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Conference on electrical Insulation and Dielectric Phenomena, (CEIDP)

作者： Jierui Zhou Marina Dabaghian Anna Marie LaChance Jing Hao Wesley Zhong Luyi Sun Yang Cao Department of Electrical and Computer Engineering University of Connecticut Storrs CT USA Electrical Insulation Research Center Institute of Materials Science University of Connecticut Storrs CT USA Department of Chemical and Biomolecular Engineering University of Connecticut Storrs CT USA Polymer Program Institute of Materials Science University of Connecticut Storrs CT USA

Polymer-thin films are critical dielectric materials for capacitive energy storage in power and electronic systems. The rapid development of wide bandgap semiconductors urgently calls for polymers that can attain high energy density and high charge-discharge efficiency at elevated temperatures. However, high-temperature polymers usually suffer from compromised dielectric breakdown strength and soaring conduction loss due to the intrinsic constraint between their bandgaps and thermal stability. In this work, we propose a facile and high throughput interface engineering technique utilizing nanocoatings formed by montmorillonite (MMT) nanoclays, which can serve as an out-of-the-box solution to bypass this constraint. The highly ordered MMT-based nanocoatings with layered structure can significantly block the excessive charge injection at high electric fields and dissipate the charge carriers along the in-plane direction. The MMT-coated PI films exhibit improved breakdown strength, suppressed conduction loss, and boosted charging-discharging efficiency. This work holds the promise of improving the dielectric properties of polymers through surface engineering, enabling their application at concurrent electrical and thermal extremes.

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Prediction of Post-COVID-19 Pandemic Learning Mode Preferences Using Machine Learning

Prediction of Post-COVID-19 Pandemic Learning Mode Preferenc...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Agus Pratondo Astri Novianty Budi Laksono Putro Siska Komala Sari Department of Multimedia Engineering School of Applied Sciences Telkom University Bandung Indonesia Department of Computer Engineering School of Electrical Engineering Telkom University Bandung Indonesia Department of Computer Science Education Indonesia University of Education Bandung Indonesia Diploma Program of Information System School of Applied System Telkom University Bandung Indonesia

The COVID-19 epidemic has had a huge impact on the educational landscape, prompting the adoption of online and remote learning as viable alternatives to conventional in-person instruction. In order to create effective educational methods as institutions prepare for the post-pandemic period, it is essential to understand students' preferences for various learning modes. With the aid of machine learning techniques, this study seeks to forecast preferences for learning styles in post-pandemic higher education. The study made use of a dataset compiled from a wide range of college students, which included information on the institution type (public or private), program type (bachelor's or diploma), academic discipline (science or humanities), gender, year of study, internet use, communication costs, comorbidity status, vaccination history, gadget and laptop ownership, and preferred learning mode (online, in-person, or both). For the aim of prediction, a Support Vector Machine (SVM) was used. Its kernel functions included linear, polynomial, radial basis function (RBF), and sigmoid. Performance criteria like accuracy, precision, recall, and F1 score were used to assess the models after the dataset was randomly partitioned into training and testing sets. The findings showed that for identifying the preferred mode of learning, SVM with the RBF kernel had the highest prediction accuracy (91.67%). Further proving the RBF kernel's efficacy, the confusion matrix analysis showed that high values in the diagonal represented accurate predictions for each of the three classes (both online and onsite). The results imply that machine learning approaches, in particular SVM with the RBF kernel, may accurately forecast students' preferences for learning modes in the post-pandemic situation. In a post-pandemic society, the findings provide insightful information that may be used to build adaptable and inclusive learning models and put them into practice.

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Analysis of Common Mode Currents and Harmonic Pollution at Supplying Induction Motors from Static Converters with Variable Modulation Frequency

Analysis of Common Mode Currents and Harmonic Pollution at S...

