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.

Single-Crystalline Si STacked ARray (STAR) NAND Flash Memory

Abstract: In this paper, a 3-D NAND Flash memory array having multiple single-crystal Si nanowires is investigated. Device structure and fabrication process are described including the electrical isolation of stacked nanowires. Numerical simulation results focused on NAND Flash memory operation are delivered. Devices and array with stacked bit lines are fabricated, and memory characteristics such as program/erase select gate operation are measured. Array scheme is also discussed for the high-density bit-cost scalable 3-D stacked bit-line NAND Flash memory application.

All-solid-state spatial light modulator with independent phase and amplitude control for three-dimensional LiDAR applications

Abstract: Spatial light modulators are essential optical elements in applications that require the ability to regulate the amplitude, phase and polarization of light, such as digital holography, optical communications and biomedical imaging. With the push towards miniaturization of optical components, static metasurfaces are used as competent alternatives. These evolved to active metasurfaces in which light-wavefront manipulation can be done in a time-dependent fashion. The active metasurfaces reported so far, however, still show incomplete phase modulation (below 360°). Here we present an all-solid-state, electrically tunable and reflective metasurface array that can generate a specific phase or a continuous sweep between 0 and 360° at an estimated rate of 5.4 MHz while independently adjusting the amplitude. The metasurface features 550 individually addressable nanoresonators in a 250 × 250 μm2 area with no micromechanical elements or liquid crystals. A key feature of our design is the presence of two independent control parameters (top and bottom gate voltages) in each nanoresonator, which are used to adjust the real and imaginary parts of the reflection coefficient independently. To demonstrate this array’s use in light detection and ranging, we performed a three-dimensional depth scan of an emulated street scene that consisted of a model car and a human figure up to a distance of 4.7 m. By controlling two voltage gates separately from one another, a spatial light modulator has been made that can continuously vary the phase of 360 degrees while independently adjusting the amplitude.

Low bend loss optical fiber

Abstract: Disclosed is a low bend loss optical fiber including: a core; an inner layer disposed at outside of the core, which has a refractive index lower than a refractive index of the core, the refractive index of the inner layer gradually decreasing as it becomes farther from the core; and a trench layer disposed at outside of the inner layer, which has a lowest refractive index.

Mobile energy management system

Abstract: According to an aspect of the disclosure, an energy management apparatus for a mobile energy management system and method includes detecting an availability of at least one network device at a site, displaying a proximity control selector within a graphical user interface of a mobile device associated with the site that can be toggled to enable and disable proximity detection using the mobile device, detecting a distance of the mobile device relative to the site in response to enabling proximity detection on the mobile device, and initiating a change to the operating condition of the network device in response to detecting a change in the distance of the mobile device relative to the site and the setting of the proximity control selector. According to an aspect of the disclosure, the network device may be a thermostat associated with the HVAC system of the site or other energy consuming appliances.

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Abstract: Although the latest high-end smartphone has powerful CPU and GPU, running deeper convolutional neural networks (CNNs) for complex tasks such as ImageNet classification on mobile devices is challenging. To deploy deep CNNs on mobile devices, we present a simple and effective scheme to compress the entire CNN, which we call one-shot whole network compression. The proposed scheme consists of three steps: (1) rank selection with variational Bayesian matrix factorization, (2) Tucker decomposition on kernel tensor, and (3) fine-tuning to recover accumulated loss of accuracy, and each step can be easily implemented using publicly available tools. We demonstrate the effectiveness of the proposed scheme by testing the performance of various compressed CNNs (AlexNet, VGGS, GoogLeNet, and VGG-16) on the smartphone. Significant reductions in model size, runtime, and energy consumption are obtained, at the cost of small loss in accuracy. In addition, we address the important implementation level issue on 1?1 convolution, which is a key operation of inception module of GoogLeNet as well as CNNs compressed by our proposed scheme.