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future-Proofing Small Schools: Rethinking Education with AI

Future-Proofing Small Schools: Rethinking Education with AI

引用

17th International conference on computer Supported Education, CSEDU 2025

作者： Mangione, Giuseppina Rita Jose De Santis, Francesca Zampolini, Lydia Gentile, Manuel INDIRE Firenze Italy ITD/CNR Palermo Italy

ISBN: (纸本)9789897587467

This study investigates the transformative role of Artificial Intelligence (AI) in revitalising teaching practices in small and rural schools, addressing their unique challenges. Combining a systematic literature review and a participatory imagination lab (workshop) with Italian teachers, the research adopts a dual methodological approach. The review identifies key focus areas for action, emphasising how AI can address critical issues in "non-standard" educational contexts such as multigrade classrooms, teacher turnover, and geographical isolation. The imagination lab complements this by exploring how these challenges are recognised in the Italian context and what solutions are envisioned using technology cards. This participatory methodology enables the co-design of potential AI-driven strategies tailored to real-world scenarios. The study underscores the significance of small schools as unique laboratories for educational innovation, highlighting the replicability and scalability of this approach. Extending such methods to a broader network of small schools offers the potential to refine technological solutions, develop tailored intervention clusters, and foster evidence-based, scalable policies for equitable and resilient education in similar contexts worldwide. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Teaching

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Gesture control systems in Human Prohibited Areas

Gesture Control Systems in Human Prohibited Areas

引用

Computing for Sustainability and Intelligent future (COMP-SIF), International conference on

作者： Omsai Kongara Ravi Kumar B N Rohan DJ Mohan Kumar Reddy Narendra Kumar E BMS Institute of Technology & Management Bangalore India

ISBN: (数字)9798331538538

ISBN: (纸本)9798331538545

With the use of sophisticated movement monitoring, computer vision, and artificial intelligence algorithms, gesture control systems transform interactions in environments that pose a threat to human safety. These solutions guarantee efficiency and safety while making it simpler to operate the gadget without using physical contact. They have difficulties in hazardous areas where human exposure poses concerns, such as nuclear power plants, military installations, and industrial locations. In order to improve operational safety and availability, the inquiry focuses on creating a scalable and economical solution for the dynamic environment that can be customized. This solution should provide high accuracy and sensitivity in real time.

关键词： computer vision Sensitivity Tracking Transforms control systems Real-time systems Safety Sustainable development Power generation Monitoring

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A Fully Sparse Detector with Cascade Heads for LiDAR-based 3D Object Detection 13

A Fully Sparse Detector with Cascade Heads for LiDAR-based 3...

引用

13th International conference on Intelligent control and Information Processing, ICICIP 2025

作者： Chen, Junnan Zhang, Gang Hu, Xiaolin Zeng, Zhigang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Department of Computer Science and Technology Institute for AI BNRist THU-Bosch JCML Center Tsinghua Universigy Beijing China

ISBN: (纸本)9798331516147

LiDAR-based 3D object detection is a critical component of perception systems in autonomous driving. Existing detectors typically rely on dense feature maps for 3D object prediction. However, as the perception range expands, the computational overhead associated with dense feature maps increases quadratically, creating significant challenges for scaling to long-range detection scenarios. To address this issue, fully sparse detectors have recently been proposed, but they often suffer from suboptimal performance or excessively complex architectures. In this paper, we present CHNet, a fully sparse detector designed to overcome these limitations by introducing a cascade head module, which consists of two sequential heads. By generating coarse object predictions, creating new feature points based on centers of the predicted objects, and aggregating features of the entire object to these new center points, CHNet enhances the qualities of object feature representations, achieving higher detection performance. Notably, CHNet effectively addresses the center feature missing problem in LiDAR-based 3D object detection by adding at most a hundred new feature points, offering a potential avenue for future research. On the widely used Waymo Open and Argoverse2 datasets, CHNet achieves impressive results without any additional embellishments. © 2025 IEEE.

关键词： Object recognition

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Leveraging Contracts for Failure Monitoring and Identification in Automated Driving systems 22nd

Leveraging Contracts for Failure Monitoring and Identifica...

