Statistical modelling of CSP solving algorithms performance

The goal of this work is to try to create a statistical model, based only on easily computable parameters from the CSP problem to predict runtime behaviour of the solving algorithms, and let us choose the best algorithm to solve the problem. Although it seems that the obvious choice should be MAC, experimental results obtained so far show, that with big numbers of variables, other algorithms perfom much better, specially for hard problems in the transition phase.

Validation and statistical analysis of two high performance liquid chromatography methods for the determination of indinavir sulfate raw material and capsules

Two high performance liquid chromatography (HPLC) methods for the quantitative determination of indinavir sulfate were tested, validated and statistically compared. Assays were carried out using as mobile phases mixtures of dibutylammonium phosphate buffer pH 6.5 and acetonitrile (55:45) at 1 mL/min or citrate buffer pH 5 and acetonitrile (60:40) at 1 mL/min, an octylsilane column (RP-8) and a UV spectrophotometric detector at 260 nm. Both methods showed good sensitivity, linearity, precision and accuracy. The statistical analysis using the t-student test for the determination of indinavir sulfate raw material and capsules indicated no statistically significant difference between the two methods.

Statistical monitoring of student performance: an early warning system

Weekly monitoring of profiles of student performances on formative and summative coursework throughout the year can be used to quickly identify those who need additional help, possibly due to acute and sudden-onset problems. Such an early-warning system can help retention, but also assist students in overcoming problems early on, thus helping them fulfil their potential in the long run. We have developed a simple approach for the automatic monitoring of student mark profiles for individual modules, which we intend to trial in the near future. Its ease of implementation means that it can be used for very large cohorts with little additional effort when marks are already collected and recorded on a spreadsheet.

The cross-currency hedging performance of implied versus statistical forecasting models

This article examines the ability of several models to generate optimal hedge ratios. Statistical models employed include univariate and multivariate generalized autoregressive conditionally heteroscedastic (GARCH) models, and exponentially weighted and simple moving averages. The variances of the hedged portfolios derived using these hedge ratios are compared with those based on market expectations implied by the prices of traded options. One-month and three-month hedging horizons are considered for four currency pairs. Overall, it has been found that an exponentially weighted moving-average model leads to lower portfolio variances than any of the GARCH-based, implied or time-invariant approaches.

Interval training at 95% and 100% of the velocity at VO2 max: effects on aerobic physiological indexes and running performance

The objective of this study was to analyze the effect of two different high-intensity interval training (HIT) programs on selected aerobic physiological indices and 1500 and 5000 m running performance in well-trained runners. The following tests were completed (n = 17): (i) incremental treadmill test to determine maximal oxygen uptake (VO2max), running velocity associated with VO2 max (VVO2max), and the velocity corresponding to 3.5 mmol/L of blood lactate concentration (vOBLA); (ii) submaximal constant-intensity test to determine running economy (RE); and (iii) 1500 and 5000 m time trials on a 400 m track. Runners were then randomized into 95% vVO(2max) or 100% vVO(2max) groups, and undertook a 4 week training program consisting of 2 HIT sessions (performed at 95% or 100% vVO(2max), respectively) and 4 submaximal run sessions per week. Runners were retested on all parameters at the completion of the training program. The VO2 max values were not different after training for both groups. There was a significant increase in post-training vVO(2 max), RE, and 1500 in running performance in the 100% vVO(2 max) group. The vOBLA and 5000 m running performance were significantly higher after the training period for both groups. We conclude that vOBLA and 5000 m running performance can be significantly improved in well-trained runners using a 4 week training program consisting of 2 HIT sessions (performed at 95% or 100% vVO(2max)) and 4 submaximal run sessions per week. However, the improvement in vVO(2 max), RE, and 1500 in running performance seems to be dependent on the HIT program at 100% vVO(2 max).

Diagnostic Performance and Additional Value of Elastosonography in Focal Breast Lesions: Statistical Correlation between Size-Dependant Strain Index Measurements, Multimodality-BI-RADS Score, and Histopathology in a Clinical Routine Setting

