The ratios of specific heats, γ = (CP/CV), for three gases (air, argon and carbon dioxide) were calculated by measuring the oscillations of different masses in various apparatus. The experiments followed Rüchardt's and Rinkel's methods; a 100ml glass gas syringe was additionally used to extend the investigation as well as a technique to elimination of friction. The approaches and results were compared; the most accurate method (Rüchardt's method alongside compensation for friction) yielded:
Air, γ = 1.358 ± 0.0038
Argon, γ = 1.6597 ± 0.0009
Carbon dioxide, γ = 1.2996 ± 0.0087
These differ from the literature value by 3.0%, 0.6% and 1.5% respectively. The reasons for these apparent discrepancies are discussed.
This article presents methods and results in the application of the Markov Chain Monte Carlo analysis to a problem in missing data. The data used here are The Atlantic Slave Trade Database (tastd), 2010 version, available online. The article begins with background to the Bayesian statistical framework, Markov chains, and Monte Carlo methods, as compared with the frequentist statistical framework, still more widely used in economic (and demographic?) analyses.. It then describes the data, their analysis, the results, and a discussion of their strengths and weaknesses. The results provide a new estimate of the volume of African embarkations and American arrivals in the transatlantic slave trade for the period from 1650 to 1870, by decade, for eleven African regions of embarkation and seven American and European regions of arrival. These results are compared with earlier estimates of Atlantic slave trade volume by frequentist methods.
This is a LaTeX template for preparing EU Future and Emerging Technologies (FET) Open Proposals. It is based on the h2020proposal.cls LaTeX class for writing EU Horizon 2020 Research & Innovation Actions (RIA) proposals.
Disclaimer: The template is based on this document (PDF) provided by the EU Participants Portal.
Use the original source and the http://ec.europa.eu/ documentation for reference.
The authors make no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability, suitability or availability with respect to the original template.
Please see the comments at the start of the proposal template for further details and license information.
Giacomo Indiveri, with contributions from Elisabetta Chicca
We develop 3 term-based models(Naive tf, log tf, and BM25), unigram language model, and Pointwise
Online AdaGrad approach to select top 100 documents of each query. We use MIN((TP+FN),100) as
denominator when calculating AP. We also perform some methods in preprocessing and running stage to
obtain better MAP, as well less running time of the whole program. 2 rounds of scanning are needed in