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Self-powered tactile sensor for real-time recognition of Morse code based on machine learning

Nano Research 2025年第2期18卷 760-768页

作者： Shenxing Tan Yang Jiang Xujiang Chao Fei Liang Ripeng Li Tao Jiang Hai-Dong Yu Zhong Lin Wang Guangzhou Institute of Blue Energy Guangzhou 510555China Frontiers Science Center for Flexible Electronics Xi'an Institute of Flexible Electronics(IFE)and Xi'an Institute of Biomedical Materials&EngineeringNorthwestern Polytechnical UniversityXi'an 710072China Beijing Key Laboratory of Micro-Nano Energy and Sensor Center for High-Entropy Energy and SystemsBeijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijing 101400China School of Nanoscience and Engineering University of Chinese Academy of SciencesBeijing 100049China School of Mechanical Engineering Northwestern Polytechnical UniversityXi’an 710072China School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and TelecommunicationsBeijing 100876China

Developing lightweight,green,and flexible wearable electronics with high sensitivity and multifunctional sensing capabilities is of important significance in the field of outdoor sports,such as mountaineering,animal tracking and *** work proposes a silk fibroin fibers-based triboelectric nanogenerator(SF TENG)to harvest tiny energy from human fingertip tapping and act as a self-powered tactile *** SF-TENG adopts a green,efficient,and low-cost fabrication strategy,in which a breathable and electropositive silk fibroin fiber membrane and a silver conductive layer are prepared by electrostatic spinning and magnetron sputtering,and combined with a conductive cloth and a breathable tape to form a flexible sensor that can be attached to a human *** thin and soft portable TENG device,having a thickness of only 0.3 mm and a mass of 354 mg at the dimension of 4.5 cm×4.5 cm,can generate a maximum power density of 1.0 mW·m^(–2).Furthermore,the SF-TENG has excellent sensitivity of 1.767 mV·Pa^(–1) with good cyclic *** superior sensing characteristics provide new avenues for Morse code applications toward outdoor wearable autonomous *** proposed SF-TENG offers promising solutions in multi-scenario outdoor sport,human-machine interface interaction,and security systems.

关键词： flexible electronics triboelectric nanogenerator silk fibroin Morse code translation

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On-chip sample preparation and biosensing: Can porous silicon membranes do it all?

On-chip sample preparation and biosensing: Can porous silico...

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2023 International Electron Devices Meeting, IEDM 2023

作者： Leïchlé, T. He, Y. Vasconcellos, D. Silvade Imbemon, E. Bourrier, D. Université de Toulouse Cnrs LAAS-CNRS Toulouse France School of Electrical and Computer Engineering Georgia Tech-CNRS International Research Laboratory AtlantaGA United States

ISBN: (纸本)9798350327670

Porous silicon is a promising material for analytical biology, which has been used not only for biosensing but also for sample preparation in microfluidics. We therefore speculate that porous silicon membranes can be used to achieve all the functions involved in the analytical process on a single chip. However, integrating several membranes with the different characteristics required to implement these functions on-chip is challenging. In this work, we present a fabrication strategy for the monolithic integration of multiple membranes with tunable properties in planar microfluidics, thus paving the way towards the use of porous silicon to do it all, from sample preparation to biosensing. © 2023 IEEE.

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Investigation of Au-AuSn Bonding Below Eutectic Temperature for Gigahertz Bulk Acoustic Wave Transmission 24

Investigation of Au-AuSn Bonding Below Eutectic Temperature ...

