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Physical Review Letters 2023年第8期130卷 083802-083802页

作者： Sen Yang Joshua A. Allen Chuchuan Hong Kellen P. Arnold Sharon M. Weiss Justus C. Ndukaife Interdisciplinary Materials Science Vanderbilt University Nashville Tennessee 37235 USA Vanderbilt Institute of Nanoscale Science and Engineering Vanderbilt University Nashville Tennessee 37235 USA Department of Electrical and Computer Engineering Vanderbilt University Nashville Tennessee 37235 USA

Photonic crystal cavities with bowtie defects that combine ultrahigh Q and ultralow mode volume are theoretically studied for low-power nanoscale optical trapping. By harnessing the localized heating of the water layer near the bowtie region, combined with an applied alternating current electric field, this system provides long-range electrohydrodynamic transport of particles with average radial velocities of 30 μm/s towards the bowtie region on demand by switching the input wavelength. Once transported to a given bowtie region, synergistic interaction of optical gradient and attractive negative thermophoretic forces stably trap a 10 nm quantum dot in a potential well with a depth of 10 kBT using a mW input power.

关键词： Electrokinetic flows Fluid-particle interactions Microfluidics Nanophotonics Photonic crystals Optical tweezers

Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear array.

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arXiv 2024年

作者： Ginio, Noam Lindenbaum, Michael Fishbain, Barak Liberzon, Dan Faculty of Civil and Environmental Engineering Technion Haifa320003 Israel Faculty of Computer Science Technion Haifa320003 Israel Interdisciplinary Program for Marine Engineering Technion Haifa320003 Israel

Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address these challenges a novel method was developed, using polarization filter equipped camera as the main sensor and Machine Learning (ML) algorithms for data processing [1,2]. The developed method training and evaluation was based on in-house made supervised dataset. Here we present this supervised dataset of polarimetric images of the water surface coupled with the water surface elevation measurements made by a linear array of resistance-type wave gauges (WG). The water waves were mechanically generated in a laboratory waves basin, and the polarimetric images were captured under an artificial light source. Meticulous camera and WGs calibration and instruments synchronization supported high spatio-temporal resolution. The data set covers several wavefield conditions, from simple monochromatic wave trains of various steepness, to irregular wavefield of JONSWAP prescribed spectral shape and several wave breaking scenarios. The dataset contains measurements repeated in several camera positions relative to the wave field propagation direction. © 2024, CC BY-NC-ND.

关键词： Water waves

Multi-task Learning for Few-Shot Differential Diagnosis of Breast Cancer Histopathology Images 2nd

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Multi-task Learning for Few-Shot Differential Diagnosis of...

2nd Workshop on Medical Image Learning with Noisy and Limited Data, MILLanD 2023

作者： Thoriya, Krishna Mutreja, Preeti Kalra, Sumit Paul, Angshuman Department of Electrical Engineering Indian Institute of Technology Jodhpur Jodhpur India Novealthy Innovations Pvt. Ltd. Jodhpur India Department of Computer Science Engineering Indian Institute of Technology Jodhpur Jodhpur India Interdisciplinary Research Platform - Smart Healthcare Indian Institute of Technology Jodhpur Jodhpur India

ISBN: (纸本)9783031471964

Deep learning models may be useful for the differential diagnosis of breast cancer histopathology images. However, most modern deep learning methods are data-hungry. But, large annotated dataset of breast cancer histopathology images are elusive. As a result, the application of such deep learning methods for the differential diagnosis of breast cancer is limited. To deal with this problem, we propose a few-shot learning approach for the differential diagnosis of the histopathology images of breast tissue. Our model is trained through two stages. We initially train our model for a binary classification task of identifying benign and malignant tissues. Subsequently, we propose a multi-task learning strategy for the few-shot differential diagnosis of breast tissues. Experiments on publicly available breast cancer histopathology image datasets show the efficacy of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Histology

Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using Random Forest, KNN, Decision Tree and Naïve Bayes 7

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Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using ...

7th IEEE International Conference on Information Technology and Digital Applications, ICITDA 2022

作者： Pohan, Husni Iskandar Suparta, Wayan Heryadi, Yaya Wibowo, Antoni Lukas Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

Dengue Hemorrhagic Fever is an acute viral infectious disease caused by the dengue virus. Transmitted through the bite of Aedes Mosquitoes and divided into 4 severity. Severity 1 and 2 are characterized by a decrease in platelet levels below normal and there is a change in hemoconcentration, while Severity 3 and 4 are included in Dengue Shock Syndrome (DSS). The purpose of the study was to classify the severity of dengue, based on age, gender, platelets, body temperature, bleeding, and also doctor's recommendation. The advancement of information technology is the reason for the development of medical science, especially with artificial intelligence. Abundant medical data becomes a source that can be processed in improving the quality of medical information. The method chosen is Random Forest, kNN, Decision Tree and Naïve Bayes. The dataset used is the medical records of all DHF patients for 30 months in the period Jan 2019 to June 2021, at the Nadhifa Al Ghiffari Clinic in Bojongsoang District, Bandung Regency. © 2022 IEEE.

