In this paper we investigate the issue of resource matching between jobs and machines in Intel’s compute farm. We show that common heuristics such as Best-Fit and Worse-Fit may fail to properly utilize the available resources when applied to either cores or memory in isolation. In an attempt to overcome the problem we propose Mix-Fit, a heuristic which attempts to balance usage between resource...

This study investigated how a job seeker self-presentation affects recruiter’s hiring recommendations in an online communities and what categories of self-presentation contribute to fit perceptions for obtaining hiring recommendations. The study participants viewed potential candidates’ LinkedIn profiles and responded to questions regarding the argument quality and source credibility of their s...

This paper discusses a recent development in partial least squares (PLS) path modeling, namely goodness-of-fit indices. In order to illustrate the behavior of the goodness-of-fit index (GoF) and the relative goodness-of-fit index (GoFrel), we estimate PLS path models with simulated data, and contrast their values with fit indices commonly used in covariance-based structural equation modeling. T...

We have earlier reported the MOLSDOCK technique to perform rigid receptor/flexible ligand docking. The method uses the MOLS method, developed in our laboratory. In this paper we report iMOLSDOCK, the 'flexible receptor' extension we have carried out to the algorithm MOLSDOCK. iMOLSDOCK uses mutually orthogonal Latin squares (MOLS) to sample the conformation and the docking pose of the ligand an...

Radiologists routinely document mammography results in free text dictations. In the last decade, there has been an increase in the volume of mammography performed in the U.S. As a result, The American College of Radiology has standardized the practice of screening mammography by introducing a controlled vocabulary and practice standards tracked by audits. Extracting data from these free text re...

We formulate optical flow estimation as a two-stage regression problem. Based on characteristics of these two regression models and conclusions on modern regression methods, we choose a Least Trimmed Squares followed by weighted Least Squares estimator to solve the optical flow constraint (OFC); and at places where this one-stage robust method fails due to poor derivative quality, we use a Leas...

Given a set of scattered data with derivative values. If the data is noisy or there is an extremely large number of data, we use an extension of the penalized least squares method of von Golitschek and Schumaker [Serdica, 18 (2002), pp.1001-1020] to fit the data. We show that the extension of the penalized least squares method produces a unique spline to fit the data. Also we give the error bou...