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2024 IEEE Conference on Computational Imaging Using Synthetic Apertures, CISA 2024

作者： Choudhury, Nazia Afroz Yonel, Bariscan Yazici, Birsen Rensselaer Polytechnic Institute Electrical Computer and Systems Engineering TroyNY United States

ISBN: (纸本)9798350308648

Phaseless imaging is a prominent field of study in many imaging modalities. In practical applications, the phaseless measurements usually contain noise and outliers, limiting the reconstruction algorithms' performance. In this paper, we study the reverse Kullback-Leibler divergence (RKLD) as a robust objective function for mitigating the effects of corrupted measurements. We optimize RKLD using the state-of-the-art Wirtinger Flow (WF) algorithm for image reconstruction. Then, we numerically demonstrate the performance of RKLD using simulated coded diffraction measurements and a real optical dataset. Additionally, we compare RKLD's performance with other well-known loss functions used by the WF framework, namely, £2-intensity, Poisson, and £2-magnitude. Our simulation results demonstrate that RKLD-based optimization provides higher quality reconstructed images than the other loss functions in the presence of noise and outliers. © 2024 IEEE.

关键词： Image reconstruction

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STABILITY AND INTERACTION ANALYSIS OF GRID-FORMING TYPE IV WIND TURBINES 23

STABILITY AND INTERACTION ANALYSIS OF GRID-FORMING TYPE IV W...

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23rd Wind and Solar Integration Workshop, WIW 2024

作者： Udawatte, Harith E. Ravanji, Mohammad H. Bahrani, Behrooz Department of Electrical & Computer Systems Engineering Monash University Melbourne Australia Department of Electrical Engineering Sharif University of Technology Tehran Iran

ISBN: (纸本)9781837242689

The global shift to renewable energy, especially wind power, is critical for achieving carbon-neutral power systems but poses challenges to grid stability due to reduced system inertia from inverter-based resources. Grid-forming (GFM) control modes are emerging as key solutions to these stability issues. Given the vast potential of wind energy, ensuring that wind turbine generators (WTGs) comply with GFM control standards is essential. This paper explores GFM capabilities in Type IV WTGs, focusing on the interactions between grid-side and machine-side control dynamics. A simplified small-signal model is developed to efficiently analyse the direct coupling between active power and DC-link control, highlighting how GFM parameters like droop and inertia, along with the DC controller bandwidth, affect system stability. Time-domain simulations validate the proposed tuning guidelines and reveal distinct WTG response characteristics at different wind speeds during grid contingencies. These insights lay the groundwork for robust GFM control designs, essential for a stable integration of wind turbines into high-renewable power systems. © Energynautics GmbH.

关键词： Windmill

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RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

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2024 Prognostics and System Health Management Conference, PHM 2024

作者： Cai, Congrui Lu, Zhonghai School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Embedded Systems Master Program Sweden School of Electrical Engineering and Computer Science Department of Electrical Engineering KTH Royal Institute of Technology Sweden

ISBN: (纸本)9798350360585

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms. © 2024 IEEE.

关键词： Long short-term memory

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Intelligent Dynamic Inversion Controller Design for Ball and Beam System

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computers, Materials & Continua 2022年第8期72卷 2341-2355页

作者： Ibrahim M.Mehedi Abdulah Jeza Aljohani Md Mottahir Alam Mohamed Mahmoud Mohammed J.Abdulaal Muhammad Bilal Waleed Alasmary Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Electrical and Computer Engineering Electrical and Computer EngineeringTN38505United States Computer and Information Systems Umm Al-Qura UniversityMakkahSaudi Arabia

