检索结果-内蒙古大学图书馆

Communications and Networking (MeditCom), IEEE International Mediterranean Conference on

作者： Tanin Sultana Sorina Dumitrescu Dept. of Electrical and Computer Engineering McMaster University Hamilton Canada

ISBN: (数字)9798350309485

ISBN: (纸本)9798350309492

This work considers a downlink hybrid NOMAOMA multiuser transmission system that divides users into pairs, each pair sharing one channel using Non-Orthogonal Multiple Access (NOMA), while different pairs are assigned orthogonal channels using Orthogonal Multiple Access (OMA). To achieve high system efficiency while guaranteeing fairness, we propose a joint power and channel allocation framework with the proportional fairness objective, which maximizes the sum of logarithmic rates. The problem is decoupled into the power allocation (PA) and channel assignment (CA) subproblems, which are solved iteratively. Our main contribution is proposing a globally optimal solution algorithm for the CA subproblem, which is obtained by casting the problem as a bipartite graph matching problem. We show empirically that the proposed joint PA-CA solution performs very close to the exhaustive search for small numbers of users. Extensive experiments demonstrate that the proposed framework significantly outperforms several benchmark schemes in both system efficiency and fairness. Index Terms-NOMA, joint channel and power allocation, proportional fairness, sum of logarithmic rates, bipartite graph matching.

关键词： NOMA Casting Channel allocation Benchmark testing Downlink Search problems Hybrid power systems

来源：评论

学校读者我要写书评

暂无评论

A superconducting full-wave bridge rectifier

arXiv

引用

arXiv 2024年

作者： Castellani, Matteo Medeiros, Owen Buzzi, Alessandro Foster, Reed A. Colangelo, Marco Berggren, Karl K. Dept. of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States

Superconducting thin-film electronics are attractive for their low power consumption, fast operating speeds, and ease of interface with cryogenic systems such as single-photon detector arrays, and quantum computing devices. However, the lack of a reliable superconducting two-terminal asymmetric device, analogous to a semiconducting diode, limits the development of power-handling circuits, fundamental for scaling up these technologies. Existing efforts to date have been limited to single-diode proofs of principle and lacked integration of multiple controllable and reproducible devices to form complex circuits. Here, we demonstrate a robust superconducting diode with tunable polarity using the asymmetric vortex surface barrier in niobium nitride micro-bridges, achieving a 43 % peak rectification efficiency, and showing half-wave rectification up to 120 MHz. We then realize and integrate several such diodes into a bridge rectifier circuit on a single microchip that performs continuous full-wave rectification up to 3 MHz and AC-to-DC conversion of a 50 MHz signal in periodic bursts with an estimated peak power efficiency of 50 %. © 2024, CC BY.

关键词： Quantum computers

来源：评论

学校读者我要写书评

暂无评论

Optimizing 3D Flight Paths for Multiple UAVs with Connectivity Management in Urban Delivery Systems 19

Optimizing 3D Flight Paths for Multiple UAVs with Connectivi...

引用

19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Lee, Yeongmin Syahran, Raihan Muhammad Spangenberger, Mael Yang, Huigyu Oh, Jiyong Choo, Hyunseung Dept. of Artificial Intelligence Sungkyunkwan University Suwon Korea Republic of Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of Convergence Research Institute Sungkyunkwan University Suwon Korea Republic of Dept. of AI Systems Engineering Sungkyunkwan University Suwon Korea Republic of Dept. of Informatics Télécom SudParis Évry France

ISBN: (纸本)9798331507817

The dynamic deployment of aerial vehicles in urban delivery scenarios demands precise route planning, reliable data links, and efficient use of network infrastructure. Although prior efforts have explored various aspects of unmanned navigation or communication optimization, existing approaches often overlook the combined impact of three-dimensional path selection and robust connectivity maintenance. To address this gap, this paper proposes a deep reinforcement learning framework employing Independent Proximal Policy Optimization (IPPO) to steer the flight paths of unmanned vehicles while curtailing needless interactions with base stations (BSs). By incorporating communication-specific metrics, Reference Signal Received Power (RSRP), the proposed system adapts to urban conditions and upholds resilient network links. Comprehensive performance evaluations reveal the potential of the framework to reduce excessive BS connections by up to 82.24%, preserve RSRP levels above -80 dBm, and balance handover frequencies across flight trajectories. These findings affirm the scalability and effectiveness of the method for achieving efficient aerial navigation and consistent communication in urban delivery services. © 2025 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

A Novel Method to Detect Oral Carcinoma Using Box Annotation Based on YOLO Model

A Novel Method to Detect Oral Carcinoma Using Box Annotation...

