Encoding points on hyperelliptic curves over finite fields in deterministic polynomial time

We present families of (hyper)elliptic curve which admit an efficient deterministic encoding function

Finding home: Black queer historical scholarship in the United States Part II

This essay surveys the extant historical and historically minded scholarship about the political, social, and cultural life of African American/black LGBT/queer. Characterizing this area of inquiry as “black queer historical studies,” this essay addresses scholars’ diverse approaches to the challenge of archival research, current scholarship about the intersecting histories of blackness and queerness in the United States, and four key topical concerns: black “lesbian” histories, gender transgression, class, and community formation/politics.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149251/1/hic312533.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149251/2/hic312533_am.pd

Predicting growth rates and recessions: assessing US leading indicators under real-time conditions

In this paper we analyze the power of various indicators to predict growth rates of aggregate production using real-time data. In addition, we assess their ability to predict turning points of the economy. We consider four groups of indicators: survey data, composite indicators, real economic indicators, and financial data. Almost all indicators are found to improve short-run growth forecasts whereas the results for four-quarter-ahead growth forecasts and the prediction of recession probabilities in general are mixed. We can confirm the result that an indicator suited to improve growth forecasts does not necessarily help to produce more accurate recession forecasts. Only composite leading indicators perform generally well in both forecasting exercises

Towards a consolidation of worldwide journal rankings - A classification using random forests and aggregate rating via data envelopment analysis

AbstractThe question of how to assess research outputs published in journals is now a global concern for academics. Numerous journal ratings and rankings exist, some featuring perceptual and peer-review-based journal ranks, some focusing on objective information related to citations, some using a combination of the two. This research consolidates existing journal rankings into an up-to-date and comprehensive list. Existing approaches to determining journal rankings are significantly advanced with the application of a new classification approach, ‘random forests’, and data envelopment analysis. As a result, a fresh look at a publication׳s place in the global research community is offered. While our approach is applicable to all management and business journals, we specifically exemplify the relative position of ‘operations research, management science, production and operations management’ journals within the broader management field, as well as within their own subject domain

Bayesian Mode Regression

This article has been made available through the Brunel Open Access Publishing Fund.Like mean, quantile and variance, mode is also an important measure of central tendency of a distribution. Many practical questions, particularly in the analysis of big data, such as \Which element (gene or le or signal) is the most typical one among all elements in a network?" are directly related to mode. Mode regression, which provides a convenient summary of how the regressors a ect the conditional mode, is totally di erent from other models based on conditional mean or conditional quantile or conditional variance. Some inference methods for mode regression exist but none of them is from the Bayesian perspective. This paper introduces Bayesian mode regression by exploring three different approaches, including their theoretic properties. The proposed approacher are illustrated using simulated datasets and a real data set