High Speed Blanking: An Experimental Method to Measure Induced Cutting Forces

Lien vers la version éditeur: http://link.springer.com/article/10.1007/s11340-013-9738-1A new blanking process that involves punch speed up to 10 ms −1 has obvious advantages in increased productivity. However, the inherent dynamics of such a process makes it difficult to develop a practical high speed punch press. The fracture phenomenon governing the blanking process has to be well understood to correctly design the machine support and the tooling. To observe this phenomenon at various controlled blanking speeds a specific experimental device has been developed. The goal is to measure accurately the shear blanking forces imposed on the specimen during blanking. In this paper a new method allowing the blanking forces to be measured and taking into account the proposed test configuration is explained. This technique has been used to determine the blanking forces experienced when forming C40 steel and quantifies the effect of process parameters such as punch die clearance, punch speed, and sheet metal thickness on the blanking force evolution

Budgeted Reinforcement Learning in Continuous State Space

A Budgeted Markov Decision Process (BMDP) is an extension of a Markov Decision Process to critical applications requiring safety constraints. It relies on a notion of risk implemented in the shape of a cost signal constrained to lie below an - adjustable - threshold. So far, BMDPs could only be solved in the case of finite state spaces with known dynamics. This work extends the state-of-the-art to continuous spaces environments and unknown dynamics. We show that the solution to a BMDP is a fixed point of a novel Budgeted Bellman Optimality operator. This observation allows us to introduce natural extensions of Deep Reinforcement Learning algorithms to address large-scale BMDPs. We validate our approach on two simulated applications: spoken dialogue and autonomous driving.Comment: N. Carrara and E. Leurent have equally contribute

The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices

There has been definite progress recently in proving the variational single-letter formula given by the heuristic replica method for various estimation problems. In particular, the replica formula for the mutual information in the case of noisy linear estimation with random i.i.d. matrices, a problem with applications ranging from compressed sensing to statistics, has been proven rigorously. In this contribution we go beyond the restrictive i.i.d. matrix assumption and discuss the formula proposed by Takeda, Uda, Kabashima and later by Tulino, Verdu, Caire and Shamai who used the replica method. Using the recently introduced adaptive interpolation method and random matrix theory, we prove this formula for a relevant large sub-class of rotationally invariant matrices.Comment: Presented at the 2018 IEEE International Symposium on Information Theory (ISIT

A Reasonably Gradual Type Theory

Gradualizing the Calculus of Inductive Constructions (CIC) involves dealing with subtle tensions between normalization, graduality, and conservativity with respect to CIC. Recently, GCIC has been proposed as a parametrized gradual type theory that admits three variants, each sacrificing one of these properties. For devising a gradual proof assistant based on CIC, normalization and conservativity with respect to CIC are key, but the tension with graduality needs to be addressed. Additionally, several challenges remain: (1) The presence of two wildcard terms at any type-the error and unknown terms-enables trivial proofs of any theorem, jeopardizing the use of a gradual type theory in a proof assistant; (2) Supporting general indexed inductive families, most prominently equality, is an open problem; (3) Theoretical accounts of gradual typing and graduality so far do not support handling type mismatches detected during reduction; (4) Precision and graduality are external notions not amenable to reasoning within a gradual type theory. All these issues manifest primally in CastCIC, the cast calculus used to define GCIC. In this work, we present an extension of CastCIC called GRIP. GRIP is a reasonably gradual type theory that addresses the issues above, featuring internal precision and general exception handling. GRIP features an impure (gradual) sort of types inhabited by errors and unknown terms, and a pure (non-gradual) sort of strict propositions for consistent reasoning about gradual terms. Internal precision supports reasoning about graduality within GRIP itself, for instance to characterize gradual exception-handling terms, and supports gradual subset types. We develop the metatheory of GRIP using a model formalized in Coq, and provide a prototype implementation of GRIP in Agda.Comment: 27pages + 2pages bibliograph

