Explaining Violation Traces with Finite State Natural Language Generation Models

An essential element of any verification technique is that of identifying and communicating to the user, system behaviour which leads to a deviation from the expected behaviour. Such behaviours are typically made available as long traces of system actions which would benefit from a natural language explanation of the trace and especially in the context of business logic level specifications. In this paper we present a natural language generation model which can be used to explain such traces. A key idea is that the explanation language is a CNL that is, formally speaking, regular language susceptible transformations that can be expressed with finite state machinery. At the same time it admits various forms of abstraction and simplification which contribute to the naturalness of explanations that are communicated to the user

Microscopic Theory of Spontaneous Decay in a Dielectric

The local field correction to the spontanous dacay rate of an impurity source atom imbedded in a disordered dielectric is calculated to second order in the dielectric density. The result is found to differ from predictions associated with both "virtual" and "real" cavity models of this decay process. However, if the contributions from two dielectric atoms at the same position are included, the virtual cavity result is reproduced.Comment: 12 Page

Reflexivity of the translation-dilation algebras on L^2(R)

The hyperbolic algebra A_h, studied recently by Katavolos and Power, is the weak star closed operator algebra on L^2(R) generated by H^\infty(R), as multiplication operators, and by the dilation operators V_t, t \geq 0, given by V_t f(x) = e^{t/2} f(e^t x). We show that A_h is a reflexive operator algebra and that the four dimensional manifold Lat A_h (with the natural topology) is the reflexive hull of a natural two dimensional subspace.Comment: 10 pages, no figures To appear in the International Journal of Mathematic

Successful completion of a cyclic ground test of a mercury ion auxiliary propulsion system

An engineering model Ion Auxiliary Propulsion System (IAPS) 8-cm thruster (S/N 905) has completed a life test at NASA Lewis Research Center. The mercury ion thruster successfully completed and exceeded the test goals of 2557 on/off cycles and 7057 hr of operation at full thrust. The final 1200 cycles and 3600 hr of the life test were conducted using an engineering model of the IAPS power electronics unit (PEU) and breadboard digital controller and interface unit (DCIU). This portion of the test is described in this paper with a charted history of thruster operating parameters and off-normal events. Performance and operating characteristics were constant throughout the test with only minor variations. The engineering model power electronics unit operated without malfunction; the flight software in the digital controller and interface unit was exercised and verified. Post-test inspection of the thruster revealed facility enhanced accelerator grid erosion but overall the thruster was in good condition. It was concluded that the thruster performance was not drastically degraded by time or cycles. Additional cyclic testing is currently under consideration

Cross-Lingual Classification of Crisis Data

Many citizens nowadays flock to social media during crises to share or acquire the latest information about the event. Due to the sheer volume of data typically circulated during such events, it is necessary to be able to efficiently filter out irrelevant posts, thus focusing attention on the posts that are truly relevant to the crisis. Current methods for classifying the relevance of posts to a crisis or set of crises typically struggle to deal with posts in different languages, and it is not viable during rapidly evolving crisis situations to train new models for each language. In this paper we test statistical and semantic classification approaches on cross-lingual datasets from 30 crisis events, consisting of posts written mainly in English, Spanish, and Italian. We experiment with scenarios where the model is trained on one language and tested on another, and where the data is translated to a single language. We show that the addition of semantic features extracted from external knowledge bases improve accuracy over a purely statistical model

Dynamic RKKY interaction in graphene

The growing interest in carbon-based spintronics has stimulated a number of recent theoretical studies on the RKKY interaction in graphene, based on which the energetically favourable alignment between magnetic moments embedded in this material can be calculated. The general consensus is that the strength of the RKKY interaction in graphene decays as 1/D3 or faster, where D is the separation between magnetic moments. Such an unusually fast decay for a 2-dimensional system suggests that the RKKY interaction may be too short ranged to be experimentally observed in graphene. Here we show in a mathematically transparent form that a far more long ranged interaction arises when the magnetic moments are taken out of their equilibrium positions and set in motion. We not only show that this dynamic version of the RKKY interaction in graphene decays far more slowly but also propose how it can be observed with currently available experimental methods.Comment: 7 pages, 2 figures, submitte

