检索结果-内蒙古大学图书馆

IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)

作者： Giuseppe De Simone Luca Greco Alessia Saggese Mario Vento Department of Information and Electrical Engineering and Applied Mathematics (DIEM) University of Salerno Salerno Italy

ISBN: (数字)9798331516857

ISBN: (纸本)9798331516864

In order to increase the social acceptability of social robots, it is important to foster more natural and effective interactions. To achieve this aim, the robot needs to be equipped with Multi-Engagement capabilities, so as to understand if and when people in the scene want to interact with the robot and to detect specifically who wants to interact. In order to face this challenge, in this paper we propose a multimodal architecture, exploiting both audio and video modalities, combining a deep learning based head pose estimator with an active speaker detector. The engagement is thus modeled through a Behavior Tree, which takes into account the history of the engagements with users and decides accordingly for an appropriate behavior of the robot. The proposed architecture has been integrated into a social robot within a ROS framework, running directly on board of an embedded NVIDIA Jetson device. Furthermore, the experimental results confirm that it is able to achieve an F-Score of 0.82 over the widely adopted UE-HRI dataset. Additionally, the system’s human-robot interaction capabilities were assessed by collecting surveys in real-world settings, which indicated a positive impact on user engagement and interaction quality.

关键词： Surveys Deep learning Social robots Detectors Programming User experience Dynamic programming History Robots Faces

来源：评论

学校读者我要写书评

暂无评论

Adaptive Prescribed Time Path Following Controller for Underactuated Surface Vessels 13

Adaptive Prescribed Time Path Following Controller for Under...

引用

13th International Conference on Intelligent Control and Information Processing, ICICIP 2025

作者： Ghommam, Jawhar Saad, Maarouf Zhu, Quanmin Rahman, Mohammed H. Dept. of Electrical and Computer Engineering Sultan Qaboos University Muscat Oman Dept. of Electrical Engineering Ecole de Technologie Superieure Montreal Canada Dept. of Engineering Design and Mathematics University of the West of England Bristol United Kingdom Mechanical Engineering Department University of Wisconsin-Milwaukee Wisconsin United States

ISBN: (纸本)9798331516147

Heading control of marine vehicles is an important issue in navigation and control engineering. This paper investigates the design of a prescribed-time robust adaptive path following control problem of an underactuated surface vessel with parametric uncertainties, unknown disturbances and control input constraints. The establishment of prescribed-time property consists of a prescribed-time regulation of the steering control systems and novel prescribed-time Line of Sight (LOS) guidance control, both of which satisfy the prescribed-time requirement. The feasibility of separate independent control design for the steering and the guidance control systems is guaranteed through the development of new results on nonlinear prescribed-time cascade systems with non-vanishing uncertainties. The Lyapunov method is employed to show that the equilibrium point of the whole system is prescribed-time input to state stable. Numerical simulations are carried out to validate the performance of the proposed control strategy. © 2025 IEEE.

关键词： Steering

来源：评论

学校读者我要写书评

暂无评论

Towards Trustworthy and Explainable Socially Assistive Robots: A Cognitive Architecture for Dietary Guidance

Towards Trustworthy and Explainable Socially Assistive Robot...

引用

2025 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots, SIMPAR 2025

作者： D'Arco, Luigi Raggioli, Luca Randazzo, Gianni De Gasperis, Giovanni Chella, Antonio Costantini, Stefania Rossi, Silvia University of Naples Federico Ii Department of Electrical Engineering and Information Technologies Naples Italy University of Palermo Department of Engineering Palermo Italy Università Degli Studi Dell'Aquila Department of Information Engineering Computer Science and Mathematics L'Aquila Italy

ISBN: (纸本)9798331516857

Socially Assistive Robots (SARs) are rising as promising tools for promoting healthy lifestyle habits. To achieve such a goal, it is necessary that they are able to perform trustworthy and legible behaviors. In this work, we propose a cognitive architecture that integrates multimodal perception, symbolic reasoning, memory-enhanced decision-making, and adaptive interaction strategies to create an explainable and engaging dietary assistant. The key idea is to provide the robot with the capability to iteratively interact with a user and adapt the dietary plan based on their current state, preferences, and food restrictions, while conveying explicitly the inner decision and thought process. To achieve this, we employ a graph-enhanced Large Language Model (LLM), which queries contextual, semantic, and episodic acquired knowledge to generate personalized meal recommendations. These must subsequently be refined through a verification process that enforces constraints such as caloric limits and ingredient intolerances, ensuring dietary adherence. To have a transparent decision-verification process, the robot has to progressively verbalize the reasoning process while providing justifications for the recommendations to also enhance the user's trust. Non-verbal context-relevant movements are also generated to allow the robot to express empathy. We expect our framework to increase user trust, engagement, and adherence to healthy behaviors, allowing SARs to function as credible and effective health assistants. © 2025 IEEE.

