Compilation and Equivalence of Imperative Objects (Revised Report)

We adopt the untyped imperative object calculus of Abadi andCardelli as a minimal setting in which to study problems of compilationand program equivalence that arise when compiling object orientedlanguages. We present both a big-step and a small-stepsubstitution-based operational semantics for the calculus. Our firsttwo results are theorems asserting the equivalence of our substitution based semantics with a closure-based semantics like that given by Abadi and Cardelli. Our third result is a direct proof of the correctness of compilation to a stack-based abstract machine via a small-step decompilation algorithm. Our fourth result is that contextual equivalence of objects coincides with a form of Mason and Talcott's CIUequivalence; the latter provides a tractable means of establishing operational equivalences. Finally, we prove correct an algorithm, used inour prototype compiler, for statically resolving method offsets. This isthe first study of correctness of an object-oriented abstract machine,and of operational equivalence for the imperative object calculus

Using machine learning to infer reasoning provenance from user interaction log data: based on the data/frame theory of sensemaking

The reconstruction of analysts’ reasoning processes (reasoning provenance) during complex sensemaking tasks can support reflection and decision making. One potential approach to such reconstruction is to automatically infer reasoning from low-level user interaction logs. We explore a novel method for doing this using machine learning. Two user studies were conducted in which participants performed similar intelligence analysis tasks. In one study, participants used a standard web browser and word processor; in the other, they used a system called INVISQUE (Interactive Visual Search and Query Environment). Interaction logs were manually coded for cognitive actions based on captured think-aloud protocol and posttask interviews based on Klein, Phillips, Rall, and Pelusos’s data/frame model of sensemaking as a conceptual framework. This analysis was then used to train an interaction frame mapper, which employed multiple machine learning models to learn relationships between the interaction logs and the codings. Our results show that, for one study at least, classification accuracy was significantly better than chance and compared reasonably to a reported manual provenance reconstruction method. We discuss our results in terms of variations in feature sets from the two studies and what this means for the development of the method for provenance capture and the evaluation of sensemaking systems

Casimir micro-sphere diclusters and three-body effects in fluids

Our previous article [Phys. Rev. Lett. 104, 060401 (2010)] predicted that Casimir forces induced by the material-dispersion properties of certain dielectrics can give rise to stable configurations of objects. This phenomenon was illustrated via a dicluster configuration of non-touching objects consisting of two spheres immersed in a fluid and suspended against gravity above a plate. Here, we examine these predictions from the perspective of a practical experiment and consider the influence of non-additive, three-body, and nonzero-temperature effects on the stability of the two spheres. We conclude that the presence of Brownian motion reduces the set of experimentally realizable silicon/teflon spherical diclusters to those consisting of layered micro-spheres, such as the hollow- core (spherical shells) considered here.Comment: 11 pages, 9 figure

Game theory meets information security management

Part 1: Intrusion DetectionInternational audienceThis work addresses the challenge “how do we make better security decisions?” and it develops techniques to support human decision making and algorithms which enable well-founded cyber security decisions to be made. In this paper we propose a game theoretic model which optimally allocates cyber security resources such as administrators’ time across different tasks. We first model the interactions between an omnipresent attacker and a team of system administrators seen as the defender, and we have derived the mixed Nash Equilibria (NE) in such games. We have formulated general-sum games that represent our cyber security environment, and we have proven that the defender’s Nash strategy is also minimax. This result guarantees that independently from the attacker’s strategy the defender’s solution is optimal. We also propose Singular Value Decomposition (SVD) as an efficient technique to compute approximate equilibria in our games. By implementing and evaluating a minimax solver with SVD, we have thoroughly investigated the improvement that Nash defense introduces compared to other strategies chosen by common sense decision algorithms. Our key finding is that a particular NE, which we call weighted NE, provides the most effective defense strategy. In order to validate this model we have used real-life statistics from Hackmageddon, the Verizon 2013 Data Breach Investigation report, and the Ponemon report of 2011. We finally compare the game theoretic defense method with a method which implements a stochastic optimization algorithm

Differential exposure and reactivity to interpersonal stress predict sex differences in adolescent depression

This study tested the hypothesis that higher rates of depression in adolescent girls are explained by their greater exposure and reactivity to stress in the interpersonal domain in a large sample of 15-year-olds. Findings indicate that adolescent girls experienced higher levels of total and interpersonal episodic stress, whereas boys experienced higher levels of chronic stress (academic and close friendship domains). Higher rates of depression in girls were explained by their greater exposure to total stress, particularly interpersonal episodic stress. Adolescent girls were also more reactive (more likely to become depressed) to both total and interpersonal episodic stress. The findings suggest that girls experience higher levels of episodic stress and are more reactive to these stressors, increasing their likelihood of becoming depressed compared to boys. Results were discussed in terms of girls' greater interpersonal focus and implications for understanding sex differences in depression

Enhanced empirical data for the fundamental diagram and the flow through bottlenecks

In recent years, several approaches for modelling pedestrian dynamics have been proposed and applied e.g. for design of egress routes. However, so far not much attention has been paid to their 'quantitative' validation. This unsatisfactory situation belongs amongst others on the uncertain and contradictory experimental data base. The fundamental diagram, i.e. the density-dependence of the flow or velocity, is probably the most important relation as it connects the basic parameter to describe the dynamic of crowds. But specifications in different handbooks as well as experimental measurements differ considerably. The same is true for the bottleneck flow. After a comprehensive review of the experimental data base we give an survey of a research project, including experiments with up to 250 persons performed under well controlled laboratory conditions. The trajectories of each person are measured in high precision to analyze the fundamental diagram and the flow through bottlenecks. The trajectories allow to study how the way of measurement influences the resulting relations. Surprisingly we found large deviation amongst the methods. These may be responsible for the deviation in the literature mentioned above. The results are of particular importance for the comparison of experimental data gained in different contexts and for the validation of models.Comment: A contribution to: Pedestrian and Evacuation Dynamics 2008 (Springer) 12 pages, 7 figure