Population Density-based Hospital Recommendation with Mobile LBS Big Data

The difficulty of getting medical treatment is one of major livelihood issues in China. Since patients lack prior knowledge about the spatial distribution and the capacity of hospitals, some hospitals have abnormally high or sporadic population densities. This paper presents a new model for estimating the spatiotemporal population density in each hospital based on location-based service (LBS) big data, which would be beneficial to guiding and dispersing outpatients. To improve the estimation accuracy, several approaches are proposed to denoise the LBS data and classify people by detecting their various behaviors. In addition, a long short-term memory (LSTM) based deep learning is presented to predict the trend of population density. By using Baidu large-scale LBS logs database, we apply the proposed model to 113 hospitals in Beijing, P. R. China, and constructed an online hospital recommendation system which can provide users with a hospital rank list basing the real-time population density information and the hospitals' basic information such as hospitals' levels and their distances. We also mine several interesting patterns from these LBS logs by using our proposed system

Hypo-Steiner heuristic for multicast routing in all-optical WDM mesh networks

International audienceIn sparse light splitting all-optical WDM networks, the more destinations a light-tree can accommodate, the fewer light-trees andwavelengths amulticast session will require. In this article, a Hypo-Steiner light-tree algorithm (HSLT) is proposed to construct a HSLT light-tree to include as many destinations as possible. The upper bound cost of the light-trees built by HSLT is given as N(N −1)/2, where N is the number of nodes in the network. The analytical model proves that, under the same condition, more destinations could be held in a HSLT than a Member-Only (Zhang et al., J. Lightware Technol, 18(12), 1917–1927 2000.) light-tree. Extensive simulations not only validate the proof but also show that the proposed heuristic outperforms the existing multicast routing algorithms by a large margin in terms of link stress, throughput, and efficiency ofwavelength usage

Impact of Modern Human Activities on the Songhua River’s Health in Heilongjiang Province

The Songhua River is the largest river in Heilongjiang province. During the past decades, intense human activities had extensive effects on the river. Protecting the Songhua River requires diagnosing threats on a large scale. Here we conducted the first comprehensive survey on the rivers’ health throughout the Heilongjiang province, investigating into land use of riversides, modern industries along riversides and other human factors. The results showed that water quality, habitat quality and biological assemblages of the Songhua River are facing deterioration. Farmland, sand dredging operations and tourism depending on water resource may be the main factors which lead to the unhealthy state. This study will be helpful for developing riparian zone restoration plans, or adopting both biological and engineering measures to minimize the degradation of the Songhua River

Light-Hierarchy: The Optimal Structure for Multicast Routing in WDM Mesh Networks

Based on the false assumption that multicast incapable (MI) nodes could not be traversed twice on the same wavelength, the light-tree structure was always thought to be optimal for multicast routing in sparse splitting Wavelength Division Multiplexing (WDM) networks. In fact, for establishing a multicast session, an MI node could be crosswise visited more than once to switch a light signal towards several destinations with only one wavelength through different input and output pairs. This is called Cross Pair Switching (CPS). Thus, a new multicast routing structure light-hierarchy is proposed for all-optical multicast routing, which permits the cycles introduced by the CPS capability of MI nodes. We proved that the optimal structure for minimizing the cost of multicast routing is a set of light-hierarchies rather than the light-trees in sparse splitting WDM networks. Integer linear programming (ILP) formulations are developed to search the optimal light-hierarchies. Numerical results verified that the light-hierarchy structure could save more cost than the light-tree structure