Retrieval of NO2 Column Amounts from Ground-Based Hyperspectral Imaging Sensor Measurements

Total column amounts of NO2 (TCN) were estimated from ground-based hyperspectral imaging sensor (HIS) measurements in a polluted urban area (Seoul, Korea) by applying the radiance ratio fitting method with five wavelength pairs from 400 to 460 nm. We quantified the uncertainty of the retrieved TCN based on several factors. The estimated TCN uncertainty was up to 0.09 Dobson unit (DU), equivalent to 2.687 ?? 1020 molecules m???2) given a 1?? error for the observation geometries, including the solar zenith angle, viewing zenith angle, and relative azimuth angle. About 0.1 DU (6.8%) was estimated for an aerosol optical depth (AOD) uncertainty of 0.01. In addition, the uncertainty due to the NO2 vertical profile was 14% to 22%. Compared with the co-located Pandora spectrophotometer measurements, the HIS captured the temporal variation of the TCN during the intensive observation period. The correlation between the TCN from the HIS and Pandora also showed good agreement, with a slight positive bias (bias: 0.6 DU, root mean square error: 0.7 DU)

Impact of Induced Seismicity on the Housing Market: Evidence from Pohang

In this study, we analyze the case of induced seismicity in Pohang, South Korea, in 2017 to investigate the effect of seismic risk perception on the local residential property market. Based on a hedonic pricing model with a difference-in-differences method, we examine the geographic distribution of the effects of unexpected earthquake hazards. Our results indicate an overall reduction in local property values, but the magnitudes of negative externality for housing prices decrease with respect to the distance from the epicenter. In areas within 3 km of the epicenter, the asset value reduced by approximately 20% after an earthquake event, but if the distance from the epicenter was higher than 12 km, the negative effect on the price was not significant. In addition, we examine how the experience of seismic events affect the preference on the anti-seismic building structure. The results show that the market valuation on the anti-seismic system significantly escalated after the earthquake

Impact of Induced Seismicity on the Housing Market: Evidence from Pohang

In this study, we analyze the case of induced seismicity in Pohang, South Korea, in 2017 to investigate the effect of seismic risk perception on the local residential property market. Based on a hedonic pricing model with a difference-in-differences method, we examine the geographic distribution of the effects of unexpected earthquake hazards. Our results indicate an overall reduction in local property values, but the magnitudes of negative externality for housing prices decrease with respect to the distance from the epicenter. In areas within 3 km of the epicenter, the asset value reduced by approximately 20% after an earthquake event, but if the distance from the epicenter was higher than 12 km, the negative effect on the price was not significant. In addition, we examine how the experience of seismic events affect the preference on the anti-seismic building structure. The results show that the market valuation on the anti-seismic system significantly escalated after the earthquake

On Training Neural Network Decoders of Rate Compatible Polar Codes via Transfer Learning

Neural network decoders (NNDs) for rate-compatible polar codes are studied in this paper. We consider a family of rate-compatible polar codes which are constructed from a single polar coding sequence as defined by 5G new radios. We propose a transfer learning technique for training multiple NNDs of the rate-compatible polar codes utilizing their inclusion property. The trained NND for a low rate code is taken as the initial state of NND training for the next smallest rate code. The proposed method provides quicker training as compared to separate learning of the NNDs according to numerical results. We additionally show that an underfitting problem of NND training due to low model complexity can be solved by transfer learning techniques

Hydraulic Resistance Analysis Based on Cohesive Strength and Toughness of Synthetic Polymerized Rubber Gel Used as Water-Leakage Repair Material for Concrete Structures

As construction in urban centers increases internationally, many concrete infrastructures are being built at 100 m or more underground, and the influence of groundwater on these facilities is also increasing. Accordingly, the importance of waterproofing and leak-proofing technology for securing long-term durability and safety of underground concrete facilities has been greatly emphasized. The most important required performance of such leak repair technology is to withstand structural behavior and groundwater pressure well. Currently, as a leak repair material for underground concrete facilities, a synthetic rubber-based polymer rubber gel with adhesive flexibility is used internationally. However, quantitative data on how deep the material can perform underground are lacking. In general, the water pressure resistance evaluation of leak repair materials only checks whether it withstands the water pressure of 30 m (0.3 MPa) underground. Therefore, in this study, the toughness of the synthetic rubber polymerized gel (SPRG) leak repair material was calculated using three factors: viscosity, cohesive strength (adhesion strength), and elongation, and an analysis method that can be replaced with water pressure resistance was proposed. In addition, in the correlation between toughness and underground water pressure, it was possible to find out the thickness of the leak repair material used by the underground depth. As a result, it was possible to know the required thickness of the leak repair material according to the depth of the structure to be built underground

Hydraulic Resistance Analysis Based on Cohesive Strength and Toughness of Synthetic Polymerized Rubber Gel Used as Water-Leakage Repair Material for Concrete Structures

As construction in urban centers increases internationally, many concrete infrastructures are being built at 100 m or more underground, and the influence of groundwater on these facilities is also increasing. Accordingly, the importance of waterproofing and leak-proofing technology for securing long-term durability and safety of underground concrete facilities has been greatly emphasized. The most important required performance of such leak repair technology is to withstand structural behavior and groundwater pressure well. Currently, as a leak repair material for underground concrete facilities, a synthetic rubber-based polymer rubber gel with adhesive flexibility is used internationally. However, quantitative data on how deep the material can perform underground are lacking. In general, the water pressure resistance evaluation of leak repair materials only checks whether it withstands the water pressure of 30 m (0.3 MPa) underground. Therefore, in this study, the toughness of the synthetic rubber polymerized gel (SPRG) leak repair material was calculated using three factors: viscosity, cohesive strength (adhesion strength), and elongation, and an analysis method that can be replaced with water pressure resistance was proposed. In addition, in the correlation between toughness and underground water pressure, it was possible to find out the thickness of the leak repair material used by the underground depth. As a result, it was possible to know the required thickness of the leak repair material according to the depth of the structure to be built underground

Schottky Barrier Lowering Induced by Ultrathin Aluminum Oxynitride Interlayer in Metal/SiC Junctions

It is known that the electrical characteristics of SiC Schottky diode depend strongly on the interface energy barrier (Schottky barrier) and lower Schottky barriers bring essential advantages of improving the power efficiency and obtaining the fast switching. In this work, the Schottky barrier of metal/SiC junction is reported experimentally to be reduced significantly with an ultra-thin (down to ~1.0 nm) aluminum oxynitride (AlON) interlayer inserted at the junction interface. It was also found that the contact resistance of junction decreased with the AlON interlayer. The barrier height was lowered by up to 0.8 eV and the reduction was similar for three types of metal with different work function (Pt: 5.65 eV, Ni: 5.01 eV, Cu: 4.33 eV). The adjustment of Schottky barrier with an interlayer is generally considered due to the potential change driven by fixed changes in the interlayer or Fermi-level depinning associated with the suppression of metal-induced gap states. In our case, the Fermi-level pinning factor remained almost unchanged (Fig. 1), implying that the surface states of SiC is NOT the main factor of the observed Schottky barrier reduction. It seems most likely that the Schottky barrier reduction arises from the fixed positive charges in the AlON thin film