Reliability

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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753 Views

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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777 Views

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 paper presents the reliability study on field-aged photovoltaic connectors of different makes, collected from solar PV plants situated in different regions across India, each characterized by diverse climatic conditions having an operational life of two to ten years. A series of tests conforming to IEC 62852 incorporating C-AST is conducted on connectors encompassing both field-aged and control samples. Thereafter these samples and new field-aged samples underwent SEM for further analysis.

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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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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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