scholarly journals A Pragmatic Approach to Semantic Annotation for Search of Legal Texts – An Experiment on GDPR

2021 ◽  
Author(s):  
Adeline Nazarenko ◽  
François Lévy ◽  
Adam Wyner
Keyword(s):  
Gold Standard ◽  
Large Scale ◽  
Semantic Annotation ◽  
Legal Reasoning ◽  
Statistical Information ◽  
Coarse Grained ◽  
Third Way ◽  
Plain Text ◽  
Legal Texts ◽  
Further Development

Tools must be developed to help draft, consult, and explore textual legal sources. Between statistical information retrieval and the formalization of textual rules for automated legal reasoning, we defend a more pragmatic third way that enriches legal texts with a coarse-grained, interpretation-neutral, semantic annotation layer. The aim is that legal texts can be enriched on a large scale at a reasonable cost, paving the way for new search capabilities that will facilitate mining of legal sources. This new approach is illustrated on a proof-of-concept experiment that consisted in semantically annotating a significant part of the French version of the GDPR. The paper presents the design methodology of the annotation language, a first version of a Core Legal Annotation Language (CLAL), together with its formalization in XML, the gold standard resulting from the annotation of GDPR, and examples of user questions that can be better answered by semantic than by plain text search. This experimentation demonstrates the potential of the proposed approach and provides a basis for further development. All resources developed for that GDPR experiment are language independent and are publicly available.

A Case for Automated Large Scale Semantic Annotation

2003 ◽  
Author(s):  
Stephen Dill ◽  
Nadav Eiron ◽  
David Gibson ◽  
Daniel Gruhl ◽  
R. Guha ◽  
...  
Keyword(s):  
Large Scale ◽  
Semantic Annotation

scholarly journals The Principle of Directive-Compliant Development of the Law and the Contra Legem Limit

2020 ◽  
Vol 16 (4) ◽  
pp. 465-488
Author(s):  
Thomas M.J. Möllers
Keyword(s):  
Case Law ◽  
Third Party ◽  
Broad Term ◽  
Legal Texts ◽  
Classical Methodology ◽  
The Law ◽  
Legal Methodology ◽  
The Relationship ◽  
Further Development ◽  
Domestic Law

AbstractThe Europeanisation of domestic law calls for a classical methodology to ‘update’ the established traditions of the law. The relationship between European directives and national law is difficult, since directives do apply, but European legal texts need to be implemented into national law. Whilst directives are not binding on private individuals, there is no direct third-party effect, but only an ‘indirect effect’. This effect is influenced by the stipulations of the ECJ, but is ultimately determined in accordance with methodical principles of national law. The ECJ uses a broad term of interpretation of the law. In contrast, in German and Austrian legal methodology the wording of a provision defines the dividing line between interpretation and further development of the law. The article reveals how legal scholars and the case-law have gradually shown in recent decades a greater willingness to shift from a narrow, traditional boundary of permissible development of the law to a modern line of case-law regarding the boundary of directive-compliant, permissible development of the law.

scholarly journals Mean-Field Models for EEG/MEG: From Oscillations to Waves

2021 ◽  
Author(s):  
Áine Byrne ◽  
James Ross ◽  
Rachel Nicks ◽  
Stephen Coombes
Keyword(s):  
Gap Junction ◽  
Large Scale ◽  
Mean Field ◽  
Coarse Grained ◽  
Neural Mass Model ◽  
Neuron Network ◽  
Mass Model ◽  
Mean Field Model ◽  
Neural Mass ◽  
The Rich

AbstractNeural mass models have been used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. Here we consider a simple spiking neuron network model that has recently been shown to admit an exact mean-field description for both synaptic and gap-junction interactions. The mean-field model takes a similar form to a standard neural mass model, with an additional dynamical equation to describe the evolution of within-population synchrony. As well as reviewing the origins of this next generation mass model we discuss its extension to describe an idealised spatially extended planar cortex. To emphasise the usefulness of this model for EEG/MEG modelling we show how it can be used to uncover the role of local gap-junction coupling in shaping large scale synaptic waves.

scholarly journals Simba

2021 ◽  
Vol 64 (6) ◽  
pp. 107-116
Author(s):  
Yakun Sophia Shao ◽  
Jason Cemons ◽  
Rangharajan Venkatesan ◽  
Brian Zimmer ◽  
Matthew Fojtik ◽  
...  
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Data Locality ◽  
Coarse Grained ◽  
Batch Size ◽  
Peak Performance ◽  
Large Scale Systems ◽  
High Area ◽  
On Chip ◽  
And Storage

