检索结果-内蒙古大学图书馆

CLEO: Applications and Technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Walden, D. Chakraborty, D. Cheng, J. Straksys, A. Stirke, A. Melo, W.C.M.A. Jukna, A. Komissarov, I. Sobolewski, Roman Department of Physics and Astronomy University of Rochester RochesterNY14627 United States Laboratory for Laser Energetics University of Rochester RochesterNY14623-1299 United States Materials Science Graduate Program University of Rochester RochesterNY14627 United States State Research Institute Center for Physical Sciences & Technology Vilnius Lithuania Department of Physics Vilnius Gediminas Technical University Vilnius Lithuania Department of Electrical and Computer Engineering University of Rochester RochesterNY14627 United States

A novel method has been developed to evaluate the water diffusion dynamics in gelatin-based gels, based on transient terahertz time-domain spectroscopy measurements. Such gels are widely used models for human skin. &#... 详细信息

关键词： Terahertz spectroscopy

来源：评论

学校读者我要写书评

暂无评论

Quantum Kernel-Based Long Short-term Memory

Quantum Kernel-Based Long Short-term Memory

引用

Acoustics, Speech, and Signal Processing Workshops (ICASSPW), IEEE International Conference on

作者： Yu-Chao Hsu Tai-Yu Li Kuan-Cheng Chen National Center for High-Performance Computing NARlabs Hsinchu Taiwan Cross College Elite Program National Cheng Kung University Tainan Taiwan Department of Electrical and Electronic Engineering Imperial College London London UK Centre for Quantum Engineering Science and Technology (QuEST) Imperial College London London UK

ISBN: (数字)9798331519315

ISBN: (纸本)9798331519322

The integration of quantum computing into classical machine learning architectures has emerged as a promising approach to enhance model efficiency and computational capacity. In this work, we introduce the Quantum Kernel-Based Long Short-Term Memory (QK-LSTM) network, which utilizes quantum kernel functions within the classical LSTM framework to capture complex, non-linear patterns in sequential data. By embedding input data into a high-dimensional quantum feature space, the QK-LSTM model reduces the reliance on large parameter sets, achieving effective compression while maintaining accuracy in sequence modeling tasks. This quantum-enhanced architecture demonstrates efficient convergence, robust loss minimization, and model compactness, making it suitable for deployment in edge computing environments and resource-limited quantum devices (especially in the NISQ era). Benchmark comparisons reveal that QK-LSTM achieves performance on par with classical LSTM models, yet with fewer parameters, underscoring its potential to advance quantum machine learning applications in natural language processing and other domains requiring efficient temporal data processing.

关键词： Performance evaluation Quantum computing Computational modeling Computer architecture Signal processing Minimization Data models Natural language processing Speech processing Long short term memory

来源：评论

学校读者我要写书评

暂无评论

Design and exploration of vertically stacked complementary tunneling field-effect transistors

引用

Applied Physics Express 2024年第1期17卷 014001-014001页

作者： Thoti, Narasimhulu Li, Yiming Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Biomedical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

The purpose of this letter is to study the design and explore vertically stacked complementary tunneling field-effect transistors (CTFETs) using CFET technology for emerging technology nodes. As a prior work, the CTFET’s device-level simulations are implemented and deliberated in strict compliance with the experimental settings. This work comprises the study of physical and DC analyses by scaling the p- to n-CTFET separation (D pn), being a significant factor in CFET/CTFET design for its process difficulty. By utilizing the 50% benefit in footprint, the work is further extended to CTFET static random access memory implementation and characterization with hold/read noise margin analysis. © 2023 The Author(s). Published on behalf of The Japan Society of Applied Physics by IOP Publishing Ltd

关键词： Si-Ge alloys

来源：评论

学校读者我要写书评

暂无评论

Computation of homoclinic points using particle swarm optimization in 2-dimensional discrete dynamical systems

Computation of homoclinic points using particle swarm optimi...

