Sentence examples for machine have demonstrated from inspiring English sources

Mr. Bush and his political machine have demonstrated again and again that what most of us experience daily as being the real world has nothing to do with how the machine chooses and acts.

Early operation of these machines has demonstrated the importance of the details of beam initial conditions in determining the downstream evolution.

However, recent studies showed that vertebral fracture assessment (VFA) using dual-energy X-ray absorptiometry (DXA) machines has demonstrated great utility for vertebral visualization [ 16- 18].

Applications to the volumetric error measurement of a robot and two types of machine tools have demonstrated the high-precision capability of this 3D laser ball bar.

Simulations results performed on the basis of two versions of the sliding-mode controller and applied to a multi-machine model have demonstrated better performances when compared to an Hamiltonian passive controller design.

Electronic voting machines also have demonstrated vulnerabilities, making it imperative to cross-check them versus the paper trail wherever possible.

Machine learning techniques have demonstrated progress, but the lack of underlying formal semantics impedes the potential for sharing and reusing classifications across systems.

Among them, machine learning-based methods have demonstrated their advantage and showed better performance than the other two categories of methods when a large annotated corpus is available.

In a new paper, researchers from MIT's Computer Science and Artificial Intelligence Lab and the machine-learning startup PatternEx have demonstrated an artificial-intelligence platform called AI² that can predict 85percentt of cyber-attacks, by continuously incorporating input from human experts.

Recent studies [1] have demonstrated that machine learning-based approaches have the potential to predict compound-protein interactions on a large scale by learning from limited interaction data supplemented with information on the similarity among compounds and among proteins.

We have demonstrated a machine learning method of processing imperfect tomographic reconstructions which provides for a much more accurate image classification than conventional thresholding and which does not require altering the source data with image filters before processing.