检索结果-内蒙古大学图书馆

Vector based fault isolation in closed-loop systems

IFAC-PapersOnLine 2024年第4期58卷 664-669页

作者： Henrik Niemann Niels Kjølstad Poulsen Dept. of Electrical and Photonics Engineering Tech. Uni. of Denmark DK-2800 Kgs. Lyngby Denmark Dept. of Applied Mathematics and Computer Science Tech. Uni. of Denmark DK-2800 Kgs. Lyngby Denmark

Isolation of parametric faults in closed-loop MIMO systems is considered in this paper. A double residual generator is applied for the isolation. First, it is shown that there is a linear dependency of the single parametric faults and the residual vector. Based on this linear dependency together with the dual residual vector, residual output directions are calculated for each parametric fault. These output directions for the residuals are independent of the value of the single faults. The fault isolation is then done by comparing the residual vector with the calculated output vectors for the different faults. To isolate a fault, the calculated output vector for the given fault and the residual vector need to be parallel. The scalar vector product between the vectors is applied as a simple test method for fault isolation.

关键词： Active fault isolation residual generators parametric faults closed-loop systems

来源：评论

学校读者我要写书评

暂无评论

Priority-Driven Task Scheduling and Resource Allocation in Cloud Environment

Priority-Driven Task Scheduling and Resource Allocation in C...

引用

Ubiquitous Networking (UNet), International Conference on

作者： Hicham Ben Alla Said Ben Alla Abdellah Ezzati Mathematics and Computer Science Department LAVETE laboratory Science and Technical Faculty Hassan 1 University Settat Morocco Industrial Systems Engineering Department LAVETE laboratory National School of Applied Sciences - Berrechid Hassan 1 University Settat Morocco

ISBN: (数字)9798350356144

ISBN: (纸本)9798350356151

Currently, efficient task scheduling and resource allocation processes are crucial for optimizing performance in cloud computing environments. In this paper, we introduce a novel approach that prioritizes tasks based on their specific requirements and allocates resources accordingly. Task priority is determined through a scoring threshold that considers different requirements such as deadline, temporal requirements, and task length. To ensure efficient matching, virtual machines (VMs) are categorized into three distinct groups using K-means clustering. Simulations conducted within the CloudSim simulator demonstrate the effectiveness of this method, leading to significant reductions in makespan and energy consumption, while simultaneously improving resource utilization compared to existing algorithms.

关键词： Cloud computing Energy consumption Processor scheduling Computational modeling Clustering algorithms Dynamic scheduling Resource management

来源：评论

学校读者我要写书评

暂无评论

Adaptive Trajectory Correction for Underwater Object Tracking

引用

IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Luo, Xudong Yuan, Di Shu, Xiu Liu, Qiao Chang, Xiaojun He, Zhenyu Xidian University Guangzhou Institute of Technology Guangzhou510555 China Guangzhou University School of Computer Science and Cyber Engineering Guangzhou510006 China Chongqing Normal University National Center for Applied Mathematics Chongqing401331 China University of Technology Faculty of Engineering and Information Technology Australian Artificial Intelligence Institute Sydney Australia Harbin Institute of Technology School of Computer Science and Technology Shenzhen518055 China

Most extant underwater object tracking (UOT) utilize generic tracking algorithms, which lack applicability to underwater tracking scenarios. Moreover, these algorithms primarily emphasize minimizing interference from various challenging tasks to prevent target drift, but pay less attention to the strategies for mitigating target drift once it occurs. To alleviate the above problems, we propose a simple, effective, and UOT-focused adaptive trajectory correction framework, named ATCTrack. From the perspective of tracking failure, this methodology aims to promptly identify and rectify unreasonable target drift through accurate trajectory coordinate correction and trajectory template updates. Additionally, to mitigate the adverse effects of potential erroneous corrections, we implement an adaptive strategy that corrects only significant target drift, allowing for self-correction within a certain margin. Finally, we introduce an adaptive underwater image enhancement technique to improve the underwater image quality and maintain the trajectory's stability and clarity. Our tracker achieves state-of-the-art performance on the currently prevalent UOT tracking benchmarks compared to other trackers. © 1991-2012 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Recognizing Driver Activities Using Deep Learning Approaches Based on Smartphone Sensors 1

引用

15th Multi-disciplinary International Conference on Artificial Intelligence, MIWAI 2022

作者： Mekruksavanich, Sakorn Jantawong, Ponnipa Hnoohom, Narit Jitpattanakul, Anuchit Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao Mueang Phayao Thailand Image Information and Intelligence Laboratory Department of Computer Engineering Faculty of Engineering Mahidol University Nakhon Pathom Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9783031209925

