This article is devoted to the development of Intelligent Verbal Interaction Methods with Non-Player Characters in Metaverse Applications. The creation of a character model using MetaHuman Creator and the implementati...
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This paper delves into the dynamic landscape of computer security, where malware poses a paramount threat. Our focus is a riveting exploration of the recent and promising hardware-based malware detection approaches. L...
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Landslides are critical natural hazards whose frequency and severity are increasing due to climate change and human activities. The consequences of landslides are severe and can lead to the destruction of homes, infra...
Landslides are critical natural hazards whose frequency and severity are increasing due to climate change and human activities. The consequences of landslides are severe and can lead to the destruction of homes, infrastructures and the contamination of water supplies, with severe impact also on the local ecosystems and the disruption of natural habitats. This article examines the application of an ad-hoc neural network-based intelligent system to evaluate the landslide susceptibility of the terrain on the basis of satellite data. The proposed system is validated on data from Lombardia and Abruzzo, two Italian regions that have been particularly subject to the landslide phenomenon. Results indicate that the CNN model is able to correctly identify landslide occurrences with high accuracy, demonstrating that CNNs are capable of providing accurate susceptibility mapping at a local scale and surpassing the performance of existing solutions available in the literature.
This paper addresses the output tracking problem of network control systems (NCSs) with random communication constraints, especially when the lower bound of the time delay induced by random communication constraints i...
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ISBN:
(数字)9789887581598
ISBN:
(纸本)9798331540845
This paper addresses the output tracking problem of network control systems (NCSs) with random communication constraints, especially when the lower bound of the time delay induced by random communication constraints is relatively large. Firstly, the output tracking problem is converted into the stabilization problem of an augmented system. Then, a networked predictive output tracking control scheme with time-varying control gains is proposed to compensate for the impact of the communication constraints so as to complete the desired output tracking performance under the large time delays. And, a set of control gains are calculated for each different time delay, which improves the adaptability of NCSs to time delays. Next, a sufficient condition is derived to keep the system stability. Finally, the effectiveness of the proposed method is verified by numerical simulations.
In this paper, we propose an algorithm for detecting artifacts in long-term video-EEG monitoring data in the problem of diagnosing cerebral ischemia after subarachnoid hemorrhage. The algorithm is based on a threshold...
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Traumatic brain injury (TBI) is a burgeoning medical disorder across the world particularly among young adults and children. TBI can cause intracranial hematoma (ICH), a lethal condition which requires prompt and accu...
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This paper models a platooning system consisting of trucks and a third-party service provider (TPSP), which performs platoon coordination, distributes the platooning profit in platoons, and charges trucks in exchange ...
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Complex mechatronic systems are typically composed of interconnected modules, often developed by independent teams. This development process challenges the verification of system specifications before all modules are ...
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In this paper, we propose an efficient continuous-time LiDAR-Inertial-Camera Odometry, utilizing non-uniform B-splines to tightly couple measurements from the LiDAR, IMU, and camera. In contrast to uniform B-spline-ba...
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The adaptability of devices can be significant for a customer that inserts them in an industrial production line. The ability to modify an object bought along with a machine that can be personalized with its features ...
The adaptability of devices can be significant for a customer that inserts them in an industrial production line. The ability to modify an object bought along with a machine that can be personalized with its features can change how they want to do measurements for different reasons, like predictive maintenance. Fog computing local centers already exist in the market, but they are usually on-the-shelf products with no margin of change for any user. However, with the usage of Docker and containers, this can change. This paper describes a fog computing local central called Concentrator, which can not only execute its essential functions built-in by the producer but also be customized by the user to add in the elaborations on other external sensors, expanding its capabilities and usage. We wanted to improve the device already tested on a Linux PC on a Raspberry Pi and try its performance and characteristics, seeing if it could be transformed into an embedded architecture and an industrial feature.
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