The Importance of Transparency and Willingness to Share Personal Information

This study investigates the extent to which individuals are willing to share their sensitive personal information with companies. The study examines whether skepticism can influence willingness to share information. Additionally, it seeks to determine whether transparency can moderate the relationship between skepticism and willingness to share and whether 1) companies perceived motives, 2) individual’s prior privacy violations, 3) individuals’ propensity to take risks, and 4) individuals self-efficacy act as antecedents of skepticism. Partial Least Squares (PLS) regression is used to examine the relationships between all the factors. The findings indicate that skepticism does have a negative impact on willingness to share personal information and that transparency can reduce skepticis

Computer transformation of partial differential equations into any coordinate system

The use of tensors to provide a compact way of writing partial differential equations in a form valid in all coordinate systems is discussed. In order to find solutions to the equations with their boundary conditions they must be expressed in terms of the coordinate system under consideration. The process of arriving at these expressions from the tensor formulation was automated by a software system, TENSR. An allied system that analyzes the resulting expressions term by term and drops those that are negligible is also described

SIGNIFICANT DEVELOPMENTS IN SOUTHERN AGRICULTURE IN THE DECADE OF THE 1970S AND EMERGING POLICY ISSUES IN THE 1980S

Teaching/Communication/Extension/Profession,

Evaluation of user reactions to a prototype on-line information retrieval system

Human reaction to operation of document search and retrieval syste

Ablation article and method

An ablation article, such as a conical heat shield, having an ablating surface is provided with at least one discrete area of at least one seed material, such as aluminum. When subjected to ablation conditions, the seed material is ablated. Radiation emanating from the ablated seed material is detected to analyze ablation effects without disturbing the ablation surface. By providing different seed materials having different radiation characteristics, the ablating effects on various areas of the ablating surface can be analyzed under any prevailing ablation conditions. The ablating article can be provided with means for detecting the radiation characteristics of the ablated seed material to provide a self-contained analysis unit

Locally Estimating Core Numbers

Graphs are a powerful way to model interactions and relationships in data from a wide variety of application domains. In this setting, entities represented by vertices at the "center" of the graph are often more important than those associated with vertices on the "fringes". For example, central nodes tend to be more critical in the spread of information or disease and play an important role in clustering/community formation. Identifying such "core" vertices has recently received additional attention in the context of {\em network experiments}, which analyze the response when a random subset of vertices are exposed to a treatment (e.g. inoculation, free product samples, etc). Specifically, the likelihood of having many central vertices in any exposure subset can have a significant impact on the experiment. We focus on using $k$-cores and core numbers to measure the extent to which a vertex is central in a graph. Existing algorithms for computing the core number of a vertex require the entire graph as input, an unrealistic scenario in many real world applications. Moreover, in the context of network experiments, the subgraph induced by the treated vertices is only known in a probabilistic sense. We introduce a new method for estimating the core number based only on the properties of the graph within a region of radius $\delta$ around the vertex, and prove an asymptotic error bound of our estimator on random graphs. Further, we empirically validate the accuracy of our estimator for small values of $\delta$ on a representative corpus of real data sets. Finally, we evaluate the impact of improved local estimation on an open problem in network experimentation posed by Ugander et al.Comment: Main paper body is identical to previous version (ICDM version). Appendix with additional data sets and enlarged figures has been added to the en