检索结果-内蒙古大学图书馆

IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Yonathan Michael Mohamad Alansari Sajid Javed Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates Center for Autonomous Robotic Systems Khalifa University Abu Dhabi United Arab Emirates

ISBN: (数字)9798350374285

ISBN: (纸本)9798350374292

The integration of Natural Language (NL) descriptions with contemporary tracking algorithms constitutes a new and dynamic field, exhibiting no indications of deceleration in the near future. Nevertheless, the absence of comprehensive language descriptions for tracking datasets, particularly in the domain of underwater tracking datasets, presents a substantial impediment to the advancement of this field. Typically, the textual descriptions accompanying these datasets are brief, inadequately informative, lack details regarding relative location or directional movement, and occasionally deviate from the manner in which a human would naturally describe the target in ordinary conversation. In response to this challenge, we propose the development of vividly descriptive NL descriptions tailored for the UVOT400 dataset, which focuses on underwater tracking. These descriptions aim to encapsulate a myriad of factors in order to furnish as comprehensive an understanding as possible regarding the target fish. Subsequent evaluations of these descriptions, conducted in conjunction with contemporary language-based tracking systems, have revealed superior performance in comparison to the best-performing visual-only trackers employed for benchmarking purposes with the aforementioned dataset.

关键词： Visualization Target tracking Heuristic algorithms Surveillance Refining Natural languages Oral communication

来源：评论

学校读者我要写书评

暂无评论

An MCS Navigation System Based on Road Surface Quality for Bicycle Riders

An MCS Navigation System Based on Road Surface Quality for B...

引用

International Conference on Smart Computing (SMARTCOMP)

作者： Federico Montori Rocco Pastore Luca Sciullo Luciano Bononi Luca Bedogni Department of Computer Science and Engineering University of Bologna Italy Advanced Research Center on Electronic Systems “Ercole De Castro” University of Bologna Italy University of Modena and Reggio Emilia Italy

ISBN: (数字)9798350349948

ISBN: (纸本)9798350349955

Road surface quality is a major concern for bicycle riders and plays an important role in the mobility infrastructure. In the era where smarter cities aim to increase the well-being of citizens and the efficiency of infrastructures, navigation systems relying on Mobile Crowdsensing (MCS) are mostly designed for car drivers, and account for road traffic conditions. To cover the gap, in this paper, we propose a full architectural pipeline of an MCS-based navigation system for bicycle riders that accounts for the road surface quality. The MCS paradigm leverages the sensor data produced by the personal devices of participating citizens to describe phenomena of common interest. Our system classifies road segments using inertial sensor data gathered by users, using a combination of supervised and unsupervised methods, as human labeling in this context is impractical and too subjective. We prove the efficacy of our method in a controlled environment, and then we implement and deploy the full system in a real city, finally reporting on its results.

关键词： Navigation Roads Urban areas Pipelines Bicycles Road traffic Planning

来源：评论

学校读者我要写书评

暂无评论

AutoOptLib: Tailoring Metaheuristic Optimizers via Automated Algorithm Design

arXiv

引用

arXiv 2023年

作者： Zhao, Qi Yan, Bai Hu, Taiwei Chen, Xianglong Duan, Qiqi Yang, Jian Shi, Yuhui The Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China The Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen518055 China The Department of Computer Science Johns Hopkins University BaltimoreMD United States The School of Computer Science and Technology Harbin Institute of Technology Shenzhen518055 China

Metaheuristics are prominent gradient-free optimizers for solving hard problems that do not meet the rigorous mathematical assumptions of analytical solvers. The canonical manual optimizer design could be laborious, untraceable and error-prone, let alone human experts are not always available. This arises increasing interest and demand in automating the optimizer design process. In response, this paper proposes AutoOptLib, the first platform for accessible automated design of metaheuristic optimizers. AutoOptLib leverages computing resources to conceive, build up, and verify the design choices of the optimizers. It requires much less labor resources and expertise than manual design, democratizing satisfactory metaheuristic optimizers to a much broader range of researchers and practitioners. Furthermore, by fully exploring the design choices with computing resources, AutoOptLib has the potential to surpass human experience, subsequently gaining enhanced performance compared with human problem-solving. To realize the automated design, AutoOptLib provides 1) a rich library of metaheuristic components for continuous, discrete, and permutation problems;2) a flexible algorithm representation for evolving diverse algorithm structures;3) different design objectives and techniques for different optimization scenarios;and 4) a graphic user interface for accessibility and practicability. AutoOptLib is fully written in Matlab/Octave;its source code and documentation are available at https://***/qz89/AutoOpt and https://***/, respectively. Copyright © 2023, The Authors. All rights reserved.

关键词： User interfaces

来源：评论

学校读者我要写书评

暂无评论

Electrical Motor Fault Detection System using AI's Random Forest Classifier Technique

Electrical Motor Fault Detection System using AI's Random Fo...

