2,218 research outputs found
Multidisciplinary perspectives on Artificial Intelligence and the law
This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Swift: A modern highly-parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications
Numerical simulations have become one of the key tools used by theorists in
all the fields of astrophysics and cosmology. The development of modern tools
that target the largest existing computing systems and exploit state-of-the-art
numerical methods and algorithms is thus crucial. In this paper, we introduce
the fully open-source highly-parallel, versatile, and modular coupled
hydrodynamics, gravity, cosmology, and galaxy-formation code Swift. The
software package exploits hybrid task-based parallelism, asynchronous
communications, and domain-decomposition algorithms based on balancing the
workload, rather than the data, to efficiently exploit modern high-performance
computing cluster architectures. Gravity is solved for using a
fast-multipole-method, optionally coupled to a particle mesh solver in Fourier
space to handle periodic volumes. For gas evolution, multiple modern flavours
of Smoothed Particle Hydrodynamics are implemented. Swift also evolves
neutrinos using a state-of-the-art particle-based method. Two complementary
networks of sub-grid models for galaxy formation as well as extensions to
simulate planetary physics are also released as part of the code. An extensive
set of output options, including snapshots, light-cones, power spectra, and a
coupling to structure finders are also included. We describe the overall code
architecture, summarize the consistency and accuracy tests that were performed,
and demonstrate the excellent weak-scaling performance of the code using a
representative cosmological hydrodynamical problem with billion
particles. The code is released to the community alongside extensive
documentation for both users and developers, a large selection of example test
problems, and a suite of tools to aid in the analysis of large simulations run
with Swift.Comment: 39 pages, 18 figures, submitted to MNRAS. Code, documentation, and
examples available at www.swiftsim.co
Automatic Generation of Personalized Recommendations in eCoaching
Denne avhandlingen omhandler eCoaching for personlig livsstilsstøtte i sanntid ved bruk av informasjons- og kommunikasjonsteknologi. Utfordringen er å designe, utvikle og teknisk evaluere en prototyp av en intelligent eCoach som automatisk genererer personlige og evidensbaserte anbefalinger til en bedre livsstil. Den utviklede løsningen er fokusert på forbedring av fysisk aktivitet. Prototypen bruker bærbare medisinske aktivitetssensorer. De innsamlede data blir semantisk representert og kunstig intelligente algoritmer genererer automatisk meningsfulle, personlige og kontekstbaserte anbefalinger for mindre stillesittende tid. Oppgaven bruker den veletablerte designvitenskapelige forskningsmetodikken for å utvikle teoretiske grunnlag og praktiske implementeringer. Samlet sett fokuserer denne forskningen på teknologisk verifisering snarere enn klinisk evaluering.publishedVersio
Fast Algorithms for Separable Linear Programs
In numerical linear algebra, considerable effort has been devoted to
obtaining faster algorithms for linear systems whose underlying matrices
exhibit structural properties. A prominent success story is the method of
generalized nested dissection~[Lipton-Rose-Tarjan'79] for separable matrices.
On the other hand, the majority of recent developments in the design of
efficient linear program (LP) solves do not leverage the ideas underlying these
faster linear system solvers nor consider the separable structure of the
constraint matrix.
We give a faster algorithm for separable linear programs. Specifically, we
consider LPs of the form , where the
graphical support of the constraint matrix is -separable. These include flow problems on planar graphs
and low treewidth matrices among others. We present an time algorithm for these LPs, where is
the relative accuracy of the solution.
Our new solver has two important implications: for the -multicommodity
flow problem on planar graphs, we obtain an algorithm running in
time in the high accuracy regime; and when the
support of is -separable with , our
algorithm runs in time, which is nearly optimal. The latter
significantly improves upon the natural approach of combining interior point
methods and nested dissection, whose time complexity is lower bounded by
, where is the
matrix multiplication constant. Lastly, in the setting of low-treewidth LPs, we
recover the results of [DLY,STOC21] and [GS,22] with significantly simpler data
structure machinery.Comment: 55 pages. To appear at SODA 202
Science and Innovations for Food Systems Transformation
This Open Access book compiles the findings of the Scientific Group of the United Nations Food Systems Summit 2021 and its research partners. The Scientific Group was an independent group of 28 food systems scientists from all over the world with a mandate from the Deputy Secretary-General of the United Nations. The chapters provide science- and research-based, state-of-the-art, solution-oriented knowledge and evidence to inform the transformation of contemporary food systems in order to achieve more sustainable, equitable and resilient systems
- …