Thermal reactions between aluminum and palladium layered films

Phase formation and reaction during annealing in thin film couples of aluminum and palladium were studied by transmission electron microscopy, X-ray diffraction and Auger depth profiling techniques in the temperature range 200– 500°C. The known bulk phases of Al₃Pd₂, AlPd, Al₃Pd₅ and AlPd₂ were confirmed and two additional aluminum-rich phases were tentatively identified as Al₃Pd and Al₄Pd. In all the samples studied the reactions were initiated by the formation of the β-AlPd phase, which was then followed by the formation of the Al₃Pd₂ phase. Subsequent reactions caused precipitation of AlPd₂ particles if unreacted palladium was present, otherwise Al₄Pd particles were precipitated. The reaction rate was usually reduced if single-crystal, instead of polycrystalline, palladium film was used.     

Lattice-based certificateless public-key encryption in the standard model

The notion of certificateless public-key encryption (CL-PKE) was introduced by Al-Riyami and Paterson in 2003 that avoids the drawbacks of both traditional PKI-based public-key encryption (i.e., establishing public-key infrastructure) and identity-based encryption (i.e., key escrow). So CL-PKE like identity-based encryption is certificate-free, and unlike identity-based encryption is key escrow-free. In this paper, we introduce simple and efficient CCA-secure CL-PKE based on (hierarchical) identity-based encryption. Our construction has both theoretical and practical interests. First, our generic transformation gives a new way of constructing CCA-secure CL-PKE. Second, instantiating our transformation using lattice-based primitives results in a more efficient CCA-secure CL-PKE than its counterpart introduced by Dent in 2008.     

3D SLAM from stereoimages

A method of visual navigation by stereoimages for autonomous underwater vehicles is suggested. Two modifications of the method are considered. The first one is based on integration of measurement data of onboard navigation system with visual data. The second modification relies on the use of a six-cloud computation scheme. Results of computational experiments with model data are presented.     

Efficient algorithms for minimum-cost flow problems with piecewise-linear convex costs

We present two efficient algorithms for the minimum-cost flow problem in which arc costs are piecewise-linear and convex. Our algorithms are based on novel algorithms of Orlin, which were developed for the case of linear arc costs. Our first algorithm uses the Edmonds-Karp scaling technique. Its complexity isO(M logU(m+n logM)) for a network withn vertices,m arcs, M linear cost segments, and an upper boundU on the supplies and the capacities. The second algorithm is a strongly polynomial version of the first, and it uses Tardos's idea of contraction. Its complexity isO(M logM(m+n logM)). Both algorithms improve by a factor of at leastM/m the complexity of directly applying existing algorithms to a transformed network in which arc costs are linear.The final stage of this work was performed while Ron Shamir was a visitor at DIMACS (Center for Discrete Mathematics and Theoretical Computer Science), Rutgers University. Supported in part by National Science Foundation Grant NSF-STC88-09648, and by Air Force Grants AFOSR-89-0512 and AFOSR-90-0008.     

Complete forward displacement solutions for a class of three-branch parallel manipulators

Forward displacement solutions are presented for a class of spatial parallel manipulators. In particular, considered are manipulators consisting of a platform supported through passive spherical joints by three branches, each branch having three-revolute joints forming its main arm. Solutions are described for arbitrary main-arm layouts and for all possible cases of redundant (nine, eight, and seven sensors) and non-redundant (six sensors) sensing of branch main-arm joint displacements. It is demonstrated that closed-form forward displacement solutions can be found for all cases of redundant sensing. Furthermore, it is shown that a closed-form solution can be obtained for one of the two possible cases of non-redundant sensing of the main-arm joint displacements. The only case of joint displacement sensing not allowing a closed-form forward displacement solution is two joints sensed per branch, a case that can be expressed as a 16th-order polynomial of a single variable. Due to the importance of having efficient and failure-safe solutions for the forward displacement problem, it is suggested that appropriate redundancy in displacement sensing should be an important consideration in the design of parallel manipulation devices. © 1994 John Wiley & Sons, Inc.     

Algorithmic stability and sanity-check bounds for leave-one-out cross-validation.

In this article we prove sanity-check bounds for the error of the leave-one-out cross-validation estimate of the generalization error: that is, bounds showing that the worst-case error of this estimate is not much worse than that of the training error estimate. The name sanity check refers to the fact that although we often expect the leave-one-out estimate to perform considerably better than the training error estimate, we are here only seeking assurance that its performance will not be considerably worse. Perhaps surprisingly, such assurance has been given only for limited cases in the prior literature on cross-validation. Any nontrivial bound on the error of leave-one-out must rely on some notion of algorithmic stability. Previous bounds relied on the rather strong notion of hypothesis stability, whose application was primarily limited to nearest-neighbor and other local algorithms. Here we introduce the new and weaker notion of error stability and apply it to obtain sanity-check bounds for leave-one-out for other classes of learning algorithms, including training error minimization procedures and Bayesian algorithms. We also provide lower bounds demonstrating the necessity of some form of error stability for proving bounds on the error of the leave-one-out estimate, and the fact that for training error minimization algorithms, in the worst case such bounds must still depend on the Vapnik-Chervonenkis dimension of the hypothesis class.     

Competitive analysis of incentive compatible on-line auctions

This paper studies auctions in a setting where the different bidders arrive at different times and the auction mechanism is required to make decisions about each bid as it is received. Such settings occur in computerized auctions of computational resources as well as in other settings. We call such auctions, on-line auctions.

We first characterize exactly on-line auctions that are incentive compatible, i.e. where rational bidders are always motivated to bid their true valuation. We then embark on a competitive worst-case analysis of incentive compatible on-line auctions. We obtain several results, the cleanest of which is an incentive compatible on-line auction for a large number of identical items. This auction has an optimal competitive ratio, both in terms of seller's revenue and in terms of the total social efficiency obtained.     

Why is a computational framework for motivational and metacognitive control needed?

This paper discusses, in the context of computational modelling and simulation of cognition, the relevance of deeper structures in the control of behaviour. Such deeper structures include motivational control of behaviour, which provides underlying causes for actions, and also metacognitive control, which provides higher-order processes for monitoring and regulation. It is argued that such deeper structures are important and thus cannot be ignored in computational cognitive architectures. A general framework based on the Clarion cognitive architecture is outlined that emphasises the interaction amongst action selection, motivation, and metacognition. The upshot is that it is necessary to incorporate all essential processes; short of that, the understanding of cognition can only be incomplete.