24,356 research outputs found
Simplifying Contract-Violating Traces
Contract conformance is hard to determine statically, prior to the deployment
of large pieces of software. A scalable alternative is to monitor for contract
violations post-deployment: once a violation is detected, the trace
characterising the offending execution is analysed to pinpoint the source of
the offence. A major drawback with this technique is that, often, contract
violations take time to surface, resulting in long traces that are hard to
analyse. This paper proposes a methodology together with an accompanying tool
for simplifying traces and assisting contract-violation debugging.Comment: In Proceedings FLACOS 2012, arXiv:1209.169
Boundary interpolation for slice hyperholomorphic Schur functions
A boundary Nevanlinna-Pick interpolation problem is posed and solved in the
quaternionic setting. Given nonnegative real numbers , quaternions all of modulus , so that the
-spheres determined by each point do not intersect and for , and quaternions , we wish to find a slice
hyperholomorphic Schur function so that and
Our arguments relies on the theory of slice hyperholomorphic
functions and reproducing kernel Hilbert spaces
Nanofriction behavior of cluster-assembled carbon films
We have characterized the frictional properties of nanostructured (ns) carbon
films grown by Supersonic Cluster Beam Deposition (SCBD) via an Atomic
Force-Friction Force Microscope (AFM-FFM). The experimental data are discussed
on the basis of a modified Amonton's law for friction, stating a linear
dependence of friction on load plus an adhesive offset accounting for a finite
friction force in the limit of null total applied load. Molecular Dynamics
simulations of the interaction of the AFM tip with the nanostructured carbon
confirm the validity of the friction model used for this system. Experimental
results show that the friction coefficient is not influenced by the
nanostructure of the films nor by the relative humidity. On the other hand the
adhesion coefficient depends on these parameters.Comment: 22 pages, 6 figures, RevTex
RoboJam: A Musical Mixture Density Network for Collaborative Touchscreen Interaction
RoboJam is a machine-learning system for generating music that assists users
of a touchscreen music app by performing responses to their short
improvisations. This system uses a recurrent artificial neural network to
generate sequences of touchscreen interactions and absolute timings, rather
than high-level musical notes. To accomplish this, RoboJam's network uses a
mixture density layer to predict appropriate touch interaction locations in
space and time. In this paper, we describe the design and implementation of
RoboJam's network and how it has been integrated into a touchscreen music app.
A preliminary evaluation analyses the system in terms of training, musical
generation and user interaction
A new procedure to analyze RNA non-branching structures
RNA structure prediction and structural motifs analysis are challenging tasks in the investigation of RNA function. We propose a novel procedure to detect structural motifs shared between two RNAs (a reference and a target). In particular, we developed two core modules: (i) nbRSSP_extractor, to assign a unique structure to the reference RNA encoded by a set of non-branching structures; (ii) SSD_finder, to detect structural motifs that the target RNA shares with the reference, by means of a new score function that rewards the relative distance of the target non-branching structures compared to the reference ones. We integrated these algorithms with already existing software to reach a coherent pipeline able to perform the following two main tasks: prediction of RNA structures (integration of RNALfold and nbRSSP_extractor) and search for chains of matches (integration of Structator and SSD_finder)
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