The rough neural networks (RNNs) are the neural networks based on rough set and one kind of hot research in the artificial intelligence in recent years, which synthesize the advantage of rough set to process uncertainly question: attributes reduce by none information losing then extract rule, and the neural networks have the strongly fault tolerance, self-organization, massively parallel proces...

An analogy between the thermodynamic inequalities presented by Nicholson et al. [Nat. Phys. 16, 1211 (2020)] and Yoshimura Ito [Phys. Rev. Res. 3, 013175 (2021)] is discussed. As a result, time–energy uncertainty relation in chemical thermodynamics terms of Gibbs free energy potential derived. It numerically demonstrated that uncertainly holds model system oscillatory Brusselator reactions. Our...

There are a variety of degradation models in the literature, each with certain effect random variation around mean path on time-to-failure device being degraded. To assess dependence that exerts resulting time-to-failure, this paper presents copula functions for time-to-failure-based respect to two well-known models, namely, multiplicative model and additive model. The implied case have explici...

Marshall et al. recently estimated population densities, range sizes, instant and cumulative total sizes for Tyrannosaurus rex with narrow ranges of uncertainly. I revisit the assumptions that led them to these conclusions show many parameters are associated much wider margins error than they estimated. Biogeographic estimates seem have been especially unrealistic, seriously hampering effort ca...

By creating a single market and introducing competition and the de facto global standard, GSM, the European Union (EU) achieved economies of scale and has been the world's leader in the mobile communications sector. A number of interrelated issues surrounding the third-generation (3G) system have recently become visible, however. The first indication is the high 3G spectrum license prices mobil...

Motivated by the widespread use of networked and/or embedded control systems, an algorithm for stabilizing sampled-data feedback control systems with uncertainly time-varying sampling intervals is proposed, where it is assumed that the sampled state is available for feedback. The algorithm is an extension of that for stability analysis in the authors’ previous study, and is based on the robustn...

None of the processing models in the software development has explained the software systems performance evaluation and modeling; likewise, there exist uncertainty in the information systems because of the natural essence of requirements and this may cause other challenges in the processing of software development. By definition an extended version of UML (Fuzzy-UML), the functional requirement...

Many works in the past showed that human judgments of uncertainty do not conform very well to Probability Theory. The present paper reports four experiments that were conducted in order to evaluate if human judgments of uncertainty conform better to Possibility Theory. At first, two experiments investigate the descriptive properties of some basic possibilistic measures. Then a new measurement a...

Building a robust and effective human-agent team is difficult, as teams can fail for many reasons. In this study, we investigated the performance of human-agent teams with divisional and functional team structure under different level of task load uncertainty. Divisional teams show robustness against uncertainly but can lead to poorer performance. Three reasons related to team coordination were...