FUZZY COGNITIVE MAPS EMBEDDED IN A LOW COST AUTONOMOUS MOBILE ROBOT

Author(s):  
Márcio Mendonça ◽  
Guilherme Bender Sartori ◽  
Lucas Botoni de Souza ◽  
Giovanni Bruno Marquini Ribeiro
2014 ◽  
Vol 24 (1) ◽  
pp. 213-225 ◽  
Author(s):  
Piotr Szwed ◽  
Paweł Skrzyński

Abstract For contemporary software systems, security is considered to be a key quality factor and the analysis of IT security risk becomes an indispensable stage during software deployment. However, performing risk assessment according to methodologies and standards issued for the public sector or large institutions can be too costly and time consuming. Current business practice tends to circumvent risk assessment by defining sets of standard safeguards and applying them to all developed systems. This leads to a substantial gap: threats are not re-evaluated for particular systems and the selection of security functions is not based on risk models. This paper discusses a new lightweight risk assessment method aimed at filling this gap. In this proposal, Fuzzy Cognitive Maps (FCMs) are used to capture dependencies between assets, and FCM-based reasoning is performed to calculate risks. An application of the method is studied using an example of an e-health system providing remote telemonitoring, data storage and teleconsultation services. Lessons learned indicate that the proposed method is an efficient and low-cost approach, giving instantaneous feedback and enabling reasoning on the effectiveness of the security system.


2020 ◽  
Vol 6 (2) ◽  
pp. 105-110
Author(s):  
Ali Hakan ISIK ◽  
Ömer ÇETİN

2011 ◽  
Vol 403-408 ◽  
pp. 3917-3924
Author(s):  
Deep Sharma ◽  
S. K. Dwivedy

In this paper, an autonomous mobile robot has been designed and fabricated which can be used in both indoor and outdoor for industrial and household applications. Here using six servo motors and four DC motors with their controllers (servo controller and L293D DC Motor controller) the mobile robot can pick any object from its workspace and by avoiding collision it can place the object in the desired location. ASCII ultrasonic sensor and motion sensor are used along with ATmega 2560 microcontroller which is programmed to take the sensors output as its input and controls the dc motor and servo motors to pick and place objects and avoid obstacle during motion of the mobile robot. Here low-cost solar panels have been used to recharge the Li-ion batteries used for the motors and microcontroller in case of outdoor environment. The obstacle avoidance and path planning algorithms have been developed and a case study has been presented in this paper.


Diagnosis ◽  
2014 ◽  
Vol 1 (4) ◽  
pp. 289-293 ◽  
Author(s):  
Claudio Lucchiari ◽  
Raffaella Folgieri ◽  
Gabriella Pravettoni

AbstractAnticipating that the problem of diagnostic errors will not easily be solved through education, debiasing techniques or incentives-based systems, experts have proposed the systematic use of decision support tools (or decision aids) in medical practice. These tools are active knowledge resources that use patient data to generate case-specific advice to support clinical decision making. We argue that designing these decision support tools incorporates both discrete, analytical information as well as intuitive elements that would optimize their impact on clinical everyday activities. The use of fuzzy cognitive maps should allow developers to achieve this aim, by incorporating published evidence, intuition and qualitative assessment in a low-cost software program that could be implemented in various clinical settings.


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