301 research outputs found
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 Âżeld 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 AunĂ©s, LI.; Wallace, RJ.; Salido Gregorio, MA.; Barber SanchĂs, 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. In: Ninth symposium of abstraction, reformulation, and approximation (SARA-11), pp 34–41Dechter R, Dechter A (1988) Belief maintenance in dynamic constraint networks. In: Proceedings of the 7th national conference on, artificial intelligence (AAAI-88), pp 37–42Dechter R, Meiri I, Pearl J (1991) Temporal constraint networks. Artif Intell 49(1):61–95Fargier H, Lang J (1993) Uncertainty in constraint satisfaction problems: a probabilistic approach. In: Proceedings of the symbolic and quantitative approaches to reasoning and uncertainty (EC-SQARU-93), pp 97–104Fargier H, Lang J, Schiex T (1996) Mixed constraint satisfaction: a framework for decision problems under incomplete knowledge. In: Proceedings of the 13th national conference on, artificial intelligence, pp 175–180Fowler D, Brown K (2000) Branching constraint satisfaction problems for solutions robust under likely changes. In: Proceedings of the international conference on principles and practice of constraint programming (CP-2000), pp 500–504Goles E, MartĂnez S (1990) Neural and automata networks: dynamical behavior and applications. Kluwer Academic Publishers, DordrechtHays W (1973) Statistics for the social sciences, vol 410, 2nd edn. Holt, Rinehart and Winston, New YorkHebrard E (2006) Robust solutions for constraint satisfaction and optimisation under uncertainty. PhD thesis, University of New South WalesHerrmann H, Schneider C, Moreira A, Andrade Jr J, Havlin S (2011) Onion-like network topology enhances robustness against malicious attacks. J Stat Mech Theory Exp 2011(1):P01,027Larrosa J, Schiex T (2004) Solving weighted CSP by maintaining arc consistency. Artif Intell 159:1–26Larrosa J, Meseguer P, Schiex T (1999) Maintaining reversible DAC for Max-CSP. J Artif Intell 107(1):149–163Mackworth A (1977) On reading sketch maps. In: Proceedings of IJCAI’77, pp 598–606Sam J (1995) Constraint consistency techniques for continuous domains. These de doctorat, École polytechnique fĂ©dĂ©rale de LausanneSchiex T, Fargier H, Verfaillie G (1995) Valued constraint satisfaction problems: hard and easy problems. In: Proceedings of the 14th international joint conference on, artificial intelligence (IJCAI-95), pp 631–637Taillard E (1993) Benchmarks for basic scheduling problems. Eur J Oper Res 64(2):278–285Verfaillie G, Jussien N (2005) Constraint solving in uncertain and dynamic environments: a survey. Constraints 10(3):253–281Wallace R, Freuder E (1998) Stable solutions for dynamic constraint satisfaction problems. In: Proceedings of the 4th international conference on principles and practice of constraint programming (CP-98), pp 447–461Wallace RJ, Grimes D (2010) Problem-structure versus solution-based methods for solving dynamic constraint satisfaction problems. In: Proceedings of the 22nd international conference on tools with artificial intelligence (ICTAI-10), IEEEWalsh T (2002) Stochastic constraint programming. In: Proceedings of the 15th European conference on, artificial intelligence (ECAI-02), pp 111–115William F (2006) Topology and its applications. Wiley, New YorkWiner B (1971) Statistical principles in experimental design, 2nd edn. McGraw-Hill, New YorkYorke-Smith N, Gervet C (2009) Certainty closure: reliable constraint reasoning with incomplete or erroneous data. J ACM Trans Comput Log (TOCL) 10(1):
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