A Self Supervised Convolutional Neural Network Outdoor Scene Relighting

Outdoor scene relighting is a difficult trouble that calls forexact know-how of the scene geometry, illumination and albedo. Currentstrategies are absolutely supervised, requiring excessive exceptional ar?tificial renderings to educate a answer. Such renderings are synthesizedthe usage of priors discovered from restrained facts. In contrast, we ad?vise a self-supervised technique for relighting. Our technique is educatedbest on corpora of pics accrued from the net with none user-supervision.This without a doubt infinite supply of education facts lets in educationa popular relighting answer. Our technique first decomposes an photointo its albedo, geometry and illumination. A novel relighting is thenproduced through enhancing the illumination parameters. Our answerseize shadow the usage of a committed shadow prediction map, and doesnow no longer depend on correct geometry estimation. We compare ourmethod subjectively and objectively the usage of a brand new datasetwith ground-reality relighting. Results display the capacity of our methodto provide photo-sensible and bodily achievable results, that generalizesto unseen scenes

A Hecke-equivariant decomposition of spaces of Drinfeld cusp forms via representation theory, and an investigation of its subfactors

There are various reasons why a naive analog of the Maeda conjecture has to fail for Drinfeld cusp forms. Focussing on double cusp forms and using the link found by Teitelbaum between Drinfeld cusp forms and certain harmonic cochains, we observed a while ago that all obvious counterexamples disappear for certain Hecke-invariant subquotients of spaces of Drinfeld cusp forms of fixed weight, which can be defined naturally via representation theory. The present work extends Teitelbaum’s isomorphism to an adelic setting and to arbitrary levels, it makes precise the impact of representation theory, it relates certain intertwining maps to hyperderivatives of Bosser-Pellarin, and it begins an investigation into dimension formulas for the subquotients mentioned above. We end with some numerical data for $$A={\mathbb {F}}_3[t]$$ A = F 3 [ t ] that displays a new obstruction to an analog of a Maeda conjecture by discovering a conjecturally infinite supply of $${\mathbb {F}}_3(t)$$ F 3 ( t ) -rational eigenforms with combinatorially given (conjectural) Hecke eigenvalues at the prime t.

Pornifying the Network

Watching pornography online is a deeply personal, if not secretive act, yet the ease with which a near-infinite supply of adult content is shored up by networks of shared experiences. In fact, the persistent assumption that consuming adult content is a ‘closed’ experience has largely stunted efforts to reconceptualize online pornography as a “network experience.” As Wendy Chun asks, “Why are networked devices described as ‘personal,’ when they are so chatty and promiscuous?” This article, therefore, attempts to ‘pornify the network’ by tracing the movement, flows, and processual emergence of networks that have been crucial to the formation and continued proliferation of online pornography. Two case studies are used to illustrate the persistence of this framework: the first theorizes ‘edging’ in early online pornography, while the second puts into question the politics of the world’s largest porn website deploying user data for titillating effect. Theorizing a pornified network ultimately reroutes persistent technological imaginaries of the network through affect, sensation, and the entanglements of desire.

Nonergodic Jackson networks with infinite supply–local stabilization and local equilibrium analysis

Classical Jackson networks are a well-established tool for the analysis of complex systems. In this paper we analyze Jackson networks with the additional features that (i) nodes may have an infinite supply of low priority work and (ii) nodes may be unstable in the sense that the queue length at these nodes grows beyond any bound. We provide the limiting distribution of the queue length distribution at stable nodes, which turns out to be of product form. A key step in establishing this result is the development of a new algorithm based on adjusted traffic equations for detecting unstable nodes. Our results complement the results known in the literature for the subcases of Jackson networks with either infinite supply nodes or unstable nodes by providing an analysis of the significantly more challenging case of networks with both types of nonstandard node present. Building on our product-form results, we provide closed-form solutions for common customer and system oriented performance measures.

Geometric auxetics

We formulate a mathematical theory of auxetic behaviour based on one-parameter deformations of periodic frameworks. Our approach is purely geome- tric, relies on the evolution of the periodicity lattice and works in any dimension. We demonstrate its usefulness by predicting or recognizing, without experiment, computer simulations or numerical approximations, the auxetic capabilities of several well-known structures available in the literature. We propose new principles of auxetic design and rely on the stronger notion of expansive behaviour to provide an infinite supply of planar auxetic mechanisms and several new three-dimensional structures.

STATIC STOCHASTIC KNAPSACK PROBLEMS

Two stochastic knapsack problem (SKP) models are considered: the static broken knapsack problem (BKP) and the SKP with simple recourse and penalty cost problem. For both models, we assume: the knapsack has a constant capacity; there are n types of items and each type has an infinite supply; a type i item has a deterministic reward vi and a random weight with known distribution Fi. Both models have the same objective to maximize expected total return by finding the optimal combination of items, that is, quantities of items of each type to be put in knapsack. The difference between the two models is: if knapsack is broken when total weights of items put in knapsack exceed the knapsack's capacity, for the static BKP model, all existing rewards would be wiped out, while for the latter model, we could still keep the existing rewards in knapsack but have to pay a fixed penalty plus a variant cost proportional to the overcapacity amount. This paper also discusses the special case when knapsack has an exponentially distributed capacity.