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VISION-iT:A Framework for Digitizing Bubbles and Droplets

Energy and AI 2024年第1期15卷 26-35页

作者： Youngjoon Suh Sanghyeon Chang Peter Simadiris Tiffany B.Inouye Muhammad Jahidul Hoque Siavash Khodakarami Chirag Kharangate Nenad Miljkovic Yoonjin Won Department of Mechanical and Aerospace Engineering University of CaliforniaIrvine4200 Engineering GatewayCA 92617-2700USA Department of Electrical Engineering and Computer Science University of CaliforniaIrvine5200 Engineering HallCA 92617-2700USA Department of Mechanical Science and Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA Mechanical and Aerospace Engineering Department Case Western Reserve UniversityClevelandOH44106USA Department of Electrical and Computer Engineering University of Illinois at Urbana-ChampaignUrbanaIL61801USA Materials Research Laboratory University of Illinois at Urbana-ChampaignUrbanaIL61801USA International Institute for Carbon Neutral Energy Research(WPI-12CNER) Kyushu University744 Moto-okaNishi-kuFukuoka 819-0395Japan

Quantifying the nucleation processes involved in liquid-vapor phase-change phenomena,while dauntingly challenging,is central in designing energy conversion and thermal management *** technological advances in the deep learning and computer vision field offer the potential for quantifying such complex two-phase nucleation processes at unprecedented *** leveraging these new technologies,a multiple object tracking framework called“vision inspired online nuclei tracker(VISION-iT)”has been proposed to extract large-scale,physical features residing within boiling and condensation ***,extracting high-quality features that can be integrated with domain knowledge requires detailed discussions that may be field-or case-specific *** this regard,we present a demonstration and discussion of the detailed construction,algorithms,and optimization of individual modules to enable adaptation of the framework to custom *** concepts and procedures outlined in this study are transferable and can benefit broader audiences dealing with similar problems.

关键词： Deep learning computer vision Nucleation Heat transfer Phase-change phenomena

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CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

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computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood Ul Haq Muhammad Athar Javed Sethi Najib Ben Aoun Ala Saleh Alluhaidan Sadique Ahmad Zahid farid Department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and Information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan Department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, COMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the COMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence

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Carbon nanotube transistor technology for More-Moore scaling

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Nano research 2021年第9期14卷 3051-3069页

作者： Qing Cao Department of Materials Science and Engineering Department of Electrical and Computer EngineeringDepartment of Chemistry Seitz Materials Research LaboratoryUniversity of Illinois at Urbana-ChampaignUrbanaIL 61820USA

Scaling of silicon field-effect transistors has fueled the exponential development of microelectronics in the past 60 years,but is now close to its physical limits with the critical dimensions of state-of-the-art silicon devices approaching the sub-10 nm *** nanotubes have been suggested to hold great promise of replacing the central role of silicon in the next-generation logic switches with their unique geometrical and electrical *** this article,I firstly examine the scaling advantages of carbon nanotubes compared to silicon from technology-development perspective,and then review the latest progress on addressing the manufacturability issues for scaled carbon-nanotube transistors,from materials to device-integration ***,the possible pathways for nanotube transistors to transition into commercial applications are discussed.

关键词： carbon nanotube transistor scaling

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Multi-Timescale Trading Strategy for Renewable Power to Ammonia Virtual Power Plant in the Electricity, Hydrogen, and Ammonia Markets

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2023年第4期1卷 322-335页

作者： Wu, Sirui Lin, Jin Li, Jiarong Liu, Feng Song, Yonghua Xu, Yanhui Cheng, Xiang Yu, Zhipeng Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing100087 China Tsinghua University Sichuan Energy Internet Research Institute Chengdu610213 China University of Macau Department of Electrical and Computer Engineering Macau999078 China Tsinghua University Department of Electrical Engineering Beijing100087 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China

Renewablepower to ammonia (RePtA) is a prominent zero-carbon pathway for decarbonization. Due to the imbalance between renewables and production energy demand, the RePtA system relies on electricity exchange with the power grid. Participating in the electricity market as a virtual power plant (VPP) may help to reduce energy costs. However, the power profile of local photovoltaics and wind turbines is similar to those in the market, resulting in rising energy costs under the conventional strategy. Hence, we develop a multi-timescale trading strategy for the RePtA VPP in the electricity, hydrogen, and ammonia markets. By utilizing the hydrogen and ammonia buffer systems, the RePtA VPP can optimally coordinate production planning. Moreover, we find it possible to describe the trading of electricity, ammonia, and hydrogen in a unified timeframe. The two-stage robust optimization model of the electricity market is extended to multiple markets and solved by the column and constraint generation (CC&G) algorithm. The case is derived from an actual project in the Inner Mongolia Autonomous Region. Sensitivity analysis demonstrates the economic advantages of the RePtA VPP joining multiple markets over the conventional strategy and reveals the necessity of the hydrogen and ammonia buffer and reactor flexibility. © 2023 IEEE.

关键词： Ammonia

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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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Generation of Squeezed Light in Silicon Nitride Photonic Integrated Chips

Generation of Squeezed Light in Silicon Nitride Photonic Int...

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CLEO: Fundamental Science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Liu, Shuai Hariri, Abdulkarim Wu, Bo-Han Zhang, Yuheng Zhang, Zheshen Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States

ISBN: (纸本)9781957171395

关键词： Photonic integrated circuits

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Investigating Thermal Effects and Mitigation Strategies in Multi-Finger GaN HEMTs 2

Investigating Thermal Effects and Mitigation Strategies in M...

