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In this paper, we attempt to address the challenging problem of counting built-structures in the satellite imagery. Building density is a more accurate estimate of the population density, urban area expansion and its impact on the environment, than the built-up area segmentation. However, building shape variances, overlapping boundaries, and variant densities make this a complex task. To tackle this difficult problem, we propose a deep learning based regression technique for counting built-structures in satellite imagery. Our proposed framework intelligently combines features from different regions of satellite image using attention based re-weighting techniques. Multiple parallel convolutional networks are designed to capture information at different granulates. These features are combined into the FusionNet which is trained to weigh features from different granularity differently, allowing us to predict a precise building count. To train and evaluate the proposed method, we put forward a new large-scale and challenging built-structure-count dataset. Our dataset is constructed by collecting satellite imagery from diverse geographical areas (planes, urban centers, deserts, etc.,) across the globe (Asia, Europe, North America, and Africa) and captures the wide density of built structures. Detailed experimental results and analysis validate the proposed technique. FusionNet has Mean Absolute Error of 3.65 and R-squared measure of 88% over the testing data. Finally, we perform the test on the 274.3 × 10 3 m 2 of the unseen region, with the error of 19 buildings off the 656 buildings in that area. [ABSTRACT FROM AUTHOR]

Abstract: This paper addresses the design of container liner shipping networks taking into consideration container management issues including empty container repositioning. We examine two typical service networks with different ship sizes: multi-port calling by conventional ship size and hub-and-spoke by mega-ship. The entire solution process is performed in two phases: the service network design and container distribution. A wide variety of numerical experiments are conducted for the Asia–Europe and Asia–North America trade lanes. In most scenarios the multi-port calling is superior in terms of total cost, while the hub-and-spoke is more advantageous in the European trade for a costly shipping company. [Copyright &y& Elsevier]

With global improvements in life expectancy, one important concern is to understand whether there is reduction in inequalities or greater cross-country convergence in expected length of life at various age thresholds. Insights on convergence patterns can help governments and other stakeholders decide upon health investments across age groups. This paper applies a novel econometric approach to test convergence and identify convergent clubs in life expectancy at various age groups for 201 countries/areas between 1950 and 2015. Life expectancy estimates for 201 countries/areas (1950 and 2015) from United Nations Department of Economic and Social Affairs (UNDESA) World Population Prospects (2015 Revision) are used for the analysis. We find global convergence in life expectancy at birth, but do not observe grand convergence for any other age groups. In the case of life expectancy at younger ages, most countries are moving in the same direction, but significant cross-country variations and convergence clubs are noted for older adults and elderly. Most of the better performing countries/areas are from Western Europe, Northern Europe and North America, the average performers are from South America, Eastern Europe, Southern Europe, South Asia, Central Asia, Eastern Africa, Central Africa, and the Caribbean Islands whereas the poor-performing ones are mainly Western Africa, Southern African and Oceania. In addition, we observe increasing between-country variance in life expectancy for older adults and elderly. The analysis reveals increasing global heterogeneity in the survival experience of older adults and the elderly population which has remained a neglected aspect in the discussions on global life expectancy improvements. Data, research and policy focus on life-expectancy at older ages is therefore critical to accelerate survival gains among older adults and elderly, particularly from the developing world. • Country explains 34% of the variability in life expectancy improvement. • At older ages, there are three life expectancy trajectories a country can be in. • Studying variability is a better metric for capturing life expectancy inequities. [ABSTRACT FROM AUTHOR]