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.

Poverty and Depressed Mood Among Urban African-American Adolescents: A Family Stress Perspective

Abstract: We examined the role of family stress as a mediator of the relationship between poverty and depressed mood among 1,704 low-income, inner-city African- American adolescents. Nearly half of participants (47%) reported clinically significant levels of depressive symptoms. Being female, reporting higher levels of family stress, and scoring higher on a poverty index were significantly associated with increased reports of depressed mood. Family stress significantly mediated the relationship between poverty and adolescent depressed mood, explaining 50% of the total effect. Sex-specific analyses revealed that this relationship only held for females, and there was no direct relationship between poverty and depressed mood for males. Results lend further support to family stress theory, although they suggest that the model may be more relevant for females than males. Implications for community-based preventive intervention and social policy are discussed.

Specifications of a high-level conflict-free firewall policy language for multi-domain networks

Abstract: Multiple firewalls typically cooperate to provide security properties for a network, despite the fact that these firewalls are often spatially distributed and configured in isolation. Without a global view of the network configuration, such a system is ripe for misconfiguration, causing conflicts and major security vulnerabilities.We propose FLIP, a high-level firewall configuration policy language for traffic access control, to enforce security and ensure seamless configuration management. In FLIP, firewall security policies are defined as high-level service-oriented goals, which can be translated automatically into access control rules to be distributed to appropriate enforcement devices. FLIP guarantees that the rules generated will be conflict-free, both on individual firewall and between firewalls. We prove that the translation algorithm is both sound and complete.FLIP supports policy inheritance and customization features that enable defining a global firewall policy for large-scale enterprise network quickly and accurately. Through a case study, we argue that firewall policy management for large-scale networks is efficient and accurate using FLIP.

CSLIM: contextual SLIM recommendation algorithms

Abstract: Context-aware recommender systems (CARS) take contextual conditions into account when providing item recommendations. In recent years, context-aware matrix factorization (CAMF) has emerged as an extension of the matrix factorization technique that also incorporates contextual conditions. In this paper, we introduce another matrix factorization approach for contextual recommendations, the contextual SLIM (CSLIM) recommendation approach. It is derived from the sparse linear method (SLIM) which was designed for Top-N recommendations in traditional recommender systems. Based on the experimental evaluations over several context-aware data sets, we demonstrate that CLSIM can be an effective approach for context-aware recommendations, in many cases outperforming state-of-the-art CARS algorithms in the Top-N recommendation task.

Individual Agents, Firms, and the Real Estate Brokerage Process

Abstract: This study examines how individual agents affect house selling prices and time on the market while controlling for brokerage firm-specific effects as well as supply and demand conditions that vary by neighborhood. Firm size effects disappear once firm specialization and agent characteristics are taken into account but geographic concentration by firms leads to higher selling prices. For individual agents, neither sex nor selling own listings affects price or selling time, but there are gains from partnering transactions across firms. Agents who specialize in listing properties obtain higher prices for their sellers while those who specialize in selling obtain lower prices for their buyers. Houses nearer to other transactions of an agent sell for higher prices. Finally, greater scale of listing and selling activity by an agent tends to lower selling price or lengthen the time on the market.