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Power Quality and Electromagnetic Compatibility at Low Frequency (PQEMC-LF)

作者： Iurie Nuca Lu Wan Petre - Marian Nicolae Ileana - Diana Nicolae Flavia Grassi Xinglong Wu Electrical Engineering Energetic and Aeronautics Dept. University of Craiova Craiova Romania Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy Computer Science and Information Technology Dept. University of Craiova Craiova Romania

The problems of Electromagnetic Compatibility (EMC) in three-phase systems are less studied than single-phase or direct current, due to the smaller ratio of emissions relative to the rated power of such systems. This paper is focused on the problem of emissions in three-phase variable frequency drive systems in the low-frequency EMC range, specifically on the common mode current through the connected ground wire between the static converter and power grid. The common mode current is determined to be variable depending on switching frequency. For a deeper understanding Fast Fourier Transform was used to decompose the signal. Main parameter to understand the magnitude of common mode current was the RMS of the current. The decomposition showed a significant DC component which cannot be picked up by the used RF probe, thus presenting a noise offset necessary to be considered when calculating the total effective value of common mode current. The analysis was made on the time-domain representation and the frequency behavior of the converter. The paper suggests that the standard measurement in the low-frequency range and the picked-up signal are investigated enough, as there is a disparity in the impact of emissions in the low-frequency range compared to what off-the-shelf devices have to offer, which are standard compliant, but still present considerable emissions.

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Robust digital molecular design of binarized neural networks 27

Robust digital molecular design of binarized neural networks

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27th International Conference on DNA Computing and Molecular programming, DNA 2021

作者： Linder, Johannes Chen, Yuan-Jyue Wong, David Seelig, Georg Ceze, Luis Strauss, Karin University of Washington Paul G. Allen School of Computer Science and Engineering SeattleWA United States Microsoft Research RedmondWA United States University of Washington Department of Bioengineering SeattleWA United States University of Washington Department of Electrical and Computer Engineering SeattleWA United States

ISBN: (纸本)9783959772051

Molecular programming - a paradigm wherein molecules are engineered to perform computation - shows great potential for applications in nanotechnology, disease diagnostics and smart therapeutics. A key challenge is to identify systematic approaches for compiling abstract models of computation to molecules. Due to their wide applicability, one of the most useful abstractions to realize is neural networks. In prior work, real-valued weights were achieved by individually controlling the concentrations of the corresponding "weight" molecules. However, large-scale preparation of reactants with precise concentrations quickly becomes intractable. Here, we propose to bypass this fundamental problem using Binarized Neural Networks (BNNs), a model that is highly scalable in a molecular setting due to the small number of distinct weight values. We devise a noise-tolerant digital molecular circuit that compactly implements a majority voting operation on binary-valued inputs to compute the neuron output. The network is also rate-independent, meaning the speed at which individual reactions occur does not affect the computation, further increasing robustness to noise. We first demonstrate our design on the MNIST classification task by simulating the system as idealized chemical reactions. Next, we map the reactions to DNA strand displacement cascades, providing simulation results that demonstrate the practical feasibility of our approach. We perform extensive noise tolerance simulations, showing that digital molecular neurons are notably more robust to noise in the concentrations of chemical reactants compared to their analog counterparts. Finally, we provide initial experimental results of a single binarized neuron. Our work suggests a solid framework for building even more complex neural network computation. © 2021 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： Neural networks

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Development and Characterization of Zinc Dry Electrodes for Wearable Electrophysiology

Development and Characterization of Zinc Dry Electrodes for ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Cassia Rizq Alessandro D’Amico Aidan Truel Joelle Faybishenko Min Suk Lee Jeong-Hoon Kim Gert Cauwenberghs Virginia R. de Sa Department of Bioengineering University of California San Diego La Jolla USA Department of Cognitive Science University of California San Diego La Jolla USA Halıcıoğlu Data Science Institute University of California San Diego La Jolla USA Department of Electrical and Computer Engineering University of California San Diego La Jolla USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Zinc dry electrodes were fabricated and investigated for wearable electrophysiology recording. Results from electrochemical impedance spectroscopy and electromyography functionality testing show that zinc electrodes are suitable for use in electrophysiology. Two electrode configurations were tested: a standard disc and a custom tripolar concentric ring configuration. However, no functional benefit was observed with the tripolar concentric ring electrodes as compared to the disc electrodes.

