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opencc-zeroJun 2024View details →

A synthetic dataset for the exploration of survival and classification models: prediction of heart attack or stroke within a 10-year follow-up period

<div> <div></div> </div> <div> <div> <div> Machine learning methodologies are increasingly popular in health care research. This shift to integrated data science approaches necessitates professional development of the existing health care data analyst workforce. To enhance a smooth transition, educational resources need to be developed. Barriers to accessing real healthcare datasets, vital for health care data analyses methodologies training purposes, include financial, ethical and patient confidentiality concerns. Synthetic datasets mimicking real-world complexities offer a simpler solution. We present a synthetic dataset which mirrors routinely collected primary care data on heart attack and stroke among the adult population. The data incorporates much of the practical challenges encountered in routinely collected primary care systems such as missing data, informative censoring, interactions, variable irrelevance, and noise and can be used for training in methods which handle these difficulties. The intent is for the user to build models of heart/stroke risk using survival-based methodologies. By sharing this synthetic dataset openly, our goal is to contribute a transformative asset for professional training in health and social care data analysis. The dataset covers demographics, lifestyle variables, comorbidities, systolic blood pressure, hypertension treatment, family history of cardiovascular diseases, respiratory functioning, and experience of heart-attack and/or stroke. This initiative aims to bridge the gap in sophisticated healthcare datasets for training, fostering professional development of the health and social care research workforce. This study is funded by the National Institute for Health and Care Research ARC Wessex and the National Centre for Research Methods. The views expressed in this summary are those of the author(s) and not necessarily those of the National Institute for Health and Care Research or the Department of Health and Social Care.   </div> </div> </div>

opencc-by-4.0Nov 2018View details →

Modeling Sulfate Attack in Modern Concrete for Building Sustainable and Resilient Infrastructure

Corresponding data set for Tran-SET Project No. 17CTAM01. Abstract of the final report is stated below for reference: "External sulfate attack is a complex phenomenon and is manifested in the form of large expansion, cracking, and spalling depending on the exposure solution and material constituent properties. Several models were developed in the past to demonstrate sulfate attack mechanisms that account for the diffusion of sulfate ions into the porous concrete and the successive deformation triggered by the chemical reaction and precipitation of expansive agents. However, none of these models accounts for the effect of the migration of solvent water from the low solute concentration solution to high solute concentration solution driven by the osmotic pressure. Osmotic pressure is believed to cause spalling and cracking of concrete substrates coated with semipermeable membrane that prohibits diffusion of ions from the surroundings into the porous body. In order to determine the effect of osmotic pressure on the deformation of concrete exposed to sulfate solution, a coupled poromechanical model has been developed. Sensitivity analysis has been performed to investigate the effect of material constituent properties and exposure solution on the osmotic pressure induced damage propensity of concrete. It has been found that concrete surface can exhibit high instantaneous tensile stress developed by the gradient in the salt concentration between the pore solution and external surroundings."

opencc-by-4.0May 2023View details →

Transfer-Path-Based Hardware-Reuse Strong PUF Achieving Modeling Attack Resilience With >200 Million Training CRPs [DATASET]

This is the CRP dataset for the IEEE TIFS paper titled "Transfer-Path-Based Hardware-Reuse Strong PUF Achieving Modeling Attack Resilience With >200 Million Training CRPs". It contains 2 packages with details as below: Package 1: "CRPs_14k_2048TPs_bit5_bit6.zip" Description: It consists of 2048*3 files, which contains all the CRPs extracted from 2048 TPs with DOA disable. Using these data, we can train each ANN model for each TP(i,j), and the corresponding prediction results are shown in Fig. 14 and Fig. 15 in the paper. - "tdc_stim_i_j.csv" is the 64-bit challenges of TP(i,j). - "tdc_resp_F1_i_j_bit5.csv" is the responses of TP(i,j) with bit(5) of TDC used as PUF response - "tdc_resp_F1_i_j_bit6.csv" is the responses of TP(i,j) with bit(6) of TDC used as PUF response Package 2: "CRPs_DOA_330818x1024_bit5_bit6.zip" Description: It consists of 3 files. Using the dataset, we trained each ANN model for each bit in RSobf, and the prediction results of all the ANN models are shown in Fig.17. Notice that the length of RS is dependent on the specific challenge. Here, only those RS consisting of ≥1024 responses are selected and only the first 1024 bits in the selected RS are used for authentication accordingly. - "chal_330818.csv" is the 330818 64-bit challenges. - "resp_330818x1024_bit5.csv" is the 330818 1024-bit obfuscated response streams (RSobf) extracted from 2048 TPs using bit(5) of TDC. - "resp_330818x1024_bit6.csv" is the 330818 1024-bit RSobf extracted from 2048 TPs using bit(6) of TDC.

opencc-by-4.0Aug 2023View details →

Modeling Attack Resistant Strong PUF Exploiting Stagewise Obfuscated Interconnections With Improved Reliability [DATASET and Source Code]

