Deep Network Flow for Multi-Object Tracking

Data association problems are an important component of many computer vision applications, with multi-object tracking being one of the most prominent examples. A typical approach to data association involves finding a graph matching or network flow that minimizes a sum of pairwise association costs, which are often either hand-crafted or learned as linear functions of fixed features. In this work, we demonstrate that it is possible to learn features for network-flow-based data association via backpropagation, by expressing the optimum of a smoothed network flow problem as a differentiable function of the pairwise association costs. We apply this approach to multi-object tracking with a network flow formulation. Our experiments demonstrate that we are able to successfully learn all cost functions for the association problem in an end-to-end fashion, which outperform hand-crafted costs in all settings. The integration and combination of various sources of inputs becomes easy and the cost functions can be learned entirely from data, alleviating tedious hand-designing of costs.Comment: Accepted to CVPR 201

A Multidimensional Relativistic Hydrodynamics Code with a General Equation of State

The ideal gas equation of state with a constant adiabatic index, although commonly used in relativistic hydrodynamics, is a poor approximation for most relativistic astrophysical flows. Here we propose a new general equation of state for a multi-component relativistic gas which is consistent with the Synge equation of state for a relativistic perfect gas and is suitable for numerical (special) relativistic hydrodynamics. We also present a multidimensional relativistic hydrodynamics code incorporating the proposed general equation of state, based on the HLL scheme, which does not make use of a full characteristic decomposition of the relativistic hydrodynamic equations. The accuracy and robustness of this code is demonstrated in multidimensional calculations through several highly relativistic test problems taking into account nonvanishing tangential velocities. Results from three-dimensional simulations of relativistic jets show that the morphology and dynamics of the relativistic jets are significantly influenced by the different equation of state and by different compositions of relativistic perfect gases. Our new numerical code, combined with our proposed equation of state is very efficient and robust, and unlike previous codes, it gives very accurate results for thermodynamic variables in relativistic astrophysical flows.Comment: 32 pages, 9 figures, accepted by ApJ

Rayleigh scattering, mode coupling, and optical loss in silicon microdisks

High refractive index contrast optical microdisk resonators fabricated from silicon-on-insulator wafers are studied using an external silica fiber taper waveguide as a wafer-scale optical probe. Measurements performed in the 1500 nm wavelength band show that these silicon microdisks can support whispering-gallery modes with quality factors as high as 5.2 x 10^5, limited by Rayleigh scattering from fabrication induced surface roughness. Microdisks with radii as small as 2.5 microns are studied, with measured quality factors as high as 4.7 x 10^5 for an optical mode volume of 5.3 cubic wavelengths in the material.Comment: 4 pages, 2 figures; contains minor correction to doublet splitting theor

lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations

Logistic regression provides a flexible framework for detecting various types of differential item functioning (DIF). Previous efforts extended the framework by using item response theory (IRT) based trait scores, and by employing an iterative process using group--specific item parameters to account for DIF in the trait scores, analogous to purification approaches used in other DIF detection frameworks. The current investigation advances the technique by developing a computational platform integrating both statistical and IRT procedures into a single program. Furthermore, a Monte Carlo simulation approach was incorporated to derive empirical criteria for various DIF statistics and effect size measures. For purposes of illustration, the procedure was applied to data from a questionnaire of anxiety symptoms for detecting DIF associated with age from the Patient--Reported Outcomes Measurement Information System.

Do Bank Loans Curb Corporate Moral Hazard?

In this paper, we discuss optimal contract drafting between a lender with deficient monitoring capabilities and an agency-ridden borrower with insufficient budget to finance an investable project. The theoretical implications are as follows: First, the first best solution (FBS) is achievable under no hidden action. However, the borrower’s action is hardly observable in practice. Second, with unobservable managerial decisions the borrower exerts sub-optimal effort (moral hazard), and the probability of default increases. Lastly, with a penalizing discretion entitled to the bank on a long-term contract, the financial intermediary will be able to control the firm’s managerial action effectively such that the solution is equivalent to the FBS attained under no hidden action. Empirical implications are followed

Management competencies of golf course directors

Scope and Method of Study: The purpose of this study was: (1) to identify differences in response toward the importance of management competencies among golf course directors who held PGA membership in diverse regions of the United States; (2) to identify the differences in the perceived importance of management competencies among PGA golf professionals in disparate types of golf courses (private, semiprivate, and public) in the United States; (3) to determine if there was consistency among PGA golf professionals as to preferred competencies for golf course directors; and (4) to discover the importance of needed competencies identified in the PGA professionals' analysis for golf course directors in private, semi-private, and public golf courses in the United States.Findings and Conclusions: The perceived importance of the management competencies among PGA golf directors at disparate types of golf courses in diverse regions was tested using the Competencies of Golf Course Directors (CGCD) instrument. Statistical analyses indicated that the importance of preferred management competencies differed among golf course directors in diverse golf environments. Some differences were shown to exist between golf course directors in diverse regions and in disparate types of golf courses. Therefore, there was little consistency in the perceived importance of each competency among golf course directors. Competency factors identified by golf course directors indicated the presence of a 2-factor competency model, which consisted of 76 observed competencies including (1) Golf Operations and (2) Client Care Development. Overall response rate for this study was low (10.3 percent) compared to other online surveys. However, the CGCD explained 36.5 percent of variance in the response group