Fun Inc.: Why Gaming Will Dominate The Twenty First Century

American is the world’s greatest video gaming nation, and it should be proud of this status. It dominates globally in terms of the value of this market, but also in the sophistication of its audience and the quality of its industry. It’s thanks to games, in large part, that I have got t know American as I do. Or, to be more precise, it’s thanks to games that I have got to know certain Americans. I am far from alone this. The greatest value and interest of any medium is always the human experiences it enables, not the machinery in which it encodes them. And, at their best, electronic games can show us at our best: creatively, socially, politically, and intellectually. We need to take this world “gamers” and throw it away, together with all those other generalizations that open up no debate and that mask the future under vague hopes and wild fears. We need talk seriously, now, about how to get the best out of games, where the worst really lies, and what the games we play can tell us about ourselves and our future. The news may not all be good. But we cannot afford to ignore it

Accounting for seasonal patterns in syndromic surveillance data for outbreak detection

BACKGROUND: Syndromic surveillance (SS) can potentially contribute to outbreak detection capability by providing timely, novel data sources. One SS challenge is that some syndrome counts vary with season in a manner that is not identical from year to year. Our goal is to evaluate the impact of inconsistent seasonal effects on performance assessments (false and true positive rates) in the context of detecting anomalous counts in data that exhibit seasonal variation. METHODS: To evaluate the impact of inconsistent seasonal effects, we injected synthetic outbreaks into real data and into data simulated from each of two models fit to the same real data. Using real respiratory syndrome counts collected in an emergency department from 2/1/94–5/31/03, we varied the length of training data from one to eight years, applied a sequential test to the forecast errors arising from each of eight forecasting methods, and evaluated their detection probabilities (DP) on the basis of 1000 injected synthetic outbreaks. We did the same for each of two corresponding simulated data sets. The less realistic, nonhierarchical model's simulated data set assumed that "one season fits all," meaning that each year's seasonal peak has the same onset, duration, and magnitude. The more realistic simulated data set used a hierarchical model to capture violation of the "one season fits all" assumption. RESULTS: This experiment demonstrated optimistic bias in DP estimates for some of the methods when data simulated from the nonhierarchical model was used for DP estimation, thus suggesting that at least for some real data sets and methods, it is not adequate to assume that "one season fits all." CONCLUSION: For the data we analyze, the "one season fits all " assumption is violated, and DP performance claims based on simulated data that assume "one season fits all," for the forecast methods considered, except for moving average methods, tend to be optimistic. Moving average methods based on relatively short amounts of training data are competitive on all three data sets, but are particularly competitive on the real data and on data from the hierarchical model, which are the two data sets that violate the "one season fits all" assumption

Image features for visual teach-and-repeat navigation in changing environments

We present an evaluation of standard image features in the context of long-term visual teach-and-repeat navigation of mobile robots, where the environment exhibits significant changes in appearance caused by seasonal weather variations and daily illumination changes. We argue that for long-term autonomous navigation, the viewpoint-, scale- and rotation- invariance of the standard feature extractors is less important than their robustness to the mid- and long-term environment appearance changes. Therefore, we focus our evaluation on the robustness of image registration to variable lighting and naturally-occurring seasonal changes. We combine detection and description components of different image extractors and evaluate their performance on five datasets collected by mobile vehicles in three different outdoor environments over the course of one year. Moreover, we propose a trainable feature descriptor based on a combination of evolutionary algorithms and Binary Robust Independent Elementary Features, which we call GRIEF (Generated BRIEF). In terms of robustness to seasonal changes, the most promising results were achieved by the SpG/CNN and the STAR/GRIEF feature, which was slightly less robust, but faster to calculate

The ethics of ‘Trials within Cohorts’ (TwiCs): 2nd international symposium - London, UK. 7-8 November 2016

On 7-8 th November 2016, 60 people with an interest in the ‘ Trials within Cohorts ’ (TwiCs) approach for randomised controlled trial design met in London. The purpose of this 2 nd TwiCs international symposium was to share perspectives and experiences on ethical aspects of the TwiCs design, discuss how TwiCs relate to the current ethical frame- work, provide a forum in which to discuss and debate ethical issues and identify future directions for conceptual and empirical research. The symposium was supported by the Wellcome Trust and the NIHR CLAHRC Yorkshire and Humber and organised by members of the TwiCs network led by Clare Relton and attended by people from the UK, the Netherlands, Norway, Canada and USA. The two-day sympo- sium enabled an international group to meet and share experiences of the TwiCs design (also known as the ‘ cohort multiple RCT design ’ ), and to discuss plans for future research. Over the two days, invited plenary talks were interspersed by discussions, posters and mini pre- sentations from bioethicists, triallists and health research regulators. Key findings of the symposium were: (1) It is possible to make a compelling case to ethics committees that TwiCs designs are ap- propriate and ethical; (2) The importance of wider considerations around the ethics of inefficient trial designs; and (3) some questions about the ethical requirements for content and timing of informed consent for a study using the TwiCs design need to be decided on a case-by-case basis

Critical thinking : your guide to effective argument, successful analysis and independent study

vii, 314 p. : col. ill. ; 26 cm

Berpikir Kritis: Panduan Beragumen, Menganalisis, dan Melakukan Studi Mandiri Secara Menyakinkan (BI)

x, 455 halaman.; gambar.; 19x24,5 c

Learning and approximate inference in dynamic hierarchical models

Contains fulltext : 34584.pdf (preprint version ) (Open Access