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6th IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd4.0 and IoT 2023

作者： Baccanini, Marco Alberto Bassi, Ezio Marabelli, Filippo Benzi, Francesco Frosini, Lucia University of Pavia Department of Electrical Computer and Biomedical Engineering Pavia Italy Lenze Italia Srl Milano Italy

ISBN: (纸本)9798350396577

In the industrial context, the transformation of any process related information to a digital format affects the entire company, from administration to production and logistics (digitization). This paper focuses on Edge Computing, which consists in extending the scope of a Programmable Logic Controller (PLC) from the standard coordination and control of an industrial drive, to include a Condition Monitoring process. The latter can be implemented without interference with the regular real time control operation of the plant, and still a number of relevant data are detected and processed on-time, both to monitor the quality of the operation, and to perform Diagnostics Algorithms. The software architecture and some relevant experimental results are reported in the paper © 2023 IEEE.

关键词： Condition monitoring

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Direct ink writing of gradient shear-stiffening elastomer for enhanced toughness and impact resistance

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Journal of Industrial and engineering Chemistry 2025年 149卷 593-603页

作者： Gong, Liping Zhao, Chunyu Lu, Hongda Zhang, Qingtian Chen, Zexin Yang, Junjie Yang, Jinyu Sun, Shuaishuai Du, Haiping Li, Weihua School of Mechanical Materials Mechatronic and Biomedical Engineering University of Wollongong Wollongong2522 Australia CAS Key Laboratory of Mechanical Behaviour and Design of Materials Department of Modern Mechanics University of Science and Technology of China Hefei230027 China School of Electrical Computer and Telecommunication Engineering University of Wollongong Wollongong2522 Australia

Shear-stiffening materials have garnered significant attention due to their inherent ability to rapidly respond to changes in strain rate. However, conventional studies on these materials exhibit limited mechanical performance and insufficient structural design, hindering applications in material science and smart mechatronics. Inspired by the gradient structure of a squid beak, this study uses a direct-ink-writing (DIW) technology to develop a novel gradient shear-stiffening elastomer (GSSE). Comprehensive characterizations were conducted to optimize the printability of the shear-stiffening elastomer under various testing conditions, including rheology, compression, and tension. Additionally, the toughness and impact resistance of the elastomer were systematically investigated. It is demonstrated that the biomimetic GSSE exhibits enhanced flexibility, efficient energy dissipation, and outstanding impact resistance. Consequently, this work advances the field of shear-stiffening elastomers for diverse applications by leveraging the gradient structure design strategy to achieve superior mechanical performance under complex loading conditions. © 2025 The Author(s)

关键词： Strain rate

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Au/SiC Microfluidic Devices Fabricated by Rapid Laser Cladding for Photocatalytic Degradation of Water Pollutants

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ACS Sustainable Chemistry and engineering 2024年第11期12卷 4486-4496页

作者： Chang, Chun-Hao Lin, Hsiu-Pen Chen, Chien-Wei Lu, Yu-Cheng Hsiao, Fu-He Hsieh, Chi-Hsiang Lin, Bo-Cheng Yu, Bang-Ying Ma, Dai-Liang Kuo, Hao-Chung Tu, Chang-Ching Li, Bor-Ran Institute of Biomedical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electrical and Computer Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Centre for Emergent Functional Matter Science National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electrophysics College of Science National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei11492 Taiwan Department of Photonics Institute of Electro-Optical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Taisic Materials Corp. Taoyuan320 Taiwan Department of Electrical Engineering National Central University Taoyuan32001 Taiwan Medical Device Innovation and Translation R&D Center National Yang Ming Chiao Tung University Taipei112304 Taiwan

The increasing proliferation of third-generation semiconductor silicon carbide (SiC) products has led to the emergence of SiC powder as an industrial byproduct. To reutilize the SiC efficiently, we propose a facile method for fabrication of photocatalytic plates from reclaimed SiC. Our approach involves affixing the SiC onto a glass surface with laser cladding, followed by sputter deposition of a gold film and laser annealing. The resulting nanogold-coated SiC plate exhibited enhanced photocatalytic activity due to the injection of hot electrons into the SiC via surface plasmon resonance. Unlike chemical reduction, which requires hours for the synthesis, purification, and isolation of Au/SiC, our approach accomplished this in just 30 min. When illuminated, the Au/SiC plate generated electron-hole pairs that formed radicals in the presence of water and oxygen, leading to the decomposition of methylene blue. Furthermore, the Au/SiC plate can be integrated into a microfluidic device for an enhanced degradation rate and efficiency. This research provides a simple and environmentally friendly approach to the production of photocatalytic plates from reclaimed SiC and contributes to sustainable development. © 2024 The Authors. Published by American Chemical Society.

