检索结果-内蒙古大学图书馆

An evaluation of lightweight deep learning techniques in medical imaging for high precision COVID-19 diagnostics

Healthcare Analytics 2022年 2卷 100096-100096页

作者： Ukwandu, Ogechukwu Hindy, Hanan Ukwandu, Elochukwu Department of Computer Communication and Information Systems School of Engineering and Built Environment Glasgow Caledonian University United Kingdom Computer Science Department Faculty of Computer and Information Sciences Ain Shams University Cairo 11566 Egypt Department of Applied Computing and Engineering Cardiff School of Technologies Cardiff Metropolitan University Cardiff CF5 2YB United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom

Timely and rapid diagnoses are core to informing on optimum interventions that curb the spread of COVID-19. The use of medical images such as chest X-rays and CTs has been advocated to supplement the Reverse-Transcription Polymerase Chain Reaction (RT-PCR) test, which in turn has stimulated the application of deep learning techniques in the development of automated systems for the detection of infections. Decision support systems relax the challenges inherent to the physical examination of images, which is both time consuming and requires interpretation by highly trained clinicians. A review of relevant reported studies to date shows that most deep learning algorithms utilised approaches are not amenable to implementation on resource-constrained devices. Given the rate of infections is increasing, rapid, trusted diagnoses are a central tool in the management of the spread, mandating a need for a low-cost and mobile point-of-care detection systems, especially for middle- and low-income nations. The paper presents the development and evaluation of the performance of lightweight deep learning technique for the detection of COVID-19 using the MobileNetV2 model. Results demonstrate that the performance of the lightweight deep learning model is competitive with respect to heavyweight models but delivers a significant increase in the efficiency of deployment, notably in the lowering of the cost and memory requirements of computing resources. © 2022 The Author(s)

关键词： COVID-19 detection Diagnostic analytics Lightweight deep learning techniques Machine learning Point-of-care Resource-constrained devices

来源：评论

学校读者我要写书评

暂无评论

Joint Beam Scheduling and Resource Allocation for Flexible RSMA-aided Near-Field Communications

arXiv

引用

arXiv 2024年

作者： Zhou, Jiasi Zhou, Cong Mao, Yijie Tellambura, Chintha School of Medical Information and Engineering Xuzhou Medical University Xuzhou221004 China School of Electronic and Information Engineering Harbin Institute of Technology Harbin150001 China School of Information Science and Technology Shanghai Tech University Shanghai201210 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada

Supporting immense throughput and ubiquitous connectivity holds paramount importance for future wireless networks. To this end, this letter focuses on how the spatial beams configured for legacy near-field (NF) users can be leveraged to serve extra NF or far-field users while ensuring the rate requirements of legacy NF users. In particular, a flexible rate splitting multiple access (RSMA) scheme is proposed to efficiently manage interference, which carefully selects a subset of legacy users to decode the common stream. Beam scheduling, power allocation, common rate allocation, and user selection are jointly optimized to maximize the sum rate of additional users. To solve the formulated discrete non-convex problem, it is split into three subproblems. The accelerated bisection searching, quadratic transform, and simulated annealing approaches are developed to attack them. Simulation results reveal that the proposed transmit scheme and algorithm achieve significant gains over three competing benchmarks. Copyright © 2024, The Authors. All rights reserved.

关键词： Near field communication

来源：评论

学校读者我要写书评

暂无评论

Study on the handheld monitoring equipment and the supervisory method for transportation loss of oil tank trucks

Study on the handheld monitoring equipment and the superviso...

引用

2021 International Conference on Smart Transportation, Energy and Power, STEP 2021

作者： Zhizhou, He Zuobi, Wang Hua, Ma Shideyi Hejingbin Zhaoxia, Mu Yuanbo, Bai Department of Computer Science Xi'An Petroleum University Shaanxi Province Xi'an City710000 China Changqing Oilfield No.2 Oil Production Plant Gansu Province Qing'yang745000 China CNPC Chuanqing Drilling Engineering Company Limited Shaanxi Province Xi'an City710000 China Department of Digital Media Xi'An Petroleum University Shaanxi Province Xi'an City710000 China

At present, the oil of oil fields in remote areas and well sites without petroleum pipeline are mainly transported by oil tankers. Oil will spill and be stolen during the process of transportation, resulting in a large difference between the amount of oil loaded at first and the amount of oil unloaded in the end. The traditional method is to measure and print the bill when loading oil, not to re-measure when unloading oil, and to pay according to the bill, which causes great economic loss. Aiming at tackle this problem, this paper designs and realizes a handheld monitoring device and supervision method for the transportation loss of oil tanker. It integrates EEPROM, RTC real-time clock, PCF8563T memory, LED display lamp, LCD1602 display screen and speakers, and communicates and transmits oil quantity information with primary instruments of oil pumping equipment and oil unloading equipment, the information stored by the device can be read by the communication software of the host computer, and the information can be analyzed, calculated and settled accurately by the management software of the host computer. It can effectively prevent oil leakage and oil stealing during transportation. © Published under licence by IOP Publishing Ltd.

