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An upgraded variant of backtracking search algorithm and its application to COVID-19 CT images segmentation

Multimedia Tools and Applications 2025年 1-57页

作者： Debnath, Sanjib Nama, Sukanta Chakraborty, Sanjoy Saha, Apu Kumar Mirjalili, Seyedali Department of Computer Science & Engineering National Institute of Technology Agartala Tripura Agartala799046 India Department of Science & Humanities Gomati District Polytechnic Fulkumari Tripura Udaipur799013 India Department of Information Technology Bir Bikram Memorial College Tripura Agartala India Department of Mathematics National Institute of Technology Agartala Tripura Agartala799046 India Center for Artificial Intelligence Research and Optimization Torrens University Australia Brisbane Australia Faculty of Electrical Engineering and Computer Science VŠB-TU Ostrava Ostrava Czech Republic University Research and Innovation Center Obuda University Budapest Hungary Department of Computer Science & Engineering The ICFAI University Tripura Tripura 799210 India

To improve the performance of the original backtracking search algorithm (BSA), this work combines BSA with a centralized population initialization and an elitism-based local escape operator and proposes a new, improved variant of BSA called CiBSA. BSA's performance is improved by centralized population initialization regarding search capability, convergence speed, and capacity to jump out of the local optimum. The suggested algorithm's elitism-based local escape operator method prevents BSA searching slowness and enhances convergence rates and local search efficiency. The performance of the proposed algorithm has been tested on a set of 54 test suites. An extensive comparison with other recent meta-heuristics algorithms (MA) demonstrates that both methodologies substantially assist BSA in boosting the quality of its solutions and speeding up the convergence rate. The proposed CiBSA is then applied to a real-world problem: image segmentation using Kapur's entropy function. The proposed CiBSA is successfully applied to the segmentation of COVID-19 CT images using Kapur's entropy for grey-scale images. Considering the performance matrices Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Feature Similarity Index (FSIM), and Intersection over Union (IoU), the suggested CiBSA outperformed conventional MA algorithms. In COVID-19 CT image segmentation trials, CiBSA has superior segmentation capability and adaptability at varied threshold levels than other approaches. As a result, CiBSA has a lot of potential for enhancing COVID-19 diagnosis accuracy. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Signal to noise ratio

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Compact Fractal-Shaped Frequency Selective Surface for Distant Liquid Sensing With Multiple Sensitive Spots

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IEEE Sensors Journal 2025年第9期25卷 15031-15042页

作者： Neyestanak, Morteza Lotfi Moghadas, Hamid Mirabbasi, Shahriar Servati, Peyman Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Wireless Systems Engineering Technology School of Media and Information Technology Northern Alberta Institute of Technology EdmontonABT5G 2R1 Canada

This article introduces compact battery-less wireless radio frequency (RF) sensors using fractal-shaped electromagnetic surfaces. Fractal structures allow a compact total size of 0.75λ0 × 0.75λ0 at 2.9 GHz. In conventional sensors based on a frequency selective surface (FSS), the material under test (MUT) needs to be placed in all the unit cells or play the role of a substrate. However, in the proposed sensors, the MUT covers only 3%–7% of the electromagnetic surface with a volume of 1 mL. In contrast with conventional RF sensors with one local sensitive spot, the proposed surface can provide multiple sensitive spots. This capability has been tested using several different liquids including isopropyl alcohol (IPA), methanol, ethanol, acetone, and deionized (DI) water. The proposed sensing platform exhibits remarkable sensitivity while the reader antenna is over 10 cm away from the FSS. Changing the MUT from air to IPA and DI water results in a 40 and 350 MHz shift in the resonant frequency, respectively. This sensor can tolerate polarization misalignment between the reader antenna and the FSS. © 2025 IEEE. All rights reserved.

关键词： Frequency selective surfaces

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XMeta-OS: A Conceptual Framework for Unified Resource Management in Distributed Edge-Cloud Environments 3rd

XMeta-OS: A Conceptual Framework for Unified Resource Manag...

