LUCY
发表于 2025-4-1 05:29:32
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
发表于 2025-4-1 09:55:17
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
反话
发表于 2025-4-1 13:32:31
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现晕光
发表于 2025-4-1 15:53:57
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
发表于 2025-4-1 20:05:35
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协迫
发表于 2025-4-2 02:39:03
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
发表于 2025-4-2 04:40:56
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
高兴去去
发表于 2025-4-2 07:50:30
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