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Design of High-Performance Optical TE Modulator Based on Si/VO2/Si Structure 2

Design of High-Performance Optical TE Modulator Based on Si/...

引用

2nd International engineering Conference on electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Heidari, Mohsen Mansour, Ibrahim Vatani, Sareh Heydari, Ebrahim Tarbiat Modares University Department of Electrical and Computer Engineering Tehran Iran Zarqa University Zarqa Jordan College of Engineering University of Business and Technology Jeddah21448 Saudi Arabia University of Nevada Department of Electrical and Biomedical Engineering RenoNV89557 United States

ISBN: (纸本)9798350373363

Phase transition in vanadium dioxide (VO2) from insulation to metallic phase, makes it an attractive candidate for the realization of electro-absorption modulators. In this paper, we investigate and design a high-performance modulator at the telecommunication wavelength of λ = 1.55 μm, based on a silicon rib waveguide incorporated with a nanostrip V02 layer. The modulator utilizes an asymmetric structure for enhancing the modulation depth and reaching the minimum insertion loss. We show that for transverse electric optical modes, the asymmetric structure shows better characteristics. The results show a high-modulation depth of about 6.54 dB/μm and the corresponding insertion loss of about 1.34 dB/μm. © 2023 IEEE.

关键词： Optical signal processing

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Non-Invasive, Cerebral Blood Volume Measurements During Sleep: Toward Naturalistic Measurements of Glymphatic Flux

Non-Invasive, Cerebral Blood Volume Measurements During Slee...

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Optical Tomography and Spectroscopy, OT and S 2024 - Part of Optica Biophotonics Congress: biomedical Optics

作者： Otic, Nikola Renna, Marco Lewis, Laura Franceschini, Maria Angela Robinson, Mitchell B. Department of Biomedical Engineering Boston University BostonMA United States Harvard Medical School MGH/HST Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital CharlestownMA United States Department of Electrical Engineering and Computer Science Institute for Medical Engineering and Science Massachusetts Institute of Technology CambridgeMA United States

The hemodynamic sources of glymphatic flow are typically measured using MRI. In this work, we demonstrate the feasibility of measuring cerebral hemodynamics through NIRS toward the goal of estimating glymphatic flux i... 详细信息

ISBN: (纸本)9781957171340

关键词： Hemodynamics

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IoT-Enabled Facial Recognition for Smart Hospitality for Contactless Guest Services and Identity Verification 11

IoT-Enabled Facial Recognition for Smart Hospitality for Con...

引用

11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Srinivasan, S. Raja, R. Jehan, C. Murugan, S. Srinivasan, C. Muthulekshmi, M. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India Department of Electrical and Electronics Engineering Tamil Nadu Namakkal India Vel Tech Multitech Dr.Rangarajan Dr.Sagunthala Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350350357

The proposed system integrates face recognition and Internet of Things (IoT) technology to revolutionize the hospitality industry. It uses OpenCV, a widely recognized computer vision library, to deliver smooth, contactless guest services and rigorous identification verification. This paper proposes a novel method to improve visitor experiences by removing check-in and allowing personalized services. The IoT -enabled face recognition system presented in this paper streamlines the visitor experiences. Facial biometrics eliminates the need for identity papers, making the check-in process simple. The proposed system, OpenCV, is used for face detection, identification, and verification. The system's design includes strategically positioned cameras for visitor identification and tracking. Health and safety are crucial, so this system's contactless nature is a major benefit. The solution also increases visitor safety by lowering the danger of fraud and illegal access. The IoT-enabled face recognition technology improves operational efficiency, guest satisfaction, and security in the hospital industry. © 2024 IEEE.

关键词： Internet of things

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A Real-time Affordance-based Object Pose Estimation Approach for Robotic Grasp Pose Estimation

A Real-time Affordance-based Object Pose Estimation Approach...

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2023 International Conference on System Science and engineering, ICSSE 2023

作者： Wong, Shang-Wen Chiu, Yu-Chen Tsai, Chi-Yi Tamkang University Doctoral Program in Robotics College of Engineering New Taipei City Taiwan Tamkang University Department of Electrical and Computer Engineering New Taipei City Taiwan

ISBN: (纸本)9798350322941

This paper proposes a pose estimation system for robot grasping based on a novel Object Affordance Detection and Segmentation (OADS) network. The proposed system consists of four modules: (1) OADS network;(2) point cloud extraction;(3) object pose estimation;(4) grasp pose estimation. Based on the OADS network, the proposed system achieves affordance-based object pose estimation results. The proposed grasp pose estimation system is evaluated on a laboratory-made dual-arm robot. Experimental results show that the proposed system achieves high detection rate and high accuracy in affordance detection and segmentation tasks, leading to a high success rate in object grasping tasks with lab-made dual-arm robot. © 2023 IEEE.

