RESEARCH

A deep neural network (DNN) is an artificial neural network (ANN) with multiple layers between the input and output layers. There are different types of neural networks but they always consist of the same components: neurons, synapses, weights, biases, and functions. Deep Learning deals with training large neural networks with complex input output transformations. The prediction accuracy of a neural net depends on its weights and biases. The process of improving the accuracy of neural network is called training. The output from a forward prop net is compared to that value which is known to be correct.

Enterprise blockchain is a distributed ledger that maintains data and transaction consistency across all nodes. The implication is that the same data is available to all network users, improving transparency while drastically reducing verification time. Verifiable credentials are a digital version of the actual physical documents. These standardized certificates come from an entity that certifies the veracity of data concerning a location/site/individual. The certificates allow the secure, online sharing of such data. The information contained is fully verifiable and secure, because it is shared via a distributed, decentralized, trusted method : blockchain.

An instruction set architecture (ISA) defines the set of basic operations a computer must support. The ISA acts as an interface between the hardware and the software, specifying both what the processor is capable of doing as well as how it gets done. A single ISA can have different microarchitecture implementations. Modern ISAs, which include ARM processors, which are ubiquitous in mobile devices, and MIPS processors, which are RISC (reduced instruction set computer) chips. RISC is an alternative to the Complex Instruction Set Computing (CISC) architecture and is often considered the most efficient CPU architecture technology available today.