检索结果-内蒙古大学图书馆

European Conference on Antennas and Propagation, EuCAP

作者： Zhan Chen Wei Hu Yuchen Gao Lehu Wen Qi Luo National Key Laboratory of Antennas and Microwave Technology Xidian University Xi'an China Department of Electronic and Electrical Engineering Brunel University London Uxbridge United Kingdom Engineering and Computer Science School of Physics University of Hertfordshire Hatfield United Kingdom

A novel wideband dual-polarized conformal antenna array with low profile is presented by using dual characteristic modes (CMs) in this paper. First, by utilizing two set of orthogonal CMs that operate at the adjacent bands, a wide impedance bandwidth with dual-polarized operation is achieved in the antenna element design. Then, a columnar surface bending study is performed, leading to the development of a 4×5 cylindrical conformal array. The suggested conformal array exhibits a wide impedance bandwidth of 10.4%, a high polarized isolation of 15.1 dB and a low profile of 1.3mm (0.015λ), under 100-mm (1.16λ) radius of curvature. Such a low-profile wideband dual-polarized conformal antenna array provides an attractive option for contemporary and future communications systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

2021 Monthly Rice Production in Chinese Coastal Provinces 3

2021 Monthly Rice Production in Chinese Coastal Provinces

引用

3rd International Conference on Big Data Analytics and Practices, IBDAP 2022

作者： Parmar, Ajeet Munasinghe, Thilanka Tubbs, Heidi Anyamba, Assaf Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering Troy United States Rensselaer Polytechnic Institute Department of Information Technology and Web Science Troy United States Oak Ridge National Laboratory Geospatial Science and Human Security Division Oak Ridge United States

ISBN: (数字)9781665469388

ISBN: (纸本)9781665469388

This paper explores the dynamics of rice production in the Chinese provinces of Liaoning, Jilin, Heilongjiang, Shanghai, Jiangsu, and Zhejiang and seeks to predict monthly rice production in the months of April through October using precipitation and Normalized Difference Vegetation Index as the predictor variables available. We utilize ridge and lasso regression models to predict the rice yield. Results indicate that a lasso regression model with an R2 value of 0.9991501 with an adjusted R2 value of 0.9991502 and a ridge regression model with an R2 value of 0.9865443 with an adjusted R2 value of 0.9870637 are possible. The lasso regression model does not account for all predictor variables while the ridge regression model does. Both models could be expanded upon to include more observations. © 2022 IEEE.

关键词： Regression analysis

来源：评论

学校读者我要写书评

暂无评论

Sailfish: A Dependency-Aware and Resource Efficient Scheduling for Low Latency in Clouds

Sailfish: A Dependency-Aware and Resource Efficient Scheduli...

引用

IEEE International Conference on Big Data

作者： Jinwei Liu Yingjie Lao Ying Mao Rajkumar Buyya Department of Computer and Information Sciences Florida A&M University Tallahassee FL USA Department of Electrical and Computer Engineering Clemson University Clemson SC USA Department of Computer and Information Science Fordham University Bronx NY USA School of Computing and Information Systems The University of Melbourne Parkville VIC Australia

Efficiently scheduling jobs in clouds is critical for job performance, system throughput and resource utilization. The growing importance of parallel applications in clouds introduces challenges in scheduling data-parallel jobs. Production data-parallel jobs increasingly have complex dependency structure, i.e., complex task dependencies expressed as directed acyclic graphs (DAGs), and heterogeneous resource demands. NP-hard problems are introduced by relaxing either of these challenges (i.e., scheduling of homogeneous tasks with dependency constraints or independent and heterogeneous tasks) for scheduler design. It is challenging to design a scheduler for simultaneously achieving low latency and high resource utilization due to the complex dependency structure and job heterogeneity. In this paper, we propose Sailfish, a dependency-aware and resource efficient scheduling for low latency in clouds. Sailfish first uses the machine learning algorithm to classify jobs into two categories (high priority jobs and low priority jobs) based on the extracted features. Next, Sailfish splits the jobs into tasks and distributes the tasks to the master nodes based on the dependency of tasks and the load of master nodes. Then, Sailfish utilizes the dependency information of tasks to determine tasks’ priority, and packs tasks by leveraging the complementary of tasks’ requirements on different resource types and task dependency. Finally, the master nodes leverage the proposed mutual reinforcement algorithm to distribute tasks to workers in the system based on the resource demands of tasks, the available resources of workers and task dependency. Extensive experimental results based on a real cluster and experiments using real-world Amazon EC2 cloud service show that Sailfish can improve the average resource utilization (by up to 40%) and reduce the latency (the average job completion time) significantly (by up to 91%) compared to the existing schedulers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Enhanced Resource Selection Scheme for Efficient Intra-Platoon Message Delivery

