检索结果-内蒙古大学图书馆

IEEE Conference on Decision and Control

作者： Andre Coelho Alin Albu-Schaeffer Arne Sachtler Hrishik Mishra Davide Bicego Christian Ott Antonio Franchi Institute of Robotics and Mechatronics of the German Aerospace Center (DLR) Oberpfaffenhofen Germany Dextrous Robotics Inc Memphis TN USA Robotics and Mechatronics Lab Faculty of Electrical Engineering Mathematics & Computer Science University of Twente Netherlands Department of Informatics Technical University of Munich Germany Automation and Control Institute (ACIN) Technical University of Vienna Austria LAAS-CNRS University of Toulouse France

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper proposes a Nonlinear Model-Predictive Control (NMPC) method capable of finding and converging to energy-efficient regular oscillations, which require no control action to be sustained. The approach builds up on the recently developed Eigenmanifold theory, which defines the sets of line-shaped oscillations of a robot as an invariant two-dimensional submanifold of its state space. By defining the control problem as a nonlinear program (NLP), the controller is able to deal with constraints in the state and control variables and be energy-efficient not only in its final trajectory but also during the convergence phase. An initial implementation of this approach is proposed, analyzed, and tested in simulation.

关键词： Analytical models Aerospace electronics Energy efficiency Trajectory Mechanical systems Oscillators Robots

来源：评论

学校读者我要写书评

暂无评论

Canonical Computations in Cellular Automata and Their Application for Reservoir Computing

Canonical Computations in Cellular Automata and Their Applic...

引用

Conference on Artificial Life, ALIFE 2023

作者： Lindell, Trym A. E. Hudcová, Barbora Nichele, Stefano Artificial Intelligence Lab Department of Computer Science Faculty of Technology Art and Design Oslo Metropolitan University Oslo Norway Machine Learning Research Group Østfold University College Halden Norway Department of Algebra Faculty of Mathematics Charles University Prague Czech Republic Czech Institute of Informatics Robotics and Cybernetics CTU Prague Czech Republic

Cellular Automata (CAs) have potential as powerful parallel computational systems, which has lead to the use of CAs as reservoirs in reservoir computing. However, why certain Cellular Automaton (CA) rules, sizes and input encodings are better or worse at a given task is not well understood. We present a method that enables identification and visualization of the specific information content, flow and transformations within the space-time diagram of CA. We interpret each spatio-temporal location in CA’s space-time diagram as a function of its input and call this novel notion the CA’s Canonical Computations (CCs). This allows us to analyze the available information from the space-time diagrams as partitions of the input set. The method also reveals how inputencoder-rule interactions transform the information flow by changing features like spatial and temporal location stability as well as the specific information produced. This general approach for analysing CA is discussed for the engineering of reservoir computing systems. © 2023, Massachusetts Institute of Technology. All rights reserved.

关键词： Sequential machines

来源：评论

学校读者我要写书评

暂无评论

Multi-Objective Optimization of High-Power Fiber Laser Cutting of Thick Mild Steel by Using Response Surface Methodology

SSRN

引用

SSRN 2023年

作者： Liu, Yanjie Yoshigoe, Kenji Ullah, Farhan Zhang, Shijin Zhao, Yue Shanghai Key Lab of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China School of Software Northwestern Polytechnical University Xi’an710129 China Department of Electrical Engineering and Computer Science Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

High-power continuous wave fiber laser cutting is a next-generation cutting technology for rapid prototyping and small-scale fabrication. To utilize the advantage offered by this technology in terms of high-quality cutting, the laser cutting process parameters must be optimized. In this study, separation speed experiment on thick mild steel plates was performed using a 12-kW continuous-wave multimode ytterbium-doped fiber laser, and a high-power fiber laser cutting cut-through criterion for thick carbon steel plates was proposed. The response surface method was used to model and optimize the cut quality characteristics. Material thickness, laser power, cutting speed, gas pressure, and defocus amount were selected as input factors, whereas kerf taper and material removal rate (MRR) were selected as output quality characteristics. The effects of the various factors on the kerf taper and MRR were investigated using analysis of variance, and second-order regression models were developed for the kerf taper and MRR. Furthermore, a multi-objective optimization method was used to optimize the kerf taper and MRR. The percentage errors of the validation experiments and multi-objective optimization results were 5.27% and 1.93% for the kerf taper and MRR, respectively. Moreover, the analysis revealed that the material removal mechanism and the kerf taper formation mechanism are related to the melt flow. The findings presented in this paper contribute to the improvement of quality and accuracy when cutting thick plates by using a high-power fiber laser. © 2023, The Authors. All rights reserved.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Full-pose Trajectory Tracking of Overactuated Multi-Rotor Aerial Vehicles with Limited Actuation Abilities

