9781510658639

Photoacoustic ophthalmoscopy in rodents is gaining research momentum, due to advancement in transducer shape and technology. Needle transducers emerged as most valuable tool for photoacoustic retinal imaging and have proven to be sensitive enough to resolve retinal vasculature in-vivo. Nevertheless, placement of the eye and screening of the retina remains challenging, since needle transducers must remain static during image acquisition, while the optical field of view is limited. Such restriction mandates movement of the mouse to rotate the eye and therefore the imaging area on the retina. The needle transducer needs to be temporarily detached during this process to avoid damage to the eye or the transducer. Re-attachment involves additional application of ultrasound gel and doesn’t guarantee ideal placement for optimized imaging performance. Additive manufacturing can help to tackle those challenges and allows to design novel rotational rodent holders for imaging. Hence, we present a fully 3D printable rotatable tip/tilt mouse platform with the eye in the center of rotation, combined with a printable needle transducer holder. Such system guarantees optimal placement of the needle transducer during imaging and rotation of the mouse eye, avoiding detachment of the transducer and effortless screening of the retina. The capabilities for retinal screening are demonstrated by a multimodal optical coherence photoacoustic ophthalmoscopy system employing two separated wavelengths, 1310 nm for optical coherence and 570 nm for photoacoustic ophthalmoscopy. © 2023 SPIE.

关键词： Optical tomography

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Comparison of Algebraic Reconstruction Technique Methods and Generative Adversarial Network in Image Reconstruction of Magnetic Induction Tomography (MIT)

Comparison of Algebraic Reconstruction Technique Methods and...

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2021 International Conference on Biomedical engineering, ICoBE 2021

作者： Lubis, A.J. Nasir, N.F. Mohd Zakaria, Z. Jusoh, M. Azizan, M.M. Zakaria, M.Z. Kazim, M.N.F.M. Rahman, S. Faculty of Engineering and Computer Science Universitas Harapan Medan Medan Indonesia Computer Engineering Program Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Biomedical Electronic Engineering Program Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Universiti Malaysia Perlis Perlis Malaysia Department of Electrical and Electronic Department Faculty of Engineering and Built Environment Universiti Sains Islam Malaysia Negeri Sembilan Malaysia Faculty of Mechanical Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Mechatronic Engineering Program Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Perlis Malaysia

Magnetic induction tomography (MIT) is a technique used for imaging electromagnetic properties of objects using eddy current effects. The non-linear characteristics had led to more difficulties with its solution especially in dealing with low conductivity imaging materials such as biological tissues. Two methods that could be applied for MIT image processing which is the Generative Adversarial Network (GAN) and the Algebraic Reconstruction Technique (ART). ART is widely used in the industry due to its ability to improve the quality of the reconstructed image at a high scanning speed. GAN is an intelligent method which would be able to carry out the training process. In the GAN method, the MIT principle is used to find the optimum global conductivity distribution and it is described as a training process and later, reconstructed by a generator. The output is an approximate reconstruction of the distribution's internal conductivity image. Then, the results were compared with the previous traditional algorithm, namely the regularization algorithm of BPNN and Tikhonov Regularization method. It turned out that GAN had able to adjust the non-linear relationship between input and output. GAN was also able to solve non-linear problems that cannot be solved in the previous traditional algorithms, namely Back Propagation Neural Network (BPNN) and Tikhonov Regularization method. There are several other intelligent algorithms such as CNN (Convolution Neural Network) and K-NN (K-Nearest Neighbor), but such algorithms have not been able to produce the expected image quality. Thus, further study is still needed for the improvement of the image quality. The expected result in this study is the comparison of these two techniques, namely ART and GAN to get the best results on the image reconstruction using MIT. Thus, it is shown that GAN is a better candidate for this purpose. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Generative adversarial networks

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Curriculum-Based Reinforcement Learning for an Effective Multi-Agent Path Planning Algorithm in Warehouse Scenarios

Curriculum-Based Reinforcement Learning for an Effective Mul...

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Iure Rosa L. De Oliveira Kevin B. De Carvalho Alexandre S. Brandão Graduate Program in Computer Science Universidade Federal de Viçosa Viçosa Brazil Electrical Engineering Department Universidade Federal de Vicosa Viçosa Brazil

Multi-robot systems can provide substantial increase in efficiency and/or flexibility in different scenarios. Applications in various settings have been studied in the literature, such as disaster management, surveillance, object transportation as well as search-and-rescue. A particular case that can highly benefit from the employment of multiple agents is the logistics in a warehouse scenario. This work proposes an multi-agent Q-learning based algorithm with curriculum learning and transfer learning to perform the path planning process. With progressively more complex stages of training as well as knowledge transfer from one stage to another, the algorithm is capable of achieve high success rates. In order to validate the proposed method, simulations were done to compare it to other combinations of the used techniques, as well as using Q-learning only. Scalability tests were also performed. The proposed method achieved up to 94% success rate after training.

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Advances and Challenges in Multi-Domain Task-Oriented Dialogue Policy Optimization

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APSIPA Transactions on Signal and Information Processing 2023年第1期12卷

作者： Rohmatillah, Mahdin Chien, Jen-Tzung EECS International Graduate Program National Yang Ming Chiao Tung University Taiwan Institute of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan

Developing a successful dialogue policy for a multi-domain task-oriented dialogue (MDTD) system is a challenging task. Basically, a desirable dialogue policy acts as the decision-making agent who understands the user's intention to provide suitable responses within a short conversation. Furthermore, offering the precise answers to satisfy the user requirements makes the task even more challenging. This paper surveys recent advances in multi-domain task-oriented dialogue policy optimization and summarizes a number of solutions to policy learning. In particular, the case study on the task of travel assistance using the MDTD dataset based on MultiWOZ containing seven different domains is investigated. The dialogue policy optimization methods, categorized into dialogue act level and word level, are systematically presented. Moreover, this paper addresses a number of challenges and difficulties including the user simulator design and the dialogue policy evaluation which need to be resolved to further enhance the robustness and effectiveness in multi-domain dialogue policy representation. © 2023 M. Rohmatillah and J.-T. Chien.

关键词： Reinforcement learning

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