The Ball and beam system(BBS)is an attractive laboratory experimental tool because of its inherent nonlinear and open-loop unstable *** an effective ball and beam system controller is a real challenge for researchers and *** this paper,the control design technique is investigated by using Intelligent Dynamic Inversion(IDI)method for this nonlinear and unstable *** proposed control law is an enhanced version of conventional Dynamic Inversion control incorporating an intelligent control element in *** Moore-PenroseGeneralized Inverse(MPGI)is used to invert the prescribed constraint dynamics to realize the baseline control law.A sliding mode-based intelligent control element is further augmented with the baseline control to enhance the robustness against uncertainties,nonlinearities,and external *** semi-global asymptotic stability of IDI control is guaranteed in the sense of *** simulations and laboratory experiments are carried out on this ball and beam physical system to analyze the effectiveness of the *** addition to that,comparative analysis of RGDI control with classical Linear Quadratic Regulator and Fractional Order Controller are also presented on the experimental test bench.

关键词： Ball and beam system(BBS) unstable system internal model PD controllers IDI control robust control

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MIMO performance enhancement of MIMO arrays using PCS-based near-field optimization technique

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Science China(Information Sciences) 2023年第6期66卷 170-185页

作者： Yipeng WANG Xiaoming CHEN Huiling PEI Wei E.I.SHA Yi HUANG Ahmed A.KISHK School of Information and Communications Engineering Xi'an Jiaotong University Key Laboratory of Micro-Nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science and Electronic EngineeringZhejiang University Department of Electrical Engineering and Electronics University of Liverpool Department of Electrical and Computer Engineering Concordia University

Extensive efforts have been made in designing large multiple-input multiple-output(MIMO)arrays. Nevertheless, improvements in conventional antenna characteristics cannot ensure significant MIMO performance improvement in realistic multipath environments. Array decorrelation techniques have been proposed, achieving correlation reductions by either tilting the antenna beams or shifting the phase centers away from each other. Hence, these methods are mainly limited to MIMO terminals with small arrays. To avoid such problems, this work proposes a decorrelation optimization technique based on phase correcting surface(PCS)that can be applied to large MIMO arrays, enhancing their MIMO performances in a realistic(non-isotropic)multipath environment. First, by using a near-field channel model and an optimization algorithm, a near-field phase distribution improving the MIMO capacity is obtained. Then the PCS(consisting of square elements)is used to cover the array's aperture, achieving the desired near-field phase *** examples demonstrate the effectiveness of this PCS-based near-field optimization technique. One is a1 × 4 dual-polarized patch array(working at 2.4 GHz)covered by a 2 × 4 PCS with 0.6λ center-to-center distance. The other is a 2 × 8 dual-polarized dipole array, for which a 4 × 8 PCS with 0.4λ center-to-center distance is designed. Their MIMO capacities can be effectively enhanced by 8% and 10% in single-cell and multi-cell scenarios, respectively. The PCS has insignificant effects on mutual coupling, matching, and the average radiation efficiency of the patch array, and increases the antenna gain by about 2.5 dB while keeping broadside radiations to ensure good cellular coverage, which benefits the MIMO performance of the *** proposed technique offers a new perspective for improving large MIMO arrays in realistic multipath in a statistical sense.

关键词： antenna correlation array antenna multiple-input multiple-output (MIMO) capacity

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Semi‑supervised contour‑driven broad learning system for autonomous segmentation of concealed prohibited baggage items

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Visual Computing for Industry,Biomedicine,and Art 2024年第1期7卷 1-18页

作者： Divya Velayudhan Abdelfatah Ahmed Taimur Hassan Muhammad Owais Neha Gour Mohammed Bennamoun Ernesto Damiani Naoufel Werghi Department of Electrical Engineering and Computer Sciences Center for Cyber‑Physical SystemsKhalifa University of Science and TechnologyAbu Dhabi 127788United Arab Emirates Department of Electrical Computer and Biomedical EngineeringAbu Dhabi UniversityAbu Dhabi 59911United Arab Emirates Department of Computer Science and Software Engineering the University of Western AustraliaPerthWA 6009Australia