TechRxiv

引用

TechRxiv 2023年

作者： Hamandi, Mahmoud Al-Ali, Ismail Seneviratne, Lakmal Franchi, Antonio Zweiri, Yahya The Department of Aerospace Engineering Khalifa University of Science and Technology Abu Dhabi United Arab Emirates The Department of Mechanical Engineering Khalifa University Abu Dhabi United Arab Emirates Khalifa University of Science and Technology Abu Dhabi United Arab Emirates The Robotics and Mechatronics Lab Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands The Department of Computer Control and Management Engineering Sapienza University of Rome Rome00185 Italy LAAS CNRS Université de Toulouse Toulouse31000 France Khalifa University Abu Dhabi United Arab Emirates Center for Artificial Intelligence and Robotics New York University Abu Dhabi Saadiyat Island Abu Dhabi129188 United Arab Emirates

This paper presents a novel optimization-based full-pose trajectory tracking method to control overactuated multirotor aerial vehicles with limited actuation abilities. The proposed method allocates feasible control inputs to track a reference trajectory, while ensuring the tracking of the reference position, and while tracking the closest feasible attitude. The optimization simultaneously searches for a feasible trajectory and corresponding feasible control inputs from the infinite possible solutions, while ensuring smooth control inputs. The proposed real-time algorithm is tested in extensive simulation on multiple platforms with fixed and actuated propellers. The simulation experiments show the ability of the proposed approach to exploit the complex set of feasible forces and moments of overactuated platforms while allocating smooth feasible control inputs. © 2023, CC BY.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

Design and Development of the FlexBE WebUI with Introductory Tutorials

Journal of Computing Sciences in Colleges

引用

Journal of Computing sciences in Colleges 2024年第3期40卷

作者： Samuel Raymond Grace Walters Josh Luzier David C. Conner Capable Humanitarian Robotics and Intelligent Systems Lab Department of Physics Computer Science and Engineering Christopher Newport University Newport News VA

Hierarchical Finite State Machines (HFSMs) continue to be a popular strategy for high-level behavioral control in robotics. Within the Robot Operating System (ROS) ecosystem, the Flexible Behavior Engine (FlexBE) provides an easy to use Python implementation with an intuitive user interface for runtime monitoring and "collaborative autonomy." In this paper, we describe the latest evolution of the FlexBE UI, that leverages FastAPI to provide a Python-based native ROS node interface, to a web-based user interface. Additionally, the paper describes a "quick-start" introductory tutorial to state machines using FlexBE. This system provides a natural introduction to HFSM-based techniques.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Vaccine efficacy and SARS-CoV-2 control in California and *** the session 2020e2026:A modeling study

引用

Infectious Disease Modelling 2022年第1期7卷 62-81页

作者： Md Shahriar Mahmud Md Kamrujjaman Md Mashih Ibn Yasin Adan Md Alamgir Hossain Md Mizanur Rahman Md Shahidul Islam Muhammad Mohebujjaman Md Mamun Molla Department of Computer Science and Engineering State University of BangladeshDhaka1205Bangladesh Department of Mathematics University of DhakaDhaka1000Bangladesh Department of Mathematics and Statistics University of CalgaryCalgaryABCanada Computational Biology Research Lab(CBRL) Department of PharmacyJagannath UniversityDhaka1100Bangladesh Hitotsubashi Institute for Advanced Study Hitotsubashi UniversityNaka KunitachiTokyo186-8601Japan Department of Mathematics and Physics Texas A&M International UniversityLaredoTX78041USA Department of Mathematics&Physics North South UniversityDhaka1229Bangladesh Center for Applied Scientific Computing(CASC) North South UniversityDhaka1229Bangladesh