关键词： Nutrition

来源：评论

学校读者我要写书评

暂无评论

Quantifying Public Response to COVID-19 Events: Introducing the Community Sentiment and Engagement Index 15

Quantifying Public Response to COVID-19 Events: Introducing ...

引用

15th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2025

作者： Thakur, Nirmalya Patel, Kesha A. Poon, Audrey Cui, Shuqi Azizi, Nazif Shah, Rishika Shah, Riyan South Dakota School of Mines and Technology Department of Electrical Engineering and Computer Science Rapid CitySD57701 United States Emory University Department of Mathematics AtlantaGA30322 United States Emory University Department of Computer Science AtlantaGA30322 United States

ISBN: (纸本)9798331507695

This study introduces the Community Sentiment and Engagement Index (CSEI)., developed to capture nuanced public sentiment and engagement variations on social media, particularly in response to major events related to COVID-19. Constructed with diverse sentiment indicators, CSEI integrates features like engagement, daily post count, compound sentiment, fine-grain sentiments (fear, surprise, joy, sadness, anger, disgust, and neutral), readability, offensiveness, and domain diversity. Each component is systematically weighted through a multi-step Principal Component Analysis (PCA)-based framework, prioritizing features according to their variance contributions across temporal sentiment shifts. This approach dynamically adjusts component importance, enabling CSEI to precisely capture high-sensitivity shifts in public sentiment. CSEI's development showed statistically significant correlations with its constituent features, underscoring internal consistency and sensitivity to specific sentiment dimensions. CSEI's responsiveness was validated using a dataset of 4,510,178 Reddit posts about COVID-19. The analysis focused on 15 major events, including the WHO's declaration of COVID-19 as a pandemic, the first reported cases of COVID-19 across different countries, nationallockdowns, vaccine developments, and crucial public health measures. Cumulative changes in CSEI revealed prominent peaks and valleys aligned with these events, indicating significant patterns in public sentiment across different phases of the pandemic. Pearson correlation analysis further confirmed a statistically significant relationship between CSEI daily fluctuations and these events (p = 0.0428), highlighting CSEI's capacity to infer and interpret the shifts in public sentiment and engagement in response to major events related to COVID-19. © 2025 IEEE.

关键词： Spatio-temporal data

来源：评论

学校读者我要写书评

暂无评论

Education 4.0: Considering the Development of Teachers’ Psychological Dispositions Towards the Use of ICT with Kindergarten Children 14th

Education 4.0: Considering the Development of Teachers’ P...

引用

14th International Conference on Methodologies and Intelligent Systems for Technology Enhanced Learning, mis4TEL 2024

作者： Peretti, Sara Caruso, Federica Pino, Maria Chiara Di Mascio, Tania Centre of Excellence DEWS University of L’Aquila L’Aquila Italy Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Department of Biotechnological and Applied Clinical Sciences L’Aquila Italy

ISBN: (纸本)9783031855603

Since 2020, the COVID-19 pandemic has forced teachers to rapidly adopt Information and Communication Technology (ICT) tools for distance learning, transforming education into an all-digital environment. This shift posed significant challenges, especially for kindergarten teachers accustomed to traditional, face-to-face methods. These changes will have long-term impacts on education, influencing teachers’ attitudes and beliefs, which take time to stabilize and evaluate. The present paper addresses this by posing the question: In 2024, four years after the COVID-19 pandemic, what attitudes have kindergarten teachers developed towards ICT integration in the classroom? For this purpose, the standardized "Intrapersonal Technology Integration Scale" was chosen to assess the beliefs of Italian kindergarten teachers. The study includes 49 kindergarten teachers, all women. Data analysis showed that they have a strong interest in using ICT, indicating a need for ongoing support and training initiatives. However, teachers did not report feeling self-efficacy in using ICT with children in the classroom. This finding is crucial as it can influence their expectations and motivation towards integrating these technologies into daily teaching activities. In conclusion, this study highlights the critical importance of teachers’ attitudes in shaping future learning environments within the Education 4.0 era and provides suggestions to maximize ICT integration starting from early education to better meet the needs of future citizens. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Teaching

来源：评论

学校读者我要写书评

暂无评论

Invisible Servoing: A Visual Servoing Approach with Return-Conditioned Latent Diffusion

Invisible Servoing: A Visual Servoing Approach with Return-C...

