Abstract: A memory device includes an input unit configured to receive a plain text and output plain blocks and CTS plain block, a multi-core unit including a plurality of encryption/decryption cores configured to encrypt each of the plain blocks provided from the input unit and output cipher blocks in accordance with control of an encryption/decryption core control unit, a CTS core unit including a CTS core configured to encrypt the CTS plain block provided from the input unit into a CTS cipher block, and an output unit configured to receive the cipher blocks and the CTS cipher block and output a cipher text. The CTS plain block is generated through a CTS calculation based on the plain text.

Abstract: Provided is a power management device including a first power domain operating in a sleep mode consuming minimal power, and a second power domain turned on exclusively when a wake signal is received from an external device within a communication range of the first power domain, wherein the first power domain includes an always-on Digital Low-DropOut (DLDO), and the second power domain includes a main Low-DropOut (LDO), and split sequence control is performed on power management in the first power domain and the second power domain.

Abstract: An imaging lens system includes a first lens group, an optical path conversion element, and a second lens group arranged in order from an object side. An optical axis of the second lens group is disposed eccentrically in a direction with respect to a geometric optical axis of the optical path conversion element.

Abstract: An apparatus and method for predicting a friction coefficient of a road surface are disclosed. The apparatus includes a microphone that obtains a sound signal around a tire mounted on a vehicle, and a controller that estimates a state and a type of the road surface and a degree of tire wear corresponding to the sound signal around the tire based on a first deep learning model, estimates a peak adjustment factor and an initial inclination adjustment factor of a friction coefficient curve corresponding to the state and the type of the road surface and the degree of tire wear based on a second deep learning model, and predicts the friction coefficient based on the peak adjustment factor and the initial inclination adjustment factor of the friction coefficient curve.