scholarly journals A Joint Two-Phase Time-Sensitive Regularized Collaborative Ranking Model for Point of Interest Recommendation

2020 ◽  
Vol 32 (6) ◽  
pp. 1050-1063 ◽  
Author(s):  
Mohammad Aliannejadi ◽  
Dimitrios Rafailidis ◽  
Fabio Crestani
Author(s):  
Gholamreza Keshavarzi ◽  
Tracie J. Barber ◽  
Guan Yeoh

The motion and transport of bubbles in fluid flows have many engineering applications. The rise of a bubble has been a point of interest for both numerical and experimental studies. Various tracking methodologies have been developed, including markers, level sets and volume tracking. In order to validate numerical models of bubble flow, detailed experimental data describing the transient bubble shape is needed. This is best found from a 2D comparison rather than 3D experiment because computational resources for determining an accurate shape can be maximized. No real full time shape and subsequent deformation of this 2D bubble has yet been demonstrated. In this paper 2D bubble experiments have been conducted, in which a single bubble has been injected inside a close-walled tank and the rising of the bubble has been captured through a high speed camera. This data is now being used as a benchmark for numerical interface capturing and two phase flow methodology validations.


Author(s):  
Junhai Luo ◽  
Liying Fan

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assisted. It is especially relevant for sensor nodes location in UWSNs. Global Positioning System (GPS) is not suitable for using in UWSNs because of the underwater propagation problems. Hence some localization algorithms based on the precise time synchronization between sensor nodes have been proposed which are not feasible for UWSNs. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme base on the Particle Swarm Optimization (PSO) algorithm to decrease the localization error. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence in this algorithm, we use a small number of mobile beacons to help achieve location without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.


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