Sonstige
Road condition acquisition and assessment are the key to guarantee their permanent availability. In order to maintain a country's whole road network, millions of high-resolution images have to be analyzed annually. Currently, this requires cost and time excessive manual labor. We aim to automate this process to a high degree by applying deep neural networks. Such networks need a lot of data to be trained successfully, which are not publicly available at the moment. In this paper, we present the GAPs dataset, which is the first freely available pavement distress dataset of a size, large enough to train high-performing deep neural networks. It provides high quality images, recorded by a standardized process fulfilling German federal regulations, and detailed distress annotations. For the first time, this enables a fair comparison of research in this field. Furthermore, we present a first evaluation of the state of the art in pavement distress detection and an analysis of the effectiveness of state of the art regularization techniques on this dataset.
A study on knowledge and practices of first aid and CPR among police officers in Colombo and Gampaha
(2017)
Around 85% of deaths in developing countries have been found to be due to road traffic accidents (RTAs), which cost the countries around 1-2% of their gross national product (GNP). In Sri Lanka there were 2,436 deaths reported from 36,045 RTAs in 2014. This study aimed at assessing first aid and cardiopulmonary resuscitation (CPR) knowledge among police officers and identifying its relationship to their first aid and CPR practices. A study was done on 493 police officers from Colombo and Gampaha who were selected using convenience sampling through a self-administered questionnaire. The results showed that the police officers had unsatisfactory knowledge and practices of CPR and interventions for bleeding and fractures. These should therefore be focused in their further training.