Assurance of evolving large cyber-physical systems (CPS) is time-consuming, and usually a bottleneck for deploying them with confidence. Several factors contribute to this problem, including the lack of effective reus...
ISBN:
(纸本)9798400716072
Assurance of evolving large cyber-physical systems (CPS) is time-consuming, and usually a bottleneck for deploying them with confidence. Several factors contribute to this problem, including the lack of effective reuse of assurance results, the difficulty to integrate multiple analyses for multiple subsystems, and the lack of explicit consideration of the different levels of trust that different analyses provide. In this paper, we present an approach to assure large CPS that aims to overcome these barriers.
Modern web applications use features like camera and geolocation for personalized experiences, requiring user permission via browser prompts. To explain these requests, applications provide rationales - contextual inf...
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Context: SBSI ties together the Brazilian Information systems community since 2004, 20 years ago. Through their research, the community has matured, grown and established, through authorships, institutions, research i...
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ISBN:
(纸本)9798400709968
Context: SBSI ties together the Brazilian Information systems community since 2004, 20 years ago. Through their research, the community has matured, grown and established, through authorships, institutions, research interests, and collaborations. Problem: complexity, diversity and plurality grew as the SBSI, and IS community, grew and spread;presenting self-monitoring challenges. There are few meta-scientific studies covering collaborations and quantitative studies, in different dimensions. Solution: we conducted a comprehensive and complete study, analyzing several SBSI aspects, with a materialistic emphasis on authorship (3595) and studies (1052), covering all 19 years of the event. IS Theory: Argumentative theory, Critical social theory. Method: we conducted a descriptive-analytical study, similar to a scope review. We use quantitative analyzes and Social Network analysis techniques, prioritizing a temporal perspective, exposing the evolution of phenomena. We deal with different dimensions and interrelate the appropriate or plausible ones. Summarization of Results: this work reiterates or enriches the findings of previous works. Reinforces a low number of female authors, while several of the most prolific authors are women. As institutions, USP, UNIRIO, UFPE, UFRJ and UNISINOS stand out. The Southeast region, Rio Grande do Sul and Pernambuco stands out. Collaborations and authorship numbers differs. Brazilian Portuguese predominates as the main language, except in 2021, an outlier. The keywords are reflect an emphasis on information systems. Contributions and Impacts on the IS area: we present a multidimensional Brazilian IS panorama understanding, for better meta-scientific and organizational decision-making. It serves as input and complement to think about Brazilian IS challenges, current and future.
With the broader adoption of virtual reality (VR), objective physiological measurements to automatically assess a user's emotional state are gaining importance. Emotions affect human behavior, perception, cognitio...
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ISBN:
(纸本)9798400700699
With the broader adoption of virtual reality (VR), objective physiological measurements to automatically assess a user's emotional state are gaining importance. Emotions affect human behavior, perception, cognition, and decision-making. Their recognition allows analysis of VR experiences and enables systems to react to and interact with a user's emotions. Facial expressions are one of the most potent and natural signals to recognize emotions. Automatic facial expression recognition (FER) typically relies on facial images. However, users wear head-mounted displays (HMDs) in immersive VR environments, which occlude almost the entire upper half of the face. That severely limits the capabilities of conventional FER methods. We address this emerging challenge with our systematic literature review. To our knowledge, it is the first review on FER in immersive VR scenarios where HMDs partially occlude a user's face. We identified 256 related works and included 21 for detailed analysis. Our review provides a comprehensive overview of the state-of-the-art and draws conclusions for future research.
This work develops a distributed graph neural network (GNN) methodology for mesh-based modeling applications using a consistent neural message passing layer. As the name implies, the focus is on enabling scalable oper...
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5G claims to support mobility up to 500 km/h according to the 3GPP standard. However, its field performance under high-speed scenes remains in mystery. In this paper, we conduct the first large-scale measurement campa...
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The increasing use of camera streams on mobile systems has raised significant privacy concerns due to unauthorized visual data access by applications. Existing solutions either burden users with excessive interaction ...
ISBN:
(纸本)9798400714795
The increasing use of camera streams on mobile systems has raised significant privacy concerns due to unauthorized visual data access by applications. Existing solutions either burden users with excessive interaction or lack semantic understanding of contextual privacy norms. This paper introduces PrivacyAgent, a novel visual privacy protection framework leveraging multimodal large language models (LLMs) to enable context-aware and fine-grained privacy control on mobile systems. PrivacyAgent intercepts camera streams via a virtualized I/O layer and restricts untrusted apps to privacy-compliant content with minimal user overhead.
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.
Accurate data acquisition plays a pivotal role during the execution of diverse maintenance, monitoring, and testing tasks involving switchgear equipment. This significance is particularly pronounced when dealing with ...
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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.
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