检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Chen, Wei-Lun Hsieh, Chia-Yeh Kao, Yu-Hsiang Liu, Kai-Chun Peng, Sheng-Yu Tsao, Yu Research Center for Information Technology Innovation Academic Sinica Taiwan Graduate Institute of Electrical Engineering National Taiwan University Taiwan Bachelor’s Program in Medical Informatics and Innovative Applications Fu Jen Catholic University Taiwan Department of Electrical Engineering National Taiwan University Taiwan College of Information and Computer Sciences University of Massachusetts AmherstMA01003 United States Department of Electrical Engineering National Taiwan University of Science of Technology Taiwan

This study presents a novel approach to human keypoint detection in low-resolution thermal images using transfer learning techniques. We introduce the first application of the Timed Up and Go (TUG) test in thermal image computer vision, establishing a new paradigm for mobility assessment. Our method leverages a MobileNetV3-Small encoder and a ViTPose decoder, trained using a composite loss function that balances latent representation alignment and heatmap accuracy. The model was evaluated using the Object Keypoint Similarity (OKS) metric from the COCO Keypoint Detection Challenge. The proposed model achieves better performance with AP, AP50, and AP75 scores of 0.861, 0.942, and 0.887 respectively, outperforming traditional supervised learning approaches like Mask R-CNN and ViTPose-Base. Moreover, our model demonstrates superior computational efficiency in terms of parameter count and FLOPS. This research lays a solid foundation for future clinical applications of thermal imaging in mobility assessment and rehabilitation monitoring. Copyright © 2025, The Authors. All rights reserved.

关键词： Thermography (imaging)

来源：评论

学校读者我要写书评

暂无评论

The growing memristor industry

引用

Nature 2025年第8059期640卷 613-622页

作者： Lanza, Mario Pazos, Sebastian Aguirre, Fernando Sebastian, Abu Le Gallo, Manuel Alam, Syed M. Ikegawa, Sumio Yang, J. Joshua Vianello, Elisa Chang, Meng-Fan Molas, Gabriel Naveh, Ishai Ielmini, Daniele Liu, Ming Roldan, Juan B. Department of Materials Science and Engineering National University of Singapore Singapore Singapore Institute for Functional Intelligent Materials National University of Singapore Singapore Singapore Centre for Advanced 2D Materials (CA2DM) National University of Singapore Singapore Singapore Materials Science and Engineering Program Physical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Intrinsic Semiconductor Technologies London United Kingdom IBM Research – Zurich Rüschlikon Switzerland Everspin Technologies Chandler AZ United States Department of Electrical and Computer Engineering University of Southern California Los Angeles CA United States CEA-Leti Université Grenoble Alpes Grenoble France Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan Weebit Nano Hod Hasharon Israel Dipartimento di Elettronica Informazione e Bioingegneria (DEIB) Politecnico di Milano and *** Milano Italy Key Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing China Departamento de Electrónica y Tecnología de Computadores Universidad de Granada Facultad de Ciencias Granada Spain

The semiconductor industry is experiencing an accelerated transformation to overcome the scaling limits of the transistor and to adapt to new requirements in terms of data storage and computation, especially driven by artificial intelligence applications and the Internet of Things. In this process, new materials, devices, integration strategies and system architectures are being developed and optimized. Among them, memristive devices and circuits—memristors are two-terminal memory devices that can also mimic some basic bioelectronic functions—offer a potential approach to create more compact, energy-efficient or better-performing systems. The memristor industry is growing quickly, raising abundant capital investment, creating new jobs and placing advanced products in the market. Here we analyse the status and prospects of the memristor industry, focusing on memristor-based products that are already commercially available, prototypes with a high technological readiness level that might affect the market in the near future, and discuss obstacles and pathways to their implementation. © Springer Nature Limited 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Probabilistic genotype-phenotype maps reveal mutational robustness of RNA folding, spin glasses, and quantum circuits

引用

Physical Review Research 2025年第1期7卷 013118-013118页

作者： Anna Sappington Vaibhav Mohanty Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Harvard-MIT Program in Health Sciences and Technology Harvard Medical School Boston Massachusetts 02115 USA and Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Harvard/MIT MD-PhD Program Harvard Medical School Boston Massachusetts 02115 USA and Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Chemistry and Chemical Biology Harvard University Cambridge Massachusetts 02138 USA

