• Geomechanics and Engineering
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• v.38 no.1
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• pp.29-44
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• 2024

This research investigates the effectiveness of data augmentation techniques in the automated analysis of B-scan images from ground-penetrating radar (GPR) using deep learning. In spite of the growing interest in automating GPR data analysis and advancements in deep learning for image classification and object detection, many deep learning-based GPR data analysis studies have been limited by the availability of large, diverse GPR datasets. Data augmentation techniques are widely used in deep learning to improve model performance. In this study, we applied four data augmentation techniques (geometric transformation, color-space transformation, noise injection, and applying kernel filter) to the GPR datasets obtained from a testbed. A deep learning model for GPR data analysis was developed using three models (Faster R-CNN ResNet, SSD ResNet, and EfficientDet) based on transfer learning. It was found that data augmentation significantly enhances model performance across all cases, with the mAP and AR for the Faster R-CNN ResNet model increasing by approximately 4%, achieving a maximum mAP (Intersection over Union = 0.5:1.0) of 87.5% and maximum AR of 90.5%. These results highlight the importance of data augmentation in improving the robustness and accuracy of deep learning models for GPR B-scan analysis. The enhanced detection capabilities achieved through these techniques contribute to more reliable subsurface investigations in geotechnical engineering.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.14-28
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• 2010

The aim of this study is to investigate crime hotspot areas using the spatio-temporal cluster analysis which is possible to search simultaneously time range as well as space range as an alternative method of existing hotspot analysis only identifying crime occurrence distribution patterns in urban area. As for research method, first, crime data were collected from criminal registers provided by official police authority in M city, Gyeongnam and crime occurrence patterns were drafted on a map by using Geographic Information Systems(GIS). Second, by utilizing Ripley K-function and Space-Time Scan Statistics analysis, the spatio-temporal distribution of crime was examined. The results showed that the risk of crime was significantly clustered at relatively few places and the spatio-temporal clustered areas of crime were different from those predicted by existing spatial hotspot analysis such as kernel density analysis and k-means clustering analysis. Finally, it is expected that the results of this study can be not only utilized as a valuable reference data for establishing urban planning and crime prevention through environmental design(CPTED), but also made available for the allocation of police resources and the improvement of public security services.

• Journal of the Korea Computer Graphics Society
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• v.23 no.2
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• pp.29-39
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• 2017

This paper presents a unified framework to efficiently and realistically simulate surface and wave foams. The framework is designed to first project 3D water particles from an underlying water solver onto 2D screen space in order to reduce the computational complexity of determining where foam particles should be generated. Because foam effects are often created primarily in fast and complicated water flows, we analyze the acceleration and curvature values to identify the areas exhibiting such flow patterns. Foam particles are emitted from the identified areas in 3D space, and each foam particle is advected according to its type, which is classified on the basis of velocity, thereby capturing the essential characteristics of foam wave motions. We improve the realism of the resulting foam by classifying it into two types: surface foam and wave foam. Wave foam is characterized by the sharp wave patterns of torrential flow s, and surface foam is characterized by a cloudy foam shape even in water with reduced motion. Based on these features, we propose a technique to correct the velocity and position of a foam particle. In addition, we propose a kernel technique using the screen space density to efficiently reduce redundant foam particles, resulting in improved overall memory efficiency without loss of visual detail in terms of foam effects. Experiments convincingly demonstrate that the proposed approach is efficient and easy to use while delivering high-quality results.

• Journal of Korea Water Resources Association
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• v.45 no.3
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• pp.275-290
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• 2012

In this study, we have developed an optimal time distribution model through extraction of peaks over threshold (POT) series. The median values for annual maximum rainfall dataset, which are obtained from the magnetic recording (MMR) and the automatic weather system(AWS) data at Seoul meteorological observatory, were used as the POT criteria. We also suggested the improved methodology for the time distribution of extreme rainfall compared to Huff method, which is widely used for time distributions of design rainfall. The Huff method did not consider changing in the shape of time distribution for each rainfall durations and rainfall criteria as total amount of rainfall for each rainfall events. This study have suggested an extracting methodology for rainfall events in each quartile based on interquartile range (IQR) matrix and selection for the mode quartile storm to determine the ranking cosidering weighting factors on minutely observation data. Finally, the optimal time distribution model in each rainfall duration was derived considering both data size and characteristics of distribution using kernel density function in extracted dimensionless unit rainfall hyetograph.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.54-67
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• 2023

Mount Tai, with an elevation of 1,532 meters, has a reputation as ''The Most Revered of the Five Sacred Mountains (五嶽獨尊)", despite not being the highest mountain in China. A guidebook is a book or pamphlet that contains an introduction and description of specific activities or facilities, especially detailed and accurate information about scenic spots, which provide superior vistas to than other commercially publicized locations. The study aims to investigate Mount Tai's landscape characteristics by analyzing the landscape types and elements, the Kernel Density, the Mean Center and the Standard Deviational Ellipse of the landscape elements appearing in guidebooks introducing Mount Tai. The research results of this study are summarized as follows. First, the landscape type characteristics of Mount Tai are dominated by natural landscapes, which are different from what was shown highlighted in poems and Big Data as they proposed that the landscape characteristics of Mount Tai is dominated by human activities. Second, from the perspective of subdivided landscape types, the landscape elements that appeared in Mount Tai are topography, structure, architecture, plants, semantics, human beings and image orderly, based on the proportion of landscape elements. Third, from the perspective of landscape elements by times series, "Fengshan (封禅)", "sacrifices (祭祀)" and "legends" mostly appeared in the 1950s and 1980s, and after the 1990s, "climbing" and "overlooking" mostly appeared. Fourth, the landscape elements of Mount Tai are concentrated in Daiding (岱顶) and Dai Temple (岱庙) in all periods in terms of spatial distribution. This will become an important space for Mount Tai scenic spots in the future. Moreover, as a whole, the landscape elements of Mount Tai have changed from the concentrated distribution form in Mount Tai scenic spot to the scattered distribution form including Mount Tai and Tai'an City. This will provide necessary enlightenment for the landscape preservation and the re-production of guidebooks of Mount Tai scenic spot in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.457-467
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• 2021

