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Non-invasive glucose sensing via the fingernail bed using THz radiation

Current Directions in Biomedical Engineering 2023年第1期9卷 507-510页

作者： Jalali, Mandana Prokscha, Andreas Kaiser, Thomas Yan, Yijun Taro Svejda, Jan Erni, Daniel Kubiczek, Tobias Balzer, Jan Preu, Sascha General and Theoretical Electrical Engineering (ATE) Faculty of Engineering University of Duisburg-Essen Essen Duisburg Germany CENIDE-Center for Nanointegration Duisburg-Essen Duisburg D-47048 Germany Institute of Digital Signal Processing Faculty of Engineering University of Duisburg-Essen Duisburg D-47048 Germany Chair of Communication Systems Faculty of Engineering University of Duisburg-Essen Duisburg D-47048 Germany Terahertz Devices and Systems Institute of Microwave Engineering and Photonics Department of Electrical Engineering and Information Technology Technical University of Darmstadt Darmstadt D-64283 Germany

The possibility of establishing a novel technique for reliably accessing glycemic information in a non-invasive, easy to implement method at THz frequencies via the fingernail bed is investigated. The nail bed's major content is blood at its various glucose levels and is also partially protected from environmental conditions by the nail plate, making it a desirable platform for non-invasive glucose sensing. The study is based on a 2D computational electromagnetics (EM) model of the layered fingernail in COMSOL Multiphysics, where the required dielectric function (i.e. permittivity and conductivity) of the fingernail plate is measured using THz-Time-Domain-Spectroscopy (THz-TDS), and the glucose-dependend dielectric functions of the fingernail bed are taken from available experimental data in the literature. From this data a material model using a multipole Cole-Cole model is established for both, the nail plate and the nail bed, where the glucose content in the latter is varied from 3.0-19.0 mmol/l. A numerical analysis of the THz reflectometry at the fingernail in the frequency range of 0.1-2.0 THz revealed that the reflectance spectra are sensitive to the glucose content in the nail bed proving that accurate glucose sensing via the fingernail bed may become feasible around 0.2-0.4 THz. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Glucose

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Analysis of Surface Roughness with 3D SAR Imaging at 1.5 THz

Analysis of Surface Roughness with 3D SAR Imaging at 1.5 THz

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International Conference on Infrared and Millimeter Waves

作者： A. Batra Y. Ivanenko V. T. Vu M. Wiemeler M. I. Pettersson D. Goehringer T. Kaiser Institute of Digital Signal Processing University of Duisburg-Essen Duisburg Germany Department of Mathematics and Natural Sciences Blekinge Institute of Technology Karlskrona Sweden Chair of Adaptive Dynamic Systems Technische Universitaet Dresden Dresden Germany

The expansion of the synthetic aperture radar (SAR) to the emerging THz spectrum has enabled a new era of applications in the areas of automobile, security, non-destructive testing, and material characterization. Thanks to the sub-mm wavelength, extraction of material surface properties is possible and of significant interest for the THz SAR applications. The properties define the surface scattering behavior, which is relational to the applied frequency. This study focuses on surface classification. We evaluate the scattering behavior of a rough surface and a smooth surface at 1.5 THz based on a SAR processing sequence that is introduced in this paper. First, we form the 3D SAR images of the metallic objects and then evaluate the surface properties based on the variation in the energy reflected by the object’s surface.

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On the Predictive Power of Objective Intelligibility Metrics for the Subjective Performance of Deep Complex Convolutional Recurrent Speech Enhancement Networks

TechRxiv

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TechRxiv 2022年

作者： Gelderblom, Femke B. Tronstad, Tron V. Svendsen, Torbjørn Myrvoll, Tor Andre Acoustics group of the Department of Sustainable Communication Technologies SINTEF Digital Trondheim Norway Signal Processing group at the Department of Electronic Systems Norwegian University of Science and Technology Trondheim Norway

Speech enhancement (SE) systems aim to improve the quality and intelligibility of degraded speech signals obtained from far-field microphones. Subjective evaluation of the intelligibility performance of these SE systems is uncommon. Instead, objective intelligibility measures (OIMs) are generally used to predict subjective performance increases. Many recent deep learning based SE systems, are expected to improve the intelligibility of degraded speech as measured by OIMs. However, validation of the OIMs for this purpose is lacking. Therefore, in this study, we evaluate the predictive performance of five popular OIMs. We compare the metrics’ predictions with subjective results. For this purpose, we recruited 50 human listeners, and subjectively tested both single channel and multi-channel Deep Complex Convolutional Recurrent Network (DCCRN) based speech systems. We find that none of the OIMs gave reliable predictions, and that all OIMs overestimated the intelligibility of ‘enhanced’ speech signals. © 2022, CC BY-NC-SA.