引用

International Conference on Advanced systems and Electric Technologies (IC_ASET)

作者： Raziq Yaqub Hassan Ali Mohd Helmy Bin Abd Wahab Departmnet of Electrical Engineering and Computer Science Alabama A&M University Huntsville AL USA Department of Sustainable Systems Engineering University of Doha for Science and Technology (UDST) Qatar Doha Departmnet of Computer Engineering Universiti Tun Hussein Onn Malaysia (UTHM) Johor Malaysia

Induction motors are very commonly used to create traction for electric vehicles. In electric vehicles and other rotating machine systems, faults develop during regular operation, which, if unaddressed, can accelerate the damage to machines. Therefore, early detection and prediction of faults hold the key importance in predictive and preventive maintenance. This work focuses on collecting sounds and vibrations data of an electric motor, which are the critical indicators of fault initiation in electric vehicle systems. We use artificial intelligence (AI) to predict and classify the types of faults associated with different vibration frequencies and sound levels. We explore random forest classifier technique for faults prediction and derive promising results for different fault conditions. Results show that we correctly predicted and classified different types of manually induced faults associated with different vibration frequencies and sound levels with a 92% accuracy and 86 to 91 % precision level.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Engine Failure Detection of Raw Mill Machine via Discrete Variational Auto-encoder

Engine Failure Detection of Raw Mill Machine via Discrete Va...

引用

2022 International Conference on Data and Software engineering, ICoDSE 2022

作者： Abruzi, Izhar Brur Iqbal, Mohammad Mukhlash, Imam Rukmi, Alvida Mustika Kurniati, Nani Kimura, Masaomi Institut Teknologi Sepuluh Nopember Sukolilo Department of Mathematics Surabaya60111 Indonesia Institut Teknologi Sepuluh Nopember Sukolilo Department of Industrial and Systems Engineering Surabaya60111 Indonesia Shibaura Institute of Technology Department of Computer Science and Engineering 3 Chome-7-5 Toyosu Tokyo Koto135-8548 Japan

ISBN: (数字)9798350397055

ISBN: (纸本)9798350397055

We present a deep learning model to detect failure engine state by observing the discrete latent sensor behaviors. Further, we investigate the behaviors from the reconstruction loss of the model until we find its value starting to jump out (anomaly stage). As a result, this work aims to forecast the failure time of the engine as early as possible. To notice the anomaly, we formulate a piecewise function based on alpha -quantile of the loss value inside the proposed model. Unlike the existing studies focusing on the continuous latent, this work draws the discrete latent from discrete variational auto-encoder (DVAE) to predict the failure state better. For evaluation purposes, we evaluated the proposed model on a real dataset from the raw mill machine of a cement factory in Indonesia. From the experiments, we are satisfied to see the proposed model performances detecting the failure state of the raw mill machine as early as possible compared to the state-of-the-art model. © 2022 IEEE.

关键词： Engines

来源：评论

学校读者我要写书评

暂无评论

Advancing Precision Aquaculture Through Big Data Analytics and Machine Learning in Canadian Fish Farming

Advancing Precision Aquaculture Through Big Data Analytics a...

引用

OCEANS 2024 - Halifax, OCEANS 2024

作者： Bravo, Francisco Amorim, Joana Amirkandeh, Melika Besharati Bodorik, Peter Cerqueira, Vitor Gomes, Nuno R.C. Korus, Jennie Oliveira, Mariana Parent, Marianne Pimentel, João Reilly, Derek Sclodnick, Tyler Grant, Jon Filgueira, Ramón Whidden, Christopher Universidad Adolfo Ibañez Facultad de Ingenieria y Ciencias Santiago Chile Dalhousie University Faculty of Computer Science Halifax Canada University of Porto Faculty of Engineering Portugal Barcelona Spain Innovasea Marine Systems Bedford Canada Charlottetown Canada Dalhousie University Department of Oceanography Halifax Canada Marine Affairs Program Dalhousie University Halifax Canada

ISBN: (纸本)9798331540081

The aquaculture industry faces significant challenges related to sustainability, productivity, and fish welfare. Key issues include managing environmental conditions, disease, pests, and data integration from various sensors and monitoring systems. The BigFish project aims to address these challenges through advanced analytics and machine learning, focusing on three case studies in Atlantic salmon farms: predicting oxygen levels, reducing sea lice infestations, and improving data interaction and visualization. Predictive models for oxygen levels and sea lice infestation, as well as natural language interfaces for data visualization, demonstrate the potential for improved decision-making and management practices in aquaculture. Early results indicate the effectiveness of these approaches, highlighting the importance of data-driven solutions in enhancing industry sustainability and productivity. © 2024 IEEE.

