Purdue University

About: Purdue University is a education organization based out in West Lafayette, Indiana, United States. It is known for research contribution in the topics: Population & Heat transfer. The organization has 73219 authors who have published 163563 publications receiving 5775236 citations. The organization is also known as: Purdue & Purdue-West Lafayette.

t-Closeness: Privacy Beyond k-Anonymity and l-Diversity

Abstract: The k-anonymity privacy requirement for publishing microdata requires that each equivalence class (ie, a set of records that are indistinguishable from each other with respect to certain "identifying" attributes) contains at least k records Recently, several authors have recognized that k-anonymity cannot prevent attribute disclosure The notion of l-diversity has been proposed to address this; l-diversity requires that each equivalence class has at least l well-represented values for each sensitive attribute In this paper we show that l-diversity has a number of limitations In particular, it is neither necessary nor sufficient to prevent attribute disclosure We propose a novel privacy notion called t-closeness, which requires that the distribution of a sensitive attribute in any equivalence class is close to the distribution of the attribute in the overall table (ie, the distance between the two distributions should be no more than a threshold t) We choose to use the earth mover distance measure for our t-closeness requirement We discuss the rationale for t-closeness and illustrate its advantages through examples and experiments

Effects of human resource systems on manufacturing performance and turnover

Abstract: Using an empirical taxonomy identifying two types of human resource systems, “control” and “commitment,” this study tested the strategic human resource proposition that specific combinations of policies and practices are useful in predicting differences in performance and turnover across steel “minimills.” The mills with commitment systems had higher productivity, lower scrap rates, and lower employee turnover than those with control systems. In addition, human resource system moderated the relationship between turnover and manufacturing performance.

Field-scale variability of soil properties in central iowa soils

Abstract: Spatial distributions of soil properties at the field and watershed scale may affect yield potential, hydrologic responses, and transport of herbicides and NO⁻₃ to surface or groundwater. Our research describes field-scale distributions and spatial trends for 28 different soil parameters at two sites within a watershed in central Iowa. Two of 27 parameters measured at one site and 10 of 14 parameters measured at the second site were normally distributed. Spatial variability was investigated using semivariograms and the ratio of nugget to total semivariance, expressed as a percentage, was used to classify spatial dependence. A ratio of 75% indicated weak spatial dependence. Twelve parameters at Site one, including organic C, total N, pH, and macroaggregation, and four parameters at Site two, including organic C and total N, were strongly spatially dependent. Six parameters at Site one, including biomass C and N, bulk density, and denitrification, and 9 parameters at Site two, including biomass C and N and bulk density, were moderately spatially dependent. Three parameters at Site one, including NO⁻₃ N and ergosterol, and one parameter at Site two, mineral-associated N, were weakly spatially dependent. Distributions of exchangeable Ca and Mg at Site one were not spatially dependent. Spatial distributions for some soil properties were similar for both field sites. We will be able to exploit these similarities to improve our ability to extrapolate information taken from one field to other fields within similar landscapes.

A survey of decision tree classifier methodology

Abstract: A survey is presented of current methods for decision tree classifier (DTC) designs and the various existing issues. After considering potential advantages of DTCs over single-state classifiers, the subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed. The relation between decision trees and neutral networks (NN) is also discussed. >