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Secure Channel Creation for Task Delivery in Vehicular Cloud Computing to Avoid Denial of Service (DoS) 3

Secure Channel Creation for Task Delivery in Vehicular Cloud...

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3rd international conference on Automation, Computing and Renewable Systems, ICACRS 2024

作者： Meenambika, A. Pavalarajan, S. Lavanya, N. Anu Jerom, B. Ajith Divya, S. Department of Computer Science and Business Systems PSNA College of Engineering and Technology Dindigul India PSNA College of Engineering and Technology Dindigul India Department of Artificial Intelligence and Data Science PSNA College of Engineering and Technology Dindigul India

ISBN: (纸本)9798331532420

Vehicular Cloud Computing (VCC) offers a promising platform for supporting various automotive applications and services. However, its distributed and dynamic nature makes it susceptible to Denial-of-Service (DoS) attacks, particularly during channel establishment. This research proposes a comprehensive approach to mitigate these risks by integrating a suite of security mechanisms. These include rate-limiting, resource management, traffic analysis, access control, authentication, encryption, intrusion detection, behavioral analysis, and blacklisting/whitelisting techniques. By incorporating these measures, the proposed approach enhances the security and reliability of VCC, ensuring the availability of critical automotive services and protecting vehicles from the impact of DoS attacks. © 2024 IEEE.

关键词： Cloud platforms

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Artificial intelligence-Based Detection of Autism Spectrum Disorder Using Linguistic Features 3

Artificial Intelligence-Based Detection of Autism Spectrum D...

引用

3rd international conference on Computing and Machine intelligence (ICMI)

作者： Li, Juliana Harker Sch San Jose CA 95124 USA

ISBN: (纸本)9798350372977;9798350372984

Artificial intelligence (AI) technology has recently shown promising results in detecting Autism Spectrum Disorder (ASD), but it faces significant challenges because it is still in early stages of development. This study proposes to use linguistic features in the detection of ASD using artificial intelligence. In order to systematically understand different AI model performances, two types of AI models have been explored and evaluated. Five classical ML models were used: logistic regression, Gaussian naive Bayes, random forests, k-nearest neighbors (K-NN), and support vector machines (SVMs), and two deep learning models were used: multilayer perceptron (MLP) and a convolutional neural network (CNN). All model development work is based on analyzing speech transcripts of 64 children total aged 3 to 6 from two data banks, CHILDES and ASDBank, including 30 children with ASD and 34 typically developing (TD) controls. The first step was to examine the annotations of the transcriptions, then extract various linguistic features from the texts. AI models were trained to determine whether a child has ASD based on the characteristics of the transcripts analyzed. There are three major findings of this study. First, neural network models will outperform classical models in ASD detection by around 5%-10%. The models multilayer perceptron and convolutional neural networks achieved 83% and 84% accuracy, respectively. Second, among the classical machine learning models, logistic regression, SVMs, K-NN, and random forests all achieved accuracies in the range 77%-80%, while Gaussian naive Bayes performed the worst by around 10%. Third, the linguistic feature with the highest importance in ASD detection is MLU, and the features MLU, MLT, rUtts, and rTNW show significant distinctions between age and gender demographics in addition to having high importance in ASD detection. Overall, this research recommends using deep learning for clinical applications of ASD detection.

关键词： Autism Spectrum Disorder Natural Language Processing Artificial intelligence Machine Learning Deep Learning Linguistics

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Securing Image using Triple Data Encryption Standard 3

Securing Image using Triple Data Encryption Standard

引用

3rd international conference on Artificial intelligence For Internet of Things, AIIoT 2024

作者： Rao, Meghana G Cenitta, D. Arjunan, R. Vijaya Babu, D. Vijendra Manipal Institute of Technology MAHE Department of CSE Karnataka Manipal India Manipal Institute of Technology Manipal Academy of Higher Education Department of CSE Karnataka India Vellore Institute of Technology School of Electronics Engineering Tamil Nadu Vellore632014 India