关键词： Deep neural networks

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Exploiting sparseness in damage characterization: A close look at the regularization techniques

arXiv

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arXiv 2022年

作者： Memarzadeh, Esmaeil Bernal, Dionisio Ulriksen, Martin D. Civil and Environmental Engineering Center for Digital Signal Processing Northeastern University BostonMA United States Department of Energy Technology Aalborg University Esbjerg 6700 Denmark

The idea of exploiting sparseness in under-determined damage characterization problems is not new, and regularizations techniques that tend to promote sparseness, such as L1-norm minimization, have been investigated in the last ten years or so. Although various claims of merit have been made, two interconnected issues put these claims into question, and this paper brings some attention to the matter. The first is that the relationship between the structural parameters and the modal features previously considered has been linear and to ensure that the premise was closely realized, only very small damage severities have been considered. The second issue, intimately related to the first, is the fact that the noise, which has been typically taken as small relative to the "change in the features", is then unrealistically small. In problems where the damage is sufficiently large, the nonlinear dependence of the features on the parameters cannot be generally discarded. It is found that the attainable performance is much less "impressive" that what has been often claimed. The paper also examines the potential merit of using Lp-norm (0 © 2022, CC BY-NC-ND.

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CHALLENGES IN IMPLEMENTING A RECOMMENDER SYSTEM FOR HISTORICAL RESEARCH IN THE HUMANITIES

arXiv

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arXiv 2024年

作者： Atzenhofer-Baumgartner, Florian Geiger, Bernhard C. Trattner, Christoph Vogeler, Georg Kowald, Dominik Institute of Interactive Systems and Data Science Graz University of Technology Graz Austria Department of Digital Humanities University of Graz Graz Austria Know Center Research GmbH Graz Austria Signal Processing and Speech Communication Laboratory Graz University of Technology Graz Austria University of Bergen & Media Futures Bergen Norway

This extended abstract describes the challenges in implementing recommender systems for digital archives in the humanities, focusing on ***, a platform for historical legal documents. We discuss three key aspects: (i) the unique characteristics of so-called charters as items for recommendation, (ii) the complex multi-stakeholder environment, and (iii) the distinct information-seeking behavior of scholars in the humanities. By examining these factors, we aim to contribute to the development of more effective and tailored recommender systems for (digital) humanities research. © 2024, CC BY-SA.

关键词： Recommender systems

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CNN based Emotion Detection in Cross Linguistic Children speech 24

CNN based Emotion Detection in Cross Linguistic Children spe...

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24th International Congress on Acoustics, ICA 2022

作者： Lyakso, Elena Frolova, Olga Ruban, Nersisson Mekala, A. Mary Joseph Raj, Alex Noel Matveev, Anton Matveev, Yuri The Child Speech Research Group St. Petersburg State University St. Petersburg Russia School of Electrical Engineering VIT Vellore India School of Information Technology & Engineering VIT Vellore India Key Laboratory of Digital Signal and Image Processing of Guangdong Province Department of Electronics Engineering College of Engineering Shantou University China

The goal of this cross-linguistic study is to analyze the speech of children in the age group of 8-12 years and automatic classification of children's emotions from various speech data in Russian and Tamil languages. A standardized approach for the collection of speech (spontaneous and acting speech - emotional words, phrases, and meaningless texts) was used. Two emotional child speech corpora include the emotional speech of 95 Russian children and 40 Indian children were created. Annotation of the emotional speech was carried out in four categories "joy - neutral - sadness – anger" by two speech specialists of the same nationality of the child. The set of 2505 labeled audio files of Russian children and 418 labeled audio files of Tamil children were used. The SVM classifier shows slightly better results in Russian language, and the MLP classifier in Tamil. Inter-Cultural approach (mixed dataset of Russian and Indian speech) revealed that the accuracy of recognition of all emotions remains higher. In Cross-Cultural approach, on samples of Tamil speech, anger state is recognized better, and in samples of Russian speech – sad state. Using 5 Layered CNN Model, the accuracy was revealed for Russian speech is higher than for Indian children. © 2022 Proceedings of the International Congress on Acoustics. All rights reserved.

关键词： Emotion Recognition

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Effects Analysis of Phase Sequence Arrangement on Electromagnetic Environment in 1000 kV Same-Tower Double-circuit Ultra-high Voltage AC Transmission Lines

Effects Analysis of Phase Sequence Arrangement on Electromag...

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Power Science and technology (ICPST), IEEE International Conference on

作者： Lili Jing Xiaoxia Guo Yang Nie Sen Su Institute for Digital Energy Technology Jining Normal Universit Inner Mongolia China Department of Physics and Electronic Information Jining Normal University Inner Mongolia China Key Laboratory of High Speed Signal Processing and Internet of Things Technology Application Jining Normal University Inner Mongolia China Huachi Kinetic Energy (Beijing) Technology Co LTD Beijing China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

Using the "Ximeng to Shandong 1000 kV Ultra-High Voltage AC Transmission Line Project" as a case study, this study focuses on comparing various indicators under both forward and reverse phase sequence arrangements to determine the most suitable phase sequence arrangement meeting electromagnetic environment requirements. Through measurements and comparisons of electromagnetic environment parameters and various indicators such as surface electric field strength of conductors, maximum surface field strength of conductors, corona inception field strength of conductors, corona inception voltage, and width of areas with field strength exceeding 4 kV/m (between the outer sides of the lines at 4 kV/m), it is concluded that the reverse phase sequence arrangement is appropriate for double-circuit lines on the same tower. This is because the reverse phase sequence arrangement for such lines can concurrently reduce tower height and transmission corridor width. It represents the optimal arrangement for conductor phase sequence and aims to offer guidance for engineering decision-makers.