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24th Electronics Packaging Technology Conference, EPTC 2022

作者： Chen, Daniel S.H. Wai, Eva L.C. Yeo, Yi Xuan Sharma, Jaibir Lal, Amit Chai, Kevin T.C. Singapore138634 Singapore School of Electrical and Computer Engineering Cornell University SonicMEMS Laboratory IthacaNY United States

ISBN: (纸本)9798350398854

This work reports a novel approach to form chip-level Au to AuSn bonding below eutectic temperature, and the techniques to investigate the bonding interface quality for gigahertz bulk acoustic wave (BAW) transmission. The primary study involved bonding a 6\times 6 mm MEMS chip with BAW transducer arrays to an 8\times 8 mm silicon substrate by an intermediate Au-AuSn layer deposited by e-beam evaporation. The bonding was achieved by using a custom-made chip bonder where the compression was done at room temperature and later heat treated in an N2 ambient oven at 200°C to form the bond. The bonding quality was evaluated by pulsating the MEMS transducers with 80 ns pulsed-RF signal at 1.465 GHz to generate a packet of bulk acoustic waves and then assess the reflected echo signals. With good interface bonding, it is hypothesized that acoustic energy can propagate through the bonded layer and back to the transducers. By analyzing the received echo signals on the transducer array, we predicted whether acoustic transmission through the bonding interface occurred. Electro-acoustic measurements were done pre/post bonding to compare the pulse-echo signature differences. There are a total of 32 transducer arrays, which cover half of the MEMS chip area and were used to correlate with the CSAM inspection to determine the uniformity of the bond. © 2022 IEEE.

关键词： MEMS

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Using Large Language Models to Mitigate Human-Induced Bias in SMS Spam: An Empirical Approach 4

Using Large Language Models to Mitigate Human-Induced Bias i...

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4th IEEE International Conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Fuhnwi, Gerard Shu Revelle, Matthew Whitaker, Bradley Izurieta, Clemente Montana State University Gianforte School of Computing BozemanMT United States Montana State University Electrical & Computer Engineering BozemanMT United States Montana State University Pacific Northwest National Laboratory Idaho National Laboratory Gianforte School of Computing BozemanMT United States

ISBN: (纸本)9798331518882

Short Message Service (SMS) is a widely used text messaging feature on both basic and smartphones. SMS spam detection is a crucial task. Traditional machine learning approaches often struggle in this domain due to their reliance on manually crafted features, such as keyword detection, which can result in overly simplistic patterns and misclassification of more complex messages. With this shortcoming, these models can amplify human-induced biases if the training data contains inconsistent labeling or subjective interpretations, leading to unfair treatment of specific keywords or contexts. Conversely, advanced LLMs present effective approaches to addressing such issues, as they can more accurately capture linguistic patterns, contextual nuances, and textual ambiguities than traditional models, representing a substantial advancement in improving label accuracy. This paper proposes utilizing LLMs to address humaninduced labeling bias in spam detection and applying different prompt design methods to guide the process. In text classification, we surveyed two leading-edge LLMs, ChatGPT and Gemini, and evaluated them on the English SMS spam dataset source from UC Irvine's Machine Learning Repository. We explored the highest-performing prompt designs using approaches like in-context learning. The findings indicate that in-context techniques for prompting improve model effectiveness by reducing human-induced (contextual) labeling bias in SMS spam detection with a Balanced Accuracy of 82% 97% and an Equal Opportunity Difference (EOD) of precisely zero, indicating LLMs' trustworthiness (fairness) in reducing this bias compared to traditional machine learning approaches. Our results also suggested that expanding the sample size can decrease LLMs' ability to reduce human-induced labeling bias in spam detection. In general, this study provides information on the strengths and limitations of LLMs and suggestions for methods to minimize human-induced labeling bias in spam detection

关键词： Adversarial machine learning

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On the Explicit Relation between Mains-Side Current THD and DC Link Voltage Controller Gain in Grid-Connected Converters 26

On the Explicit Relation between Mains-Side Current THD and ...

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26th IEEE International Conference on Intelligent engineering systems, INES 2022

作者： Kuperman, Alon School of Electrical and Computer Engineering Ben-Gurion University of the Negev Applied Energy Laboratory Beer-Sheva8410501 Israel

ISBN: (数字)9781665492096

ISBN: (纸本)9781665492096

It is known that attainable DC link voltage loop bandwidth in grid-connected converters is limited due to trade-off with AC-side current total harmonic distortion (THD). The letter reveals that THD requirement inflicts the value of DC link voltage controller gain only at double-grid frequency. On the other hand, the desired phase margin poses another restriction on the controller performance. As a result, if a typical PI compensator is employed, two abovementioned performance merits impose DC link voltage loop dynamics. The letter concludes that dynamic performance may be improved without deteriorating grid-side current quality by adding a degree-of-freedom to compensator structure so that the loop gain magnitude at double-grid frequency and the crossover frequency are decoupled. Experimental results validate the revealed findings. © 2022 IEEE.

