1,794 research outputs found
On Bayesian new edge prediction and anomaly detection in computer networks
Monitoring computer network traffic for anomalous behaviour presents an important security challenge. Arrivals of new edges in a network graph represent connections between a client and server pair not previously observed, and in rare cases these might suggest the presence of intruders or malicious implants. We propose a Bayesian model and anomaly detection method for simultaneously characterising existing network structure and modelling likely new edge formation. The method is demonstrated on real computer network authentication data and successfully identifies some machines which are known to be compromised
Latent structure blockmodels for Bayesian spectral graph clustering
Spectral embedding of network adjacency matrices often produces node representations living approximately around low-dimensional submanifold structures. In particular, hidden substructure is expected to arise when the graph is generated from a latent position model. Furthermore, the presence of communities within the network might generate community-specific submanifold structures in the embedding, but this is not explicitly accounted for in most statistical models for networks. In this article, a class of models called latent structure block models (LSBM) is proposed to address such scenarios, allowing for graph clustering when community-specific one dimensional manifold structure is present. LSBMs focus on a specific class of latent space model, the random dot product graph (RDPG), and assign a latent submanifold to the latent positions of each community. A Bayesian model for the embeddings arising from LSBMs is discussed, and shown to have a good performance on simulated and real world network data. The model is able to correctly recover the underlying communities living in a one-dimensional manifold, even when the parametric form of the underlying curves is unknown, achieving remarkable results on a variety of real data
Progress in Precursor Skills and Front Crawl Swimming in Children With and Without Developmental Coordination Disorder
This study investigated swimming performance and the influence of task complexity among children with and without Developmental Coordination Disorder (DCD). Two groups of children were matched by age - 11 controls without DCD and 11 children with DCD. Repeated measures ANOVA showed that children with DCD performed significantly lower level than age-matched controls for all the water competency tasks and front crawl. Both groups improved significantly in water competency and front crawl over 10 lessons. Significant interactions suggested that children with DCD showed different rates of change during the acquisition of the glide and front crawl. Both groups regressed with increased task complexity. Awareness of motor learning difficulties experienced by children enables teachers, parents, and children to have realistic expectations. A supportive environments for children with DCD will enable them to achieve the important swimming skill competencies and reduce drop-out rates in learn-to-swim programs
On conjectures of Hovey-Strickland and Chai
We prove the height two case of a conjecture of Hovey and Strickland that provides a -local analogue of the Hopkins--Smith thick subcategory theorem. Our approach first reduces the general conjecture to a problem in arithmetic geometry posed by Chai. We then use the Gross--Hopkins period map to verify Chai's Hope at height two and all primes. Along the way, we show that the graded commutative ring of completed cooperations for Morava -theory is coherent, and that every finitely generated Morava module can be realized by a -local spectrum as long as . Finally, we deduce consequences of our results for descent of Balmer spectra
On stratification for spaces with Noetherian mod cohomology
Let be a topological space with Noetherian mod cohomology and let be the commutative ring spectrum of -valued cochains on . The goal of this paper is to exhibit conditions under which the category of module spectra on is stratified in the sense of Benson, Iyengar, Krause, providing a classification of all its localizing subcategories. We establish stratification in this sense for classifying spaces of a large class of topological groups including Kac--Moody groups as well as whenever admits an -space structure. More generally, using Lannes' theory we prove that stratification for is equivalent to a condition that generalizes Chouinard's theorem for finite groups. In particular, this relates the generalized telescope conjecture in this setting to a question in unstable homotopy theory
Buckling tests of structural elements applicable to large erectable space trusses
Detailed data on columns and center a joint for completeness is presented. Buckling data for a tripod arrangement of these columns using a cluster joint is also presented. The objectives of these test are: (1) to gain insight into joint requirements for truss structure; (2) to assess the structural qualities of the column and center joint designs; (3) to investigate the restraint provided by octetruss core members (tripod) to the cluster joints; (4) to provide insight into the level of analysis required to predict buckling behavior of Gr/E nestable columns both as simple columns and in a tripod arrangement; and (5) to provide a data base for Gr/E nestable columns
New Langevin and Gradient Thermostats for Rigid Body Dynamics
We introduce two new thermostats, one of Langevin type and one of gradient
(Brownian) type, for rigid body dynamics. We formulate rotation using the
quaternion representation of angular coordinates; both thermostats preserve the
unit length of quaternions. The Langevin thermostat also ensures that the
conjugate angular momenta stay within the tangent space of the quaternion
coordinates, as required by the Hamiltonian dynamics of rigid bodies. We have
constructed three geometric numerical integrators for the Langevin thermostat
and one for the gradient thermostat. The numerical integrators reflect key
properties of the thermostats themselves. Namely, they all preserve the unit
length of quaternions, automatically, without the need of a projection onto the
unit sphere. The Langevin integrators also ensure that the angular momenta
remain within the tangent space of the quaternion coordinates. The Langevin
integrators are quasi-symplectic and of weak order two. The numerical method
for the gradient thermostat is of weak order one. Its construction exploits
ideas of Lie-group type integrators for differential equations on manifolds. We
numerically compare the discretization errors of the Langevin integrators, as
well as the efficiency of the gradient integrator compared to the Langevin ones
when used in the simulation of rigid TIP4P water model with smoothly truncated
electrostatic interactions. We observe that the gradient integrator is
computationally less efficient than the Langevin integrators. We also compare
the relative accuracy of the Langevin integrators in evaluating various static
quantities and give recommendations as to the choice of an appropriate
integrator.Comment: 16 pages, 4 figure
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