The fading breadwinner role and the implications for young couples

It is a commonplace that the past few decades have been a time of increasing importance in the role of women as income providers, both within and outside of marriage. Drawing on data from the 1964 and 1993 March Current Population Surveys (CPS), we document the changing division of income provision within marriage and the association between changing marital income-provision roles and younger couples' economic welfare over the past thirty years. We find that the proportion of marriages in which husbands are primary breadwinners has declined dramatically, with a corresponding rise in "co-provider" marriages. Regression analyses show that (1) co- provider marriages are economically advantaged compared to other income-provision-role arrangements in both the early 1960s and the early 1990s; and (2) a relatively substantial part of the total improvement in younger couples' economic welfare over time stems from the shift towards co-provider marriages.

The mobile wireless classroom: pocket PCs in higher education

Since 2003, EWU has been using the Mobile Wireless Classroom, a pilot project consisting of a self-contained portable set of 30 Pocket PCs for electronic assessments. Pocket PCs were selected as an alternative to laptop computers as they maintain much of the same capability but at a fraction of the cost and are much less invasive in general classroom use. Students ranging from first-quarter freshmen in English Composition to last-quarter seniors in Developmental Psychology use the Pocket PCs to respond to lectures, watch videos of laboratory procedures, and to submit writing samples for peer review. Professors using the mobile assessments can quickly gather feedback from students and pinpoint areas where further review is needed

Constant-degree graph expansions that preserve the treewidth

Many hard algorithmic problems dealing with graphs, circuits, formulas and constraints admit polynomial-time upper bounds if the underlying graph has small treewidth. The same problems often encourage reducing the maximal degree of vertices to simplify theoretical arguments or address practical concerns. Such degree reduction can be performed through a sequence of splittings of vertices, resulting in an _expansion_ of the original graph. We observe that the treewidth of a graph may increase dramatically if the splittings are not performed carefully. In this context we address the following natural question: is it possible to reduce the maximum degree to a constant without substantially increasing the treewidth? Our work answers the above question affirmatively. We prove that any simple undirected graph G=(V, E) admits an expansion G'=(V', E') with the maximum degree <= 3 and treewidth(G') <= treewidth(G)+1. Furthermore, such an expansion will have no more than 2|E|+|V| vertices and 3|E| edges; it can be computed efficiently from a tree-decomposition of G. We also construct a family of examples for which the increase by 1 in treewidth cannot be avoided.Comment: 12 pages, 6 figures, the main result used by quant-ph/051107

A Photometrically and Morphologically Variable Infrared Nebula in L483

We present narrow and broad K-band observations of the Class 0/I source IRAS 18148-0440 that span 17 years. The infrared nebula associated with this protostar in the L483 dark cloud is both morphologically and photometrically variable on a time scale of only a few months. This nebula appears to be an infrared analogue to other well-known optically visible variable nebulae associated with young stars, such as Hubble's Variable Nebula. Along with Cepheus A, this is one of the first large variable nebulae to be found that is only visible in the infrared. The variability of this nebula is most likely due to changing illumination of the cloud rather than any motion of the structure in the nebula. Both morphological and photometric changes are observed on a time scale only a few times longer than the light crossing time of the nebula, suggesting very rapid intrinsic changes in the illumination of the nebula. Our narrow-band observations also found that H_2 knots are found nearly twice as far to the east of the source as to its west, and that H_2 emission extends farther east of the source than the previously known CO outflow.Comment: 19 pages, 6 figures, 1 tabl

