• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3488-3493
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• 2022

Accelerator driven subcritical systems have long been discussed as facilities which can be used for solving the nuclear waste problem. The physics of these systems is very different from conventional reactors and new techniques had to be developed for reactivity monitoring. One such technique is the Area Ratio Method which studies the response of a subcritical system upon insertion of a large number of neutron pulses. An issue associated with this technique is the spatial dependence of measured reactivity which is intrinsic to the sub criticality of the system since the reactor does not operate on the fundamental mode and measured reactivity depends on the detector position. This is generally addressed by defining Bell-Glasstone spatial correction factor. This factor upon multiplication with measured reactivity gives the correct reactivity which is independent of detector location. Monte Carlo Methods are used for evaluating these factors. This paper presents a complete three dimensional map of spatial correction factors for BRAHMMA subcritical system. In addition, the dataset obtained also helps in identifying detector locations where the correction factor is close to unity, thereby implying no correction if the detector is used at those locations.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.459-466
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• 2023

In the last decade, artificial intelligence's dramatic advancement with the development of various deep learning techniques has significantly contributed to remote sensing fields and satellite image applications. Among many prominent areas, super-resolution research has seen substantial growth with the release of several benchmark datasets and the rise of generative adversarial network-based studies. However, most previously published remote sensing benchmark datasets represent spatial resolution within approximately 10 meters, imposing limitations when directly applying for super-resolution of small objects with cm unit spatial resolution. Furthermore, if the dataset lacks a global spatial distribution and is specialized in particular land covers, the consequent lack of feature diversity can directly impact the quantitative performance and prevent the formation of robust foundation models. To overcome these issues, this paper proposes a method to generate benchmark datasets by simulating the modulation transfer functions of the sensor. The proposed approach leverages the simulation method with a solid theoretical foundation, notably recognized in image fusion. Additionally, the generated benchmark dataset is applied to state-of-the-art super-resolution base models for quantitative and visual analysis and discusses the shortcomings of the existing datasets. Through these efforts, we anticipate that the proposed benchmark dataset will facilitate various super-resolution research shortly in Korea.

• Journal of Korea Water Resources Association
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• v.30 no.5
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• pp.549-559
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• 1997

A multiply-connected network unsteady flow model for the main reach of the Han River is developed. It is a variable parameter model which allows variable roughness coefficient for each computational point according to the spatial position and the value of discharge. Sensitivities of the model to roughness coefficient and weir-flow discharge coefficient are tested, and as a result Manning's roughness coefficient is selected as the calibration parameter. The model is calibrated and verified using the records of the past flood events. A modified Gauss-Newton method is used for the optimal calibration of roughness coefficients. From the calibration of variable parameter model, spatial variation and discharge dependence of Manning's roughness coefficient are identified. That is, the roughness coefficient is higher for the upstream reach of the Wangsook stream Junction, and it decreases as the discharge increases. It turns out through the verification that the stages calculated by the variable parameter model agree better with the observed than those by the conventional single parameter model. Spatial variation of the roughness coefficient appears to be more significant than the dependence of the discharge.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.79-87
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• 2011

A spatial time series model was used for analyzing the method of spatial time series (not the ARIMA model that is popular for analyzing spatial time series) by using chicken pox data which is a highly contagious disease and grid data due to ARIMA not reflecting the spatial processes. Time series model contains a weighting matrix, because that spatial time series model influences the time variation as well as the spatial location. The weighting matrix reflects that the more geographically contiguous region has the higher spatial dependence. It is hypothesized that the weighting matrix gives neighboring areas the same influence in the study of the spatial time series model. Therefore, we try to present the conclusion with a weighting matrix in a way that gives the same weight to existing neighboring areas in the study of the suitability of the STARMA model, spatial time series model and STBL model, in the comparative study of the predictive power for statistical inference, and the results. Furthermore, through the Kalman-Filter method we try to show the superiority of the Kalman-Filter method through a parameter assumption and the processes of prediction.

• International Journal of High-Rise Buildings
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• v.8 no.4
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• pp.313-324
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• 2019

This paper presents the analysis of wind speeds data measured on top of three neighboring high-rise buildings close to a beach in Xiamen city, China, during Typhoon "Usagi" 2013. Wind tunnel simulation was carried out to validate the field measurement results. Turbulence intensity, turbulence integral scale, power spectrum and cross correlation of recorded wind speed were studied in details. The low frequency trend component of the typhoon speed was also discussed. The field measurement results show turbulence intensity has strong dependence to the wind speed, upwind terrain and even the relative location to the Typhoon center. The low frequency fluctuation could severely affect the characteristics of wind. Cross correlation of the measured wind speeds on different buildings also showed some dependence on the upwind terrain roughness. After typhoon made landfall, the spatial correlation of wind speeds became weak with the coherence attenuating quickly in frequency domain.

