DePaul University

About: DePaul University is a education organization based out in Chicago, Illinois, United States. It is known for research contribution in the topics: Population & Context (language use). The organization has 5658 authors who have published 11562 publications receiving 295257 citations.

Race and Ethnicity in Leisure Behavior: Where Have We Been and Where Do We Need to Go?

Abstract: The ethnic and racial profile of the U.S. is undergoing a major shift such that in the decades ahead people of color will constitute a majority of the population. This demographic condition already...

Non-pharmacologic interventions for CFS: A randomized trial

Abstract: Non-pharmacological behavioral treatments for CFS have been suggested as promising. These trials have tested protocols composed of behavioral, cognitive and cognitive–behavioral interventions but there have been few efforts to differentially evaluate their outcomes. The primary purpose of the current study was to evaluate the effectiveness of nurse delivered non-pharmacologic interventions. In the present study, 114 participants diagnosed with CFS were randomly assigned to four 6-month interventions. The interventions were: cognitive–behavior therapy, cognitive therapy, anaerobic activity, and a relaxation control group. The study found that these interventions led to increases in several areas of functioning, with more consistent changes occurring among those participants in the cognitive condition. For the 25 variables in this study, significant change occurred for 28%, 20%, 16%, and 12% of the variables for the cognitive, cognitive behavior therapy, anaerobic activity, and relaxation conditions, respectively. However, the majority of participants continued to be diagnosed with CFS following the treatment trial. Implications of these findings are discussed.

Types and effects for asymmetric cryptographic protocols

Abstract: We present the first type and effect system for proving authenticity properties of security protocols based on asymmetric cryptography. The most significant new features of our type system are: (1) a separation of public types (for data possibly sent to the opponent) from tainted types (for data possibly received from the opponent) via a subtype relation; (2) trust effects, to guarantee that tainted data does not, in fact, originate from the opponent; and (3) challenge/response types to support a variety of idioms used to guarantee message freshness. We illustrate the applicability of our system via protocol examples. This material is based upon work supported by the National Science Foundation under Grant No. 0208549.

Supporting Domain Analysis through Mining and Recommending Features from Online Product Listings

Abstract: Domain analysis is a labor-intensive task in which related software systems are analyzed to discover their common and variable parts. Many software projects include extensive domain analysis activities, intended to jumpstart the requirements process through identifying potential features. In this paper, we present a recommender system that is designed to reduce the human effort of performing domain analysis. Our approach relies on data mining techniques to discover common features across products as well as relationships among those features. We use a novel incremental diffusive algorithm to extract features from online product descriptions, and then employ association rule mining and the (k)-nearest neighbor machine learning method to make feature recommendations during the domain analysis process. Our feature mining and feature recommendation algorithms are quantitatively evaluated and the results are presented. Also, the performance of the recommender system is illustrated and evaluated within the context of a case study for an enterprise-level collaborative software suite. The results clearly highlight the benefits and limitations of our approach, as well as the necessary preconditions for its success.