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IEEE International Symposium on Biomedical Imaging

作者： Jorge García-Torres Øyvind Meinich-Bache Siren Rettedal Kjersti Engan Dept. of Electrical Engineering and Computer Science University of Stavanger Norway Laerdal Medical AS Stavanger Norway Dept. for Simulation-based Learning Stavanger University Hospital Norway Faculty of Health Sciences University of Stavanger Norway

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Approximately 10% of newborns need some assistance to start breathing and 5% proper ventilation. It is crucial that interventions are initiated as soon as possible after birth. Accurate documentation of Time of Birth (ToB) is thereby essential for documenting and improving newborn resuscitation performance. However, current clinical practices rely on manual recording of ToB, typically with minute precision. In this study, we present an AI-driven, video-based system for automated ToB detection using thermal imaging, designed to preserve the privacy of healthcare providers and mothers by avoiding the use of identifiable visual data. Our approach achieves 91.4% precision and 97.4% recall in detecting ToB within thermal video clips during performance evaluation. Additionally, our system successfully identifies ToB in 96% of test cases with an absolute median deviation of 1 second compared to manual annotations. This method offers a reliable solution for improving ToB documentation and enhancing newborn resuscitation outcomes.

关键词： Pediatrics Privacy Accuracy Annotations Medical services Infrared imaging Manuals Documentation Activity recognition Videos

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Efficient Perovskite quantum dots Light Emitting Diodes

Efficient Perovskite quantum dots Light Emitting Diodes

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International Conference on Display Technology, 2024

作者： Deng, Ming Li, Yanming Zhang, Xuanyu Xiang, Chaoyu Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo Zhejiang 315211 China Division of Functional Materials and Nanodevices Ningbo Institute of Materials Technology and Engineering Hangzhou Bay Campus Chinese Academy of Sciences Zhejiang Ningbo315300 China Zhejiang Provincial Engineering Research Center of Energy Optoelectronic Materials and Devices Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China Division of Functional Materials and Nanodevices Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Zhejiang Ningbo315201 China Department of Mechanical Materials and Manufacturing Engineering University of Nottingham Ningbo China Zhejiang Ningbo315100 China

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Passivity Based Control of Four-Switch Buck-Boost DC-DC Converter without Operation Mode Detection 48

Passivity Based Control of Four-Switch Buck-Boost DC-DC Conv...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Komurcugil, Hasan Bayhan, Sertac Guler, Naki Guzman, Ramon Eastern Mediterranean University Department of Computer Engineering Famagusta Turkey Hamad Bin Khalifa University Qatar Environment and Energy Research Institute Doha Qatar Technology Faculty Gazi University Department of Electrical-Electronic Engineering Ankara Turkey Technical Science Vocational School Gazi University Electrical and Energy Department Ankara Turkey Technical University of Catalonia Spain

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

This paper presents a passivity-based control approach for four-switch buck-boost (FSBB) DC-DC converters. The state variables are selected as the inductor current and the capacitor voltage errors. The passivity based control is formulated that targets to drive the inductor current and capacitor voltage to their reference values. The reference of the inductor current is produced by a proportional-integral controller that operates on the capacitor voltage error. Two control input equations are defined for buck and boost operations due to the fact that FSBB converter contains separate switches for buck and boost stages. As a consequence of controlling each stage by the dedicated control input, the passivity based control method eliminates the need for using a mode detection algorithm. The validity and superiority of the proposed approach has been studied by Matlab/Simulink simulations under load step, reference voltage step and operation mode variations for buck and boost modes. The results reveal that the proposed control approach can regulate the output voltage under all cases. © 2022 IEEE.

关键词： Controllers

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Enhancing Content-Based Histopathology Image Retrieval Using QR Code Representation

Enhancing Content-Based Histopathology Image Retrieval Using...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Hamidreza Rouzegar Shahryar Rahnamayan Azam Asilian Bidgoli Masoud Makrehchi Department of Electrical Computer and Software Engineering Ontario Tech University Oshawa ON Canada Engineering Department Brock University St. Catharines ON Canada Faculty of Science Wilfrid Laurier University Waterloo ON Canada

The growing field of Content-Based Medical Image Retrieval (CBMIR) plays an integral role in the diagnosis and treatment plan of numerous diseases, including cancer. However, the effective representation of gigapixel medical images via a large number of extracted features remains a challenging task, crucially influencing other processes in a digital workflow. In this paper, we propose a novel QR code representation strategy to enhance retrieval performance. Unlike the traditional one-dimensional binary representation methods (i.e., barcodes), this 2D approach captures more intricate and informative patterns from the features by differentiating each pair of features resulting in a 2D binary vector. We delve into three distinct QR code generation strategies, namely, the Thresholding QR, the MinMax QR, and the Hybrid QR, each offering unique strengths. Our experiments on representing whole slide images of the Cancer Genome Atlas (TCGA) dataset reveal that while the Hybrid QR tends to provide balanced performance, there are instances where the other two methods outshine. Even though this approach requires more memory usage, the considerable enhancement in accuracy justifies this trade-off; obviously, in medical applications, accuracy holds the highest priority. Hence, the findings indicate that QR codes can effectively improve the performance of CBMIR systems by not only accelerating the retrieval process but also increasing the accuracy of image retrieval, leading to potentially more accurate diagnoses and treatment planning.

