M-Fivebrane from the Open Supermembrane

Covariant field equations of M-fivebrane in eleven dimensional curved superspace are obtained from the requirement of kappa-symmetry of an open supermembrane ending on a fivebrane. The worldvolume of the latter is a (6|16) dimensional supermanifold embedded in the (11|32) dimensional target superspace. The kappa-symmetry of the system imposes a constraint on this embedding, and a constraint on a modified super 3-form field strength on the fivebrane worldvolume. These constraints govern the dynamics of the M-fivebrane.Comment: 11 pages, Latex, references and appendix adde

Executive Orders: Issuance, Modification, and Revocation

Executive orders, presidential memoranda, and proclamations are used extensively by Presidents to achieve policy goals, set uniform standards for managing the executive branch, or outline a policy view intended to influence the behavior of private citizens. The U.S. Constitution does not define these presidential instruments and does not explicitly vest the President with the authority to issue them. Nonetheless, such orders are accepted as an inherent aspect of presidential power. Moreover, if they are based on appropriate authority, they have the force and effect of law. This report discusses the nature of these written instruments, executive orders in particular, with a focus on the scope of presidential authority to execute such instruments, as well as judicial and congressional responses to their issuance

A new evolutionary search strategy for global optimization of high-dimensional problems

Global optimization of high-dimensional problems in practical applications remains a major challenge to the research community of evolutionary computation. The weakness of randomization-based evolutionary algorithms in searching high-dimensional spaces is demonstrated in this paper. A new strategy, SP-UCI is developed to treat complexity caused by high dimensionalities. This strategy features a slope-based searching kernel and a scheme of maintaining the particle population's capability of searching over the full search space. Examinations of this strategy on a suite of sophisticated composition benchmark functions demonstrate that SP-UCI surpasses two popular algorithms, particle swarm optimizer (PSO) and differential evolution (DE), on high-dimensional problems. Experimental results also corroborate the argument that, in high-dimensional optimization, only problems with well-formative fitness landscapes are solvable, and slope-based schemes are preferable to randomization-based ones. © 2011 Elsevier Inc. All rights reserved

TiFi: Taxonomy Induction for Fictional Domains [Extended version]

Taxonomies are important building blocks of structured knowledge bases, and their construction from text sources and Wikipedia has received much attention. In this paper we focus on the construction of taxonomies for fictional domains, using noisy category systems from fan wikis or text extraction as input. Such fictional domains are archetypes of entity universes that are poorly covered by Wikipedia, such as also enterprise-specific knowledge bases or highly specialized verticals. Our fiction-targeted approach, called TiFi, consists of three phases: (i) category cleaning, by identifying candidate categories that truly represent classes in the domain of interest, (ii) edge cleaning, by selecting subcategory relationships that correspond to class subsumption, and (iii) top-level construction, by mapping classes onto a subset of high-level WordNet categories. A comprehensive evaluation shows that TiFi is able to construct taxonomies for a diverse range of fictional domains such as Lord of the Rings, The Simpsons or Greek Mythology with very high precision and that it outperforms state-of-the-art baselines for taxonomy induction by a substantial margin

A solution to the crucial problem of population degeneration in high-dimensional evolutionary optimization

Three popular evolutionary optimization algorithms are tested on high-dimensional benchmark functions. An important phenomenon responsible for many failures - population degeneration - is discovered. That is, through evolution, the population of searching particles degenerates into a subspace of the search space, and the global optimum is exclusive from the subspace. Subsequently, the search will tend to be confined to this subspace and eventually miss the global optimum. Principal components analysis (PCA) is introduced to discover population degeneration and to remedy its adverse effects. The experiment results reveal that an algorithm's efficacy and efficiency are closely related to the population degeneration phenomenon. Guidelines for improving evolutionary algorithms for high-dimensional global optimization are addressed. An application to highly nonlinear hydrological models demonstrates the efficacy of improved evolutionary algorithms in solving complex practical problems. © 2011 IEEE

Handling boundary constraints for particle swarm optimization in high-dimensional search space

Despite the fact that the popular particle swarm optimizer (PSO) is currently being extensively applied to many real-world problems that often have high-dimensional and complex fitness landscapes, the effects of boundary constraints on PSO have not attracted adequate attention in the literature. However, in accordance with the theoretical analysis in [11], our numerical experiments show that particles tend to fly outside of the boundary in the first few iterations at a very high probability in high-dimensional search spaces. Consequently, the method used to handle boundary violations is critical to the performance of PSO. In this study, we reveal that the widely used random and absorbing bound-handling schemes may paralyze PSO for high-dimensional and complex problems. We also explore in detail the distinct mechanisms responsible for the failures of these two bound-handling schemes. Finally, we suggest that using high-dimensional and complex benchmark functions, such as the composition functions in [19], is a prerequisite to identifying the potential problems in applying PSO to many real-world applications because certain properties of standard benchmark functions make problems inexplicit. © 2011 Elsevier Inc. All rights reserved

Local Commutativity and Causality in Interacting PP-wave String Field Theory

In this paper, we extend our previous study of causality and local commutativity of string fields in the pp-wave lightcone string field theory to include interaction. Contrary to the flat space case result of Lowe, Polchinski, Susskind, Thorlacius and Uglum, we found that the pp-wave interaction does not affect the local commutativity condition. Our results show that the pp-wave lightcone string field theory is not continuously connected with the flat space one. We also discuss the relation between the condition of local commutativity and causality. While the two notions are closely related in a point particle theory, their relation is less clear in string theory. We suggest that string local commutativity may be relevant for an operational defintion of causality using strings as probes.Comment: Latex, JHEP3.cls, 18 pages, no figures. v2: add comments about the UV-IR mixing effect displayed in our result. version to appear in JHE