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Optimizing the Ferroelectric Properties of Hf1-xZrxO2 Films via Crystal Orientation

ACS Applied Electronic Materials 2023年第2期5卷 1114-1122页

作者： Teng, Chih-Yu Cheng, Chia-Chieh Li, Kai-Shin Hu, Chenming Lin, Jhih-Min Lin, Bi-Hsuan Tang, Mau-Tsu Tseng, Yuan-Chieh Department of Materials Science & Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Taiwan Semiconductor Research Institute Hsinchu30010 Taiwan Intelligent Semiconductor Nano-system Technology Research Center National Yang Ming Chiao Tung University 1001 Ta Hsueh Road Hsinchu30010 Taiwan Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States National Synchrotron Radiation Research Center Hsinchu30076 Taiwan

This study exploits the coupling of crystallographic and ferroelectric (FE) properties in an effort to enhance the FE performance of Hf1-xZrxO2 (HZO). The proposed scheme involved optimizing the orientation of orthorhombic (O)-phase crystals along the preferred polarization axis by applying an electric pulse during annealing. The proposed electric pulse annealing (EPA) process reduced the need for wake-up treatment;however, it imposed limited changes on the amount of the O-phase and leakage performance, compared with rapid thermal annealing (RTA). Excessively high EPA doses induced an O → M (monoclinic) phase transformation, which sacrificed FE polarization but preserved the wake-up-free-like properties. Our results demonstrate that optimizing the orientation of polycrystalline O-phase may be as important as maximizing the quantity of O-phase for HZO applications. © 2023 American Chemical Society.

关键词： Ferroelectricity

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VSCODE- Code With Voice Using Natural Language Processing(NLP) 1

VSCODE- Code With Voice Using Natural Language Processing(NL...

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1st International Conference on computer, Power and Communications, ICCPC 2022

作者： Prakash, M. Gnana Ponmalar, A. Deeba, S. Akilandeswari, A. Rasool, Saira Banu Mohammed Lavanya, P. Sri Sai Ram Institute of Technology Department of Information Technology Tamil Nadu Chennai India Sri Manakula Vinayagar Engineering College Department of Computer Science and Engineering Tamil Nadu Puducherry India Saveetha School of Engineering Simats Tamil Nadu Chennai India Applied College Najran University Department of Information System Saudi Arabia

ISBN: (纸本)9798350397840

Physically Challenged people who are interested in coding, in the current scenario cannot code and exhibit their knowledge in programming skills. Our project enables them to code without using a keyboard. They can code entirely by their voice and execute their code. We are converting the user's speech to text by Natural Language Processing (NLP). With the use of text obtained from NLP model we generate code snippets using our custom code generator API. The code snippets are generated in the Visual Studio Code text editor using our own VSCode extension. © 2022 IEEE.

关键词： Speech recognition

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Movement Pattern Biofeedback Training After Total Knee Arthroplasty: A Randomized Controlled Trial

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Arthritis Care and Research 2025年第6期77卷 732-743页

作者： Bade, Michael J. Christiansen, Cory L. Zeni, Joseph A. Dayton, Michael R. Forster, Jeri E. Cheuy, Victor A. Christensen, Jesse C. Hogan, Craig Koonce, Ryan Dennis, Doug Peters, Amy Stevens-Lapsley, Jennifer E. University of Colorado Anschutz Medical Campus and Eastern Colorado VA Health Care System Geriatric Research Education and Clinical Center (GRECC) Aurora CO United States Rutgers University Newark NJ United States University of Colorado Anschutz Medical Campus Aurora United States University of Colorado Anschutz Medical Campus and VA Rocky Mountain Mental Illness Research Education and Clinical Center VA Eastern Colorado Health Care System Aurora United States University of California San Francisco United States VA Salt Lake City Healthcare System Salt Lake City UT United States Colorado Joint Replacement Advent Health Porter Denver CO United States Department of Mechanical and Materials Engineering Ritchie School of Engineering and Computer Science University of Denver Denver CO United States Department of Orthopedics School of Medicine University of Colorado Anschutz Medial Campus Aurora United States Department of Biomedical Engineering School of Engineering University of Tennessee Knoxville TN United States