关键词： Silicon carbide

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Navigating Complexity: Data Structure Impact on Path Planning Algorithms in Autonomous Systems 6

Navigating Complexity: Data Structure Impact on Path Plannin...

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6th IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2024

作者： Emad, Hend Mabrouk, Mai S. Elnokrashy, Ahmed F. Nile University Biomedical Informatics Giza Egypt Nile University Computer Science Giza Egypt Benha University Electrical Engineering Benha Egypt

ISBN: (纸本)9798350378511

Navigating a busy cityscape with a fleet of autonomous vehicles requires each to seamlessly maneuver through traffic with split-second decisions. Path planning is the backbone of such advanced machinery applications, from mobile robots to unmanned ground vehicles, where the choice of data structure plays a pivotal role in determining memory usage, planning time, and algorithm reliability. This research rigorously evaluates Grassfire, Dijkstra, A *, and RRT* algorithms based on key metrics using real GPS readings, across diverse environment representations and obstacle conditions. Our findings provide guidance for selecting the optimal algorithms and data structures tailored to specific environmental complexities. By evaluating the performance of these algorithms under various environmental conditions, the study offers insights that can help researchers and practitioners choose the most suitable algorithms and data structures for their autonomous vehicle applications. The ability to match the algorithm and data structure to the specific environmental challenges faced by autonomous vehicles is crucial for ensuring efficient and reliable path planning, which is the backbone of advanced machinery applications. © 2024 IEEE.

关键词： Robot programming

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Quantifying the Effects of Chemotherapy-Induced Toxicity and Knockout of the Transcription Factor c-Myc on Mice Kidney Metabolism Using Optical Imaging

Quantifying the Effects of Chemotherapy-Induced Toxicity and...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Neghabi, Mehrnoosh Nategh, Parisa Ceyhan, Busenur Konjalwar, Shalaka Santana, Aline G. Machi, Jaqueline F. Rodrigues, Claudia O. Ranji, Mahsa Department of Electrical Engineering and Computer Science Florida Atlantic University United States Department of Biomedical Science Florida Atlantic University United States

The study explores knockout of c-Myc and doxorubicin toxicity influence on mouse kidney's metabolism. Cryo-imaging unveils knockout is significantly more oxidized compared to control group while this was not obser... 详细信息

ISBN: (纸本)9781957171395

关键词： Chemical lasers

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Microfluidic compartmentalization of rat vagal afferent neurons to model gut-brain axis

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Bioelectronic Medicine 2024年第1期10卷 1-13页

作者： Girardi, Gregory Zumpano, Danielle Raybould, Helen Seker, Erkin Department of Biomedical Engineering University of California – Davis DavisCA95616 United States Department of Anatomy Physiology and Cell Biology University of California – Davis DavisCA95616 United States Department of Electrical and Computer Engineering University of California – Davis DavisCA95616 United States

Background: Vagal afferent neurons represent the key neurosensory branch of the gut-brain axis, which describes the bidirectional communication between the gastrointestinal system and the brain. These neurons are important for detecting and relaying sensory information from the periphery to the central nervous system to modulate feeding behavior, metabolism, and inflammation. Confounding variables complicate the process of isolating the role of the vagal afferents in mediating these physiological processes. Therefore, we developed a microfluidic model of the sensory branch of the gut-brain axis. We show that this microfluidic model successfully compartmentalizes the cell body and neurite terminals of the neurons, thereby simulates the anatomical layout of these neurons to more accurately study physiologically-relevant processes. Methods: We implemented a primary rat vagal afferent neuron culture into a microfluidic platform consisting of two concentric chambers interconnected with radial microchannels. The microfluidic platform separated cell bodies from neurite terminals of vagal afferent neurons. We then introduced physiologically-relevant gastrointestinal effector molecules at the nerve terminals and assessed their retrograde transport along the neurite or capacity to elicit an electrophysiological response using live cell calcium imaging. Results: The angle of microchannel outlets dictated the probability of neurites growing into a chamber versus tracking along chamber walls. When the neurite terminals were exposed to fluorescently-labeled cholera toxin subunit B, the proteins were taken up and retrogradely transported along the neurites over the course of 24 h. Additionally, mechanical perturbation (e.g., rinsing) of the neurite terminals significantly increased intracellular calcium concentration in the distal soma. Finally, membrane-displayed receptor for capsaicin was expressed and trafficked along newly projected neurites, as revealed by confocal microscopy

