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Effects of Viscous Dissipation and Periodic Heat Flux on MHD Free Convection Channel Flow with Heat Generation

Frontiers in Heat and Mass Transfer 2024年第1期22卷 141-156页

作者： Mustafa Abdullah Robotics and Artificial Intelligence Engineering Department Faculty of EngineeringAl-Ahliyya Amman UniversityAmman19328Jordan

This study investigates the influence of periodic heat flux and viscous dissipation on magnetohydrodynamic(MHD)flow through a vertical channel with heat generation.A theoretical approach is *** channel is exposed to a perpendicular magnetic field,while one side experiences a periodic heat flow,and the other side undergoes a periodic temperature *** solutions for the governing partial differential equations are obtained using a finite difference approach,complemented by an eigenfunction expansion method for analytical *** and discussions illustrate how different variables affect the flow velocity and temperature *** offers comprehensive insights into MHD flow behavior and its interactions with the magnetic field,heat flux,viscous dissipation,and heat *** findings hold significance for engineering applications concerning fluid dynamics and heat transfer,offering valuable knowledge in this *** study concludes that the transient velocity and temperature profiles exhibit periodic patterns under periodic heat flow conditions.A temperature reduction is observed with an increase in the wall temperature phase *** contrast,an increase in the heat flux phase angle values raises the temperature values.

关键词： Magnetohydrodynamics(MHD) heat generation viscous dissipation periodic heat flux vertical channel

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Performance Analysis of Re-ID in YOLOv9 and BoT-SORT Algorithm for Multi-object Detection and Tracking

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Journal of Institute of Control, robotics and Systems 2025年第2期31卷 160-165页

作者： Young Kim, Sun Ho Kang, Chang School of Mechanical Engineering Kunsan National University Korea Republic of Department of Artificial Intelligence and Robotics Sejong University Korea Republic of

This paper proposes a method for integrating YOLOv9 and BoT-SORT algorithms for multi-object tracking in a multi-camera environment. Particularly, it focuses on analyzing the impact of re-identification (Re-ID) techniques on the overall tracking system performance. Three Re-ID methods-MobileNetV2, OSNet, and OSNet-AIN-are evaluated using the MSMT17 dataset and then applied to the BoT-SORT algorithm to compare multi-object tracking performances. Experimental results show that BoT-SORT with OSNet-AIN achieves the best performance in HOTA, MOTA, and IDF1 metrics. This demonstrates that effective Re-ID techniques can significantly contribute to improving object tracking performance in complex real-world environments. © ICROS 2025.

关键词： Object detection

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Overview on the Development of Input Shaping Control for Removing Residual Vibrations

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Journal of Institute of Control, robotics and Systems 2024年第4期30卷 296-311页

作者： Kang, Brian Byunghyun Kang, Chul-Goo Department of Artificial Intelligence and Robotics Sejong University Seoul Korea Republic of Department of Mechanical Engineering Konkuk University Seoul Korea Republic of

Eliminating unwanted residual vibration is crucial in engineering systems, and this removal should be as effective and swift as possible. Input shaping control emerges as a powerful open-loop control technique to effectively eliminate residual vibrations, and it can be readily implemented in real-world engineering applications. This paper delves into the historical developments of input shaping control over the past seven decades. A key issue in input shaping control has been achieving robustness against modeling errors in both natural frequency and damping ratio. Input shaping control originated in the late 1950s under the name of posicast control. Subsequently, in the late 1980s, its robustness was significantly enhanced by incorporating derivative constraints and allowing nonzero residual vibration at no modeling error. These advancements have paved the way for the widespread application of input shaping control in various engineering problems. In 2019, impulse vectors were introduced as a mathematical tool for designing and analyzing input shapers, leading to the development of new input shapers using impulse vectors. This paper presents a comprehensive overview of the development of input shaping control, including zero-vibration and derivative (ZVD), extra-insensitive (EI), multi-mode, equal time and magnitude (ETM), unity-magnitude (UM), and negative equal-magnitude (NEM) shapers. © 2024, Institute of Control, robotics and Systems. All rights reserved.