Thanks for your interest in our work! In order to facilitate your assessment and replication, we provides the dataset and source codes (verilog/python model/matlab) of our work (OIPUF) here.  By the way, our latest work (SOI PUF and cSOI PUF) published in IEEE TIFS (2024) is based on OIPUF.  <blockquote> If you have any questions, please feel free to contact with us: <a href="mailto:chongyaoxu@126.com">chongyaoxu@126.com</a> / <a href="mailto:mklaw@um.edu.mo">mklaw@um.edu.mo</a> Full text about OIPUF can be downloaded from <a href="https://ieeexplore.ieee.org/document/10103139">https://ieeexplore.ieee.org/document/10103139</a> Full text about SOI PUF and cSOI PUF can be downloaded from <a href="https://ieeexplore.ieee.org/document/10458688">https://ieeexplore.ieee.org/document/10458688</a> Source code and FPGA project of SOI PUF and cSOI PUF can be download from <a href="https://github.com/yg99992/SOI_PUF">https://github.com/yg99992/SOI_PUF</a>.  </blockquote>   Matlab code <code>matlab/Generate_OI_block.m</code> This is a matlab manuscript used for generating the verilog code of random OI block. <code>matlab/OIPUF_64x4_placement.m</code> This is a matlab function used for generating XDC file for constraining the placement of (64,4)-OI block <code>matlab/OIPUF_64x8_placement.m</code> This is a matlab function used for generating XDC file for constraining the placement of (64,8)-OI block <code>matlab/OIPUF_placement_example.m</code> An example manuscript used for demonstrating the usage of OIPUF_64x4_placement.m and OIPUF_64x8_placement.m   Python code <code>python/puf_models.py</code> The python models of XOR PUFs and OIPUFs, which can be used to generate CRPs. for example: <pre><code>from puf_models import oi_puf # generate a (64,4)-OIPUF and further use the generated OIPUF to generate 1M CRPs crps, puf_instance = oi_puf.gen_CRPs_PUF(64, 4, 1_000_000)   </code></pre>   <code>python/attack_pypuf.py</code> A manuscript used to conduct to ANN attack on XOR PUF and OIPUF ('pypuf' package should be installed correctly).   Verilog code <code>verilog/OIPUF_64_4/</code> All the verilog files of (64, 4)-OIPUF <code>verilog/OIPUF_64_8/</code> All the verilog files of (64, 8)-OIPUF   CRP datasets extracted from FPGA It consists of 13 CRP files (All the CRPs are extracted from FPGA): <code>FPGA_CRPs/FPGA3_CHAL_100M.csv</code> The 100 million 64-bit challenges <code>FPGA_CRPs/FPGA3_k4_PUF0.csv</code> The 100 million 1-bit responses extracted from (64,4)-OIPUF0 <code>FPGA_CRPs/FPGA3_k4_PUF1.csv</code> The 100 million 1-bit responses extracted from (64,4)-OIPUF1 <code>FPGA_CRPs/FPGA3_k4_PUF2.csv</code> The 100 million 1-bit responses extracted from (64,4)-OIPUF2 <code>FPGA_CRPs/FPGA3_k4_PUF3.csv</code> The 100 million 1-bit responses extracted from (64,4)-OIPUF3 <code>FPGA_CRPs/FPGA3_k4_PUF4.csv</code> The 100 million 1-bit responses extracted from (64,4)-OIPUF4 <code>FPGA_CRPs/FPGA3_k4_PUF5.csv</code> The 100 million 1-bit responses extracted from (64,4)-OIPUF5 <code>FPGA_CRPs/FPGA3_k8_PUF0.csv</code> The 100 million 1-bit responses extracted from (64,8)-OIPUF0 <code>FPGA_CRPs/FPGA3_k8_PUF1.csv</code> The 100 million 1-bit responses extracted from (64,8)-OIPUF1 <code>FPGA_CRPs/FPGA3_k8_PUF2.csv</code> The 100 million 1-bit responses extracted from (64,8)-OIPUF2 <code>FPGA_CRPs/FPGA3_k8_PUF3.csv</code> The 100 million 1-bit responses extracted from (64,8)-OIPUF3 <code>FPGA_CRPs/FPGA3_k8_PUF4.csv</code> The 100 million 1-bit responses extracted from (64,8)-OIPUF4 <code>FPGA_CRPs/FPGA3_k8_PUF5.csv</code> The 100 million 1-bit responses extracted from (64,8)-OIPUF5

opencc-by-4.0Mar 2022View details →

Refinement of an Attacker Model for Attack Paths Generation | Test Dataset

This repository contains the test models and associated tests of the evaluation of the bachelor thesis "Refinement of an Attacker Model for Attack Paths Generation" / German: "Verfeinerung des Angreifermodells und Fähigkeiten in einer Angriffspfadgenerierung". The basis for the model used is the TravelPlaner CaseStudy. The tests for measuring the performance delta are also included. Palladio Bench 5, Java 11 and the following GitHub repositories are used for execution: Analysis: https://github.com/Patrick-Spiesberger/Palladio-Addons-ContextConfidentialityAnalysis_Mitigation Meta model: https://github.com/Patrick-Spiesberger/Palladio-Addons-ContextConfidentialityMetamodell_Mitigation Environment installation is included in the README files. See also the previous work by Maximilian Walter: Analysis: https://github.com/FluidTrust/Palladio-Addons-ContextConfidentiality-Analysis Meta Model: https://github.com/FluidTrust/Palladio-Addons-ContextConfidentiality-Metamodel

opencc-by-4.0Aug 2024View details →

Black-box Membership Inference Attacks against Fine-tuned Diffusion Models

We have provided some fine-tuned model checkpoints and datasets to help readers reproduce the experiments presented in the paper.