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3rd International Conference on Advances in Computing research, ACR 2025

作者： Zacharioudakis, Eleftherios Kakoulli, Elena Evripidou, Salomi Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Pafos Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9783031876462

This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is possible. This approach offer a new GPU abstraction layer and dynamic edge-cloud allocation model that offer enhanced flexibility and resource utilization over existing systems like Kubernetes and OpenStack. By using likely sensitive data, the model applied cloud-pushed deployment model. XMeta-OS manages computer resources in real-time. Therefore, fulfilling high performance various needs. It allocates CPU and GPU in real-time to workloads requiring massive parallel processing, such as machine learning, scientific simulations, real-time data analytics, and transportation tasks. Fabrication in the laboratory of an edge-cloud environment can help to assess the scalability, fault tolerance and efficiency of the system. It showcases the overall architectural design of XMeta-OS. Changes to the kernel and security solutions for safe and effective distribution are suggested. This article presents the design of the XMeta-OS. The future of XMeta-OS entails usage and testing with which we see latency, energy, computation and other such measurements in labs. XMeta-OS is a solution to cost performance, emerging application, large-scale edge-cloud deployments, and distributed GPU-enabled infrastructures. Meta-Operating System in Edge-Cloud Continuum for dynamic resource management of GPU. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cluster computing

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Damage-Free Neutral Beam Etching for Gate Recess in E-Mode AlGaN/GaN HEMTs

IEEE Electron Device Letters

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IEEE Electron Device Letters 2025年第5期46卷 705-708页

作者： Chen, Yi-Ho Chu, Fu-Chuan Aslam, Muhammad Lee, Yao-Jen Li, Yiming Samukawa, Seiji National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Graduate Degree Program of College of Electrical and Computer Engineering Hsinchu300093 Taiwan National Chung-Shan Institute of Science and Technology Solid State Devices Section Electronic System Research Division Taoyuan325 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

Recess gate etching is a critical technique for achieving enhancement-mode (E-mode) AlGaN/GaN high-electron mobility transistors (HEMTs) because the interface is susceptible to the etching damage. This study fabricates recess gates using the neutral beam etching (NBE) technique. By adjusting the aperture thickness in the NBE apparatus, we simulate both NB-mode and plasma-mode etching. The electrical characteristics of E-mode HEMTs fabricated using these two modes are analyzed and compared through DC, noise, and pulsed IV measurements. The results demonstrate that NB-recessed HEMTs exhibit superior performance. © 1980-2012 IEEE.

关键词： Aluminum gallium nitride

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Role of Power Electronics in Power Quality Management of Smart Grid with AI Interfacing

Role of Power Electronics in Power Quality Management of Sma...

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International Conference on Computational Intelligence and Smart Technologies in electrical engineering, CISTEE 2023

作者： Rai, Shiwani Shukla, Hiramani Pathre, Ayonija Kumar, Alok Jaiswal, Pooja Ansari, Aftab Ahmed Department of Electrical and Electronic Engineering IES Institute of Technology and Management IES University Bhopal MP Bhopal India Department of Electrical Engineering U.V. Patel college of Engineering Ganpat University Gujarat Mehsana-Gozaria Highway Ganpat Vidyanagar India Department of Computer Science and Engineering JNCT MP Bhopal India Department of Electrical and Electronics Engineering Trinity Institute of Technology and Research Bhopal India Aspen Enggicon Pvt. Ltd. Jharkand Ranchi India Vidya Pratishthans Kamalnayan Baja Institute of Engineering and Technology Maharashtra Baramati India Department of Electrical and Electronics Engineering Bansal Institute of Research Technology and Science MP Bhopal India

ISBN: (纸本)9789819604753

With continual evolution in power sector and Power Electronics (PE) and the need for better performance with less human interfacing has raised the necessity for AI interfacing in power sector. AI, i.e., Artificial Intelligence is a computer software or machine which is capable of replicating human expertise without any human interference. PE, plays a dominant role in transmitting, converting, and controlling power from kilowatts to gigawatts, efficiently and flexibly between the power grids with 95% efficiency. Its interference with AI can take modern smart grid system into the next level of techno-automation without any human interference. The application of PE is at its peak for enhancing the Power Quality (PQ) of the system. This paper presents a review of transformation of the existing system into hi-tech PE integration to obtain high power quality with AI interfacing to reduce human supervision and to reduce the PQ events to take place in power system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electric power transmission networks

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Noise-Robust Speech Emotion Recognition Using Shared Self-Supervised Representations with Integrated Speech Enhancement

Noise-Robust Speech Emotion Recognition Using Shared Self-Su...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Tzeng, Jing-Tong Leem, Seong-Gyun Salman, Ali N. Lee, Chi-Chun Busso, Carlos College of Semiconductor Research National Tsing Hua University Taiwan Department of Electrical and Computer Engineering The University of Texas Dallas United States Department of Electrical Engineering National Tsing Hua University Taiwan Language Technologies Institute Carnegie Mellon University United States

