Samsung Electronics Co., Ltd.

Korea University Research and Business Foundation

Korea Institute of Science and Technology

Heejeong Lim

Sanghoon Sull

Seongwook Yoon

Jaehyun Kim

Yuntae Kim

Donghoon Sagong

Hyung-jun Kim

Sanghyeon Kim

Yeon-Su Kim

Hojin Ju

Jaehwan Pi

Jae-Phil Shim

A method of obtaining and imputing missing data and a measurement system having the same are disclosed. The method includes obtaining measurement values of measurement variables, among z variables corresponding to z components of a measurement object, wherein z is a natural number greater than 1, and the z variables of the measurement object include measurement variables and missing variables which are not measured, and the measurement variables are of an amount less than z; generating missing data having the measurement variables with the measurement values and the missing variables with missing values in the z components, wherein each of the missing values is predetermined value indicating that a missing variable has not been measured; generating k pieces of final imputation data having k final imputation values, by using the missing data, wherein k is a natural number greater than 1, each of the k final imputation values are in the z components, and using the missing data includes performing multiple imputations on the missing data; and generating average data having average component values in the z components, wherein each of the average component values in a component is an average value of the k final imputation values of the k pieces of final imputation data in the component, and selecting, in each of the z components, a next measurement variable, wherein a difference value between a final imputation values and an average component value, of the next measurement variable, is larger than a difference value of the missing variables.

Method of obtaining and imputing missing data and measurement system using the same

An electronic device includes a memory storing a plurality of motion prediction models, and a processor configured to estimate a current pose of the electronic device based on external data; predict a first motion of the electronic device at a future first prediction time through a first model in which the plurality of motion prediction models are combined for the future first prediction time, and calculate a first pose of the electronic device at the first prediction time based on the current pose and the first motion; and predict a second motion of the electronic device at a future second prediction time through a second model in which the plurality of motion prediction models are combined for the future second prediction time, and calculate a second pose of the electronic device at the second prediction time based on the first pose and the second motion.

Electronic device for predicting pose and operating method thereof

A method for manufacturing a semiconductor device includes: forming a sacrificial layer on a first substrate, the sacrificial layer being made of a material whose lattice constant is different from that of germanium (Ge) by a preset threshold or below; forming a germanium (Ge) layer on the sacrificial layer; forming an insulation layer on a second substrate; bonding the germanium (Ge) layer onto the insulation layer; and removing the sacrificial layer and the first substrate by etching the sacrificial layer in a state where the germanium (Ge) layer is bonded to the insulation layer. In this method, a germanium-on-insulator (GeOI) structure having various surface orientations may be formed by means of epitaxial lift-off (ELO), and a strain may be applied to the germanium (Ge) layer using a lattice constant of the sacrificial layer.

Semiconductor device including strained germanium and method for manufacturing the same

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Seoul, South Korea

Heejeong Lim