Joint parameter identification is a key problem in the modeling of assembled complex structural. Dynamic behavior of mechanical joints may be with random feature due to the stochastic properties of preload, joint geometry, contact surface and its finishes, etc. A procedure for stochastic mechanical joint identification based on a novel model updating technique combined with probabilistic approa...

A procedure is developed for identification of probabilistic system uncertainty regions for a linear time-invariant system with unknown dynamics, on the basis of time sequences of input and output data. The classical framework is handled in which the system output is contaminated by a realization of a stationary stochastic process. Given minor and verifiable prior information on the system and ...

Managing and controlling knowledge intensive dynamic systems requires being able to estimate, analyze, and evaluate, under conditions of uncertainty, the existing system and the impact of actions, such as changes in personnel or resources on this system. Our approach to this problem is dynamic network analysis. Using a combination of statistical and simulation tools, we analyze the robustness u...

We study the identification capacity of classical-quantum channels (“cq-channels”), under channel uncertainty and privacy constraints. To be precise, we consider first compound memoryless cq-channels and determine their identification capacity; then we add an eavesdropper, considering compound memoryless wiretap cqq-channels, and determine their secret identification capacity. In the first case...

The efficiency of the automatic execution of complex assembly tasks can be enhanced by the identification of the contact state. In this paper we derive a new method for testing a hypothesized contact state using force sensing in the presence of sensing and control uncertainty. The hypothesized contact state is represented as a collection of elementary contacts. The feasibility of the elementary...

This work deals with the problem of identification of Discrete Possibilistic Dynamic System (DPDS), using the technologies of Genetic Algorithmms (GA). Applying the results from [5-9,11-13,15,16,18-20], the fuzzy recurrent process with possibilistic uncertainty, the source of which is expert knowledge reflections on the states of evolutionary complex extremal system, is constructed. The dynamic...

Some of the most robust effects of linguistic variables on eye movements in reading are those of word length. Their leading explanation states that they are caused by visual acuity limitations on word recognition. However, Bicknell (2011) presented data showing that a model of eye movement control in reading that includes visual acuity limitations and models the process of word identification f...

The expected improvement (EI) algorithm is a popular strategy for information collection in optimization under uncertainty. The algorithm is widely known to be too greedy, but nevertheless enjoys wide use due to its simplicity and ability to handle uncertainty and noise in a coherent decision theoretic framework. To provide rigorous insight into EI, we study its properties in a simple setting o...

This study tried to examine EFL translators’ uncertainty and uncertainty management strategies through employing think aloud procedures. The participants of this study were some MA andBA translators selected from several universities in Iran. To this aim, a proficiency test was firstly administered among the volunteers. Then, think aloud protocol and retrospective interview were used to collect...