Objective: Habitual movement compensations, such as decreased surgical peak knee extension moments (pKEM), persist years after total knee arthroplasty (TKA), are linked to poorer recovery, and may influence contralateral osteoarthritis progression. The purpose of this randomized clinical trial was to determine if a movement training program (MOVE) improves movement quality and recovery after TKA compared to a standardized rehabilitation program without movement training (CONTROL). Methods: One hundred thirty-eight individuals were randomized to either MOVE or CONTROL groups after TKA. Participants were assessed preoperatively, 10 weeks after (end of intervention), and six months after (primary endpoint) TKA. Outcomes assessed were pKEM during walking, six-minute walk test, stair climb test, 30-second sit to stand test (30STS), timed up and go test (TUG), physical activity level, strength, range of motion, and self-reported outcomes. Results: At six months, there were no between-group differences in surgical pKEM during walking (primary outcome). The MOVE group exhibited less contralateral pKEM compared to CONTROL during self-selected gait speed (d = 0.44, P = 0.01). CONTROL performed better on TUG and 30STS at 10 weeks (P < 0.05), but differences attenuated at six months. Conclusion: The MOVE intervention did not lead to improved surgical pKEM during walking after TKA compared to CONTROL. However, the MOVE group did demonstrate less contralateral pKEM during walking. The CONTROL group demonstrated faster recovery on the TUG and 30STS, but it is unknown if this is due to improved recovery in the surgical knee or increased movement compensation relying on contralateral knee function. © 2024 American College of Rheumatology.

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A Disposable Sensor for PM2.5 and PM10 Based on Wireless Magnetoelastic Resonators

A Disposable Sensor for PM2.5 and PM10 Based on Wireless Mag...

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IEEE SENSORS

作者： Zeyu Li Haowen Li Yogesh B. Gianchandani Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Center for Wireless Integrated MicroSensing and System (WIMS) University of Michigan Ann Arbor United States

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

With the increasing awareness of the negative health impacts of airborne particulate matter (PM) on population health, there is a strong need for the development of low-cost PM sensors for citizens to monitor PM2.5 and PM10 exposure. A plastic chip measuring $\mathbf{22} \times \mathbf{14}\ \mathbf{mm}^{\mathbf{2}}$ is reported; it is comprised of two stages, for PM2.5 and PM10, each incorporating an impactor and a magnetoelastic resonator. The resonators are wirelessly interrogated by planar coils incorporated into an underlying PCB. Experimental test results show sensitivity levels of $\mathbf{0.117} \mathbf{Hz}/(\mathbf{min}\times\boldsymbol{\mu} \mathbf{g}/\mathbf{m}^{\mathbf{3}})$ for PM2.5 and $\mathbf{0.056}\ \mathbf{Hz}/(\mathbf{min}\times\boldsymbol{\mu} \mathbf{g}/\mathbf{m}^{\mathbf{3}})$ for the larger particles contained in PM10. Accelerated tests show a projected service lifetime exceeding 416 days in the designated operation mode and environmental conditions.

关键词： Wireless communication Wireless sensor networks Semiconductor device measurement Sensitivity Pollution Magnetic sensors Magnetic separation Particle measurements Pollution measurement Plastics

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Towards an Accurate Liver Disease Prediction Based on Two-level Ensemble Stacking Model

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IEEE Access 2024年

作者： Mohamed, Marghny H. Ali, Botheina H. Taloba, Ahmed I. Aseeri, Ahmad O. Elaziz, Mohamed Abd El-Sappgah, Shaker El-Rashidy, Nora Assiut University Faculty of Computers and Information Department of Computer Science Assiut Egypt Japan University of Science and Technology - P.O Box 179 Computer science and information technology New Borg El-Arab City Alexandria21934 Egypt Arish University Faculty of Computers and Information Department of Information System Egypt Prince Sattam Bin Abdulaziz University College of Computer Engineering and Sciences Department of Computer Science Al Kharj11942 Saudi Arabia Galala University Faculty of Computer Science and Engineering Suez435611 Egypt Benha University Faculty of Computers and Artificial Intelligence Information Systems Department Banha13518 Egypt Kafrelsheikh University Faculty of Artificial Intelligence Department of Machine Learning and Information Retrieval El-Geish st Kafrelsheikh33516 Egypt

The difficulty of detecting liver disease at an early stage goes back to its limited number of symptoms. In this study, single and ensemble machine learning (ML) algorithms are applied to the Indian Liver Patient Dataset (ILPD) dataset, and their results, without and with feature selection techniques, are compared between each other and to the existing studies. Also, a two-level ensemble stacking model is applied based on several meta-ensemble classifiers and the feature selection technique to optimize the accuracy of the ensemble classifiers. Several data preprocessing techniques are employed to optimize the accuracy of the proposed work, including data encoding, data cleaning, data scaling, data skewing transformation, data balancing, and feature selection. The choices of single model ML are logistic regression (LR), K-nearest neighbors (KNN), decision tree (DT), linear discriminant analysis (LDA), and multilayer perceptron (MLP). In contrast, the choices of ensemble ML models are extra tree classifier, random forest (RF), gradient boosting, AdaBoost, extreme gradient boosting (XGBoost), and ensemble stacking classifier. Among the ensemble models, the ensemble stacking model achieved the highest accuracies (93.88% and 94.12%) when trained without and with the feature selection technique using the 10-fold cross-validation. The two-level ensemble stacking model achieved the highest performance with the metrics values: accuracy (94.01%), Precision (94.44%), Recall (94.25%), F1-score (94.01%), and area under the ROC curve (94.25%) when trained with feature selection technique. These results indicate that our proposed technique achieved a high prediction model for liver disease. © 2013 IEEE.

