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Showing 5 open source projects for "claw-code"
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XG-PON Module for NS-3 (moved to GitHub)
Codebase moved to GitHub - use the Blue button or link in Description
2023-03-20: the latest version of the XG-PON model for ns-3.35 is in GitHub (https://github.com/ajerikko/xgpon4ns3-v3/releases/tag/v3.1). It contains major changes to example code. Please use it for new activities. 10-Gigabit-capable Passive Optical Network (XG-PON), is regarded as one of the key technologies for future Internet access networks. This project develops an XG-PON module for the NS-3 network simulator - a G987 (ITU-T) standards-compliant, configurable, and extensible module that can simulate XG-PON that can support a wide range of research topics. ... -
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TraceMetrics
TraceMetrics is a trace file analyzer for Network Simulator 3 (ns-3).
...Such tool is needed because a research simulation may generate a trace file with thousands of lines, becoming dificult to analyze manually. Due to this, this tool can be handy in case someone needs a metric that the tool already support. TraceMetrics is an opensource tool, developed in Java and the code can be found here. We encourage the users to report any bugs found in the tool, mailing us at tracemetrics (at) tracemetrics.net -
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Positioning Algorithms
Positioning Algorithms for Mobile Ad Hoc Networks.
The DV-Hop, Amorphous, Centroid and APIT source code for NS2. Please reference this work as follows: A. Pineda-Briseño, R. Menchaca-Mendez, E. Chavez, G. Guzman, R. Menchaca-Mendez, R. Quintero, M. Torres, M. Moreno, and J. L. Diaz-De-Leon. "A Probabilistic Approach to Location Estimation in MANETs." Ad Hoc & Sensor Wireless Networks, vol. 28, no. 1-2, pp. 97-114, 2015. -
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Main source code is moved at https://github.com/jpahullo/planetsim. We recommend authors of contributions sections to move your code to github. Since then, contributions remain here for your use at will. PlanetSim is an object oriented simulation framework for overlay networks and services. This framework presents a layered and modular architecture with well defined hotspots documented using classical design patterns.
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Transform months of data modeling and coding into days.Efficiently model your business and data models, and generate code for your data pipelines, data lakehouse, and analytical applications
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SNNSraster is a utility for quick ANN analysis of raster GIS maps with the use of Stuttgart Neural Network Simulator trained network files. It was developed to read and write binary raster files. SNNSraster is a project of the Geography Laboratory of the University of Siena. The code was developed by Giancarlo Macchi Jánica between 2006 and 2007. SNNSraster's fundamental objective is to improve the ability to integrate the use of artificial neural networks in GIS environments.
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