570 research outputs found
Trapping Phenomenon Attenuates the Consequences of Tipping Points for Limit Cycles
We would like to thank the partial support of this work by the Brazilian agencies FAPESP (processes: 2011/19296-1, 2013/26598-0, and 2015/20407-3), CNPq and CAPES. MSB acknowledges EPSRC Ref. EP/I032606/1.Peer reviewedPublisher PD
Chimera states emerging from dynamical trapping in chaotic saddles
Nonlinear systems possessing nonattracting chaotic sets, such as chaotic
saddles, embedded in their state space may oscillate chaotically for a
transient time before eventually transitioning into some stable attractor. We
show that these systems, when networked with nonlocal coupling in a ring, are
capable of forming chimera states, in which one subset of the units oscillates
periodically in a synchronized state forming the coherent domain, while the
complementary subset oscillates chaotically in the neighborhood of the chaotic
saddle constituting the incoherent domain. We find two distinct transient
chimera states distinguished by their abrupt or gradual termination. We analyze
the lifetime of both chimera states, unraveling their dependence on coupling
range and size. We find an optimal value for the coupling range yielding the
longest lifetime for the chimera states. Moreover, we implement transversal
stability analysis to demonstrate that the synchronized state is asymptotically
stable for network configurations studied here
Using laser ultrasound to detect sub-surface defects in metal laser powder bed fusion components
Laser powder bed fusion offers many advantages over conventional manufacturing methods, such as the integration of multiple parts which can result in significant weight-savings. The increased design freedom that layer-wise manufacture allows has also been seen to enhance component performance at little or no added cost. However, for such benefits to be realised, the material quality must first be assured. Laser ultrasonic testing is a non-contact inspection technique which has been proposed as suitable for in-situ monitoring of metal additive manufacturing processes. This paper explores the current capability of this technique to detect manufactured, sub-surface defects in Ti-6Al-4V samples, ex-situ. The results are compared with x-ray computed tomography reconstructions and focus variation microscopy. Whilst laser ultrasound has been used to identify material discontinuities, further work is required before this technique could be implemented in-situ
Identifying Self-Admitted Technical Debt
Technical debt is a metaphor coined to express the trade off between productivity and quality, e.g., when developers take shortcuts or perform quick hacks during the development of software projects. These non optimal solutions are often implemented to allow the project to move faster in the short term, at the cost of increased maintenance in the future. The accumulation of technical debt during the ever changing life-cycle of a project is unavoidable, and if not properly managed can severely hinder the development of the project. To help alleviate the impact of technical debt, a number of studies focused on the detection of technical debt. However, a recent study has shown that one possible source to detect technical debt is using source code comments, also referred to as self-admitted technical debt. Therefore, in this dissertation we use empirical studies and NLP techniques to propose an approach to automatically identify self-admitted technical debt.
First, we examine source code comments to determine the different types of technical debt, and we propose four simple filtering heuristics to eliminate comments that are not likely to contain technical debt. Then, we read through more than 33K comments, and we find that self-admitted technical debt can be classified into five main types - design debt, defect debt, documentation debt, requirement debt and test debt. In addition, two most common types of self-admitted technical debt are design and requirement debt, making up between 42% to 84% and 5% to 45% of the classified comments, respectively.
Second, we leverage the knowledge obtained in our first study to present an approach to automatically identify design and requirement self-admitted technical debt using Natural Language Processing (NLP). We study 10 open source projects: Ant, ArgoUML, Columba, EMF, Hibernate, JEdit, JFreeChart, Jmeter, JRuby and SQuirrel SQL and find that 1) we are able to effectively identify self-admitted technical debt, significantly outperforming state-of-the-art techniques; 2) that words related to sloppy or mediocre source code are the best indicators of design debt, whereas for requirement debt, words related to enhancing or completing tasks are the best indicators; and 3) we can achieve 90% of the best classification performance, using as little as 23% of the comments for both design and requirement self-admitted technical debt, and 80% of the best performance, using as little as 9% and 5% of the comments for design and requirement self-admitted technical debt, respectively
Scale-free avalanches in arrays of FitzHugh-Nagumo oscillators
The activity in the brain cortex remarkably shows a simultaneous presence of
robust collective oscillations and neuronal avalanches, where intermittent
bursts of pseudo-synchronous spiking are interspersed with long periods of
quiescence. The mechanisms allowing for such a coexistence are still a matter
of an intensive debate. Here, we demonstrate that avalanche activity patterns
can emerge in a rather simple model of an array of diffusively coupled neural
oscillators with multiple timescale local dynamics in vicinity of a canard
transition. The avalanches coexist with the fully synchronous state where the
units perform relaxation oscillations. We show that the mechanism behind the
avalanches is based on an inhibitory effect of interactions, which may quench
the spiking of units due to an interplay with the maximal canard. The avalanche
activity bears certain heralds of criticality, including scale-invariant
distributions of event sizes. Furthermore, the system shows an increased
sensitivity to perturbations, manifested as critical slowing down and a reduced
resilience.Comment: 9 figure
- …