Classifying Crises-Information Relevancy with Semantics

Social media platforms have become key portals for sharing and consuming information during crisis situations. However, humanitarian organisations and affected communities often struggle to sieve through the large volumes of data that are typically shared on such platforms during crises to determine which posts are truly relevant to the crisis, and which are not. Previous work on automatically classifying crisis information was mostly focused on using statistical features. However, such approaches tend to be inappropriate when processing data on a type of crisis that the model was not trained on, such as processing information about a train crash, whereas the classifier was trained on floods, earthquakes, and typhoons. In such cases, the model will need to be retrained, which is costly and time-consuming. In this paper, we explore the impact of semantics in classifying Twitter posts across same, and different, types of crises. We experiment with 26 crisis events, using a hybrid system that combines statistical features with various semantic features extracted from external knowledge bases. We show that adding semantic features has no noticeable benefit over statistical features when classifying same-type crises, whereas it enhances the classifier performance by up to 7.2% when classifying information about a new type of crisis

Impurity segregation in graphene nanoribbons

The electronic properties of low-dimensional materials can be engineered by doping, but in the case of graphene nanoribbons (GNR) the proximity of two symmetry-breaking edges introduces an additional dependence on the location of an impurity across the width of the ribbon. This introduces energetically favorable locations for impurities, leading to a degree of spatial segregation in the impurity concentration. We develop a simple model to calculate the change in energy of a GNR system with an arbitrary impurity as that impurity is moved across the ribbon and validate its findings by comparison with ab initio calculations. Although our results agree with previous works predicting the dominance of edge disorder in GNR, we argue that the distribution of adsorbed impurities across a ribbon may be controllable by external factors, namely an applied electric field. We propose that this control over impurity segregation may allow manipulation and fine-tuning of the magnetic and transport properties of GNRs.Comment: 5 pages, 4 figures, submitte

Extended Timed Up and Go assessment as a clinical indicator of cognitive state in Parkinson\u27s disease

Objective: To evaluate a modified extended Timed Up and Go (extended-TUG) assessment against a panel of validated clinical assessments, as an indicator of Parkinson’s disease (PD) severity and cognitive impairment. Methods: Eighty-seven participants with idiopathic PD were sequentially recruited from a Movement Disorders Clinic. An extended-TUG assessment was employed which required participants to stand from a seated position, walk in a straight line for 7 metres, turn 180 degrees and then return to the start, in a seated position. The extended-TUG assessment duration was correlated to a panel of clinical assessments, including the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), Quality of Life (PDQ-39), Scales for Outcomes in Parkinson’s disease (SCOPA-Cog), revised Addenbrooke’s Cognitive Index (ACE-R) and Barratt’s Impulsivity Scale 11 (BIS-11). Results: Extended-TUG time was significantly correlated to MDS-UPDRS III score and to SCOPA-Cog, ACE-R (p\u3c0.001) and PDQ-39 scores (p\u3c0.01). Generalized linear models determined the extended-TUG to be a sole variable in predicting ACE-R or SCOPA-Cog scores. Patients in the fastest extended-TUG tertile were predicted to perform 8.3 and 13.4 points better in the SCOPA-Cog and ACE-R assessments, respectively, than the slowest group. Patients who exceeded the dementia cut-off scores with these instruments exhibited significantly longer extended-TUG times. Conclusions: Extended-TUG performance appears to be a useful indicator of cognition as well as motor function and quality of life in PD, and warrants further evaluation as a first line assessment tool to monitor disease severity and response to treatment. Poor extended-TUG performance may identify patients without overt cognitive impairment form whom cognitive assessment is needed