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Zhihan Lv

Researcher at Qingdao University

Publications -  460
Citations -  14707

Zhihan Lv is an academic researcher from Qingdao University. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 54, co-authored 313 publications receiving 8997 citations. Previous affiliations of Zhihan Lv include Chinese Academy of Sciences & Warsaw University of Technology.

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Soft frequency reuse-based optimization algorithm for energy efficiency of multi-cell networks

TL;DR: This paper utilizes the fractional program, successive convex approximation, Lagrange dual, and Karush–Kuhn–Tucker (KKT) conditions to transform the objective function into a concave function and proposes a global energy efficiency optimization algorithm to search for the optimal energy efficiency of networks.
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Mobile crowd sensing of human-like intelligence using social sensors: A survey

TL;DR: This survey reviews the mobile crowd sensing applications on social sensors based on social sensor receiver platform from three categories: public security, smart city, and location based services.
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A Fast Image Retrieval Method Designed for Network Big Data

TL;DR: A fast image retrieval method which designed for big data, which has a great improvement in the effective performance of feature extraction and can also get better search matching results.
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Deployment optimization for 3D industrial wireless sensor networks based on particle swarm optimizers with distributed parallelism

TL;DR: A modified 3D coverage model and a lifetime model with reliability constraint are presented to facilitate the mathematical analysis of the deployment problem and thorough understandings are obtained w.r.t. both the deploymentproblem and the optimizers.
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An energy-efficient multicast algorithm with maximum network throughput in multi-hop wireless networks

TL;DR: An energy-efficient multicast algorithm in multi-hop wireless networks is proposed aiming at new generation wireless communications to maximize network throughput and minimize networks' energy consumption by exploiting network coding and sleeping scheme.