An empirical study of different strategies for the parallel simulation of large-scale communication networks

This paper reports a new parallel and distributed simulation architecture for OMNeT++, an open-source discrete event simulation environment. The primary application area of OMNeT++ is the simulation of communication networks. Support for a conservative PDES protocol (the Null Message Algorithm) and the relatively novel Ideal Simulation Protocol has been implemented.Placeholder modules, a novel way of distributing the model over several logical processes (LPs) is presented. The OMNeT++ PDES implementation has a modular and extensible architecture, allowing new synchronization protocols and new communication mechanisms to be added easily, which makes it an attractive platform for PDES research, too. We intend touse this framework to harness the computational capacity of highperformance cluster computersfor modeling very large scale telecommunication networks to investigate protocol performance and rare event failure scenarios.

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Audio Mining: The Role of Vocal Tone in Persuasion

Journal of Consumer Research ◽

10.1093/jcr/ucab012 ◽

2021 ◽

Author(s):

Xin (Shane) Wang ◽

Shijie Lu ◽

X I Li ◽

Mansur Khamitov ◽

Neil Bendle

Keyword(s):

Empirical Study ◽

Large Scale ◽

Controlled Experiments ◽

The Core ◽

Content Model ◽

Stereotype Content ◽

Key Indicators ◽

The Impact ◽

Insight Into

Abstract Persuasion success is often related to hard-to-measure characteristics, such as the way the persuader speaks. To examine how vocal tones impact persuasion in an online appeal, this research measures persuaders’ vocal tones in Kickstarter video pitches using novel audio mining technology. Connecting vocal tone dimensions with real-world funding outcomes offers insight into the impact of vocal tones on receivers’ actions. The core hypothesis of this paper is that a successful persuasion attempt is associated with vocal tones denoting (1) focus, (2) low stress, and (3) stable emotions. These three vocal tone dimensions—which are in line with the stereotype content model—matter because they allow receivers to make inferences about a persuader’s competence. The hypotheses are tested with a large-scale empirical study using Kickstarter data, which is then replicated in a different category. In addition, two controlled experiments provide evidence that perceptions of competence mediate the impact of the three vocal tones on persuasion attempt success. The results identify key indicators of persuasion attempt success and suggest a greater role for audio mining in academic consumer research.

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GPU-accelerated hydraulic simulations of large-scale natural gas pipeline networks based on a two-level parallel process

Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles ◽

10.2516/ogst/2020076 ◽

2020 ◽

Vol 75 ◽

pp. 86

Author(s):

Yue Xiang ◽

Peng Wang ◽

Bo Yu ◽

Dongliang Sun

Keyword(s):

Natural Gas ◽

Large Scale ◽

Parallel Simulation ◽

Simulation Software ◽

Gas Pipeline ◽

Processing Unit ◽

Pipeline Network ◽

Natural Gas Pipeline ◽

Pipeline Networks ◽

Speedup Ratio

The numerical simulation efficiency of large-scale natural gas pipeline network is usually unsatisfactory. In this paper, Graphics Processing Unit (GPU)-accelerated hydraulic simulations for large-scale natural gas pipeline networks are presented. First, based on the Decoupled Implicit Method for Efficient Network Simulation (DIMENS) method, presented in our previous study, a novel two-level parallel simulation process and the corresponding parallel numerical method for hydraulic simulations of natural gas pipeline networks are proposed. Then, the implementation of the two-level parallel simulation in GPU is introduced in detail. Finally, some numerical experiments are provided to test the performance of the proposed method. The results show that the proposed method has notable speedup. For five large-scale pipe networks, compared with the well-known commercial simulation software SPS, the speedup ratio of the proposed method is up to 57.57 with comparable calculation accuracy. It is more inspiring that the proposed method has strong adaptability to the large pipeline networks, the larger the pipeline network is, the larger speedup ratio of the proposed method is. The speedup ratio of the GPU method approximately linearly depends on the total discrete points of the network.

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Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1713568115 ◽

2018 ◽

Vol 115 (7) ◽

pp. 1433-1438 ◽

Cited By ~ 49

Author(s):

Tim Gernat ◽

Vikyath D. Rao ◽

Martin Middendorf ◽

Harry Dankowicz ◽

Nigel Goldenfeld ◽

...

Keyword(s):

Social Networks ◽

Social Interactions ◽

Communication Networks ◽

Disease Transmission ◽

Large Scale ◽

Reference Network ◽

Interaction Patterns ◽

Human Communication ◽

Automated Monitoring ◽

Phone Calls

Social networks mediate the spread of information and disease. The dynamics of spreading depends, among other factors, on the distribution of times between successive contacts in the network. Heavy-tailed (bursty) time distributions are characteristic of human communication networks, including face-to-face contacts and electronic communication via mobile phone calls, email, and internet communities. Burstiness has been cited as a possible cause for slow spreading in these networks relative to a randomized reference network. However, it is not known whether burstiness is an epiphenomenon of human-specific patterns of communication. Moreover, theory predicts that fast, bursty communication networks should also exist. Here, we present a high-throughput technology for automated monitoring of social interactions of individual honeybees and the analysis of a rich and detailed dataset consisting of more than 1.2 million interactions in five honeybee colonies. We find that bees, like humans, also interact in bursts but that spreading is significantly faster than in a randomized reference network and remains so even after an experimental demographic perturbation. Thus, while burstiness may be an intrinsic property of social interactions, it does not always inhibit spreading in real-world communication networks. We anticipate that these results will inform future models of large-scale social organization and information and disease transmission, and may impact health management of threatened honeybee populations.

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