关键词： Object detection

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EmoNet: Deep Learning-based Emotion Climate Recognition Using Peers' Conversational Speech, Affect Dynamics, and Physiological Data 46

EmoNet: Deep Learning-based Emotion Climate Recognition Usin...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Alhussein, Ghada Alkhodari, Mohanad Saleem, Shiza Roumeliotou, Efstratia Hadjileontiadis, Leontios J. Khalifa University Department of Biomedical Engineering and Biotechnology Abu Dhabi United Arab Emirates University of Oxford Cardiovascular Clinical Research Facility Radcliffe Department of Medicine Oxford United Kingdom Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki Greece

ISBN: (纸本)9798350371499

Understanding the emotional dynamics within social interactions is crucial for meaningful interpretation. Despite progress in emotion recognition systems, recognizing the collective emotional climate among peers has been understudied. Addressing this gap, we propose EmoNet, an AI model transcending traditional emotion identification. EmoNet employs Mel-frequency cepstral coefficients and a Temporal Convolutional Network to extract deep features from speech signals. It uniquely integrates affect dynamics and physiological inputs (heart rate, electrodermal activity), providing a holistic view of emotion climates. Tested on K-EmoCon dataset, EmoNet excels in arousal and valence classification, achieving 87.82% and 83.79% accuracy, respectively. These results position EmoNet as a valuable tool for understanding and influencing emotion climates in real-world conversations, with applications in healthcare and human-computer interactions. © 2024 IEEE.

关键词： Emotion Recognition

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Stabilizing Control Design by Integrable Differential Passive Outputs 63

Stabilizing Control Design by Integrable Differential Passiv...

引用

63rd IEEE Conference on Decision and Control, CDC 2024

作者： Monfared, Morteza Nazari Kawano, Yu Cucuzzella, Michele University of Pavia Computer and Biomedical Engineering Department of Electrical Pavia27100 Italy Hiroshima University Graduate School of Advance Science and Engineering Higashi-hiroshima739-8527 Japan Nijenborgh 4 AG Groningen9747 Netherlands

ISBN: (纸本)9798350316339

Differential passivity of a nonlinear system has been introduced as passivity of its variational system. Applying standard passivity-based control techniques to differentially passive systems leads to controllers for the corresponding variational systems. However, it is challenging to construct controllers for the original nonlinear systems if the differential passive outputs are non-exact differential one-forms. In this letter, our objective is to provide a systematic procedure to address this issue when differential passive outputs are integrable, i.e., when non-exact differential passive outputs can be made exact by multiplying them by suitable integrating factors. In particular, under suitable detectability assumptions, we propose one static and two dynamic state feedback stabilizing controllers, where each dynamic controller has a form of input-and output-shaping, respectively. We illustrate their effectiveness by stabilization of counter-current heat exchangers. © 2024 IEEE.

关键词： State feedback

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Spectral Recursive Approach to the Time-Domain Inverse Kernel

Spectral Recursive Approach to the Time-Domain Inverse Kerne...

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2023 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2023

作者： Liebau, Thomas J. Manteghi, Majid Virginia Tech Department of Electrical and Computer Engineering BlacksburgVA24060 United States Virginia Tech Engineering Mechanics Program BlacksburgVA24060 United States

ISBN: (纸本)9781946815187

We study the response of the infinite strip to an H-polarized impulsive line source. The infinite-plane solution, valid for times such that the influence of the source has yet to propagate to the boundary, is used to express the inverse kernel explicitly in terms of the effects of truncation. By extracting the immediate response of each boundary to the source, we obtain a form of the inverse kernel that separates the early-time response due to specular reflections, and the late-time response associated with resonances. © 2023 USNC-URSI.