关键词： Controllers

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Low-profile metamaterial with ultra-wide band ratio based on active frequency selective surfaces

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Optics Express 2025年第7期33卷 15901-15916页

作者： Xu, Ruize Ren, Peng Li, Yi Gu, Chao Xu, Baoyi Xue, Wei Wang, Minrui Xiang, Zheng State Key Laboratory of Integrated Services Networks Xidian University No. 2 South Taibai Road Xi’an710071 China Centre for Wireless Innovation School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast BelfastBT3 9DT United Kingdom School of Electronics and Information Northwestern Polytechnical University Xi’an710072 China

This paper presents a low-profile metamaterial with ultra-wide band ratio (BR) based on active frequency selective surfaces (AFSSs) to overcome the limited tuning range and suboptimal profile of current designs. The proposed design consists of a periodic pattern printed on the top of a thin substrate and a bias network on the bottom, with varactor diodes symmetrically integrated into the top metal layer. Based on the equivalent circuit model, the mechanism of wideband tuning is analyzed theoretically. The corresponding simulation results indicate that the designed AFSS can achieve a large tuning range for the first operating band from 1.12 to 7.86 GHz while maintaining stability in the second operating band. This allows for a continuous variation from a small BR to a large BR, with a tuning range reaching 601.79%. To the best of the authors’ knowledge, this is the first time that the concept of band ratio range (BRR) has been proposed to characterize the level of BR variation. Considering the feasibility of fabrication and limitations due to the tuning range of a single commercially available varactor diode, measurements were performed based on two fabricated prototypes. The simulation results are consistent with the experimental results. Compared with existing literature, the proposed AFSS can provide significant advantages such as good angular stability, polarization insensitivity, miniaturization, and ultra-wideband tunability. Our design is applicable to controlling the propagation of electromagnetic waves in various communication systems and is well-suited for electromagnetic shielding in communication devices or optical devices across different frequency bands. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Electromagnetic shielding

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An Efficient Particle YOLO Detector for Urine Sediment Detection 4th

An Efficient Particle YOLO Detector for Urine Sediment Dete...

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Chen, Zejian Hu, Rong Chen, Fukun Fan, Haoyi Ching, Fum Yew Li, Zuoyong Su, Shimei Fujian Provincial Key Laboratory of Big Data Mining and Applications School of Computer Science and Mathematics Fujian University of Technology Fujian Fuzhou350118 China School of Computer and Artificial Intelligence Zhengzhou University Henan Zhengzhou450001 China School of Computer Sciences Universiti Sains Malaysia Penang11800 Malaysia Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fujian Fuzhou350121 China School of Electrical Engineering Zhengzhou University Henan Zhengzhou450001 China

ISBN: (纸本)9783031201011

Urine sediment detection is an essential aid in assessing kidney health. Traditional machine learning approaches treat urine sediment particle detection as an image classification task, segmenting particles for detection based on information such as edges or thresholds. However, the segmentation of sediment particles is complex due to the low contrast and weak edge characteristics of urine sediment images. In this paper, we consider urine sediment particle detection as a object detection task and propose the YOLOv5s-CBL, a detector dedicated to particle detection. Specifically, to mitigate the impact of background noise on detection accuracy, we inherit CBAM on the YOLOv5s model to help the network filter useless noise information and find regions of interest to extract target features. Then, we expand the original three-scale feature layer to improve the sensitivity of the model to larger-scale target sediment particles. Finally, we use the BiFPN structure instead of the original PANet combined with the FPN structure, which can more effectively fuse multiple different scales of information to improve the detection performance of the model. We compared state-of-the-art methods on two real-world datasets, and the experimental results demonstrated the effectiveness of YOLOv5s-CBL. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object detection

