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Analytical Validation of a Webcam-Based Assessment of Speech Kinematics: Digital Biomarker Evaluation following the V3 Framework

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Digital Biomarkers 2023年第1期7卷 7-17页

作者： Simmatis, Leif Alavi Naeini, Saeid Jafari, Deniz Xie, Michael Kai Yue Tanchip, Chelsea Taati, Niyousha McKinlay, Scotia Sran, Rupinder Truong, Justin Guarin, Diego L Taati, Babak Yunusova, Yana University Health Network Toronto Rehabilitation Institute TorontoON Canada Department of Speech-Language Pathology Rehabilitation Sciences Institute Temerty Faculty of Medicine University of Toronto TorontoON Canada Hurvitz Brain Sciences Program Sunnybrook Research Institute TorontoON Canada Department of Computer Science University of Toronto TorontoON Canada Clinical Integrative Biology Sunnybrook Research Institute TorontoON Canada Department of Applied Physiology and Kinesiology University of Florida GainesvilleFL United States

Introduction: Kinematic analyses have recently revealed a strong potential to contribute to the assessment of neurological diseases. However, the validation of home-based kinematic assessments using consumer-grade video technology has yet to be performed. In line with best practices for digital biomarker development, we sought to validate webcam-based kinematic assessment against established, laboratory-based recording gold standards. We hypothesized that webcam-based kinematics would possess psychometric properties comparable to those obtained using the laboratory-based gold standards. Methods: We collected data from 21 healthy participants who repeated the phrase "buy Bobby a puppy"(BBP) at four different combinations of speaking rate and volume: Slow, Normal, Loud, and Fast. We recorded these samples twice back-to-back, simultaneously using (1) an electromagnetic articulography ("EMA";NDI Wave) system, (2) a 3D camera (Intel RealSense), and (3) a 2D webcam for video recording via an in-house developed app. We focused on the extraction of kinematic features in this study, given their demonstrated value in detecting neurological impairments. We specifically extracted measures of speed/acceleration, range of motion (ROM), variability, and symmetry using the movements of the center of the lower lip during these tasks. Using these kinematic features, we derived measures of (1) agreement between recording methods, (2) test-retest reliability of each method, and (3) the validity of webcam recordings to capture expected changes in kinematics as a result of different speech conditions. Results: Kinematics measured using the webcam demonstrated good agreement with both the RealSense and EMA (ICC-A values often ≥0.70). Test-retest reliability, measured using the absolute agreement (2,1) formulation of the intraclass correlation coefficient (i.e., ICC-A), was often "moderate"to "strong"(i.e., ≥0.70) and similar between the webcam and EMA-based kinematic features. Finally, th

关键词： Kinematics

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Statistical Data Mining with Slime Mould Optimization for Intelligent Rainfall Classification

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computer Systems science & Engineering 2023年第10期47卷 919-935页

作者： Ramya Nemani G.Jose Moses Fayadh Alenezi K.Vijaya Kumar Seifedine Kadry Jungeun Kim Keejun Han Department of Mathematics Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science and Engineering University Institute of Engineering and Technology(UIET)Guru Nanak UniversityHyderabadIndia Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia Department of Computer Science and Engineering GITAM School of TechnologyVishakhapatnam CampusGITAM(Deemed to be a University)VishakhapatnamIndia Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea Division of Computer Engineering Hansung UniversitySeoul02876Korea

Statistics are most crucial than ever due to the accessibility of huge counts of data from several domains such as finance,medicine,science,engineering,and so *** data mining(SDM)is an interdisciplinary domain that examines huge existing databases to discover patterns and connections from the *** varies in classical statistics on the size of datasets and on the detail that the data could not primarily be gathered based on some experimental strategy but conversely for other ***,this paper introduces an effective statistical Data Mining for Intelligent Rainfall Prediction using Slime Mould Optimization with Deep Learning(SDMIRPSMODL)*** the presented SDMIRP-SMODL model,the feature subset selection process is performed by the SMO algorithm,which in turn minimizes the computation *** rainfall *** neural network with long short-term memory(CNN-LSTM)technique is *** last,this study involves the pelican optimization algorithm(POA)as a hyperparameter *** experimental evaluation of the SDMIRP-SMODL approach is tested utilizing a rainfall dataset comprising 23682 samples in the negative class and 1865 samples in the positive *** comparative outcomes reported the supremacy of the SDMIRP-SMODL model compared to existing techniques.