Recent studies of genotype-phenotype maps have reported universally enhanced phenotypic robustness to genotype mutations, a feature essential to evolution. Virtually all of these studies make a simplifying assumption that each genotype—represented as a sequence—maps deterministically to a single phenotype, such as a discrete structure. Here we introduce probabilistic genotype-phenotype (PrGP) maps, where each genotype maps to a vector of phenotype probabilities, as a more realistic and universal language for investigating robustness in a variety of physical, biological, and computational systems. We study three model systems to show that PrGP maps offer a generalized framework which can handle uncertainty emerging from various physical sources: (1) thermal fluctuation in RNA folding, (2) external field disorder in the spin-glass ground state search problem, and (3) superposition and entanglement in quantum circuits, which are realized experimentally on IBM quantum computers. In all three cases, we observe a biphasic robustness scaling which is enhanced relative to random expectation for more frequent phenotypes and approaches random expectation for less frequent phenotypes. We derive an analytical theory for the behavior of PrGP robustness, and we demonstrate that the theory is highly predictive of empirical robustness.

关键词： Quantum computers

来源：评论

学校读者我要写书评

暂无评论

Role of high energy photons in dual spectral source rapid isothermal CVD

引用

JOURNAL OF ELECTRONIC MATERIALS 1997年第10期26卷 1184-1188页

作者： Singh, R Chen, Y Department of Electrical and Computer Engineering Material Science and Engineering Program Clemson University Clemson Department of Electrical and Computer Engineering Clemson University Clemson

The use of tungsten halogen lamps and the deuterium lamp as the source of thermal and optical energies has been exploited to deposit thin films of Ta2O5 on Si and conducting substrates, The leakage current densities are as low as 10(-10) A/cm(2) for gate voltage under 5V. Photons in visible, ultraviolet, and vacuum ultraviolet (lambda < 800 nm) regions provide higher bulk and surface diffusion coefficients as well as reduced activation energy for the chemical process involved in the chemical vapor deposition process. The low thermal mass of the substrate provides limited reaction processing capability. The photochemical and photophysical processes allow the participating atoms and molecules to adjust their bond geometries and occupy sites which result in overall reduction of stress and strain energy and provide materials with overall low microscopic defects at low processing temperature and with high throughput. New experimental results of Al-Ta2O5-Si3N4-poly Si-Al structure are presented. The leakage current-voltage characteristics are better than those reported by other researchers.

关键词： dielectrics metalorganic chemical vapor deposition (MOCVD) rapid isothermal processing (RIP) Ta2O5

来源：评论

学校读者我要写书评

暂无评论

DESCRIPTION AND PERFORMANCE OF A FIBEROPTIC CONFOCAL FLUORESCENCE SPECTROMETER

引用

APPLIED SPECTROSCOPY 1994年第3期48卷 350-355页

作者： RICHARDSKORTUM, R DURKIN, A ZENG, J Biomedical Engineering Program Department of Electrical and Computer Engineering University of Texas at Austin Austin Texas 78712

We describe a fiber-optic-based confocal fluorescence spectrometer for obtaining depth-resolved, attenuated fluorescence emission spectra with lateral resolution of several microns and depth resolution of tens of microns. The confocal optics of the spectrometer are small, inexpensive, and easy to construct and to interface to existing spectrometers. We compare the performance of this system to that of conventional fluorescence spectrometers for nonscattering homogeneous and inhomogeneous samples. We demonstrate that the confocal measurements readily provide information about the sample geometry and optical properties not available from nonconfocal measurements. Potential applications of the technique are discussed.

关键词： FLUORESCENCE SPECTROSCOPY CONFOCAL FIBER OPTIC

来源：评论

学校读者我要写书评

暂无评论

ACOUSTIC TRANSMISSION OF THE RESPIRATORY SYSTEM USING SPEECH STIMULATION

引用

IEEE TRANSACTIONS ON BIOMEDICAL engineering 1991年第2期38卷 126-132页

作者： COHEN, A BERSTEIN, AD Department of Electrical and Computer Engineering Biomedical Engineering Program Ben-Gurion University of the Negev Beersheba Israel

Two methods for the analysis of the acoustic transmission of the respiratory system are presented. Continuous speech utterance is used as acoustic stimulation. The transmitted acoustic signal is recorded from various sites over the chest wall. The AR method analyzes the power spectral density function of the transmitted sound, which heavily depends on the microphone assembly and the utterance. The method was applied to a screening problem and was tested on a small database that consisted of 19 normal and five abnormal patients. Using the first five AR coefficients and the prediction error of an AR(10) model, as discriminating features, the system screened all abnormals. An ARMA method is suggested, which eliminates the dependence on microphone and utterance. In this method, the generalized least squares identification algorithm is used to estimate the ARMA transfer function of the respiratory system. The normal transfer function demonstrates a peak at the range of 130-250 Hz and sharp decrease in gain for higher frequencies. A pulmonary fibrotic patient demonstrated a peak at the same frequency range, a much higher gain in the high frequency range with an additional peak at about 700 Hz.

