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TSMC was founded in Taiwan in 1987 by Morris Chang as the world's first dedicated semiconductor foundry. It has long been the leading company in its field. [15] [16] When Chang retired in 2018, after 31 years of TSMC leadership, Mark Liu became chairman and C. C. Wei became Chief Executive.
Eigenvalues and eigenvectors. In linear algebra, it is often important to know which vectors have their directions unchanged by a given linear transformation. An eigenvector ( / ˈaɪɡən -/ EYE-gən-) or characteristic vector is such a vector. Thus an eigenvector of a linear transformation is scaled by a constant factor when the linear ...
MEDICIS. Produces isotopes for medical purposes. The Large Hadron Collider ( LHC) is the world's largest and highest-energy particle collider. [1] [2] It was built by the European Organization for Nuclear Research (CERN) between 1998 and 2008 in collaboration with over 10,000 scientists and hundreds of universities and laboratories across more ...
Excess steam from the drywell enters the wetwell water pool via downcomer pipes. SFP: spent fuel pool area. SCSW: secondary concrete shield wall. The Fukushima nuclear accident was a major nuclear accident at the Fukushima Daiichi nuclear power plant in Ōkuma, Fukushima, Japan which began on March 11, 2011.
The resistivity can be expressed using the SI unit ohm metre (Ω⋅m) — i.e. ohms multiplied by square metres (for the cross-sectional area) then divided by metres (for the length).Both resistance and resistivity describe how difficult it is to make electrical current flow through a material, but unlike resistance, resistivity is an intrinsic property and does not depend on geometric ...
Top: Lightning and neon lights are commonplace generators of plasma. Bottom left: A plasma globe, illustrating some of the more complex plasma phenomena, including filamentation. Bottom right: A plasma trail from the Space Shuttle Atlantis during re-entry into Earth's atmosphere, as seen from the International Space Station. Plasma (from ...
Principal component analysis ( PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing . The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.