With the exponential rise in global air traffic,ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation *** X-ray baggage monitoring is now standard,manual screening has several limitations,including the propensity for errors,and raises concerns about passenger *** address these drawbacks,researchers have leveraged recent advances in deep learning to design threatsegmentation ***,these models require extensive training data and labour-intensive dense pixelwise annotations and are finetuned separately for each dataset to account for inter-dataset ***,this study proposes a semi-supervised contour-driven broad learning system(BLS)for X-ray baggage security threat instance segmentation referred to as *** research methodology involved enhancing representation learning and achieving faster training capability to tackle severe occlusion and class imbalance using a single training routine with limited baggage *** proposed framework was trained with minimal supervision using resource-efficient image-level labels to localize illegal items in multi-vendor baggage *** specifically,the framework generated candidate region segments from the input X-ray scans based on local intensity transition cues,effectively identifying concealed prohibited items without entire baggage *** multi-convolutional BLS exploits the rich complementary features extracted from these region segments to predict object categories,including threat and benign *** contours corresponding to the region segments predicted as threats were then utilized to yield the segmentation *** proposed C-BLX system was thoroughly evaluated on three highly imbalanced public datasets and surpassed other competitive approaches in baggage-threat segmentation,yielding 90.04%,78.92%,and 59.44%in terms of mIoU on GDXray,SIXray,and Compass-XP,***,the lim

关键词： Baggage X-ray imagery Broad learning systems Threat detection Threat segmentation

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Development of Mutal Recognition of Education Approach in Advanced computer-Oriented engineering Technologies in the Baltic Region 64

Development of Mutal Recognition of Education Approach in Ad...

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64th IEEE Annual International Scientific Conference on Power and electrical engineering of Riga Technical University, RTUCON 2023

作者： Kunicina, Nadezhda Rassolkin, Anton Bruzgiene, Rasa Plonis, Darius Caiko, Jelena Riga Technical University Institute of Electrical Engineering and Electronics Feee Riga Latvia Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia Kaunas University of Technology Faculty of Informatics Department of Computer Sciences Kaunas Lithuania Vilnius Gediminas Technical University Department of Electronic Systems Vilnius Lithuania

ISBN: (纸本)9798350317732

The continued improvement and development of study programmes content for mutual recognition of study programmes among the largest technical universities in the Baltic region provides a very good opportunity for regional development as it brings a good advancement in academics and research at the involved universities, allows for more flexible and reliable collaboration with industrial partners, and provides an opportunity to develop new technologies and implement them for regional support. The goal of the development is to promote the involvement of students in the design of adaptive systems by providing them with the necessary set of skills that will allow them to immediately engage in the design of innovative adaptive systems and successfully solve technological challenges that have been identified through the cooperation of educational and research institutions. The adoption of an innovative educational strategy will aid in the creation of new technology and creative solutions even before students begin their studies. Collaboration between academic personnel and industry will help students build their abilities. © 2023 IEEE.

关键词： Students

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A Wirelessly Powered, Battery-less, Miniaturized Microchip for Implantable Biopotential-Monitoring Applications

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IEEE Sensors Journal 2025年第11期25卷 19545-19554页

作者： Jang, Jaeeun Habibagahi, Iman Mathews, Roshan P. Gwak, Wonseop Rahmani, Hamed Babakhani, Aydin Kwangwoon University School of Semiconductor Systems Engineering Seoul Korea Republic of University of California at Los Angeles Department of Electrical Engineering Los AngelesCA90095 United States New York University Department of Electrical and Computer Engineering BrooklynNY11201 United States