关键词： Voltage measurement Power transmission lines Phase measurement Poles and towers Area measurement Conductors Transmission line measurements

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A Low-Latency and High-Performance SCL Decoder with Frame-Interleaving

A Low-Latency and High-Performance SCL Decoder with Frame-In...

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IEEE International Symposium on circuits and Systems (ISCAS)

作者： Leyu Zhang Yuqing Ren Yifei Shen Wuyang Zhou Alexios Balatsoukas-Stimming Chuan Zhang Andreas Burg CAS Key Laboratory of Wireless-Optical Communications University of Science and Technology of China (USTC) China Telecommunication Circuits Laboratory École Polytechnique Fédérale de Lausanne (EPFL) Switzerland Department of Electrical Engineering Eindhoven University of Technology Netherlands Lab of Efficient Architectures for Digital-Communication and Signal-Processing (LEADS) Southeast University China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

In this paper, we describe a frame-interleaving hardware architecture for a generalized node-based successive cancellation list (SCL) decoder. By efficiently reusing otherwise idle computational units, two independent frames can be decoded simultaneously, resulting in a significant throughput gain. Based on this new architecture, we also exploit graph ensembles to diversify the decoding, enhancing the error-correcting performance by 0.28 dB and reducing the worst-case latency for serial graph processing by over 32%. Implementation results show that the proposed SCL decoder with frame-interleaving architecture achieves a throughput of 7.15 Gbps and an area efficiency of 37.63 Gbps/mm 2 , which is 1.56× and 1.11× better than the state-of-the-art node-based SCL decoders.

关键词： Codes circuits and systems Computer architecture Throughput Hardware Decoding Computational efficiency

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Guest Editorial circuits, systems, and algorithms for beyond 5G and Toward 6G

IEEE Open Journal of Circuits and Systems

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IEEE Open Journal of circuits and Systems 2021年 2卷 223-225页

作者： Zhang, Chuan Liu, Liang Studer, Christoph Laboratory of Efficient Architectures for Digital-Communication and Signal-Processing Southeast University Nanjing211189 China National Mobile Communications Research Laboratory Southeast University Nanjing211189 China Purple Mountain Laboratories Nanjing211189 China Department of Electrical and Information Technology Lund University Lund221 00 Sweden Department of Information Technology and Electrical Engineering ETH Zürich Zürich8029 Switzerland

This special section of the IEEE OPEN JOURNAL OF circuitS AND SYSTEMS (OJCAS) is dedicated to highlight the state-of-the-art research progress on circuits, systems, and algorithms associated with the design of beyond ... 详细信息

关键词： Special issues and sections 5G mobile commuincation 6G mobile communication Algorithm design and analysis Wireless communication

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Optimal Training Positive Sample Size Determination for Deep Learning Caries Recognition Model Establishment with Cbct Images

SSRN

引用

SSRN 2024年

作者： Wang, Yanlin Li, Gang Zhang, Xinyue Wang, Yue Zhang, Zhenhao Li, Jupeng Ma, Junqi Wang, Lingxing Department of Oral and Maxillofacial Radiology Peking University School Hospital of Stomatology National Center for Stomatology National Clinical Research Center for Oral Diseases National Engineering Research Center of Oral Biomaterials and Digital Medical Device Beijing Key Laboratory of Digital Stomatology NHC Key Laboratory of Digital Stomatology Beijing China Signal and image processing laboratory School of Electronic Information Engineering Beijing Jiao tong University Beijing China Algorithm Department YOFO Medical Technology Co. Ltd Anhui China

Background and objective When performing model training, it is necessary to consider the balance between the impact of sample size, actual resource and time constraints. To do so, the single-arm objective performance criteria for deep learning optimal training positive sample size determination was proposed for caries recognition and identified with three network models. Methods The expected sensitivity of 0.6 and specificity of 0.85 were applied to the single-arm objective performance criteria calculation formula, resulting in an optimal training set with 263 positive samples. According to a ratio of 8:1:1 for the distribution of training set, validation set and test set, the U-Net, YOLOv5n and CariesDetectNet were trained and validated on the clinically self-collected cone-beam computed tomography (CBCT) images. To evaluate performance, an additional set of test sets was used to test the three models. The accuracy of the three best-performed models for caries detection was evaluated through comparisons with the detection accuracy of caries by two dental radiologists. Results When the number of carious teeth reached about 250, the models reached the optimal level of performance. Among the three models, the U-Net performed best, with accuracy, sensitivity, specificity, F1-Score, Dice similarity coefficients, and intersection over union of 0.9929, 0.9307, 0.9989, 0.9590, 0.9435 and 0.9008, respectively. And the three models performed higher accuracy than dental radiologists for caries recognition. Conclusions This study indicated that the optimal number of images with caries in the training set was predictable and it could be calculated through the single-arm objective performance criteria. © 2024, The Authors. All rights reserved.

关键词： Deep learning

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