Reliability
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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Quantum computing is one of the most promising technology advances of the latest years. Once only a conceptual idea to solve physics simulations, quantum computation is today a reality, with numerous machines able to execute quantum algorithms. One of the hardest challenges in quantum computing is reliability. Qubits are highly sensitive to noise, which can make the output useless. Moreover, lately it has been shown that superconducting qubits are extremely susceptible to external sources of faults, such as ionizing radiation.
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This paper presents a real-time reconfigurable Cyber-Power Grid Operation Testbed (CPGrid-OT) with multi-vendor, industry-grade hardware, and software.
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The Phoenix Contact Relay (PCR) dataset is provided for the development of algorithms for the analysis of lifetime data. It differs from previously published datasets in the number and complexity of measurements, as well as the scope of units tested and the practical relevance of the data. Thus, it provides an opportunity to develop and evaluate new concepts for predictive maintenance. The PCR data set presented includes the life data of 546 relays with a total of more than 106 million switching cycles, collected over a period of several years at a sampling rate of 10 kHz.
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Power transformers are inevitably subjected to external short circuit impact during their service period. The electromagnetic force generated by the fault current may cause winding destabilization and collapse. The radial buckling of the inner winding accounts for a considerable proportion. Based on the effective contact of the sticks, the traditional analytical methods ignore the manufacturing deviation and operation impact (MDOI) characterized by assembly gaps and insulation shrinkage.
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This paper investigates the prescribed performance control (PPC) problem for a class of nonlinear strict-feedback systems with sensor/actuator faults. A shifting function is introduced to modify the output tracking error generated by the practically measured system state, based on which an improved PPC method is proposed to achieve the convergence of output tracking error to the prescribed region, and this convergence is shown to be independent of the initial tracking condition and insusceptible to sensor/actuator faults.
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A synthetic data for low power (P ≤10 mW) InGaAsP MQW-DFB lasers operating at a wavelength (λ) ranging from 1.53 to 1.57 µm at a case temperature laying between -40 ℃ to 85 ℃ with side mode suppression ratio of more than 35 dB is generated and can be used for laser lifetime prediction using machine learning based approaches.
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