Income Distribution and Public Transfers as Social Safety Nets in Korea

Using 5-year balanced household panel data, this paper shows that the inequality of per capita income in Korea aggravated during the financial crisis in 1998. The decomposition analysis of income inequality by factor component shows that the dominant positive effect on the income inequality is by the asset income. Next is the wage income, followed by the other income. Furthermore, this paper shows that social safety net programs were not yet in place during the initial period of the crisis. Public transfers were not effective social safety net devices and did not contribute in decreasing income inequality. Private transfers, on the other hand, were effective devices and narrowed the disparity in household income.

Fabrication and characterization of corrosion-resistant surface layer on Mg-alloys by using large-pulsed electron beam (LPEB) irradiation process

Department of Mechanical EngineeringThis research was begun for finding an appropriate industrial application of electron beam process.Particularly, since last decade, the surface treatment method using electron beam has been largely investigated. However, in the all published researches for Mg-alloys known for the world lightest-weight metal, the energy density level of the electron beam surface treatment was limited at only 2.5 - 3 J/??? and the electrochemical performance has not yet been enhanced for engineering application. In this thesis, the energy density was increased up to 10 J/??? with parameter optimization by applying large pulsed electron beam (LPEB) irradiation process on AZ31 plate specimens. Firstly, through mathematical modelling of energy absorptivity of LPEB, the pitch of irradiation pattern was anticipated to adequate value. Appling the prediction model, the temperature profile was simulated by 2-D heat transfer equation. The estimated result was verified by real-time temperature measurement. The process was assessed how to be progressed rapid quenching and tempering. At over 20 cycles, the substrate temperature was above eutectic point (220???) of Mg-Al alloy, but it was not increased over 300??? due to self-diffusion. To analyze the surface modification effects mechanically, it was demonstrated brightness, deformation of LPEB treated surface with the results of ball-on-disc wear test. The mechanical characteristics were enhanced by ~30% using LPEB process. For electrochemical analysis, the surface corrosion characteristics were qualitatively and quantitatively evaluated by 3-electrode cell test. Potentiodynamic polarization and electrochemical impedance spectroscopy was applied to evaluation. Then, low-field approximation and equivalent circuit modelling was used to certify the optimum LPEB parameter. At as-received sample, it presented irregular results since the oxide layerit can protect the bare surface from corrosion, but it was easily damaged than the newly modified surface layer by LPEB process. The result was demonstrated that the electrochemical characteristics were improved by ~45%. In addition, using the scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analyses, the morphology and the microstructure with chemical composition transformation were detailed discussed by metallurgically. As a result, it was presented that the tool mark was eliminated with new wavy surface morphology and the Al content was increased up to maximum level when the energy density is 5 J/???. Consequently, the LPEB irradiation was verified that it can efficiently fabricate nano-grained corrosion-resistant surface layer with activating surface alloying induced by vaporization and re-melting process in Mg-Al binary alloy system. However, the technology was analyzed to require more development because surface defects were appeared by LPEB process due to inhomogeneous evaporation of Mg such as crater, crack, and micro-pole.ope

Acetylation of Seaweed Alginate by Pseudomonas Syringae.

Acetylation of bacterial alginate by Pseudomonas syringae subsp. phaseolicola ATCC 19304 was independent of alginate biosynthesis. This allowed the development of a process for acetylating seaweed alginate using immobilized P. syringae ATCC 19304 cells. About 50% of the mannuronic acid residues of seaweed alginate were acetylated by carbon immobilized P. syringae cells in a fluidized bed, up-flow reactor system fed continuously with seaweed alginate and gluconic acid. O-Acetylation by this process was found to be specific for the C-2 and/or C-3 position(s) of mannuronate residues. Acetylated seaweed alginate showed altered properties including increased viscosity and changed affinities for some cations

3D Nanoprinting Technologies for Tissue Engineering Applications

Tissue engineering recovers an original function of tissue by replacing the damaged part with a new tissue or organ regenerated using various engineering technologies. This technology uses a scaffold to support three-dimensional (3D) tissue formation. Conventional scaffold fabrication methods do not control the architecture, pore shape, porosity, or interconnectivity of the scaffold, so it has limited ability to stimulate cell growth and to generate new tissue. 3D printing technologies may overcome these disadvantages of traditional fabrication methods. These technologies use computers to assist in design and fabrication, so the 3D scaffolds can be fabricated as designed and standardized. Particularly, because nanofabrication technology based on two-photon absorption (2PA) and on controlled electrospinning can generate structures with submicron resolution, these methods have been evaluated in various areas of tissue engineering. Recent combinations of 3D nanoprinting technologies with methods from molecular biology and cell dynamics have suggested new possibilities for improved tissue regeneration. If the interaction between cells and scaffold system with biomolecules can be understood and controlled and if an optimal 3D environment for tissue regeneration can be realized, 3D nanoprinting will become an important tool in tissue engineering

Development of Multidisciplinary Design Optimization Process for a Large Scale Hybrid Composite Wind Turbine Blade

Development of a multidisciplinary design optimization (MDO) of a large scale hybrid composite wind turbine blade is performed. Multiple objectives are considered in the MDO process to maximize annual energy production and lifetime profit, minimize weight and power production rate. A wind turbine blade is divided into regions and the layup sequences for each region are considered as design variables. The scale of wind turbine blade is also considered to find the optimum size of a wind turbine blade. Applied loads due to extreme wind conditions for rotor rotation and rotor stop condition are considered for finite element analysis (FEA) to evaluate the structural strength. The designed structural strength and stiffness are demonstrated to withstand the loads due to harmonic excitation from rotor rotation. An MDO process for obtaining an optimum hybrid composite laminate layup and an optimum length of a wind turbine blade is developed and illustrated in this research. The finite element (FE) model and cost estimation model are calibrated and the developed MDO process is verified for an optimum design. The optimum hybrid composite layup sequence and size of a large scale wind turbine blade are highlighted in this research

Neural Fourier Shift for Binaural Speech Rendering

We present a neural network for rendering binaural speech from given monaural audio, position, and orientation of the source. Most of the previous works have focused on synthesizing binaural speeches by conditioning the positions and orientations in the feature space of convolutional neural networks. These synthesis approaches are powerful in estimating the target binaural speeches even for in-the-wild data but are difficult to generalize for rendering the audio from out-of-distribution domains. To alleviate this, we propose Neural Fourier Shift (NFS), a novel network architecture that enables binaural speech rendering in the Fourier space. Specifically, utilizing a geometric time delay based on the distance between the source and the receiver, NFS is trained to predict the delays and scales of various early reflections. NFS is efficient in both memory and computational cost, is interpretable, and operates independently of the source domain by its design. With up to 25 times lighter memory and 6 times fewer calculations, the experimental results show that NFS outperforms the previous studies on the benchmark dataset.Comment: Submitted to ICASSP 202