• Geophysics and Geophysical Exploration
• /
• v.8 no.1
• /
• pp.50-58
• /
• 2005

Recently, the imaging of geological structures beneath water-covered areas has been in great demand because of numerous tunnel and bridge construction projects on river or lake sites. An electrical resistivity survey can be effective in such a situation because it provides a subsurface image of faults or weak zones beneath the water layer. Even though conventional resistivity surveys in water-covered areas, in which electrodes are installed on the water bottom, do give high-resolution subsurface images, much time and effort is required to install electrodes. Therefore, an easier and more convenient method is sought to find the strike direction of the main zones of weakness, especially for reconnaissance surveys. In this paper, we investigate the applicability of the streamer resistivity survey method, which uses electrodes in a streamer cable towed by ship or boat, for delineating a fault zone. We do this through numerical experiments with models of water-covered areas. We demonstrate that the fault zone can be imaged, not only by installing electrodes on the water bottom, but also by using floating electrodes, when the depth of water is less than twice the electrode spacing. In addition, we compare the signal-to-noise ratio and resolving power of four kinds of electrode arrays that can be adapted to the streamer resistivity method. Following this numerical study, we carried out both conventional and streamer resistivity surveys for the planned tunnel construction site located at the Han River in Seoul, Korea. To obtain high-resolution resistivity images we used the conventional method, and installed electrodes on the water bottom along the planned route of the tunnel beneath the river. Applying a two-dimensional inversion scheme to the measured data, we found three distinctive low-resistivity anomalies, which we interpreted as associated with fault zones. To determine the strike direction of these three fault zones, we used the quick and convenient streamer resistivity.

• Clinical and Experimental Pediatrics
• /
• v.50 no.9
• /
• pp.875-881
• /
• 2007

Purpose : Chromosome analysis is important in genetic study and genetic counseling. This study was performed to evaluate the type and incidence of chromosome abnormalities in a single hospital for 25 years. Methods : Chromosome analyses were performed on peripheral blood lymphocytes, obtained from 4,856 patients with suspected chromosomal aberrations, referred to cytogenetic laboratory in Department of Pediatrics, Kyungpook National University Hospital from May 1981 to October 2005. Results : We analyzed 4,567 cases. Children were 3,014 cases (66.0%) and adult were 1,553 cases (34.0 %). The most common purpose of the chromosomal analysis was growth and developmental abnormality in children and infertility in adults. Total chromosomal aberration rate was 16.9% (770/4,567). Among those cases, the numerical abnormalities were 12.2% (558 cases), the structural abnormalities were 4.1% (187 cases), and others were 0.5% (25 cases). The relative frequencies of autosomal abnormalities were 6.4% (294 cases) in Down syndrome; 0.2% (7 cases) in Edwards syndrome; 0.1% (4 cases) in Patau syndrome; 0.2% (10 cases) in other abnormalities, of sex chromosome, 2.9% (131 cases) in Klinefelter syndrome; 2.2% (99 cases) in Turner syndrome; 0.2% (8 cases) in 47, XXX; 0.1% (3 cases) in 47, XYY. Among the structural abnormalities, translocation was 1.8% (84 cases), inversion was 0.8% (37 cases), deletion was 0.4% (17 cases), and insertion was 0.3% (13 cases), in order of frequency. Conclusion : In this study, the type, incidence and distribution of cytogenetic abnormalities by karyotype were reviewed. We hope that our study could be used as a basic information on the diagnosis, treatment and genetic counseling for chromosome abnormalities in Korea.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_3
• /
• pp.933-948
• /
• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.