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On the non-submodularity of the problem of adding links to minimize the effective graph resistance

arXiv

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arXiv 2025年

作者： Achterberg, Massimo A. Kooij, Robert E. Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology P.O. Box 5031 Delft2600 GA Netherlands P.O. Box 96800 Den Haag2509 JE Netherlands

We consider the optimisation problem of adding k links to a given network, such that the resulting effective graph resistance is as small as possible. The problem was recently proven to be NP-hard, such that optimal solutions obtained with brute-force methods require exponentially many computation steps and thus are infeasible for any graph of realistic size. Therefore, it is common in such cases to use a simple greedy algorithm to obtain an approximation of the optimal solution. It is known that if the considered problem is submodular, the quality of the greedy solution can be guaranteed. However, it is known that the optimisation problem we are facing, is not submodular. For such cases one can use the notion of generalized submodularity, which is captured by the submodularity ratio γ. A performance bound, which is a function of γ, also exists in case of generalized submodularity. In this paper we give an example of a family of graphs where the submodularity ratio approaches zero, implying that the solution quality of the greedy algorithm cannot be guaranteed. Furthermore, we show that the greedy algorithm does not always yield the optimal solution and demonstrate that even for a small graph with 10 nodes, the ratio between the optimal and the greedy solution can be as small as 0.878. © 2025, CC BY.

关键词： Optimization algorithms

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Intelligent System for Vehicles License Plate Recognition Using a Hybrid Model of GAN, CNN and ELM 2

Intelligent System for Vehicles License Plate Recognition Us...

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2nd International Conference for Innovation in Technology, INOCON 2023

作者： Nirmala, B. Nithya, S. Vidhiya, R. Sunalini, K.K. Kumar, Buddha Hari Varadharajan, Bhoopathy CSE Sri Ramachandra Faculty of Engineering and Technology Sri Ramachandra Institute of Higher Education and Research Porur Tamilnadu Chennai India SRMIST Electrical and Electronics Department RAMAPURAM Tamilnadu Chennai India KPR Institute of Engineering and Technology Department of English Tamilnadu India Koneru Lakshmaiah Education Foundation Department of English Andhra Pradesh Guntur India Vignan's Institute of Engineering for Women Department of Electronics and Communication Engineering Andhra Pradesh Visakhapatnam India Malla Reddy College of Engineering Department of Computer Science and Engineering Telangana Secunderabad India

ISBN: (纸本)9798350320923

The scientific community has given license plate recognition systems a lot of consideration. The current methods for vehicle identification need to be improved due to the swift increase in vehicle numbers. In order to lessen reliance on labor, a fully automated system is needed. With the growth of Intelligent Transportation Systems, demand for license plate recognition has increased significantly. License Plate Recognition (LPR) is susceptible to environmental factors such as a complex image background, angle view, and shift in illumination, it is still difficult to correctly recognize the digit letters on license plates. When reading license plates automatically, license plate recognition uses character recognition and image processing to identify the vehicles. The license plate detection and identification subsystems are typically combined into the vehicle license recognition system in order to locate the vehicle and identify the license plate. The Extreme Learning Machine (ELM) is used for categorization, identification, and training. This research suggests a GANCNN-ELM-based technique for detecting vehicle license plates. This method produces an accuracy of about 98.94% which outperforms the GAN-ELM, GAN-SVM, and GAN-CNN models. © 2023 IEEE.

关键词： Support vector machines

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Two-Stream Thermal Imaging Fusion for Enhanced Time of Birth Detection in Neonatal Care

arXiv

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arXiv 2025年

作者： García-Torres, Jorge Meinich-Bache, Øyvind Brunner, Sara Rettedal, Siren Kolstad, Vilde Engan, Kjersti Department of Electrical Engineering and Computer Science University of Stavanger Norway Strategic Research Laerdal Medical Stavanger Norway Faculty of Health Sciences University of Stavanger Norway Department for Simulation-based Learning Stavanger University Hospital Norway

Around 10% of newborns require some help to initiate breathing, and 5% need ventilation assistance. Accurate Time of Birth (ToB) documentation is essential for optimizing neonatal care, as timely interventions are vital for proper resuscitation. However, current clinical methods for recording ToB often rely on manual processes, which can be prone to inaccuracies. In this study, we present a novel two-stream fusion system that combines the power of image and video analysis to accurately detect the ToB from thermal recordings in the delivery room and operating theater. By integrating static and dynamic streams, our approach captures richer birth-related spatiotemporal features, leading to more robust and precise ToB estimation. We demonstrate that this synergy between data modalities enhances performance over single-stream approaches. Our system achieves 95.7% precision and 84.8% recall in detecting birth within short video clips. Additionally, with the help of a score aggregation module, it successfully identifies ToB in 100% of test cases, with a median absolute error of 2 seconds and an absolute mean deviation of 4.5 seconds compared to manual annotations. © 2025, CC BY.

