Data, Volume 9, Issue 5 (May 2024) – 6 articles

The described data set contains features from the machine control of a five-axis milling machine. The features were recorded during thirteen series productions. Each series production includes a changeover process in which the machine was set up for the production of a different product. In addition to the timestamps and the twenty recorded features derived from Numerical Control (NC) variables, the data set also contains labels for the different production phases. For this purpose, up to 23 phases were assigned, which are based on a generalized milling process. The data set consists of thirteen .csv files, each representing a series production. The data set was recorded in a production company in the contract manufacturing sector for components with real series orders in ongoing industrial production. Full article

In this work, we present and describe a spectral library (SL) with 15 vascular plant species from Montesinho Natural Park (MNP), a protected area in Northeast Portugal. We selected species from the vascular plants that are characteristic of the habitats in the MNP, based on their prevalence, and also included one invasive species: Alnus glutinosa (L.) Gaertn, Castanea sativa Mill., Cistus ladanifer L., Crataegus monogyna Jacq., Frangula alnus Mill., Fraxinus angustifolia Vahl, Quercus pyrenaica Willd., Quercus rotundifolia Lam., Trifolium repens L., Arbutus unedo L., Dactylis glomerata L., Genista falcata Brot., Cytisus multiflorus (L’Hér.) Sweet, Erica arborea L., and Acacia dealbata Link. We collected spectra (300–2500 nm) from five records per leaf and leaf side, which resulted in 538 spectra compiled in the SL. Additionally, we computed five vegetation indices from spectral data and analysed them to highlight specific characteristics and differences among the sampled species. We detail the data repository information and its organisation for a better understanding of the data and to facilitate its use. The SL structure can add valuable information about the selected plant species in MNP, contributing to conservation purposes. This plant species SL is publicly available in Zenodo platform. Full article

This study presents an extensive collection of data on the aerodynamic behavior at a low Reynolds number and geometric coefficients for 2900 airfoils obtained through the class shape transformation (CST) method. By employing a verified OpenFOAM-based CFD simulation framework, lift and drag coefficients were determined at a Reynolds number of 10⁵. Considering the limited availability of data on low Reynolds number airfoils, this dataset is invaluable for a wide range of applications, including unmanned aerial vehicles (UAVs) and wind turbines. Additionally, the study offers a method for automating CFD simulations that could be applied to obtain aerodynamic coefficients at higher Reynolds numbers. The breadth of this dataset also supports the enhancement and creation of machine learning (ML) models, further advancing research into the aerodynamics of airfoils and lifting surfaces. Full article

Hancheng is located in the eastern part of China’s Shaanxi Province, near the west bank of the Yellow River. It is located at the junction of the active geological structure area. The rock layer is relatively fragmented, and landslide disasters are frequent. The occurrence of landslide disasters often causes a large number of casualties along with economic losses in the local area, seriously restricting local economic development. Although risk assessment and deformation mechanism analysis for single landslides have been performed for landslide disasters in the Hancheng area, this area lacks a landslide traces database. A complete landslide database comprises the basic data required for the study of landslide disasters and is an important requirement for subsequent landslide-related research. Therefore, this study used multi-temporal high-resolution optical images and human-computer interaction visual interpretation methods of the Google Earth platform to construct a landslide traces database in Hancheng County. The results showed that at least 6785 landslides had occurred in the study area. The total area of the landslides was about 95.38 km², accounting for 5.88% of the study area. The average landslide area was 1406.04 m², the largest landslide area was 377,841 m², and the smallest landslide area was 202.96 m². The results of this study provides an important basis for understanding the spatial distribution of landslides in Hancheng County, the evaluation of landslide susceptibility, and local disaster prevention and mitigation work. Full article

Legitimate identification of devices is crucial to ensure the security of present and future IoT ecosystems. In this regard, AI-based systems that exploit intrinsic hardware variations have gained notable relevance. Within this context, on-chip sensors included for monitoring purposes in a wide range of SoCs remain almost unexplored, despite their potential as a valuable source of both information and variability. In this work, we introduce and release a dataset comprising data collected from the on-chip temperature and voltage sensors of 20 microcontroller-based boards from the STM32L family. These boards were stimulated with five different algorithms, as workloads to elicit diverse responses. The dataset consists of five acquisitions (1.3 billion readouts) that are spaced over time and were obtained under different configurations using an automated platform. The raw dataset is publicly available, along with metadata and scripts developed to generate pre-processed T–V sequence sets. Finally, a proof of concept consisting of training a simple model is presented to demonstrate the feasibility of the identification system based on these data. Full article

We describe 20 datasets derived through signal filtering and feature extraction steps applied to the raw time series EEG data of 20 epileptic patients, as well as the methods we used to derive them. Background: Epilepsy is a complex neurological disorder which has seizures as its hallmark. Electroencephalography plays a crucial role in epilepsy assessment, offering insights into the brain’s electrical activity and advancing our understanding of seizures. The availability of tagged training sets covering all seizure phases—inter-ictal, pre-ictal, ictal, and post-ictal—is crucial for data-driven epilepsy analyses. Methods: Using the sliding window technique with a two-second window length and a one-second time slip, we extract multiple features from the preprocessed EEG time series of 20 patients from the Freiburg Seizure Prediction Database. In addition, we assign a class label to each instance to specify its corresponding seizure phase. All these operations are made through a software application we developed, which is named Training Builder. Results: The 20 tagged training datasets each contain 1080 univariate and bivariate features, and are openly and publicly available. Conclusions: The datasets support the training of data-driven models for seizure detection, prediction, and clustering, based on features engineering. Full article