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2nd International Microwave and Antenna Symposium, IMAS 2024

作者： Avval, Amirreza G. Nouri, Soheil Denninghoff, Dan Darwish, Ali El-Ghazaly, Samir M. University of Arkansas Department of Electrical Engineering and Computer Science FayettevilleAR United States Hrl Laboratories MalibuCA United States Army Research Laboratory AdelphiMD United States

ISBN: (纸本)9798350356359

Gallium Nitride High Electron Mobility Transistors have garnered attention as promising solutions for high-power and high-frequency applications, attributed to their exceptional features such as high electron mobility, high breakdown voltage, and wide bandgap. However, the efficacy of GaN HEMTs is challenged by some restrictive phenomena, notably self-heating and thermal effects. This paper presents experimental results from DC analysis conducted on different GaN HEMT devices featuring various numbers of fingers, alongside an examination of the thermal impact on device performance. The correlation between finger count in multi-finger HEMTs and device performance is explored, followed by a discussion on mitigation strategies aimed at optimizing device design and structures to address these challenges. © 2024 IEEE.

关键词： III-V semiconductors

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Efficient Hardware Design of a Secure Cancellable Biometric Cryptosystem

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Intelligent Automation & Soft Computing 2023年第4期36卷 929-955页

作者： Lamiaa A.Abou Elazm Walid El-Shafai Sameh Ibrahim Mohamed G.Egila H.Shawkey Mohamed K.H.Elsaid Naglaa F.Soliman Hussah Nasser AlEisa Fathi E.Abd El-Samie Department of Microelectronics Electronics Research InstituteAlnozhaEgypt Department of Electronics and Electrical Communications Engineering Ain Shams UniversityCairoEgypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh 11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Biometric security is a growing trend,as it supports the authentication of persons using conﬁdential biometric *** of the transmitted data in multi-media systems are susceptible to attacks,which affect the security of these *** systems provide sufﬁcient protection and privacy for *** recently-introduced cancellable biometric recognition systems have not been investigated in the presence of different types of *** addition,they have not been studied on different and large biometric *** point that deserves consideration is the hardware implementation of cancellable biometric recognition *** paper presents a suggested hybrid cancellable biometric recognition system based on a 3D chaotic *** rationale behind the utilization of the 3D chaotic cryptosystem is to guarantee strong encryption of biometric templates,and hence enhance the security and privacy of *** suggested cryptosystem adds signiﬁcant permutation and diffusion to the encrypted biometric *** introduce some sort of attack analysis in this paper to prove the robustness of the proposed cryptosystem against *** addition,a Field Programmable Gate Array(FPGA)implementation of the pro-posed system is *** obtained results with the proposed cryptosystem are compared with those of the traditional encryption schemes,such as Double Random Phase Encoding(DRPE)to reveal superiority,and hence high recogni-tion performance of the proposed cancellable biometric recognition *** obtained results prove that the proposed cryptosystem enhances the security and leads to better efﬁciency of the cancellable biometric recognition system in the presence of different types of attacks.

关键词： Information security cancellable biometric recognition systems cryptanalysis 3D chaotic map encryption FPGA

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Estimating Floating Ice Coverage in Tidewater Glacier Bays Automatically from Aerial Imagery

Estimating Floating Ice Coverage in Tidewater Glacier Bays A...

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OCEANS 2024 - Halifax, OCEANS 2024

作者： Vishnu, Hari Tianyue, Lin Chitre, Mandar Kalyan, Bharath Venables, Emily J. Tropical Marine Science Institute National University of Singapore Acoustic Research Laboratory Singapore National University of Singapore Department of Electrical and Computer Engineering Singapore UiT The Arctic University of Norway Norway

ISBN: (纸本)9798331540081

This study focuses on the estimation of floating ice distribution on the sea surface from aerial imagery at tidewater glaciers. The presence of ice-mélange in the glacial bay affects ice-loss at the glacier terminus via buttressing of the glacier face, insulation from ocean heat and breaking of oceanic currents. Thus, estimation of its formation, evolution, distribution and dissipation will aid an understanding of climate-change mechanisms at glacial bays. Given the challenges stemming from lack of data and labeled training samples, we employ a pre-trained vision model with zero-shot performance, the Segment Anything Model (SAM). SAM is fine-tuned to perform automatic estimation of floating-ice distribution on a dataset of images collected in Svalbard at various locations and through various modalities, by segmenting the images into floating ice and ocean surface not covered by ice. The Low-rank adaptation technique is employed on the image encoder structure to reduce the training data and hardware resources needed for model fine-tuning. This approach opens new avenues for real-time analysis of glacial dynamics and their implications on global climate patterns. © 2024 IEEE.

关键词： Aerial photography

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Dubins Vehicle Intercept of a Brownian Target on a Sphere 63

Dubins Vehicle Intercept of a Brownian Target on a Sphere

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Milutinovic, Dejan Casbeer, David W. University of California Department of Electrical and Computer Engineering Santa CruzCA United States Air Force Research Laboratory Control Science Center Wright-Patterson AFBOH United States

ISBN: (纸本)9798350316339

This paper focuses on a navigation of a Dubins vehicle (DV) to intercept a moving target on a sphere. The uncertainty in the target motion is described by a Brownian motion model. An Itô-type stochastic differential equation for the relative motion between DV and the Brownian moving target is derived. This stochastic differential equation is used to formulate an intercept controller as a minimum time optimal controller. The properties of the controller are incorporated into the numerical computations of the controller, which by its construction can intercept a Brownian target. Our numerical simulation results show that the computed controller can intercept both stationary and moving targets on the sphere. © 2024 IEEE.

关键词： Stochastic systems

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