Filter Results
3604 results
X-ray diffraction and energy dispersion X-ray fluorescence data for cathode materials of Li-ion batteries. Samples named as Blend, Cath1, Cath2, Cath3.
Data Types:
  • Other
  • Software/Code
  • Image
  • Dataset
The files uploaded include working tables related to the bycatch mitigation and outcomes (Table A.1); seal exclusion device (SED) trials with problems encountered and how they were solved (Table A.2); square mesh net barrier trials (Table A.3); underwater footage analysed (Table A.4) and the current license conditions regarding SED requirements (Fig.A.1).
Data Types:
  • Slides
  • Dataset
  • Document
The included tests were performed at McMaster University in Hamilton, Ontario, Canada by Dr. Phillip Kollmeyer (phillip.kollmeyer@gmail.com). If this data is utilized for any purpose, it should be appropriately referenced. A brand new 3Ah LG HG2 cell was tested in an 8 cu.ft. thermal chamber with a 75amp, 5 volt Digatron Firing Circuits Universal Battery Tester channel with a voltage and current accuracy of 0.1% of full scale. these data are used in the design process of an SOC estimator using a deep feedforward neural network (FNN) approach. The data also includes a description of data acquisition, data preparation, development of an FNN example script. The test data, or similar data, has been used for some publications, including: C. Vidal, P. Kollmeyer, M. Naguib, P. Malysz, O. Gross, and A. Emadi, “Robust xEV Battery State-of-Charge Estimator Design using Deep Neural Networks,” in Proc WCX SAE World Congress Experience, Detroit, MI, Apr 2020 C. Vidal, P. Kollmeyer, E. Chemali and A. Emadi, "Li-ion Battery State of Charge Estimation Using Long Short-Term Memory Recurrent Neural Network with Transfer Learning," 2019 IEEE Transportation Electrification Conference and Expo (ITEC), Detroit, MI, USA, 2019, pp. 1-6.
Data Types:
  • Other
  • Software/Code
  • Slides
  • Tabular Data
  • Dataset
  • Document
  • Text
  • File Set
Retention data used in publications in or submitted to Journal of Chromatography A with A. R. Horner as first author. Retention data for ~ 100 compounds on a Waters BEH C-18 column in acidic acetonitrile/water mobile phases at phase ratio and temperatures giving a range of k for each compound about 1 - 100. These are in the CSV file "RetentionData". The compounds/solutes are identified by number. The correspondence between the number and the compound name is in "Compound List and Conditions". Enthalpies for the compounds and functional group counts are in FGEnthalpyData.xlsx
Data Types:
  • Other
  • Tabular Data
  • Dataset
  • Document
We provide several cases of audio recordings of qualitative research interviews, as well as raw quantitative research data, as well as informed consent forms and scale templates.
Data Types:
  • Other
  • Software/Code
  • Dataset
  • Document
The authors universal (meta-)logical reasoning approach is demonstrated and discussed with a challenge puzzle in epistemic reasoning: the wise men puzzle. The presented solution puts a particular emphasis on the adequate modeling of common knowledge.
Data Types:
  • Other
  • Dataset
  • Document
  • File Set
This is the code to accompany the paper "On The Radon--Nikodym Spectral Approach With Optimal Clustering". This is a software implementing the algorithms of interpolation, classification, and optimal clustering based on the Lebesgue quadrature technique. Whereas in a Bayesian approach new observations change only outcome probabilities, in the Radon-Nikodym approach not only outcome probabilities but also the probability space change with new observations. This is a remarkable feature of the approach: both the probabilities and the probability space are constructed from the data. A regular PCA variation expansion depends on attributes normalizing. The PCA variation expansion in the Lebesgue quadrature basis is unique thus does not depend on attributes scale, moreover it is invariant relatively any non-degenerated linear transform of input vector components.
