Beam energy and system dependence of rapidity-even dipolar flow

New measurements of rapidity-even dipolar flow, v$^{even}_{1}$, are presented for several transverse momenta, $p_T$, and centrality intervals in Au+Au collisions at $\sqrt{s_{NN}}~=~200,~39$ and $19.6$ GeV, U+U collisions at $\sqrt{s_{NN}}~=~193$ GeV, and Cu+Au, Cu+Cu, d+Au and p+Au collisions at $\sqrt{s_{NN}}~=~200$~GeV. The v$^{even}_{1}$ shows characteristic dependencies on $p_{T}$, centrality, collision system and $\sqrt{s_{_{NN}}}$, consistent with the expectation from a hydrodynamic-like expansion to the dipolar fluctuation in the initial state. These measurements could serve as constraints to distinguish between different initial-state models, and aid a more reliable extraction of the specific viscosity $\eta/s$

Influence of finite volume effect on the Polyakov Quark-Meson model

In the current work, we study the influence of a finite volume on $2+1$ $SU(3)$ Polyakov Quark-Meson model (PQM) order parameters, (fluctuations) correlations of conserved charges and the quark-hadron phase boundary. Our study of the PQM model order parameters and the (fluctuations) correlations of conserved charges indicates a sizable shift of the quark-hadron phase boundary to higher values of baryon chemical potential ($\mu_{B}$) and temperature ($T$) for decreasing the system volume. The detailed study of such effect could have important implications for the extraction of the (fluctuations) correlations of conserved charges of the QCD phase diagram from heavy ion data.Comment: 12 pages, 8 figure

PRES: A score metric for evaluating recall-oriented information retrieval applications

Information retrieval (IR) evaluation scores are generally designed to measure the effectiveness with which relevant documents are identified and retrieved. Many scores have been proposed for this purpose over the years. These have primarily focused on aspects of precision and recall, and while these are often discussed with equal importance, in practice most attention has been given to precision focused metrics. Even for recalloriented IR tasks of growing importance, such as patent retrieval, these precision based scores remain the primary evaluation measures. Our study examines different evaluation measures for a recall-oriented patent retrieval task and demonstrates the limitations of the current scores in comparing different IR systems for this task. We introduce PRES, a novel evaluation metric for this type of application taking account of recall and the user’s search effort. The behaviour of PRES is demonstrated on 48 runs from the CLEF-IP 2009 patent retrieval track. A full analysis of the performance of PRES shows its suitability for measuring the retrieval effectiveness of systems from a recall focused perspective taking into account the user’s expected search effort

Applying the KISS principle for the CLEF-IP 2010 prior art candidate patent search task

We present our experiments and results for the DCU CNGL participation in the CLEF-IP 2010 Candidate Patent Search Task. Our work applied standard information retrieval (IR) techniques to patent search. In addition, a very simple citation extraction method was applied to improve the results. This was our second consecutive participation in the CLEF-IP tasks. Our experiments in 2009 showed that many sophisticated approach to IR do not improve the retrieval effectiveness for this task. For this reason of we decided to apply only simple methods in 2010. These were demonstrated to be highly competitive with other participants. DCU submitted three runs for the Prior Art Candidate Search Task, two of these runs achieved the second and third ranks among the 25 runs submitted by nine different participants. Our best run achieved MAP of 0.203, recall of 0.618, and PRES of 0.523

A new metric for patent retrieval evaluation

Patent retrieval is generally considered to be a recall-oriented information retrieval task that is growing in importance. Despite this fact, precision based scores such as mean average precision (MAP) remain the primary evaluation measures for patent retrieval. Our study examines different evaluation measures for the recall-oriented patent retrieval task and shows the limitations of the current scores in comparing different IR systems for this task. We introduce PRES, a novel evaluation metric for this type of application taking account of recall and user search effort. The behaviour of PRES is demonstrated on 48 runs from the CLEF-IP 2009 patent retrieval track. A full analysis of the performance of PRES shows its suitability for measuring the retrieval effectiveness of systems from a recall focused perspective taking into account the expected search effort of patent searchers