Temporal expression normalisation in natural language texts

Automatic annotation of temporal expressions is a research challenge of great interest in the field of information extraction. In this report, I describe a novel rule-based architecture, built on top of a pre-existing system, which is able to normalise temporal expressions detected in English texts. Gold standard temporally-annotated resources are limited in size and this makes research difficult. The proposed system outperforms the state-of-the-art systems with respect to TempEval-2 Shared Task (value attribute) and achieves substantially better results with respect to the pre-existing system on top of which it has been developed. I will also introduce a new free corpus consisting of 2822 unique annotated temporal expressions. Both the corpus and the system are freely available on-line.Comment: 7 pages, 1 figure, 5 table

An Efficient Normalisation Procedure for Linear Temporal Logic and Very Weak Alternating Automata

In the mid 80s, Lichtenstein, Pnueli, and Zuck proved a classical theorem stating that every formula of Past LTL (the extension of LTL with past operators) is equivalent to a formula of the form $\bigwedge_{i=1}^n \mathbf{G}\mathbf{F} \varphi_i \vee \mathbf{F}\mathbf{G} \psi_i$, where $\varphi_i$ and $\psi_i$ contain only past operators. Some years later, Chang, Manna, and Pnueli built on this result to derive a similar normal form for LTL. Both normalisation procedures have a non-elementary worst-case blow-up, and follow an involved path from formulas to counter-free automata to star-free regular expressions and back to formulas. We improve on both points. We present a direct and purely syntactic normalisation procedure for LTL yielding a normal form, comparable to the one by Chang, Manna, and Pnueli, that has only a single exponential blow-up. As an application, we derive a simple algorithm to translate LTL into deterministic Rabin automata. The algorithm normalises the formula, translates it into a special very weak alternating automaton, and applies a simple determinisation procedure, valid only for these special automata.Comment: This is the extended version of the referenced conference paper and contains an appendix with additional materia

Assessing temporal complementarity between three variable energy sources by means of correlation and compromise programming

Renewable energies are deployed worldwide to mitigate climate change and push power systems towards sustainability. However, the weather-dependent nature of renewable energy sources often hinders their integration to national grids. Combining different sources to profit from beneficial complementarity has often been proposed as a partial solution to overcome these issues. This paper introduces a novel method for quantifying total temporal energetic complementarity between three different variable renewable sources, based on well-known mathematical techniques: correlation coefficients and compromise programming. It has the major advantage of allowing the simultaneous assessment of partial and total complementarity. The method is employed to study the complementarity of wind, solar and hydro resources on different temporal scales in a region of Poland. Results show that timescale selection has a determinant impact on the total temporal complementarity.Comment: Submitted for peer revie

Accurate object reconstruction by statistical moments

Statistical moments can offer a powerful means for object description in object sequences. Moments used in this way provide a description of the changing shape of the object with time. Using these descriptions to predict temporal views of the object requires efficient and accurate reconstruction of the object from a limited set of moments, but accurate reconstruction from moments has as yet received only limited attention. We show how we can improve accuracy not only by consideration of formulation, but also by a new adaptive thresholding technique that removes one parameter needed in reconstruction. Both approaches are equally applicable for Legendre and other orthogonal moments to improve accuracy in reconstruction

Evolving structures of star-forming clusters

Understanding the formation and evolution of young star clusters requires quantitative statistical measures of their structure. We investigate the structures of observed and modelled star-forming clusters. By considering the different evolutionary classes in the observations and the temporal evolution in models of gravoturbulent fragmentation, we study the temporal evolution of the cluster structures. We apply different statistical methods, in particular the normalised mean correlation length and the minimum spanning tree technique. We refine the normalisation of the clustering parameters by defining the area using the normalised convex hull of the objects and investigate the effect of two-dimensional projection of three-dimensional clusters. We introduce a new measure $\xi$ for the elongation of a cluster. It is defined as the ratio of the cluster radius determined by an enclosing circle to the cluster radius derived from the normalised convex hull. The mean separation of young stars increases with the evolutionary class, reflecting the expansion of the cluster. The clustering parameters of the model clusters correspond in many cases well to those from observed ones, especially when the $\xi$ values are similar. No correlation of the clustering parameters with the turbulent environment of the molecular cloud is found, indicating that possible influences of the environment on the clustering behaviour are quickly smoothed out by the stellar velocity dispersion. The temporal evolution of the clustering parameters shows that the star cluster builds up from several subclusters and evolves to a more centrally concentrated cluster, while the cluster expands slower than new stars are formed.Comment: 11 pages, 10 figures, accepted by A&A; slightly modified according to the referee repor

A Feature Learning Siamese Model for Intelligent Control of the Dynamic Range Compressor

In this paper, a siamese DNN model is proposed to learn the characteristics of the audio dynamic range compressor (DRC). This facilitates an intelligent control system that uses audio examples to configure the DRC, a widely used non-linear audio signal conditioning technique in the areas of music production, speech communication and broadcasting. Several alternative siamese DNN architectures are proposed to learn feature embeddings that can characterise subtle effects due to dynamic range compression. These models are compared with each other as well as handcrafted features proposed in previous work. The evaluation of the relations between the hyperparameters of DNN and DRC parameters are also provided. The best model is able to produce a universal feature embedding that is capable of predicting multiple DRC parameters simultaneously, which is a significant improvement from our previous research. The feature embedding shows better performance than handcrafted audio features when predicting DRC parameters for both mono-instrument audio loops and polyphonic music pieces.Comment: 8 pages, accepted in IJCNN 201

Unsupervised Learning with Normalised Data and Non-Euclidean Norms

Peer reviewe

New methods for B meson decay constants and form factors from lattice NRQCD

We determine the normalisation of scalar and pseudoscalar current operators made from non-relativistic $b$ quarks and Highly Improved Staggered light quarks in lattice Quantum Chromodynamics (QCD) through $\mathcal{O}(\alpha_s)$ and $\Lambda_{\text{QCD}}/m_b$. We use matrix elements of these operators to extract $B$ meson decay constants and form factors, then compare to those obtained using the standard vector and axial-vector operators. This provides a test of systematic errors in the lattice QCD determination of the $B$ meson decay constants and form factors. We provide a new value for the $B$ and $B_s$ meson decay constants from lattice QCD calculations on ensembles that include $u$, $d$, $s$ and $c$ quarks in the sea and those which have the $u/d$ quark mass going down to its physical value. Our results are $f_B=0.196(6)$ GeV, $f_{B_s}=0.236(7)$ GeV and $f_{B_s}/f_B =1.207(7)$, agreeing well with earlier results using the temporal axial current. By combining with these previous results, we provide updated values of $f_B=0.190(4)$ GeV, $f_{B_s}=0.229(5)$ GeV and $f_{B_s}/f_B = 1.206(5)$.Comment: 14 pages, 10 figure