Efficient Attack Graph Analysis through Approximate Inference

Attack graphs provide compact representations of the attack paths that an attacker can follow to compromise network resources by analysing network vulnerabilities and topology. These representations are a powerful tool for security risk assessment. Bayesian inference on attack graphs enables the estimation of the risk of compromise to the system's components given their vulnerabilities and interconnections, and accounts for multi-step attacks spreading through the system. Whilst static analysis considers the risk posture at rest, dynamic analysis also accounts for evidence of compromise, e.g. from SIEM software or forensic investigation. However, in this context, exact Bayesian inference techniques do not scale well. In this paper we show how Loopy Belief Propagation - an approximate inference technique - can be applied to attack graphs, and that it scales linearly in the number of nodes for both static and dynamic analysis, making such analyses viable for larger networks. We experiment with different topologies and network clustering on synthetic Bayesian attack graphs with thousands of nodes to show that the algorithm's accuracy is acceptable and converge to a stable solution. We compare sequential and parallel versions of Loopy Belief Propagation with exact inference techniques for both static and dynamic analysis, showing the advantages of approximate inference techniques to scale to larger attack graphs.Comment: 30 pages, 14 figure

Improving the Efficiency of Reasoning Through Structure-Based Reformulation

Abstract. We investigate the possibility of improving the efficiency of reasoning through structure-based partitioning of logical theories, combined with partitionbased logical reasoning strategies. To this end, we provide algorithms for reasoning with partitions of axioms in first-order and propositional logic. We analyze the computational benefit of our algorithms and detect those parameters of a partitioning that influence the efficiency of computation. These parameters are the number of symbols shared by a pair of partitions, the size of each partition, and the topology of the partitioning. Finally, we provide a greedy algorithm that automatically reformulates a given theory into partitions, exploiting the parameters that influence the efficiency of computation.

Redundancy, Deduction Schemes, and Minimum-Size Bases for Association Rules

Association rules are among the most widely employed data analysis methods in the field of Data Mining. An association rule is a form of partial implication between two sets of binary variables. In the most common approach, association rules are parameterized by a lower bound on their confidence, which is the empirical conditional probability of their consequent given the antecedent, and/or by some other parameter bounds such as "support" or deviation from independence. We study here notions of redundancy among association rules from a fundamental perspective. We see each transaction in a dataset as an interpretation (or model) in the propositional logic sense, and consider existing notions of redundancy, that is, of logical entailment, among association rules, of the form "any dataset in which this first rule holds must obey also that second rule, therefore the second is redundant". We discuss several existing alternative definitions of redundancy between association rules and provide new characterizations and relationships among them. We show that the main alternatives we discuss correspond actually to just two variants, which differ in the treatment of full-confidence implications. For each of these two notions of redundancy, we provide a sound and complete deduction calculus, and we show how to construct complete bases (that is, axiomatizations) of absolutely minimum size in terms of the number of rules. We explore finally an approach to redundancy with respect to several association rules, and fully characterize its simplest case of two partial premises.Comment: LMCS accepted pape

Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings

Constraint programming is a paradigm wherein relations between variables are stated in the form of constraints. Many real life problems come from uncertain and dynamic environments, where the initial constraints and domains may change during its execution. Thus, the solution found for the problem may become invalid. The search forrobustsolutions for constraint satisfaction problems (CSPs) has become an important issue in the ¿eld of constraint programming. In some cases, there exists knowledge about the uncertain and dynamic environment. In other cases, this information is unknown or hard to obtain. In this paper, we consider CSPs with discrete and ordered domains where changes only involve restrictions or expansions of domains or constraints. To this end, we model CSPs as weighted CSPs (WCSPs) by assigning weights to each valid tuple of the problem constraints and domains. The weight of each valid tuple is based on its distance from the borders of the space of valid tuples in the corresponding constraint/domain. This distance is estimated by a new concept introduced in this paper: coverings. Thus, the best solution for the modeled WCSP can be considered as a most robust solution for the original CSP according to these assumptionsThis work has been partially supported by the research projects TIN2010-20976-C02-01 (Min. de Ciencia e Innovacion, Spain) and P19/08 (Min. de Fomento, Spain-FEDER), and the fellowship program FPU.Climent Aunés, LI.; Wallace, RJ.; Salido Gregorio, MA.; Barber Sanchís, F. (2013). Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings. Artificial Intelligence Review. 1-26. https://doi.org/10.1007/s10462-013-9420-0S126Climent L, Salido M, Barber F (2011) Reformulating dynamic linear constraint satisfaction problems as weighted csps for searching robust solutions. 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