Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

In real world scheduling applications, machines might not be available during certain time periods due to deterministic or stochastic causes. In this article, the machine scheduling with availability constraints for both deterministic and stochastic cases with different environments, constraints and performance measures will be discussed. The existing body of research work in the literature wil...

In this research work, an improved two-dimensional semi-analytical subdomain based method for performance computation in IPM machine considering infinite-/finite-magnetic material permeability in pseudo-Cartesian coordinates by using hyperbolic functions has been presented. In the developed technique, all subdomains are divided into periodic or non-periodic regions with homogeneous or non-homog...

statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. this paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. the thermal conductivity of nanofluids increases with the volume fraction and temperature. machine learni...

State machine replication, or “consensus”, is a central abstraction for distributed systems where a set of nodes seek to agree on an ever-growing, linearly-ordered log. In this paper, we propose a practical new paradigm called Thunderella for achieving state machine replication by combining a fast, asynchronous path with a (slow) synchronous “fall-back” path (which only gets executed if somethi...

background: dairy farming work involves frequent use of poor postures. these postures may increase the risk of developing musculoskeletal disorders among dairy workers. objective: to assess postural load during performance of various tasks related to dairy farming. methods: this cross-sectional study was conducted on a dairy farm in iran. in order to assess postural load, tasks related to dairy...