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3rd International Conference on Image processing and Vision Engineering, IMPROVE 2023

作者： Lehmann, Lars Seidel, Roman Hirtz, Gangolf Digital Signal Processing and Circuit Technology Chemnitz University Reichenhainer Str. 70 Chemnitz Germany

ISBN: (纸本)9789897586422

In a medical therapy, the exact execution of the training exercises developed by the therapist is a crucial task for the success of the therapy. Currently, a therapist has to treat up to 15 patients at the same time on an outpatient basis. To compensate this deficit, an automated assistance system needs to be created. Previous approaches have focused on a parameterised segment angle-based assessment for training exercise feedback. This work focuses on a reference-based approach. This reference is created by the therapist and thus corresponds to the ideal movement model and can be individually adapted to the patient. It is necessary to compare this reference with the patients’ real movement in real time, to detect deviations and to output them as errors. For this purpose, the reference can be adapted to the body size of the patient and the patients’ current position and orientation can be taken into account, or it can be described by reference segments, i.e. an angle-based comparison of the reference. Our work highlights the the segment and reference-based assessment approach and compares them to each other. © 2023 by SCITEPRESS – Science and technology Publications, Lda.

关键词： Feedback control

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Effect of Pectoral Muscles on CNN based Mammographic Cancer Detection 18

Effect of Pectoral Muscles on CNN based Mammographic Cancer ...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Dhimann, Santoresh Kumari Sawhney, Tinny Yadav, Rakesh Kumar Maharishi University of Information Technology Department of Computer Science and Engineering Lucknow India University of Jammu Digital Signal Processing Lab Department of Electronics Jammu India

ISBN: (纸本)9789380544519

Cancer is attributed to abnormal growth of tissue cells in any part of the living body. The number of cancer patients is increasing worldwide. The reason of the development of abnormal cells within the body is still unknown to the researchers. The most common is breast cancer and it is affective affecting one out of every ten women. The reason of breast lesions formation may be calcification or mass deposit and digital mammography is generally used for verifying it. It is a cheap, non-toxic, and user-friendly test, but needs expert opinion for ascertaining the presence of cancer. The accuracy of mammographic detection varies between 80% and 90%. Recently, Convolutional neural networks (CNNs) have shown their application in automatic detection of the cancer, but inclusion of pectoral muscle in the mammogram reduces the efficiency of the CNN system as the texture of the muscle resembles with cancerous tissues. Further, CNN based detection requires high resolution images which in turn requires state of art technology-based machines, generally, not available in rural area-based clinics. The focus of the proposed research is to investigate effect of low-quality blurred input mammograms on the detection of pectoral muscle boundary, so that the pectoral muscle removed mammograms can be applied to CNN system for automatic prediction of cancerous images. The investigations carried out have shown that low quality blurred images can also be employed for detecting cancerous tissues provided the pectoral muscle is removed from the mammograms before using CNN based classifier. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： cancer detection CNN Hough lines mammogram pectoral muscle

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2D MXene Ti_(3)C_(2)T_(x)Enhanced Plasmonic Absorption in Metasurface for Terahertz Shielding

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Computers, Materials & Continua 2023年第5期75卷 3453-3464页

作者： Zaka Ullah Muath Al Hasanl Ismail Ben Mabrouk Muhammad Junaid Fawad Sheikh Faculty of Electrical Engineering College of EngineeringAl Ain UniversityAl Ain64141UAE Department of Electrical Engineering Durham UniversityDurhamUK Department of Electrical Engineering Baluchistan University of Technology and management sciencesQuettaPakistan Institute of Digital Signal Processing Universitat Duisburg EssenDuisburgGermany