关键词： Microfluidics

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14-Bit SAR ADC with on-Chip Digital Bubble Sorting Calibration Technology

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Chinese Journal of Electronics 2025年第1期34卷 125-136页

作者： Hua Fan Zhuorui Chen Tongrui Xu Franco Maloberti Qi Wei Quanyuan Feng School of Integrated Circuit Science and Engineering(Exemplary School of Microelectronics) University of Electronic Science and Technology of China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Chongqing Institute of Microelectronics Industry Technology University of Electronic Science and Technology of China Department of Electrical Computer and Biomedical Engineering University of Pavia Department of Precision Instrument Tsinghua University Institute of Microelectronics Southwest Jiaotong University

This article designs a 14-bit successive approximation register analog-to-digital converter（SAR ADC）.A novel digital bubble sorting calibration method is proposed and applied to eliminate the effect of capacitor mismatch on the linearity of the SAR ADC. To reduce the number of capacitors, a hybrid architecture of a high 8-bit binary-weighted capacitor array and a low 6-bit resistor array is adopted by the digital-to-analog（DAC）. The common-mode voltage VCM-based switching scheme is chosen to reduce the switching energy and area of the DAC. The time-domain comparator is employed to obtain lower power consumption. Sampling is performed through a gate voltage bootstrapped switch to reduce the nonlinear errors introduced when sampling the input signal. Moreover, the SAR logic and the whole calibration is totally implemented on-chip through digital integrated circuit（IC） tools such as design compiler, IC compiler, etc. Finally, a prototype is designed and implemented using 0.18 μm bipolar-complementary metal oxide semiconductor（CMOS）-double-diffused MOS 1.8 V CMOS technology. The measurement results show that the SAR ADC with on-chip bubble sorting calibration method achieves the signal-to-noise-and-distortion ratio of 69.75 dB and the spurious-free dynamic range of 83.77 dB.

关键词： Semiconductor device measurement Capacitors Linearity Switches Calibration System-on-chip Frequency measurement Time-domain analysis Sorting Signal to noise ratio

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A Hybrid Adversarial-TransUnet Architecture for Improving LV Segmentation Using Cardiac Cine Images 1st

A Hybrid Adversarial-TransUnet Architecture for Improving L...

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1st International Conference on Intelligent Systems, Blockchain, and Communication Technologies, ISBCom 2024

作者： Abdeltawab, Hisham Jani, Md. Rafsan Hasan, Md Rakibul Yasser, Ibrahim Khalifa, Fahmi Department of Biomedical Engineering and Systems Cairo University Cairo12613 Egypt Department of Electrical and Computer Engineering Morgan State University BaltimoreMD21251 United States Department of Electronics and Communications Engineering Mansoura University Mansoura35516 Egypt

ISBN: (纸本)9783031823763

Cardiac image segmentation is crucial for the assessment of heart anatomy and function. Deep learning (DL) has been widely employed for cardiac image segmentation and the accuracy of the segmentation has improved due to the advances in DL research and the existence of large cardiac datasets. In this study, we introduce a DL framework based on adversarial training for the delineation of the left ventricle (LV) from cardiac magnetic resonance imagining (CMRI). Our framework consists of two networks: the segmenter which is a neural network that predicts segmentation maps for the myocardium, the discriminator which is a convolutional neural network that discriminates between the ground truth and the predicted segmentation maps. We investigate two different architectures for the segmenter (Unet and TransUnet). The adversarial training can identify and correct the differences between the predicted and the ground truth maps and results in better segmentation accuracy than stand-alone Unet or TransUnet. The proposed framework has been evaluated on cine CMRI, collected from 100 patients, and evaluated using different metrics (Dice coefficient, Jaccard Index, and Hausdorff distance). The results documented an improvement of the segmentation accuracy (0.91, 0.82, 4.69 mm) using the proposed framework with TransUnet compared to the segmentation obtained by stand-alone Unet (0.75, 0.68, 7.54 mm). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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EffiSegNet: Gastrointestinal Polyp Segmentation through a Pre-Trained EfficientNet-based Network with a Simplified Decoder 46

