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Novel Approach of a Smart Medical Mirror System for Medical Applications 5

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Novel Approach of a Smart Medical Mirror System for Medical ...

5th IEEE Middle East and Africa Conference on Biomedical engineering, MECBME 2020

作者： Halaby, Shady Khoury, George Zeid Daou, Roy Abi Hayek, Ali Boercsoek, Josef Lebanese German University Biomedical Technologies Department Jounieh Lebanon Lebanese German University Biomedical Technologies Department Jounieh Lebanon Lebanese German University Biomedical Technologies Department Jounieh Lebanon University of Kassel Faculty of Electrical Engineering/Computer Science Department of Computer Architecture and System Programming Germany University of Kassel Faculty of Electrical Engineering/Computer Science Department of Computer Architecture and System Programming Germany

ISBN: (纸本)9781728123585

Humans always face problems when it comes to medical check-up due to lack of time or laziness. However, lots of medical problems and fatal illnesses can be detected at earlier stages if the person is subject to continuous check-up. Hence, the idea of the proposed system is to design a tool enabling the measurement of the basic vital signs with the smallest effort possible from the person's side. Thus, this paper proposes a smart medical mirror system that acts as a normal mirror and also delivers the basic vital signs of the user such as the heart rate, SPO2, body temperature, and Body Mass Index (BMI). The system takes five seconds for initialization and starts the measurements and displays the results. The user will not lose time as this check-up can be performed every morning while the person is wearing his clothes and getting ready to start his daily activities. The system was tested by multiple users having different body statuses. The recorded values showed very small differences with the exact ones. At the end, the system was able to meet the user specifications concerning its portability, sensitivity, accuracy and, most importantly, its low cost. © 2020 IEEE.

关键词： Mirrors

Harmonic-Coupled Riccati Equation and its Applications in Distributed Filtering

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arXiv 2022年

作者： Qian, Jiachen Duan, Peihu Duan, Zhisheng Shi, Ling State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Electronic and Computer Engineering the Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

The coupled Riccati equations (CREs) are a set of multiple Riccati-like equations whose solutions are coupled with each other through matrix means. They are a fundamental mathematical tool to depict the inherent dynamics of many complex systems, including Markovian systems or multi-agent systems. This paper investigates a new kind of CREs called harmonic-coupled Riccati equations (HCREs), whose solutions are coupled using harmonic means. We first introduce the specific form of HCREs and then analyze the existence and uniqueness of its solutions under the conditions of collective observability and primitiveness of coupling matrices. Additionally, we ensure the uniqueness of HCREs solutions with several mild conditions. Based on this newly established theory, we greatly simplify the steady-state estimation error covariance of consensus-on-information-based distributed filtering (CIDF) into the solutions to a discrete-time Lyapunov equation (DLE). This leads to a significant conservativeness reduction of traditional performance evaluation techniques for CIDF. The obtained results are remarkable since they not only enrich the theory of CREs, but also provide a novel insight into the synthesis and analysis of CIDF algorithms. We finally validate our theoretical findings through several numerical experiments. Copyright © 2022, The Authors. All rights reserved.

关键词： Multi agent systems

A self-supervised CNN for image watermark removal

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arXiv 2024年

作者： Tian, Chunwei Zheng, Menghua Jiao, Tiancai Zuo, Wangmeng Zhang, Yanning Lin, Chia-Wen the School of Software Northwestern Polytechnical University Shaanxi Xi’an710129 China the National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Shaanxi Xi’an710129 China the School of Computer Science and Technology Harbin Institute of Technology Heilongjiang Harbin150001 China the Peng Cheng Laboratory Laboratory Guangdong Shenzhen518055 China the School of Computer Science Northwestern Polytechnical University the National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Shaanxi Xi’an710129 China the Department of Electrical Engineering the Institute of Communications Engineering National Tsing Hua University Hsinchu300 Taiwan

Popular convolutional neural networks mainly use paired images in a supervised way for image watermark removal. However, watermarked images do not have reference images in the real world, which results in poor robustness of image watermark removal techniques. In this paper, we propose a self-supervised convolutional neural network (CNN) in image watermark removal (SWCNN). SWCNN uses a self-supervised way to construct reference watermarked images rather than given paired training samples, according to watermark distribution. A heterogeneous U-Net architecture is used to extract more complementary structural information via simple components for image watermark removal. Taking into account texture information, a mixed loss is exploited to improve visual effects of image watermark removal. Besides, a watermark dataset is conducted. Experimental results show that the proposed SWCNN is superior to popular CNNs in image watermark removal. Codes can be obtained at https://***/hellloxiaotian/SWCNN. Copyright © 2024, The Authors. All rights reserved.