ISBN: (纸本)9798350368741

Recent studies have demonstrated the effectiveness of fine-tuning self-supervised speech representation models for speech emotion recognition (SER). However, applying SER in real-world environments remains challenging due to pervasive noise. Relying on low-accuracy predictions due to noisy speech can undermine the user's trust. This paper proposes a unified self-supervised speech representation framework for enhanced speech emotion recognition designed to increase noise robustness in SER while generating enhanced speech. Our framework integrates speech enhancement (SE) and SER tasks, leveraging shared self-supervised learning (SSL)-derived features to improve emotion classification performance in noisy environments. This strategy encourages the SE module to enhance discriminative information for SER tasks. Additionally, we introduce a cascade unfrozen training strategy, where the SSL model is gradually unfrozen and fine-tuned alongside the SE and SER heads, ensuring training stability and preserving the generalizability of SSL representations. This approach demonstrates improvements in SER performance under unseen noisy conditions without compromising SE quality. When tested at a 0 dB signal-to-noise ratio (SNR) level, our proposed method outperforms the original baseline by 3.7% in F1-Macro and 2.7% in F1-Micro scores, where the differences are statistically significant. © 2025 IEEE.

关键词： multitask learning noisy speech Speech emotion recognition speech enhancement

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Multimodal Pain Assessment Βased on Physiological Biosignals: The Impact of Demographic Factors on Perception and Sensitivity 11

Multimodal Pain Assessment Βased on Physiological Biosignal...

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11th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2025

作者： Pavlidou, Elisavet Tsiknakis, Manolis Department of Electrical and Computer Engineering Hellenic Mediterranean University Estavromenos Heraklion71410 Greece Computational BioMedicine Laboratory Institute of Computer Science Foundation for Research & Technology-Hellas Vassilika Vouton Heraklion70013 Greece

ISBN: (纸本)9789897587436

Pain is a multidimensional and highly personalized sensation that affects individuals’ physical and emotional state. Visual analog scales, numeric rate indicators, and various questionnaires, all relying on patient-reported outcome measurements, are considered the "gold" standard methods for assessing the severity of pain. Nevertheless, self-report tools require cognitive, linguistic, and social abilities, which may manifest variations in certain populations such as neonates, individuals with intellectual disabilities, and those affected by dementia. The purpose of this study is to automate the process through multimodal physiological-data-driven machine-learning models in order to gain deeper insights into pain sensation. We developed a pipeline using electrocardiogram (ECG), galvanic skin response (GSR), and electromyogram (EMG), along with demographic information from the BioVid dataset. The Pan & Tompkins algorithm was applied for ECG signal processing, while statistical analysis was used for feature extraction across all signals. Our study achieved 82.83% accuracy in the SVM classification task of baseline (BL) vs the highest level of pain (PA4) for females aged 20-35. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Sensory perception

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Elastic Spectrum Sensing: An Adaptive Sensing Method for Non-Terrestrial Communication Under Highly Dynamic Channels

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IEEE Transactions on Wireless Communications 2025年第5期24卷 3868-3881页

作者： Xu, Tianheng Xu, Yinjun Zhou, Ting Zhang, Haijun Hu, Honglin Leung, Victor C. M. Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai201210 China Shanghai Frontier Innovation Research Institute Shanghai201100 China University of Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing100049 China Shanghai University School of Microelectronics Shanghai200444 China Institute of Artificial Intelligence Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing100083 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T1Z4 Canada

With the rapid development of space technology, the role of satellite communications has become progressively significant. Non-terrestrial communication is deemed a critical scenario in the sixth generation (6G) communication systems, which showcases seamless connectivity, minimal geographic constraints and substantial communication capacity. Simultaneously, satellites and terminals spring up, spatial density increases, which further emphasizes the scarcity of spectrum resources. Consequently, to improve spectrum utilization for non-terrestrial communication is a significant concern. Spectrum sensing, which allows dynamic resource reuse, plays an important role in 6G. However, high mobility in non-terrestrial scenarios poses great challenges, such as fast time-varying channels, Doppler effect, etc., which seriously affect sensing accuracy and cannot well support optimal spectrum utilization. Motivated by such circumstances, this paper proposes an elastic sensing method for the downlink non-terrestrial communication scenario. Firstly, we design the system architecture and sensing workflow. To overcome the negative effects raised by high mobility, we propose the elastic sensing criterion and multi-area dividing scheme for the sensing zone. Thresholds affected by the elastic sensing are derived for different areas. Finally, the numerical results show that from -10 dB to -5 dB, the proposed method can improve the total performance by an average of 28.3% while stabilizing the false alarm probability around 0.1 typical level and demonstrating higher constancy compared with traditional technologies from −10 dB to −5 dB. © 2002-2012 IEEE.

