The characteristics that make up the general identity of engineering technology (ET) degree programs and their graduates are well known;however, the explicit characteristics of ET capstone nationally is unknown. In ot...
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Artificial Intelligence has been playing a profound role in the global economy,social progress,and people’s daily *** the increasing capabilities and accuracy of AI,the application of AI will have more impacts on man...
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Artificial Intelligence has been playing a profound role in the global economy,social progress,and people’s daily *** the increasing capabilities and accuracy of AI,the application of AI will have more impacts on manufacturing and service areas in the era of industry *** study conducts a systematic literature review to study the state-of-the-art on AI in industry *** paper describes the development of industries and the evolution of *** paper also identifies that the development and application of AI will bring not only opportunities but also challenges to industry *** findings provide a valuable reference for researchers and practitioners through a multi-angle systematic analysis of *** the era of industry 4.0,AI system will become an innovative and revolutionary assistance to the whole industry.
In contrast to text-independent speaker verification, which has received significant attention from researchers and has many competitions dedicated to it, text-dependent speaker verification (TdSV) has been less explo...
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The evolution from 5G to 6G represents a significant leap in wireless communication technology, moving beyond enhanced mobile broadband, low latency, and increased connectivity offered by 5G. The evolution of 5G is ex...
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In contrast to text-independent speaker verification, which has received significant attention from researchers and has many competitions dedicated to it, text-dependent speaker verification (TdSV) has been less explo...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
In contrast to text-independent speaker verification, which has received significant attention from researchers and has many competitions dedicated to it, text-dependent speaker verification (TdSV) has been less explored recently. The TdSV Challenge 2024 was organized to analyze and explore novel methods for this type of speaker verification and aims to motivate participants to develop new approaches to TdSV, conduct comprehensive analyses, and investigate advanced techniques such as self-supervised learning. This challenge builds on the achievements of the short-duration speaker verification (SdSV) Challenges held in 2020 and 2021 and focuses specifically on TdSV in two distinct scenarios. The first scenario involves conventional TdSV, while the second focuses on speaker enrollment using user-defined passphrases. This paper provides a detailed description of both tasks, introduces the evaluation rules, and presents a comprehensive analysis of the results obtained from this challenge.
The ubiquitous deployment of robots across diverse domains, from industrial automation to personal care, underscores their critical role in modern society. However, this growing dependence has also revealed security v...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
The ubiquitous deployment of robots across diverse domains, from industrial automation to personal care, underscores their critical role in modern society. However, this growing dependence has also revealed security vulnerabilities. An attack vector involves the deployment of malicious software (malware) on robots, which can cause harm to robots themselves, users, and even the surrounding environment. Machine learning approaches, particularly supervised ones, have shown promise in malware detection by building intricate models to identify known malicious code patterns. However, these methods are inherently limited in detecting unseen or zero-day malware variants as they require regularly updated massive datasets that might be unavailable to robots. To address this challenge, we introduce RoboGuardZ, a novel malware detection framework based on zero-shot learning for robots. This approach allows RoboGuardZ to identify unseen malware by establishing relationships between known malicious code and benign behaviors, allowing detection even before the code executes on the robot. To ensure practical deployment in resource-constrained robotic hardware, we employ a unique parallel structured pruning and quantization strategy that compresses the RoboGuardZ detection model by 37.4% while maintaining its accuracy. This strategy reduces the size of the model and computational demands, making it suitable for real-world robotic systems. We evaluated RoboGuardZ on a recent dataset containing real-world binary executables from multi-sensor autonomous car controllers. The framework was deployed on two popular robot embedded hardware platforms. Our results demonstrate an average detection accuracy of 94.25% and a low false negative rate of 5.8% with a minimal latency of 20 ms, which demonstrates its effectiveness and practicality.
Zero-day vulnerabilities pose a significant challenge to robot cyber-physical systems (CPS). Attackers can exploit software vulnerabilities in widely-used robotics software, such as the Robot Operating System (ROS), t...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
Zero-day vulnerabilities pose a significant challenge to robot cyber-physical systems (CPS). Attackers can exploit software vulnerabilities in widely-used robotics software, such as the Robot Operating System (ROS), to manipulate robot behavior, compromising both safety and operational effectiveness. The hidden nature of these vulnerabilities requires strong defense mechanisms to guarantee the safety and dependability of robotic systems. In this paper, we introduce RoboCop, a cyber-physical attack detection framework designed to protect robots from zero-day threats. RoboCop leverages static software features in the pre-execution analysis along with runtime state monitoring to identify attack patterns and deviations that signal attacks, thus ensuring the robot’s operational integrity. We evaluated RoboCop on the F1-tenth autonomous car platform. It achieves a 93% detection accuracy against a variety of zero-day attacks targeting sensors, actuators, and controller logic. Importantly, in on-robot deployments, it identifies attacks in less than 7 seconds with a 12% computational overhead.
We demonstrate a wide gamut of color generation by large-scale, lithography-free, and environment-friendly plasmonic structures with a resolution of 100 urn for macroscopic color printing by utilizing femtosecond lase...
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We demonstrate a wide gamut of color generation by large-scale, lithography-free, and environment-friendly plasmonic structures with a resolution of 100 µm for macroscopic color printing by utilizing femtosecond ...
Pandemic-tracking apps may form a future infrastructure for public health surveillance. Yet, there has been relatively little exploration of the potential societal implications of such an infrastructure. In semi-struc...
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