4,268 research outputs found
Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models
Machine learning techniques are now integral to the advancement of
intelligent urban services, playing a crucial role in elevating the efficiency,
sustainability, and livability of urban environments. The recent emergence of
foundation models such as ChatGPT marks a revolutionary shift in the fields of
machine learning and artificial intelligence. Their unparalleled capabilities
in contextual understanding, problem solving, and adaptability across a wide
range of tasks suggest that integrating these models into urban domains could
have a transformative impact on the development of smart cities. Despite
growing interest in Urban Foundation Models~(UFMs), this burgeoning field faces
challenges such as a lack of clear definitions, systematic reviews, and
universalizable solutions. To this end, this paper first introduces the concept
of UFM and discusses the unique challenges involved in building them. We then
propose a data-centric taxonomy that categorizes current UFM-related works,
based on urban data modalities and types. Furthermore, to foster advancement in
this field, we present a promising framework aimed at the prospective
realization of UFMs, designed to overcome the identified challenges.
Additionally, we explore the application landscape of UFMs, detailing their
potential impact in various urban contexts. Relevant papers and open-source
resources have been collated and are continuously updated at
https://github.com/usail-hkust/Awesome-Urban-Foundation-Models
Architectures and Key Technical Challenges for 5G Systems Incorporating Satellites
Satellite Communication systems are a promising solution to extend and
complement terrestrial networks in unserved or under-served areas. This aspect
is reflected by recent commercial and standardisation endeavours. In
particular, 3GPP recently initiated a Study Item for New Radio-based, i.e., 5G,
Non-Terrestrial Networks aimed at deploying satellite systems either as a
stand-alone solution or as an integration to terrestrial networks in mobile
broadband and machine-type communication scenarios. However, typical satellite
channel impairments, as large path losses, delays, and Doppler shifts, pose
severe challenges to the realisation of a satellite-based NR network. In this
paper, based on the architecture options currently being discussed in the
standardisation fora, we discuss and assess the impact of the satellite channel
characteristics on the physical and Medium Access Control layers, both in terms
of transmitted waveforms and procedures for enhanced Mobile BroadBand (eMBB)
and NarrowBand-Internet of Things (NB-IoT) applications. The proposed analysis
shows that the main technical challenges are related to the PHY/MAC procedures,
in particular Random Access (RA), Timing Advance (TA), and Hybrid Automatic
Repeat reQuest (HARQ) and, depending on the considered service and
architecture, different solutions are proposed.Comment: Submitted to Transactions on Vehicular Technologies, April 201
THE COLUMBUS GROUND SEGMENT – A PRECURSOR FOR FUTURE MANNED MISSIONS
In the beginning the space programs were self standing national activities, often in competition to other nations. Today space flight becomes more and more an international task. Complex space mission and deep space explorations are not longer to be stemmed by one agency or nation alone but are joint activities of several nations. The best example for such a joint (ad-) venture at the moment is the International Space Station ISS.
Such international activities define complete new requirements for the supporting ground segments. The world-wide distribution of a ground segment is not any longer limited to a network of ground stations with the aim to provide a good coverage of the space craft. The coverage is sometimes – like for the ISSanyway ensured by using a relay satellite system instead. In addition to the enhanced down- and uplink methods a ground segment is aimed to connect the different centres of competence of all participating agencies/nations.
From the space craft operations point of view such transnational ground segments are required to support distributed and shared operations in a predefined decision/commanding hierarchy. This has to be taken into account in the technical topology as well as for the operational set-up and teaming.
Last not least increases the duration of missions, which requires a certain flexibility of the ground segment and long-term maintenance strategies for the ground segment with a special emphasis on nonintrusive replacements. The Russian space station MIR has been in the orbit for about 15 years, the ISS is currently targeted for 2020, to be for over 20 years in space
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Semantic units: organizing knowledge graphs into semantically meaningful units of representation
Background
In today’s landscape of data management, the importance of knowledge graphs and ontologies is escalating as critical mechanisms aligned with the FAIR Guiding Principles—ensuring data and metadata are Findable, Accessible, Interoperable, and Reusable. We discuss three challenges that may hinder the effective exploitation of the full potential of FAIR knowledge graphs.
Results
We introduce “semantic units” as a conceptual solution, although currently exemplified only in a limited prototype. Semantic units structure a knowledge graph into identifiable and semantically meaningful subgraphs by adding another layer of triples on top of the conventional data layer. Semantic units and their subgraphs are represented by their own resource that instantiates a corresponding semantic unit class. We distinguish statement and compound units as basic categories of semantic units. A statement unit is the smallest, independent proposition that is semantically meaningful for a human reader. Depending on the relation of its underlying proposition, it consists of one or more triples. Organizing a knowledge graph into statement units results in a partition of the graph, with each triple belonging to exactly one statement unit. A compound unit, on the other hand, is a semantically meaningful collection of statement and compound units that form larger subgraphs. Some semantic units organize the graph into different levels of representational granularity, others orthogonally into different types of granularity trees or different frames of reference, structuring and organizing the knowledge graph into partially overlapping, partially enclosed subgraphs, each of which can be referenced by its own resource.
Conclusions
Semantic units, applicable in RDF/OWL and labeled property graphs, offer support for making statements about statements and facilitate graph-alignment, subgraph-matching, knowledge graph profiling, and for management of access restrictions to sensitive data. Additionally, we argue that organizing the graph into semantic units promotes the differentiation of ontological and discursive information, and that it also supports the differentiation of multiple frames of reference within the graph
New Design Techniques for Dynamic Reconfigurable Architectures
L'abstract è presente nell'allegato / the abstract is in the attachmen
Image data processing system requirements study. Volume 1: Analysis
Digital image processing, image recorders, high-density digital data recorders, and data system element processing for use in an Earth Resources Survey image data processing system are studied. Loading to various ERS systems is also estimated by simulation
ASCR/HEP Exascale Requirements Review Report
This draft report summarizes and details the findings, results, and
recommendations derived from the ASCR/HEP Exascale Requirements Review meeting
held in June, 2015. The main conclusions are as follows. 1) Larger, more
capable computing and data facilities are needed to support HEP science goals
in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of
the demand at the 2025 timescale is at least two orders of magnitude -- and in
some cases greater -- than that available currently. 2) The growth rate of data
produced by simulations is overwhelming the current ability, of both facilities
and researchers, to store and analyze it. Additional resources and new
techniques for data analysis are urgently needed. 3) Data rates and volumes
from HEP experimental facilities are also straining the ability to store and
analyze large and complex data volumes. Appropriately configured
leadership-class facilities can play a transformational role in enabling
scientific discovery from these datasets. 4) A close integration of HPC
simulation and data analysis will aid greatly in interpreting results from HEP
experiments. Such an integration will minimize data movement and facilitate
interdependent workflows. 5) Long-range planning between HEP and ASCR will be
required to meet HEP's research needs. To best use ASCR HPC resources the
experimental HEP program needs a) an established long-term plan for access to
ASCR computational and data resources, b) an ability to map workflows onto HPC
resources, c) the ability for ASCR facilities to accommodate workflows run by
collaborations that can have thousands of individual members, d) to transition
codes to the next-generation HPC platforms that will be available at ASCR
facilities, e) to build up and train a workforce capable of developing and
using simulations and analysis to support HEP scientific research on
next-generation systems.Comment: 77 pages, 13 Figures; draft report, subject to further revisio
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