ISBN: (纸本)9783031209918

Human motion detection based on smartphone sensors has gained popularity for identifying everyday activities and enhancing situational awareness in pervasive and ubiquitous computing research. Modern machine learning and deep learning classifiers have been demonstrated on benchmark datasets to interpret people’s behaviors, including driving activities. While driving, driver behavior recognition may assist in activating accident detection. In this paper, we investigate driving behavior detection using deep learning techniques and smartphone sensors. We proposed the DriveNeXt classifier, which employs convolutional layers to extract spatial information and multi-branch aggregation transformation. This research evaluated the proposed model using a publicly available benchmark dataset that captures four activities: a driver entering/exiting and sitting/standing out of a vehicle. Classifier performance was evaluated using two common HAR indicators (accuracy and F1-score). The recommended DriveNeXt outperforms previous baseline deep learning models with the most fantastic accuracy of 96.95% and the highest F1-score of 96.82%, as shown by many investigations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

Pain Forecasting using Self-supervised Learning and Patient Phenotyping: An attempt to prevent Opioid Addiction

arXiv

引用

arXiv 2023年

作者： Padhee, Swati Banerjee, Tanvi Abrams, Daniel M. Shah, Nirmish Computer Science and Engineering Wright State University DaytonOH United States Engineering Science and Applied Mathematics Northwestern University EvanstonIL United States Department of Medicine Duke University DurhamNC United States

Sickle Cell Disease (SCD) is a chronic genetic disorder characterized by recurrent acute painful episodes. Opioids are often used to manage these painful episodes;the extent of their use in managing pain in this disorder is an issue of debate. The risk of addiction and side effects of these opioid treatments can often lead to more pain episodes in the future. Hence, it is crucial to forecast future patient pain trajectories to help patients manage their SCD to improve their quality of life without compromising their treatment. It is challenging to obtain many pain records to design forecasting models since it is mainly recorded by patients’ self-report. Therefore, it is expensive and painful (due to the need for patient compliance) to solve pain forecasting problems in a purely supervised manner. In light of this challenge, we propose to solve the pain forecasting problem using self-supervised learning methods. Also, clustering such time-series data is crucial for patient phenotyping, anticipating patients’ prognoses by identifying"similar" patients, and designing treatment guidelines tailored to homogeneous patient subgroups. Hence, we propose a self-supervised learning approach for clustering time-series data, where each cluster comprises patients who share similar future pain profiles. Experiments on five years of real-world datasets show that our models achieve superior performance over state-of-the-art benchmarks and identify meaningful clusters that can be translated into actionable information for clinical decision-making. Copyright © 2023, The Authors. All rights reserved.

关键词： Supervised learning

来源：评论

学校读者我要写书评

暂无评论

Theoretical and Numerical Investigation of Acoustic Cavitation Bubble Based on the Impact of Ultrasound Frequency

引用

Bulletin of the Russian Academy of sciences: Physics 2023年第Suppl 3期87卷 S341-S347页

作者： Ahmed K. Abu-Nab Abu-Bakr, Ali F. Zain Abu Shaeer Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Koom32511 Egypt Phystech School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology Moscow oblast Dolgoprudny141700 Russia Department of Basic Science Higher Institute of Engineering and Technology Kafr El Sheikh33511 Egypt

Abstract: Acoustic cavitation is the expansion and contraction of existing microbubbles in liquids brought on by an ultrasonic field. The dynamics of oscillations at higher pressures and temperatures when the cavitation bubbles collapse can be used to characterize cavitation dynamical behavior. This work deals with the theoretical and numerical investigation of acoustic cavitation in viscoelastic media considering the influence of ultrasound frequency. An acoustic pressure equation combined with a modified Rayleigh–Plesset equation forms the theoretical framework for ultrasound cavitation dynamics. The numerical solutions of the given cavitation bubble model were obtained taking into account the effect of acoustic pressure, using the exponential B-Spline collection method. The dynamics of the cavitation bubbles’ radius and the internal pressure of acoustic cavitation were examined at different values of viscosity and the impact of physical parameters on the monatomic, diatomic, and adiabatic gas-filled spherical bubble’s collapse dynamics for (k = 7/5, 5/3, 1) respectively. © Pleiades Publishing, Ltd. 2023. ISSN 1062-8738, Bulletin of the Russian Academy of sciences: Physics, 2023, Vol. 87, Suppl. 3, pp. S341–S347. Pleiades Publishing, Ltd., 2023. ISSN 1062-8738, Bulletin of the Russian Academy of sciences: Physics, 2023. Pleiades Publishing, Ltd., 2023.

关键词： Dynamics

来源：评论

学校读者我要写书评

暂无评论

Optimized Blockchain-Based EMR Sharing via Secure Channel-Free Universal Designated Verifier Signature Proofs

引用

IEEE Internet of Things Journal 2025年

作者： Huang, Peida Lin, Chao Ning, Jianting Wu, Wei Fujian Normal University Fujian Provincial Key Laboratory of Network Security College of Computer and Cyber Security Cryptology/Center for Applied Mathematics of Fujian Province Fuzhou350117 China Wuhan University School of Cyber Science and Engineering Wuhan430072 China Fujian Normal University College of Mathematics and Statistics Fuzhou350117 China

