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A Transparent Ultrasound Array for Real-Time Optical,Ultrasound,and Photoacoustic Imaging

Biomedical engineering Frontiers 2022年第1期3卷 284-297页

作者： Haoyang Chen Sumit Agrawal Mohamed Osman Josiah Minotto Shubham Mirg Jinyun Liu Ajay Dangi Quyen Tran Thomas Jackson Sri-Rajasekhar Kothapalli Department of Biomedical Engineering The Pennsylvania State UniversityUniversity ParkPA 16802USA School of Electrical Engineering and Computer Science The Pennsylvania State UniversityUniversity ParkPA 16802USA Penn State Cancer Institute The Pennsylvania State UniversityHersheyPA 17033USA Graduate Program in Acoustics The Pennsylvania State UniversityUniversity ParkPA 16802USA

Objective and Impact *** imaging of ultrasound and optical contrasts can help map structural,functional,and molecular biomarkers inside living subjects with high spatial *** is a need to develop a platform to facilitate this multimodal imaging capability to improve diagnostic sensitivity and ***,combining ultrasound,photoacoustic,and optical imaging modalities is challenging because conventional ultrasound transducer arrays are optically *** a result,complex geometries are used to coalign both optical and ultrasound waves in the same field of *** elegant solution is to make the ultrasound transducer transparent to ***,we demonstrate a novel transparent ultrasound transducer(TUT)linear array fabricated using a transparent lithium niobate piezoelectric material for real-time multimodal *** TUT-array consists of 64 elements and centered at~6 MHz *** demonstrate a quad-mode ultrasound,Doppler ultrasound,photoacoustic,and fluorescence imaging in real-time using the TUT-array directly coupled to the tissue mimicking *** TUT-array successfully showed a multimodal imaging capability and has potential applications in diagnosing cancer,neurological,and vascular diseases,including image-guided endoscopy and wearable imaging.

关键词： Ultrasound specificity transparent

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Monitoring AI-modified content at scale: a case study on the impact of ChatGPT on AI conference peer reviews 24

Monitoring AI-modified content at scale: a case study on the...

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Proceedings of the 41st International Conference on Machine Learning

作者： Weixin Liang Zachary Izzo Yaohui Zhang Haley Lepp Hancheng Cao Xuandong Zhao Lingjiao Chen Haotian Ye Sheng Liu Zhi Huang Daniel A. McFarland James Y. Zou Department of Computer Science Stanford University Machine Learning Department NEC Labs America Department of Electrical Engineering Stanford University Graduate School of Education Stanford University Department of Computer Science and Department of Management Science and Engineering Stanford University Department of Computer Science UC Santa Barbara Department of Biomedical Data Science Stanford University Graduate School of Education and Department of Sociology and Graduate School of Business Stanford University Department of Computer Science and Department of Electrical Engineering and Department of Biomedical Data Science Stanford University

We present an approach for estimating the fraction of text in a large corpus which is likely to be substantially modified or produced by a large language model (LLM). Our maximum likelihood model leverages expert-written and AI-generated reference texts to accurately and efficiently examine real-world LLM-use at the corpus level. We apply this approach to a case study of scientific peer review in AI conferences that took place after the release of ChatGPT: ICLR 2024, NeurIPS 2023, CoRL 2023 and EMNLP 2023. Our results suggest that between 6.5% and 16.9% of text submitted as peer reviews to these conferences could have been substantially modified by LLMs, i.e. beyond spell-checking or minor writing updates. The circumstances in which generated text occurs offer insight into user behavior: the estimated fraction of LLM-generated text is higher in reviews which report lower confidence, were submitted close to the deadline, and from reviewers who are less likely to respond to author rebuttals. We also observe corpus-level trends in generated text which may be too subtle to detect at the individual level, and discuss the implications of such trends on peer review. We call for future interdisciplinary work to examine how LLM use is changing our information and knowledge practices.

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Uncertainty Quantification Using Subsampling for Assembly-Free Estimates of Genomic Distance and Phylogenetic Relationships 26th

Uncertainty Quantification Using Subsampling for Assembly-F...