关键词： Prediction models

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Simulation and analysis of ultra-low material loss of single-mode photonic crystal fiber in terahertz (THz) spectrum for communication applications

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Journal of Optical Communications 2023年第s1期44卷 S631-S639页

作者： Hossain, Md. Selim Hasan, Md. Mahedi Sen, Shuvo Mollah, Md. Sarwar Hossain Azad, Mir Mohammad Tangail Santosh1902 Bangladesh Dhaka Bangladesh Department of Management and Information System Prime University Dhaka Bangladesh Department of Computer Science and Engineering Khwaja Yunus Ali University Enayetpur Sirajganj Bangladesh

This analysis represents a circular shape based cladding with two elliptical shape cores in photonic crystal fiber (PCF) for the terahertz (THz) range. Here, we present a single-mode photonic crystal fiber (SM-PCF) with five layers of circular shape of air holes (CAH) structure along with two layers of elliptical shape of air holes (EAH) core configuration in the center to decrease the different types of losses. For broad-band communications, our proposed SM-PCF is highly useful due to the obtaining of ultra-low effective material loss (UML) in the terahertz regime. Perfectly matched layers (PMLs) and finite element method (FEM) established on COMSOL Multiphysics software has been used to design this PCF fiber. Simulated outcomes show a particularly an UML deficit of 0.014 cm−1, power fraction in the core area (CA) and large effective area (EA) of 72%, and 5.90 × 10−8 m2 respectively at 1 terahertz (THz) frequency. Also, other aspects of optical fiber for THz signal banquet with confinement loss (CL), scattering loss (SL) and V-parameter have been calculated here. Moreover, our proposed SM-PCF shows single-mode propagation by V-parameter pointer over 0.80–3 THz frequency. So, we can say that our designed PCF fiber will be suitable for various effective communication areas at the terahertz (THz) spectrum. © 2023 Walter de Gruyter GmbH. All rights reserved.

关键词： Photonic crystal fibers

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SkeletonGait: Gait Recognition Using Skeleton Maps

arXiv

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arXiv 2023年

作者： Fan, Chao Ma, Jingzhe Jin, Dongyang Shen, Chuanfu Yu, Shiqi Research Institute of Trustworthy Autonomous System Southern University of Science and Technology China Department of Computer Science and Engineering Southern University of Science and Technology China The University of Hong Kong Hong Kong

The choice of the representations is essential for deep gait recognition methods. The binary silhouettes and skeletal coordinates are two dominant representations in recent literature, achieving remarkable advances in many scenarios. However, inherent challenges remain, in which silhouettes are not always guaranteed in unconstrained scenes, and structural cues have not been fully utilized from skeletons. In this paper, we introduce a novel skeletal gait representation named skeleton map, together with SkeletonGait, a skeleton-based method to exploit structural information from human skeleton maps. Specifically, the skeleton map represents the coordinates of human joints as a heatmap with Gaussian approximation, exhibiting a silhouette-like image devoid of exact body structure. Beyond achieving state-of-the-art performances over five popular gait datasets, more importantly, SkeletonGait uncovers novel insights about how important structural features are in describing gait and when they play a role. Furthermore, we propose a multi-branch architecture, named SkeletonGait++, to make use of complementary features from both skeletons and silhouettes. Experiments indicate that SkeletonGait++ outperforms existing state-of-theart methods by a significant margin in various scenarios. For instance, it achieves an impressive rank-1 accuracy of over 85% on the challenging GREW dataset. All the source code is available at https://***/ShiqiYu/OpenGait. © 2023, CC BY-NC-ND.

