Detecting system failures from durations and binary cues

Durations are often used to judge the status of an invisible process. However, the apparent duration of an interval depends on the actual duration and on other variables, such as the workload during the interval and the person's expectations. An experiment dealt with the use of durations as an information source on the state of an invisible process and the effects of expectations and workload on decisions regarding the process. Eighty-nine participants observed a computerized simulation of a process which could be either intact or faulty, with intact processes ending on average sooner than faulty ones, and they had to indicate whether or not the process is intact and to estimate its duration. A binary cue with either intermediate or no validity indicated whether the process was supposedly intact or not, generating expectations about the duration of the process. Perceived durations and the decisions about the intactness of a process depended on the actual process duration, as well as on the expectations generated by the binary cue. In addition, task workload affected time estimates, but it had no effect on participants' tendency to adhere to cue recommendations or their ability to distinguish between intact and faulty processes. Results show that users' duration-based decisions about the status of a computerized process are affected by internal and external cues. While users can use durations as an information source, they should, whenever possible, be accompanied by additional indicators, lowering the inherent uncertainty in the duration estimation process.     

A scalable lock-free stack algorithm

The literature describes two high performance concurrent stack algorithms based on combining funnels and elimination trees. Unfortunately, the funnels are linearizable but blocking, and the elimination trees are non-blocking but not linearizable. Neither is used in practice since they perform well only at exceptionally high loads. The literature also describes a simple lock-free linearizable stack algorithm that works at low loads but does not scale as the load increases. The question of designing a stack algorithm that is non-blocking, linearizable, and scales well throughout the concurrency range, has thus remained open.     

Vortex-Loops and Phase Nucleation in Superfluid 4He and 3He

We propose a new model for the nature of the nucleation of solid from the superfluid phases of ⁴ He and ³ He. A fast solidification event in the superfluid results in a local release of pressure and a velocity field in the superfluid. This in turn facilitates the nucleation of vortex-loops. The kinetic energy gain of this process balances the surface tension, as the solid surface is quickly covered by many vortex-loops (hairy snow-ball). We show that this scenario gives good agreement with experiments on heterogeneous nucleation.     

Self‐Assembly of DNA Origami Heterodimers in High Yields and Analysis of the Involved Mechanisms

Efficient fabrication of structurally and functionally diverse nanomolecular devices and machines by organizing separately prepared DNA origami building blocks into a larger structure is limited by origami attachment yields. A general method that enables attachment of origami building blocks using ‘sticky ends' at very high yields is demonstrated. Two different rectangular origami monomers are purified using agarose gel electrophoresis conducted in solute containing 100 × 10^?3 m NaCl, a treatment that facilitates the dissociation of most of the incorrectly hybridized origami structures that form through blunt‐end interactions during the thermal annealing process and removes these structures as well as excess strands that otherwise interfere with the desired heterodimerization reaction. Heterodimerization yields of gel‐purified monomers are between 98.6% and 99.6%, considerably higher than that of monomers purified using the polyethylene glycol (PEG) method (88.7–96.7%). Depending on the number of PEG purification rounds, these results correspond to about 4‐ to 25‐fold reduction in the number of incorrect structures observed by atomic force microscopy. Furthermore, the analyses of the incorrect structures observed before and after the heterodimerization reactions and comparison of the purification methods provide valuable information on the reaction mechanisms that interfere with heterodimerization.     

Preference-based learning to rank

This paper presents an efficient preference-based ranking algorithm running in two stages. In the first stage, the algorithm learns a preference function defined over pairs, as in a standard binary classification problem. In the second stage, it makes use of that preference function to produce an accurate ranking, thereby reducing the learning problem of ranking to binary classification. This reduction is based on the familiar QuickSort and guarantees an expected pairwise misranking loss of at most twice that of the binary classifier derived in the first stage. Furthermore, in the important special case of bipartite ranking, the factor of two in loss is reduced to one. This improved bound also applies to the regret achieved by our ranking and that of the binary classifier obtained. Our algorithm is randomized, but we prove a lower bound for any deterministic reduction of ranking to binary classification showing that randomization is necessary to achieve our guarantees. This, and a recent result by Balcan et al., who show a regret bound of two for a deterministic algorithm in the bipartite case, suggest a trade-off between achieving low regret and determinism in this context. Our reduction also admits an improved running time guarantee with respect to that deterministic algorithm. In particular, the number of calls to the preference function in the reduction is improved from Ω(n ²) to O(nlog?n). In addition, when the top k ranked elements only are required (k?n), as in many applications in information extraction or search engine design, the time complexity of our algorithm can be further reduced to O(klog?k+n). Our algorithm is thus practical for realistic applications where the number of points to rank exceeds several thousand.     

