I was lucky to be selected to the Square Kilometre Array Big Data Africa School funded by the SKA and the Development of Africa With Radio Astronomy (DARA). It was held in Cape Town, South Africa. Big Data is a cloudy idea. Easy to know when you have it, hard to describe. I like thinking of it as data that is sufficiently large such that it is difficult to draw information from it "easily".
The task of decision-making under uncertainty is daunting, especially for problems which have significant complexity. Healthcare policy makers across the globe are facing problems under challenging constraints, with limited tools to help them make data driven decisions. In this work we frame the process of finding an optimal malaria policy as a stochastic multi-armed bandit problem, and implement three agent based strategies to explore the policy space. We apply a Gaussian Process regression to the findings of each agent, both for comparison and to account for stochastic results from simulating the spread of malaria in a fixed population. The generated policy spaces are compared with published results to give a direct reference with human expert decisions for the same simulated population. Our novel approach provides a powerful resource for policy makers, and a platform which can be readily extended to capture future more nuanced policy spaces.
Faculty Of Engineering Cairo University Giza, Egypt Diagnosis of anemia depends upon the observation of variations in color, shape and gray level distribution inside the Red Blood Cells (RBC's). The most important of all is the variation in the outer contour of an individual cell. In this paper, several new closed contour features are presented, together with some techniques for preprocessing and feature extraction. Preprocessing includes contour extraction and run length coding of a closed contour, while features include concavity, unsymmetry and zero crossing of slope density curve. Features are rotation, transformation and scale invariant in addition to being highly noise tolerant. An efficient design of a decision tree is presented for classification.
"Computer systems can automatically detect and interpret what is happening on video surveillance cameras; Siri allows anyone to have a personal assistant in their pocket; Watson has beaten two former champions on Jeopardy and Google driverless cars have driven over 500 000km accident-free. Modern technology is increasingly intelligent," says Suren Govender, Accenture Analytics MD. With the growing availability of sensors, better algorithms for data analytics and growing computational power, these intelligent technologies are becoming more prevalent and are being incorporated in everyday life and business. "The cognitive era is about thinking itself – how we gather information, access it and make decisions," notes Hamilton Ratshefola, country GM at IBM South Africa. Cognitive analytics engines have the ability to build knowledge and learn, they understand natural language, reason and interact more naturally with human beings than traditional programmable systems.
The intelligence exhibited by machine also known as Artificial Intelligence is an area that very many large technology companies are investing into these days. Apple made its mark in artificial intelligence by introducing its digital assistant Siri, google and Microsoft also followed. Social media giants; Facebook and amazon have shown indications of investing in Artificial Intelligence. The interest of these companies in this field of computer science is an indicator that Artificial Intelligence is an area that offers a lot of promise. The country has tried to use AI in some areas for example KCCA introduced the smart traffic lights at Wandegeya.