关键词： Textures

Sentisand: Visualizing Individual Sentiments on Social Media Through Storytelling

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SSRN

SSRN 2024年

作者： Xie, Yejuan Jing, Jielin Saha, Tulika Chen, Rongrong Wang, Yunzhe Li, Yushi Ji, Chengtao School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou China Department of Computer Science University of Liverpool Liverpool United Kingdom Guangdong Provincial Key Laboratory IRADS BNU-HKBU United International College Zhuhai China School of Electronics and Information Engineering Suzhou University of Science and Technology Suzhou China

Utilizing visualization techniques for opinion mining and sentiment exploration of social media texts is a pivotal concern in the visualization field. Research predominantly concentrates on the collective expression of numerous users on popular topics within the public domain. However, there is a need to focus on sentiment changing or evolving for individuals. This paper tries to integrate sentiment analysis with visualization techniques to enable individual users to visually explore the underlying sentiment stories behind their social media texts. Therefore, the SentiSand system is designed and developed based on user requirements. It employs innovative visual design to transform the text from users’ social media into a series of visual stories to facilitate users tracking their sentiment changes. The system provides the functionalities of visualizing the overview of the sentiment evolution over a specified period, the sentiment polarity distribution, and words used over that period as well. In a user study, ten participants with diverse backgrounds are invited to evaluate the system. The results demonstrate that SentiSand can effectively and intuitively depict sentiment states and changes. All participants gave the system high ratings across dimensions of creativity, practicality, and narrative coherence. Overall, this paper introduces a novel perspective and methodology for visualizing personal sentiments, thereby contributing to an enhanced comprehension of and intervention in individual sentiment states. © 2024, The Authors. All rights reserved.

关键词： Sentiment analysis

Microdisk Design for Vertical Collection from Quantum Emitters

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Microdisk Design for Vertical Collection from Quantum Emitte...

Frontiers in Optics + Laser science 2021, FiO+LS 2021 - Part of Frontiers in Optics, FiO 2021

作者： Hammond, Ian M. Duan, Yuqin Trusheim, Matthew E. Englund, Dirk R. Camacho, Ryan M. Department of Electrical and Computer Engineering Brigham Young University ProvoUT84602 United States Research Laboratory of Electronics M.I.T. CambridgeMA02139 United States Department of Electrical Engineering and Computer Science M.I.T. CambridgeMA02139 United States U.S. Army Research Laboratory Sensors and Electron Devices Directorate AdelphiMD20783 United States

We report on progress to improve the free space coupling and Purcell enhancement of a diamond microdisk resonator using eigenfrequency modal analysis and robust topology optimization. Frontiers in Optics / Laser Scien... 详细信息

ISBN: (纸本)9781557528209

关键词： Modal analysis

Fine-Resolution Silicon Photonic Wavelength-Selective Switch Using Hybrid Multimode Racetrack Resonators

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arXiv 2023年

作者： Cohen, Lucas M. Fatema, Saleha Wankhade, Vivek V. Lingaraju, Navin B. Zhang, Bohan Onural, Deniz Popović, Miloš Weiner, Andrew M. The Purdue Quantum Science and Engineering Institute The Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States SRI International ArlingtonVA22209 United States The John Hopkins University Applied Physics Laboratory 11100 Johns Hopkins Rd LaurelMD20723 United States The Department of Electrical and Computer Engineering Boston University BostonMA02215 United States

In this work, we describe a procedure for synthesizing racetrack resonators with large quality factors and apply it to realize a multi-channel wavelength-selective switch (WSS) on a silicon photonic chip. We first determine the contribution of each component primitive to propagation loss in a racetrack resonator and use this data to develop a model for the frequency response of arbitrary order, coupled-racetrack channel dropping filters. We design second-order racetrack filters based on this model and cascade multiple such filters to form a 1×7 WSS. We find good agreement between our model and device performance with second-order racetrack that have ≈ 1 dB of drop-port loss, ≈ 2 GHz FWHM linewidth, and low optical crosstalk due to the quick filter roll-off of ≈ 5.3 dB/GHz. Using a control algorithm, we show three-channel operation of our WSS with a channel spacing of only 10 GHz. Owing to the high quality factor and quick roll-off of our filter design, adjacent channel crosstalk is measured to be © 2023, CC BY.