关键词： Gait analysis

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Adhesive bioelectronics for closed-loop therapy

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Med-X 2025年第1期3卷 1-32页

作者： Jung, Hyunjin Lee, Hyelim Shin, Mikyung Son, Donghee Department of Electrical and Computer Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea Center for Neuroscience Imaging Research Institute for Basic Science Suwon Republic of Korea Department of Intelligent Precision Healthcare Convergence Sungkyunkwan University (SKKU) Suwon Republic of Korea Department of Biomedical Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea Department of Artificial Intelligence System Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea

Wearable and implantable devices mark a major advancement in biomedical engineering, enabling continuous bio-signal monitoring and treatment based on precise feedback. However, traditional rigid bioelectronic devices face challenges in seamlessly interfacing with soft organs, often leading to tissue damage and inflammation. To address these issues, soft bioelectronics that better conform to the body while maintaining performance accuracy have been developed. Despite these advancements, the dynamic nature of body movements and the complex chemical environment in the body can compromise the stability of devices over time. Therefore, recent innovations have focused on ultrathin and stretchable designs that enhance conformal contact through van der Waals forces, as well as the incorporation of adhesive hydrogels, to improve adhesion, even in the presence of biofluids. This review provides a comprehensive overview of the advancements in wearable and implantable bioelectronics aimed at achieving conformal tissue adhesion and long-term stability, covering structural modifications to bilayer designs. Finally, the integration of bioelectronics with closed-loop therapies to significantly enhance treatment efficacy is explored. • Materials strategies and device fabrication/integration processes optimally tailored to various organs are addressed. • Mechanical and electrical characterizations of wearable and implantable adhesive bioelectronics are described, while emphasizing challenges and opportunities in long-term stable tissue interfacing. • Various demonstrations of closed-loop bio-integrated systems using soft stretchable adhesive materials, and their futuristic perspectives are introduced.

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Detail-Enhancing Framework for Reference-Based Image Super-Resolution

arXiv

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arXiv 2024年

作者： Wang, Zihan Xiong, Ziliang Tang, Hongying Yuan, Xiaobing Shanghai Institution of Micro-system and Information Technology University of Chinese Academy of Science China Computer Vision Laboratory Department of Electrical Engineering LiU Sweden School of Information Science and Technology Shanghai Tech University China

Recent years have witnessed the prosperity of reference-based image super-resolution (Ref-SR). By importing the high-resolution (HR) reference images into the single image super-resolution (SISR) approach, the ill-posed nature of this long-standing field has been alleviated with the assistance of texture transferred from reference images. Although the significant improvement in quantitative and qualitative results has verified the superiority of Ref-SR methods, the presence of misalignment before texture transfer indicates room for further performance improvement. Existing methods tend to neglect the significance of details in the context of comparison, therefore not fully leveraging the information contained within low-resolution (LR) images. In this paper, we propose a Detail-Enhancing Framework (DEF) for reference-based super-resolution, which introduces the diffusion model to generate and enhance the underlying detail in LR images. If corresponding parts are present in the reference image, our method can facilitate rigorous alignment. In cases where the reference image lacks corresponding parts, it ensures a fundamental improvement while avoiding the influence of the reference image. Extensive experiments demonstrate that our proposed method achieves superior visual results while maintaining comparable numerical outcomes. Copyright © 2024, The Authors. All rights reserved.

关键词： Textures

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Retinal Image Pre-Processing Using Equalization and thResholding (RIPPER) 23

Retinal Image Pre-Processing Using Equalization and thReshol...

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Proceedings of the 2023 10th International Conference on Bioinformatics Research and Applications

作者： Nnamdi Nwanze Chukwuemeka C. Nwanze Abumere Akinwale Larry Baitch Computer Science & Engineering North Central College USA School of Optometry Mass. Coll. of Pharm & Health Sciences USA Department of Ophthalmology Veterans Healthcare System USA

ISBN: (纸本)9798400708152

The eye is the only location on the human body that enables non-invasive evaluation of blood vessels. Clinicians can correlate the presence of systemic diseases, such as hypertension and diabetes, with the appearance of the ocular blood vessels. As such, there has been significant interest in accurate retinal vessel segmentation and classification. Traditionally, segmentation and classification methods first pre-process an image, then apply a vessel identifying technique. The results of this process is then compared to a gold-standard–typically an image that has been manually segmented by a human domain expert. In this paper, we propose RIPPER (Retinal Image Pre-Processing using Equalization And thResholding) a highly effective retinal image pre-processing technique for use in both manual and automated vessel segmentation systems. We apply RIPPER to two publicly available retinal image databases, DRIVE and HRF, which contain gold standard segmentations for each image. Our results show that using RIPPER can increase the accuracy of the gold standard images by up to 20% thereby allowing for increased performance in retinal vessel segmentation and classification systems.

关键词： convolutional neural networks datasets deep learning fundus images image pre-processing image processing machine learning retinal blood vessel segmentation retinal blood vessels classification retinal vessels vessel segmentation

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