关键词： Robustness (control systems)

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Grasp Detection with Hierarchical Multi-Scale Feature Fusion and Inverted Shuffle Residual

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Tsinghua Science and Technology 2024年第1期29卷 244-256页

作者： Wenjie Geng Zhiqiang Cao Peiyu Guan Fengshui Jing Min Tan Junzhi Yu State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Grasp detection plays a critical role for robot *** pixel-wise grasp detection networks with encoder-decoder structure receive much attention due to good accuracy and ***,they usually transmit the high-level feature in the encoder to the decoder,and low-level features are *** is noted that low-level features contain abundant detail information,and how to fully exploit low-level features remains ***,the channel information in high-level feature is also not well ***,the performance of grasp detection is *** solve these problems,we propose a grasp detection network with hierarchical multi-scale feature fusion and inverted shuffle *** low-level and high-level features in the encoder are firstly fused by the designed skip connections with attention module,and the fused information is then propagated to corresponding layers of the decoder for in-depth feature *** a hierarchical fusion guarantees the quality of grasp ***,an inverted shuffle residual module is created,where the high-level feature from encoder is split in channel and the resultant split features are processed in their respective *** such differentiation processing,more high-dimensional channel information is kept,which enhances the representation ability of the ***,an information enhancement module is added before the encoder to reinforce input *** proposed method attains 98.9%and 97.8%in image-wise and object-wise accuracy on the Cornell grasping dataset,respectively,and the experimental results verify the effectiveness of the method.

关键词： grasp detection hierarchical multi-scale feature fusion skip connections with attention inverted shuffle residual

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Vision‐audio fusion SLAM in dynamic environments

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CAAI Transactions on intelligence Technology 2023年第4期8卷 1364-1373页

作者： Tianwei Zhang Huayan Zhang Xiaofei Li Shenzhen Institute of Artificial Intelligence and Robotics for Society ShenzhenChina Department of Robotics Ritsumeikan UniversityShigaJapan Westlake University and Westlake Institute for Advanced Study HangzhouChina

Moving humans,agents,and subjects bring many challenges to robot self‐localisation and environment *** adapt to dynamic environments,SLAM researchers typically apply several deep learning image segmentation models to eliminate these moving ***,these moving obstacle segmentation methods cost too much computation resource for the onboard processing of mobile *** the current industrial environment,mobile robot collaboration scenario,the noise of mobile robots could be easily found by on‐board audio‐sensing processors and the direction of sound sources can be effectively acquired by sound source estimation algorithms,but the distance estimation of sound sources is ***,in the field of visual perception,the 3D structure information of the scene is relatively easy to obtain,but the recognition and segmentation of moving objects is more *** address these problems,a novel vision‐audio fusion method that combines sound source localisation methods with a visual SLAM scheme is proposed,thereby eliminating the effect of dynamic obstacles on multi‐agent *** heterogeneous robots experiments in different dynamic scenes indicate very stable self‐localisation and environment reconstruction performance of our method.

关键词： dynamic environment intelligent robots sensor fusion

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Advancements and Performance Analysis of Feature Detection and Matching Methods in Visual Odometry

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Journal of Institute of Control, robotics and Systems 2025年第3期31卷 231-236页

作者： Choi, Ji Hun Kang, Chang Ho Kim, Sun Young Department of Artificial Intelligence Sejong University Korea Republic of Department of AI Robotics Sejong University Korea Republic of School of Mechanical Engineering Kunsan National University Korea Republic of

This study presents a comprehensive performance analysis of feature detectors and descriptors in visual odometry (VO) based on four key metrics: absolute trajectory error (ATE), relative pose error (RPE), cumulative drift, and frames per second (FPS). Five algorithm-based methods (SIFT, ROOTSIFT, ORB, KAZE, and AKAZE) and five AI-based methods (SuperPoint, DISK, ALIKED, D2NET, and Xfeat) are evaluated using two matching strategies: Brute-Force and LIGHTGLUE. Performance assessment is conducted on the KITTI dataset, demonstrating that KAZE achieves the best results in ATE and cumulative drift, while ALIKED outperforms in RPE and FPS. These findings offer valuable insights for selecting the optimal feature detection and description techniques in real-world VO applications. © ICROS 2025.

关键词： Deep learning

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Data Augmentation via Face Morphing for Recognizing Intensities of Facial Emotions

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IEEE Transactions on Affective Computing 2023年第2期14卷 1228-1235页

作者： Huang, Tsung-Ren Hsu, Shin-Min Fu, Li-Chen National Taiwan University Department of Psychology Center for Artificial Intelligence & Advanced Robotics Taipei106319 Taiwan National Taiwan University Center for Artificial Intelligence & Advanced Robotics Department of Electrical Engineering Department of Computer Science and Information Engineering Taipei106319 Taiwan

Being able to recognize emotional intensity is a desirable feature for a facial emotional recognition (FER) system. However, the development of such a feature is hindered by the paucity of intensity-labeled data for model training. To ameliorate the situation, the present study proposes using face morphing as a novel way of data augmentation to synthesize faces that express different degrees of a designated emotion. Such an approach has been successfully validated on humans and machines. Specifically, humans indeed perceived different levels of intensified emotions in these parametrically synthesized faces, and FER systems based on neural networks indeed showed improved sensitivities to intensities of different emotions when additionally trained on the synthesized faces. Overall, the proposed data augmentation method is not only simple and effective but also useful for building FER systems that recognize facial expressions of mixed emotions. © 2010-2012 IEEE.