引用

Advances in Computing,Communication, electrical, and Smart Systems (iCACCESS), International Conference on

作者： Shahara Laila Romana Rahman Ema Syed Md. Galib Abu Rafe Md Jamil A F M Shahab Uddin Dept. of Computer Science and Engineering Jashore University of Science and Technology Jashore Bangladesh Dept. of Computer Science and Engineering Jashore University of Science and Technolgy Jashore Bangladesh

Oral carcinoma affects millions of individuals globally and is a major public health problem due to its high fatality rate. Treatment effectiveness depends on early detection and improves survival rates. An effective method for automated oral cancer screening is deep learning. The paper's primary goal is to use deep learning techniques to advance the state of oral cancer diagnosis, specifically YOLOv5 and YOLOv7. We aimed to achieve accurate detection by leveraging bounding box annotations for both two distinct types of data: collected clinical data and benchmark data of oral carcinoma. The proposed methodology encompasses data collection, preprocessing, expert-driven bounding box annotation and the use of cutting-edge deep learning models for lesion identification, YOLOv5 and YOLOv7. Bounding box serving as expert annotations are meticulously added to pinpoint cancerous regions within the images. Subsequently, a comprehensive evaluation is conducted, measuring the performance of both models based on precision, recall rate (sensitivity) and mean average precision (mAP). Our findings reveal that YOLOv5 outperforms YOLOv7 in terms of oral cancer detection, demonstrating superior precision and recall rates. In the evaluation of this research, the YOLOv5 model demonstrated strong performance metrics on both clinical and lip and tongue cancer datasets. For the lip and tongue cancer dataset, the YOLOv5 model achieved a precision of 97.2%, a mAP (mean Average Precision) of 97.7% and a recall of 96.3%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improvement Accuracy Identification and Learning Speed of Offline Signatures Based on SqueezeNet with ADAM Backpropagation 9

Improvement Accuracy Identification and Learning Speed of Of...

引用

9th International Conference on Information Technology, computer and electrical engineering, ICITACEE 2022

作者： Purbanugraha, Yosepin Petra Rochim, Adian Fatchur Setiawan, Iwan Universitas Diponegoro Dept. of Electrical Engineering Semarang50275 Indonesia Universitas Diponegoro Dept. of Computer Engineering Semarang50275 Indonesia

ISBN: (数字)9781665471503

ISBN: (纸本)9781665471480

Signatures play an essential role in human life because they are used as an authentication approach in organizations such as banks, businesses, and legal authorities. In offline signature identification, dynamic information such as velocity of the stroke, hand vibration, signature image position and pen pressure from the signature writing process is lost, so offline analysis has less information and as a result the identification becomes more complicated. Currently, from various websites, there are many electronic documents that contain offline signatures. This leads to the problem of offline signature identification. Offline signature identification can be viewed as part of the Fine-Grained Visual Classification (FGVC) problem. FGVC research is a challenge because there are problems with fine-grained datasets and it can quickly become a big problem due to factors such as angle of view, tilt, and the location of objects in the image. In recent years, Convolutional Neural Networks (CNN) are a powerful and very successful approach for identification purposes. In this research, a CNN with small networks architecture namely SqueezeNet is optimized using Adaptive Moment Estimation (ADAM) to achieves high accuracy and learning speed, it is trained using four public signature datasets, namely BHSig260-Bengali, BHSig260-Hindi, CEDAR, UTSig and then it is tested to identify the original signature samples taken from each dataset. The optimized SqueezeNet achieves better results compared with other deep learning or machine learning algorithms. The optimized SqueezeNet takes under 3 minutes to train networks for each dataset and its identification average accuracy reaches above 99,79% for each dataset. © 2022 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

A Room Temperature Compensated Lateral Field Excited Lithium Tantalate Sensor Platform

A Room Temperature Compensated Lateral Field Excited Lithium...

