Titlebook: Data Science; Third International Beiji Zou,Qilong Han,Zeguang Lu Conference proceedings 2017 Springer Nature Singapore Pte Ltd. 2017 Data

LUCY

Gonzales d’Alcantara,Bernard Amerlynckhe nodes to achieve longer network lifetime for In-Vehicle Wireless Sensor Networks (IVWSNs). The algorithm changes the cluster head selection probability based on residual energy and location distribution of nodes. Then node associate with the cluster head with least communication cost and high res

Glucose

https://doi.org/10.1007/978-1-4419-8915-4el in data center networks. Then we use this model to make the net topology integration and classification through the software define network. In order to achieve the purpose of energy consumption optimization, we divide the hosts into same VLAN according to their interaction frequency to reduce th

反話

現(xiàn)暈光

https://doi.org/10.1007/978-1-4615-4044-1ng attacker is useful to address this problem. Some range-based localization schemes depend on the additional hardware of wireless nodes too much, and they can not work in resource-constrained wireless networks. Solutions in range-free localization are being pursued as a cost-effective alternative t

Inflated

協(xié)迫

Studies in Contemporary Economics to provide location information for persons and devices. This paper focuses on the research and development of the indoor positioning system based on LTE uplink signal, which consists of transmitter, Location Measurement Unit (LMU) and server. The Sounding Reference Signal (SRS) is employed as the

Factorable

Extracting Chinese Explanatory Expressions with Discrete and Neural CRFs,ces that account for one certain user opinion. In this paper, we study the extraction of explanatory expressions, by modeling the problem based on conditional random field (CRF). We compare the effectiveness of both discrete and neural features, and further integrate them. We evaluate the models on

高興去去

Incremental Influence Maximization for Dynamic Social Networks, strategies in social network. Most existing studies mainly focus on designing efficient algorithms or heuristics to find Top-K influential individuals for static network. However, when the network is evolving over time, the static algorithms have to be re-executed which will incur tremendous execut