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.

User equipment and power control method for random access

Abstract: An improved power control method and apparatus of a mobile terminal is provided for facilitating random access procedure in a mobile communication system based on a distributed antenna system. A method includes receiving, by the terminal, system information from a base station, the system information including transmit power information for transmitting a random access preamble; calculating a transmit power using the transmit power information; and transmitting the random access preamble using with the calculated transmit power.

Method for manufacturing a semiconductor package

Abstract: A method for manufacturing a semiconductor package, including providing a lead frame in which die pad and side rail areas of the lead frame are mechanically interconnected to, and electrically isolated from each other so that the exposed bottom surface of the die pad does not become coated with a metal plating film during surface treatment for coating outer leads of the lead frame.

Organic light-emitting display device and method for manufacturing the same

Abstract: Provided is an organic light-emitting display device (OLED) and method of manufacturing the same. The OLED comprises a substrate and a thin film transistor, with source/drain electrodes, located at a predetermined area on the substrate. A passivation layer is located on the source/drain electrodes with a via hole exposing one of the source/drain electrodes. A first pixel electrode is located at the bottom of the via hole, electrically coupled to the exposed source/drain electrode, and extending onto the side wall of the via hole and the passivation layer. A planarization pattern fills the via hole in which the first pixel electrode is located and exposes the portion of the first pixel electrode on the passivation layer.

Cyclone dust collecting apparatus for a vacuum cleaner

Abstract: A cyclone dust collecting apparatus for a vacuum cleaner includes a hollow cylindrical cyclone body having an open upper end through which air and contaminants are drawn in and a dust discharge port located proximate a lower end of the cyclone body. The dust discharge port receives contaminants that have been separated from the air by centrifugal force and discharged from the cyclone body. The apparatus further includes a dust receptacle connected to the cyclone body for collecting the contaminants discharged from the cyclone body through the dust discharge port. A base member is connected to and closes the lower end of the cyclone body and the dust receptacle, and a cover is removably connected to the upper end of the cyclone body and the dust receptacle. The cover has an air intake channel for drawing in outside air and contaminants into the cyclone body and an air discharge channel for discharging clean air from the cyclone body. The apparatus further includes a backflow prevention means for guiding contaminants that have been discharged from the cyclone body into the dust receptacle and preventing a backflow of the contaminants collected in the dust receptacle from returning to the cyclone body.

Multi-relational Poincaré Graph Embeddings

Abstract: Hyperbolic embeddings have recently gained attention in machine learning due to their ability to represent hierarchical data more accurately and succinctly than their Euclidean analogues. However, multi-relational knowledge graphs often exhibit multiple simultaneous hierarchies, which current hyperbolic models do not capture. To address this, we propose a model that embeds multi-relational graph data in the Poincare ball model of hyperbolic space. Our Multi-Relational Poincare model (MuRP) learns relation-specific parameters to transform entity embeddings by Mobius matrix-vector multiplication and Mobius addition. Experiments on the hierarchical WN18RR knowledge graph show that our Poincare embeddings outperform their Euclidean counterpart and existing embedding methods on the link prediction task, particularly at lower dimensionality.