ISBN: (纸本)9798350372120

This study explores the efficacy of securing images through the implementation of the Triple Data Encryption Standard (TDES). TDES, a symmetric-key block cipher, is examined for its role in enhancing the confidentiality, integrity, and authenticity of sensitive visual data. The encryption process transforms image content into an unreadable format, providing a robust defense against unauthorized access. Additionally, cryptographic checks embedded in TDES contribute to the preservation of data integrity, ensuring that image content remains unaltered during transmission or storage. The study delves into TDES's compliance with industry standards, its flexibility in key management, and cross-platform compatibility. Furthermore, TDES's computational complexity acts as a deterrent against unauthorized access, fortifying its role as a scalable and comprehensive solution for image security. The findings highlight the practical applications of TDES in safeguarding visual data across various contexts, offering insights into its effectiveness in addressing confidentiality concerns and protecting against potential threats. © 2024 IEEE.

关键词： Cryptography

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Interactive Agent Foundation Model: A Meta-Learning Strategy 3

Interactive Agent Foundation Model: A Meta-Learning Strategy

引用

3rd international conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Dwivedi, Mani Dwivedi, Anuj Kr. KIET Group of Institutions Delhi-NCR Department of Computer Science and Engineering Ghaziabad India Galgotias College of Engineering and Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798331523893

Artificial intelligence (AI) systems are evolving from static, task-specific models to dynamic, agent-based systems that perform well in a variety of scenarios. We present an Interactive Agent Foundation Model using a novel multi-task agent training methodology that includes many pretraining techniques such as language modelling, visual masked autoencoders, and next-action prediction. This framework's adaptability and versatility have been shown in the robotics, gaming AI, and healthcare sectors, yielding results that are pertinent to the situation. Effective multimodal and multitask learning is made possible by utilizing a variety of data sources, such as textual information, gaming data, robotics sequences, and large-scale video datasets. Our method offers a viable way forward for creating adaptable, proactive, multimodal systems. © 2025 IEEE.

关键词： robot learning

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Enhancing Human-robot Interaction through PID Control and Sensor Integration 3

Enhancing Human-Robot Interaction through PID Control and Se...

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3rd international conference on Power Electronics and IoT applications in Renewable Energy and its Control, PARC 2024

作者： Agrawal, Ayush Kumar Kumar, Jayendra Kumar, Avanish Arvind, Pratul National Institute of Technology Department of Electronics and Communication Jamshedpur831014 India Delhi Technological University Department of Electrical Engineering Delhi India Dr. Akhilesh das Gupta Institute of Technology & Management Department of Electrical & Electronics Engineering New Delhi110053 India

ISBN: (纸本)9798350309409

The study in this research investigates the application of a PID controller for achieving precise control of a robotic arm, with a focus on emulating human-like motions. The results demonstrate the successful generation of accurate joint angles during arm motion, showcasing the effectiveness of PID control in determining correct angles for seamless joint movements. The PID controller's mechanism, evaluating the variance between desired and observed positions, ensures minimal deviation, leading to error-free arm motions marked by smoothness and precision. The robotic arm, developed in our laboratory, integrates the PID controller for controlled motion, offering a user-friendly and efficient system. Notably, the study extends the application of PID control by integrating an MPU9250 sensor onto an individual's hand, enhancing the interaction between the robotic arm and the user. This integration enables real-time motion tracking and feedback, allowing the robotic arm to respond accurately to the user's gestures and movements. The PID-controlled robotic arm not only excels in accuracy but also demonstrates real-time adjustability, adaptability, and stability, showcasing its versatility for potential applications in diverse fields. This research lays a foundation for advancing PID-controlled robotic systems, emphasizing precision, adaptability, and intuitive operation, with implications for industrial automation, medical assistance, and interactive human-robot collaboration. © 2024 IEEE.

