With rising uncertainty in the real world, online Reinforcement Learning (RL) has been receiving increasing attention due to its fast learning capability and improving data efficiency. However, online RL often suffers...
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作者：
Kaafarani, RimaIsmail, LeilaZahwe, OussamaICCS-Lab
Computer Science Department American University of Culture and Education Beirut1507 Lebanon Laboratory
School of Computing and Information Systems The University of Melbourne Melbourne Australia Laboratory
Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University Abu Dhabi United Arab Emirates National Water and Energy Center
United Arab Emirates University Abu Dhabi United Arab Emirates
Blockchain technology has piqued the interest of businesses of all types, while consistently improving and adapting to developers and business owners requirements. Therefore, several blockchain platforms have emerged,...
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Cyber-Physical Production systems (CPPSs) are highly configurable and versatile production systems that utilize diverse hardware components through control software. Managing control software variants in CPPS developm...
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Spatial computing is a technological advancement that facilitates the seamless integration of devices into the physical environment, resulting in a more natural and intuitive digital world user experience. Spatial com...
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Events are considered as the fundamental building blocks of the world. Mining event-centric opinions can benefit decision making, people communication, and social good. Unfortunately, there is little literature addres...
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In this paper, we propose the design of a novel tri-band compact patch antenna. This antenna is resonant within frequencies 2.45 GHz, 3.5 GHz, and 5.8 GHz, making it compatible with wireless local area network (WLAN),...
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ISBN:
(纸本)9781665490382
In this paper, we propose the design of a novel tri-band compact patch antenna. This antenna is resonant within frequencies 2.45 GHz, 3.5 GHz, and 5.8 GHz, making it compatible with wireless local area network (WLAN), world interoperability for microwave access (WiMAX), and Bluetooth. The flexible Roger RT5880 substrate with a thickness of 0.8 mm is used to construct the antenna, and a 50 Ω microstrip line is used as its feeding technique. The final structure has a small size of 30 × 20 × 0.8 mm 3 compared to state-of-the-art designs. Through simulations, we demonstrate the stable and satisfying performances of the novel antenna design over the three targeted frequency bands, thus favoring its use for integrated systems that operate within WLAN, WiMAX, and Bluetooth wireless bands.
Head pose estimation from a monocular image is crucial for applications in computer vision, AR/VR, and human–computer interaction. However, it remains challenging due to occlusions, lighting variations, and limited d...
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Head pose estimation from a monocular image is crucial for applications in computer vision, AR/VR, and human–computer interaction. However, it remains challenging due to occlusions, lighting variations, and limited data. Landmark-based methods often suffer from localization errors, while landmark-free models tend to be complex and computationally expensive. To address these issues, we propose a lightweight, landmark-free CNN regressor guided by anthropometric facial measures. The model comprises two components: an Anthropometric Facial Measure Regressor (AFMR) that estimates a 4D vector of key facial segment lengths, and a CNN-based module that generates five uncertainty-based facial heatmaps. Evaluations on the BIWI and AFLW datasets show that our method outperforms state-of-the-art approaches, reducing localization error by 0.13° and 0.67°, respectively, while achieving faster convergence, lower parameter count, and real-time suitability.
Ensuring safety in smart buildings is crucial due to the increasing prevalence of smoke and fire hazards in modern environments. This paper introduces a novel privacy-preserving FL approach based on a CNN1D for smoke ...
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ISBN:
(数字)9798331527396
ISBN:
(纸本)9798331527402
Ensuring safety in smart buildings is crucial due to the increasing prevalence of smoke and fire hazards in modern environments. This paper introduces a novel privacy-preserving FL approach based on a CNN1D for smoke and fire detection in smart buildings. Our system integrates data from wearable environmental sensors to train a lightweight, edge-deployable DL-CNN1D model, ensuring data privacy while enabling collaborative learning across distributed clients using Federated Averaging (FedAvg) aggregation. Experiments conducted on a comprehensive air measurement dataset for smoke and fire detection demonstrate exceptional performance, with the global model achieving 99.97% accuracy, 99.96% precision, in smoke and fire recognition. Our model demonstrates a low communication cost of 0.4 MB, underscoring its efficiency for real-time applications. Our FL-based approach represents a significant step towards balancing the need for robust safety systems with growing privacy concerns in smart building environments.
Current service robots without learning ability are not qualified for many complex tasks. Therefore, it is very significant to decompose the complex task into repeatable execution unit. In this paper, we propose a com...
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