Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  First,...

BACKGROUND Despite the efforts to decrease the rate of preterm birth, preterm delivery is still the main cause of neonatal morbidity and mortality. Identifying patients threatened with preterm delivery remains one of the main obstetric challenges. The aim of this study was to estimate the potential value of elastographic evaluation of internal cervical os stiffness at 18-22 weeks of pregnancy i...

Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  First,...

This paper considers the use of image quality metric for still image compression systems comparison. Considering the fact that the conventional PSNR cannot suuciently reeect the result of subjective assessment, other quality measures have been considered to design the variable bit-rate coders. Indeed, distortion measures are developed for the purpose of predicting the subjective quality of pict...

The paper describes static analysis algorithms aimed at finding three types of errors related to the concept a synchronizing monitor: redefinition variable mutually exclusive locking inside critical section; use an incorrect type when entering monitor; blocking involving object that has methods reference instance (this) lock. Developed rely on symbolic execution technology and involve interproc...