关键词： Microphone Device Component Error of prediction frequency ranges Respiratory System Thoracic Wall power spectral density function TRANSFER FUNCTIONS sound transmission

来源：评论

学校读者我要写书评

暂无评论

Molecular architecture of mammalian pyruvate dehydrogenase complex

引用

Protein & Cell 2025年第1期16卷 72-78页

作者： Maofei Chen Yutong Song Sensen Zhang Yitang Zhang Xudong Chen Minghui Zhang Meng Han Xin Gao Sai Li Maojun Yang Tsinghua-Peking Center for Life Sciences Beijing Frontier Research Center for Biological StructureSchool of Life SciencesTsinghua UniversityBeijing 100084China Ministry of Education Key Laboratory of Protein Science Tsinghua UniversityBeijing 100084China State Key Laboratory of Membrane Biology Tsinghua UniversityBeijing 100084China Department of Biochemistry and Molecular Biology School of Basic Medical SciencesShenzhen University Health Science CenterShenzhen 518060China Protein Research Technology Center Protein Chemistry and Omics PlatformSchool of Life SciencesTsinghua UniversityBeijing 100084China Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Computational Bioscience Research Center King Abdullah University of Science and TechnologyThuwal 23955-6900Kingdom of Saudi Arabia Cryo-EM Facility Center Southern University of Science and TechnologyShenzhen 518055China Beijing Life Science Academy Beijing 102209China

Dear Editor,Pyruvate dehydrogenase complex(PDHc) is a large multienzyme assembly(Mr = 4–10 million Daltons) consisting of three essential components: pyruvate dehydrogenase(E1p), dihydrolipoyl transacetylase(E2p), and dihydrolipoyl dehydrogenase(E3). These three enzymes perform distinct functions sequentially to catalyze the oxidative decarboxylation of pyruvate with formation of nicotinamide adenine dinucleotide(NADH) and acetyl-coenzyme A(Patel and Roche, 1990).

关键词： sequentially oxidative Dalton

来源：评论

学校读者我要写书评

暂无评论

Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using a Deep Learning Approach

Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using ...

引用

International Symposium on Applied Science 2024, ISAS 2024

作者： Raza, Aquib Ching, Congo Tak Shing Liu, Peng-Ta Phan, Thien-Luan Tran, Ngoc-Luan Nguyen, Ha Anh T. Rameez, Mohammad Li, Hung-Chung Linh, Dao Nguyen Phuong Van Hieu, Nguyen Tran, Trung Nghia National Taiwan University Taipei City10673 Taiwan Research Center for Information Technology Academia Sinica Taipei City11529 Taiwan Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung402 Taiwan Department of Electrical Engineering National Chi Nan University Nantou County Taiwan Advanced Plant and Food Crop Biotechnology Center National Chung Hsing University Taichung402 Taiwan International Doctoral Program in Agriculture National Chung Hsing University Taichung402 Taiwan Fall Prevention Center Department of Physical Medicine & Rehabilitation Changhua Christian Hospital Changhua500 Taiwan Department of Physics and Electronic Engineering University of Science Vietnam National University - Ho Chi Minh City Ho Chi Minh City70000 Viet Nam Department of Computer Science University of York York HeslingtonYO10 5DD United Kingdom Undergraduate Program of Intellectual Creativity Engineering National Chung Hsing University Taichung402 Taiwan Ho Chi Minh City72409 Viet Nam HCMUT Vietnam National University Ho Chi Minh City Thu Duc Ho Chi Minh City71308 Viet Nam

