Abstract: A ferroelectric memory device and a semiconductor die are provided. The ferroelectric memory device includes a gate electrode; a channel layer, overlapped with the gate electrode; source/drain contacts, in contact with separate ends of the channel layer; a ferroelectric layer, lying between the gate electrode and the channel layer; and a first insertion layer, extending in between the ferroelectric layer and the channel layer, and comprising a metal carbonitride or a metal nitride.

Abstract: A device comprises a first transistor, a second transistor, a first contact, and a second contact. The first transistor comprises a first gate structure, first source/drain regions on opposite sides of the first gate structure, and first gate spacers spacing the first gate structure apart from the first source/drain regions. The second transistor comprises a second gate structure, second source/drain regions on opposite sides of the second gate structure, and second gate spacers spacing the second gate structure apart from the second source/drain regions. The first contact forms a first contact interface with one of the first source/drain regions. The second contact forms a second contact interface with one of the second source/drain regions. An area ratio of the first contact interface to top surface the first source/drain region is greater than an area ratio of the second contact interface to top surface of the second source/drain region.

Abstract: The present invention disclose an iris recognition method, which utilizes a matching pursuit algorithm to simplify the extraction and reconstruction of iris features and reduce the memory space required by each iris feature vector without the penalty of recognition accuracy. The iris recognition method of the present invention comprises an iris-localization component and a pattern matching component. The iris-localization component locates the iris region via the color difference between different portions of the eyeball. The primary iris features are extracted from iris information and transformed into a sequence of iris feature vectors by a matching pursuit algorithm. Thus, the iris image can be represented by a sequence of atoms, and each atom contains base, amplitude and location. Then, the comparison between the feature vectors of two irises is performed to determine whether the two irises match.