Timothy has helped provide CEOs and CFOs with deep-dive analytics, providing beautiful stories behind the numbers, graphs ... the occurrence of sampling errors. Random sampling establishes ...

We propose a sampling method on OSNs, based on a Metropolis-Hastings Random Walk (MHRW) algorithm. In this regard, we have developed a social explorer in order to collect random samples from Facebook.

Currently, the only reliable diagnostic tool is liver biopsy, which is limited by its invasiveness, poor acceptability, sampling errors, and high cost (5 ... Some alternative methods, such as random ...

Abstract: Graph sampling is frequently used to address scalability issues when analyzing large graphs. Many algorithms have been proposed to sample graphs, and the performance of these algorithms has ...

Here, we develop a pathway sampling method via swarm intelligence and graph theory and demonstrate that our PALLAS method is an effective tool to help understand phase transformations in solid-state ...

Telerehabilitation Market Digital healthcare, personalized remote therapy, and increasing demand for accessible rehabilitation services are ...

The Central Limit Theorem is useful when analyzing large data sets because it assumes that the sampling distribution ... from a large group of independent random samples converges to the true ...

This useful study shows a protective role of type 1 IFN during Mycobacterium tuberculosis infection. It shows that the type 1 IFN response in human skin TST inversely correlates with TB severity, ...

Osteogenic differentiation is essential for bone development, metabolism, and repair; however, the underlying regulatory relationships among genes remain poorly understood. To elucidate the ...