关键词： Face recognition

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Few-Shot Object Detection via Dual-Domain Feature Fusion and Patch-Level Attention

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1237-1250页

作者： Guangli Ren Jierui Liu Mengyao Wang Peiyu Guan Zhiqiang Cao Junzhi Yu State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics Peking UniversityBeijing 100871China

Few-shot object detection receives much attention with the ability to detect novel class objects using limited annotated *** transfer learning-based solution becomes popular due to its simple training with good accuracy,however,it is still challenging to enrich the feature diversity during the training *** fine-grained features are also insufficient for novel class *** deal with the problems,this paper proposes a novel few-shot object detection method based on dual-domain feature fusion and patch-level *** original base domain,an elementary domain with more category-agnostic features is superposed to construct a two-stream backbone,which benefits to enrich the feature *** better integrate various features,a dual-domain feature fusion is designed,where the feature pairs with the same size are complementarily fused to extract more discriminative ***,a patch-wise feature refinement termed as patch-level attention is presented to mine internal relations among the patches,which enhances the adaptability to novel *** addition,a weighted classification loss is given to assist the fine-tuning of the classifier by combining extra features from FPN of the base training *** this way,the few-shot detection quality to novel class objects is *** on PASCAL VOC and MS COCO datasets verify the effectiveness of the method.

关键词： few-shot object detection dual-domain feature fusion patch-level attention

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Complex environment localization system using complementary ceiling and ground map information

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Autonomous Robots 2023年第6期47卷 669-683页

作者： Yu, Chee-An Chen, Hao-Yun Wang, Chun-Chieh Fu, Li-Chen Department of Electrical Engineering National Taiwan University Taipei Taiwan NTU Center for Artificial Intelligence and Advanced Robotics Taipei Taiwan

This paper proposes a robust localization system using complementary information extracted from ceiling and ground plans, particularly applicable to dynamic and complex environments. The ceiling perception provides the robot with stable and time-invariant environmental features independent of the dynamic changes on the ground, whereas the ground perception allows the robot to navigate in the ground plane while avoiding stationary obstacles. We propose an architecture to fuse ground 2D LiDAR scan and ceiling 3D LiDAR scan with our enhanced mapping algorithm associating perception from both sources efficiently. The localization ability and the navigation performance can be promisingly secured even in a harsh environment with our complementary sensed information from the ground and ceiling. The salient feature of our work is that our system can simultaneously map both the ceiling and ground plane efficiently without extra efforts of deploying articulated landmarks and apply such hybrid information effectively, which facilitates the robot to travel through any indoor environment with human crowds without getting lost. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Ceilings

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Classification of Jackfruit Species Using Deep Learning Model 2

Classification of Jackfruit Species Using Deep Learning Mode...

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2nd IEEE International Conference on Recent Advances in Information Technology for Sustainable Development, ICRAIS 2024

作者： Veeresha, R.K. Karegoudra, Shilpa Kumar, Bhavin Pavan, Pavan Department of Robotics and Artificial Intelligence Udupi574110 India Department of Computer Science and Engineering Udupi574110 India

ISBN: (纸本)9798350354461

Identifying Jackfruit spices using a deep learning model involves leveraging advanced neural network architectures to classify spices accurately. The model is trained on a dataset containing images of various spices commonly used with Jackfruit, such as deng surya, manmohan, prakashchandra, vietnamearly, and others. Through multiple layers of convolutional neural networks (CNNs) and possibly recurrent neural networks (RNNs), the model learns intricate patterns and features within the images to differentiate between different species. Transfer learning techniques might also be employed to adapt pre-trained models to the specific task of spice identification. The model's performance is evaluated on a separate test dataset to measure its accuracy, precision, recall, and F1 score. The paper provides a comprehensive overview of the deep learning approach to identifying Jackfruit spices, highlighting its potential applications in culinary research, food industry automation, and dietary analysis. © 2024 IEEE.

关键词： Convolutional neural networks

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