5 research outputs found
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An analysis-ready and quality controlled resource for pediatric brain white-matter research
We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets.
BárbaraAvelar-Pereira 9
, EthanRoy2
, Valerie J.Sydnor3,4,5,
JasonD.Yeatman1,2, The Fibr Community Science Consortium*, TheodoreD.Satterthwaite3,4,5,88
& Ariel Roke
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Pioneering Seismic Risk Assessments in Bucharest
Bucharest, Romania, experiences a major earthquake on average every 80 years, yet most citizens live in seismically vulnerable buildings. By conducting interviews with seismic experts, locating seismically vulnerable buildings in Bucharest, and structuring a newspaper article, the project team aimed to assist the Romanian NGO Re:Rise to conduct seismic risk assessments and inform the public on the seismic risk of historical buildings. The team generated recommendations for conducting seismic risk assessments, used GIS to identify 480 buildings as a historically vulnerable building type, and outlined the structure for an article about the severity of the issue. The team hopes that the project inspires change by helping to prepare the citizens of Bucharest for the next major earthquake
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Open Source 5G Networks, Spoofing Attacks, and Proof-of-Concept Multi-Node Continuous Spectrum Analysis
As 5G networks increase in popularity, so do their security concerns. This report will be focused primarily on 5G Spoofing Attacks and proposes a way to prevent this. This is done by taking advantage of the Global User Temporary Identifier (GUTI), Random Access Control, and other aspects of 5G specifications to create a connection to a User Equipment (UE) that would accept 5G data packets and hold them from an adversary gNB. The original plan for this project was to create a 5G network and design spoofing and targeted attacks; however, several issues with the OAI software prevented this plan from materializing. Because of this, the latter part of this project shifted its focus to creating a network of sensor nodes to collect data from 5G networks that would allow for further analysis