关键词： Statistical data mining predictive models deep learning rainfall prediction parameter tuning

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Noncrossing Longest Paths and Cycles

arXiv

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arXiv 2024年

作者： Aloupis, Greg Biniaz, Ahmad Bose, Prosenjit De Carufel, Jean-Lou Eppstein, David Maheshwari, Anil Odak, Saeed Smid, Michiel Tóth, Csaba D. Valtr, Pavel Khoury College of Computer Sciences Northeastern University BostonMA United States School of Computer Science University of Windsor WindsorON Canada School of Computer Science Carleton University OttawaON Canada School of Electrical Engineering and Computer Science University of Ottawa OttawaON Canada Computer Science Department University of California IrvineCA United States Department of Mathematics California State University Northridge Los AngelesCA United States Department of Computer Science Tufts University MedfordMA United States Department of Applied Mathematics Charles University Czech Republic

Edge crossings in geometric graphs are sometimes undesirable as they could lead to unwanted situations such as collisions in motion planning and inconsistency in VLSI layout. Short geometric structures such as shortest perfect matchings, shortest spanning trees, shortest spanning paths, and shortest spanning cycles on a given point set are inherently noncrossing. However, the longest such structures need not be noncrossing. In fact, it is intuitive to expect many edge crossings in various geometric graphs that are longest. Recently, Álvarez-Rebollar, Cravioto-Lagos, Marín, Solé-Pi, and Urrutia (Graphs and Combinatorics, 2024) constructed a set of points for which the longest perfect matching is noncrossing. They raised several challenging questions in this direction. In particular, they asked whether the longest spanning path, on any finite set of points in the plane, must have a pair of crossing edges. They also conjectured that the longest spanning cycle must have a pair of crossing edges. In this paper, we give a negative answer to the question and also refute the conjecture. We present a framework for constructing arbitrarily large point sets for which the longest perfect matchings, the longest spanning paths, and the longest spanning cycles are noncrossing. © 2024, CC BY.

关键词： Trees (mathematics)

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WEIERSTRASS SEMIGROUPS AND AUTOMORPHISM GROUP OF A MAXIMAL FUNCTION FIELD WITH THE THIRD LARGEST POSSIBLE GENUS, q ≡ 1 (mod 3)

arXiv

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arXiv 2024年

作者： Beelen, Peter Montanucci, Maria Vicino, Lara Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby2800 Denmark Faculty of Science and Engineering Bernoulli Institute University of Groningen Groningen9747AG Netherlands

In this article we continue the work started in [3], explicitly determining the Weierstrass semigroup at any place and the full automorphism group of a known Fq2-maximal function field Y3 having the third largest genus, for q ≡ 1 (mod 3). This function field arises as a Galois subfield of the Hermitian function field, and its uniqueness (with respect to the value of its genus) is a well-known open problem. Knowing the Weierstrass semigroups may provide a key towards solving this problem. Surprisingly enough, Y3 has many different types of Weierstrass semigroups and the set of its Weierstrass places is much richer than its set of Fq2-rational places. We show that a similar exceptional behaviour does not occur in terms of automorphisms, that is, Aut(Y3) is exactly the automorphism group inherited from the Hermitian function field, apart from small values of *** Codes 14H37, 14H05 Copyright © 2024, The Authors. All rights reserved.