关键词： Aquaculture

来源：评论

学校读者我要写书评

暂无评论

An Efficacy Analysis of Data using Fuzzy Logic and Fractal Encryption Techniques for Cloud Platform Data Security

An Efficacy Analysis of Data using Fuzzy Logic and Fractal E...

引用

Knowledge engineering and Communication systems (ICKECS), International Conference on

作者： P Dineshkumar V Jeeva C Nithiesh P J Arun K Sathish Kumar Department of Information Technology K. S. Rangasamy College of Technology Tiruchengode India Computer Science and Business Systems Sri Sai Ram Engineering College Chennai India

ISBN: (数字)9798350359688

ISBN: (纸本)9798350359695

In the realm of cloud computing, safeguarding data confidentiality is paramount. This paper introduces a novel approach to data security in cloud platforms, merging fuzzy logic and fractal encryption techniques. Fuzzy logic accommodates uncertain data, enabling adaptable encryption strategies tailored to cloud dynamics. Fractal encryption harnesses self-similarity in fractals to create intricate encryption keys, fortifying data protection. Together, they propose a robust solution to mitigate unauthorized access, data breaches, and cyber threats. Through theoretical exploration and practical testing, the efficacy of this approach is demonstrated, highlighting its potential to address cloud security challenges. The scalability and versatility of these methods make them applicable across diverse cloud infrastructures, ensuring comprehensive data protection. This paper advocates for the adoption of fuzzy logic and fractal encryption as proactive measures to enhance cloud platform security, fostering trust among users and stakeholders.

关键词： Fuzzy logic Knowledge engineering Cloud computing Scalability Merging Data protection Fractals

来源：评论

学校读者我要写书评

暂无评论

Hermitian {P,k+1}-(anti-)reflexive solutions to a quaternion matrix equation

引用

Computational and Applied Mathematics 2025年第6期44卷

作者： Liu, Xin Li, Wanqi Yuan, Shifang Zhang, Yang Macau Institute of Systems Engineering Faculty of Innovation Engineering Macau University of Science and Technology Avenida Wai Long TaiPa999078 China School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology Avenida Wai Long TaiPa999078 China School of Mathematics and Computational Science Wuyi University Jiangmen529020 China Department of Mathematics University of Manitoba WinnipegMBR3T 2N2 Canada

In this paper, we consider the Hermitian {P,k+1}-(anti-)reflexive solutions to the quaternion matrix equation AXB+CXD=E and AX=E, respectively. We use the complex representation method to obtain the necessary and sufficient conditions for the existence of the Hermitian {P,k+1}-reflexive solution (resp. Hermitian {P,k+1}-anti-reflexive solution), respectively, and derive their solutions when the matrix equations have the Hermitian {P,k+1}-reflexive solution (resp. Hermitian {P,k+1}-anti-reflexive solution). Finally, two examples are provided to verify the effectiveness of our method. © The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2025.

关键词： Polynomials

来源：评论

学校读者我要写书评

暂无评论

Integrated Real-Time Control and Scheduling for Safety Critical Cyber-Physical systems

Integrated Real-Time Control and Scheduling for Safety Criti...

引用

IEEE Symposium on Real-Time and Embedded Technology and Applications

作者： Marion Sudvarg Andrew Clark Chris Gill Department of Computer Science and Engineering James McKelvey School of Engineering Washington University in St. Louis St. Louis Missouri United States Department of Electrical and Systems Engineering James McKelvey School of Engineering Washington University in St. Louis St. Louis Missouri United States

ISBN: (数字)9798331543402

ISBN: (纸本)9798331543419

Cyber-physical systems (CPS) must interact with varying environments at fine-grained time-scales, assuring control safety and stability while optimizing application-specific performance objectives. To address those requirements, co-design of real-time control and scheduling has received considerable attention over multiple decades, to allow rigorous assurance of system properties while enabling diverse forms of adaptation to changing operating conditions. In this paper, we present a new formalization of the periodicity requirements for control inputs to (1) guarantee reachability of safe (and avoidance of unsafe) portions of the system state space, (2) adaptively manage dynamic periodicity constraints that may change as the state space is traversed, and (3) express minimum periods to enable safe hand-offs between high-performance controllers and more conservative backup controllers. Our evaluations of this approach confirm that it is able to maintain system safety and stability while optimizing system performance.

关键词： System performance Cyber-physical systems Aerospace electronics Dynamic scheduling Control systems Real-time systems Safety

来源：评论

学校读者我要写书评

暂无评论

A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements

arXiv

引用

arXiv 2024年

作者： Xu, Gehui Chen, Guanpu Fidan, Baris Hong, Yiguang Qi, Hongsheng Parisini, Thomas Johansson, Karl H. The Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden The Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China The Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom The Department of Engineering and Architecture University of Trieste Trieste34127 Italy

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multi-player non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies. Copyright © 2024, The Authors. All rights reserved.

关键词： Sensor nodes

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：