• Journal of the Korean housing association
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• v.13 no.4
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• pp.35-42
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• 2002

The purpose of this study is to look into the question-What kind of factors, among various influencing factors of temple architecture, change the development of villages with their its relationships to the temple. For the study, the villages located around a temple site with special geographic characteristics were chosen. It was analyzed and generalized what kind of social factors were chosen and applied to the design of residential buildings in those villages. The characteristics of the buildings in the villages that have relationships with the temple appeared to be as follows; Financial factor of the temple, rather than religious influences of it, appeared to influence strongly over the forms of building and the spaces of village. The village which formed along a new entrance axis to the temple were transformed to have a spatial organization along with added sightseeing and commercial functions. The villages have different spatial structures depending on their land uses. In short, the form of entrance axis to the temple has changed the economical dependence of villages on the temple, and becomes the major factor of transforming the spatial organization of the villages.

• The Journal of Fisheries Business Administration
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• v.46 no.3
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• pp.63-72
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• 2015

This study aims to empirically analyze the relationship between climate change elements and catch amount of coastal fisheries, which is predicted to be vulnerable to climate change since its business scale is too small and fishing ground is limited. Using panel data from 1974 to 2013 by region, we tested the relationship between the sea temperature, salinity and the coastal fisheries production. A spatial panel model was applied in order to reflect the spatial dependence of the ocean. The results indicated that while the upper(0-20m) sea temperature and salinity have no significant influence on the coastal fisheries production, the lower(30-50m) sea temperature has significant positive effects on it and, by extension, on the neighboring areas's production. Therefore, with sea temperature forecast data derived from climate change scenarios, it is expected that these results can be used to assess the future vulnerability to the climate change.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.12-12
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• 2010

By using scanning tunneling microscopy/spectroscopy (STM/S), we can make images of various physical properties in nanometer-scale spatial resolutions. Here, I demonstrate imaging of two electron-correlated subjects; screening and superconductivity by STM/S. The electrostatic potential around a charge is described with the Coulomb potential. When the charge is located in a metal, the potential is modified because of the free electrons in the host. The potential modification, called screening, is one of the fundamental phenomena in the condensed matter physics. Using low-temperature STM we have developed a method to measure electrostatic potential in high spatial and energy resolutions, and observed the potential around external charges screened by two-dimensional surface electronic states. Characteristic potential decay and the Friedel oscillation were clearly observed around the charges [1]. Superconductivity of nano-size materials, whose dimensions are comparable with the coherence length, is quite different from their bulk. We investigated superconductivity of ultra-thin Pb islands by directly measuring the superconducting gaps using STM. The obtained tunneling spectra exhibit a variation of zero bias conductance (ZBC) with a magnetic field, and spatial mappings of ZBC revealed the vortex formation [2]. Size dependence of the vortex formation will be discussed at the presentation.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.120-120
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• 2020

Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.

• Journal of Korea Water Resources Association
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• v.49 no.12
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• pp.1007-1014
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• 2016

The FORGEX (Focused Rainfall Growth Extension) method was developed to estimate rainfall quantiles in the United Kingdom. This method does not need any regional grouping and can estimate rainfall quantiles with relatively long return period. The spatial dependence formula (ln $N_e$) was derived to consider the distance from growth curve of proper population to the distributed network maximum (netmax) data using the UK rainfall data. For this reason, there is an inaccurate problem in rainfall quantiles when this formula is applied in Korea. In this study, the new formula was derived in order to improve such shortcomings using rainfall data of 64 sites from the Korea Meteorological Administration (KMA). A 42-year period (1973~2014) was taken as the reference period from rainfall data, then the formula was derived using three parameters such as rainfall duration, number of site, area of network. Then the new formula was applied to the FORGEX method for regional rainfall frequency analysis. In addition, rainfall quantiles were compared with those from the UK formula. As a result, the new formula shows more accurate results than the UK formula, in which the FORGEX method by the UK formula underestimates rainfall quantiles. Finally, the new improved formula may estimate accurate rainfall quantiles for long return period.