关键词： Oil tanks

来源：评论

学校读者我要写书评

暂无评论

The Adaptive Consensus Reaching Process Driven by Multi-Objectives Optimization with Application in Microgrid Ancillary Services Configuration

SSRN

引用

SSRN 2024年

作者： Tao, Xiwen Wang, Jiali School of Economics and Management Nanjing Institute of Technology Jiangsu Nanjing211167 China School of Economics and Management Nanjing University of Science and Technology Jiangsu Nanjing210094 China Electrical & Computer Engineering Department University of Alberta EdmontonABT6G2E1 Canada

Under the condition of renewable energy high-penetration, electricity ancillary services have become a critical factor affecting the operational efficiency and reliability of microgrid systems. The microgrid ancillary services configuration (ASC) necessitates the consensus consolidation of multiple departments’ preferences from microgrid operators. Therefore, the group decision making (GDM) mechanism, oriented to consensus reaching, is a vital tool supporting the ASC configuration. In the ASC configuration decision process, consensus reaching process (CRP) necessitates simultaneously optimizing multiple decision objectives: improving the consensus degree, enhancing service utility, and reducing decision opinion fuzziness. However, existing CRP models often prioritize the group consensus level as the sole driving factor, with limited attention paid to the multi-objective optimization capabilities. To respond to the multi-objective optimization feature of microgrid ASC problem, this paper leverages the ER random network model and social learning theory to construct an adaptive CRP model, incorporating multiple decision objectives as inducing factors in the novel CRP model. The proposed CRP model encompasses network generation mechanism and opinion interaction mechanism, induced by service utility and interaction signals, respectively. For the utility-induced network generation mechanism, considering the potential influence of group network on the individual decision makers (DMs), this study takes service utility as the induced factor to randomly identify the neighbor nodes for building the local decision environment, superimposed to form the global interaction network. For the signal-induced opinion interaction mechanism, this study introduces the social learning theory to construct an introspective opinion interaction mechanism induced by the interaction signal, guiding DMs to updating opinion adaptively. The proposed CRP model is employed to address the GDM-based mi

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

U-Net vs Transformer: Is U-Net Outdated in Medical Image Registration?

arXiv

引用

arXiv 2022年

作者： Jia, Xi Bartlett, Joseph Zhang, Tianyang Lu, Wenqi Qiu, Zhaowen Duan, Jinming School of Computer Science University of Birmingham BirminghamB15 2TT United Kingdom Department of Biomedical Engineering University of Melbourne MelbourneVIC3010 Australia Tissue Image Analytics Centre Department of Computer Science University of Warwick CoventryCV4 7AL United Kingdom Institute of Information Computer Engineering Northeast Forestry University Harbin150400 China Alan Turing Institute LondonNW1 2DB United Kingdom

Due to their extreme long-range modeling capability, vision transformer-based networks have become increasingly popular in deformable image registration. We believe, however, that the receptive field of a 5-layer convolutional U-Net is sufficient to capture accurate deformations without needing long-range dependencies. The purpose of this study is therefore to investigate whether U-Net-based methods are outdated compared to modern transformer-based approaches when applied to medical image registration. For this, we propose a large kernel U-Net (LKU-Net) by embedding a parallel convolutional block to a vanilla U-Net in order to enhance the effective receptive field. On the public 3D IXI brain dataset for atlas-based registration, we show that the performance of the vanilla U-Net is already comparable with that of state-of-the-art transformer-based networks (such as TransMorph), and that the proposed LKU-Net outperforms TransMorph by using only 1.12% of its parameters and 10.8% of its mult-adds operations. We further evaluate LKU-Net on a MICCAI Learn2Reg 2021 challenge dataset for inter-subject registration, our LKU-Net also outperforms TransMorph on this dataset and ranks first on the public leaderboard as of the submission of this work. With only modest modifications to the vanilla U-Net, we show that U-Net can outperform transformer-based architectures on inter-subject and atlas-based 3D medical image registration. Code is available at https://***/xi-jia/LKU-Net. Copyright © 2022, The Authors. All rights reserved.

