Chest X-Ray (CXR) is one of the most common types of radiology examination for the diagnosis of thorax diseases. Computer-Aided Diagnosis (CAD) was developed to help radiologists to achieve diagnostic excellence in a short period of time and to enhance patient healthcare. In this paper, we seek to improve the performance of CAD system in the task of thorax diseases diagnosis by providing a new method that combines the advantages of CNN models in image feature extraction with those of problem transformation methods in the multi-label classification task. The experimental study is tested on two publicly available CXR datasets ChestX-ray14 (Frontal view) and CheXpert (Frontal and Lateral view). The results show that our proposed method outperformed current state-of-the-art.

An accurate short-term global solar irradiation (GHI) forecast is essential for integrating the photovoltaic systems into the electricity grid by reducing some of the problems caused by the intermittency of solar energy, including rapid fluctuations in energy, management storage, and the high...

Conceiving a smart city is coming to maturity, to make less the problems produced by the swift urbanization. It mainly focuses on how to increase the quality and comfort of citizens by using information and communication technologies. That being said, make smart cities will offer a flamboyant metamorphosis for the success of cities' development, they propose a way adapted to the multitude of urban concerns, and customized technological solutions. One of the core component related to Intelligent Transport Systems, the Vehicular Ad hoc Network a particular application of Mobile Ad hoc Network, characterized by high dynamics due to the rapid movement of vehicles. Applying vehicular communication environments has led to the improvement of road safety and such others services. This paper aims to explore important dimensions that are critical for the development of a smart city. Following a mixture between two approaches, this paper conceives in the first way a framework for smartness human behavior and mentality offering solutions to develop a successful smart city, then in the second part, we investigated the impact of the human driver behavior on ITS by suggesting an integration of such models in simulation, in order to propose a new model of communication to warn other vehicles on the road so as to prevent accidents from happening and to ensure smart mobility with security aspects perspective. Furthermore, we demonstrate that even complex behavior model can be represented using realistic simulation studies, the experimental results indicate that driver's behavior has a significant impact in traffic. This exploratory research argues that human capital, and smart mobility are the fundamental constructs of smartness.