Objective. To evaluate the diagnostic benefit of real-time elastography (RTE) in clinical routine. Strain indices (SI) for benign and malignant tumors were assessed. Methods. 100 patients with 110 focal breast lesions were retrieved. Patients had mammography (MG), ultrasound (US), and, if necessary, MRI. RTE was conducted after ultrasound. Lesions were assessed with BI-RADS for mammography and ultrasound. Diagnosis was established with histology or follow-up. Results. SI for BI-RADS 2 was 1.71 ± 0.86. Higher SI (2.21 ± 1.96) was observed for BI-RADS 3 lesions. SI of BI-RADS 4 and 5 lesions were significantly higher (16.92 ± 20.89) and (19.54 ± 10.41). 31 malignant tumors exhibited an average SI of 16.13 ± 14.67; SI of benign lesions was 5.29 ± 11.87 (P value <0.0001). ROC analysis threshold was >3.8 for malignant disease. Sensitivity of sonography was 90.3% (specificity 78.5%). RTE showed a sensitivity of 87.1% (specificity 79.7%). Accuracy of all modalities combined was 96.8%. In BI-RADS 3 lesions RTE was able to detect all malignant lesions (sensitivity 100%, specificity 92.9%, and accuracy 93.9%). Conclusions. RTE increased sensitivity and specificity for breast cancer detection when used in combination with ultrasound.

Performance Evaluation of the New Connecticut Leading Employment Index Using Lead Profiles and BVAR Models

Dua and Miller (1996) created leading and coincident employment indexes for the state of Connecticut, following Moore's (1981) work at the national level. The performance of the Dua-Miller indexes following the recession of the early 1990s fell short of expectations. This paper performs two tasks. First, it describes the process of revising the Connecticut Coincident and Leading Employment Indexes. Second, it analyzes the statistical properties and performance of the new indexes by comparing the lead profiles of the new and old indexes as well as their out-of-sample forecasting performance, using the Bayesian Vector Autoregressive (BVAR) method. The new indexes show improved performance in dating employment cycle chronologies. The lead profile test demonstrates that superiority in a rigorous, non-parametric statistic fashion. The mixed evidence on the BVAR forecasting experiments illustrates the truth in the Granger and Newbold (1986) caution that leading indexes properly predict cycle turning points and do not necessarily provide accurate forecasts except at turning points, a view that our results support.

Performance recovery from exercise: A review from a statistical point of view

Background. Research into methods for recovery from fatigue due to exercise is a popular topic among sport medicine, kinesiology and physical therapy. However, both the quantity and quality of studies and a clear solution of recovery are lacking. An analysis of the statistical methods in the existing literature of performance recovery can enhance the quality of research and provide some guidance for future studies. Methods: A literature review was performed using SCOPUS, SPORTDiscus, MEDLINE, CINAHL, Cochrane Library and Science Citation Index Expanded databases to extract the studies related to performance recovery from exercise of human beings. Original studies and their statistical analysis for recovery methods including Active Recovery, Cryotherapy/Contrast Therapy, Massage Therapy, Diet/Ergogenics, and Rehydration were examined. Results: The review produces a Research Design and Statistical Method Analysis Summary. Conclusion: Research design and statistical methods can be improved by using the guideline from the Research Design and Statistical Method Analysis Summary. This summary table lists the potential issues and suggested solutions, such as, sample size calculation, sports specific and research design issues consideration, population and measure markers selection, statistical methods for different analytical requirements, equality of variance and normality of data, post hoc analyses and effect size calculation.^

Atmospheric parameters, spectral indexes and their relation to CPV spectral performance

Air Mass and atmosphere components (basically aerosol (AOD) and precipitable water (PW)) define the absorption of the sunlight that arrive to Earth. Radiative models such as SMARTS or MODTRAN use these parameters to generate an equivalent spectrum. However, complex and expensive instruments (as AERONET network devices) are needed to obtain AOD and PW. On the other hand, the use of isotype cells is a convenient way to characterize spectrally a place for CPV considering that they provide the photocurrent of the different internal subcells individually. Crossing data from AERONET station and a Tri-band Spectroheliometer, a model that correlates Spectral Mismatch Ratios and atmospheric parameters is proposed. Considering the amount of stations of AERONET network, this model may be used to estimate the spectral influence on energy performance of CPV systems close to all the stations worldwide.

Applying logic forms and statistical methods to CL-SR performance

This paper describes a CL-SR system that employs two different techniques: the first one is based on NLP rules that consist on applying logic forms to the topic processing while the second one basically consists on applying the IR-n statistical search engine to the spoken document collection. The application of logic forms to the topics allows to increase the weight of topic terms according to a set of syntactic rules. Thus, the weights of the topic terms are used by IR-n system in the information retrieval process.

Statistical Appendices to “Performance of Long-Term Care Systems in Europe”. ENEPRI Research Report 117A, 21 December 2012

This document provides statistical appendices underpinning the research presented in ENEPRI Research Report No. 117, “Performance of Long-Term Care Systems in Europe”, December 2012. Esther Mot is Senior Researcher in the Netherlands Bureau for Economic Policy Analysis (CPB) and Riemer Faber is researcher at CPB. Joanna Geerts is researcher and Peter Willemé is health economist in the Social Security Research Group at the Federal Planning Bureau (FPB).