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Vertical load estimation in tractors via in-wheel optical sensing 20

Vertical load estimation in tractors via in-wheel optical se...

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20th IFAC symposium on System Identification (SYSID)

作者： Cestari, R. G. Lucchini, A. Leati, E. Norgia, M. Formentin, S. Savaresi, S. M. Politecn Milan Dept Elect Informat & Bioengn Milan Italy CNH Ind Milan Italy

This paper presents a novel approach for estimating the vertical load exerted on the rear axle of agricultural vehicles during fieldwork using tire compression measurements. The system comprises an optical time-of-flight (TOF) sensor integrated into the wheel rim, a microcontroller, and online identification algorithm. The sensor exhibits minimal measurement error, approximately 1%, which, when combined with effective preprocessing and a piecewise linear regression model fueled by tire pressure data, yields a root mean square error (RMSE) of around 7%, with a maximum drawdown of 3% when considering periodic updates. This technology promises to reduce production costs while enabling optimal tire pressure calibration, thereby ensuring reduced fuel consumption and improved comfort for agricultural vehicle operators. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licneses/by-nc-nd/4.0/)

关键词： Sensors and actuators system identification agricultural vehicles automation in vehicles

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Benchmarking Derivative-Free Global Optimization Methods on Variable Dimension Robotics Problems 13

Benchmarking Derivative-Free Global Optimization Methods on ...

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13th ieee Congress on Evolutionary Computation, CEC 2024

作者： Küdela, Jakub Juříček, Martin Parǎk, Roman Tzanetos, Alexandros Matoušek, Radomil Institute of Automation and Computer Science Brno University of Technology Brno Czech Republic Jönköping University Department of Computing Jönköping Sweden

ISBN: (纸本)9798350308365

Several real-world applications introduce derivativefree optimization problems, called variable dimension problems, where the problem's dimension is not known in advance. Despite their importance, no unified framework for developing, comparing, and benchmarking variable dimension problems exists. The robot arm controlling problem is a variable dimension problem where the number of joints to optimize defines the problem's dimension. For a holistic study of global optimization methods, we studied 14 representative methods from 4 different categories, i.e., (i) local search optimization techniques with random restarts, (ii) state-of-the-art DIRECT-type methods, (iii) established Evolutionary Computation approaches, and (iv) state-of-the-art Evolutionary Computation approaches. To investigate the effect of the problem's dimensionality on the solution we generated 20 instances of various combinations among the number of predefined and open decision variables, and we performed experiments for various computational budgets. The results attest that the robot arm controlling problem provides a proper benchmark for variable dimensions. Furthermore, methods in-corporating local search techniques have dominant performance for higher dimensionalities of the problem, while state-of-the-art EC methods dominate in the lower dimensionalities. © 2024 ieee.

关键词： Budget control

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An Automated Measurement Method for Deformity Parameters Required for Taylor Spatial Frame Correction 8

An Automated Measurement Method for Deformity Parameters Req...

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8th International symposium on Computer Science and Intelligent control, ISCSIC 2024

作者： Chang, Cheng Sun, Hao Guo, Xin Hebei University of Technology School of Artificial Intelligence TianJin China Hebei University of Technology School of Artificial Intelligence Control Engineering Technology Innovation Center of Hebei Province Tianjin China

ISBN: (纸本)9798350380286

An clinical practice, obtaining accurate deformity parameters of the bone is crucial for Taylor spatial frame correction of tibial deformities. The accuracy of these parameters directly affects the precision of the generated correction prescription and the success rate of the surgery. Manual measurement procedures are cumbersome, often requiring tools such as rulers and auxiliary lightboxes. Additionally, due to the constraints of two-dimensional measurements, it can be challenging to capture standard X-rays that meet the requirements in some situations. Three-dimensional automated measurements, to a certain extent, overcome the limitations arising from insufficiently favorable objective shooting conditions. Moreover, the automation of the measurement process is more advanced. To address these challenges, this study proposes an automated system for measuring tibial deformities specifically tailored for Taylor spatial frame correction. Firstly, a bone point cloud segmentation network is developed, which takes labeled tibial point clouds as input and predicts key feature points. Subsequently, the fitted tibial shaft axis is obtained by fitting these segmented feature points from multiple angles. Based on the fitting results, the deformity parameters required for Taylor spatial frame correction are computed. The measurement results obtained through this method demonstrate a high level of precision in orthopedics and significantly alleviate the workload of physicians. © 2024 ieee.

关键词： Velocity measurement

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Global-Local Adaptive Attention-Based U-Net for Single Image Deblurring

Global-Local Adaptive Attention-Based U-Net for Single Image...

