Abstract The enhancement of surgical simulation tools is an important research study, to assist in the assessment and feedback of medical training practice. In this research, the Spring Tensor Model (STEM) has been used for laparoscopic end-effector navigation through obstacles and high-risk areas. The modelling of the surgical trainer as part of the laparoscopic simulator seeks to emulate the physical environment as a virtualised representation in the integrated infrastructure. Combining sensor network framework paradigms to a surgical knowledge-based construct demonstrates how STEMcan enhance medical practice. The architectural hybridisation of the training framework has enabled the adaptation of STEM modelling techniques for a simulated laparoscopic training methodology. The primary benefit of the architecture is that this integration strategy has resulted in a seamless transition of the heuristic framework to be applied to surgical training.

Abstract In this article the author makes an attempt to characterize the factors which are to be taken into consideration while designing the ground radar component of Air Defense systems, in order to enable them to operate on the modern battlefield. He presents the latest theoretical views on the relationship between the usage of anti-radar weapons and the organizational and technical defense mechanisms which can be deployed against such weapons. In particular the author emphasizes the protection of radars against anti-radiation missiles (ARMs) which present the biggest threat for effective Air Defense systems. He also stresses the need to combine radars into one system which enables the streamlining of their work parameters and thus ensuring their complex usage. The gaining of those capabilities will guarantee that the parameters of the air surveillance radar zone can be defined effectively.