BUSCADOR RECOLECTA

The dataset contains the following files: (1) readme.txt, it is a text file including details about the content of the dataset; (2) Measurement in ARSD_SMS_Data.xls, it is a MS Excel file containing the data used in the analysis of the primary studies, reported in Section 4 of the paper; and, (3) Metrics in ARSD.pdf, it is pdf file containing the complete list of metrics reported in the different primary studies. The metrics are classified into the following categories: QR metrics, QMIs, and QMI metrics. In the MS Excel file, the data is organised in separated sheets: (a) RQ1 - Literature characterisation; (b) RQ2 - QR Metrics, where QR refers to Quality Requirements; (c) RQ3 - QMI, where QMI refers to Quality Management Indicators; (d) RQ3 - Tools, corresponding to the reported tools used to manage QMIs; and, (e) RQ3 - QMI Metrics., This dataset has been used to generate part of the results included in the manuscript: “Quality Measurement in Agile and Rapid Software Development: A Systematic Mapping”, submitted to the Information and Software Technology journal (IST) at the time of publishing this dataset. The paper reports the results of a systematic mapping study surveying the literature related to quality requirements management through metrics in agile and rapid software development processes. The dataset contains the data extracted from the primary studies that was used in the analysis phase of the study and reported in the results section of the paper. The data extracted from the primary studies has been complemented with some data used for specific purposes, e.g. during the analysis phase, we included the list of companies collaborating in the paper analysing the authors’ affiliations to understand the level of implication of companies in the field. Complementing the data analysed, the dataset includes some detailed results that are not included in the body of the paper, i.e., the list of metrics reported in the selected primary studies.

This file includes data on system vertical and lateral stiffness of stainless steel frames under gravity and gravity plus wind load scenarios obtained from the finite element simulations carried out on six stainless steel frames.

Numerical Model for a 19th Century Hydrometric (Case 1: 1000 L/s inlet flow). Aquests datasets són els models numèrics que corresponen als 6 casos de simulacions fetes amb el software de CFD anomenat Flow3D.

Data was generated using the general purpose finite element software ABAQUS and performing advanced nonlinear analyses. The database is comprised of ultimate load factors corresponding to different random samples of six different nominal stainless steel frames under gravity and wind load combinations. The values of the random variable assignments are given for each case. The full details of the finite element model can be found in: Arrayago, I.; Rasmussen, K.J.R.; Zhang, H. System-based reliability analysis of stainless steel frames subjected to wind loads. "Structural Safety", July 2022, vol. 97, art. No. 102211. DOI: https://doi.org/10.1016/j.strusafe.2022.102211

Data associated with the study called "Selectively targeting tumorigenicity in osteosarcoma". Each file corresponds to the raw data of one of the figures of the paper

This file includes finite element simulation data (ultimate load factors) carried out on 60 steel and stainless steel frames, including regular and irregular frame configurations with different section sizes. Ultimate load factors corresponding to different initial imperfection combinations are included.

These data are associated to the paper with the same title and are structured according to the figures in the paper. These data correspond to the research results of the WP3 of the European Project 4D-POLYSENSE., The present dataset reports the scientific results corresponding to a scientific study where a bidimensional (2D) polypropylene flexible mesh material has been converted into a fourth dimension (4D) dynamic system. The platform is composed by a fibres of isotactic polypropylene (iPP) mesh coated with thermosensitive poly(N-isopropylacrylamide-co-N,N'-methylene bis(acrylamide) (PNIPAAm-co-MBA) hydrogel, and undergoes variations in its geometry by reversible folding/unfolding behaviour. Folding and unfolding motion in aqueous solution of bilayer and monolayer systems composed by two or one layer of hydrogel, respectively, are reported in the present dataset. Furthermore, an infrared thermographic camera and an optical microscope were used to evaluate the macroscopic and microscopic structure stimulus response in air. Additionally, PP-g-PNIPAAm meshes showed an increase in the mechanical properties (bursting strength) with respect to the uncoated mesh.

We have created a representative dataset based on the collection of different traffic metrics from VANET simulations in urban scenarios. The five collected metrics that compose the dataset used to train and test our ML-based forwarding algorithm are available bandwidth, distance to destination, vehicles’ density, MAC layer losses, and vehicle’s trajectory. Notice that those metrics are gathered by the vehicles from the beacons periodically interchanged with the vehicles in their neighborhood (i.e., with vehicles within their transmission range). This way, nodes have local knowledge of the VANET, according to the decentralized nature inherent in VANETs.

Aportació de dades globals de la recerca a la Catalunya Central, facilitades per la majoria d’institucions membres de l’observatori.

Using a previous mechanical characterization of two types of material, several lab-test work have been done. The data shows the particle size distribution of these tests, all the inputs and the model simulation presented in the related paper to this data base. The new mathematical approach use the operative conditions and the feed particle size distribution to obtain a product, which is compared with the lab-test results, An improved approach is presented to model the product particle size distribution resulting from grinding in high-pressure roll crusher with the aim to be used in standard high-pressure grinding rolls (HPGR). This approach uses different breakage distribution function parameter values for a single particle compression condition and a bed compression condition. Two materials were used for the experiments; altered Ta-bearing granite and a calc-silicate tungsten ore. A set of experiments was performed with constant operative conditions, while varying a selected condition to study the influence of the equipment set-up on the model. The material was comminuted using a previously determined specific pressing force, varying the feed particle size, roll speed and the static gap. A fourth group of experiments were performed varying the specific pressing force. Experimental results show the high performance of the comminution in a high-pressure environment. The static gap was the key in order to control the product particle size. A mathematical approach to predict the product particle size distribution is presented and it showed a good fit when compared to experimental data. This is the case when a narrow particle size fraction feed is used, but the fit became remarkably good with a multi-size feed distribution. However, when varying the specific pressing force in the case of the calc-silicate material, the results were not completely accurate. The hypothesis of simultaneous single particle compression and bed compression for different size ranges and with different parameters of the distribution function was probed and reinforced by various simulations that exchanged bed compression parameters over the single particle compression distribution function, and vice versa.