引用

2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Trusty, Yuri Khmeleva, Ekaterina McGann, Jason Hartz, Jequil Emanetoglu, Nuri Vetelino, John University of Maine Dept. of Electrical and Computer Engineering OronoME United States University of Washington Bothell Dept. of Physics BothellWA United States University of Maine Dept. of Mechanical Engineering OronoME United States

ISBN: (纸本)9798350346459

The quartz crystal monitor (QCM) is a common sensor platform based on the room temperature compensated pure shear mode (PSM) of thickness field excited (TFE) AT-cut quartz. However, with electrodes on both crystal faces, TFE only allows sensing of mechanical property changes. Lateral field excitation (LFE), where both electrodes are on a single face, enables the detection of both mechanical and electrical changes, potentially leading to higher sensitivity. As lithium tantalate (LT) has an LFE PSM and piezoelectric coupling several times greater than that of quartz, LFE LT was chosen as a possible replacement for TFE quartz. A theoretical search of all LT cuts identified those exhibiting a room temperature compensated PSM. A set of orientations ranging from (YXwl) 0°/-85° to 0°/-90° was chosen for experimental verification. The temperature response of each sample was shown to be parabolic, with a roughly linear relationship between crystal cut angle and temperature inflection point/turnaround temperature. Specifically, the (YXwl) 0°/-87° cut with a turnaround temperature at 26.4°C demonstrates that a room temperature PSM in LT can be excited via LFE. Future work focusing on the development of an LT sensing platform could profoundly impact sensor systems in agriculture, homeland security, global warming, and medical applications. © 2023 IEEE.

关键词： Electrodes

来源：评论

学校读者我要写书评

暂无评论

S-Band Active Circulator with Reactive Load Tuning for Isolation Recovery

S-Band Active Circulator with Reactive Load Tuning for Isola...

引用

IEEE Annual Conference on Wireless and Microwave Technology (WAMICON)

作者： Laila Marzall Marcus Wolff Sofia Mvokany Zoya Popović Dept. of Electrical Computer Engineering University of Colorado Boulder Boulder USA

ISBN: (数字)9798331509606

ISBN: (纸本)9798331509613

This work presents a $3.4-\text{GHz}$ gallium nitride (GaN) active circulator with independently tunable reactive loads, which can compensate for impedance mismatch and maintain isolation that results from phased array scan impedance. Simulated results demonstrate isolation improvements of 13.4, 10.5, 19.7 and 31.8 dB for $|\Gamma|$ mismatches of $0.2\left(\theta=180^{\circ}\right.$ and $\left.\theta=270^{\circ}\right)$ and 0.3 $(\theta=0^{\circ}$ and $\theta=90^{\circ})$ , respectively. This concept shows promise for application in full duplex phased array front ends, where high isolation is critical.

关键词： Phased arrays Wireless communication Simulation Circulators Couplers Reflection Reflection coefficient Impedance Gallium nitride Tuning

来源：评论

学校读者我要写书评

暂无评论

Low-Power and Superior Performance Design of Ternary Logic Cells Using CNFET and MOSFET Devices for VLSI Applications

Low-Power and Superior Performance Design of Ternary Logic C...

引用

International Conference on VLSI Design

作者： Siva Chinmai Varma Bhupathiraju Sridhara Sai Krishna Yashwanth Komuravelly Ramakant Yadav Dept. of Electrical and Computer Engineering Mahindra University Hyderabad Telangana India

