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arXiv 2023年

作者： Bhide, Neeraja Hashimoto, Nanami Dokurno, Kazimierz Van der Hoorn, Chris Hoogendoorn-Lanser, Sascha Nordhoff, Sina Delft Center for Systems and Control Delft University of Technology Netherlands Department of Cognitive Robotics Delft University of Technology Netherlands Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands Department Transport & Planning Delft University of Technology Netherlands

Automated vehicle acceptance (AVA) has been measured mostly subjectively by questionnaires and interviews, with a main focus on drivers inside automated vehicles (AVs). To ensure that AVs are widely accepted by the public, ensuring the acceptance by both drivers and passengers is key. The in-vehicle experience of passengers will determine the extent to which AVs will be accepted by passengers. A comprehensive understanding of potential assessment methods to measure the passenger experience in AVs is needed to improve the in-vehicle experience of passengers and thereby the acceptance. The present work provides an overview of assessment methods that were used to measure a driver's behavior, and cognitive and emotional states during (automated) driving. The results of the review have shown that these assessment methods can be classified by type of data-collection method (e.g., questionnaires, interviews, direct input devices, sensors), object of their measurement (i.e., perception, behavior, state), time of measurement, and degree of objectivity of the data collected. A conceptual model synthesizes the results of the literature review, formulating relationships between the factors constituting the in-vehicle experience and AVA acceptance. It is theorized that the in-vehicle experience influences the intention to use, with intention to use serving as predictor of actual use. The model also formulates relationships between actual use and well-being. A combined approach of using both subjective and objective assessment methods is needed to provide more accurate estimates for AVA, and advance the uptake and use of AVs. © 2023, CC BY.

关键词： Vehicles

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Internet of Intelligent Things (IoT) – An Overview

Internet of Intelligent Things (IoT) – An Overview

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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： Ramiz Salama Fadi Al-Turjman Manisha Aeri Satya Prakash Yadav Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Mersin Turkey Artificial Intelligence Engineering Dept. AI and Robotics Institute Near East University Nicosia Mersin Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Kyrenia Mersin Turkey Computer Science and Engineering Graphic Era Hill University Dehradun Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management (GLBITM) Greater Noida India

The basic goal of the IoT is to permit the online connection and communication of everyday physical objects like appliances, vehicles, and other gadgets. This paves the way for effortless and automated data collection and exchange, as well as interaction between the objects themselves and with humans. The Internet of Everything (IoE) is an expansion of the Internet of Things (IoT) that aims to maximize and improve human life by connecting and making the most of all available resources (humans, information, and technology). The transportation, healthcare, agricultural, energy, and manufacturing sectors are all examples. The IoIT aims to incorporate AI and ML within the IoT’s interconnected network of physical items. These objects can then independently behave in response to the information they have gathered and the instructions they have been given. This has the potential to lead to smarter, more efficient systems that can react to new information and human input in real time. The Internet of Things, the Internet of Everything, and the Industrial Internet of Things all have the same overarching goal: to pave the way for the development of more efficient and intelligent systems and processes that can enhance a wide range of human endeavors. However, in order to make sure that these technologies are used in a responsible and ethical way, it will be necessary to carefully analyze their consequences and the issues they provide.

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Intelligent Hardware Solutions for COVID -19 and Alike Diagnosis - A survey

Intelligent Hardware Solutions for COVID -19 and Alike Diagn...

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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

Globally, 210 nations have been affected by the 2019 Novel Coronavirus (COVID-19), which has been classified as a pandemic. The modern health system, as well as the economic, educational, and social sides of society, have all been severely impacted. While the rate of transmission keeps increasing, several cooperative strategies between stakeholders to create cutting-edge methods of screening and detecting COVID-19 instances among people at a comparable rate have been noticed. Also, the importance of computational models connected to the technologies of the fourth industrial revolution in accomplishing the desired feat has been emphasized. Unfortunately, there is a gap in the precision of COVID-19 case detection, prediction, and contact tracking. For patients with COVID-19 in isolation units, teleultrasound (TUS), particularly with the support of fifth generation (5G) wireless transmission technology, can offer rapid monitoring, quick clinical progress assessment, and assistance with guiding interventional procedures. Also, it helps conserve medical resources like equipment and supplies while lowering the risk of infection among medical personnel. The review of computer models presented in this work can be used to improve the effectiveness of COVID-19 pandemic case detection and prediction. We concentrate on adoptable big data, AI, and nature-inspired computing solutions for the current pandemic. According to the review, models inspired by nature have shown strong performance in feature selection for medical problems. In pandemic-related cases like COVID-19, contact tracing using big data analytics should also be investigated.