关键词： Deformation

来源：评论

学校读者我要写书评

暂无评论

Privacy-Preserving Decentralized Signature-Based Access Control

引用

IEEE Transactions on Dependable and Secure Computing 2025年

作者： Han, Jinguang Chen, Liqun Susilo, Willy Southeast University School of Cyber Science and Engineering Jiangsu Nanjing210096 China Ministry of Education Engineering Research Center of Blockchain Application China University of Surrey Department of Computer Science GuildfordGU2 7XH United Kingdom University of Wollongong School of Computing & Information Technology New South Walse WollongongNSW2522 Australia

Decentralized access control reduces trust on the central authority. Considering privacy issues, privacy-preserving decentralized access control (PPDAC) schemes were proposed. However, existing schemes did not consider the unforgeability and aggregtability of access permissions and the traceability of illegal users. In this paper, we propose a privacy-preserving decentralized signature-based access control (PPDSBAC) scheme to fix the above problems. In our scheme, each access permission is a multi- signatures on a keyword, time period and pseudonym, hence is unforgeable and aggregatable. Services are encrypted by using different keywords and time periods. A user can use a pseudonym to access a service directly if he/she gets required access permissions from required authorization authorities. Furthermore, in the case that trace is required, a trace authority can de-anonymise users and identify their real identities. We formalize both the definition and security model of our scheme, and propose a concrete construction. Then, the implementation and evaluation are conducted to show its efficiency. Finally, the security of our scheme is formally proven. The novelty is to construct a PPDAC scheme with unlinkable access requests, unforgeable and aggregatable access permissions, non-interactive authentication and traceability. © 2004-2012 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Study of Helicopter Optimal Autorotation Landing Procedure in Tail Rotor Drive Failure

Study of Helicopter Optimal Autorotation Landing Procedure i...

引用

2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Yan, Xufei Chen, Renliang Zhu, Shiqiang Xie, Anhuan Gu, Jason Research Center for Intelligent Robotics Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China National Key Laboratory of Science and Technology on Rotorcraft Aeromechanics College of Aeronautics Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

This paper investigates the optimal landing trajectory and control procedure when a helicopter undergoes autorotation due to tail rotor drive failure (TRDF), in which an optimal control methodology is proposed. First, a helicopter flight dynamics model with TRDF was developed. Then, the autorotation in TRDF was converted to be a nonlinear optimal control problem, solved by direct node collocation method and sequential quadratic programming algorithm. Finally, a model helicopter (Z11) with single main rotor and tail rotor was used to demonstrate the proposed approach. An optimal autorotation landing procedure in TRDF was determined accordingly. Results indicate that the airframe will immediately respond to the excess torque generated by the main rotor via yawing, sideslip and rolling when TRDF occurs. The pilot is recommended to shut down the engine and perform a series of critical operations to stabilize the violent yaw and roll movements. In addition, flight test data were used to validate the numerical simulations of autorotation landing. The proposed optimal control approach provides a useful tool to investigate helicopter TRDF autorotation landing procedure. © 2022 IEEE.

关键词： Helicopters

来源：评论

学校读者我要写书评

暂无评论

An Edge-Aware Graph Autoencoder Trained on Scale-Imbalanced Data for Traveling Salesman Problems

arXiv

引用

arXiv 2023年

作者： Liu, Shiqing Yan, Xueming Jin, Yaochu Nature Inspired Computing and Engineering Faculty of Technology Bielefeld University Bielefeld33619 Germany School of Information Science and Technology Guangdong University of Foreign Studies Guangzhou510006 China Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom

In recent years, there has been a notable surge in research on machine learning techniques for combinatorial optimization. It has been shown that learning-based methods outperform traditional heuristics and mathematical solvers on the Traveling Salesman Problem (TSP) in terms of both performance and computational efficiency. However, most learning-based TSP solvers are primarily designed for fixed-scale TSP instances, and also require a large number of training samples to achieve optimal performance. To fill this gap, this work proposes a data-driven graph representation learning method for solving TSPs with various numbers of cities. Specifically, we formulate the TSP as a link prediction task and propose an edge-aware graph autoencoder (EdgeGAE) model that can solve TSPs by learning from various-scale samples with an imbalanced distribution. A residual gated encoder is trained to learn latent edge embeddings, followed by an edge-centered decoder to output link predictions in an end-to-end manner. Furthermore, we introduce an active sampling strategy into the training process to improve the model's generalization capability in large-scale scenarios. To investigate the model's practical applicability, we generate a scale-imbalanced dataset comprising 50,000 TSP instances ranging from 50 to 500 cities. The experimental results demonstrate that the proposed edge-aware graph autoencoder model achieves a highly competitive performance among state-of-the-art graph learning-based approaches in solving TSPs with various scales, implying its remarkable potential in dealing with practical optimization challenges. © 2023, CC BY.