关键词： Decision trees

On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection

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arXiv 2023年

作者： Park, Sangha Mok, Jisoo Jung, Dahuin Lee, Saehyung Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

Successful detection of Out-of-Distribution (OoD) data is becoming increasingly important to ensure safe deployment of neural networks. One of the main challenges in OoD detection is that neural networks output overconfident predictions on OoD data, make it difficult to determine OoD-ness of data solely based on their predictions. Outlier exposure addresses this issue by introducing an additional loss that encourages low-confidence predictions on OoD data during training. While outlier exposure has shown promising potential in improving OoD detection performance, all previous studies on outlier exposure have been limited to utilizing visual outliers. Drawing inspiration from the recent advancements in vision-language pre-training, this paper venture out to the uncharted territory of textual outlier exposure. First, we uncover the benefits of using textual outliers by replacing real or virtual outliers in the image-domain with textual equivalents. Then, we propose various ways of generating preferable textual outliers. Our extensive experiments demonstrate that generated textual outliers achieve competitive performance on large-scale OoD and hard OoD benchmarks. Furthermore, we conduct empirical analyses of textual outliers to provide primary criteria for designing advantageous textual outliers: near-distribution, descriptiveness, and inclusion of visual semantics. © 2023, CC BY-NC-SA.

关键词： Forecasting

MAMMOS: MApping Multiple human MOtion with Scene understanding and natural interactions

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MAMMOS: MApping Multiple human MOtion with Scene understandi...

International Conference on computer Vision Workshops (ICCV Workshops)

作者： Donggeun Lim Cheongi Jeong Young Min Kim Dept. of Electrical and Computer Engineering Seoul National University Samsung Research Interdisciplinary Program in Artificial Intelligence and INMC Seoul National University

We present MAMMOS, an automated framework that generates the motions of multiple humans that naturally interact with each other in a given 3D scene. Many practical VR scenarios require creating dynamic human characters in harmony with the surrounding environment and other people. However, it is hard for an artist to manually generate multiple character motions tailored to the given 3D scene structure, or gather sufficient data to train an automated system that jointly considers the entangled requirements. MAMMOS is a hierarchical framework that successfully handles spatio-temporal constraints and generates high-quality motions. Given a simple tuple of action labels of the desired motion sequence, MAMMOS first places anchors in time and location for characters that avoid collisions yet enable necessary interactions. Then we generate the timelines of individual collision-free paths within the scene and connect them to perform diverse and natural motions. To the best of our knowledge, we are the first to generate long-horizon motion sequences of multiple humans with realistic interactions such that we can automatically populate the 3D scenes.

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Expanding the Surgical Robotics Community: An Intuitive Sim-to-Real Control Framework for Raven-II with a Budget-Friendly Gamepad Controller

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Expanding the Surgical Robotics Community: An Intuitive Sim-...

International Symposium on Medical Robotics (ISMR)

作者： Mai Bui Natalie Chalfant Cuiling Sun Sean Fabrega Haonan Peng Kevin Huang Yun-Hsuan Su Department of Computer Science Mount Holyoke College South Hadley MA Department of Electrical and Computer Engineering University of Washington Seattle WA Picker Engineering Program Smith College Northampton MA

ISBN: (数字)9798350377118

ISBN: (纸本)9798350377125

This paper proposes a low-cost interface and refined digital twin for the Raven-II surgical robot. Previous simulations of the Raven-II, e.g. via the Asynchronous Multibody Framework (AMBF), presented salient drawbacks, including control inputs inconsistent with Raven-II software, and lack of stable, high-fidelity physical contact simulations. This work bridges both of these gaps, both (1) enabling robust, simulated contact mechanics for dynamic physical interactions with the Raven-II, and (2) developing a universal input format for both simulated and physical platforms. The method furthermore proposes a low cost, commodity game-controller interface for controlling both virtual and real realizations of Raven-II, thus greatly reducing the barrier to access for Raven-II research and collaboration. Overall, this work aims to eliminate the inconsistencies between simulated and real representations of the Raven-II. Such a development can expand the reach of surgical robotics research. Namely, providing end-to-end transparency between the simulated AMBF and physical Raven-II platforms enables a software testbed previously unavailable, e.g. for training real surgeons, for creating digital synthetic datasets, or for prototyping novel architectures like shared control strategies. Experiments validate this transparency by comparing joint trajectories between digital twin and physical testbed given identical inputs. This work may be extended and incorporated into recent efforts in developing modular or common software infrastructures for both simulation and control of real robotic devices, such as the Collaborative Robotics Toolkit (CRTK).

