Abstract: Compared with conventional dynamic nonlinear equation systems, a hybrid double-deck dynamic nonlinear equation system (H3DNES) not only has multiple layers describing more different tasks in ...

Red Bull team principal Laurent Mekies has explained the different characteristics of the Marina Bay Circuit in Singapore means the team’s “equations” will “move a bit” to find the optimum setup. The ...

Abstract: Two asynchronous distributed algorithms are presented for solving a linear equation of the form Ax=b with at least one solution. The equation is simultaneously and asynchronously solved by m ...

In grade school, you were probably constantly drilled on mathematics. Whether it be multiplication tables, simple addition, or complicated division, it was taught over and over again that quick math ...

You can finally fold a fitted sheet without frustration. Fitted sheets have got a well-earned reputation for being one of the most annoying laundry items to fold. Unlike their flat sheet cousins, ...

Abstract: The solving of nonlinear equation systems (e.g., complex transcendental dispersion equation systems in waveguide systems) is a fundamental topic in science and engineering. Davidenko method ...

IGNOU has revised the examination schedule for Term-End Examinations (TEE) for the December session. Candidates can fill out the exam form for Online Distance Learning (ODL) and online programmes ...

Abstract: In testing systems, Item Response Theory (IRT) is a widely used model for accurately synthesizing user response information. However, compared to Classical Test Theory (CTT) approaches, it ...

Rachel Reeves is spending the summer grappling with the various options at her disposal to fill a £50bn hole in the public finances. The chancellor will be presented in the coming weeks with a range ...

Abstract: Spectral clustering (SC) has been widely used in many applications and shows excellent performance. Its high computational cost limits its applications; many strategies including the anchor ...

Abstract: Graph contrastive learning (GCL) has emerged as a powerful method for dealing with noise and fluctuations in graph-structured data, and can be applied to social networks and knowledge graphs ...