IMPROVED CLASSIFICATION MODELS TO DISTINGUISH NATURAL FROM ANTHROPIC OIL SLICKS IN THE GULF OF MEXICO: SEASONALITY AND RADARSAT-2 BEAM MODE EFFECTS UNDER A MACHINE LEARNING APPROACH

Distinguishing between natural and anthropic oil slicks is a challenging task, especially in the Gulf of Mexico, where these events can be simultaneously observed and recognized as seeps or spills.In this study, a powerful data analysis provided by machine learning (ML) methods was employed to develop, test, and implement a classification model (CM

Micro-scale Cyber-Physical Systems (MCPSs) can be automatically and formally estimated by probabilistic model checking, on the level of system model MDPs (Markov Decision Processes) against desired requirements m7 mega truck in PCTL (Probabilistic Computation Tree Logic).The counterexamples in probabilistic model checking are witnesses of requireme

The Hajj and Umrah religious mass gatherings hosted by the Kingdom of Saudi Arabia can facilitate the transmission of infectious diseases.The pilgrimages have been associated with a number of local and international outbreaks of meningococcal disease.These include serogroup A disease outbreaks in 1987 and throughout the 1990s and two international

INTRODUCTION:Adverse drug reactions (ADRs) are global public health problems.In its severe form it may cause hospital admission, morbidity and mortality.Early reporting of suspected ADRs to regulatory authorities is known to be appropriate measure toinsure health and safety of public form such adverse drug reaction of drugs.In Addis Ababa, there is