关键词： Strips Reflection Kernel Time-domain analysis

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Classifying Upper Extremity Motor Function Using Deep Learning and Third-Person Video Data

Classifying Upper Extremity Motor Function Using Deep Learni...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Tran, Tan Chang, Lin-Ching Lum, Peter The Catholic University of America Department of Electrical Engineering and Computer Science WashingtonDC United States New Jersey Institute of Technology Department of Informatics NewarkNJ United States The Catholic University of America Department of Biomedical Engineering WashingtonDC United States

ISBN: (纸本)9798350362480

Post-stroke rehabilitation of upper extremity (UE) motor function is essential. Despite the widespread use of UE rehabilitation in clinical settings, assessing the success of these treatments is challenging. Methods for evaluating UE motor function include task performance under clinical supervision, patient self-reports, and data analysis from wearable devices equipped with accelerometers and gyroscopes. In prior research, we demonstrated that machine learning and deep learning models using data from a single wrist-worn accelerometer sensor could accurately differentiate between functional and non-functional UE movements in stroke patients. To overcome the limitations of single wrist-worn accelerometer sensors - challenges in capturing the full context of functional movements - this study presents a new deep learning (DL) based framework designed to classify functional and non-functional arm movements in videos captured from a conventional camera. The system is entirely automated and comprises two DL networks. The first network performs human pose estimation, extracting 2D pose key points of the paretic arm(s) and torso on 2-second sequences of the frames. The second network then uses these 2D pose landmarks to classify the movement sequence as functional or non-functional. This system offers two key benefits for rehabilitation. First, it can automatically generate initial annotations for video frames, significantly reducing the time needed for manual labeling. Second, analyzing the effectiveness of UE rehabilitation through third-person videos allows for objective outcome measurement of UE treatments in stroke survivors' home environments. © 2024 IEEE.

关键词： Accelerometers

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The Design of the Logarithmic Detector in the Front-End Board of Sonography Systems 1

The Design of the Logarithmic Detector in the Front-End Boar...

引用

1st International engineering Conference on electrical, Energy, and Artificial Intelligence, EICEEAI 2022

作者： Moravej, Yasaman Boostani, Reza Abusuilik, Saleh Mansour, Ibrahim M. School of Electrical and Computer Engineering Shiraz University Biomedical Department Shiraz Iran Shiraz University Reza Boostani Biomedical Group Faculty of Electrical and Computer Shiraz Iran Zarqa University Department of Mechanical Engineering Zarqa Jordan Zarqa University Faculty of Engineering Electrical Department Zarqa Jordan

ISBN: (纸本)9798350332742

Front-End design is one of the most challenging parts in an ultrasound system (sonography) in which the modulated signals from the body are received with very low amplitude within the frequency range of 2 to12 MHz. Since the main concern is to design small circuits, here, an applicable circuit is proposed with the objective of using the minimum number of electronic devices which absorbs very low noise within its nominal range. The proposed circuit is the logarithmic amplifier detector which is a part of the Front-End board. The conventional logarithmic amplifiers use an inductor to modulate the current to voltage in order to be robust against noise. Here, in addition to proposing an efficient circuit, the inductor is replaced with a small circuit. The simulation results in the OrCAD software demonstrate the proper behavior of the proposed circuit. © 2022 IEEE.

关键词： Electric inductors

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Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases 46

Eye-tracking in Mixed Reality for Diagnosis of Neurodegenera...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Daniol, Mateusz Hemmerling, Daria Sikora, Jakub Jemiolo, Pawel Wodzinski, Marek Wojcik-Pedziwiatr, Magdalena Agh University of Kraków Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Krakow Poland Information Systems Institute Sierre Switzerland Andrzej Frycz Modrzewski Krakow University Department of Neurology Krakow Poland

ISBN: (纸本)9798350371499

Parkinson's disease ranks as the second most prevalent neurodegenerative disorder globally. This research aims to develop a system leveraging Mixed Reality capabilities for tracking and assessing eye movements. In this paper, we present a medical scenario and outline the development of an application designed to capture eye-tracking signals through Mixed Reality technology for the evaluation of neurodegenerative diseases. Additionally, we introduce a pipeline for extracting clinically relevant features from eye-gaze analysis, describing the capabilities of the proposed system from a medical perspective. The study involved a cohort of healthy control individuals and patients suffering from Parkinson's disease, showcasing the feasibility and potential of the proposed technology for non-intrusive monitoring of eye movement patterns for the diagnosis of neurodegenerative *** relevance - Developing a non-invasive biomarker for Parkinson' s disease is urgently needed to accurately detect the disease's onset. This would allow for the timely introduction of neuroprotective treatment at the earliest stage and enable the continuous monitoring of intervention outcomes. The ability to detect subtle changes in eye movements allows for early diagnosis, offering a critical window for intervention before more pronounced symptoms emerge. Eye tracking provides objective and quantifiable biomarkers, ensuring reliable assessments of disease progression and cognitive function. The eye gaze analysis using Mixed Reality glasses is wireless, facilitating convenient assessments in both home and hospital settings. The approach offers the advantage of utilizing hardware that requires no additional specialized attachments, enabling examinations through personal eyewear © 2024 IEEE.

关键词： Neurodegenerative diseases

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