关键词： Algebra

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AN IMPROVED VARIATIONAL METHOD FOR IMAGE DENOISING

arXiv

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arXiv 2024年

作者： Huang, Jing-En Lin, Ku-Te Liao, Jia-Wei Tsai, Yu-Ju Yueh, Mei-Heng Department of Mathematics National Taiwan Normal University Taipei Taiwan Department of Mathematics National Central University Taoyuan Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Applied Mathematics National Yang Ming Chiao Tung University Hsinchu Taiwan

The total variation (TV) method is an image denoising technique that aims to reduce noise by minimizing the total variation of the image, which measures the variation in pixel intensities. The TV method has been widely applied in image processing and computer vision for its ability to preserve edges and enhance image quality. In this paper, we propose an improved TV model for image denoising and the associated numerical algorithm to carry out the procedure, which is particularly effective in removing several types of noises and their combinations. Our improved model admits a unique solution and the associated numerical algorithm guarantees the convergence. Numerical experiments are demonstrated to show improved effectiveness and denoising quality compared to other TV models. Such encouraging results further enhance the utility of the TV method in image processing. Copyright © 2024, The Authors. All rights reserved.

关键词： Image denoising

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Dynamics of self-hybridized exciton–polaritons in 2D halide perovskites

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Light(science & Applications) 2024年第1期13卷 13-22页

作者： Surendra B.Anantharaman Jason Lynch Christopher E.Stevens Christopher Munley Chentao Li Jin Hou Hao Zhang Andrew Torma Thomas Darlington Francis Coen Kevin Li Arka Majumdar PJames Schuck Aditya Mohite Hayk Harutyunyan Joshua R.Hendrickson Deep Jariwala Department of Electrical and Systems Engineering University of PennsylvaniaPhiladelphiaPA19104USA KBR Inc. BeavercreekOH45431USA Air Force Research Laboratory Sensors DirectorateWright-Patterson Air Force BaseOH45433USA Department of Physics University of WashingtonSeattleWA98195USA Department of Physics Emory UniversityAtlantaGA30322USA Department of Chemical and Biomolecular Engineering Rice UniversityHoustonTX77005USA Department of Materials Science and Nanoengineering Rice UniversityHoustonTX77005USA Applied Physics Program Smalley‐Curl InstituteRice UniversityHoustonTX77005USA Department of Mechanical Engineering Columbia UniversityNew YorkNY10027USA Department of Electrical and Computer Engineering University of WashingtonSeattleWA98195USA

Excitons,bound electron–hole pairs,in two-dimensional hybrid organic inorganic perovskites(2D HOIPs)are capable of forming hybrid light-matter states known as exciton-polaritons(E–Ps)when the excitonic medium is confined in an optical *** the case of 2D HOIPs,they can self-hybridize into E–Ps at specific thicknesses of the HOIP crystals that form a resonant optical cavity with the ***,the fundamental properties of these self-hybridized E–Ps in 2D HOIPs,including their role in ultrafast energy and/or charge transfer at interfaces,remain ***,we demonstrate that>0.5µm thick 2D HOIP crystals on Au substrates are capable of supporting multiple-orders of self-hybridized E–P *** E–Ps have high Q factors(>100)and modulate the optical dispersion for the crystal to enhance sub-gap absorption and *** varying excitation energy and ultrafast measurements,we also confirm energy transfer from higher energy E–Ps to lower energy E–***,we also demonstrate that E–Ps are capable of charge transport and transfer at *** findings provide new insights into charge and energy transfer in E–Ps opening new opportunities towards their manipulation for polaritonic devices.

关键词： charge polar excitation

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QUANTUM SABIDUSSI’S THEOREM

arXiv

引用

arXiv 2024年

作者： Árnadóttir, Arnbjörg Soffía van Dobben De Bruyn, Josse Kar, Prem Nigam Roberson, David E. Zeman, Peter Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby2800 Denmark QMATH Department of Mathematical Sciences University of Copenhagen Universitetsparken 5 Copenhagen Ø2100 Denmark

Sabidussi’s theorem [Duke Math. J. 28, 1961] gives necessary and sufficient conditions under which the automorphism group of a lexicographic product of two graphs is a wreath product of the respective automorphism groups. We prove a quantum version of Sabidussi’s theorem for finite graphs, with the automorphism groups replaced by quantum automorphism groups and the wreath product replaced by the free wreath product of quantum groups. This extends the result of Chassaniol [J. Algebra 456, 2016], who proved it for regular graphs. Moreover, we apply our result to lexicographic products of quantum vertex transitive graphs, determining their quantum automorphism groups even when Sabidussi’s conditions do not *** Codes 46L67 (Primary), 05C25, 05C76, 46L85 (Secondary) Copyright © 2024, The Authors. All rights reserved.

