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This dataset consists of a simulated exponential distribution data, featuring n=5000n = 5000n=5000 data points, each generated with a rate parameter of 9. The exponential distribution is commonly used to model the time between events in a Poisson process, where the rate parameter indicates the average number of events occurring in a unit of time. In this case, the relatively high rate parameter of 9 suggests that events are expected to happen frequently.

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.

Most existing graph keyword search works assume that the graph data is complete and clean, that is, there are no missing information (such as keywords or edges) and contaminated information (such as keywords) on the graph. However, real-world graphs often suffer from missing or being contaminated, making the keyword search on graphs much more challenging. We provide this dataset for the keyword search on dirty graphs.

Electrical Impedance Tomography system measures change in path conductivity of a cross section of ROI. ROI is created by surrounding a cross-section by metal electrodes. These inject microlevel charges into ROI and attenuation due to ROI material is reconstructed. 

X-ray CT is a well known non destructive imaging technology used primarily in medical applications. However, industrial CT are used for industrial applciations. 

Computational Fluid dynamics assist flow simulation of fluid channels.