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Enhanced Local Attention with Deep Neural Networks for EEG Decoding 4th

Enhanced Local Attention with Deep Neural Networks for EEG...

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4th International Workshop on Human Brain and Artificial Intelligence, HBAI 2024

作者： Tao, Wei Ye, Jiawo Ieong, Chio-In Wu, Haiyan Wan, Feng Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Taipa China Centre for Cognitive and Brain Sciences Institute of Collaborative Innovation University of Macau Taipa China Centre for Artificial Intelligence and Robotics Institute of Collaborative Innovation University of Macau Taipa China Guangdong Institute of Intelligence Science and Technology Zhuhai China Department of Psychology Faculty of Social Sciences University of Macau Taipa China

ISBN: (纸本)9789819640003

Channel-wise attention mechanisms have significantly improved deep learning-based decoding in brain-computer interfaces (BCIs). However, these methods often fail to fully utilize spatial and temporal dynamics, focusing instead on individual channel enhancements to the detriment of broader EEG signal dynamics. To address these limitations, we introduce the Enhanced Local Attention (ELA) module, seamlessly integrated into deep neural networks that enhances EEG decoding performance. It captures long-range dependencies from deep features across two dimensions through a streamlined architecture. The ELA module employs adaptive 1D convolution for precise localization of spatial and temporal information without reducing dimensions. Additionally, it utilizes group normalization to enhance feature representation by normalizing features across groups. Its lightweight design enables easy integration into existing deep learning frameworks. Comprehensive evaluations on the BCI-IV2b dataset highlight the ELA module’s superior performance. Specifically, it increases the decoding accuracy of EEGNet in the motor imagery task from 81.89% to 85.97%. Furthermore, when integrated with ADFCNN, the ELA module achieves an accuracy of 88.13%, consistently outperforming other state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep neural networks

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(Benefits of Internet of Things (IoT) Applications in Health care - An Overview)

(Benefits of Internet of Things (IoT) Applications in Health...

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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： Ramiz Salama Fadi Al-Turjman Preeti Chaudhary Satya Prakash Yadav Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Mersin Turkey Artificial Intelligence Engineering Dept. AI and Robotics Institute Near East University Nicosia Mersin Turkey Research Center for AI and IoT Faculty ofEngineering University of Kyrenia Kyrenia Mersin Turkey Computer Science and Engineering Graphic Era Hill University Dehradun Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management (GLBITM) Greater Noida India

In a nutshell, the IoT refers to the idea of integrating high-tech technology in the form of "smart" gadgets and sensors into a single setting to gather data. There are still numerous areas in which machines cannot compete favorably with people, but data collection and analysis are undeniably two of their strongest points. The Internet of Things makes it possible to fully or partially automation data, it involves related activities, which is obviously very important for the healthcare industry. What exactly is the Internet connected medical things, and how exactly might it make a significant impact on the sector? By having to apply the concept of the internet of things (IoT) to the field of medicine, several significant advancements have become possible, including the ability to automatically control the thermostat of containers while transmitting inoculations and antibiotics, the accurate tracking of the ailments of a lot of illnesses without a need for additional meetings with a general practitioner, the correct and most useful use of meds, and a great deal more. All of this is realizable because of the capability of MedTech gadgets to carry out continuous monitoring system. The potential applications of internet of things technology in healthcare are very interesting. Let’s review the ways in which this technology.

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Improving Referring Expression Comprehension by Suppressing Expression-unrelated Proposals 3

Improving Referring Expression Comprehension by Suppressing ...

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3rd International Conference on Electronic Information Engineering and computer, EIECT 2023

作者： Wang, Qun Zhu, Feng Li, Xiang Ye, Ruida Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Northeastern University Faculty of Computer Science and Engineering Shenyang110016 China Space Engineering University Department of Aerospace Engineering and Technology Beijing101416 China

ISBN: (纸本)9798350357707

The prevailing referring expression comprehension (REC) method is based on two stages: 1) detecting multiple candidate proposals using an object detector and 2) aligning proposals with text descriptions. Existing two-stage models have achieved significant improvements with excellent alignment modules. However, their alignment modules treat each proposal equally without filtering expression-unrelated proposals. These expression-unrelated proposals may interfere with the alignment modules' ability to accurately reason about the target proposal. These proposals also increase the difficulty of training alignment modules. To solve this problem, we propose a new framework, that can suppress expression-unrelated proposals for alignment modules. Specifically, we first design a suppression module, which calculates the relevance scores between the proposals and the expression by using the semantics in the expression. Then, these scores are integrated into three basic alignment modules, including subject, location, and relationship modules, to guide each module to focus on the expression-related proposals. We conduct extensive experiments on three benchmark datasets, and the results show the effectiveness of our suppression module and performance improvement. © 2023 IEEE.

