One Dimensional Continuum Falicov-Kimball Model in the Strongly Correlated Limit

In this paper we study the thermodynamics of the one dimensional continuum analogue of the Falicov-Kimball model in the strongly correlated limit using a method developed by Salsburg, Zwanzig and Kirkwood for the Takahashi gas. In the ground state it is found that the $f$ electrons form a cluster. The effect of including a Takahashi repulsion between $f$ particles is also studied where it is found that as the repulsion is increased the ground state $f$ electron configuration changes discontinuously from the clustered configuration to a homogeneous or equal spaced configuration analogous to the checkerboard configuration which arises in the lattice Falicov-Kimball model.Comment: 17 pages, Standard Latex File (UUencoded Postscript file of figures available upon request. To appear in physica A) MELB-MATHS-PP-1096783, email: [email protected]

Does concealed handgun carry make campus safer? A panel data analysis of crime on college and university campuses

The purpose of this report is to recommend and test an empirical strategy for assessing the impact that concealed carry policies have on crime at college and university campuses. I use panel data obtained from the Department of Education for all crimes reported on four-year, undergraduate, federal financial aid-receiving institutions between 2001 and 2014 to model the impact of campus carry legislation. Differences in legislation across states, time, and school types allow for estimation of a triple difference regression model. Results of OLS estimations show that campus carry has no significant observable association with rates of aggravated assault, sexual assault, robbery, burglary, and motor theft committed on campus at the 95% confidence interval. These results are robust to a number of different assumptions, including time lag and negative binomial modeling approaches. However, true effects may be difficult to determine precisely as model estimations present large standard errors. Notably, my analysis does not attempt to control for variables that may also influence campus crime rates, such as local economic conditions, gun ownership rates, or rates of concealed carrying on campus. This analysis is therefore only a starting point for further research and the results contained here should be considered preliminary. At most, my analysis may throw partisan narratives surrounding campus carry into some measure of doubt. In particular, results fail to demonstrate a measurable deterrent effect theorized by campus carry advocates, or a criminal enabling effect theorized by opponents of the policy. Regardless of crime changes, I suggest that policymakers considering this controversial measure should also weigh how concealed carrying policies may influence a variety of other variables, including student suicides – a full understanding of which requires considerable caution and further research.Public Polic

Berge, Türme und Tempel in altorientalischen und mediterranen Kulturen

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Analytic Methods for Optimizing Realtime Crowdsourcing

Realtime crowdsourcing research has demonstrated that it is possible to recruit paid crowds within seconds by managing a small, fast-reacting worker pool. Realtime crowds enable crowd-powered systems that respond at interactive speeds: for example, cameras, robots and instant opinion polls. So far, these techniques have mainly been proof-of-concept prototypes: research has not yet attempted to understand how they might work at large scale or optimize their cost/performance trade-offs. In this paper, we use queueing theory to analyze the retainer model for realtime crowdsourcing, in particular its expected wait time and cost to requesters. We provide an algorithm that allows requesters to minimize their cost subject to performance requirements. We then propose and analyze three techniques to improve performance: push notifications, shared retainer pools, and precruitment, which involves recalling retainer workers before a task actually arrives. An experimental validation finds that precruited workers begin a task 500 milliseconds after it is posted, delivering results below the one-second cognitive threshold for an end-user to stay in flow.Comment: Presented at Collective Intelligence conference, 201

Hotels-50K: A Global Hotel Recognition Dataset

Recognizing a hotel from an image of a hotel room is important for human trafficking investigations. Images directly link victims to places and can help verify where victims have been trafficked, and where their traffickers might move them or others in the future. Recognizing the hotel from images is challenging because of low image quality, uncommon camera perspectives, large occlusions (often the victim), and the similarity of objects (e.g., furniture, art, bedding) across different hotel rooms. To support efforts towards this hotel recognition task, we have curated a dataset of over 1 million annotated hotel room images from 50,000 hotels. These images include professionally captured photographs from travel websites and crowd-sourced images from a mobile application, which are more similar to the types of images analyzed in real-world investigations. We present a baseline approach based on a standard network architecture and a collection of data-augmentation approaches tuned to this problem domain