关键词： Graphic methods

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LowResIR-Net: Lightweight Residual Network for ADL Recognition Using Low-Resolution Infrared Sensor Data

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Procedia computer science 2025年 256卷 1358-1366页

作者： Sakorn Mekruksavanich Wikanda Phaphan Anuchit Jitpattanakul Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao 56000 Thailand Research Group in Statistical Learning and Inference Department of Applied Statistics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok 10800 Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok 10800 Thailand

Detecting activities of daily living (ADL) is crucial for supported living and medical monitoring. Traditional approaches rely on high-resolution sensors and computationally intensive algorithms, limiting their scalability and practical use in real-world settings. This research introduces LowResIR-Net, a compact deep residual network architecture specifically tailored for recognizing ADL utilizing low-resolution infrared sensor data. LowResIR-Net efficiently extracts key features from low-dimensional data by leveraging the advantages of infrared sensing, such as privacy protection and light resilience. Its architecture combines residual connections with depth-wise convolutions, enhancing feature learning while maintaining a compact model size. The model’s performance is evaluated using the Coventry-2018 dataset, containing low-resolution infrared data from three residential sensor locations. Our tests have shown that in all three cases, LowResIR-Net consistently achieves superior performance compared to other cutting-edge deep learning models, such as CNN, LSTM, BiLSTM, GRU, and BiGRU. LowResIR-Net attains the most excellent accuracies of 90.18%, 93.75%, and 93.30%, and F1-scores of 81.81%, 89.55%, and 88.92% for scenarios I, II, and III, respectively. Furthermore, it achieves these results with fewer parameters than most other models. LowResIR-Net’s strong performance highlights its ability to accurately capture complex patterns in low-resolution infrared data for ADL detection. This study demonstrates the potential of lightweight deep learning and low-resolution infrared sensors in developing privacy-focused and computationally efficient wellness monitoring systems.

关键词： Activities of daily living low-resolution infrared sensors deep residual networks lightweight architecture healthcare monitoring

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On Isbell's Density Theorem for bitopological pointfree spaces II

arXiv

引用

arXiv 2024年

作者： Moshier, M. Andrew Carollo, Imanol Mozo Walters-Wayland, Joanne CECAT Department of Mathematics & Computer Science Chapman University OrangeCA92866 United States Department of Applied Economics University of the Basque Country UPV/EHU Donostia20018 Spain

With the aim of studying subspaces in pointfree bitopology, we characterize extremal epimorphism in biframes and show that a smallest dense one always exists, providing an analogue of Isbell’s Density Theorem. Further we study the functoriality of assigning to each biframe its lattice of subbilocales and its smallest dense *** Codes 06D22, 54B05, 54E55 Copyright © 2024, The Authors. All rights reserved.

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Helmet Detection System for Motorcycle Riders with Explainable Artificial Intelligence Using Convolutional Neural Network and Grad-CAM 1

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15th Multi-disciplinary International Conference on Artificial Intelligence, MIWAI 2022

作者： Intagorn, Suradej Pinitkan, Suriya Panmuang, Mathuros Rodmorn, Chonnikarn Department of Mathematics Statistics and Computer Science Faculty of Liberal Arts and Science Kasetsart University Kamphaeng Saen Campus Nakhon Pathom Thailand Department of Educational Technology and Communications Faculty of Technical Education Rajamangala University of Technology Thanyaburi Pathum Thani Thailand Department of Applied Statistics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9783031209925

ISBN: (纸本)9783031209918

Motorcycle accidents are one of the most common causes of injury and death in road users. This research has applied convolutional neural network (CNN) and explainable AI to detect motorcyclist without helmet and explain why CNN made that decision. The concept is based on deep learning and CNN principles applied to automatically detect motorcycle riders without helmet from images using three baseline classifiers: support vector machine, random forest and logistic regression to compare with deep convolutional neural network and measure accuracy with accuracy and F1-Score. The results revealed that CNN's F1-Score was 0.8326, which was the highest among all predictive models. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Support vector machines

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