关键词： Electrodes Electromyography Recording engineering in medicine and biology Zinc Standards Testing Electrochemical impedance spectroscopy

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Comparison of Coherent and Incoherent Donut Beams for Deep Tissue STED Microscopy

Comparison of Coherent and Incoherent Donut Beams for Deep T...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Thariq Shanavas Robert R. McLeod Mark E. Siemens Juliet T. Gopinath Department of Physics University of Colorado Boulder CO USA Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO USA Department of Physics University of Denver Denver CO Materials Science Engineering Program University of Colorado Boulder CO USA

We numerically compare the null quality for STED microscopy generated by Laguerre-Gaussian beams with orbital angular momentum and donut beams generated by incoherent addition of orthogonal Hermite Gaussian beams when... 详细信息

ISBN: (纸本)9781957171258

关键词： Biological imaging Gaussian beams Microscopy Spatial light modulators Spiral phase Step index fibers

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A Development of Object Detection System based on Deep Learning Approach to Support the Laparoscope Manipulating Robot (LMR)

A Development of Object Detection System based on Deep Learn...

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2022 International electrical engineering Congress, iEECON 2022

作者： Sonsilphong, Suphachoke Sonsilphong, Amornthep Hormdee, Daranee Khampitak, Kovit Khon Kaen University Data Science Health Informatics Program Academic Affairs Faculty of Medicine Khon Kaen Thailand Rajamangala University of Technology Isan Department of Electrical Engineering Khon Kean Thailand Khon Kaen University Embedded System RD Group Department of Computer Engineering Faculty of Engineering Khon Kean Thailand Khon Kean University Faculty of Medicine Department of Obstetrics and Gynecology Khon Kean Thailand

ISBN: (纸本)9781665402064

This paper presents the development of an object detection system based on the deep learning approach of computer vision to support the laparoscopic surgical robotic position control system. The system comprises two main phases, the training phase, and the real-time operating phase. In the training phase, a modified YOLOv4 algorithm is proposed to be adopted within the Darknet framework for training the weights of detection models. The best detection model is then selected to be assigned to the object detector in the real-time operating phase. The validation result of the detection model across the experiment datasets is 90% accuracy on average during the training phase. To validate the viability of real-time object detection, the proposed system was implemented in two test-cases of gynecologic surgery with the soft-body cadavers. © 2022 IEEE.

关键词： Laparoscopy

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CVO: Curriculum Vitae Optimization by Recommending Keywords to Undergraduate Students 11th

CVO: Curriculum Vitae Optimization by Recommending Keywords...

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11th and 12th EAI International Conference on Big Data Technologies and Applications, BDTA 2021 and BDTA 2022

作者： Santos, Cibele Góes, Fabrício Martins, Carlos da Cunha, Felipe Post-Graduation Program in Electrical Engineering Pontifícia Universidade Católica de Minas Gerais MG Belo Horizonte30535-901 Brazil Informatics Department University of Leicester Leicester United Kingdom Post-Graduation Program in Informatics Pontifícia Universidade Católica de Minas Gerais MG Belo Horizonte30535-901 Brazil Department of Computer Science Pontifícia Universidade Católica de Minas Gerais MG Belo Horizonte30535-901 Brazil