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Bishoy Gerges Barbara Bazzana Nicolò Botteghi Youssef Aboudorra Antonio Franchi Robotics and Mechatronics group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede The Netherlands Department of Applied Mathematics University of Twente Enschede The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

In this paper, we present a novel visual servoing (VS) approach based on latent Denoising Diffusion Probabilistic Models (DDPMs), that explores the application of generative models for vision-based navigation of UAVs (Uncrewed Aerial Vehicles). Opposite to classical VS methods, the proposed approach allows reaching the desired target view, even when the target is initially not visible. This is possible thanks to the learning of a latent representation that the DDPM uses for planning and a dataset of trajectories encompassing target-invisible initial views. A compact representation is learned from raw images using a Cross-Modal Variational Autoencoder. Given the current image, the DDPM generates trajectories in the latent space driving the robotic platform to the desired visual target. The approach has been validated in simulation using two generic multi-rotor UAVs (a quadrotor and a hexarotor). The results show that we can successfully reach the visual target, even if not visible in the initial view. A video summary with simulations can be found in: https://***/2Hb3nkkcszE.

关键词： Location awareness Visualization Pipelines Noise reduction Autonomous aerial vehicles Visual servoing Trajectory Planning Standards Robots

来源：评论

学校读者我要写书评

暂无评论

Wheel Arrangement of a Rocker-bogie Mechanism with Omni-directional Wheels for Reduced DOF Design

Wheel Arrangement of a Rocker-bogie Mechanism with Omni-dire...

引用

2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Tokudome, Yusuke Yamamoto, Yuya Watanabe, Yuta Uahchinkul, Chinvudh Muramatsu, Satoshi Inagaki, Katsuhiko Tokai University Course of Electrical and Electronic Engineering Kanagawa259-1292 Japan Tokai University Course of Science and Technology Kanagawa259-1292 Japan Tokai University Department of Applied Computer Engineering Kanagawa259-1292 Japan

ISBN: (纸本)9798331531614

Wheeled mobile mechanisms are essentially unsuitable for moving over rough terrain, but the rocker bogie mechanism is known as a six-wheeled mobile mechanism with high ground adaptability that solves this problem. However, this mechanism requires a large number of degrees of freedom (DOF), at least 10 DOF, or 12 DOF in the case of an omni-directional moving function. This contains problems in terms of control system configuration, mechanism development, and energy efficiency. In this study, the number of DOFs is reduced to a maximum of 6 DOFs and a minimum of 4 DOFs by applying omni-directional wheels to the rocker bogie mechanism. First, we examined how the two main types of omni-directional wheels should be arranged in relation to the six wheels. Based on the results, an actual machine was developed for evaluation, and its effectiveness was confirmed through step over experiment on several types of stairs. © 2025 IEEE.

关键词： Bogies (railroad rolling stock)

来源：评论

学校读者我要写书评

暂无评论

Advanced Computational Modeling for Brain Tumor Detection:Enhancing Segmentation Accuracy Using ICA-Ⅰ and ICA-Ⅱ Techniques

引用

computer Modeling in engineering & Sciences 2025年第4期143卷 255-287页

作者： Abdullah A Asiri Toufique A.Soomro Ahmed Ali Faisal Bin Ubaid Muhammad Irfan Khlood M.Mehdar Magbool Alelyani Mohammed S.Alshuhri Ahmad Joman Alghamdi Sultan Alamri Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Artificial Intelligence and Cyber Futures Institute Charles UniversityBathurstNSW 2795Australia Department of Electronic Engineering The University of LarkanoLarkana75660Pakistan Electrical Engineering Department Sukkur IBA UniversitySukkur65200Pakistan Computer Science Department Sukkur IBA UniversitySukkur65200Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajran61441Saudi Arabia Department of Radiological Sciences College of Applied Medical ScienceKing Khalid UniversityGuraigerAbha62521Saudi Arabia Radiology andMedical Imaging Department College of AppliedMedical SciencesPrince Sattam bin Abdulaziz UniversityKharj11942Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesTaif UniversityTaif21944Saudi Arabia

Global mortality rates are greatly impacted by malignancies of the brain and nervous ***,Magnetic Resonance Imaging(MRI)plays a pivotal role in detecting brain tumors;however,manual assessment is time-consuming and susceptible to human *** address this,we introduce ICA2-SVM,an advanced computational framework integrating Independent Component Analysis Architecture-2(ICA2)and Support Vector Machine(SVM)for automated tumor segmentation and ***2 is utilized for image preprocessing and optimization,enhancing MRI consistency and *** Fast-MarchingMethod(FMM)is employed to delineate tumor regions,followed by SVM for precise *** on the Contrast-Enhanced Magnetic Resonance Imaging(CEMRI)dataset demonstrates the superior performance of ICA2-SVM,achieving a Dice Similarity Coefficient(DSC)of 0.974,accuracy of 0.992,specificity of 0.99,and sensitivity of ***,themodel surpasses existing approaches in computational efficiency,completing analysis within 0.41 *** integrating state-of-the-art computational techniques,ICA2-SVM advances biomedical imaging,offering a highly accurate and efficient solution for brain tumor *** research aims to incorporate multi-physics modeling and diverse classifiers to further enhance the adaptability and applicability of brain tumor diagnostic systems.