The sharing of electronic medical records (EMR) significantly enhances disease research and healthcare system efficiency. However, outsourcing EMRs to cloud servers introduces risks such as tampering and malicious propagation by recipients. Existing solutions combining blockchain and Universal Designated Verifier Signature Proofs (UDVSP) mitigate these risks but rely on secure channels for key sharing, adding communication and computation costs that hinder deployment. In this paper, we introduce the first Secure Channel-Free Universal Designated Verifier Signature Proofs (SCF-UDVSP) scheme, leveraging simplified cryptographic techniques like the Σ-protocol and public key encryption. Integrating SCF-UDVSP with blockchain, we develop an optimized EMR sharing system that effectively prevents these attacks including tampering and malicious propagation. Security proofs and performance analysis validate the feasibility and effectiveness of our proposed system. Compared to existing UDVSP solutions, our approach reduces computational costs by approximately 59.3% without increasing communication overhead, while also eliminating the need for establishing a secure channel. © 2014 IEEE.

关键词： Authentication Protocol

来源：评论

学校读者我要写书评

暂无评论

Wearable Fall Detection Based on Motion Signals Using Hybrid Deep Residual Neural Network 1

引用

15th Multi-disciplinary International Conference on Artificial Intelligence, MIWAI 2022

ISBN: (数字)9783031209925

ISBN: (纸本)9783031209918

There have been several approaches for wearable fall detection devices during the last twenty years. The majority of technologies relied on machine learning. Although the given findings appear that the issue is practically addressed, critical problems remain about feature extraction and selection. In this research, the constraint of machine learning on feature extraction is addressed by including a hybrid convolutional operation in our proposed deep residual network, called the DeepFall model. The proposed network automatically generates high-level motion signal characteristics that can be utilized to track falls and everyday activities. FallAllD dataset, a publicly available standard dataset for fall detection that gathered motion signals of falls and other events, was utilized to analyze the proposed network. We performed investigations using a 5-fold cross-validation technique to determine overall accuracy and F-measure. The experimental outcomes show that the proposed DeepFall performs better accuracy (95.19%) and F-measure (92.79%) than the state-of-the-art baseline deep learning networks. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fall detection

来源：评论

学校读者我要写书评

暂无评论

Parameter Estimation for Partially Observed McKean-Vlasov Diffusions

arXiv

引用

arXiv 2024年

作者： Jasra, Ajay Maama, Mohamed Tempone, Raul School of Data Science The Chinese University of Hong Kong CN Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Chair of Mathematics for Uncertainty Quantification RWTH Aachen University Aachen52062 Germany

In this article we consider likelihood-based estimation of static parameters for a class of partially observed McKean-Vlasov (POMV) diffusion process with discrete-time observations over a fixed time interval. In particular, using the framework of [5] we develop a new randomized multilevel Monte Carlo method for estimating the parameters, based upon Markovian stochastic approximation methodology. New Markov chain Monte Carlo algorithms for the POMV model are introduced facilitating the application of [5]. We prove, under assumptions, that the expectation of our estimator is biased, but with expected small and controllable bias. Our approach is implemented on several examples. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

On the constitutive behaviour of the inertial drag with radiative and dissipative heat and chemical reaction for Casson fluid flow over an extending surface through permeable medium

引用

Partial Differential Equations in applied mathematics 2025年 14卷

作者： Baithalu, Rupa Agbaje, Titilayo M Panda, Subhajit Mishra, S.R. Department of Mathematics Siksha ‘O’ Anusandhan Deemed to be University Odisha Bhubaneswar 751030 India School of Computer Science and Applied Mathematics University of the Witwatersrand Private Bag 3 Braamfontein Johannesburg 2050 South Africa Centre for Data Science Department of Computer Science and Engineering Siksha ‘O’ Anusandhan Deemed to be University Odisha Bhubaneswar 751030 India

In advanced industrial and biomedical application combined with polymer processing, blood flow analysis, and food processing, the Casson fluid model emerged as a crucial framework for illustrating the transportation of non-Newtonian fluids. The proposed analysis investigates the constitutive behavior of the Darcy-Forchheimer inertial drag considering Casson fluid flow through an extending surface packed with Darcy medium. Also, favorable body forces like radiative and dissipative heat effects and chemical reactions are analyzed to carry out the synergistic role in the thermal and concentration distribution. The suitable assumptions of transformation rules are adopted to transform the governing flow phenomena into dimensionless forms. This leads to the appearance of certain factors involved in these governing equations. Further, coupled nonlinear sets of model problems are handled numerically employing the “spectral Quasi-linearization method”. The conformity of the attribute of convergence of the current strategy and the validation with the earlier investigation supported the particular cases. Further, the behaviour of the controlling factors on the flow profiles is depicted graphically. The results reveal the effective interaction of inertial drag and radiant heat on the velocity vis-a-vis temperature distributions. Moreover, the illustration of the enhanced chemical reaction influences the concentration profile with stronger reactions leading to sharper gradients. © 2025 The Author(s)

关键词： Casson fluid Chemical reaction Darcy-Forchheimer drag Shooting based numerical technique Thermal radiation

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：