关键词： Alignment

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A Robotic Framework for the Robot@Factory 4.0 Competition

A Robotic Framework for the Robot@Factory 4.0 Competition

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Ricardo B. Sousa Cláudia D. Rocha João G. Martins João Pedro Costa João Tomás Padrão José Maria Sarmento José Pedro Carvalho Maria S. Lopes Paulo G. Costa António Paulo Moreira Faculty of Engineering University of Porto (FEUP) Porto Portugal CRIIS - Centre for Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal University of Trás-os-Montes and Alto Douro (UTAD) Vila Real Portugal C2SR - Cyber-Physical Control Systems and Robotics SYSTEC - Research Center for Systems and Technologies Porto Portugal

ISBN: (数字)9798350352344

ISBN: (纸本)9798350352351

Robotic competitions stand as platforms to propel the forefront of robotics research while nurturing STEM education, serving as hubs of both applied research and scientific innovation. In Portugal, the Portuguese robotics Open (FNR) is an event with several robotic competitions, including the Robot@Factory 4.0 competition. This competition presents an example of deploying autonomous robots on a factory shop floor. Although the literature has works proposing frameworks for the original version of the Robot@Factory competition, none of them proposes a system framework for the Robot@Factory 4.0 version that presents the hardware, firmware, and software to complete the competition and achieve autonomous navigation. This paper proposes a complete robotic framework for the Robot@Factory 4.0 competition that is modular and open-access, enabling future participants to use and improve it in future editions. This work is the culmination of all the knowledge acquired by winning the 2022 and 2023 editions of the competition.

关键词： Technological innovation Education Propulsion Production facilities Software Hardware Autonomous robots

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Weisfeiler and leman go loopy: a new hierarchy for graph representational learning 24

Weisfeiler and leman go loopy: a new hierarchy for graph rep...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Raffaele Paolino Sohir Maskey Pascal Welke Gitta Kutyniok Department of Mathematics LMU Munich and Munich Center for Machine Learning (MCML) Department of Mathematics LMU Munich Faculty of Computer Science TU Wien Department of Mathematics LMU Munich and Munich Center for Machine Learning (MCML) and Institute for Robotics and Mechatronics DLR-German Aerospace Center and Department of Physics and Technology University of Tromsø

ISBN: (纸本)9798331314385

We introduce r-loopy Weisfeiler-Leman (r-ℓWL), a novel hierarchy of graph isomorphism tests and a corresponding GNN framework, r-ℓMPNN, that can count cycles up to length r + 2. Most notably, we show that r-ℓWL can count homomorphisms of cactus graphs. This extends 1-WL, which can only count homomorphisms of trees and, in fact, we prove that r-ℓWL is incomparable to k-WL for any fixed k. We empirically validate the expressive and counting power of r-ℓMPNN on several synthetic datasets and demonstrate the scalability and strong performance on various real-world datasets, particularly on sparse graphs. Our code is available on https://***/RPaolino/loopy.

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

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computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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Robust Co-Design of Canonical Underactuated Systems for Increased Certifiable Stability

Robust Co-Design of Canonical Underactuated Systems for Incr...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Federico Girlanda Lasse Shala Shivesh Kumar Frank Kirchner Robotics Innovation Center German Research Center for Artificial Intelligence (DFKI GmbH) Bremen Germany Department of Information Engineering University of Padova Italy Department of Mechanics & Maritime Sciences Dynamics Division Chalmers University of Technology Gotheburg Sweden Faculty of Mathematics and Computer Science University of Bremen Bremen Germany

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Optimal behaviours of a system to perform a specific task can be achieved by leveraging the coupling between trajectory optimization, stabilization, and design optimization. This approach is particularly advantageous for underactuated systems, which are systems that have fewer actuators than degrees of freedom and thus require for more elaborate control systems. This paper proposes a novel co-design algorithm, namely Robust Trajectory Control with Design optimization (RTC-D). An inner optimization layer (RTC) simultaneously performs direct transcription (DIRTRAN) to find a nominal trajectory while computing optimal hyperparameters for a stabilizing time-varying linear quadratic regulator (TVLQR). RTC-D augments RTC with a design optimization layer, maximizing the system’s robustness through a time-varying Lyapunov-based region of attraction (ROA) analysis. This analysis provides a formal guarantee of stability for a set of off-nominal states. The proposed algorithm has been tested on two different underactuated systems: the torque-limited simple pendulum and the cart-pole. Extensive simulations of off-nominal initial conditions demonstrate improved robustness, while real-system experiments show increased insensitivity to torque disturbances.

关键词： Couplings Torque Regulators Stability analysis Robustness Task analysis robotics and automation

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