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Streaming analysis is widely used in cloud as well as edge infrastructures. In these contexts, fine-grained application performance can be based on accurate modeling of streaming operators. This is especially beneficial for computationally…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-30 Hannaneh Najdataei , Vincenzo Gulisano , Alessandro V. Papadopoulos , Ivan Walulya , Marina Papatriantafilou , Philippas Tsigas

This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…

Computational Physics · Physics 2025-03-11 Xiaojian Yang , Kun Xu

A calculational approach in fluid turbulence is presented. Use is made of the attracting nature of the fluid-dynamic dynamical system. An approximate approach is offerred that effectively propagates the statistics in time. Loss of…

Fluid Dynamics · Physics 2007-05-23 Edsel A. Ammons

This paper studies optical flow estimation, a critical task in motion analysis with applications in autonomous navigation, action recognition, and film production. Traditional optical flow methods require consecutive frames, which are often…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Mo Zhou , Jianwei Wang , Xuanmeng Zhang , Dylan Campbell , Kai Wang , Long Yuan , Wenjie Zhang , Xuemin Lin

Distributed link-flooding attacks constitute a new class of attacks with the potential to segment large areas of the Internet. Their distributed nature makes detection and mitigation very hard. This work proposes a novel framework for the…

Networking and Internet Architecture · Computer Science 2016-11-09 hristos Liaskos , Vasileios Kotronis , Xenofontas Dimitropoulos

The structure of a river network may be seen as a discrete set of nested sub-networks built out of individual stream segments. These network components are assigned an integral stream order via a hierarchical and discrete ordering method.…

Geophysics · Physics 2013-05-29 Peter Sheridan Dodds , Daniel H. Rothman

We present a framework to calculate the cascade size evolution for a large class of cascade models on random network ensembles in the limit of infinite network size. Our method is exact and applies to network ensembles with almost arbitrary…

Physics and Society · Physics 2018-04-25 Rebekka Burkholz , Frank Schweitzer

Understanding pedestrian dynamics is crucial for appropriately designing pedestrian spaces. The pedestrian fundamental diagram (FD), which describes the relationship between pedestrian flow and density within a given space, characterizes…

Adaptation and Self-Organizing Systems · Physics 2024-08-27 Kota Nagasaki , Keiichiro Fujiya , Toru Seo

Hydroclimatic processes are characterized by heterogeneous spatiotemporal correlation structures and marginal distributions that can be continuous, mixed-type, discrete or even binary. Simulating exactly such processes can greatly improve…

Methodology · Statistics 2017-07-24 Simon Michael Papalexiou

In nature, high-speed rain drops often impact and spread on curved surfaces e.g. tree leaves. Although a drop impact on a surface is a traditional topic for industrial applications, drop-impact dynamics on curved surfaces in natural…

Fluid Dynamics · Physics 2022-11-09 Ming Long , Jalil Hasanyan , Sunghwan Jung

Nowadays, the exponentially growing of the Web renders the problem of correlation among different topics of paramount importance. The proposed model can be used to study the evolution of network depicted by different topics on the web…

Social and Information Networks · Computer Science 2015-01-05 Massimiliano Dal Mas

We model the time evolution of gaps in tidal streams caused by the impact of a dark matter subhalo, while both orbit a spherical gravitational potential. To this end, we make use of the simple behaviour of orbits in action-angle space. A…

Astrophysics of Galaxies · Physics 2016-09-07 Amina Helmi , Helmer H. Koppelman

This proposal presents a graph computing framework intending to support both online and offline computing on large dynamic graphs efficiently. The framework proposes a new data model to support rich evolving vertex and edge data types. It…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-12-08 Zhao Yu Dong

We propose a new method to obtain kinetic properties of infrequent events from molecular dynamics simulation. The procedure employs a recently introduced variational approach [Valsson and Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] to…

Statistical Mechanics · Physics 2015-08-19 James McCarty , Omar Valsson , Pratyush Tiwary , Michele Parrinello

Human trajectory data is crucial in urban planning, traffic engineering, and public health. However, directly using real-world trajectory data often faces challenges such as privacy concerns, data acquisition costs, and data quality. A…

Machine Learning · Computer Science 2025-11-05 Qingyue Long , Can Rong , Tong Li , Yong Li

The aim of this paper is to calculate the time dependence of the mean position (and orientation) of a fluid particle when a fluid system at thermodynamic equilibrium is submitted to a mechanical action. The starting point of this novel…

Soft Condensed Matter · Physics 2022-04-25 Frederic Aitken , Ferdinand Volino

In many real-world scenarios, distribution shifts exist in the streaming data across time steps. Many complex sequential data can be effectively divided into distinct regimes that exhibit persistent dynamics. Discovering the shifted…

Machine Learning · Computer Science 2023-09-07 Weijieying Ren , Tianxiang Zhao , Wei Qin , Kunpeng Liu

This paper considers some designs for sampling and interventions in dynamic networks and spatial temporal settings. The sample spreads through the population largely by tracing network links, although random sampling or spatial designs may…

Methodology · Statistics 2013-06-05 Steven K. Thompson

In this paper, we informally introduce dynamic mind-maps that represent a new approach on the basis of a dynamic construction of connectionist structures during the processing of a data stream. This allows the representation and processing…

Neural and Evolutionary Computing · Computer Science 2008-12-18 Christoph Schommer

Networks observed in real world like social networks, collaboration networks etc., exhibit temporal dynamics, i.e. nodes and edges appear and/or disappear over time. In this paper, we propose a generative, latent space based, statistical…

Social and Information Networks · Computer Science 2018-11-08 Shubham Gupta , Gaurav Sharma , Ambedkar Dukkipati
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