Implementação da criação dinâmica de tarefas na biblioteca MPI.NET

MPI is the most used standard for the development of parallel high-performance applications and the MPI-2 version supports dynamic creation of tasks. The MPI standard provides bindings only for C, Fortran and C++, but many works support it in many other programming languages. Among this works we can highlight the MPI.NET library for the .Net Framework. This library provides an API with higher levels of abstraction. It also has competitive performance. However, it does not provide dynamic task creation support. The aim of this work is to implement this support and study how this library will respond to it. In the end, our experiments support the conclusion that the main performance problem is at the tasks initialization.Keywords: parallel programming, high performance computing, MPI.MPI é o padrão mais utilizado para o desenvolvimento de aplicações paralelas de alto desempenho e sua versão MPI-2 oferece suporte à criação dinâmica de tarefas. A norma MPI provê especifi cações para Fortran, C e C++. Surgiram algumas tentativas de suportá-la em várias outras linguagens de programação. Dessas tentativas, pode-se destacar a biblioteca MPI.NET (para o Framework. Net), a qual demonstrou uma API com maiores níveis de abstração do que as Application Programming Interface (API’s) da norma, bem como desempenho competitivo em relação a MPI-C. No entanto, essa biblioteca possui uma lacuna: o suporte à criação dinâmica de tarefas. O objetivo deste trabalho é preencher esta lacuna, estudando a utilização da biblioteca MPI.NET para a criação e execução de aplicações paralelas que utilizem criação dinâmica de tarefas. Ao final, o estudo demonstra que o grande problema de desempenho está na inicialização das tarefas.Palavras-chave: programação paralela, processamento de alto desempenho, MPI

De « l’excellence » territoriale en général et en particulier. Les campus des métiers et des qualifications de l’action « Territoires d’innovation pédagogique »

Introduction Créé dans le cadre de la Loi d’orientation et de programmation pour la refondation de l’École de la République du 8 juillet 2013, le campus des métiers et des qualifications (CMQ) est un label qui, selon la définition du ministère de l’Éducation nationale, « permet d'identifier, sur un territoire donné, un réseau d'acteurs qui interviennent en partenariat pour développer une large gamme de formations professionnelles, technologiques et générales, relevant de l'enseignement second..

Budgeted Reinforcement Learning in Continuous State Space

International audienceA Budgeted Markov Decision Process (BMDP) is an extension of a Markov Decision Process to critical applications requiring safety constraints. It relies on a notion of risk implemented in the shape of a cost signal constrained to lie below an-adjustable-threshold. So far, BMDPs could only be solved in the case of finite state spaces with known dynamics. This work extends the state-of-the-art to continuous spaces environments and unknown dynamics. We show that the solution to a BMDP is a fixed point of a novel Budgeted Bellman Optimality operator. This observation allows us to introduce natural extensions of Deep Reinforcement Learning algorithms to address large-scale BMDPs. We validate our approach on two simulated applications: spoken dialogue and autonomous driving

The Multiverse: Logical Modularity for Proof Assistants

Proof assistants play a dual role as programming languages and logical systems. As programming languages, proof assistants offer standard modularity mechanisms such as first-class functions, type polymorphism and modules. As logical systems, however, modularity is lacking, and understandably so: incompatible reasoning principles-such as univalence and uniqueness of identity proofs-can indirectly lead to logical inconsistency when used in a given development, even when they appear to be confined to different modules. The lack of logical modularity in proof assistants also hinders the adoption of richer programming constructs, such as effects. We propose the multiverse, a general type-theoretic approach to endow proof assistants with logical modularity. The multiverse consists of multiple universe hierarchies that statically describe the reasoning principles and effects available to define a term at a given type. We identify sufficient conditions for this structuring to modularly ensure that incompatible principles do not interfere, and to locally restrict the power of dependent elimination when necessary. This extensible approach generalizes the ad-hoc treatment of the sort of propositions in the Coq proof assistant. We illustrate the power of the multiverse by describing the inclusion of Coq-style propositions, the strict propositions of Gilbert et al., the exceptional type theory of Pédrot and Tabareau, and general axiomatic extensions of the logic

The Multiverse: Logical Modularity for Proof Assistants

Proof assistants play a dual role as programming languages and logical systems. As programming languages, proof assistants offer standard modularity mechanisms such as first-class functions, type polymorphism and modules. As logical systems, however, modularity is lacking, and understandably so: incompatible reasoning principles-such as univalence and uniqueness of identity proofs-can indirectly lead to logical inconsistency when used in a given development, even when they appear to be confined to different modules. The lack of logical modularity in proof assistants also hinders the adoption of richer programming constructs, such as effects. We propose the multiverse, a general type-theoretic approach to endow proof assistants with logical modularity. The multiverse consists of multiple universe hierarchies that statically describe the reasoning principles and effects available to define a term at a given type. We identify sufficient conditions for this structuring to modularly ensure that incompatible principles do not interfere, and to locally restrict the power of dependent elimination when necessary. This extensible approach generalizes the ad-hoc treatment of the sort of propositions in the Coq proof assistant. We illustrate the power of the multiverse by describing the inclusion of Coq-style propositions, the strict propositions of Gilbert et al., the exceptional type theory of Pédrot and Tabareau, and general axiomatic extensions of the logic