Kwangwoon University

About: Kwangwoon University is a education organization based out in Seoul, South Korea. It is known for research contribution in the topics: Thin film & Resonator. The organization has 4020 authors who have published 8217 publications receiving 104365 citations.

Smart Materials, Magnetic Graphene Oxide-Based Nanocomposites for Sustainable Water Purification

Abstract: Magnetic separation, one of the potential methods for the purification of toxic pollutant contaminated water, has been found to be an alternative technique for the removal of water pollutants that effectively compares with the conventional methods of treatment. Among the synthetic magnetic adsorbents, magnetic graphene oxide based nanocomposites (MGOs) have been widely used in the removal of metal pollutants and dyes from aqueous solution, and are currently attracting much attention. This chapter reviews the status and approaches of the properties of graphene and magnetic graphene oxide nanocomposites, in view of their utilization for the adsorption removal of pollutants (heavy metals, radioactive elements, organic dyes, and other pollutants) for sustainable water purification. It also reviews the primary characterization instruments required for the evaluation of structural, chemical and physical functionalities of synthesized magnetic graphene oxide nanocomposites. It first discusses pollutants and their toxic effects, and the necessity of preparation of MGOs, and then discusses in brief MGOs preparation strategies, characterizations, and applications for sustainable water purification.

Ku-band high efficiency antenna with corporate-series-fed microstrip array

Abstract: Excellent efficiency of a linearly polarized microstrip array in Ku-band is achieved by having proper impedance matching throughout the array and by properly using the corporate and series fed by microstrip transmission lines. The cavity-backed microstrip patch is used to obtain relatively wide bandwidth. The auto-tracking Ku-band antenna in the azimuth direction has developed with a very low profile for vehicle's rooftop mounting, as well as, a low manufacturing cost. The main beam of array is tilted 15/spl deg/ away from the broadside direction to provide optimum coverage for Korea satellite III.

Fast terahertz reflection tomography using block-based compressed sensing

Abstract: In this paper, a new fast terahertz reflection tomography is proposed using block-based compressed sensing. Since measuring the time-domain signal on two-dimensional grid requires excessive time, reducing measurement time is highly demanding in terahertz tomography. The proposed technique directly reduces the number of sampling points in the spatial domain without modulation or transformation of the signal. Compressed sensing in spatial domain suggests a block-based reconstruction, which substantially reduces computational time without degrading the image quality. An overlap-average method is proposed to remove the block artifact in the block-based compressed sensing. Fast terahertz reflection tomography using the block-based compressed sensing is demonstrated with an integrated circuit and parched anchovy as examples.

Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals

Abstract: In this paper, we strive to answer two questions: What is the current state of 3D hand pose estimation from depth images? And, what are the next challenges that need to be tackled? Following the successful Hands In the Million Challenge (HIM2017), we investigate the top 10 state-of-the-art methods on three tasks: single frame 3D pose estimation, 3D hand tracking, and hand pose estimation during object interaction. We analyze the performance of different CNN structures with regard to hand shape, joint visibility, view point and articulation distributions. Our findings include: (1) isolated 3D hand pose estimation achieves low mean errors (10 mm) in the view point range of [70, 120] degrees, but it is far from being solved for extreme view points; (2) 3D volumetric representations outperform 2D CNNs, better capturing the spatial structure of the depth data; (3) Discriminative methods still generalize poorly to unseen hand shapes; (4) While joint occlusions pose a challenge for most methods, explicit modeling of structure constraints can significantly narrow the gap between errors on visible and occluded joints.