关键词： Silicon photonics

FaceOri: Tracking Head Position and Orientation Using Ultrasonic Ranging on Earphones

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arXiv 2022年

作者： Wang, Yuntao Ding, Jiexin Chatterjee, Ishan Parizi, Farshid Salemi Zhuang, Yuzhou Yan, Yukang Patel, Shwetak Shi, Yuanchun Key Laboratory of Pervasive Computing Ministry of Education Department of Computer Science and Technology Tsinghua University Beijing China Institute Tsinghua University Beijing China Paul G. Allen School of Computer Science and Engineering University of Washington SeattleWA United States Electrical and Computer Engineering University of Washington SeattleWA United States Department of Computer Science and Technology Tsinghua University Beijing China

Face orientation can often indicate users' intended interaction target. In this paper, we propose FaceOri, a novel face tracking technique based on acoustic ranging using earphones. FaceOri can leverage the speaker on a commodity device to emit an ultrasonic chirp, which is picked up by the set of microphones on the user's earphone, and then processed to calculate the distance from each microphone to the device. These measurements are used to derive the user's face orientation and distance with respect to the device. We conduct a ground truth comparison and user study to evaluate FaceOri's performance. The results show that the system can determine whether the user orients to the device at a 93.5% accuracy within a 1.5 meters range. Furthermore, FaceOri can continuously track user's head orientation with a median absolute error of 10.9 mm in the distance, 3.7◦ in yaw, and 5.8◦ in pitch. FaceOri can allow for convenient hands-free control of devices and produce more intelligent context-aware interactions. Copyright © 2022, The Authors. All rights reserved.

关键词： Ultrasonic applications

Complementary multi-branch CNNs towards real-world 3D point classification

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Complementary multi-branch CNNs towards real-world 3D point ...

2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Tang, Zifeng Hao, Fusheng Zhang, Qieshi Cheng, Jun Zhang, Jin Yuan, Shuai Shenzhen Institute of Advanced Technology Chinese Academy of Science CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems China Chinese University of Hong Kong Hong Kong Shenzhen University College of Computer Science and Software Engineering China Guangdong University of Technology College of Mechanical and Electrical Engineering China

ISBN: (纸本)9781665436786

Autonomous driving requires precise and efficient point clouds processing techniques, where deep learning has shown great potential. Nonetheless, most of the existing works achieve high accuracy in synthetic data while performing unsatisfactorily in real-world datasets. On the other hand, though existing multi-view-based, volumetric-based, and point-based methods have achieved promising results, they still suffer from high computational complexity or low memory utilization efficiency. For example, the computational time and memory consumption of multi-view-based and volumetric-based methods increase at most cubically with the increasing of the input resolution, while half of the point-based methods's runtime is wasted due to their irregular memory access. To address these issues, we propose a novel method to fuse complementary CNNs, dubbed as Multi-Branch Convolutional Neural Networks (MBCNN), which achieves the current state-of-the-art performance while maintaining high efficiency. The underlying design of MBCNN is to utilize the point-based convolution as a local-feature branch and spherical convolution as a global-feature branch, to capture patterns in space and exploit the merit of the pointwise MLP, which is robust to the perturbation. Besides, we design an efficient voxel-based indexing technique to prevent the feature-extracting phase from being blocked, thus significantly accelerating the procedure of finding a point's neighbor. Experimental results show that MBCNN achieves state-of-the-art performance on the real-world 3D point clouds dataset while reducing 30% of runtime in neighbor indexing. © 2021 IEEE.

关键词： Convolutional neural networks

Dynamic Gradient Sparsification Training for Few-Shot Fine-tuning of CT Lymph Node Segmentation Foundation Model

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arXiv 2025年

作者： Luo, Zihao Gao, Zijun Liao, Wenjun Zhang, Shichuan Wang, Guotai Luo, Xiangde Department of Radiation Oncology Sichuan Cancer Hospital and Institute University of Electronic Science and Technology of China Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Department of Computer Science and Engineering The Chinese University of Hong Kong Sha Tin Hong Kong Shanghai AI Laboratory Shanghai China Department of Radiation Oncology Stanford University School of Medicine Palo AltoCA United States

Accurate lymph node (LN) segmentation is critical in radiotherapy treatment and prognosis analysis, but is limited by the need for large annotated datasets. While deep learning-based segmentation foundation models show potential in developing high-performing models with fewer samples, their medical adaptation faces LN domain-specific prior deficiencies and inefficient few-shot fine-tuning for complex clinical practices, highlighting the necessity of an LN segmentation foundation model. In this work, we annotated 36,106 visible LNs from 3,346 publicly available head-and-neck CT scans to establish a robust LN segmentation model (nnUNetv2). Building on this, we propose Dynamic Gradient Sparsification Training (DGST), a few-shot fine-tuning approach that preserves foundational knowledge while dynamically updating the most critical parameters of the LN segmentation model with few annotations. We validate it on two publicly available LN segmentation datasets: SegRap2023 and LNQ2023. The results show that DGST outperforms existing few-shot fine-tuning methods, achieving satisfactory performance with limited labeled data. We release the dataset, models and all implementations to facilitate relevant research: https://***/Zihaoluoh/LN-Seg-FM. © 2025, CC BY-SA.

关键词： computerized tomography