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22nd International conference on Software Engineering and Formal Methods, SEFM 2024

作者： Goyal, Srajan Griggio, Alberto Tonetta, Stefano Fondazione Bruno Kessler Trento Italy University of Trento Trento Italy

ISBN: (纸本)9783031773815

As the deployment of AI agents in Automated Driving systems (ADS) becomes increasingly prevalent, ensuring their safety and reliability is of paramount importance. This paper presents a novel approach to enhance the safety assurance of automated driving systems by employing formal contracts to specify and refine system-level properties. The proposed framework leverages formal methods to specify contracts that capture the expected behavior of perception and control components in ADS. These contracts serve as a basis for systematically validating system behavior against safety requirements during design and testing phases. We demonstrate the efficacy of our approach using the CARLA simulator and an off-the-shelf AI agent. By monitoring the components contracts on the ADS simulation, we could identify not only the cause of system failures, but also the situations which could lead to a system failure, facilitating the debugging and maintenance of the AI agents. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Artificial intelligence

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A Survey on Recognizing Lower Limb Movements from Surface Electromyography(sEMG) Signals 1

A Survey on Recognizing Lower Limb Movements from Surface El...

引用

1st International conference on AIML-Applications for Engineering and Technology, ICAET 2025

作者： Pandharikar, Atharva Jahagirdar, Aditi Dr. Vishwanath Karad MIT World Peace University Department of Computer Engineering and Technology Pune India

ISBN: (纸本)9798350355611

The paper presents a comprehensive framework for recognizing lower limb movements using surface electromyography (sEMG) signals, addressing the growing need for effective human activity recognition (HAR) systems in healthcare and rehabilitation. The study explores various machine learning and deep learning algorithms including Random Forest, Support Vector Machine (SVM), and hybrid models like CNN-LSTM, PC-GNN (Pearson Correlation-based Graph Neural Network) to classify movements based on sEMG sensors data collected from multiple muscles during distinct lower limb activities. The study focuses on important signal processing methods including wavelet denoising and time-domain feature extraction to improve classification accuracy. Challenges such as electrode displacement, muscle fatigue, and inter-subject variability are addressed. The suggested techniques for classifying sEMG signals outperform conventional methods, as shown by performance metrics. The results highlight how important precise sEMG signal analysis is for applications in prosthetic control, rehabilitation, and human-machine interaction. This research aims to advance the understanding of sEMG signal analysis and its practical implications for real-time human activity recognition. future work will focus on improving model robustness for practical implementation. © 2025 IEEE.

关键词： Decision trees

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Perceptions and Acceptability of Sensor-Based Activity Recognition systems Among Older Adults and Their Families 11

Perceptions and Acceptability of Sensor-Based Activity Recog...

引用

11th International conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2025

作者： Díaz-Jiménez, David López, José L. Flores-Avilés, Francisco J. Espinilla, Macarena University of Jaén Department of Computer Sciences Spain

ISBN: (纸本)9789897587436

This paper examines activity recognition systems that use sensor devices with specific activity models. It presents a new system that combines motion, open/close, and ambient sensors with wristband devices and location beacons. Alongside a detailed review of the system, the study also explores the views of two main groups of users: older adults and their family members. Although related studies exist, this research introduces the system and thoroughly analyzes user feedback. An important aspect is the acknowledgment of improvements in sensor-based smart devices, especially in terms of size and subtlety compared to earlier bracelet designs. This study included 40 anonymous participants who tested these system and key factors analyzed include acceptability, safety, peace of mind, privacy, quality of life, autonomy, trust, perceived social support, loneliness, and economic cost. This assessment offers useful insights into how users perceive and accept the system, to understand the main concerns with commonly used devices like cameras and sensors helps identify which devices older adults might be open to using in their routines. These insights are expected to guide the development of future systems that better address user needs. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Pattern recognition systems

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AI Virtual Mouse: Revolutionizing Human–computer Interaction 6th

AI Virtual Mouse: Revolutionizing Human–computer Interactio...

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6th International conference on Intelligent Communication, control and Devices, ICICCD 2024

作者： Sanka, Deekshitha Bezawada, Akash Alla, Sai Tarun Satyanarayana, A.N. Subba Rao, S.P.V. Department of ECE Sreenidhi Institute of Science and Technology Hyderabad India

ISBN: (纸本)9789819783281

Hand gestures have become a popular method for controlling digital devices. The Gesture-controlled Virtual Mouse redefines human–computer interaction by allowing users to operate digital devices using intuitive hand gestures and voice commands. This innovative system not only enhances usability but also promotes a hygienic computing environment by minimizing physical touch—an essential feature in today’s health-conscious world. Leveraging advanced Machine Learning and computer Vision techniques, including Convolutional Neural Networks (CNNs) with MediaPipe via pybind11, the system achieves high accuracy in recognizing a wide range of gestures and voice inputs. This flexibility allows the technology to be applied across various real-world scenarios, from improving accessibility for people with physical disabilities to streamlining workflow in business and industrial environments. The Gesture-Responsive Pointer controller is designed for versatility, accommodating different interaction styles, including direct hand gestures and uniform-colored gloves, with voice command support as an additional input method. Optimized for the Windows platform, this system's modularity makes it adaptable to diverse contexts, such as health care, education, and manufacturing, offering hands-free control where needed. By combining gesture recognition with voice assistant capabilities, this technology represents a significant step toward a future where AI-driven human–computer interaction is more seamless, accessible, and intuitive. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gesture recognition

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A Hybrid Deep Learning Models: Optimization for Forecasting Wireless 6G IoT Network 1

A Hybrid Deep Learning Models: Optimization for Forecasting ...