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26th International Conference on Research in Computational Molecular Biology, RECOMB 2022

作者： Rachtman, Eleonora Sarmashghi, Shahab Bafna, Vineet Mirarab, Siavash Bioinformatics and Systems Biology Graduate Program UC San Diego La JollaCA United States Department of Electrical and Computer Engineering UC San Diego La JollaCA United States Department of Computer Science and Engineering UC San Diego La JollaCA United States

Computing the distance between two genomes, often without using alignments or even access to assembled sequences, is fundamental to many downstream analyses. © 2022, The Author(s), under exclusive license to Spri... 详细信息

ISBN: (纸本)9783031047480

关键词： Uncertainty analysis

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Room-scale magnetoquasistatic wireless power transfer using a cavity-based multimode resonator

arXiv

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arXiv 2025年

作者： Sasatani, Takuya Sample, Alanson P. Kawahara, Yoshihiro Department of Electrical Engineering and Information Systems Graduate School of Engineering The University of Tokyo Bunkyo-ku Tokyo Japan Electrical Engineering and Computer Science Department University of Michigan Ann ArborMI United States

Magnetoquasistatic wireless power transfer can be used to charge and power electronic devices such as smartphones and small home appliances. However, existing coil-based transmitters, which are composed of wire conductors, have a limited range. Here, we show that multimode-quasistatic cavity resonance can provide room-scale wireless power transfer. The approach uses multidirectional, widely distributed currents on conductive surfaces that are placed around the target volume. It generates multiple, mutually unique, three-dimensional magnetic field patterns, where each pattern is attributed to different eigenmodes of a single room scale resonator. Using these modes together, a power delivery efficiency exceeding 37.1% can be achieved throughout a 3 m × 3 m × 2 m test room. With this approach, power exceeding 50 W could potentially be delivered to mobile receivers, while in accordance with safety guidelines. Copyright © 2025, The Authors. All rights reserved.

关键词： Inductive power transmission

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Enhanced Feature Extraction and Attention Mechanisms for Micro-Expression Recognition

Enhanced Feature Extraction and Attention Mechanisms for Mic...

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IEEE Workshop on Machine Learning for Signal Processing

作者： Chun-Ting Fang Tsung-Jung Liu Kuan-Hsien Liu Department of Electrical Engineering and Graduate Institute of Communication Engineering National Chung Hsing University Taiwan Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taiwan

ISBN: (数字)9798350372250

ISBN: (纸本)9798350372267

Micro-expressions refer to subtle changes in expressions that are displayed by humans in a very short period of time. As a form of non-verbal emotional expression, micro-expressions can more accurately reflect an individual's true inner feelings. We propose a shallow dual-branch 3D-CNN architecture for the first stage of feature extraction. Additionally, we enhance and optimize the channel attention module within the convolutional block attention module. We then employ Gated Recurrent Unit and Multi-Scale Multi-Head Self-Attention for the second stage of feature extraction. We tested our model on 3 different micro-expression databases and obtained competitive results. Numerous experimental results show that our method can achieve good performance with relatively simple input and architecture. The source code and pretrained models are available at https://***/dannyFan-0201/MLSP_2024.

关键词： Training Optical losses Convolutional codes Attention mechanisms Databases Convolution Source coding Logic gates Feature extraction Optical flow

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Multi-Location and Multi-Feature LMP Forecasting: A 2D Spatiotemporal LSTM-CNN Approach

Multi-Location and Multi-Feature LMP Forecasting: A 2D Spati...

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Power, Energy and electrical engineering (CPEEE), International Conference on

作者： Noelyn M. De Jesus Enrique D. Festijo Gerard Francesco DG. Apolinario Dylan Josh Domingo Lopez Graduate School Technological Institute of the Philippines Manila Philippines Electrical Engineering Technological Institute of the Philippines Manila Philippines Electrical Engineering and Computer Science Chung Yuan Christian University Taoyuan Taiwan

ISBN: (数字)9798331520090

ISBN: (纸本)9798331520106

Accurate Locational Marginal Price (LMP) forecasting is crucial for effective energy procurement in electricity markets, as it helps utilities make informed, cost-efficient decisions. This study addresses the limitations of traditional models by introducing a 2D spatiotemporal LSTM-CNN model that utilizes multi-location and multi-feature inputs to improve forecast accuracy specifically for Batangas I Electric Cooperative, Inc. (BATELEC I). Using the Dynamic Interval Price Collection (DIPC) dataset from the Independent Electricity Market Operator of the Philippines (IEMOP), which provides 5-minute interval data from June 2021 to August 2024, the model captures short-term price fluctuations across resource locations. Results indicate that the 2D Multi-Features and Multi-Locations LSTM-CNN model outperforms 1D and 3D configurations, achieving the lowest RMSE of 5.0976E-03 and effectively capturing spatial and temporal dependencies. These findings support improved decision-making in electricity markets, with future applications in real-time adaptive forecasting for enhanced market responsiveness.