This research introduces a deep learning framework that combines convolutional neural networks with autoencoders to improve the diagnostic accuracy of knee osteoarthritis. The study utilized a publicly available dataset from the Mendeley Data repository, where knee joint images were preprocessed using Contrast Limited Adaptive Histogram Equalization to enhance contrast and ensure consistent image sizing. Initially, an autoencoder was employed in an unsupervised manner to learn compressed representations of the data. These representations were then used to train a CNN to classify knee images into 'healthy' and 'osteoarthritic' categories. The model was trained using an 80:20 split for training and testing data, incorporating early stopping and data augmentation techniques to prevent overfitting and enhance generalization. Performance metrics such as accuracy, precision, recall, and the area under the Receiver Operating Characteristic curve (ROCAUC) were used to evaluate the model, resulting in a high test accuracy of 98.95%. The high precision and recall rates further confirmed the model's robustness in diagnosing KOA. To enhance interpretability, Gradient-weighted Class Activation Mapping (Grad-CAM) was applied to identify critical regions in the images that influenced the model's decisions. Additionally, t-Distributed Stochastic Neighbor Embedding (t-SNE) was used to visualize the high-dimensional encoded features in a two-dimensional space, providing deeper insights into how the model differentiates between classes. The promising results of this deep learning approach suggest its potential for broader applications in medical imaging diagnostics. By providing healthcare professionals with a tool that enhances diagnostic accuracy and operational efficiency, this framework lays the foundation for developing scalable, AI-driven diagnostic systems for various complex medical conditions. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Joints (anatomy)

来源：评论

学校读者我要写书评

暂无评论

Fiber optic SERS sensors for rapid detection and identification of Salmonella in turkey products 25

Fiber optic SERS sensors for rapid detection and identificat...

引用

Optical Fibers and Sensors for Medical Diagnostics, Treatment, and Environmental Applications XXV 2025

作者： Abuhelwa, Mai Chenggeer, Fnu Bandara, Adheesha Liu, Jiayu Willoughby, Paige Carlson, Anna Trout, Kate E. Morey, Amit Kinzel, Ed Mustapha, Azlin Almasri, Mahmoud Department of Electrical Engineering and Computer Science University of Missouri ColumbiaMO65211 United States Food Science Program University of Missouri ColumbiaMO65211 United States Cargill Inc WichitaKS67202 United States College of Health Sciences University of Missouri ColumbiaMO65211 United States Department of Poultry Science Auburn University AuburnAL36849 United States University of Notre Dame IN46556 United States

ISBN: (纸本)9781510683686

This study validates a fiber optics-based Surface Enhanced Raman Spectroscopy (SERS) sensor for detecting Salmonella in raw turkey samples. The sensor uses nanoantenna arrays on a side-polished optical fiber core with a fixed periodicity of 0.77 μm to maximize the SERS signal intensity. A 3D-printed chamber and microstructure optimize light reflection, improving sensitivity. The sensor detects Salmonella at 0.4-0.5 CFU/ml in 10 minutes, offering cost-effective, portable pathogen detection. © 2025 SPIE.

关键词： Multimode fibers

来源：评论

学校读者我要写书评

暂无评论

A Multi-Step Multivariate Fuzzy-based Time Series Forecasting on Internet of Things Data

引用

IEEE Internet of Things Journal 2025年

作者： Bitencourt, Hugo Vinicius Lucas, Patri-Cia de Oliveira Orang, Omid Silva, Petronio C. L. Guimaraes, Frederico Gadelha Universidade Federal de Minas Gerais -UFMG Graduate Program in Electrical Engineering MG Belo Horizonte31270-901 Brazil Federal Institute of Northern Minas Gerais IFNMG MG Salinas Brazil Universidade Federal de Minas Gerais -UFMG Computer Science MG Belo Horizonte31270-901 Brazil Federal Institute of Northern Minas Gerais IFNMG MG Januaria Brazil Universidade Federal de Minas Gerais -UFMG Department of Computer Science MG Belo Horizonte Brazil

Multi-step ahead time series forecasting is essential in Internet of Things (IoT) applications in smart cities and smart homes to make accurate future predictions and precise decision-making. Thus, this study introduces a novel multiple-input single-output (MISO) forecasting method called Multi-Step Embedding-based Fuzzy Time Series (MS-EFTS), designed to predict high-dimensional non-stationary time series data. As a first-order approach, it employs a direct strategy that integrates an embedding transformation with a weighted multivariate FTS (WMVFTS) model. This combination allows for effective predictions over long-term horizons within low-dimensional, learned continuous representations. The effectiveness of the proposed MS-EFTS is assessed using three high-dimensional IoT time series in this investigation. The obtained results showcase the superior performance of the proposed method compared to some deep learning forecasting methods, including LSTM, BiLSTM, TCN, and CNN-LSTM, in terms of accuracy, parsimony, and efficiency. © 2014 IEEE.

关键词： Smart homes

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：