This paper aims to analyze changes in urban space use due to social distancing measures for COVID-19 using de facto population data in Seoul during daytime, which is estimated by Seoul Metropolitan Government and telecommunication company of KT using public big data and LTE signal data. The result of kernel density estimation and spatial autocorrelation analysis shows that the distribution patterns of de facto population in 2019 and 2020 were generally similar. This is a result of showing that the government's social distancing measures enabled a certain level of normal activities while suppressing the spread of COVID-19. However, analyzing de facto population subtracting 2019 from 2020 showed different results at the micro level. De facto population decreased in commercial areas but increased in residential areas. This means that COVID-19 social distancing measures had spatially uneven effect. The results of analyzing the effect of regional, land use, economic, educational, and accessibility characteristics on the changes of de facto population using spatial regression analysis are as follows. The higher the density of commercial facilities, the more businesses subject to regulations and schools and universities that require non-face-to-face classes, the more de facto population decreased. Conversely, it was found that de facto population increased in areas with many houses and parks due to telecommuting.

• The Journal of Korea Robotics Society
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• v.7 no.4
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• pp.292-298
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• 2012

It is a real-time system that the system correctness depends not only on the correctness of the logical result of the computation but also on the result delivery time. Real-time Operating System (RTOS) is a software that manages the time of a microprocessor to ensure that the most important code runs first so that it is a good building block to design the real-time system. The real-time performance is achieved by using real-time mechanisms through data communication and synchronization of inter-task communication (ITC) between tasks. Therefore, test on the response time of real-time mechanisms is a good measure to predict the performance of real-time systems. This paper aims to analysis the response characteristics of real-time mechanisms in kernel space for real-time embedded Linux: RTAI and Xenomai. The performance evaluations of real-time mechanism depending on the changes of task periods are conducted. Test metrics are jitter of periodic tasks and response time of real-time mechanisms including semaphore, real-time FIFO, Mailbox and Message queue. The periodicity of tasks is relatively consistent for Xenomai but RTAI reveals smaller jitter as an average result. As for real-time mechanisms, semaphore and message transfer mechanism of Xenomai has a superior response to estimate deterministic real-time task execution. But real-time FIFO in RTAI shows faster response. The results are promising to estimate deterministic real-time task execution in implementing real-time systems using real-time embedded Linux.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.968-972
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• 2009

The multi-core processors are being widely exploited by many high-end systems. With significant advances in processor architecture, the network band-width required on the high-end systems is increasing drastically. It is therefore highly desirable to manage multiple cores efficiently to achieve high network band-width with minimum resource requirements. Modern operating systems, however, still have significant design and optimization space to leverage the network performance over multi-core systems. In this paper, we suggest a novel networking process scheduling scheme, which decides the best processor affinity of networking processes based on the processor cache layout, communication intensiveness, and processor loads. The experimental results show that the scheduling scheme implemented in the Linux kernel can improve the network bandwidth and the effectiveness of processor utilization by 20% and 59%, respectively.

• Korean Journal of Biological Psychiatry
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• v.15 no.2
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• pp.118-125
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• 2008

Objectives : The purpose of this study was to find brain regions in which gray matter volume was reduced and to show the capability of voxel-based morphpmetry(VBM) analysis for lateralizing clinically significant brain regions in dementia of Alzheimer's type patients compared to healthy group. Methods : MR T1-weighted images of the 20 dementia of Alzheimer's type patients were compared with those of the 20 normal controls. Images were transformed to standard MNI space. In order to observe gray matter volume change. Gray matter was smoothed with a Gaussian kernel. After these preprocessing, statistical analysis was performed using statistical parametric mapping software(SPM2). Results : Gray matter volume was significantly reduced in the bilateral parahippocampal gyri, Lt. anterior cingulate gyrus, Lt. posterior cingulate gyrus, bilateral superior temporal gyri Lt. middle temporal gyrus, Lt. superior, bilateral middle, Rt. anterior frontal gyri and Rt. precuneus in dementia of Alzheimer's type patient group. Conclusions : These VBM results confirm previous findings of temporal lobe and limbic lobe atrophic changes in dementia of Alzheimer's type, and suggest that these abnormalities may be confined to specific sites within that lobe, rather than showing a widespread distribution.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1333-1344
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• 1998

In comparison to traditional monolithic kernel, the microkernel based operating system has slower speed. But Microkernel based OS suites for multi-computer system, because It has benefits in the modularity and portability point of view. Each unit and memory of a processor must be initialized by using the boot information so that the multi-computer system OS can actively run the function of the system. This paper describes the microkernel initialization of OSF/1 AD3 MISIX that is based on OSF/1 AD3 for SPAX. It will introduce the initialization of microkernel for the SPAX which is High-speed Parallel Processing system in terms of Boot, Initialization related hardware and memory address space construction. This paper will also state the test result based on test environments. Microkernel tested in single node system that has 4 processors.