关键词： Traveling salesman problem

来源：评论

学校读者我要写书评

暂无评论

Soft Contact Simulation and Manipulation Learning of Deformable Objects with Vision-based Tactile Sensor

arXiv

引用

arXiv 2024年

作者： Shan, Jianhua Sun, Yuhao Zhang, Shixin Sun, Fuchun Chen, Zixi Shen, Zirong Stefanini, Cesare Yang, Yiyong Luo, Shan Fang, Bin School of Mechanical Engineering Anhui University of Technology China Institute for Artificial Intelligence Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China Beijing100083 China Biorobotics Institute The Department of Excellence in Robotics and AI Scuola Superiore Sant’Anna Pisa56127 Italy Department of Engineering King’s College London LondonWC2R 2LS United Kingdom Zhili College Tsinghua University Beijing100084 China

Deformable object manipulation is a challenging problem due to its complex deformable properties. With the development of artificial intelligence, learning-based methods have shown outstanding performance in the manipulation of robots. Previous works have investigated the manipulation of deformable objects via Reinforcement Learning (RL) in simulation. However, they approximate object deformation with particles, and particle states are employed as observations, which are not available in reality. To address these issues, we propose a novel approach utilizing Vision-Based Tactile Sensors (VBTSs) as the end-effector in simulation to produce observations like relative position, squeezed area, and object contour, which are transferable to real robots. However, this makes contact simulation more complex due to the gel layer of VBTS is also a deformable object. Existing simulation methods of the vision-based tactile sensor can only simulate elastic deformation, while the simulation of plastic and elastoplastic deformation is poor. This must be overcome for a more realistic contact simulation between deformable objects. In this work, we build a new contact simulation environment for deformable objects including elastic, plastic, and elastoplastic deformation. We utilize RL strategies to train agents in the simulation, and expert demonstrations are applied for challenging tasks. To achieve simulation-to-real-world (sim-to-real) transfer, transferable observations like relative position, squeezed area, and object contour are applied in RL training. Also, we build a real experimental platform, including a VBTS, to complete the sim-to-real work and robustness testing. Leveraging the developed simulation and real experiment setup, a benchmark has been created for contact simulation and manipulation learning of deformable objects with VBTS. Our work innovatively proposes a strategy that employs high-resolution VBTSs in contact simulation and manipulation of deformable objects. W

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Enhancing Dropout-based Bayesian Neural Networks with Multi-Exit on FPGA

arXiv

引用

arXiv 2024年

作者： Chen, Hao Castelli, Liam Ferianc, Martin Zhou, Hongyu Liu, Shuanglong Luk, Wayne Fan, Hongxiang The Department of Computing Imperial College London LondonSW7 2AZ United Kingdom The Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom The School of Computer Science University of Sydney Camperdown SydneyNSW2006 Australia The School of Physics and Electronics Hunan Normal University Changsha410081 China Samsung AI Center CambridgeCB1 2JH United Kingdom The Department of Computer Science and Technology University of Cambridge CB3 0FD United Kingdom

Reliable uncertainty estimation plays a crucial role in various safety-critical applications such as medical diagnosis and autonomous driving. In recent years, Bayesian neural networks (BayesNNs) have gained substantial research and industrial interests due to their capability to make accurate predictions with reliable uncertainty estimation. However, the algorithmic complexity and the resulting hardware performance of BayesNNs hinder their adoption in real-life applications. To bridge this gap, this paper proposes an algorithm and hardware co-design framework that can generate field-programmable gate array (FPGA)based accelerators for efficient BayesNNs. At the algorithm level, we propose novel multi-exit dropout-based BayesNNs with reduced computational and memory overheads while achieving high accuracy and quality of uncertainty estimation. At the hardware level, this paper introduces a transformation framework that can generate FPGA-based accelerators for the proposed efficient multi-exit BayesNNs. Several optimization techniques such as the mix of spatial and temporal mappings are introduced to reduce resource consumption and improve the overall hardware performance. Comprehensive experiments demonstrate that our approach can achieve higher energy efficiency compared to CPU, GPU, and other state-of-the-art hardware implementations. To support the future development of this research, we have open-sourced our code at: https://***/os-hxfan/MCME_FPGA_*** © 2024, CC BY-NC-SA.

关键词： Field programmable gate arrays (FPGA)

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：