Data Types:
  • Other
  • Dataset
  • File Set
In computer security, network botnets still represent a major cyber threat. Concealing techniques such as the dynamic addressing and the Domain Name Generation Algorithms (DGAs) require an improved and more effective detection process. To this extent, this data descriptor presents a collection of over 30 million manually-labelled algorithmically generated domain names decorated with a feature set ready-to-use for Machine Learning analysis. This proposed data set enables researchers to move forward the data collection, organization and pre-processing phases, eventually enabling them to focus on the analysis and the production of Machine-Learning powered solutions for network intrusion detection. To be as exhaustive as possible, 50 among the most important malware variants have been selected. Each family is available both as list of domains and as collection of features. To be more precise, the former is generated by executing the malware DGAs in a controlled environment with fixed parameters, while the latter is generated by extracting a combination of statistical and Natural Language Processing (NLP) metrics.
Data Types:
  • Other
  • Software/Code
  • Tabular Data
  • Dataset
  • Document
  • Text
  • File Set
  • Audio
This dataset support our methods publication recently accepted in Ecosystems Manuscript highlights • Stable isotope analysis suggests δ13C-CH4 oxidation and fractionation occurs during transport • Substantial fine-scale vertical and radial heterogeneity identified in tree stem CH4 emissions • Novel smartphone 3D photogrammetry can more accurately estimate the tree stem surface area compared to traditional methods • Fine-scale sampling method shows 86-89% of methane flux emanates from the lower 30cm of wetland forest tree stems   Manuscript Abstract: Tree stem methane emissions are gaining increasing attention as an overlooked atmospheric source pathway. Existing methods for measuring tree stem greenhouse gas fluxes and isotopes may provide robust integrated emission estimates, but due to their coarse resolution, the capacity to derive insights into fine-scale dynamics of tree stem emissions are limited. We demonstrate and field-test an alternative method that is Small, Nimble, In situ and allows for Fine-scale Flux (‘SNIFF’) measurements, on complex and contrasting stem surfaces. It is light weight and therefore suitable to remote field locations enabling real time data observations allowing for field-based data driven sampling regimes. This method facilitated novel results capturing fine-scale vertical and radial methane flux measurements (5cm increments) and revealed: (1) 86-89% of methane emissions emanated from the lower 30cm of sampled wetland tree species; (2) uncovered clear vertical and horizontal trends in δ13C-CH4 possibly due to fractionation associated with oxidation and mass-dependant fractionation during diffusive transport; and (3) demonstrated how substantial radial heterogeneity can occur. We also compared a variety of upscaling approaches to estimate methane flux per tree when using this method, including novel smartphone 3D photogrammetry, that resulted in a substantially higher stem surface area estimation (>16 to 36%) than traditional empirical methods. Utilising small chambers with high radial and vertical resolution capabilities may therefore facilitate future assessments into the drivers, pathways, oxidation sinks and magnitude of various tree stem greenhouse gas emissions, and compliment previous broad-scale sampling techniques.
Data Types:
  • Other
  • Software/Code
  • Image
  • Tabular Data
  • Dataset
As part of a research into new techniques for purifying recycled aluminium, a novel electromagnetic apparatus had been developed for the purpose of investigating in real-time the separation mechanisms of detrimental inclusions in aluminium alloy melts under alternating magnetic fields. The magnetic coil was designed based on the Helmholtz coil design. A viewing gap was designed for in-situ imaging studies using synchrotron X-rays. The gap was designed to maintain a uniform magnetic field in the central region where a sample is positioned. The current setup for the magnetic coil pair is able to produce a peak magnetic flux density of ~10 mT at a frequency of 25 kHz. A separate electrical resistance furnace, designed specifically to fit within the magnetic coil, was used to control the heating (up to ~850°C) and cooling of the samples. After systematic tests, commissioning, the apparatus was used in a number of in-situ and ex-situ experiments.
Data Types:
  • Other
  • Software/Code
  • Tabular Data
  • Dataset
  • Document