This paper presents a low-power, battery-less biopotential-recording integrated circuit (IC) designed for implantable leadless cardiac monitoring applications, addressing the full autonomy based on wireless energy harvesting and closed-loop control. A key technical feature is the closed-loop capability with integration of a dual-band radio frequency (RF) energy harvester and communication system utilizing industrial, scientific, and medical (ISM) bands at 40.68 MHz for downlink and 915 MHz for uplink, ensuring efficient wireless power transfer and robust bi-directional data communication. The RF harvester achieves a peak conversion efficiency exceeding 40%, a critical design challenge in maintaining consistent performance under variable power conditions. Also, proposed IC overcomes the need for a local oscillator by utilizing an externally provided clock, reducing system complexity and power consumption. Operating with a clock frequency of 100 kHz, the IC consumes only 8.8 μW, a major achievement in energy efficiency for wireless, battery-less systems. Fabricated in a 180 nm complementary metal-oxide-semiconductor (CMOS) process, the IC successfully demonstrates cardiac signal measurement and heart rate extraction under a fully battery-less environment with air medium, providing a promising solution for next-generation leadless cardiac monitoring systems. © 2001-2012 IEEE.

关键词： Inductive power transmission

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Oversampling-Enhanced Feature Fusion-Based Hybrid ViT-1DCNN Model for Ransomware Cyber Attack Detection

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computer Modeling in engineering & Sciences 2025年第2期142卷 1667-1695页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saifur Rahman Saad Arif Salim Nasar Faraj Mursal Muhammad Irfan Haris Aziz Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl Ahsa31982Saudi Arabia Department of Mechanical Industrial and Energy System EngineeringUniversity of SargodhaSargodha40100Pakistan

Ransomware attacks pose a significant threat to critical infrastructures,demanding robust detection *** study introduces a hybrid model that combines vision transformer(ViT)and one-dimensional convolutional neural network(1DCNN)architectures to enhance ransomware detection *** common challenges in ransomware detection,particularly dataset class imbalance,the synthetic minority oversampling technique(SMOTE)is employed to generate synthetic samples for minority class,thereby improving detection *** integration of ViT and 1DCNN through feature fusion enables the model to capture both global contextual and local sequential features,resulting in comprehensive ransomware *** on the UNSW-NB15 dataset,the proposed ViT-1DCNN model achieved 98%detection accuracy with precision,recall,and F1-score metrics surpassing conventional *** approach not only reduces false positives and negatives but also offers scalability and robustness for real-world cybersecurity *** results demonstrate the model’s potential as an effective tool for proactive ransomware detection,especially in environments where evolving threats require adaptable and high-accuracy solutions.

关键词： Ransomware attacks cybersecurity vision transformer convolutional neural network feature fusion encryption threat detection

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Reliable Task Offloading for 6G-Based IoT Applications

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computers, Materials & Continua 2025年第2期82卷 2255-2274页

作者： Usman Mahmood Malik Muhammad Awais Javed Ahmad Naseem Alvi Mohammed Alkhathami Department of Computer Software Engineering National University of Science and Technology(NUST)Islamabad44000Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadIslamabad45550Pakistan Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia

Fog computing is a key enabling technology of 6G systems as it provides quick and reliable computing,and data storage services which are required for several 6G *** Intelligence(AI)algorithms will be an integral part of 6G systems and efficient task offloading techniques using fog computing will improve their performance and *** this paper,the focus is on the scenario of Partial Offloading of a Task to Multiple Helpers(POMH)in which larger tasks are divided into smaller subtasks and processed in parallel,hence expediting task ***,using POMH presents challenges such as breaking tasks into subtasks and scaling these subtasks based on many interdependent factors to ensure that all subtasks of a task finish simultaneously,preventing resource ***,applying matching theory to POMH scenarios results in dynamic preference profiles of helping devices due to changing subtask sizes,resulting in a difficult-to-solve,externalities *** paper introduces a novel many-to-one matching-based algorithm,designed to address the externalities problem and optimize resource allocation within POMH ***,we propose a new time-efficient preference profiling technique that further enhances time optimization in POMH *** performance of the proposed technique is thoroughly evaluated in comparison to alternate baseline schemes,revealing many advantages of the proposed *** simulation findings indisputably show that the proposed matching-based offloading technique outperforms existing methodologies in the literature,yielding a remarkable 52 reduction in task latency,particularly under high workloads.

关键词： 6G IoT task offloading fog computing

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