An Enhanced Resource Selection Scheme for Efficient Intra-Pl...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Wang, Bingying Zheng, Jun Li, Cheng Nanjing University of Information Science and Technology School of Electronics and Information Engineering Nanjing210044 China Southeast University National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Simon Fraser University School of Engineering Science BurnabyBCV5A 1S6 Canada Memorial University Department of Electrical and Computer Engineering St. John'sNLA1B 3X5 Canada

ISBN: (纸本)9798350351255

This paper proposes an enhanced resource selection (eInP-RS) scheme for efficient intra-platoon message delivery of cooperative awareness messages (CAMs) and decentralized environmental notification messages (DENMs). To achieve this goal, the eInP-RS scheme allows each vehicle to transmit CAM and DENM packets on a C-V2X channel (CH1) and an 802.11p channel (CH2), separately, and introduces four mechanisms to enhance the standardized sensing-based SPS scheme. A contention window (CW) size adjustment mechanism is introduced to enable a vehicle to adjust its CW size according to the information it collects on CH1 in order to avoid potential packet collisions on CH2;a resource partition mechanism is introduced to divide frequency-time resources in a selection window into two sets in order for vehicles moving in opposite directions to select different resources and thus avoid potential merging collisions on CH1;an intra-platoon cooperation mechanism is introduced to enable the PL of a platoon to know the resource and channel occupation information of the platoon's hidden nodes on CH1 and CH2;and a packet collision detection mechanism is used to enable a non-platoon vehicle to detect packet collisions occurring on both channels after a lane-changing maneuver to avoid potential merging collisions. Simulation results show that the proposed eInP-RS scheme outperforms the standardized sensing-based SPS scheme in terms of the intra-platoon CAM/DENM delivery ratio and the average intra-platoon DENM delivery delay. © 2024 IEEE.

关键词： Magnetic levitation vehicles

来源：评论

学校读者我要写书评

暂无评论

Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-Resolution 27

Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale...

引用

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Xu, Tianyi Zhou, Yijie Hu, Xiaotao Zhang, Kai Zhang, Anran Qiu, Xingye Xu, Jun School of Statistics and Data Science Nankai University Tianjin China College of Computer Science Nankai University Tianjin China School of Intelligence Science and Technology Nanjing University Suzhou China Tencent Data Platform Beijing China Zhejiang University Hangzhou China Systems Engineering Research Institute China State Shipbuilding Corporation Limited Beijing China Guangdong Provincial Key Laboratory of Big Data Computing The Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781643685489

Arbitrary-scale super-resolution (ASSR) aims to learn a single model for image super-resolution at arbitrary magnifying scales. Existing ASSR networks typically comprise an off-the-shelf scale-agnostic feature extractor and an arbitrary scale upsampler. These feature extractors often use fixed network architectures to address different ASSR inference tasks, each of which is characterized by an input image and an upsampling scale. However, this overlooks the difficulty variance of super-resolution on different inference scenarios, where simple images or small SR scales could be resolved with less computational effort than difficult images or large SR scales. To tackle this difficulty variability, in this paper, we propose a Task-Aware Dynamic Transformer (TADT) as an input-adaptive feature extractor for efficient image ASSR. Our TADT consists of a multi-scale feature extraction backbone built upon groups of Multi-Scale Transformer Blocks (MSTBs) and a Task-Aware Routing Controller (TARC). The TARC predicts the inference paths within feature extraction backbone, specifically selecting MSTBs based on the input images and SR scales. The prediction of inference path is guided by a new loss function to trade-off the SR accuracy and efficiency. Experiments demonstrate that, when working with three popular arbitrary-scale upsamplers, our TADT achieves state-of-the-art ASSR performance when compared with mainstream feature extractors, but with relatively fewer computational costs. The code is available at https://***/Tillyhere/TADT. © 2024 The Authors.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Exploring Data Geometry for Continual Learning

