<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Boris Bozveliev</style></author><author><style face="normal" font="default" size="100%">Sotir Sotirov</style></author><author><style face="normal" font="default" size="100%">Tihomir Videv</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Generalized Net Model of Possible Drone’s Communication Control Cyber Theft with Intuitionistic Fuzzy Estimations</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Fuzzy sets</style></keyword><keyword><style  face="normal" font="default" size="100%">generalized nets</style></keyword><keyword><style  face="normal" font="default" size="100%">open TX</style></keyword><keyword><style  face="normal" font="default" size="100%">radio receiver</style></keyword><keyword><style  face="normal" font="default" size="100%">radio transmitter</style></keyword><keyword><style  face="normal" font="default" size="100%">RX</style></keyword><keyword><style  face="normal" font="default" size="100%">telemetry</style></keyword><keyword><style  face="normal" font="default" size="100%">TX</style></keyword><keyword><style  face="normal" font="default" size="100%">UAV</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><volume><style face="normal" font="default" size="100%">43</style></volume><pages><style face="normal" font="default" size="100%">35-44</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This article looks into the control of small, helicopter-like drones. They are more formally known as unmanned aerial vehicles (UAVs). Basically, a drone is a flying computerized machine that can be remotely controlled or fly autonomously through software-controlled flight plans in their embedded systems, working in conjunction with onboard sensors and a GPS receiver. Drones can be helpful or dangerous to us depending of their intended use. In the underlying study we use fuzzy estimations and, in this article, present a generalized net model of such a system and demonstrate the possibility of taking control over the communication between the transmitter and the receiver.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><section><style face="normal" font="default" size="100%">35</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Albena Tchamova</style></author><author><style face="normal" font="default" size="100%">Tzvetan Semerdjiev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fuzzy Logic Approach to Estimating Tendencies in Target Behavior</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">attribute data processing</style></keyword><keyword><style  face="normal" font="default" size="100%">evidence reasoning</style></keyword><keyword><style  face="normal" font="default" size="100%">Fuzzy Logic</style></keyword><keyword><style  face="normal" font="default" size="100%">Fuzzy sets</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">58-69</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In some real-world situations when kinematic data is not available or it is not sufficient to provide right decisions and/or accurate estimates, estimation schemes may incorporate the attribute data that usually exists simultaneously with kinematic data. However, attribute data is usually incomplete, inconsistent and vague, hence the importance of the problem of overcoming the arising uncertainty in such cases. This paper presents one approach to the estimation of the tendency of target behavior. The authors present an original algorithm for tracking target behavior and evaluate its performance. The algorithm is based on the application of the principles of fuzzy logic to conventional passive radar amplitude measurements. A set of fuzzy models is used to describe alternative tendencies of target behavior. Additionally, a noise reduction procedure is applied. The performance of the developed algorithm in the presence of noise is estimated based on computer simulations results.</style></abstract></record></records></xml>