引用

1st International conference on Advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Singh, B.P. Venkadeshwaran, Kuthalingam Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka Ramnagar District India

ISBN: (纸本)9798331518578

New specifications for 6G mobile networks will surpass the performance targets of 5G networks. As more 5G networks are deployed, their limits become obvious, encouraging the exploration of networks using 6G as the future solution. This paper covers 6G technology's core privacy and security concerns. Monitoring real-time structures need secured wireless sensor networks (WSNs). Denial of service (DoS) outbreaks increase secure risks for WSNs and potentially undermine the whole system. This study presents a new approach to control and optimize the security of 6G wireless networks based on blockchain technology by means of a machine learning method. Utilizing a blockchain users datagram transit protocol in conjunction with reinforcement projection regression, this research manages security of organized 6G wireless sensor net. The network is then optimized via artificially democratized cuckoo glowworm remora optimizations. Numerous network characteristics pertaining to accuracy, end-to-end latency, packet delivery ratio, energy efficiency, and throughput have formed the basis of the simulation findings. Reduced network traffic may be achieved by figuring out which node and route are best for data transfer. 98% of Throughput, energy effectiveness of 96%, 97% accuracy, end to end latency of 51%, and packet delivery ratio of 95% were all achieved by the suggested method. © 2025 IEEE.

关键词： 5G mobile communication systems

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Quality in Color: Using Knowledge Graphs for Enhanced Quality control in an Automotive Paintshop 23rd

Quality in Color: Using Knowledge Graphs for Enhanced Qual...

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23rd International Semantic Web conference, ISWC 2024

作者： Steenwinckel, Bram Soete, Colin Moens, Pieter Mussche, Joris Hoecke, Sofie Van Ongenae, Femke IDLab Ghent University – imec Gent9000 Belgium Volvo Cars Group Gent9000 Belgium

ISBN: (纸本)9783031778469

Sensors and their derived data have reshaped manufacturing by enabling real-time monitoring, improved quality control and enhanced safety, particularly in automotive processes. Despite these benefits, challenges arise within the realm of data discovery when they have to align all this data, originating from different systems and built by different manufacturers using different technologies. This paper shows our solution to resolve these challenges within the Volvo Cars paintshop. By organizing sensor metadata, link them with the originating devices and the place where the data will be stored in a knowledge graph, our approach facilitates seamless data integration for multiple paintshop applications. We show how the resulting knowledge graph helps with dashboard techniques, machine learning, and semantic reasoning to provide insights for the paintshop operators. The obtained findings clearly show the potential of knowledge graphs in production lines, paving the way for future advancements in automotive manufacturing. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Metadata

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Humanoid Robots, A future Health Care Service? 16th

Humanoid Robots, A Future Health Care Service?

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16th International conference on Social Robotics, ICSR + AI 2024

作者： Sørensen, Linda Kaarstad, Magnhild Eitrheim, Maren Fernandes, Alexandra Reegård, Kine Sunnaas Rehabilitation Hospital Nesodden Norway University of Agder Kristiansand Norway Digital Systems Institute for Energy Technology Halden Norway

ISBN: (纸本)9789819635184

In this paper we discuss the possible use of humanoid robots within the healthcare services context. Recently, new technologies such as robotics have been further developed and are currently being assessed for use within healthcare services. A research project was carried out to explore whether the humanoid robot EVE can enhance healthcare services in rehabilitation and home assistance settings. In the project we carried out empirical studies to investigate the possible functionalities and use of a robot such as EVE for healthcare personnel and patients. In this paper, we took a step further and asked: What will it take to implement the robot EVE as a healthcare service? We conducted two workshops and a focus group interview with a total of 21 participants (healthcare staff and management representatives) where we discussed possible impacts, requirements, and strategies for a sustainable implementation of humanoid robots. Based on our findings, we discuss key topics such as contextual specificities, robot control paradigms, and the concepts of robots as a service/as a product. We conclude by listing recommendations for future implementations of humanoid robots in healthcare. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Anthropomorphic robots

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