Reliability
Anomaly detection plays a crucial role in various domains, including but not limited to cybersecurity, space science, finance, and healthcare. However, the lack of standardized benchmark datasets hinders the comparative evaluation of anomaly detection algorithms. In this work, we address this gap by presenting a curated collection of preprocessed datasets for spacecraft anomalies sourced from multiple sources. These datasets cover a diverse range of anomalies and real-world scenarios for the spacecrafts.
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The Partial Discharge - Localisation Dataset, abbreviated: PD-Loc Dataset is an extensive collection of acoustic data specifically curated for the advancement of Partial Discharge (PD) localisation techniques within electrical machinery. Developed using a precision-engineered 32-sensor acoustic array, this dataset encompasses a wide array of signals, including chirps, white Gaussian noise, and PD signals.
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Privacy perception refers to the control individuals have over the use of their data, including determining who can access, share, and utilize it without interference or intrusion. In the context of the Internet of Things (IoT), particularly in Smart Home Data Monetization (SH-DM), users’ data is aggregated and made available to potential service providers to target end users with personalized advertisements.
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New capabilities involving sensors, data collection, and data analysis have enabled innovations in how engineered systems are monitored and maintained. Whereas each new evolution of maintenance philosophies has relied upon the current technological state, this research examines potential future capabilities in the field of prognostics and health management (PHM). PHM algorithms for predicting the estimated time to failure for a system are based on sensor data, physical models, or a combination of both.
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Abstract—Drones or Remote Piloted Aircrafts System (RPAS), have become incredibly popular in a variety of sectors. Critical uses of drones includes agriculture, delivery system and surveillance etc. As technology advances, the reliability of drone components becomes increasingly crucial. It is important to analyze the prime reasons of drone flight crashes as it can damage public property and it could also be harmful for human beings. Mechanical breakdowns, human error, battery failure, wildlife hazards could be one of the reasons for the flight crashes.
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The dataset includes on-state saturation voltage information for eight samples under four different test conditions. Each Excel file consists of two data columns: one for cycle numbers and the other for on-state saturation voltage. Although these data were collected during the power cycling test at the maximum junction temperature, the effect of temperature increase in the on-state voltage has been compensated. Namely, the provided on-state voltage has been unified to the corresponding to the respective 125°C or 150°C.
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The Transport-level pAcket RouTing ANalysis Tool for Cloud-native Applications (TARTAN) Dataset contains TARTAN/HiPerConTracer Traceroute runs between an endpoint in Oslo, Norway and the public Comprehensive TeX Archive Network (CTAN, https://www.ctan.org) and Comprehensive R Archive Network (CRAN, https://cran.r-project.org) mirror we
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Social Media Big Dataset for Research, Analytics, Prediction, and Understanding the Global Climate Change Trends is focused on understanding the climate science, trends, and public awareness of climate change. The use of dataset for analytics of climate change trends greatly helps in researching and comprehending global climate change trends.
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This data collection focuses on capturing user-generated content from the popular social network Reddit during the year 2023. This dataset comprises 29 user-friendly CSV files collected from Reddit, containing textual data associated with various emotions and related concepts.
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