With the huge increase of large-scale multimedia over Internet, especially images, building Content-Based Image Retrieval (CBIR) systems for large-scale images has become a big challenge. One of the drawbacks associated with CBIR is the very long execution time. In this article, we propose a fast Content-Based Image Retrieval system using Spark (CBIR-S) targeting large-scale images. Our system is composed of two steps. (i) image indexation step, in which we use MapReduce distributed model on Spark in order to speed up the indexation process. We also use a memory-centric distributed storage system, called Tachyon, to enhance the write operation (ii) image retrieving step which we speed up by using a parallel k-Nearest Neighbors (k-NN) search method based on MapReduce model implemented under Apache Spark, in addition to exploiting the cache method of spark framework. We have showed, through a wide set of experiments, the effectiveness of our approach in terms of processing time.

Background Pediatric Rheumatology is an orphan specialty in Africa which is gradually gaining importance across the continent. Main body This commentary discusses the current state of affairs in the sphere of Pediatric Rheumatology across Africa and offers practical strategies to navigate the challenges encountered in research, models of care, education and training. We outline the establishment, opportunities of growth and achievements of the Pediatric Society of the African League Against Rheumatism (PAFLAR). Conclusion This commentary lays the foundation for establishment of a formidable framework and development of partnerships for the prosperity of Pediatric Rheumatology in Africa and beyond.