38,853 research outputs found
Fatal attraction: a critique of Carl Schmitt's international political and legal theory
The ongoing Schmitt revival has extended Carl Schmitt's reach over the fields of international legal and political theory. Neo-Schmittians suggest that his international thought provides a new reading of the history of international law and order, which validates the explanatory power of his theoretical premises – the concept of the political, political decisionism, and concrete-order-thinking. Against this background, this article mounts a systematic reappraisal of Schmitt's international thought in a historical perspective. The argument is that his work requires re-contextualization as the intellectual product of an ultra-intense moment in Schmitt's friend/enemy distinction. It inscribed Hitler's ‘spatial revolution’ into a full-scale reinterpretation of Europe's geopolitical history, grounded in land appropriations, which legitimized Nazi Germany's wars of conquest. Consequently, Schmitt's elevation of the early modern nomos as the model for civilized warfare – the ‘golden age’ of international law – against which American legal universalism can be portrayed as degenerated, is conceptually and empirically flawed. Schmitt devised a politically motivated set of theoretical premises to provide a historical counter-narrative against liberal normativism, which generated defective history. The reconstruction of this history reveals the explanatory limits of his theoretical vocabulary – friend/enemy binary, sovereignty-as-exception, nomos/universalism – for past and present analytical purposes. Schmitt's defective analytics and problematic history compromise the standing of his work for purposes of international theory
Fatal Attractors in Parity Games: Building Blocks for Partial Solvers
Attractors in parity games are a technical device for solving "alternating"
reachability of given node sets. A well known solver of parity games -
Zielonka's algorithm - uses such attractor computations recursively. We here
propose new forms of attractors that are monotone in that they are aware of
specific static patterns of colors encountered in reaching a given node set in
alternating fashion. Then we demonstrate how these new forms of attractors can
be embedded within greatest fixed-point computations to design solvers of
parity games that run in polynomial time but are partial in that they may not
decide the winning status of all nodes in the input game.
Experimental results show that our partial solvers completely solve
benchmarks that were constructed to challenge existing full solvers. Our
partial solvers also have encouraging run times in practice. For one partial
solver we prove that its run-time is at most cubic in the number of nodes in
the parity game, that its output game is independent of the order in which
monotone attractors are computed, and that it solves all Buechi games and weak
games.
We then define and study a transformation that converts partial solvers into
more precise partial solvers, and we prove that this transformation is sound
under very reasonable conditions on the input partial solvers. Noting that one
of our partial solvers meets these conditions, we apply its transformation on
1.6 million randomly generated games and so experimentally validate that the
transformation can be very effective in increasing the precision of partial
solvers
A Fast Compiler for NetKAT
High-level programming languages play a key role in a growing number of
networking platforms, streamlining application development and enabling precise
formal reasoning about network behavior. Unfortunately, current compilers only
handle "local" programs that specify behavior in terms of hop-by-hop forwarding
behavior, or modest extensions such as simple paths. To encode richer "global"
behaviors, programmers must add extra state -- something that is tricky to get
right and makes programs harder to write and maintain. Making matters worse,
existing compilers can take tens of minutes to generate the forwarding state
for the network, even on relatively small inputs. This forces programmers to
waste time working around performance issues or even revert to using
hardware-level APIs.
This paper presents a new compiler for the NetKAT language that handles rich
features including regular paths and virtual networks, and yet is several
orders of magnitude faster than previous compilers. The compiler uses symbolic
automata to calculate the extra state needed to implement "global" programs,
and an intermediate representation based on binary decision diagrams to
dramatically improve performance. We describe the design and implementation of
three essential compiler stages: from virtual programs (which specify behavior
in terms of virtual topologies) to global programs (which specify network-wide
behavior in terms of physical topologies), from global programs to local
programs (which specify behavior in terms of single-switch behavior), and from
local programs to hardware-level forwarding tables. We present results from
experiments on real-world benchmarks that quantify performance in terms of
compilation time and forwarding table size
Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department
BACKGROUND:
Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, emergency department encounters in order to deliver appropriate care and referrals. Unfortunately, falls are difficult to identify without manual chart review, a time intensive process infeasible for many applications including surveillance and quality reporting. Here we describe a pragmatic NLP approach to automating fall identification.
METHODS:
In this single center retrospective review, 500 emergency department provider notes from older adult patients (age 65 and older) were randomly selected for analysis. A simple, rules-based NLP algorithm for fall identification was developed and evaluated on a development set of 1084 notes, then compared with identification by consensus of trained abstractors blinded to NLP results.
RESULTS:
The NLP pipeline demonstrated a recall (sensitivity) of 95.8%, specificity of 97.4%, precision of 92.0%, and F1 score of 0.939 for identifying fall events within emergency physician visit notes, as compared to gold standard manual abstraction by human coders.
CONCLUSIONS:
Our pragmatic NLP algorithm was able to identify falls in ED notes with excellent precision and recall, comparable to that of more labor-intensive manual abstraction. This finding offers promise not just for improving research methods, but as a potential for identifying patients for targeted interventions, quality measure development and epidemiologic surveillance
Counterfactual Causality from First Principles?
In this position paper we discuss three main shortcomings of existing
approaches to counterfactual causality from the computer science perspective,
and sketch lines of work to try and overcome these issues: (1) causality
definitions should be driven by a set of precisely specified requirements
rather than specific examples; (2) causality frameworks should support system
dynamics; (3) causality analysis should have a well-understood behavior in
presence of abstraction.Comment: In Proceedings CREST 2017, arXiv:1710.0277
Panpsychism: Ubiquitous Sentience
This public article presents three arguments for the plausibility of panpsychism: the view that sentience is a fundamental and ubiquitous element of actuality. Thereafter is presented a brief exploration of why panpsychism has been spurned.
The article was commissioned by High Existence.
– Introduction
– 1. The Genetic Argument
– 2. The Abstraction Argument
– 3. The Inferential Argument
– Why Panpsychism is Spurned
– End Remark
Detecting behavioral conflicts among crosscutting concerns
Aspects have been successfully promoted as a means to improve the modularization of software in the presence of crosscutting concerns. Within the Ideals project, aspects have been shown to be valuable for improving the modularization of idioms (see also Chapter 1). The so-called aspect interference problem is considered to be one of the remaining challenges of aspect-oriented software development: aspects may interfere with the behavior of the base code or other aspects. Especially interference among aspects is difficult to prevent, as this may be caused solely by the composition of aspects that behave correctly in isolation. A typical situation where this may occur is when multiple advices are applied at the same, or shared, join point. In this chapter we explain the problem of behavioral conflicts among aspects at shared join points, illustrated by aspects that represent idioms: Parameter checking and Error propagation. We present an approach for the detection of behavioral conflicts that is based on a novel abstraction model for representing the behavior of advice. The approach employs a set of conflict detection rules which can be used to detect both generic conflicts as well as domain or application specific conflicts. One of the benefits of the approach is that it neither requires the application programmers to deal with the conflict models, nor does it require a background in formal methods for the aspect programmers
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