ISBN: (纸本)9783031336133

Candidate selection platforms have been widely used in companies that seek agility in the process of hiring. Candidates who do not meet the requirements of a job vacancy are disqualified in the first step, called screening. This stage has been automated due to the large volume of curriculum vitae (CV) of candidates per vacancy, particularly for internship vacancies. As a consequence, candidates receive little to none feedback and do not know how to improve/optimize their CVs for new applications. The goal of this paper is to realize the curriculum vitae optimization (CVO) process for internship vacancies by implementing a recommendation system that given an undergraduate student CV, it suggests the addition of relevant keywords, taking into account the student’s undergraduate course. This system is implemented based on the clustering of CVs keywords, from an internship recruitment private company database, into profile groups which are linked to internship vacancies. The experimental results showed that recommendations improved students CVs similarity (competitiveness within a specific field) from 18.83%, with 3 keywords recommendation, up to 50.67%, with 10 words. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Students

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Miniscope3D:optimized single-shot miniature 3D fluorescence microscopy

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Light(science & Applications) 2020年第1期9卷 367-379页

作者： Kyrollos Yanny Nick Antipa William Liberti Sam Dehaeck Kristina Monakhova Fanglin Linda Liu Konlin Shen Ren Ng Laura Waller UCB/UCSF Joint Graduate Program in Bioengineering University of CaliforniaBerkeleyCA 94720USA Department of Electrical Engineering&Computer Sciences University of CaliforniaBerkeleyCA 94720USA TIPs Department Universite libre de Bruxelles(ULB)1050 BrusselsBelgium

Miniature fluorescence microscopes are a standard tool in systems ***,widefield miniature microscopes capture only 2D information,and modifications that enable 3D capabilities increase the size and weight and have poor resolution outside a narrow depth ***,we achieve the 3D capability by replacing the tube lens of a conventional 2D Miniscope with an optimized multifocal phase mask at the objective’s aperture *** the phase mask at the aperture stop significantly reduces the size of the device,and varying the focal lengths enables a uniform resolution across a wide depth *** phase mask encodes the 3D fluorescence intensity into a single 2D measurement,and the 3D volume is recovered by solving a sparsity-constrained inverse *** provide methods for designing and fabricating the phase mask and an efficient forward model that accounts for the fieldvarying aberrations in miniature *** demonstrate a prototype that is 17mm tall and weighs 2.5 grams,achieving 2.76μm lateral,and 15μm axial resolution across most of the 900×700×390μm^(3) volume at 40 volumes per *** performance is validated experimentally on resolution targets,dynamic biological samples,and mouse brain *** with existing miniature single-shot volume-capture implementations,our system is smaller and lighter and achieves a more than 2×better lateral and axial resolution throughout a 10×larger usable depth *** microscope design provides single-shot 3D imaging for applications where a compact platform matters,such as volumetric neural imaging in freely moving animals and 3D motion studies of dynamic samples in incubators and lab-on-a-chip devices.

关键词： enable resolution narrow

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Visual Control and Mapping for UAV-Based Platform Inspection

Visual Control and Mapping for UAV-Based Platform Inspection

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Leonardo A. Fagundes Carlos M. Soria Raquel F. Vassallo Alexandre S. Brandão Department of Electrical Engineering Graduate Program on Computer Science Federal University of Viçosa Viçosa MG Brazil Facultad de Ingeniería Instituto de Automática Universidad Nacional de San Juan Argentine Department of Electric Engineering Federal University of Espirito Santo Vitória ES Brazil

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Autonomous take-off and landing capabilities are crucial in UAV vision-based missions, ensuring adaptive navigation, especially in challenging environments where realtime identification and interaction with a variety of landing platforms are required. In this context, this paper presents a servo-visual controller that uses pattern detection and color segmentation techniques to identify take-off/landing platforms and estimate their current orientation. The proposed system was subjected to experimental validation with four platforms positioned in different orientations, heights, and positions, demonstrating its versatility in various conditions. Our study addresses the Flying Robots Trial League challenge, which emulates mapping and inspection tasks in offshore platforms.

关键词： Visualization Offshore installations Navigation Color Inspection Autonomous aerial vehicles Aircraft Drones Aerospace control

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