Non-Compositional Term Dependence for Information Retrieval

Modelling term dependence in IR aims to identify co-occurring terms that are too heavily dependent on each other to be treated as a bag of words, and to adapt the indexing and ranking accordingly. Dependent terms are predominantly identified using lexical frequency statistics, assuming that (a) if terms co-occur often enough in some corpus, they are semantically dependent; (b) the more often they co-occur, the more semantically dependent they are. This assumption is not always correct: the frequency of co-occurring terms can be separate from the strength of their semantic dependence. E.g. "red tape" might be overall less frequent than "tape measure" in some corpus, but this does not mean that "red"+"tape" are less dependent than "tape"+"measure". This is especially the case for non-compositional phrases, i.e. phrases whose meaning cannot be composed from the individual meanings of their terms (such as the phrase "red tape" meaning bureaucracy). Motivated by this lack of distinction between the frequency and strength of term dependence in IR, we present a principled approach for handling term dependence in queries, using both lexical frequency and semantic evidence. We focus on non-compositional phrases, extending a recent unsupervised model for their detection [21] to IR. Our approach, integrated into ranking using Markov Random Fields [31], yields effectiveness gains over competitive TREC baselines, showing that there is still room for improvement in the very well-studied area of term dependence in IR

Effects of energy storage systems grid code requirements on interface protection performances in low voltage networks

The ever-growing penetration of local generation in distribution networks and the large diffusion of energy storage systems (ESSs) foreseen in the near future are bound to affect the effectiveness of interface protection systems (IPSs), with negative impact on the safety of medium voltage (MV) and low voltage (LV) systems. With the scope of preserving the main network stability, international and national grid connection codes have been updated recently. Consequently, distributed generators (DGs) and storage units are increasingly called to provide stabilizing functions according to local voltage and frequency. This can be achieved by suitably controlling the electronic power converters interfacing small-scale generators and storage units to the network. The paper focuses on the regulating functions required to storage units by grid codes currently in force in the European area. Indeed, even if such regulating actions would enable local units in participating to network stability under normal steady-state operating conditions, it is shown through dynamic simulations that they may increase the risk of unintentional islanding occurrence. This means that dangerous operating conditions may arise in LV networks in case dispersed generators and storage systems are present, even if all the end-users are compliant with currently applied connection standards

Spectra of magnetic perturbations triggered by pellets in JET plasmas

Aiming at investigating edge localised mode (ELM) pacing for future application on ITER, experiments have been conducted on JET injecting pellets in different plasma configurations, including high confinement regimes with type-I and type-III ELMs, low confinement regimes and Ohmically heated plasmas. The magnetic perturbations spectra and the toroidal mode number, n, of triggered events are compared with those of spontaneous ELMs using a wavelet analysis to provide good time resolution of short-lived coherent modes. It is found that—in all these configurations—triggered events have a coherent mode structure, indicating that pellets can trigger an MHD event basically in every background plasma. Two components have been found in the magnetic perturbations induced by pellets, with distinct frequencies and toroidal mode numbers. In high confinement regimes triggered events have similarities with spontaneous ELMs: both are seen to start from low toroidal mode numbers, then the maximum measured n increases up to about 10 within 0.3 ms before the ELM burst