ISBN: (数字)9798331522445

ISBN: (纸本)9798331522452

This work explores the implementation of ternary logic using novel devices, particularly Carbon Nanotube Field Effect Transistors (CNFETs). CNFETs leverage single-walled carbon nanotubes as conducting channels, and by adjusting the diameter of the carbon nanotubes, we can control the device's threshold voltage. This characteristic makes CNFETs well-suited for ternary logic, as we can easily create Low Voltage Threshold (LVT) and High Voltage Threshold (HVT) devices required for implementing ternary logic. Optimized MOSFET and CNFET, N, and P-channel devices are benchmarked and compared at 45 nm technology node. Furthermore, we present the design and functionality of ternary inverters using both MOSFETs and CNFETs, including Negative Ternary Inverter (NTI), Positive Ternary Inverter (PTI), and Standard Ternary Inverter (STI). The performance of all the logic cells mentioned in the paper was benchmarked and it is observed that CNFET ternary cells have lower PDP compared to MOSFET ternary cells. A decrease of 23.78% and 20.78% in PDP is observed for NTI and PTI logic cells, respectively, and a decrease of 29.65% and 29.35% is observed for STI 1 and STI 2 logic cells, respectively.

关键词： Semiconductor device modeling Performance evaluation MOSFET Very large scale integration Carbon nanotubes Multivalued logic CMOS technology Inverters CNTFETs Delays

来源：评论

学校读者我要写书评

暂无评论

Alzheimers Disease Detection through LASSO and RFE based Feature Selection from EEG Data

Alzheimers Disease Detection through LASSO and RFE based Fea...

引用

IEEE International Conference on Biomedical engineering, computer and Information Technology for Health

作者： Zahrul Jannat Peya Nurzahan Akter Joly Md. Sharzul Mostafa Sharmina Al-Azad Md. Shymon Islam Sk. Ahadul Alam Dept. of Computer Science and Engineering North Western University Khulna Bangladesh Dept. of Computer Science and Engineering Khulna University of Engineering & Technology Khulna Bangladesh

ISBN: (数字)9798331534356

ISBN: (纸本)9798331534363

Alzheimer’s disease is a progressive neurological condition that affects memory, cognition, and basic daily functions, with symptoms typically appearing later in life. This study aims to develop a reliable, non-invasive method for early detection of Alzheimer’s using electroencephalogram (EEG) data. Given the absence of a cure, precise diagnostic tools are crucial. EEG is an affordable and non-invasive alternative, particularly beneficial for disadvantaged populations. Our approach focuses on improving early diagnosis, monitoring disease progression, and providing individualized care. Using Recursive Feature Elimination and Lasso for feature selection, we classified EEG data with machine learning algorithms (Random Forest, Support Vector Machine, and Decision Tree), with Random Forest achieving the highest accuracy of 95.45%.

关键词： Support vector machines Accuracy Machine learning algorithms Feature extraction Electroencephalography Decision trees Reliability Alzheimer's disease Random forests Monitoring

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Diverse Classification Algorithms of Machine Learning by Using Various Quality Metrics 5

Comparative Analysis of Diverse Classification Algorithms of...

引用

5th IEEE International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2023

作者： Kathiresan, V. Dinesh, G. Sarveshwaran, Velliangiri Jayakanth, J.J. Kiruthika, M. Remu, Yuvaraj GITAM University Dept. of Computer Science and Engineering Bengaluru Karnataka India SRM Institute of Science and Technology Department of Computational Intelligence Kattankulathur India

ISBN: (纸本)9798350338287

Machine learning classification algorithms and their applications are becoming increasingly popular in today's era of information science. Choosing an algorithm that is appropriate for the problem and application is a challenging task. The quality of the prediction model is significantly influenced by selecting the right algorithm. The purpose of the study and comparative analysis highlights the benefits and drawbacks of various classification algorithms from all perspectives. The Machine Learning (ML) based classification algorithms such as Logistic Regression (LR), K-Nearest Neighbour(KNN), DT (Decision Tree), SVM (Support Vector Machine), and Naïve Bayes (NB) are assessed for comparative analysis. These algorithms were tested and analysed using various datasets acquired and used from the UCIML repository. Algorithms are evaluated using well-established effective measures for accuracy, recall, and precision. A variety of datasets are used to monitor, measure, and compare each algorithm's performance in terms of metrics. Each algorithm's effectiveness and efficacy are analysed and compared from all aspects. Based on overall performance, the algorithms are ranked in the following order: logistic regression, decision tree, SVM, KNN, and Nave Bayes. © 2023 IEEE.

关键词： Decision trees

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：