As assisted and autonomous driving systems become more prevalent, the need for accurate interpretation of road traffic signs is critical for driving safety and functionality. Current camera-based recognition methods f...
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ISBN:
(纸本)9798400714795
As assisted and autonomous driving systems become more prevalent, the need for accurate interpretation of road traffic signs is critical for driving safety and functionality. Current camera-based recognition methods face challenges due to the variability of traffic signs and environmental conditions, leading to potential inaccuracies. To address this, we propose LiDARMarker, a type of machine-readable traffic sign using infrared materials, making it invisible to human drivers but detectable by LiDAR-equipped vehicles. This paper introduces the design, fabrication, and efficient decoding methods of LiDARMarker. LiDARMarker is tailored to the emerging capabilities and needs of modern vehicles, enhancing their ability and accuracy in traffic sign recognition while avoiding interference with human drivers. Through the proposal of LiDARMarker, we aim to inspire the rethinking of the design of traffic sign systems in the context of modern vehicles.
The continuous improvement in energy efficiency of existing data centers would help reduce their environmental footprints. Greening of Data Centers could be attained using renewable energy sources or more energy effic...
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ISBN:
(纸本)9781450393973
The continuous improvement in energy efficiency of existing data centers would help reduce their environmental footprints. Greening of Data Centers could be attained using renewable energy sources or more energy efficient compute systems and effective cooling systems. A reliable cooling system is necessary to generate a persistent flow of cold air to cool servers that are subjected to increasing computational load demand. As a matter of fact, servers' dissipated heat effects a strain on the cooling systems and consequently, on electricity consumption. Generated heat in the data center is categorized into different granularity levels namely: server level, rack level, room level, and data center level. Several datasets are collected at ENEA Portici Data Center from CRESCO 6 cluster - a High-Performance computing Cluster. The cooling and environmental aspects of the data center is also considered for data analysis. This research aims to conduct a rigorous exploratory data analysis on each dataset separately and collectively followed in various stages. This work presents descriptive and inferential analyses for feature selection and extraction process. Furthermore, a supervised Machine learning modelling and correlation estimation is performed on all the datasets to abstract relevant features. that would have an impact on energy efficiency in data centers.
As CMOS scaling approaches its fundamental limits, the explosive rise of AI and LLMs has unveiled profound bottlenecks in computing architectures. This paper presents two groundbreaking paradigms poised to reshape the...
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With the rapid development of machine learning and big data technologies, ensuring user privacy has become a pressing challenge. Secure multi-party computation offers a solution to this challenge by enabling privacy-p...
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The proceedings contain 74 papers. The topics discussed include: in three steps to software product lines: a practical example from the automotive industry;improving the customization of software product lines through...
ISBN:
(纸本)9781450394437
The proceedings contain 74 papers. The topics discussed include: in three steps to software product lines: a practical example from the automotive industry;improving the customization of software product lines through the definition of local features;quality-aware analysis and optimization of virtual network functions;evolvable SPL management with partial knowledge: an application to anomaly detection in time series;from feature models to feature toggles in practice;extended abstract: we’re not gonna break it! consistency-preserving operators for efficient product line configuration;multidisciplinary variability management for cyber-physical production systems;feature and variability extraction from agile specifications and their related source code for software product line migration;Baital: an adaptive weighted sampling platform for configurable systems;and Acapulco: an extensible tool for identifying optimal and consistent feature model configurations.
Federated cloud environments have emerged to integrate multiple cloud providers like AWS, Azure, and Google Cloud seamlessly into cloud computing. Optimising resource utilisation and ensuring high availability in such...
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Shared control is an emerging interaction paradigm in which a human and an AI partner collaboratively control a system. Shared control unifies human and artificial intelligence, making the human's interactions wit...
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The proceedings contain 74 papers. The topics discussed include: in three steps to software product lines: a practical example from the automotive industry;improving the customization of software product lines through...
ISBN:
(纸本)9781450392068
The proceedings contain 74 papers. The topics discussed include: in three steps to software product lines: a practical example from the automotive industry;improving the customization of software product lines through the definition of local features;quality-aware analysis and optimization of virtual network functions;evolvable SPL management with partial knowledge: an application to anomaly detection in time series;from feature models to feature toggles in practice;extended abstract: we’re not gonna break it! consistency-preserving operators for efficient product line configuration;multidisciplinary variability management for cyber-physical production systems;feature and variability extraction from agile specifications and their related source code for software product line migration;Baital: an adaptive weighted sampling platform for configurable systems;and Acapulco: an extensible tool for identifying optimal and consistent feature model configurations.
Intermittently operating embedded computing platforms powered by energy harvesting require software frameworks to protect from errors caused by Write After Read (WAR) dependencies. A powerful method of code protection...
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ISBN:
(纸本)9781450392655
Intermittently operating embedded computing platforms powered by energy harvesting require software frameworks to protect from errors caused by Write After Read (WAR) dependencies. A powerful method of code protection for systems with non-volatile main memory utilizes compiler analysis to insert a checkpoint inside each WAR violation in the code. However, such software frameworks are oblivious to the code structure-and therefore, inefficient-when many consecutive WAR violations exist. Our insight is that by transforming the input code, i.e., moving individual write operations from unique WARs close to each other, we can significantly reduce the number of checkpoints. This idea is the foundation for WARio: a set of compiler transformations for efficient code generation for intermittent computing. WARio, on average, reduces checkpoint overhead by 58%, and up to 88%, compared to the state of the art across various benchmarks.
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