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2024 China automation Congress, CAC 2024

作者： Yu, Xinran Li, Yueti Peng, Xuanzhi Wang, Chen Zou, An-Min College of Engineering Shantou University Shantou China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350368604

Image deblurring is a classical ill-posed problem aimed at recovering a clear image from a blurred one. The recent application of Transformers to image restoration tasks has significantly improved performance, thanks to their powerful long-range dependency modeling capabilities. However, the high computational cost of self-attention mechanisms limits their practical use. Additionally, the training cost for Transformer models is considerable. To address the issues of high computational cost and training cost, this paper proposes a novel Global Local Attention (GLA) mechanism that combines global and local adaptive attention. The mechanism uses 1D adaptive pooling operations to capture global context information, while fixed-size 1D pooling with different kernel sizes (7 and 11) is used to capture local details, effectively addressing both long-range dependencies and fine-grained information. Furthermore, a larger receptive field is crucial for effective image deblurring. To this end, we introduce a Feature Enhancement Module (FEM) with an expansive convolutional kernel size that serves as a bottleneck layer to further improve recovery quality. Experimental results demonstrate that our proposed model achieves competitive performance on several benchmark datasets, advancing the field of image restoration. © 2024 ieee.

关键词： Restoration

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Diffusion Ranking Scores Based Improved Hypergraph Generation Method for Visual Classification Tasks 13

Diffusion Ranking Scores Based Improved Hypergraph Generatio...

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13th ieee Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Wang, Shuai Wang, Kang Li, Xiaoli Beijing University of Technology Faculty of Information Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9798350361674

Visual classification has attracted considerable research attention in the last few decades. This paper presents an approach to improve the hypergraph structure using a diffusion ranking method and employs hypergraph neural networks for such tasks. Hyperedges are formed by connecting a set of vertices, and the generation of the hypergraph structure is typically task-dependent, making hypergraph generation methods less generalizable. Previous approaches have employed implicit hypergraphs for visual tasks, especially in visual classification, using attribute-based or neighborhood-based methods. However, these approaches cannot fully explore the global manifold structure of the feature space. To address this problem, this paper proposes a novel two-stage hypergraph construction method, which fully utilizes the ability of diffusion process to capture the manifold structure of feature data. Initially, the hypergraph structure is constructed using a neighbor-based approach, and subsequently, the final hypergraph structure is obtained by ranking scores of diffusion processes that reflect the degree of vertex similarity. Comparing with state-of-the-art hypergraph neural network algorithms on classical 3D visual image datasets, experimental results demonstrate the effectiveness of the proposed algorithm. © 2024 ieee.

关键词： Neural networks

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Data Preprocessing Method for Landslide Displacement Prediction Based on XG Boost 13

Data Preprocessing Method for Landslide Displacement Predict...

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13th ieee Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Luo, Shuang El, Xinhua Li, Xiaoli Beijing University of Technology Faculty of Information Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9798350361674

In machine learning-driven landslide prediction models, data quality directly determines the accuracy of landslide predictions. Currently, data preprocessing methods mainly involve fitting the data using moving averages or least squares methods. While these methods are effective and convenient for processing global data, they face limitations when dealing with local data during heavy rainfall events. The sharp increase in cumulative landslide displacement during significant rainfall makes it challenging for overall data preprocessing methods to effectively handle local data, leading to potential data loss and compromising data quality. To address this limitation, this paper proposes a segmented data processing approach. During periods of heavy rainfall, cubic spline interpolation is employed to interpolate missing data, providing a better representation of data variability. For smaller rainfall amounts, linear interpolation is utilized. Finally, the LOESS smoothing method is applied to further enhance data quality. These meticulous data processing steps aim to accurately capture the changing trends in rainfall-induced landslides. By providing more reliable inputs to machine learning prediction models, this approach seeks to improve the accuracy and reliability of landslide predictions. © 2024 ieee.

关键词： Data accuracy

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C-Fuzz: Fuzzing with Forced Program control Flow Jumps 22

C-Fuzz: Fuzzing with Forced Program Control Flow Jumps

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22nd ieee International symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Pan, Zhe Chen, Xu Chen, Liwei Shi, Gang Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798331509712

Fuzzing is a widely recognized and effective technique for software vulnerability detection. In recent years, significant progress has been made in bypassing complex checks, such as magic values and checksums, and improving code coverage. Increased code coverage improves the chances of discovering vulnerabilities. However, in reality, the code containing vulnerabilities constitutes only a small fraction of the entire complex program space. This means that fuzzing tools still require substantial time and computational resources to traverse the code paths that do not contain any vulnerabilities. To address this issue, we propose C-Fuzz, a novel fuzzing technique. It forcibly controls the jumps of the program's control flow during fuzzing, quickly bypassing complex checks and extensively exploring the program space. During this process, numerous crashes are discovered, and we mark these crash sites as high-risk areas. Subsequently, we use AFLGO to perform directed fuzzing on these previously stored high-risk areas to uncover more software vulnerabilities. We implemented C-Fuzz based on the traditional fuzzing tool AFL and tested it on 10 real-world programs. Experimental results show that C-Fuzz outperforms T-Fuzz and AFL in identifying unique crashes and can quickly identify vulnerability crash sites in real-world programs within 12 hours. © 2024 ieee.

