Reliability

The REST (REpresentational State Transfer) paradigm has become essential for designing distributed applications that leverage the HTTP protocol, enabling efficient data exchange and the development of scalable architectures such as microservices. However, selecting an appropriate framework among the myriad available options, especially given the diversity of emerging execution environments, presents a significant challenge. Often, this decision neglects crucial factors such as performance and energy efficiency, favoring instead developer familiarity and popularity within the industry.

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This dataset is shared for capacitor C and ESR estimation using convolution neural network. The dataset is collected in a experimental modular moultilevel converter, which includes the capacitor voltage at low and medium frequency band, and the arm current. Wavelet transform is used to transfer the time series data to images, which present the inherent data features to image patterns. In a degraded capacitor, the C decreases and the ESR increases, which result in different image patterns.

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Putting together software that lets patients make their appointments and software that helps them book appointments is making healthcare centres more accessible and useful. These systems put all of the appointment bookings in one place, so patients can make appointments across many areas and specialties. Standardizing the planning process for healthcare workers can help them save time and money by streamlining their work and lowering the costs of running their businesses.

 

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This data repository contains test data and corresponding test code for evaluating the performance of a machine learning model. The dataset includes 950 labeled samples across 7 different classes. The test code provides implementations of several common evaluation metrics, including accuracy, precision, recall, and F1-score. This resource is intended to facilitate the benchmarking and comparison of different machine learning algorithms on a standardized task.

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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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The Reflection Server Tuning dataset contains HiPerConTracer latency measurements performed in a lab setup. The purpose of the dataset is to measure the latency and jitter effects of  firewalls and Linux kernel tuning.

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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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