Background:Besides maintaining health precautions,vaccination has been the only prevention from SARS-CoV-2,though no clinically proved 100%effective vaccine has been developed till *** this stage,to withhold the debris of this pandemic-experts need to know the impact of the vaccine efficacy rates,the threshold level of vaccine effectiveness and how long this pandemic may extent with vaccines that have different efficacy *** this article,a mathematical model study has been done on the importance of vaccination and vaccine efficiency rate during an ongoing ***:We simulated a five compartment mathematical model to analyze the pandemic scenario in both California,and whole *** considered four vaccines,Pfizer(95%),Moderna(94%),AstraZeneca(79%),and Johnson&Johnson(72%),which are being used rigorously to control the SARS-CoV-2 pandemic,in addition with two special cases:a vaccine with 100%efficacy rate and no vaccine under ***-CoV-2 related data of California,and *** used in this ***:Both the infection and death rates are very high in *** model suggests that the pandemic situation in California will be under control in the last quartile of the year 2023 if vaccination program is continued with the Pfizer *** this time,six waves may happen from the beginning of the immunization where the case fatality and recovery rates will be 1.697%and 98.30%,***,according to the considered model,this period might be extended to the mid of 2024 when vaccines with lower efficacy rates are *** the other hand,the daily cases and deaths in the *** be under control at the end of 2026 with multiple *** the number of susceptible people will fall down to none in the beginning of 2027,there is less chance to stop the vaccination program if vaccinated with a vaccine other than a 100%effective vaccine or Pfizer,and at that case vaccination program must run till the mid of *** to this s

关键词： Vaccine Model California Control measurement SARS-CoV-2

来源：评论

学校读者我要写书评

暂无评论

Extraction of Rice Phenological Metrics Using Temporally Correlated Multispectral Drone Imagery

Extraction of Rice Phenological Metrics Using Temporally Cor...

引用

International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： D. Wasif M.Q. Khan R. Murtaza M.Z. Ahmad Z. Zafar M. Shahzad K. Berns M.M. Fraz School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST) Islamabad Pakistan Department of Aerospace and Geodesy Data Science in Earth Observation Technical University of Munich (TUM) Munich Germany Robotics Research Lab Technical University of Kaiserslautern Germany

The rice crop holds great potential to contribute to the economy of most South Asian agricultural countries. However, due to global warming, changes in weather and climate have made it difficult for farmers to accurately predict the timing of various growth stages in the life cycle of rice. Deciding when to apply fertilizers to maximize yield and pesticides to avoid diseases becomes a challenge with conventional farming techniques. Hence, extracting key phenological metrics and analyzing the growth dynamics of different rice varieties are essential for this purpose. The foremost issue in this process is the lack of available multispectral drone imagery datasets, especially in South-East Asia. Therefore, a novel multispectral dataset of rice crops is presented that consists of three different varieties: Kainat, Hybrid, and Super Kernel in East Punjab, Pakistan. The study’s objective is to use this dataset to model a time series of Normalized Difference Vegetation Index (NDVI) and use the change detection method to map key phenological variables using the rate of change of NDVI. The analysis of available data using phenological metrics represents that the Kainat Basmati variant is growing faster than Hybrid as it reaches its peak about ten days earlier than Hybrid. Overall, our study demonstrates that remotely captured unmanned aerial vehicle (UAV) imagery of rice can streamline the process of predicting phenological metrics of rice and provide farmers with an automated statistical model of the growth stages of various crops.

关键词： Measurement Time series analysis Crops Vegetation mapping Predictive models Autonomous aerial vehicles Kernel

来源：评论

学校读者我要写书评

暂无评论

Bananasqueezenet: A Very Fast, Lightweight Convolutional Neural Network for Diagnosis of Three Prominent Banana Leaf Diseases

SSRN

引用

SSRN 2023年

作者： Bhuiyan, Md Abdullahil Baki Abdullah, Hasan Muhammad Arman, Shifat E. Rahman, Sayed Saminur Al Mahmud, Kaies Department of Plant Pathology Bangabandhu Sheikh Mujibur Rahman Agricultural University Gazipur1706 Bangladesh GIS and Remote Sensing Lab Department of Agroforestry and Environment Bangabandhu Sheikh Mujibur Rahman Agricultural University Gazipur1706 Bangladesh Department of Robotics and Mechatronics Engineering University of Dhaka Dhaka1000 Bangladesh Department of Computer Science and Engineering APJ Abdul Kalam Technological University Kerala695016 India