With the advancement of technology,shielding for terahertz(THz)electronic and communication equipment is increasingly *** metamaterial absorption technique is mostly used to shield electromagnetic interference(EMI)in THz sensing *** most widely used THz metamaterial absorbers suffer from their narrowband properties and the involvement of complex fabrication *** with multifunctional properties,such as adjustable conductivity,broad bandwidth,high flexibility,and robustness,are driving future development to meet THz shielding *** this article,a theoretical simulation approach based on finite difference time domain(FDTD)is utilized to study the absorption and shielding characteristics of a two-dimensional(2D)MXene Ti_(3)C_(2)T_(x) metasurface absorber in the THz *** proposed metamaterial structure is made up of a square-shaped array of MXene that is 50 nmthick and is placed on top of a silicon *** bottom surface of the silicon is metalized with gold to reduce the transmission and ultimately enhance the absorption at 1–3 *** symmetric adjacent space between theMXene array results in a widening of *** proposed metasurface achieves 96%absorption under normal illumination of the incident source and acquires an average of 25 dB shielding at 1 THz bandwidth,with the peak shielding reaching 65 *** results show that 2D MXene-based stacked metasurfaces can be proven in the realization of low-cost devices for THz shielding and sensing applications.

关键词： EMI shielding terahertz plasmonic absorber metasurface

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Value Identification in Multistakeholder Recommender Systems for Humanities and Historical Research: The Case of the digital Archive *** 2

Value Identification in Multistakeholder Recommender Systems...

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2nd Workshop on the Normative Design and Evaluation of Recommender Systems, NORMalize 2024

作者： Atzenhofer-Baumgartner, Florian Geiger, Bernhard C. 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

Recommender systems remain underutilized in humanities and historical research, despite their potential to enhance the discovery of cultural records. This paper offers an initial value identification of the multiple stakeholders that might be impacted by recommendations in ***, a digital archive for historical legal documents. Specifically, we discuss the diverse values and objectives of its stakeholders, such as editors, aggregators, platform owners, researchers, publishers, and funding agencies. These in-depth insights into the potentially conflicting values of stakeholder groups allow designing and adapting recommender systems to enhance their usefulness for humanities and historical research. Additionally, our findings will support deeper engagement with additional stakeholders to refine value models and evaluation metrics for recommender systems in the given domains. Our conclusions are embedded in and applicable to other digital archives and a broader cultural heritage context. © 2024 Copyright for this paper by its authors.

关键词： Embedded systems

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Effect of Pectoral Muscles on CNN based Mammographic Cancer Detection

Effect of Pectoral Muscles on CNN based Mammographic Cancer ...

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Santoresh Kumari Dhimann Tinny Sawhney Rakesh Kumar Yadav Department of Computer Science & Engineering Maharishi University of Information Technology Lucknow India Department of Electronics Digital Signal Processing Lab University of Jammu Jammu India

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Extended State Observer Based Fault-Tolerant Predictive Control for a Four-Mecanum Wheels Mobile Robot 14

Extended State Observer Based Fault-Tolerant Predictive Cont...

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14th IEEE International Conference on Cyber technology in Automation, Control, and Intelligent Systems, CYBER 2024

作者： Yang, Binghao Wang, Dongliang Wen, Ziling Wei, Wu Li, Wenji Fan, Zhun Shantou University Key Lab of Digital Signal and Image Processing of Guangdong Province Guangdong 515063 China Shantou University School of Department of Electronic and Information Engineering Guangdong 515063 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangdong Guangzhou510640 China School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou510641 China

ISBN: (纸本)9798331506056

The application of unmanned vehicles in industrial cargo transportation is becoming increasingly widespread, particularly playing a significant role in transporting heavy-duty goods. However, when performing such tasks, whether in single-vehicle transportation or multi-vehicle collaborative transportation, the occurrence of wheel failures can potentially lead to serious safety accidents. Therefore, this paper proposes a fault-tolerant control scheme, establishing a kinematic model considering disturbances and failures, and adopts model predictive control for trajectory tracking. Additionally, an extended state observer is introduced to observe system states and counteract disturbances. To address potential failure issues, a controller reconstruction strategy is proposed. Finally, the effectiveness and superiority of the controller is validated through numerical simulation and comparative experiment. © 2024 IEEE.