关键词： Three term control systems

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Lightweight Semantic Segmentation for RoboCup SPL: A U-Net Model with MobileNetV2 and Attention Mechanisms 3

Lightweight Semantic Segmentation for RoboCup SPL: A U-Net M...

引用

3rd international conference on Artificial intelligence, Internet of Things and Cloud Computing technology, AIoTC 2024

作者： Xia, Jinwei Su, Ruiyang School of Software Engineering Jinling Institute of Technology Nanjing China School of Electronic Engineering JiangSu Ocean University Lianyungang China

ISBN: (纸本)9798331530280

Real-time and precise semantic segmentation is essential for robotic vision systems, particularly in dynamic and complex environments such as RoboCup SPL. This paper introduces a lightweight semantic segmentation model that combines the U-Net architecture with a MobileNetV2 subnetwork and the Convolutional Block Attention Module (CBAM). The UNet's encoder-decoder structure facilitates effective multi-scale feature fusion, while MobileNetV2 reduces computational overhead. CBAM further enhances the model's ability to focus on critical features. Evaluations on the RoboCup SPL instance segmentation dataset achieved a mean accuracy of 0.9370. Through comparative analysis with various backbone networks and ablation studies, we investigated the effects of CBAM, joint loss functions, and data augmentation on model performance. Results indicate that the CBAM mechanism significantly improves segmentation accuracy, and both joint loss functions and data augmentation offer additional benefits. The proposed model achieves a favorable balance between accuracy and computational efficiency, making it highly suitable for real-time applications. © 2024 IEEE.

关键词： Semantic Segmentation

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Investigating the 5G Handover in Autonomous Mobile robotic applications 3

Investigating the 5G Handover in Autonomous Mobile Robotic A...

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3rd international conference on robotics, Automation and Artificial intelligence (RAAI)

作者： Luong, Tommy Banos, Gustavo Boshoff, Marius Moldovan, Christian Schuster, David Gruhn, Volker Kuhlenkoetter, Bernd Ruhr Univ Bochum Chair Prod Syst Bochum Germany Comnovo GmbH Dortmund Germany Univ Duisburg Essen Inst Software Engn Essen Germany

ISBN: (纸本)9798350307573;9798350307566

In industrial automation, Autonomous Mobile robot (AMR) applications have been widely integrated into facilities to improve manufacturing, productivity, and flexibility of productive areas. These advancements are largely attributed to wireless connectivity such as 5G or Wi-Fi. The unlicensed networks such as Wi-Fi, currently face performance issues due to electromagnetic interferences from other overlapping neighboring networks and therefore cannot guarantee reliability or scalability for such a mission-critical task. This raises the question of whether 5G could be the wireless technology to drive the expected digital transformation. To ensure the stability of connectivity for seamless operations, it is crucial to investigate whether the handover in 5G, which differs significantly from traditional WiFi procedures, is suitable for the productive environment. The handover in mobile networks such as 5G is understood to be the transfer of the connection from one cell to another. For example, in productive environments, the handover is required when the AMR moves between different halls with multiple small cells and needs to be reconnected to another cell for a better signal quality. This paper addresses this issue and presents an exemplary investigation, in which the handover is monitored for an AMR application. Our results show that the handover process is completed without any detectable delay or packet loss during the data transmission. The results also indicate that the use of a 5G campus network could be a key enabler for the implementation of mission-critical tasks and give insights into the potential of 5G for AMR applications in industrial automation.