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Improving Multiple Sclerosis Disease Prediction Using Hybrid Deep Learning Model

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computers, Materials & Continua 2024年第10期81卷 643-661页

作者： Stephen Ojo Moez Krichen Meznah A.Alamro Alaeddine Mihoub Gabriel Avelino Sampedro Jaroslava Kniezova Department of Electrical and Computer Engineering College of EngineeringAnderson UniversityAndersonSC 29621USA Faculty of Computing and Information Al-Baha UniversityAl-Baha65528Saudi Arabia ReDCAD Laboratory University of SfaxSfax3038Tunisia Department of Information Technology College of Computer&Information SciencePrincess Nourah Bint Abdul Rahman UniversityRiyadh11564Saudi Arabia Department of Management Information Systems College of Business and EconomicsQassim UniversityP.O.Box 6640Buraidah51452Saudi Arabia School of Management and Information Technology De La Salle-College of Saint BenildeManila1004Philippines Department of Information Management and Business Systems Faculty of ManagementComenius University BratislavaBratislava 2582005Slovakia

Myelin damage and a wide range of symptoms are caused by the immune system targeting the central nervous system in Multiple Sclerosis(MS),a chronic autoimmune neurological *** disrupts signals between the brain and body,causing symptoms including tiredness,muscle weakness,and difficulty with memory and *** methods for detecting MS are less precise and time-consuming,which is a major gap in addressing this *** gap has motivated the investigation of new methods to improve MS detection consistency and *** paper proposed a novel approach named FAD consisting of Deep Neural Network(DNN)fused with an Artificial Neural Network(ANN)to detect MS with more efficiency and accuracy,utilizing regularization and combat *** use gene expression data for MS research in the GEO GSE17048 *** dataset is preprocessed by performing encoding,standardization using min-max-scaler,and feature selection using Recursive Feature Elimination with Cross-Validation(RFECV)to optimize and refine the ***,for experimenting with the dataset,another deep-learning hybrid model is integrated with different ML models,including Random Forest(RF),Gradient Boosting(GB),XGBoost(XGB),K-Nearest Neighbors(KNN)and Decision Tree(DT).Results reveal that FAD performed exceptionally well on the dataset,which was evident with an accuracy of 96.55%and an F1-score of 96.71%.The use of the proposed FAD approach helps in achieving remarkable results with better accuracy than previous studies.

关键词： Multi Sclerosis(MS) machine learning deep learning artificial neural network healthcare

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A Dual-Resonance Frequency Selective Surface Genetically Optimized for Dielectric Characterization

A Dual-Resonance Frequency Selective Surface Genetically Opt...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Howard, Christopher T. Hunt, William D. Allen, Kenneth W. Georgia Tech Research Institute Advanced Concepts Laboratory AtlantaGA United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA United States

ISBN: (纸本)9781665442282

The use of frequency-selective surfaces for the characterization of dielectric materials has been demonstrated. In this simulation study, a surface with dual resonances is optimized for this purpose using a genetic algorithm and a finite-difference time-domain model. The dependence of transmission spectra on various dielectric test materials is also presented. © 2023 IEEE.

关键词： Frequency selective surfaces

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Wildfire Risk Assessment and Detection for Remote Terrain

Wildfire Risk Assessment and Detection for Remote Terrain

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： Randy Essikpe Jennifer Blain Christen School of Biological and Health Systems Engineering School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ USA

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

Many remote powerlines do not have enough wildfire surveillance to enable preventive or mitigation measures, resulting in massive destruction in the incidence of wildfires hitting powerlines. This project seeks to build a multi-sensor-based embedded system that monitors wildfire-related weather conditions to assess the risk and alert the appropriate fire management team, via a wireless data transfer protocol in case of outbreaks. The design of the system will prove useful at power stations where other safety features are incorporated to reduce the occurrences of fires. The embedded system works based on a Hot-Dry-Windy index that monitors fire weather conditions that directly affect the spread of wildfires.

关键词： Wireless communication Wireless sensor networks Wildfires Embedded systems Protocols Prevention and mitigation Surveillance

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