opencc-by-4.0Sep 2024View details →

Topologies, Checkpoints, and Configurations for the paper "GVI-RL: Graph-Invariant RL for Attack Paths Discovery using Vulnerabilities Embedded with Large Language Models"

This repository consists of the files related to the paper "GVI-RL: Graph-Invariant RL for Attack Paths Discovery using Vulnerabilities Embedded with Large Language Models". In particular, this repository contains tensorboard logs, topologies, checkpoints, seeds, and results to ensure reproducibility of the results of the paper. The results included are related to the training/validation and hyper-parameters optimization of the outcome multi-label classifier, the GVI-RL agent, and the world model. The data folder contains also the topologies used in the study, the vulnerabilities data used to generate them and the dataset for multi-label classification. The README.md file describes the folders' structure.

opencc-by-4.0Oct 2023View details →

Dataset: Context-based Access Control and Attack Modelling and Analysis

This repository contains the dataset for my PhD thesis "Context-based Access Control and Attack Modelling and Analysis". For the description, please look at the included README.md for further description.

ClinicalTrials.gov32/100

Research on the Early Warning Model of Children Asthma Acute Attack Based on Wearable Wrist Smart Device of Huami

ClinicalTrials.gov study NCT05243667. IPD Sharing: NO. Countries: 1. Publications: 3.

closedIPD-NOFeb 2026View details →

opencc-zeroJan 2021View details →

Caterpillar survival in the city: Attack rates on model lepidopteran larvae along an urban-rural gradient show no increase in predation with increasing urban intensity (Raw Data)

Growing native plants in urban gardens is often promoted as a possible means of increasing lepidopteran populations. However, the efficacy of such efforts has not been well studied. Lepidopterans vary widely in their ability to survive in cities, and the few previous studies of caterpillar abundance or biomass across an urban-rural gradient have yielded mixed results. We placed clay caterpillar models in native plant gardens to assess whether the attack rate on these models varied with degree of urbanization (percent impervious surface within 1 km radius of each garden), and whether responses differed across predator taxa. We also examined how garden characteristics (plant biovolume density, plant species richness) affected probability of attack. Overall, attack rates on these models decreased with increasing impervious surface, although predator taxa varied in their sometimes complex responses. For parasitoid wasps, which accounted for 47% of all attacks, increasing biovolume density increased attack probability at impervious surface levels below 35%, but decreased the probability of attack at higher levels of impervious surface. In contrast, probabilities of attack by both predatory wasps and vertebrates decreased with increasing percent impervious surface, but did not vary with impervious surface for ants and spiders. Predation on caterpillars in urban gardens may be lower than in rural ones; however, this potential increase in survival may be a result of declines in some predator taxa, such as predatory wasps and insectivorous birds. More studies across an urban gradient are needed to measure factors other than predation that influence caterpillar survival in gardens.

opencc-zeroJan 2021View details →

Attack behaviour in naive Gyrfalcons is modelled by the same guidance law as in Peregrines, but at a lower guidance gain

The aerial hunting behaviours of birds are strongly influenced by flight morphology and ecology, but little is known of how this relates to the behavioural algorithms guiding flight. Here we use GPS loggers to record the attack trajectories of captive-bred Gyrfalcons (Falco rusticolus) during their maiden flights against robotic aerial targets, which we compare to existing flight data from Peregrines (Falco peregrinus). The attack trajectories of both species are well modelled by a proportional navigation (PN) guidance law, which commands turning in proportion to the angular rate of the line-of-sight to target, at a guidance gain N. However, naïve Gyrfalcons operate at significantly lower values of N than Peregrines, producing slower turning and a longer path to intercept. Gyrfalcons are less manoeuvrable than Peregrines, but physical constraint is insufficient to explain the lower values of N we found, which may reflect either the inexperience of the individual birds or ecological adaptation at the species level. For example, low values of N promote the tail-chasing behaviour that is typical of wild Gyrfalcons and which apparently serves to tire their prey in a prolonged high-speed pursuit. Likewise, during close pursuit of typical fast evasive prey, PN will be less prone to being thrown off by erratic target manoeuvres at low guidance gain. The fact that low-gain PN successfully models the maiden attack flights of Gyrfalcons suggests that this behavioural algorithm is embedded in a guidance pathway ancestral to the clade containing Gyrfalcons and Peregrines, though perhaps with much deeper evolutionary origins.

zenodo28/100

BiLSTM and BiGRU models layer's view, for detection attack.

SciDraw upload

opencc-by-4.0May 2023View details →

publicJan 2021View details →

Caterpillar survival in the city: Attack rates on model lepidopteran larvae along an urban-rural gradient show no increase in predation with increasing urban intensity (Raw Data)

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