This study investigates the response of pre-stressed anchored excavation walls under dynamic and pseudo-static loadings. A finite difference numerical model was developed using FLAC2D, results were successfully validated against full-scale experimental data. Analyses performed on 10, 20-m-height stabilized excavated slopes with 60° to 90° inclination angle horizon represent an applicable variet...

We give a graph-theoretical model for off-line fault-tolerant scheduling of dataflow algorithms onto multiprocessor architectures with distributed memory. Our framework allows the modeling of both processor and communication channel failures of the “fail silent” type (either transient or permanent), and failure masking is achieved by replicating operations and data communications. We show that,...

Due to correlation coefficient matrix of initialized samples are not always positive definite, this paper presents the improved Latin Hypercube Sampling (LHS) methods with Evolutionary Algorithm (EA) to control correlation and handle power system probability analysis problem. To deal with the non-positive definite correlation matrix, an improved median Latin hypercube sampling with evolutionary...

Process variation is a major concern in the semiconductor industry today. Probabilistic statistical static timing analysis (SSTA), where random variables are used to represent arrival times, has been proposed as a method to address this challenge. However, there are a number of modeling and accuracy difficulties associated with probabilistic SSTA analysis and optimization methods, such as how t...

Probabilistic symmetric encryption have already been widely studied, from a theoretical point of view. Nevertheless, many applications require length-preserving encryption, to be patched at a minimal cost to include privacy without modifying the format (e.g. encrypted filesystems). In this paper, we thus consider the security notions for length-preserving, deterministic and symmetric encryption...

In this era, it is essential to know the customer’s necessity before they themselves. The Recommendation system a sub-class of machine learning which deals with user data offer relevant content or product based on their taste. This paper aims develop an integrated recommendation using statistical theory and methods. Therefore, conventional Item Based Collaborative filtering probabilistic approa...

In this work we continue the study of the Weyl asymptotics of the distribution of eigenvalues of non-self-adjoint (pseudo)differential operators with small random perturbations, by treating the case of multiplicative perturbations in arbitrary dimension. We were led to quite essential improvements of many of the probabilistic aspects. Résumé Dans ce travail nous continuons l’étude de l’asymptot...

Probabilistic Programming Languages (PPLs) allow users to encode statistical inference problems and automatically apply an algorithm solve them. Popular algorithms for PPLs, such as sequential Monte Carlo (SMC) Markov chain (MCMC), are built around checkpoints -- relevant events the during execution of a probabilistic program. Deciding location is, in current not done optimally. To this problem...