关键词： Mobile robots

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Multi-View Speaker Embedding Learning for Enhanced Stability and Discriminability

Multi-View Speaker Embedding Learning for Enhanced Stability...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Liang He Zhihua Fang Zuoer Chen Minqiang Xu Ying Meng Penghao Wang School of Computer Science and Technology Xinjiang University Urumqi China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi China Department of Electronic Engineering Tsinghua University Beijing China iFly Digital Technology Hefei China

Deep neural network models based on x-vector have become the most popular framework for speaker recognition, and the quality of speaker features (embeddings) is important for open-set tasks such as speaker verification and speaker diarization. Currently, the most popular loss function is based on margin penalty, however, it only considers enlarging the inter-class distance while neglecting to reduce the intra-class feature differences. Therefore, we propose a multi-view learning approach that divides the training process into two views from the speaker embedding level. The classification view focuses on distinguishing the discriminability of different speakers, while the clustering view focuses on shrinking the feature boundaries of the same speaker, making intra-class differences smaller. The combined effect of the two perspectives achieves large inter-class distance and small intra-class distances, resulting in the extraction of more discriminative and stable speaker embeddings. We test the performance of the method on both speaker verification and speaker diarization tasks, and the results demonstrate the effectiveness of our approach.

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Speech Stuttering Detection and Removal Using Deep Neural Networks 11th

Speech Stuttering Detection and Removal Using Deep Neural Ne...

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11th International Conference on Computer Engineering and Networks, CENet2021

作者： Rajput, Shaswat Nersisson, Ruban Raj, Alex Noel Joseph Mary Mekala, A. Frolova, Olga Lyakso, Elena School of Electrical Engineering Vellore Institute of Technology Vellore India Key Laboratory of Digital Signal and Image Processing of Guangdong Province Department of Electronic Engineering College of Engineering Shantou University Shantou China School of Information Technology and Engineering Vellore Institute of Technology Vellore India St. Petersburg State University Saint Petersburg Russia

ISBN: (纸本)9789811665530

There are more than 70 million people worldwide who suffer from stuttering problems. This will affect the confidence of public speaking in people who suffer from this issue. To solve this problem many people take therapy sessions but the therapy sessions are a temporary solution, as soon as they leave therapy sessions this problem might arise again. This work aims to use state of the art machine learning algorithms that have improved over the past few years to solve this problem. We have used the dataset from UCLASS archives which provide the data for stuttered speech *** format with time-aligned transcriptions. We have tried different algorithms and optimized our model by hyper parameter tuning to maximize the model’s accuracy. The algorithm is tested on random speech data with low to heavy stuttering from the same dataset, and it is observed that there is significant reduction in the Word Error Rate (WER) for most of the test cases. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Learning algorithms

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Value Identification in Multistakeholder Recommender Systems for Humanities and Historical Research: The Case of the digital Archive ***

arXiv

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arXiv 2024年

关键词： Embedded systems

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A Concept for Myocardial Current Density Estimation with Magnetoelectric Sensors

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Current Directions in Biomedical Engineering 2023年第1期9卷 89-92页

作者： Schmidt, Gerhard Engelhardt, Erik Elzenheimer, Eric Hoffman, Johannes Schmidt, Tobias Zaman, Adrian Frey, Norbert Digital Signal Processing and System Theory Institute of Electrical Engineering and Information Technology Faculty of Engineering Kiel University Kaiserstr. 2 Kiel 24143 Germany Medical Department III Specialised in Cardiology and Angiology University Medical Center Schleswig-Holstein Arnold-Heller-Str. 3 / House K3 Kiel 24105 Germany Internal Medicine III: Heart Vascular and Lung University Medical Center Heidelberg Im Neuenheimer Feld 410 Heidelberg 69120 Germany

In this paper we present a novel noninvasive approach to estimate current densities in the heart from magnetocardiography. The proposed algorithm uses nested optimization to model current densities in equally-sized voxels of myocardial tissue. First-order Thiran all-pass filters are used to describe the propagation between *** demonstrate feasibility of the algorithm for a noise-free single-layer simulation. However, challenges remain, such as addressing measurement noise and optimizing propagation velocity. Overall, this approach has the potential to complement or replace invasive catheter-based electrophysiological studies for localization of arrhythmogenic tissue. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Magnetocardiography

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