关键词： 5G Handover robotics Industrial Automation

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Carbon Neutrality Approaches for IoT-Enabled applications 3

Carbon Neutrality Approaches for IoT-Enabled Applications

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3rd international conference on Artificial intelligence and Smart Energy, ICAIS 2023

作者： Benedict, Shajulin Indian Institute of Information Technology Kottayam Department of Computer Science and Engineering Kerala Kottayam District686635 India

ISBN: (纸本)9781665462167

Unlike others, IoT-enabled technology has expanded its base in various sectors, including finance, healthcare, agriculture, energy, and so forth. Tens of thousands of applications and products have evolved in recent years, leading to a constant threat to global climate sustainability due to the underlying carbon emissions. Researchers have developed standalone methods/approaches that aimed to tackle carbon emission problems. However, an article that expresses a list of carbon-neutral solutions and their associated technological challenges is not available. This article explores the carbon emission problems of IoT-enabled applications;and, it categorizes the carbon neutrality methods. The exploratory analysis of different carbon-neutral approaches, presented in this article, can present novel ideas and answers to questions that hover over any carbon-conscious IoT-enabled application developers. © 2023 IEEE.

关键词： Internet of things

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Architecture and Challenges of IoT in developing an Infrastructure for robot Taxi 3

Architecture and Challenges of IoT in developing an Infrastr...

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3rd international conference on Smart Data intelligence, ICSMDI 2023

作者： Vijay, A. Mustafa, Ayesha Afzal, Wardah Shehzad, Aatika Tariq, Maria Kousalya, K. Sri Ramakarishna Engineering College Tamil Nadu Coimbatore India Computer Science Univeristy of Gujrat Pakistan Electrical Engineering Research Scholar University of Engineering and Technology Lahore Pakistan Gomal Univeristy Gimak Doctor of Vertinary and Medicine Pakistan Kongu Engineering College Department of Computer Science and Engineering Perundurai India

ISBN: (纸本)9781665464871

Autonomous robot taxis are the future self-driven robot taxis that can be operated on their own without the help of any driver. They are superfast in speed and would not cause an accident. In short, they are ideal supercars. The motive behind their development is to provide such vehicles that could easily bring a revolution in the traffic system of the world. To achieve that much better performance, industrialists have started doing their work in this field by solving the issues that they are facing in the current cars to obtain their desired results. Full cooperation of such vehicle with other vehicles, road and the whole network is needed in successful launch of such vehicles. One of the major challenges in it is to convert the already formulated cars into such type of robot taxis. Then, for the smooth working of these robot taxis, the obstacles around it must be evaluated. Many other challenges along with solutions are presented in this paper. A brief analysis about the sensors used in the development of autonomous robot taxis are mentioned in the architecture section. Moreover, this article also deals with the architecture of such robot taxis. It is also predicted that these vehicles will be widely used all over the world in the near future. © 2023 IEEE.

关键词： Global positioning system

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Water Quality Monitoring and Control in Urban Areas in Real-Time via IoT and Mobile applications 3

Water Quality Monitoring and Control in Urban Areas in Real-...

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3rd international conference on Artificial intelligence For Internet of Things, AIIoT 2024

作者： Mohanasundaram, R. Sagar, Raghav Kumar Khandelwal, Animan Upadhyay, Diwas Poddar, Harshit Rajagopal, Sivakumar Vellore Institute of Technology School of Computer Science and Engineering Vellore India Vellore Institute of Technology School of Electronics Engineering Vellore India

ISBN: (纸本)9798350372120

The presence of impurities in water resulting from the expansion of industrial activities and the disregard of regulations aimed at protecting the environment presents considerable threats to the well-being of the general population. The establishment of reliable access to uncontaminated drinking water assumes paramount importance in the realm of disease prevention. The continuous monitoring of the quality of water in real-time serves as an indispensable measure for ensuring its safety. The objective of this article is to introduce a system that capitalizes on the Internet of Things (IoT) to automate the distribution and management of water resources within urban areas. By making use of embedded technology, this system allows for the uninterrupted surveillance and regulation of water quality. To further streamline the management process, an application compatible with the Android operating system has been developed to promptly notify users of any irregularities, thereby enabling remote control. Moreover, a web-based application has been designed to cater to the needs of iOS users, thereby broadening accessibility. This comprehensive approach not only heightens the level of user awareness but also provides them with greater control over their water supply, thereby enhancing public health outcomes. © 2024 IEEE.

关键词： Internet of things

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