关键词： Training Medical robotics Costs Collaboration Surgery computer architecture Software

Neural Diffeomorphic Non-uniform B-spline Flows

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arXiv 2023年

作者： Hong, Seongmin Chun, Se Young Department of Electrical and Computer Engineering Seoul National University Korea Republic of INMC Interdisciplinary Program in AI Seoul National University Korea Republic of

Normalizing flows have been successfully modeling a complex probability distribution as an invertible transformation of a simple base distribution. However, there are often applications that require more than invertibility. For instance, the computation of energies and forces in physics requires the second derivatives of the transformation to be well-defined and continuous. Smooth normalizing flows employ infinitely differentiable transformation, but with the price of slow non-analytic inverse transforms. In this work, we propose diffeomorphic non-uniform B-spline flows that are at least twice continuously differentiable while bi-Lipschitz continuous, enabling efficient parametrization while retaining analytic inverse transforms based on a sufficient condition for diffeomorphism. Firstly, we investigate the sufficient condition for Ck−2-diffeomorphic non-uniform kth-order B-spline transformations. Then, we derive an analytic inverse transformation of the non-uniform cubic B-spline transformation for neural diffeomorphic non-uniform B-spline flows. Lastly, we performed experiments on solving the force matching problem in Boltzmann generators, demonstrating that our C2-diffeomorphic non-uniform B-spline flows yielded solutions better than previous spline flows and faster than smooth normalizing flows. Our source code is publicly available at https://***/smhongok/Non-uniform-B-spline-Flow. © 2023, CC BY-NC-ND.

关键词： Interpolation

An Approach to Evaluate Modeling Adequacy for Small-Signal Stability Analysis of IBR-related SSOs in Multimachine Systems

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arXiv 2024年

作者： Karunaratne, Lilan Chaudhuri, Nilanjan Ray Yogarathnam, Amirthagunaraj Yue, Meng The School of Electrical Engineering and Computer Science Penn State University University ParkPA United States The Interdisciplinary Science Department Brookhaven National Laboratory UptonNY United States

Time-varying phasor-based analysis of subsynchronous oscillations (SSOs) involving grid-following converters (GFLCs) and its benchmarking with electromagnetic transient (EMT) models have so far been restricted to highly simplified grid models with constant voltage sources behind series R-L circuits. In this paper, modeling adequacy of bulk power systems with synchronous generators (SGs), transmission systems, loads, and GFLCs are considered. To this end, we revisit the notions of time-varying phasor calculus, highlighting the distinction between space-phasor-calculus (SPC) and two often interchangeably used frameworks namely baseband-abc and generalized averaging. We present the models of grids in SPC framework that include transmission line dynamics, load dynamics, and SG stator transients. Next, we propose a generic approach to study modeling adequacy in small-signal sense by (a) identifying critical modes through eigenvalue and singular value analysis followed by (b) using weighted maximum singular value error magnitudes as metrics, and (c) further cross-validation. Using a modified 4-machine IEEE benchmark model with up to 3 GFLCs we show that SPC framework can be used for analysis of SSOs. Further, we consider the quasistationary phasor calculus (QPC) framework that neglects transmission line, load, and SG stator dynamics to show its adequacy in SSO modeling and analysis. Time-domain and frequency-domain results with EMT models are also presented. © 2024, CC BY.

关键词： Time domain analysis

Investigation of a Biased-Flux Halbach-Configured Permanent Magnet Motor

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Investigation of a Biased-Flux Halbach-Configured Permanent ...

electrical Machines and Drives (ICEMD), International Conference on

作者： Sara Beyrami Bigdeli Mohammad Judaki Ali Rahimi Meydani Department of Electrical and Computer Engineering University of Tehran Tehran Iran College of Interdisciplinary Science and Technology University of Tehran Tehran Iran Department of Information Engineering University of Padova Padova Italy

ISBN: (数字)9798331507510

ISBN: (纸本)9798331507527

A novel biased flux permanent machine is proposed in this paper. Regarding the rare earth permanent magnets’ cost and availability, it is necessary to decrease the consumed volume of these materials. The proposed motor specific design concludes to drastically increase the PM torque density rather than the conventional intermodular permanent magnet motor due to lower consumed PM volume. Both motors are investigated in terms of the back-EMF waveform, cogging torque profile, torque profile, and overload capability. Although the proposed motor has a lower PM volume, the novel design of the stator tooth causes to higher air gap flux density which leads to the same amplitude of back-EMF and average torque for both motors. The HBFPM stator module design led to increasing the 1,6, and 12 cogging torque harmonic components. These increased harmonic components increase the torque ripple. Also, the segmented modular stator shape causes to increase in the flux leakage and concludes to decrease the power factor by 3%.

关键词： Reactive power Forging Torque Shape Air gaps Motors Permanent magnet motors Harmonic analysis Topology Torque measurement