Package-level integration using multi-chip-modules (MCMs) is a promising approach for building large-scale systems. Compared to a large monolithic die, an MCM combines many smaller chiplets into a larger system, substantially reducing fabrication and design costs. Current MCMs typically only contain a handful of coarse-grained large chiplets due to the high area, performance, and energy overheads associated with inter-chiplet communication. This work investigates and quantifies the costs and benefits of using MCMs with finegrained chiplets for deep learning inference, an application domain with large compute and on-chip storage requirements. To evaluate the approach, we architected, implemented, fabricated, and tested Simba, a 36-chiplet prototype MCM system for deep-learning inference. Each chiplet achieves 4 TOPS peak performance, and the 36-chiplet MCM package achieves up to 128 TOPS and up to 6.1 TOPS/W. The MCM is configurable to support a flexible mapping of DNN layers to the distributed compute and storage units. To mitigate inter-chiplet communication overheads, we introduce three tiling optimizations that improve data locality. These optimizations achieve up to 16% speedup compared to the baseline layer mapping. Our evaluation shows that Simba can process 1988 images/s running ResNet-50 with a batch size of one, delivering an inference latency of 0.50 ms.

scholarly journals Mobility patterns are associated with experienced income segregation in large US cities

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Esteban Moro ◽  
Dan Calacci ◽  
Xiaowen Dong ◽  
Alex Pentland
Keyword(s):  
Large Scale ◽  
Mobility Model ◽  
Coarse Grained ◽  
Spatial Proximity ◽  
Mobility Patterns ◽  
Data Set ◽  
Residential Patterns ◽  
Income Segregation ◽  
Mobility Data ◽  
Mobility Behavior

AbstractTraditional understanding of urban income segregation is largely based on static coarse-grained residential patterns. However, these do not capture the income segregation experience implied by the rich social interactions that happen in places that may relate to individual choices, opportunities, and mobility behavior. Using a large-scale high-resolution mobility data set of 4.5 million mobile phone users and 1.1 million places in 11 large American cities, we show that income segregation experienced in places and by individuals can differ greatly even within close spatial proximity. To further understand these fine-grained income segregation patterns, we introduce a Schelling extension of a well-known mobility model, and show that experienced income segregation is associated with an individual’s tendency to explore new places (place exploration) as well as places with visitors from different income groups (social exploration). Interestingly, while the latter is more strongly associated with demographic characteristics, the former is more strongly associated with mobility behavioral variables. Our results suggest that mobility behavior plays an important role in experienced income segregation of individuals. To measure this form of income segregation, urban researchers should take into account mobility behavior and not only residential patterns.

scholarly journals Heterogeneous lamella structure unites ultrafine-grain strength with coarse-grain ductility

2015 ◽  
Vol 112 (47) ◽  
pp. 14501-14505 ◽  
Author(s):  
Xiaolei Wu ◽  
Muxin Yang ◽  
Fuping Yuan ◽  
Guilin Wu ◽  
Yujie Wei ◽  
...  
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
High Strength ◽  
Back Stress ◽  
Coarse Grained ◽  
Ultrafine Grain ◽  
Asymmetric Rolling ◽  
Dislocation Hardening ◽  
Ultrafine Grained ◽  
Lamella Structure

Grain refinement can make conventional metals several times stronger, but this comes at dramatic loss of ductility. Here we report a heterogeneous lamella structure in Ti produced by asymmetric rolling and partial recrystallization that can produce an unprecedented property combination: as strong as ultrafine-grained metal and at the same time as ductile as conventional coarse-grained metal. It also has higher strain hardening than coarse-grained Ti, which was hitherto believed impossible. The heterogeneous lamella structure is characterized with soft micrograined lamellae embedded in hard ultrafine-grained lamella matrix. The unusual high strength is obtained with the assistance of high back stress developed from heterogeneous yielding, whereas the high ductility is attributed to back-stress hardening and dislocation hardening. The process discovered here is amenable to large-scale industrial production at low cost, and might be applicable to other metal systems.

scholarly journals A Novel Chaotic Neural Network Using Memristive Synapse with Applications in Associative Memory