关键词： Satellite communication systems

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From Simulation to Reality with Random Noise

From Simulation to Reality with Random Noise

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Luo, Steven Lipkis, Rory López-Francos, Ignacio Vlastos, Pavlo Agogino, Adrian Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States Intelligent Systems Division NASA Ames Research Center Moffett FieldCA94035 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

The challenging environment of autonomous vehicle (AV) navigation necessitates certain functions be performed by deep neural networks. Optimizing these models involves collecting vast quantities of domain-specific training data and ensuring that the dataset is representative of expected conditions. High-fidelity simulation plays a vital role in making this process feasible, allowing a wide range of scenarios to be explored at relatively low cost. However, learning from simulation introduces subtle biases into models, which can degrade real-world performance in unpredictable ways. This effect can be mitigated with learning schemes specialized to bridge distributional shifts (transfer learning). Given the complex nature of these methods, the underlying models, and their environments, meaningfully evaluating performance is not straightforward. Many unrelated factors can effect an improvement in generalization accuracy, but a full ablation analysis is often difficult to perform. To tease out signal from noise, it is necessary to understand how transfer learning performance is affected by noise itself. The goals of this paper are (i) to establish a domain randomization baseline for a simple classification transfer learning task and (ii) to validate the RRAV testbed as a platform for further research in sim-to-real learning. We generate imagery from a simulation of NASA Ames research Center and train a small convolutional neural network to classify camera position of an ego vehicle relative to a center line. Further models are trained with different types of noise progressively added to the data. In our experiments, we find that naive domain randomization raises sim-to-real accuracy from 64% to 79%, while training directly on real data yields an 89% accuracy ceiling. These results suggest that the isolated mechanism of domain randomization can significantly improve generalization. © 2025, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： NASA

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SEPARABLE PHYSICS-INFORMED NEURAL NETWORKS FOR SOLVING THE BGK MODEL OF THE BOLTZMANN EQUATION

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SIAM Journal on Scientific Computing 2025年第2期47卷 C451-C474页

作者： Oh, Jaemin Cho, Seung Yeon Yun, Seok-Bae Park, Eunbyung Hong, Youngjoon Department of Electrical and Computer Engineering Texas A&M University United States Department of Mathematics Gyeongsang National University Jinju Korea Republic of Department of Mathematics Sungkyunkwan University Suwon Korea Republic of Department of Artificial Intelligence Yonsei University Korea Republic of Department of Mathematical Sciences Research Institute of Mathematics Seoul National University Korea Republic of

In this study, we present a new approach based on separable physics-informed neural networks (SPINNs), specifically designed to efficiently solve the Bhatnagar-Gross-Krook (BGK) model. While the mesh-free nature of physics-informed neural networks (PINNs) offers significant advantages for handling high-dimensional partial differential equations, applying quadrature rules for accurate integral evaluation in the BGK operator can compromise these benefits and increase computational costs. To address this issue, we leverage the canonical polyadic decomposition structure of SPINNs and the linear nature of moment calculation to significantly reduce the computational expense associated with quadrature rules. However, the multiscale nature of the particle density function poses challenges for precisely approximating macroscopic moments using neural networks. To overcome this, we introduce SPINN-BGK, a specialized variant of SPINNs that fuses SPINNs with Gaussian functions and utilizes a relative loss approach. This modification enables SPINNs to decay as rapidly as Maxwellian distributions, enhancing the accuracy of macroscopic moment approximations. The relative loss design ensures that both large- and small-scale features are effectively captured by the SPINNs. The effectiveness of our approach is validated through six numerical experiments, including a complex three-dimensional Riemann problem. These experiments demonstrate the potential of our method to efficiently and accurately tackle intricate challenges in computational physics, offering significant improvements in computational efficiency and solution accuracy. © 2025 Society for Industrial and Applied Mathematics.

关键词： Boltzmann equation

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