32 Works

Trimodal Macroscopic Fundamental Diagram (MFD) for bicycles, buses and cars: Matlab model and calibration data

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This dataset provides the data and matlab model for the trimodal macroscopic fundamental diagram (MFD) for bicycles, buses and cars that is published in Loder, A., L. Bressan, M. J. Wierbos, H. Becker, A. Emmonds, M. Obee, V. L. Knoop, M. Menendez, K. W. Axhausen (2021). "How many cars in the city are too many? Towards finding the optimal modal split for a multi-modal urban road network", Frontiers in Future Transportation. The File contains a...

Design Heuristics for Additive Manufacturing Cards

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Design heuristics are design tips and strategies based on the knowledge of experienced designers that help both novices and experts generate better designs and explore more of the design space. These Design Heuristics for Additive Manufacturing are inspired by the “77 Cards: Design Heuristics for Inspiring Ideas" and are designed to help both students and professionals learn about and utilize the unique capabilities of Additive Manufacturing (AM) in their designs. These heuristics are derived from...

ETH Zurich Sensor Based Digital Health Checklist

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Design Heuristics for Additive Manufacturing Objects

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These Design Heuristics for Additive Manufacturing (DHAM) Objects are supplemental to the DHAM cards. Contained within are the necessary STL files to manufacture each of the 25 objects along with a manufacturing guide.

AV-MAVT Survey 2020 on the happiness of doctoral students and post-docs in D-MAVT

The survey was conducted at the beginning of 2020 by AV-MAVT. AV-MAVT is the association representing the non-faculty scientific staff (doctoral students, post-docs and other non-permanent scientific staff) at the department D-MAVT in ETH Zürich. It is a follow-up to a similar surveys conducted in 2016 and in 2018. The three main goals of this survey are: (i) evaluate the happiness of the non-faculty scientific staff at D-MAVT (ii) identify potential problems (iii) track the...

Not the First Digit!: Using Benford's Law to Detect Fraudulent Scientific Data

Digits in statistical data produced by natural or social processes are often distributed in a manner described by 'Benford's law'. Recently, a test against this distribution was used to identify fraudulent accounting data. This test is based on the supposition that first, second, third and other digits in real data follow the Benford distribution while the digits in fabricated do not. Is it possible to apply Benford tests to detect fabricated or falsified data as...

HRMS Breath Analysis Matlab Toolbox

This is a collection of Matlab functions and scripts, designed to aid the processing and analysis of high-resoltution mass spectrometry data from real-time breath analysis measurements. Details on the usage of the functions can be found in the individual help sections, as well as in appendix A of the dissertation "On-line Breath Analysis with Ambient High-Resolution Mass Spectrometry" by Martin Thomas Gaugg (2019), available on the ETH Research Collection.

Supplementary material for paper entitled: High-resolution short-T2 MRI using a high-performance gradient

This folder contains supplementary material for the paper entitled "High-resolution short-T2 MRI using a high-performance gradient". The content consists of Mathematica notebooks used for analytical derivation of the SNR efficiency of PETRA pulse sequence. Files are saved in different formats (.nb, .cdf, .html)

OAT-MRI coregistration protocol

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200 FPS Ultrafast Imaging with the LightProbe

Demonstration of the 200fps imaging capabilities of our digital ultrasound probe (LightProbe)

Sea ice generation code for 'Storylines of the 2018 Northern Hemisphere heat wave at pre-industrial and higher global warming levels': Python Code

This code for python accompanies the publication 'Storylines of the 2018 Northern Hemisphere heat wave at pre-industrial and higher global warming levels' in Earth System Dynamics. It contains the sea ice generation method developed for the publication and described in its section 2.5.

Landslide inventory based on optical data

AV-MAVT Survey 2022 on the happiness of doctoral students and postdocs in D-MAVT

The survey was conducted at the beginning of 2022 by AV-MAVT. AV-MAVT is the association representing the non-faculty scientific staff (doctoral students, post-docs and other non-permanent scientific staff) at the department D-MAVT in ETH Zürich. This survey has been conducted in a biennial fashion since 2016. The three main goals of this survey are: (i) to evaluate the happiness of the non-faculty scientific staff at D-MAVT (ii) to identify potential problems (iii) to track the...

Registration Year

  • 2022
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  • 2020
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  • 2019
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  • 2018
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