The latest nationwide survey of Pakistan showed that considerable progress has been made toward reducing all child mortality indicators except neonatal mortality. The aim of this study is to compare Pakistan’s under-five mortality, neonatal mortality, and postnatal newborn care rates with those of other countries. Neonatal mortality rates and postnatal newborn care rates from the Demographic and Health Surveys (DHSs) of nine low- and middle-income countries (LMIC) from Asia and Africa were analyzed. Pakistan’s maternal, newborn, and child health (MNCH) policies and programs, which have been implemented in the country since 1990, were also analyzed. The results highlighted that postnatal newborn care in Pakistan was higher compared with the rest of countries, yet its neonatal mortality remained the worst. In Zimbabwe, both mortality rates have been increasing, whereas the neonatal mortality rates in Nepal and Afghanistan remained unchanged. An analysis of Pakistan’s MNCH programs showed that there is no nationwide policy on neonatal health. There were only a few programs concerning the health of newborns, and those were limited in scale. Pakistan’s example shows that increased coverage of neonatal care without ensuring quality is unlikely to improve neonatal survival rates. It is suggested that Pakistan needs a comprehensive policy on neonatal health similar to other countries, and its effective programs need to be scaled up, in order to obtain better neonatal health outcomes.

Collecting aftermath information after a wide-area disaster is a crucial task in the disaster response that requires important human resources. We propose to assist reconnaissance teams by extracting useful data sent by the users of social networks that experienced the disaster. In particular we consider the photo sharing website Flickr as a source of information that allows one to evaluate the disaster aftermath. We propose a methodology to detect major event occurrences from the behavior of Flickr users and describe the nature of these events from the tags they post on the Flickr website. Our experiments using two study cases, namely, the Tohoku earthquake and tsunami and the Tuscaloosa tornado, reveals the value of the data published by Flickr users and highlight the value of social networks in disaster response.

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SUMMARY Current efforts to classify Internet traffic highlight accuracy. Previous studies have focused on the detection of major applications such as P2P and streaming applications. However, these applications can generate various types of traffic which are often considered as minor and ignorant traffic portions. As network applications become more complex, the price paid for not concentrating on minor traffic classes is in reduction of accuracy and completeness. In this context, we propose a fine‐grained traffic classification scheme and its detailed method, called functional separation. Our proposal can detect, according to functionalities, different types of traffic generated by a single application and should increase completeness by reducing the amount of undetected traffic. We verify our method with real‐world traffic. Our performance comparison against existing DPI‐based classification frameworks shows that the fine‐grained classification scheme achieves consistently higher accuracyand completeness. Copyright © 2013 John Wiley & Sons, Ltd.