2012 ◽  
Vol 2012 ◽  
pp. 1-19 ◽  
Author(s):  
Xiaofang Hu ◽  
Shukai Duan ◽  
Lidan Wang
Keyword(s):  
Neural Network ◽  
Associative Memory ◽  
Large Scale ◽  
Cmos Technology ◽  
Chaotic Neural Network ◽  
Circuit Element ◽  
Nanoscale Cmos ◽  
Dynamical Behaviors ◽  
Implementation Scheme ◽  
Further Development

Chaotic Neural Network, also denoted by the acronym CNN, has rich dynamical behaviors that can be harnessed in promising engineering applications. However, due to its complex synapse learning rules and network structure, it is difficult to update its synaptic weights quickly and implement its large scale physical circuit. This paper addresses an implementation scheme of a novel CNN with memristive neural synapses that may provide a feasible solution for further development of CNN. Memristor, widely known as the fourth fundamental circuit element, was theoretically predicted by Chua in 1971 and has been developed in 2008 by the researchers in Hewlett-Packard Laboratory. Memristor based hybrid nanoscale CMOS technology is expected to revolutionize the digital and neuromorphic computation. The proposed memristive CNN has four significant features: (1) nanoscale memristors can simplify the synaptic circuit greatly and enable the synaptic weights update easily; (2) it can separate stored patterns from superimposed input; (3) it can deal with one-to-many associative memory; (4) it can deal with many-to-many associative memory. Simulation results are provided to illustrate the effectiveness of the proposed scheme.

Mechanical Patterning in Animal Morphogenesis

2021 ◽  
Vol 37 (1) ◽  
Author(s):  
Yonit Maroudas-Sacks ◽  
Kinneret Keren
Keyword(s):  
Pattern Formation ◽  
Large Scale ◽  
Coarse Grained ◽  
Annual Review ◽  
Publication Date ◽  
Biochemical Processes ◽  
Substantial Progress ◽  
Biological Pattern Formation ◽  
Effective Theories ◽  
Biochemical Signals

Morphogenesis is one of the most remarkable examples of biological pattern formation. Despite substantial progress in the field, we still do not understand the organizational principles responsible for the robust convergence of the morphogenesis process across scales to form viable organisms under variable conditions. Achieving large-scale coordination requires feedback between mechanical and biochemical processes, spanning all levels of organization and relating the emerging patterns with the mechanisms driving their formation. In this review, we highlight the role of mechanics in the patterning process, emphasizing the active and synergistic manner in which mechanical processes participate in developmental patterning rather than merely following a program set by biochemical signals. We discuss the value of applying a coarse-grained approach toward understanding this complex interplay, which considers the large-scale dynamics and feedback as well as complementing the reductionist approach focused on molecular detail. A central challenge in this approach is identifying relevant coarse-grained variables and developing effective theories that can serve as a basis for an integrated framework for understanding this remarkable pattern-formation process. Expected final online publication date for the Annual Review of Cell and Developmental Biology, Volume 37 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Structural topology optimization of bridge girders in cable supported bridges

2018 ◽  
Author(s):  
Mads Baandrup ◽  
Ole Sigmund ◽  
Niels Aage
Keyword(s):  
Topology Optimization ◽  
Large Scale ◽  
Design Method ◽  
Optimization Method ◽  
Bridge Girders ◽  
Structural Topology ◽  
Box Girders ◽  
Box Girder ◽  
Fine Mesh ◽  
Further Development

<p>This work applies a ultra large scale topology optimization method to study the optimal structure of bridge girders in cable supported bridges.</p><p>The current classic orthotropic box girder designs are limited in further development and optimiza­ tion, and suffer from substantial fatigue issues. A great disadvantage of the orthotropic girder is the loads being carried one direction at a time, thus creating stress hot spots and fatigue problems. Hence, a new design concept has the potential to solve many of the limitations in the current state­ of-the-art.</p><p>We present a design method based on ultra large scale topology optimization. The highly detailed structures and fine mesh-discretization permitted by ultra large scale topology optimization reveal new design features and previously unseen eff ects. The results demonstrate the potential of gener­ ating completely different design solutions for bridge girders in cable supported bridges, which dif­ fer significantly from the classic orthotropic box girders.</p><p>The overall goal of the presented work is to identify new and innovative, but at the same time con­ structible and economically reasonable, solutions tobe implemented into the design of future cable supported bridges.</p>

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