Testing for the best alternative with an application to performance measurement

Suppose that we are searching for the maximum of many unknown and analytically untractable quantities or, say, the 'best alternative' among several candidates. If our decision is based on historical or simulated data there is some sort of selection bias and it is not evident if our choice is significantly better than any other. In the present work a large sample test for the best alternative is derived in a rather general setting. The test is demonstrated by an application to financial data and compared with the Jobson-Korkie test for the Sharpe ratios of two asset portfolios. We find that ignoring conditional heteroscedasticity and non-normality of asset returns can lead to misleading decisions. In contrast, the presented test for the best alternative accounts for these kinds of phenomena. --Ergodicity,Gordin's condition,heteroscedasticity,Jobson-Korkie test,Monte Carlo simulation,performance measurement,Sharpe ratio

The production of neutral N∗(11052)N^*(11052) resonance with hidden beauty from π−p\pi^-p scattering

We investigate the discovery potential of the predicted neutral hidden beauty $N^*(11052)$ resonance through $\pi^- p$ scattering within an effective Lagrangian approach. Two reactions $\pi^-p\rightarrow K^-\Sigma^+$ and $\pi^-p\rightarrow \eta_bn$ are studied in this work, with nucleon pole exchange as the background. It is found that the contributions of the $N^*(11052)$ resonance give clear peak structures in the magnitude of 1 $\mu b$ near the threshold of the $N^*(11052)$ in the total cross sections. The numerical results indicate that the center of mass energy $W\simeq$ 11-11.1 GeV would be a best energy window for searching the $N^*(11052)$ resonance, where the $N^*(11052)$ signal can be easily distinguished from the background. The COMPASS experiment at CERN's Super Proton Synchrotron (SPS) with pion beam of $\simeq$ 280 GeV will be an ideal platform for searching the super-heavy resonance with hidden beauty, which is hopeful to test the theoretical results

F-structure transfer-based statistical machine translation

In this paper, we describe a statistical deep syntactic transfer decoder that is trained fully automatically on parsed bilingual corpora. Deep syntactic transfer rules are induced automatically from the f-structures of a LFG parsed bitext corpus by automatically aligning local f-structures, and inducing all rules consistent with the node alignment. The transfer decoder outputs the n-best TL f-structures given a SL f-structure as input by applying large numbers of transfer rules and searching for the best output using a log-linear model to combine feature scores. The decoder includes a fully integrated dependency-based tri-gram language model. We include an experimental evaluation of the decoder using different parsing disambiguation resources for the German data to provide a comparison of how the system performs with different German training and test parses

Matched direction detectors

In this paper, we address the problem of detecting a signal whose associated spatial signature is subject to uncertainties, in the presence of subspace interference and broadband noise, and using multiple snapshots from an array of sensors. To account for steering vector uncertainties, we assume that the spatial signature of interest lies in a given linear subspace H while its coordinates in this subspace are unknown. The generalized likelihood ratio test (GLRT) for the problem at hand is formulated. We show that the GLRT amounts to searching for the best direction in the subspace H after projecting out the interferences. The distribution of the GRLT under both hypotheses is derived and numerical simulations illustrate its performance

High-Performance Architecture for Binary-Tree-Based Finite State Machines

A binary-tree-based finite state machine (BT-FSM) is a state machine with a 1-bit input signal whose state transition graph is a binary tree. BT-FSMs are useful in those application areas where searching in a binary tree is required, such as computer networks, compression, automatic control, or cryptography. This paper presents a new architecture for implementing BT-FSMs which is based on the model finite virtual state machine (FVSM). The proposed architecture has been compared with the general FVSM and conventional approaches by using both synthetic test benches and very large BT-FSMs obtained from a real application. In synthetic test benches, the average speed improvement of the proposed architecture respect to the best results of the other approaches achieves 41% (there are some cases in which the speed is more than double). In the case of the real application, the average speed improvement achieves 155%

Using a Research Log and Reflective Writing to Improve EBP and Information Literacy Skills of BSN Students

Background Baccalaureate nursing educators must prepare nurses to implement evidence-based practice (EBP). BSN nurses must be able to effectively identify, analyze, and synthesize evidence (AACN, 2008). In a nursing research course, students conducted group projects which required searching for the best evidence. Project evaluations revealed that students were not searching systematically. To facilitate EBP and information literacy skill development, a collaboration between the College of Nursing and Library Services emerged. Targeted Learning Outcomes 1. Formulate a strategic search using databases and Internet resources 2. Evaluate and select the ‘best available’ evidence 3. Document systematic search (keywords, subject headings, limiters, and results) 4. Describe why evidence was selected 5. Reflect on search process, difficulties, and potential revisions for next search. Teaching Learning Activities In spring of 2012, research logs were added to an EBP group project requiring students to identify the best evidence. Groups documented their search using a research log worksheet and narrative which included reflection of the search process, evidence appraisal, and strengths and weakness. Although the research log worksheet provided structure, specific problems including uncoordinated group searches, inadequate articulation of evidence selection, and limited reflection about strengths and weaknesses were still identified. Additional sessions reinforcing information literacy skills were integrated in the course. The information literacy skills sessions and research logs were implemented for two subsequent semesters. Evaluation of Approach Student research log and EBP group project scores will be compared over three semesters using ANOVA to determine differences in group performance. During initial data analysis, an independent t test reflected a significant difference between scores for Spring 2012 and Fall 2012 groups. The Fall 2012 groups who used research logs and experienced additional information literacy skills sessions scored significantly higher on their assignments than Spring 2012 groups. Data collection for Spring 2013 is in progress. Final study results as well as implications for nursing education will be articulated