arXiv

引用

arXiv 2023年

作者： Gao, Zhi Xu, Chen Li, Feng Jia, Yunde Harandi, Mehrtash Wu, Yuwei Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology China Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen MSU-BIT University China Department of Electrical and Computer Systems Eng. Monash University Data61 Australia

Continual learning aims to efficiently learn from a non-stationary stream of data while avoiding forgetting the knowledge of old data. In many practical applications, data complies with non-Euclidean geometry. As such, the commonly used Euclidean space cannot gracefully capture non-Euclidean geometric structures of data, leading to inferior results. In this paper, we study continual learning from a novel perspective by exploring data geometry for the non-stationary stream of data. Our method dynamically expands the geometry of the underlying space to match growing geometric structures induced by new data, and prevents forgetting by keeping geometric structures of old data into account. In doing so, making use of the mixed curvature space, we propose an incremental search scheme, through which the growing geometric structures are encoded. Then, we introduce an angular-regularization loss and a neighbor-robustness loss to train the model, capable of penalizing the change of global geometric structures and local geometric structures. Experiments show that our method achieves better performance than baseline methods designed in Euclidean space. Copyright © 2023, The Authors. All rights reserved.

关键词： Geometry

来源：评论

学校读者我要写书评

暂无评论

Stabilization and trajectory tracking of a subactuated aircraft based on a Geometric Algebra approach

Stabilization and trajectory tracking of a subactuated aircr...

引用

American Control Conference (ACC)

作者： Leonardo Escamilla Luis Rodolfo Garcia Carrillo Steven Sandoval Eduardo Steed Espinoza Quesada Klipsch School of Electrical and Computer Engineering New Mexico State University Las Cruces NM USA French-Mexican Laboratory of Informatics and Automatic Control Mexico City Mexico

A novel approach to the modeling and control of a subactuated aircraft is performed based on Geometric Algebra (GA) principles. The selected platform for analysis is a quad rotorcraft. The derived model leverages objects from GA, such as the rotor, to perform rotations, replacing the need for Euler angles and quaternions. Controllers, which operate exclusively on GA objects, are developed to regulate the altitude, attitude, and translation of the quad rotorcraft. Numerical examples, including way-point navigation and trajectory tracking, illustrate the feasibility of the GA approach.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation

arXiv

引用

arXiv 2025年

作者： Yu, Yi Xia, Song Lin, Xun Kong, Chenqi Yang, Wenhan Lu, Shijian Tan, Yap-Peng Kot, Alex C. Lab Interdisciplinary Graduate Programme Nanyang Technological University Singapore PengCheng Laboratory Shenzhen China School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Computer Science and Engineering Beihang University Beijing China College of Computing and Data Science Nanyang Technological University Singapore

Adversarial examples, characterized by imperceptible perturbations, pose significant threats to deep neural networks by misleading their predictions. A critical aspect of these examples is their transferability, allowing them to deceive unseen models in black-box scenarios. Despite the widespread exploration of defense methods, including those on transferability, they show limitations: inefficient deployment, ineffective defense, and degraded performance on clean images. In this work, we introduce a novel training paradigm aimed at enhancing robustness against transferable adversarial examples (TAEs) in a more efficient and effective way. We propose a model that exhibits random guessing behavior when presented with clean data x as input, and generates accurate predictions when with triggered data x + τ. Importantly, the trigger τ remains constant for all data instances. We refer to these models as models with trigger activation. We are surprised to find that these models exhibit certain robustness against TAEs. Through the consideration of first-order gradients, we provide a theoretical analysis of this robustness. Moreover, through the joint optimization of the learnable trigger and the model, we achieve improved robustness to transferable attacks. Extensive experiments conducted across diverse datasets, evaluating a variety of attacking methods, underscore the effectiveness and superiority of our approach. Copyright © 2025, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Intelligent Analog Beam Selection and Beamspace Channel Tracking in THz Massive MIMO with Lens Antenna Array

Intelligent Analog Beam Selection and Beamspace Channel Trac...

