308 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Rethinking Film Festivals in the Pandemic Era and After

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    ‘Rethinking Film Festivals’ explores how COVID-19 intervened in the film festival circuit by disrupting regular industry cycles and allowing new ways of reaching audiences to flourish. Films found other distribution channels, often online, while the festival format proved particularly vulnerable in a one-half-meter society. The search for a full-fledged substitute for live events and shared experiences involved all kinds of experimentation and an acceleration of digital developments that were already underway. The book documents how different festivals in different local contexts were affected differently by the pandemic and reacted differently to it as well. At the same time, the case studies confirm the interconnectedness and transnational relationships inherent in globalised media systems. Finally, the book seizes the momentum of the crisis to make the case for sustainable interventions: festivals must address their ecological footprint, decolonise their organisations, and ensure that their history and heritage is safeguarded for the future

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Geographic information extraction from texts

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    A large volume of unstructured texts, containing valuable geographic information, is available online. This information – provided implicitly or explicitly – is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction

    Applications

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    Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

    Routing protocol for V2X communications for Urban VANETs

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    Intelligent Transportation Systems (ITSs) have been attracting tremendous attention in both academia and industry due to emerging applications that pave the way towards safer enjoyable journeys and inclusive digital partnerships. Undoubtedly, these ITS applications will demand robust routing protocols that not only focus on Inter-Vehicle Communications but also on providing fast, reliable, and secure access to the infrastructure. This thesis aims mainly to introduce the challenges of data packets routing through urban environment using the help of infrastructure. Broadcasting transmission is an essential operational technique that serves a broad range of applications which demand different restrictive QoS provisioning levels. Although broadcast communication has been investigated widely in highway vehicular networks, it is undoubtedly still a challenge in the urban environment due to the obstacles, such as high buildings. In this thesis, the Road-Topology based Broadcast Protocol (RTBP) is proposed, a distance and contention-based forwarding scheme suitable for both urban and highway vehicular environments. RTBP aims at assigning the highest forwarding priority to a vehicle, called a mobile repeater, having the greatest capability to send the packet in multiple directions. In this way, RTBP effectively reduces the number of competing vehicles and minimises the number of hops required to retransmit the broadcast packets around the intersections to cover the targeted area. By investigating the RTBP under realistic urban scenarios against well-known broadcast protocols, eMDR and TAF, that are dedicated to retransmitting the packets around intersections, the results showed the superiority of the RTBP in delivering the most critical warning information for 90% of vehicles with significantly lower delay of 58% and 70% compared to eMDR and TAF. The validation of this performance was clear when the increase in the number of vehicles. Secondly, a Fast and Reliable Hybrid routing (FRHR) protocol is introduced for efficient infrastructure access which is capable of handling efficient vehicle to vehicle communications. Interface to infrastructure is provided by carefully placed RoadSide Units (RSUs) which broadcast beacons in a multi-hop fashion in constrained areas. This enables vehicles proactively to maintain fresh minimum-delay routes to other RSUs while reactively discovering routes to nearby vehicles. The proposed protocol utilizes RSUs connected to the wired backbone network to relay packets toward remote vehicles. A vehicle selects an RSU to register with according to the expected mean delay instead of the device’s remoteness. The FRHR performance is evaluated against established infrastructure routing protocols, Trafroute, IGSR and RBVT-R that are dedicated to for urban environment, the results showed an improvement of 20% to 33% in terms of packet delivery ratio and lower latency particularly in sparse networks due to its rapid response to changes in network connectivity. Thirdly, focusing on increasing FRHR’s capability to provide more stable and durable routes to support the QoS requirements of expected wide-range ITS applications on the urban environment, a new route selection mechanism is introduced, aiming at selecting highly connected crossroads. The new protocol is called, Stable Infrastructure Routing Protocol (SIRP). Intensive simulation results showed that SIRP offers low end-to-end delay and high delivery ratio with varying traffic density, while resolving the problem of frequent link failures

    Fundamentals

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    Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

    Naval Postgraduate School Academic Catalog - February 2023

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