Federated learning is an emerging paradigm that provides privacy-preserving collaboration among multiple participants for model training without sharing private data. The participants with heterogeneous devices and networking ...

The use of subword embedding has proved to be a major innovation in Neural machine translation (NMT). It helps NMT to learn better context vectors for Low resource languages (LRLs) so as to predict the target words by ...

We model the active polar fluid as a collection of orientable objects supplied with active stresses and momentum damping coming from the viscosity of bulk fluid medium. The growth kinetics of local orientation field is ...

We studied a system of polar self-propelled particles (SPPs) on a thin rectangular channel designed into three regions of order-disorder-order. The division of the three regions is made on the basis of the noise SPPs ...

In this paper, we propose a solution for optimizing the routes of Mobile Medical Units (MMUs) in the domain of vehicle routing and scheduling. The generic objective is to optimize the distance traveled by the MMUs as well ...

Soil moisture (SM) is the primary variable regulating the soil temperature (ST) differences between daytime and night-time, providing protection to crop rooting systems against sharp and sudden changes. It also has a number ...

Duplex stainless steels (DSS) have been growing continuously as they are cost effective alternative to austenitic stainless steel with better mechanical and corrosion resistance. Duplex stainless steel compositions are ...

We consider the finite horizon continuous reinforcement learning problem. Our contribution is three-fold. First,we give a tractable algorithm based on optimistic value iteration for the problem. Next,we give a lower bound ...

The magnetic spin ordering and the magnetization dynamics of a double perovskite Pr2CoFeO6 have been investigated by employing the (dc and ac) magnetization and neutron powder diffraction techniques. The study revealed ...