Randomization adaptive self-stabilization

We present a scheme to convert self-stabilizing algorithms that use randomization during and following convergence to self-stabilizing algorithms that use randomization only during convergence. We thus reduce the number of random bits from an infinite number to an expected bounded number. The scheme is applicable to the cases in which there exits a local predicate for each node, such that global consistency is implied by the union of the local predicates. We demonstrate our scheme over the token circulation algorithm of Herman (Infor Process Lett 35:63–67, 1990) and the recent constant time Byzantine self-stabilizing clock synchronization algorithm by Ben-Or, Dolev and Hoch (Proceedings of the 27th Annual ACM SIGACT-SIGOPS symposium on principles of distributed computing, (PODC), 2008). The application of our scheme results in the first constant time Byzantine self-stabilizing clock synchronization algorithm that eventually stops using random bits.     

On the Discrete Maximum Principle for the Beltrami Color Flow

We analyze the discrete maximum principle for the Beltrami color flow. The Beltrami flow can display linear as well as nonlinear behavior according to the values of a parameter β, which represents the ratio between spatial and color distances. In general, the standard schemes fail to satisfy the discrete maximum principle. In this work we show that a nonnegative second order difference scheme can be built for this flow only for small β, i.e. linear-like diffusion. Since this limitation is too severe, we construct a novel finite difference scheme, which is not nonnegative and satisfies the discrete maximum principle for all values of β. Numerical results support the analysis.

Solo-valency and the cost of coordination

This paper introduces solo-valency, a variation on the valency proof technique originated by Fischer, Lynch, and Paterson. The new technique focuses on critical events that influence the responses of solo runs by individual operations, rather than on critical events that influence a protocol’s single decision value. It allows us to derive lower bounds on the time to perform an operation for lock-free implementations of concurrent objects such as linearizable queues, stacks, sets, hash tables, counters, approximate agreement, and more. Time is measured as the number of distinct base objects accessed and the number of stalls caused by contention in accessing memory, incurred by a process as it performs a single operation. We introduce the influence level metric that quantifies the extent to which the response of a solo execution of one process can be changed by other processes. We then prove the existence of a relationship between the space complexity, latency, contention and influence level of all lock-free object implementations. Our results are broad in that they hold for implementations that may use any collection of read-modify-write operations in addition to read and write, and in that they apply even if base objects have unbounded size. Part of this work was done while the first author was a graduate student in the Department of Computer Science, Tel-Aviv University. This work was supported in part by a grant from Sun Microsystems.     

Property-Preserving Data Reconstruction

We initiate a new line of investigation into online property-preserving data reconstruction. Consider a dataset which is assumed to satisfy various (known) structural properties; e.g., it may consist of sorted numbers, or points on a manifold, or vectors in a polyhedral cone, or codewords from an error-correcting code. Because of noise and errors, however, an (unknown) fraction of the data is deemed unsound, i.e., in violation with the expected structural properties. Can one still query into the dataset in an online fashion and be provided data that is always sound? In other words, can one design a filter which, when given a query to any item I in the dataset, returns a sound item J that, although not necessarily in the dataset, differs from I as infrequently as possible. No preprocessing should be allowed and queries should be answered online.We consider the case of a monotone function. Specifically, the dataset encodes a function f:{1,…,n}?? R that is at (unknown) distance ε from monotone, meaning that f can—and must—be modified at ε n places to become monotone.Our main result is a randomized filter that can answer any query in O(log?² nlog? log?n) time while modifying the function f at only O(ε n) places. The amortized time over n function evaluations is O(log?n). The filter works as stated with probability arbitrarily close to 1. We provide an alternative filter with O(log?n) worst case query time and O(ε nlog?n) function modifications. For reconstructing d-dimensional monotone functions of the form f:{1,…,n} ^d ? ? R, we present a filter that takes (2 ^O(d)(log?n)^4d?2log?log?n) time per query and modifies at most O(ε n ^d ) function values (for constant d).     

Shape-Based Mutual Segmentation

We present a novel variational approach for simultaneous segmentation of two images of the same object taken from different viewpoints. Due to noise, clutter and occlusions, neither of the images contains sufficient information for correct object-background partitioning. The evolving object contour in each image provides a dynamic prior for the segmentation of the other object view. We call this process mutual segmentation. The foundation of the proposed method is a unified level-set framework for region and edge based segmentation, associated with a shape similarity term. The suggested shape term incorporates the semantic knowledge gained in the segmentation process of the image pair, accounting for excess or deficient parts in the estimated object shape. Transformations, including planar projectivities, between the object views are accommodated by a registration process held concurrently with the segmentation. The proposed segmentation algorithm is demonstrated on a variety of image pairs. The homography between each of the image pairs is estimated and its accuracy is evaluated.