引用

International SoC Design Conference, ISOCC

作者： Tatsumi Makino Yuu Miino Haruna Matsushita Takuji Kousaka Department of Electrical and Electronic Engineering Chukyo University Aichi Japan Graduate School of Education Naruto University of Education Tokushima Japan Department of Creative Engineering Kagawa University Kagawa Japan

ISBN: (纸本)9781665459723

This paper proposes the computation of homoclinic points using the particle swarm optimization (PSO) in 2-dimensional discrete dynamical systems. Homoclinic points are a qualitative indicator for the system analysis because their existence guarantees the occurrence of chaos. However, it has been hard to explore the exact homoclinic points because the conventional computation methods need too much precise initial values and so complicated derivatives on the points. In contrast, the PSO requires neither complicated derivatives nor exact initial values. Our method computes the homoclinic points by combining two PSOs without setting the exact initial values. We also conduct a numerical experiment with Hénon map and confirm the validity of the algorithm.

关键词： Chaos Heuristic algorithms Linear programming Particle swarm optimization Dynamical systems System analysis and design

来源：评论

学校读者我要写书评

暂无评论

Real-time Vehicle Detection and Tracking on Fisheye Traffic Monitoring Video in Compressed Domain

引用

APSIPA Transactions on Signal and Information Processing 2023年第4期12卷

作者： Ardianto, Sandy Hang, Hsueh-Ming Cheng, Wen-Huang Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Our goal is to develop real-time vehicle detection and tracking schemes for fisheye traffic monitoring video using the temporal information in the compressed domain without decoding the entire video. Two algorithms are proposed. The first algorithm starts with a conventional single-frame detector, but we introduce a multi-frame information fusion stage to improve the final detection and tracking accuracy, which is implemented using multi-modal bi-directional LSTM (MM bi-LSTM) network. The second algorithm first constructs multi-frame motion trail image, and then a single-image multi-head detector is designed to produce bounding boxes of an individual frame. The first scheme can be viewed as a detect-to-track design, and the second scheme is track-to-detect. We tested our proposals on the ICIP2020 VIP Cup dataset in H.265 video format. The aforementioned algorithms are applied to the motion fields and residual images in the H.265 compressed data set. It turns out that their detection and tracking performances are on par with their pixel-domain counterparts, and they can achieve the state-of-the-art accuracy of conventional video object detectors and trackers. If the decoding process for video compression is not counted, their computational complexities are much lower than the conventional pixel-domain video object detectors and trackers. © 2023 S. Ardianto, H.-M. Hang and W.-H. Cheng.

关键词： Image compression

来源：评论

学校读者我要写书评

暂无评论

Innovative High Step-Up Converter for Improved Photovoltaic Efficiency

Innovative High Step-Up Converter for Improved Photovoltaic ...

引用

IEEE Annual Southern Power electronics Conference (SPEC)

作者： Chun-Hsin Chang Hwa-Dong Liu Chang-Hua Lin Rashid Ahmed Khan Yi-Jie Zeng Undergraduate Program of Vehicle and Energy Engineering National Taiwan Normal University Taipei City Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei City Taiwan Graduate Institute of Green Energy and Sustainable Technology National Taiwan Normal University Taipei City Taiwan

ISBN: (数字)9798350351156

ISBN: (纸本)9798350351163

This study introduces an innovative high step-up (HSU) converter designed for solar photovoltaic systems equipped with a maximum power point (MPP) tracker. This converter efficiently increases the output voltage while maintaining low voltage stress on its components, thanks to a novel combination of primary boost cells, switched capacitors, and voltage multiplier cells. A clamping circuit minimizes leakage energy, enhancing overall efficiency. Testing of a prototype confirmed its effective MPP tracking and high efficiency, with a conversion rate of 20 V-40 V to 380 V at 150 W and efficiencies between 90 % and 96 %.