引用

作者： Zarini, Hosein Mili, Mohammad Robat Rasti, Mehdi Andreev, Sergey Nardelli, Pedro H. J. Bennis, Mehdi Sharif University of Technology Department of Computer Engineering Tehran*** Iran Pasargad Institute for Advanced Innovative Solutions Tehran199163361 Iran Oulu90014 Finland Tampere University Faculty of Information Technology and Communication Sciences Tampere33100 Finland Lappeenranta-Lahti University of Technology School of Energy Systems Department of Electrical Engineering Lappeenranta53850 Finland University of Oulu Center for Wireless Communications Oulu90014 Finland

Beamspace multiple-input-multiple-output (MIMO) as a green technology can efficiently substitute for the conventional massive MIMO, provided that the beamspace channel is acquired precisely. The prior efforts in this area of study, especially the learning-driven ones, however, indicate remarkable performance losses owing to a lack of generalization. In this paper, we propose a modified non-linear auto-regressive exogenous (NARX) model for tracking and predicting the beamspace channel over the sequences of time. Benefiting from bounded generalization error, fast convergence, limited prediction variance, and negligible performance loss, the proposed scheme achieves up to 15% spectral efficiency (SE) gain over its counterparts. We further improve this performance by means of an ensemble learning technique for simultaneously training multiple NARX modules in parallel, thus leading to a 23% SE gain. Relying on the predicted beamspace channel, we propose a beamspace analog beam selection technique through fine-tuning the architecture of a pre-trained off-the-shelf GoogleNet, which brings up to 21% SE gain over similar baselines. With the aid of an ensemble learning technique, it is further indicated numerically that up to 34% SE improvement can be achieved, as compared to the counterparts. © 2015 IEEE.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

Air-to-Ground Communications Beyond 5G: CoMP Handoff Management in UAV Network

arXiv

引用

arXiv 2024年

作者： Li, Yan Guo, Deke Luo, Lailong Xia, Minghua National Key Laboratory of Information Systems Engineering National University of Defense Technology Changsha410073 China The School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China School of Electronics and Information Technology Sun Yat-sen University Guangzhou510006 China

Air-to-ground (A2G) networks, using unmanned aerial vehicles (UAVs) as base stations to serve terrestrial user equipments (UEs), are promising for extending the spatial coverage capability in future communication systems. Coordinated transmission among multiple UAVs significantly improves network coverage and throughput compared to a single UAV transmission. However, implementing coordinated multipoint (CoMP) transmission for UAV mobility requires complex cooperation procedures, regardless of the handoff mechanism involved. This paper designs a novel CoMP transmission strategy that enables terrestrial UEs to achieve reliable and seamless connections with mobile UAVs. Specifically, a computationally efficient CoMP transmission method based on the theory of Poisson-Delaunay triangulation is developed, where an efficient subdivision search strategy for a CoMP UAV set is designed to minimize search overhead by a divide-and-conquer approach. For concrete performance evaluation, the cooperative handoff probability of the typical UE is analyzed, and the coverage probability with handoffs is derived. Simulation results demonstrate that the proposed scheme outperforms the conventional Voronoi scheme with the nearest serving UAV regarding coverage probabilities with handoffs. Moreover, each UE has a fixed and unique serving UAV set to avoid real-time dynamic UAV searching and achieve effective load balancing, significantly reducing system resource costs and enhancing network coverage performance. © 2024, CC BY-NC-SA.

关键词： Triangulation

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：