EffiSegNet: Gastrointestinal Polyp Segmentation through a Pr...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Vezakis, Ioannis A. Georgas, Konstantinos Fotiadis, Dimitrios Matsopoulos, George K. Tecreando B.V. Amsterdam Netherlands National Technical University of Athens Biomedical Engineering Laboratory School of Electrical and Computer Engineering Athens Greece University of Ioannina Dept. of Materials Science and Engineering Ioannina Greece

ISBN: (纸本)9798350371499

This work introduces EffiSegNet, a novel segmentation framework leveraging transfer learning with a pre-trained Convolutional Neural Network (CNN) classifier as its backbone. Deviating from traditional architectures with a symmetric U-shape, EffiSegNet simplifies the decoder and utilizes full-scale feature fusion to minimize computational cost and the number of parameters. We evaluated our model on the gastrointestinal polyp segmentation task using the publicly available Kvasir-SEG dataset, achieving state-of-the-art results. Specifically, the EffiSegNet-B4 network variant achieved an F 1 score of 0.9552, mean Dice (mDice) 0.9483, mean Intersection over Union (mIoU) 0.9056, Precision 0.9679, and Recall 0.9429 with a pre-trained backbone - to the best of our knowledge, the highest reported scores in the literature for this dataset. Additional training from scratch also demonstrated exceptional performance compared to previous work, achieving an F 1 score of 0.9286, mDice 0.9207, mIoU 0.8668, Precision 0.9311 and Recall 0.9262. These results underscore the importance of a well-designed encoder in image segmentation networks and the effectiveness of transfer learning approaches. © 2024 IEEE.

关键词： Semantic Segmentation

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Optimizing DC Motor Control via Leader Harris Hawks Algorithm with ITSE-ZLG Objective Function 10

Optimizing DC Motor Control via Leader Harris Hawks Algorith...

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10th IEEE International Conference on Power Systems, ICPS 2023

作者： Ayinla, Shehu Lukman Amosa, Temitope Ibrahim Rahman, Md. Siddikur Owonikoko, Waheed Rahman, Md Ashiqur Barua, Sourav Rahman, Tuhibur Liou, Molla Shahadat Hossain Department of Electrical and and Electronics Engineering Seri Iskandar Perak Malaysia University of Ilorin Department of Computer Engineering Ilorin Nigeria University of Vermont Department of Electrical and Biomedical Engineering Burlington United States Green University of Bangladesh Department of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350318739

Proportional Integral and Derivative (PID) controllers are widely employed to normalize the response of numerous DC motor-powered systems, such as electric locomotives, traction systems, etc. Specifically, this category of controller is ubiquitous due to their simplicity, ease of control, and low-cost. However, their design parameters need to be carefully tuned to enhance control performance. A novel LHHO-PID controller with a compound objective function that combine Integral of Time multiplied Squared Error (ITSE) with Zwee-Lee Gaing's (ZLG) time-domain performance criterion is presented in this current study to enhance the control performance of a DC motor system. The system's performance was assessed by analyzing its response across various dimensions, including frequency responses, convergence profile and time. The results demonstrated that the developed PID-based controller exhibited a commendable performance in regulating the DC motor speed as compared to other existing PID-based controllers in the domain. The time response analysis showed an improvement of 7.2% compared to the best performing controller in rise time, a settling time of 0.1204 seconds, zero overshoot and negligible steady state error. These findings indicate that the proposed LHHO-PID controller has the capacity to regulate the speed of a DC motor efficiently in a variety of industrial applications. © 2023 IEEE.

关键词： DC motors

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