42482105
Logical Secrets
46718511
Capability-Based Financial Instruments
Every novel cooperative arrangement of mutually suspicious parties interacting electronically -- every smart contract -- effectively requires a new cryptographic protocol. However, if every new contract requires new cryptographic protocol design, our dreams of cryptographically enabled electronic commerce would be unreachable. Cryptographic protocol design is too hard and expensive, given our unlimited need for new contracts.Just as the digital logic gate abstraction allows digital circuit designers to create large analog circuits without doing analog circuit design, we present cryptographic capabilities as an abstraction allowing a similar economy of engineering effort in creating smart contracts. We explain the E system, which embodies these principles, and show a covered-call-option as a smart contract written in a simple security formalism independent of cryptography, but automatically implemented as a cryptographic protocol coordinating five mutually suspicious parties.
16608960
Objects in Concurrent Logic Programming Languages
Concurrent Prolog supports object-oriented programming with a clean semantics and additional programming constructs such as incomplete messages, unification, direct broadcasting, and concurrency synchronization [Shapiro 1983a]. While it provides excellent computational support, we claim it does not provide good notation for expressing the abstractions of object-oriented programming. We describe a preprocessor that remedies this problem. The resulting language, Vulcan, is then used as a behicle for exploring new variants of object-oriented programming which become possible in this framework.
40582600
Concurrency Among Strangers
Programmers write programs, expressing plans for machines to execute. When composed so that they may cooperate, plans may instead interfere with each other in unanticipated ways. Plan coordination is the art of simultaneously enabling plans to cooperate, while avoiding hazards of destructive plan interference. For sequential computation within a single machine, object programming supports plan coordination well. For concurrent computation, this paper shows how hard it is to use locking to prevent plans from interfering without also destroying their ability to cooperate.
1692281
A stochastic model for studying the laminar structure of cortex from MRI
The human cerebral cortex is a laminar structure about 3 mm thick, and is easily visualized with current magnetic resonance (MR) technology. The thickness of the cortex varies locally by region, and is likely to be influenced by such factors as development, disease and aging. Thus, accurate measurements of local cortical thickness are likely to be of interest to other researchers. We develop a parametric stochastic model relating the laminar structure of local regions of the cerebral cortex to MR image data. Parameters of the model include local thickness, and statistics describing white, gray and cerebrospinal fluid (CSF) image intensity values as a function of the normal distance from the center of a voxel to a local coordinate system anchored at the gray/white matter interface. Our fundamental data object, the intensity-distance histogram (IDH), is a two-dimensional (2-D) generalization of the conventional 1-D image intensity histogram, which indexes voxels not only by their intensity value, but also by their normal distance to the gray/white interface. We model the IDH empirically as a marked Poisson process with marking process a Gaussian random field model of image intensity indexed against normal distance. In this paper, we relate the parameters of the IDH model to the local geometry of the cortex. A maximum-likelihood framework estimates the parameters of the model from the data. Here, we show estimates of these parameters for 10 volumes in the posterior cingulate, and 6 volumes in the anterior and posterior banks of the central sulcus. The accuracy of the estimates is quantified via Cramer-Rao bounds. We believe that this relatively crude model can be extended in a straightforward fashion to other biologically and theoretically interesting problems such as segmentation, surface area estimation, and estimating the thickness distribution in a variety of biologically relevant contexts.
12989752
Asymptotic performance analysis of Bayesian target recognition
This article investigates the asymptotic performance of Bayesian target recognition algorithms using deformable-template representations. Rigid computer-aided design (CAD) models represent the underlying targets; low-dimensional matrix Lie-groups (rotation and translation) extend them to particular instances. Remote sensors observing the targets are modeled as projective transformations, converting three-dimensional scenes into random images. Bayesian target recognition corresponds to hypothesis selection in the presence of nuisance parameters; its performance is quantified as the Bayes' error. Analytical expressions for this error probability in small noise situations are derived, yielding asymptotic error rates for exponential error probability decay.
44565534
On the sum number of wheels
A graph G=(V,E) is a sum graph if there exists a labelling of the vertices of G with distinct positive integers so that uv∈E if and only if the sum of the labels assigned to u and v is the label of a vertex of G. The sum number of a graph is the minimum number of isolated vertices that, together with the given graph, form a sum graph. Sum graph labellings of wheels have been examined previously by other investigators. The sum number of an n spoked wheel, σ(Wn),n⩾5, has been found to be n when n is odd and n2+2 when n is even; however the proofs of these results are incomplete. In this paper we provide a complete proof and affirm that these previous results are correct.
10226081
A MAC protocol to reduce sensor network energy consumption using a wakeup radio
For increasing the life of sensor networks, each node must conserve energy as much as possible. In this paper, we propose a protocol in which energy is conserved by amortizing the energy cost of communication over multiple packets. In addition, we allow sensors to control the amount of buffered packets since storage space is limited. To achieve this, a two-radio architecture is used which allows a sensor to "wakeup" a neighbor with a busy tone and send its packets for that destination. However, this process is expensive because all neighbors must awake and listen to the primary channel to determine who is the intended destination. Therefore, triggered wakeups on the primary channel are proposed to avoid using the more costly wakeup procedure. We present a protocol for efficiently determining how large the period for these wakeups should be such that energy consumption is reduced.
15772070
Hilbert-Schmidt Lower Bounds for Estimators on Matrix Lie Groups for ATR
Deformable template representations of observed imagery model the variability of target pose via the actions of the matrix Lie groups on rigid templates. In this paper, we study the construction of minimum mean squared error estimators on the special orthogonal group, SO(n), for pose estimation. Due to the nonflat geometry of SO(n), the standard Bayesian formulation of optimal estimators and their characteristics requires modifications. By utilizing Hilbert-Schmidt metric defined on GL(n), a larger group containing SO(n), a mean squared criterion is defined on SO(n). The Hilbert-Schmidt estimate (HSE) is defined to be a minimum mean squared error estimator, restricted to SO(n). The expected error associated with the HSE is shown to be a lower bound, called the Hilbert-Schmidt bound (HSB), on the error incurred by any other estimator. Analysis and algorithms are presented for evaluating the HSE and the HSB in cases of both ground-based and airborne targets.