Artifical Intelligence Librarian as Promotion of IAIN Lhokseumawe Library in the Revolutionary Era 4.0

Era 4.0. is a revolution in the industrial world, in the era referred to as the phenomenon distruptive innovation. In the industrial era 4.0, the emphasis lies on the digital economy pattern, artificial intelligence (artificial intelligence) big data, robotics, and automation. The impact of the industrial era 4.0 influential in various fields of work are no exception librarians. Librarian is someone who has the ability and expertise librarianship the librarians in charge to prepare themselves to face the era that is the way to equip themselves with information technology and analytical capabilities of the library so that airport users effective. Then by applying a librarian AI (artificial intelligence) to guide users in using the integrated library information. The presence of librarians AI (artificial intelligence) at IAIN Lhokseumawe made of evidence that has entered the era of disruption 4.0 will be the college library promotion strategy

Hypercomplex-Valued Recurrent Correlation Neural Networks

Recurrent correlation neural networks (RCNNs), introduced by Chiueh and Goodman as an improved version of the bipolar correlation-based Hopfield neural network, can be used to implement high-capacity associative memories. In this paper, we extend the bipolar RCNNs for processing hypercomplex-valued data. Precisely, we present the mathematical background for a broad class of hypercomplex-valued RCNNs. Then, we provide the necessary conditions which ensure that a hypercomplex-valued RCNN always settles at an equilibrium using either synchronous or asynchronous update modes. Examples with bipolar, complex, hyperbolic, quaternion, and octonion-valued RCNNs are given to illustrate the theoretical results. Finally, computational experiments confirm the potential application of hypercomplex-valued RCNNs as associative memories designed for the storage and recall of gray-scale images