This web application provides free and open access for the broader research community to the experimental planning utilities that are incorporated into ThermoData Engine (TDE) [J. Chem. Inf. Model. 2005, 45, 816-838]. TDE provides recommendations for the relative merit of a proposed measurement via assessment of the existing body of knowledge, including availability of experimental thermophysical property data, variable ranges studied, associated uncertainties, state of prediction methods, and parameters for deployment of prediction methods.

NIST X-ray Photoelectron Spectroscopy Database XPS contains over 33,000 data records that can be used for the identification of unknown lines, retrieval of data for selected elements (binding energy, Auger kinetic energy, chemical shift, and surface or interface core-level shift), retrieval of data for selected compounds (according to chemical name, selected groups of elements, or chemical classes), display of Wagner plots, and retrieval of data by scientific citation.

We present correlations found between the tensile strengths of yarns extracted from armor and the V50 ballistic limit when significant degradation of the mechanical properties of the extracted yarns was observed. These studies provided the basis for a validation dataset from which we compare the experimentally measured V50 ballistic limit results to the theoretically predicted V50 results. This approach is promising for the development of a tool for fielded-armor-performance surveillance relying upon mechanical testing of armor coupon samples.

The Web Thermo Tables (WTT) are a collection of critically evaluated thermodynamic property data for pure compounds with a primary focus on organics. These data were generated through dynamic data analysis, as implemented in the NIST ThermoData Engine software package. Also included are some critically evaluated data from the historical TRC Thermodynamic Tables archive. The Professional Edition contains information on over 28,000 compounds.

DICOM files are given for 11 CT scans which were used in a research article. Each scan contains about 1250 slices with 512x512 gray scale images, each in its own directory. The low number slices contain the diapers in the order D5 ... D1, then the vials of powder are contained in the order V11 ... V2. The symbols correspond to the injected masses which are given in the paper and which are repeated here in a file called "mass.txt". There is also a file "README.txt" which describes the directory structure.

This benchmark aims to provide tools to evaluate 3D Interest Point Detection Algorithms with respect to human generated ground truth.

Using a web-based subjective experiment, human subjects marked 3D interest points on a set of 3D models. The models were organized in two datasets: Dataset A and Dataset B. Dataset A consists of 24 models which were hand-marked by 23 human subjects. Dataset B is larger with 43 models, and it contains all the models in Dataset B. The number of human subjects who marked all the models in this larger set is 16.

This benchmark aims to provide tools to evaluate 3D Interest Point Detection Algorithms with respect to human generated ground truth. Please refer to the paper for more information about this benchmark: "Helin Dutagaci, Chun Pan Cheung, Afzal Godil: Evaluation of 3D interest point detection techniques via human-generated ground truth", The Visual Computer, 2012.

Objective: The objective of this track is to evaluate the performance of 3D shape retrieval approaches on Generic 3D Dataset.

Introduction: With the increasing number of 3D models are created every day and stored in databases, effectively searching a 3D repository for 3D shapes which are similar to a given 3D query model has become an important area of research. Benchmarking allows researchers to evaluate the quality of the results of different 3D shape retrieval approaches.

The objective of this SHREC'12 track is to evaluate the performance of different sketch-based 3D model retrieval algorithms using both hand-drawn and standard line drawings sketch queries on a watertight 3D model dataset.

**** Note that this SRD is superseded by SRD 64 Version 4.0. ****