All over the world, bananas are one of the most common fruits. It accounts for nearly 16% of global fruit production. However, every year, a large amount of banana yield losses occur due to different diseases of the banana leaf. It is essential to identify these diseases at an early stage in order to increase banana production. A visual inspection is the most common method of identifying banana leaf diseases. With visual inspection, errors are common, time is a factor, and expertise is required. This study showed how deep learning and Bayesian optimization could effectively diagnose banana leaf diseases from images without any human intervention. We collected the data from various locations in Bangladesh. The dataset consists of images of three banana leaf diseases: leaf blight, Sigatoka, and Cordana. Our proposed BananaSqueezeNet model performed exceptionally well in diagnosing banana leaf diseases from the images with an overall accuracy of 0.9625, precision of 0.9653, recall of 0.9625, specificity of 0.9875, F1-score of 0.9617, and MCC of 0.9513. The BananaSqueezeNet model outperforms three other convolutional neural networks, EfficientNetB0, MobileNetV3, and ResNet-101. BananaSqueezeNet will enable banana growers to detect banana diseases early, and we hope that it will ultimately lead to an increase in banana production in Bangladesh and around the world. © 2023, The Authors. All rights reserved.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation

arXiv

引用

arXiv 2024年

作者： Tao, Wei Zhou, Yucheng Wang, Yanlin Zhang, Hongyu Wang, Haofen Zhang, Wenqiang Shanghai Engineering Research Center of AI and Robotics Academy for Engineering and Technology Fudan University Shanghai China State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China School of Software Engineering Sun Yat-sen University Guangdong Zhuhai519082 China School of Big Data and Software Engineering Chongqing University Chongqing China College of Design and Innovation Tongji University Shanghai China Engineering Research Center of AI and Robotics Ministry of Education Academy for Engineering and Technology Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University 220 Handan Road Shanghai200433 China

Commit messages are natural language descriptions of code changes, which are important for software evolution such as code understanding and maintenance. However, previous methods are trained on the entire dataset without considering the fact that a portion of commit messages adhere to good practice (i.e., good-practice commits), while the rest do not. On the basis of our empirical study, we discover that training on good-practice commits significantly contributes to the commit message generation. Motivated by this finding, we propose a novel knowledge-aware denoising learning method called KADEL. Considering that good-practice commits constitute only a small proportion of the dataset, we align the remaining training samples with these good-practice commits. To achieve this, we propose a model that learns the commit knowledge by training on good-practice commits. This knowledge model enables supplementing more information for training samples that do not conform to good practice. However, since the supplementary information may contain noise or prediction errors, we propose a dynamic denoising training method. This method composes a distribution-aware confidence function and a dynamic distribution list, which enhances the effectiveness of the training process. Experimental results on the whole MCMD dataset demonstrate that our method overall achieves state-of-the-art performance compared with previous methods. © 2024, CC BY.

关键词： Sampling

来源：评论

学校读者我要写书评

暂无评论

Retrieve, reason, and refine: generating accurate and faithful patient instructions 22

Retrieve, reason, and refine: generating accurate and faithf...

引用

Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Fenglin Liu Bang Yang Chenyu You Xian Wu Shen Ge Zhangdaihong Liu Xu Sun Yang Yang David A. Clifton Department of Engineering Science University of Oxford School of ECE Peking University Department of Electrical Engineering Yale University Tencent JARVIS Lab China Department of Engineering Science University of Oxford and Oxford-Suzhou Centre for Advanced Research China MOE Key Lab of Computational Linguistics School of Computer Science Peking University School of Public Health Shanghai Jiao Tong University School of Medicine China

ISBN: (纸本)9781713871088

The "Patient Instruction" (PI), which contains critical instructional information provided both to carers and to the patient at the time of discharge, is essential for the patient to manage their condition outside hospital. An accurate and easy-to-follow PI can improve the self-management of patients which can in turn reduce hospital readmission rates. However, writing an appropriate PI can be extremely time-consuming for physicians, and is subject to being incomplete or error-prone for (potentially overworked) physicians. Therefore, we propose a new task that can provide an objective means of avoiding incompleteness, while reducing clinical workload: the automatic generation of the PI, which is imagined as being a document that the clinician can review, modify, and approve as necessary (rather than taking the human "out of the loop"). We build a benchmark clinical dataset and propose the Re3Writer, which imitates the working patterns of physicians to first retrieve related working experience from historical PIs written by physicians, then reason related medical knowledge. Finally, it refines the retrieved working experience and reasoned medical knowledge to extract useful information, which is used to generate the PI for previously-unseen patient according to their health records during hospitalization. Our experiments show that, using our method, the performance of five different models can be substantially boosted across all metrics, with up to 20%, 11% and 19% relative improvements in BLEU-4, ROUGE-L and METEOR, respectively. Meanwhile, we show results from human evaluations to measure the effectiveness in terms of its usefulness for clinical practice.

关键词：

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：