The Irish hospitals sweepstake in the United States of America, 1930-1939

The Irish hospitals sweepstake was established by statute in the Irish Free State in 1930 to fund the state’s hospital service. The vast majority of tickets were sold outside Ireland, particularly in countries where such gambling was illegal at the time. Initially the largest market was in the United Kingdom, but following the introduction of restrictive legislation there in 1934, the promoters of the sweepstake turned their attentions to North America and after 1936 the United States became the largest source of contributions to the Irish sweep. This article examines a number of factors concerning the relationship of the Irish sweep with the USA, including: an effort to estimate the amount of money contributed to the sweep by Americans; the role of the Irish diaspora and of prominent republicans, including Joseph McGarrity and Connie Neenan, in the illegal ticket distribution network; the efforts of American Federal agencies and government departments to disrupt the sweepstake organisation in America; how the sweep was used by those who sought to legalise gambling in the USA; the attitudes of both the Irish and American governments to the sweep’s activities in America; and how the legalisation of gambling in America brought about the demise of the Irish sweep.

Palmprint Recognition Based on Subspace Analysis of Gabor Filter Bank

This paper introduces a new technique for palmprint recognition based on Fisher Linear Discriminant Analysis (FLDA) and Gabor filter bank. This method involves convolving a palmprint image with a bank of Gabor filters at different scales and rotations for robust palmprint features extraction. Once these features are extracted, FLDA is applied for dimensionality reduction and class separability. Since the palmprint features are derived from the principal lines, wrinkles and texture along the palm area. One should carefully consider this fact when selecting the appropriate palm region for the feature extraction process in order to enhance recognition accuracy. To address this problem, an improved region of interest (ROI) extraction algorithm is introduced. This algorithm allows for an efficient extraction of the whole palm area by ignoring all the undesirable parts, such as the fingers and background. Experiments have shown that the proposed method yields attractive performances as evidenced by an Equal Error Rate (EER) of 0.03%.