Samsung

About: Samsung is a company organization based out in Seoul, South Korea. It is known for research contribution in the topics: Layer (electronics) & Signal. The organization has 134067 authors who have published 163691 publications receiving 2057505 citations. The organization is also known as: Samsung Group & Samsung chaebol.

A Nine-Phase Permanent-Magnet Motor Drive System for an Ultrahigh-Speed Elevator

Abstract: This paper presents a nine-phase permanent-magnet synchronous motor (PMSM) drive system based on multiple three-phase voltage source inverters. The nine-phase PMSM was developed as a traction motor for an ultrahigh-speed elevator. The mathematical model of the motor was simplified through symmetry of the system. Using the simplified model, the drive system can be controlled by the well-known d-q control theory. The feasibility and validity of the drive system were experimentally demonstrated at the world's tallest elevator test tower. Moreover, an additional experiment was performed to ensure the fault-tolerance capability of the system.

TV graphical user interface for providing user access to preset time periods of TV program information

Abstract: A TV GUI is provided to display a program guide that contains information on TV programming for a time period of predetermined duration. The program guide has a time scroll bar that enables a user to scroll a TV program schedule back and forward in time within the selected time period. When the user clicks on a MORE icon on the time scroll bar, the GUI switches into a "more times" mode to offer a menu of time options that represent various preselected time periods of TV programming. A time preset button may be provided on the program guide to enable users to review TV program information covering any preselected time period. A single click on the time preset button causes the GUI to switch to a program guide for the preselected time period.

Flexible display apparatus and control method thereof

Abstract: A flexible display apparatus is provided. The flexible display apparatus includes: a display configured to display an object on a screen; an actuator configured to provide shape deformation to the display; and a controller configured to determine deformation information for reconfiguring and displaying the object, control the actuator to provide the shape deformation according to the determined deformation information, and control the display to reconfigure the displayed object and display the reconfigured object.

Flexible flat panel display

Abstract: A flexible flat panel display prevents electronic units, such as a flexible printed circuit board and a driving IC, from being separated from the flexible flat panel display even when the display unit is bent. The flexible flat panel display includes: a flexible display unit including a display area adapted to display an image, a first side and a second side parallel to edges of the display area, and a third side and a fourth side perpendicular to the first and second sides, the third side and the fourth being adapted to being bent; and electronic units arranged solely on at least one of the first and second sides and absent the third and fourth sides.

Real-Time Driver Drowsiness Detection for Embedded System Using Model Compression of Deep Neural Networks

Abstract: Driver’s status is crucial because one of the main reasons for motor vehicular accidents is related to driver’s inattention or drowsiness. Drowsiness detector on a car can reduce numerous accidents. Accidents occur because of a single moment of negligence, thus driver monitoring system which works in real-time is necessary. This detector should be deployable to an embedded device and perform at high accuracy. In this paper, a novel approach towards real-time drowsiness detection based on deep learning which can be implemented on a low cost embedded board and performs with a high accuracy is proposed. Main contribution of our paper is compression of heavy baseline model to a light weight model deployable to an embedded board. Moreover, minimized network structure was designed based on facial landmark input to recognize whether driver is drowsy or not. The proposed model achieved an accuracy of 89.5% on 3-class classification and speed of 14.9 frames per second (FPS) on Jetson TK1.