关键词： Brain image segmentation MR brain enhancement independent component analysis brain tumor

来源：评论

学校读者我要写书评

暂无评论

Badminton Footwork Practice via an Immersive Virtual Reality System 31st

Badminton Footwork Practice via an Immersive Virtual Reali...

引用

31st International Conference on Multimedia Modeling, MMM 2025

作者： Jheng, Duen-Chian Harchan, Bill Louis Kostka de Sztemberg, Berenika Nawoja Hsu, Jen-Hao Hu, Min-Chun Department of Computer Science National Tsing Hua University Hsinchu Taiwan College of Electrical Engineering and Computer Science National Tsing Hua University Hsinchu Taiwan Department of Mathematics and Computer Science Adam Mickiewicz University Poznan Poland Physical Education Office National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)9789819620739

Amateur badminton players often struggle with reaching shots due to inadequate footwork, especially when dealing with fast attacks to the front court, such as drop shots. To address this issue, this research proposes leveraging Virtual Reality (VR) to create a training system focusing on improving badminton footwork. By using a VR headset and motion trackers, the system provides users with professional-level footwork training, ensuring that they practice the correct techniques and enhance their ability to respond effectively to drop shots. The demonstration video is available at https://***/MUvWCKcu6OU. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Virtual environments

来源：评论

学校读者我要写书评

暂无评论

Pose Estimation of Spacecraft Using Dual Transformers and Efficient Bayesian Hyperparameter Optimization

引用

International Journal of Advanced computer Science and Applications 2025年第4期16卷 629-644页

作者： Raja, N. Kannaiya Ramesh, Janjhyam Venkata Naga El-Ebiary, Yousef A. Baker Muniyandy, Elangovan Reddy, N. Konda Kumar, Vanipenta Ravi Devarasetty, Prasad School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh Bhopal466114 India Department of CSE Graphic Era Hill University Dehradun248002 India Department of CSE Graphic Era Deemed To Be University Uttarakhand Dehradun248002 India Faculty of Informatics and Computing UniSZA University Malaysia Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602 105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Engineering Mathematics K L University Greenfields Guntur Dist Andhra Pradesh Vaddeswaram522302 India Department of Mathematics Annamacharya University New Boyanapalli Rajampet India Department of Computer Science and Engineering DVR & Dr HS MIC College of Technology Andhra Pradesh Kanchikacherla India

Spacecraft pose estimation is an essential contribution to facilitating central space mission activities like autonomous navigation, rendezvous, docking, and on-orbit servicing. Nonetheless, methods like Convolutional Neural Networks (CNNs), Simultaneous Localization and Mapping (SLAM), and Particle Filtering suffer significant drawbacks when implemented in space. Such techniques tend to have high computational complexity, low domain generalization capacity for varied or unknown conditions (domain generalization problem), and accuracy loss with noise from the space environment causes such as fluctuating lighting, sensor limitations, and background interference. In order to overcome these challenges, this study suggests a new solution through the combination of a Dual-Channel Transformer Network with Bayesian Optimization methods. The innovation is at the center with the utilization of EfficientNet, augmented with squeeze-and-excitation attention modules, to extract feature-rich representations without sacrificing computational efficiency. The dual-channel architecture dissects satellite pose estimation into two dedicated streams—translational data prediction and orientation estimation via quaternion-based activation functions for rotational precision. Activation maps are transformed into transformer-compatible sequences via 1×1 convolutions, allowing successful learning in the transformer's encoder-decoder system. To maximize model performance, Bayesian Optimization with Gaussian Process Regression and the Upper Confidence Bound (UCB) acquisition function makes the optimal hyperparameter selection with fewer queries, conserving time and resources. This entire framework, used here in Python and verified with the SLAB Satellite Pose Estimation Challenge dataset, had an outstanding Mean IOU of 0.9610, reflecting higher accuracy compared to standard models. In total, this research sets a new standard for spacecraft pose estimation, by marrying the versatility of deep le

关键词： Convolutional neural networks

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：