关键词： Complex networks

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Model predictive control for a musculoskeletal robot with motor driven artificial muscle 4

Model predictive control for a musculoskeletal robot with mo...

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4th World Robot Conference (WRC) / symposium on Advanced Robotics and automation (SARA)

作者： Wan, Weiying Kong, Linghuan He, Wei Univ Sci & Technol Beijing Inst Artificial Intelligence Beijing 100083 Peoples R China

ISBN: (数字)9781665463690

ISBN: (纸本)9781665463690

This work develops the model predictive control (MPC) for an upper limb musculoskeletal robot model. Firstly, the numerical relationship between muscle force and bone joints is obtained, and then the control structure is designed on the basis of the joint torque and joint angles. Due to the nonlinearity of the control object, we linearize it using a feedback linearization method. Secondly, a model predictive controller is designed to obtain the linearized model. By analyzing the second-order closed-loop control system, the parameters can be adjusted to obtain a better performance. The control goal of this paper is to make a musculoskeletal robot track the desired trajectory. Simulation results verify that the designed controller is validated.

关键词： Torque Simulation Muscles Predictive models Numerical models Feedback linearization Trajectory

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Privacy-Aware Human Activity Classification using a Transformer-based Model

Privacy-Aware Human Activity Classification using a Transfor...

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ieee symposium Series on computational intelligence (ieee SSCI)

作者： Thipprachak, Khirakorn Tangamchit, Poj Lerspalungsanti, Sarawut King Mongkuts Univ Technol Thonburi Dept Comp Engn Bangkok Thailand King Mongkuts Univ Technol Thonburi Dept Control Syst & Instrumentat Engn Bangkok Thailand Natl Sci & Technol Dev Agcy Natl Met & Mat Technol Ctr Pathum Thani Thailand

ISBN: (纸本)9781665487689

Fall detection in a bathroom requires privacy as an essential issue. Ultra-wideband sensors have the ability to protect human privacy because their output has only limited information. As a result, interpreting the output is a challenging task. This research implemented a transformer model that learned time-series signals from an ultra-wideband sensor in a bathroom. First, the signals were preprocessed into the two-dimensional range-time format. Second, the range-time data were passed into a convolutional neural network encoder before going into a transformer. Third, the basic movements of humans were used for training. Finally, the encoder and the Transformer were trained separately. The model achieved good accuracy on static postures but not good on transitions due to their overlapped similarity with the static postures.

关键词： transformer-based classification ultra-wideband (UWB) human activity recognition

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Implementation of IR Lock on Poledrone (Polman Drone Education) for Precision Landing with ROS 15

Implementation of IR Lock on Poledrone (Polman Drone Educati...

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15th ieee International Conference on computational intelligence and Communication Networks, CICN 2023

作者： Khoirunnisa, Hilda Adi, Fajar Setio Mulyadewi, Anggraeni Sukarno, Setyawan Ajie Erdani, Yuliadi Anggraeni, Pipit Bandung Polytechnic for Manufacturing Department of Manufacturing Automation and Mechatronics Engineering Bandung40135 Indonesia Geotronix Pratama Indonesia Company Jakarta12440 Indonesia

ISBN: (纸本)9798350324433

Poledrone or known as quadcopter constitutes an Unmanned Aerial Vehicle (UAV) system that has four symmetrical landing rotors and has the same heights of each corner. Apart from that, Poledrone must have a good stability and be able to minimize distraction on every motion by optimizing the parameter of controller system. However, as a 6 DoF system, Poledrone has a dynamic complex with high non-linear, strong clutch and underactuated that makes it difficult to change into control algorithm. Poledrone with PID controller often suffers from overshoot causing it to be unstable which results is precision landing failure without any damage. By taking into account several strong points of PID methods, the researcher forms the implementation IR Lock with PID control on Poledrone by using ROS as the middleware. The result of result of test with IR Lock is the precision of the landing are good and the average of landing travel time is 11.073 s. But without IR-Lock The precision of the landing is quite good and the average of landing travel time is 5.84 s. This research is that the result can be used as learning aid in order to obtain accurate point more precision Poledrone landing system. So, for future work the research will combine camera with IR-Lock for making the result more accurate. © 2023 ieee.

关键词： Travel time

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