关键词： Video analysis

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Controlled Out-band Device to Device Communication in Cellular Networks Using Backup Channel in Television White Space

Controlled Out-band Device to Device Communication in Cellul...

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International Conference on Emerging Technologies, ICET

作者： Saifur Rahman Syed Luqman Shah Salim Nasar Faraj Mursal Ziaul Haq Abbas Muhammad Usman Muhammad Irfan Fazal Muhammad Electrical Engineering Department College of Engineering Nairan University Nairan Saudi Arabia TeleCoN Research Lab GIK Institute of Engineering Sciences and Technology Topi Pakistan Faculty of Electrical Engineering GIK Institute of Engineering Sciences and Technology Toni Pakistan Department of Electrical Engineering University of Engineering and Technology Mardan Pakistan Department of Computer Science University of Engineering and Technology Mardan Pakistan

In this article, we address the problem of spectrum scarcity in cellular networks (CNs). We propose a backup channel (BuC) for cellular users (CUs) who are in the same macro-cell under the control of a single macro base station (eNB). This BuC operates in the television white space and is detected by the CUs through a cognitive radio energy detection channel sensing technique with a certain probability of success. When the regular channels with the cellular eNB are all occupied, the CUs within the same coverage area of the macro eNB can utilize the sensed BuC to establish a controlled out-band device-to-device link for communication. The BuC bypasses the eNB and reduces the burden on the core of the CN. This leads to improvements in the capacity of the cellular eNB. In the proposed system model, each CU and eNB is equipped with two antennas for communication in two separate bands, i.e., cellular and TV bands. Through simulations, we have observed significant reductions in the blocking probability and probability of call delays.

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$\mathcal{H}_{\infty}$ Robust Control Design for Three-Element Industrial Boiler Supervisory System

$\mathcal{H}_{\infty}$ Robust Control Design for Three-Eleme...

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International Conference on Control, Instrumentation, and Automation

作者： Narges Ahooghalandari Reza Shadi Ahmad Fakharian Faculty of Mechanical Electrical and Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran Faculty of Electrical Biomedical and Mechatronics Engineering Qazvin Branch Islamic Azad University Qazvin Iran

ISBN: (纸本)9781665495707

In power plants, to achieve safe performance, fundamental factors, including pressure of drum, the water level in the drum, and temperature, must be under control. In this study, in the first step, a three-element linear time-invariant (LTI) industrial boiler with three inputs and outputs is introduced. However, this model may be associated with uncertainties. In this regard, the robust control mehod is performed to examine the stability and performance of the boiler system. Parametric uncertainties being assumed, an $\mathcal{H}_{\infty}$ state feedback controller via linear matrix inequalities (LMIs) techniques in comparison to the D-K iteration approach is designed. Based on numerical simulations, both controllers guarantee robust control, and the performance of the proposed robust methods is compared graphically.

关键词： Robust control Linear systems State feedback Temperature distribution Uncertainty Boilers Temperature control

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Testing Physical Unclonable Functions Implemented on Commercial Off-the-Shelf NAND Flash Memories Using Programming Disturbances 12

Testing Physical Unclonable Functions Implemented on Commerc...

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12th IEEE International Conference on Consumer Electronics, ICCE-Berlin 2022

作者： Anagnostopoulos, Nikolaos Athanasios Fan, Yufan Saleem, Muhammad Umair Mexis, Nico Gelóczi, Emiliia Klement, Felix Frank, Florian Schaller, André Arul, Tolga Katzenbeisser, Stefan University of Passau Faculty of Computer Science and Mathematics Innstraße 43 Passau94032 Germany Technical University of Darmstadt Computer Science Department Hochschulstraße 10 Darmstadt64289 Germany Technical University of Darmstadt Department of Electrical Engineering and Information Technology Merckstraße 25 Darmstadt64283 Germany EUMETSAT Allee 1 Darmstadt64295 Germany

In this work, we present a Physical Unclonable Function (PUF) implemented on a Commercial Off-The-Shelf (COTS) NAND Flash memory module using programming disturbances, and examine the robustness of its responses to environmental variations. In particular, we test a removable Flash memory module serving as a PUF, under nominal conditions, as well as under temperature and voltage variations. To determine its resilience to environmental variations, we utilise well-known PUF metrics, such as the Hamming weight and the intra-device Hamming distance. Our results prove that, in general, the tested Samsung K9F1G08U0E NAND Flash memory can be used to realise a lightweight, scalable, and flexible hardware security primitive, namely a PUF, that can be utilised in the context of smart homes, smart vehicles, and other smart applications, as well as to protect commercial devices and networks in general. However, voltage variations seem to pose a substantial threat to the adoption of this PUF in practice. This threat may be addressed by small-scale design improvements that should be implemented and tested in practice as part of future works. © 2022 IEEE.

关键词： Automation

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