Abstract: this paper a Glucose-Insulin regulator for Type 1 Diabetes using artificial neural networks (ANN) is proposed. This is done using a discrete recurrent high order neural network in order to identify and control a nonlinear dynamical system which represents the pancreas’ beta-cells behavior of a virtual patient. The ANN which reproduces and identifies the dynamical behavior system, is configured as series parallel and trained on line using the extended Kalman filter algorithm to achieve a quickly convergence identification in silico. The control objective is to regulate the glucose-insulin level under different glucose inputs and is based on a nonlinear neural block control law. A safety block is included between the control output signal and the virtual patient with type 1 diabetes mellitus. Simulations include a period of three days. Simulation results are compared during the overnight fasting period in Open-Loop (OL) versus Closed-Loop (CL). Tests in Semi-Closed-Loop (SCL) are made f

• Publication Date: 02-Jun-2014
• DOI: 10.15224/978-1-63248-010-1-25
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Abstract: Creation of business vocabulary is the first step in business modelling and development of its supporting information systems. Current CASE tools still lack this capability. The goal of the paper is to allow integrating business vocabulary and business rules with business process models in CASE tools by providing UML profile for this purpose. The idea is demonstrated by a prototype implementing the proposed UML SBVR profile, and a business process example for illustrating the advantages of using SBVR vocabulary in the modelling.

• Publication Date: 02-Jun-2014
• DOI: 10.15224/978-1-63248-010-1-26
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• Downloads: 0