19 research outputs found
Photovoltaic Power Forecasting with Ensemble of Learners: Large Test Case from PV Plants in Italy, Zambia and Australia
Photovoltaic power forecasting is nowadays a very active research topic both for industries and academia [1- 10]. In this paper a hourly day-ahead forecasting approach for photovoltaic (PV) power is described, which is based on a number of machine learning techniques independently trained and then combined in a cooperative ensemble fashion. The results of the single techniques have been in depth analysed and compared, resulting in a superior performance of the cooperative ensemble. A strong contribution of this work is the application to a very large number of PV plants (42 at the date of this paper), for an overall installed nominal power over 110 MW in Italy and over 140 MW in Zambia and Australia. Another contribution is the large historic dataset dimension comprehending years of hourly data from 2014 to 2019, allowing in most cases to test the algorithms in large periods, taking into account seasonality and time varying factors. Moreover the large test case leads to a number of different PV technologies (monocrystalline silicon, polycrystalline silicon, thin-film amorphous silicon and flexible amorphous thin-film silicon) and installations (ground and roof mounting, axis tracking). Examples of studies in the literature that include so large test cases are scarce. This work extends the results of a previous work of the authors [11], where a smaller test case was used and tracking installations were not present
MR cholangiography in orthotopic liver transplantation: sensitivity and specificity in detecting biliary complications
BACKGROUND: To assess the diagnostic value of magnetic resonance cholangiography
(MRC) when evaluating biliary complications in a large series of liver
transplants.
METHODS: One hundred and twenty-nine patients prospectively underwent magnetic
resonance (MR) imaging and MR cholangiography at 1.5-T device after orthotopic
liver transplantation (OLT). After the preliminary acquisition of axial T1- and
T2-weighted images, MRC involved respiratory-triggered, thin-slab (2 mm), heavily
T2-weighted fast spin-echo and breath-hold, thick-slab (10-50 mm), single-shot
T2-weighted sequences. MR images were blindly evaluated by two experienced
readers in conference to determine the biliary anatomy and the presence of
complications, whose final diagnosis was based on endoscopic retrograde
cholangiography, percutaneous trans-hepatic cholangiography, and by integrating
clinical follow-up with ultrasound and/or MR findings.
RESULTS: Biliary complications were found in 60 patients (46.5%) and were
represented by ischemic-type biliary lesions (n=21); anastomotic strictures
(n=13); non-anastomotic strictures (n=5); anastomotic strictures associated to
lithiasis (n=6); lithiasis (n=6); papillary dysfunctions (n=9). The sensitivity,
specificity, positive predictive value, and negative predictive value of the
reviewers for the detection of all types of biliary complications in patients
with OLT were 98%, 94%, 94%, and 98%, respectively.
CONCLUSIONS: MRC is a reliable technique for detecting post-OLT biliary
complications and should be recommended before planning therapeutic
interventions