关键词： Solid modeling Adaptation models Accuracy Three-dimensional displays Predictive models Electricity supply industry Data models Real-time systems Spatiotemporal phenomena Forecasting

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Encrypted Domain Secret Medical-Image Sharing with Secure Outsourcing Computation in IoT Environment

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IEEE Internet of Things Journal 2024年第2期11卷 2382-2393页

作者： Huang, Jingwang Cui, Qi Zhou, Zhili Yu, Keping Yang, Ching-Nung Choo, Kim-Kwang Raymond Institute of Artificial Intelligence and Blockchain Guangzhou University Guangzhou510006 China Nanjing University Information Science and Technology Engineering Research Center of Digital Forensics Ministry of Education Nanjing210044 China Nanyang Technological University School of Electrical and Electronic Engineering Jurong West639798 Singapore Guangzhou University Institute of Artificial Intelligence and Blockchain Guangzhou510006 China Hosei University Graduate School of Science and Engineering Tokyo184-8584 Japan National Dong Hwa University Department of Computer Science and Information Engineering Hualien974301 Taiwan The University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX78249 United States

In existing secret medical-image sharing (SMIS) schemes, to protect and manage secret medical-images (SMIs), the sharing and recovery of each SMI are implemented by local servers of medical institutions. However, since a lot of SMIs are produced by personal smart terminal devices in Internet of Things (IoT) environment, directly implementing the sharing and recovery processes will cause excessive communication and computing burden for those local servers, which makes the existing SMIS schemes not suitable for IoT environment. To address the above issue, we propose an encrypted domain SMIS (Enc-SMIS) scheme with secure outsourcing computation for protecting and managing medical images in IoT environment. In the proposed scheme, the medical images are first encrypted using fully homomorphic encryption (FHE) and then outsourced to a cloud server for generating a set of image shares. Subsequently, these shares are stored separately in different local servers of medical institutions. Furthermore, the recovery process is also outsourced to the cloud server when doctors need to observe the patients' medical images. Compared with the existing SMIS schemes, the proposed Enc-SMIS scheme alleviates the computing and communication burden on local servers significantly with secure outsourcing computation in the semi-honest model, and thus supports the storage and management of medical images well in IoT environment. © 2014 IEEE.

关键词： Internet of things

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Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN)

Development of Detection Lung Disease Stand Alone System Bas...

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International Conference of computer and Informatics engineering (IC2IE)

作者： Edgar Caesar Liewarnata Yosica Mariana Sofyan Tan Suryadiputra Liawatimena Winda Astuti Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Product Design Program Industrial Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification.

关键词： Training Accuracy Tuberculosis Pulmonary diseases Lungs Stethoscope Recording Convolutional neural networks Mel frequency cepstral coefficient Testing

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Evaluating a frailty education program implemented through barbershops/salons in Japan: A preliminary study

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SN Social sciences 2022年第5期2卷 1-13页

作者： Makabe, Sachiko Fujiwara, Katsuya Kume, Yu Kaga, Midori Munemura, Nobuko Kemuyama, Shoko Mitobe, Kazutaka Department of Nursing Akita University Graduate School of Health Sciences 1-1-1 Hondo Akita 010-8543 Japan Department of Mathematical Science and Electrical-Electronic-Computer Engineering Akita University Graduate School of Engineering Science Akita Japan Department of Occupational Therapy Akita University Graduate School of Health Sciences Akita Japan

Although frailty has detrimental physical and psychological effects on elderly people, it is potentially reversible. In this study, we aim to evaluate the effectiveness of a pilot frailty education program implemented through barbershops/salons in Japan. In January 2018, we selected five barbershops/salons in Japan where customers were educated on frailty, which was classified as “normal,” “prefrail,” and “frail.” We developed a web-based assessment tool to reduce the workload for barbers/stylists. Participants included 45 customers (82% women), with a median (interquartile range) age of 53.0 (47.5–57.5) years, and a mean ± SD BMI of 22.3 ± 2.7. Frailty scores indicated that 35% of participants were normal, 58% were prefrail, and 7% were frail. Frailty status scores reflected no significant differences after the intervention. Customers classified as frail were advised to visit the regional comprehensive support center for further professional frailty assessment. Participants, especially those aged over 65 years, found the web-based assessment difficult to use. In conclusion, a frailty education program implemented through barbershops/salons is possible because barbers/stylists can provide information on and assessment of frailty. Females and highly educated customers are more likely to be interested in participating. Nevertheless, a simple intervention is essential to expand the program nationwide. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022.

关键词： Barbershop Frailty Health educator Salon Super-aging society

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Multi-Location and Multi-Feature LMP Forecasting: A 2D Spatiotemporal LSTM-CNN Approach 15

Multi-Location and Multi-Feature LMP Forecasting: A 2D Spati...

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15th International Conference on Power, Energy, and electrical engineering, CPEEE 2025

作者： De Jesus, Noelyn M. Festijo, Enrique D. Apolinario, Gerard Francesco DG. Domingo Lopez, Dylan Josh Graduate School Technological Institute of the Philippines Manila Philippines Technological Institute of the Philippines Electrical Engineering Manila Philippines Chung Yuan Christian University Electrical Engineering and Computer Science Taoyuan Taiwan

ISBN: (纸本)9798331520090

关键词： Electric utilities

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