关键词： Photovoltaic systems Electric potential Renewable energy sources Capacitors Prototypes Voltage Switches Power electronics Stress Testing

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

Multivariate Time-Series Deep Learning for Joint Prediction of Temperature and Relative Humidity in a Closed Space

引用

Procedia Computer Science 2023年 227卷 1046-1053页

作者： Fergianto E. Gunawan Arief S. Budiman Bens Pardamean Endang Juana Sugiarto Romeli Tjeng W. Cenggoro Kartika Purwandari Alam A. Hidayat Anak. A.N.P. Redi Muhammad Asrol Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta 11440 Indonesia PT Impack Pratama Industri Jakarta 14350 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

An accurate predictive model of temperature and humidity plays a vital role in many industrial processes that utilize a closed space such as in agriculture and building management. With the exceptional performance of deep learning on time-series data, developing a predictive temperature and humidity model with deep learning is propitious. In this study, we demonstrated that deep learning models with multivariate time-series data produce remarkable performance for temperature and relative humidity prediction in a closed space. In detail, all deep learning models that we developed in this study achieve almost perfect performance with an R value over 0.99.

关键词： closed space deep learning humity prediction indoor temperature prediction

来源：评论

学校读者我要写书评

暂无评论

Twenty years of e-learning in health science: A bibliometric 7

Twenty years of e-learning in health science: A bibliometric

引用

7th International Conference on Computer Science and Computational Intelligence, CSCI 2022

作者： Maulana, Fairuz Iqbal Febriantono, M. Aldiki Raharja, Dwi Risza Budi Khaeruddin Herasmara, Ridho Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Indonesia Electrical Engineering Faculty of Science and Technology Raden Rahmat Islamic University Malang Indonesia

Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conventionally. Supposedly with the advancement of technology and the use of the internet everywhere, learning such as e-learning can be important, especially in the health sector. Until this research was conducted, only 514 academic documents about e-learning in health sciences were found for 20 years from 2001 to 2020, obtained in searching on the Scopus database. This study presents a comprehensive overview of studies related to E-learning in the Health Sciences sector. This study uses bibliometric analysis and indexed digital methods to map scientific publications throughout the world. This research employs the Scopus database to gather information, as well as the Scopus online analysis tool and Vosviewer to show the bibliometric network. The method consists with five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. Among the most published and indexed articles by Scopus, papers published by researchers in the United States have the highest number of publications (80), followed by United Kingdom (63) and Australia with 45 academic publications. The processed data shows the pattern and trend of increasing the number of international publications in E-learning in Health Sciences field, which Scopus index. © 2022 Elsevier B.V.. All rights reserved.

关键词： Publishing

来源：评论

学校读者我要写书评

暂无评论

Acquisition of EMG Signals for the Analysis of Muscle electrical Activity in High-Performance Athletes: An Experimental Procedure

Acquisition of EMG Signals for the Analysis of Muscle Electr...

引用

Colombian Caribbean Conference (C3), IEEE

作者： Aura Polo Orlando Moreno-Barriga Diego Ayala Julie Viloria-Porto Lácides Antonio Ripoll Solano Lely A. Luengas-C Department of Electrical and Electronic Engineering Universidad del Norte Faculty of Engineering - Universidad del Magdalena Colombia Centro de Investigación de Alto Rendimiento Deportivo y Estudios Biomédicos CIARDEB Universidad del Magdalena Santa Marta Colombia Electronic Engineering Program Faculty of Engineering Universidad del Magdalena Santa Marta Colombia Vicerrectoría de Investigación Universidad del Magdalena Santa Marta Colombia Department of Electrical and Electronic Engineering Universidad del Norte Puerto Colombia Colombia Faculty of Engineering Universidad Distrital Francisco José de Caldas Bogotá Colombia

The present research work describes the experimental process carried out, thanks to the use of surface electromyography (sEMG) for the acquisition of signals from the muscles of high-performance athletes for the analysis of the electrical activity of the muscles in preparation before the university competitions of Colombia. The signals were obtained using a wireless acquisition system based on dry active electrodes when performing a series of exercises focused on the muscles that are involved in controlling the center of gravity of the human body, such as: the rectus femoris, Internal Oblique (IO), External Oblique (EO), and spinal erector. Then, a characterization of the population under study was developed depending on the type of discipline and the exercise used. The results obtained come from the visual inspection and organization of these signals by using basic preprocessing and visualization techniques in MATLAB software. Thus, a compendium is presented with the means of the RMS values and the duration of each muscular activity depending on the type of exercise, showing ranges of values from 0.2-7mV.

关键词：

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：