• Geomechanics and Engineering
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• v.29 no.4
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• pp.391-405
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• 2022

A newly proposed grouting simulation method, the sequential diffusion solidification method was introduced into the numerical simulation of combined bi-borehole grouting. The traditional, critical and difficult numerical problem for the temporal and spatial variation simulation of the slurry is solved. Thus, numerical simulation of grouting and blocking of flowing water in karst conduits is realized and the mechanism understanding of the combined bi-borehole technology is promoted. The sensitivity analysis of the influence factors of combined bi-borehole grouting was investigated. Through orthogonal experiment, the influences of proximal and distal slurry properties, the initial flow velocity of the conduit and the proximal and distal slurry injection rate on the blocking efficiency are compared. The velocity variation, pressure variation and slurry deposition phenomenon were monitored, and the flow field characteristics and slurry outflow behavior were analyzed. The interaction mechanism between the proximal and distal slurries in the combined bi-borehole grouting is revealed. The results show that, under the orthogonal experiment conditions, the slurry injection rate has the greatest impact on blocking. With a constant slurry injection rate, the blocking efficiency can be increased by more than 30% when using slurry with weak time-dependent viscosity behavior in the distal borehole and slurry with strong time-dependent viscosity behavior in the proximal borehole respectively. According to the results of numerical simulation, the grouting scheme of "intercept the flow from the proximal borehole by quick-setting slurry, and grout cement slurry from the distal borehole" is put forward and successfully applied to the water inflow treatment project of China Resources Cement (Pingnan) Limestone Mine.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.172-172
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• 2020

In recent years, soil erosion has come to be regarded as an essential environmental problem in human life. Soil erosion causes various on- and off-site problems such as ecosystem destruction, decreased agricultural productivity, increased riverbed deposition, and deterioration of water quality in streams. To solve these problems caused by soil erosion, it is necessary to quantify where, when, how much soil erosion occurs. Empirical erosion models such as the Universal Soil Loss Equation (USLE) family models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well by utilizing big data related to climate, geography, geology, land use, etc. within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models remain powerful tools to distinguish erosion-prone areas at the macro scale but physics-based models are necessary to better analyze soil erosion and deposition and eroded particle transport. In this study, the physics-based Surface Soil Erosion Model (SSEM) was upgraded based on field survey information to produce sediment yield at the watershed scale. The modified model (hereafter MoSE) adopted new algorithms on rainfall kinematic energy and surface flow transport capacity to simulate soil erosion more reliably. For model validation, we applied the model to the Doam dam watershed in Gangwon-do and compared the simulation results with the USLE outputs. The results showed that the revised physics-based soil erosion model provided more improved and reliable simulation results than the USLE in terms of the spatial distribution of soil erosion and deposition.

• Geomechanics and Engineering
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• v.34 no.2
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• pp.155-171
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• 2023

Aiming at the grouting treatment of water inflow in karst conduits, a visualized experiment system for conduit-type grouting blocking was developed. Through the improved water supply system and grouting system, and the optimized multisource information monitoring system, the real-time observation of diffusion and deposition of slurry, and the data acquisition of pressure and velocity during the whole process of grouting were realized, which breaks through the problem that the monitoring element is easy to fail due to slurry adhesion in conventional test system. Based on the grouting experiments in static and flowing water, the diffusion and deposition behavior of the quick-setting slurry under different working conditions were analyzed. The temporal and spatial variation behavior of the pressure and velocity were studied, and the blocking mechanism of the grouting were further revealed. The results showed that: (1) Under the flowing water condition, the counter-flow diffusion distance of slurry was negatively correlated with the flow water velocity and the volume ratio of cement and sodium silicate (C-S ratio), and positively correlated with the grouting volume. The slurry deposition thickness was negatively correlated with the flowing water velocity, and positively correlated with the grouting volume and C-S ratio. (2) The pressure increased slowly before blocking of the flowing water and rapidly after blocking in karst conduits. (3) With the continuous progress of grouting, the flowing water velocity decreased slowly first, then significantly, and finally tended to be stable. According to the research results, some engineering recommendations were put forward for the grouting treatment of the conduit-type water inflow disaster, which has been successfully applied in the treatment project of the China Resources Cement (Pingnan) Limestone Mine. This study provided some guidance and reference for the parameter optimization of grouting for the treatment projects of water inflow in karst conduits.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.891-907
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• 2023

Compact Advanced Satellite 500-4 (CAS500-4) is scheduled to be launched to collect high spatial resolution data focusing on vegetation applications. To achieve this goal, accurate surface reflectance retrieval through atmospheric correction is crucial. Therefore, a machine learning-based atmospheric correction algorithm was developed to simulate atmospheric correction from a radiative transfer model using Sentinel-2 data that have similarspectral characteristics as CAS500-4. The algorithm was then evaluated mainly for forest areas. Utilizing the atmospheric correction parameters extracted from Sentinel-2 and GEOKOMPSAT-2A (GK-2A), the atmospheric correction algorithm was developed based on Random Forest and Light Gradient Boosting Machine (LGBM). Between the two machine learning techniques, LGBM performed better when considering both accuracy and efficiency. Except for one station, the results had a correlation coefficient of more than 0.91 and well-reflected temporal variations of the Normalized Difference Vegetation Index (i.e., vegetation phenology). GK-2A provides Aerosol Optical Depth (AOD) and water vapor, which are essential parameters for atmospheric correction, but additional processing should be required in the future to mitigate the problem caused by their many missing values. This study provided the basis for the atmospheric correction of CAS500-4 by developing a machine learning-based atmospheric correction simulation algorithm.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.25-41
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• 2024

For the scenario of open pit mining, at present, manual periodic verification is mainly carried out in China with the help of video surveillance, which requires continuous investment in labor cost and has poor timeliness. In order to solve this difficult problem of early warning and monitoring, this paper researches a spatialized algorithmic model and designs an early warning system for open-pit mine transboundary mining, which is realized by calculating the coordinate information of the mining and extracting equipments and comparing it with the layer coordinates of the approval range of the mines in real time, so as to realize the determination of the transboundary mining behavior of the mines. By taking the Pingxiang area of Jiangxi Province as the research object, after the field experiment, it shows that the system runs stably and reliably, and verifies that the target tracking accuracy of the system is high, which can effectively improve the early warning capability of the open-pit mines' overstepping the boundary, improve the timeliness and accuracy of mine supervision, and reduce the supervision cost.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.103-115
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• 2024

Trilateral adjustment can complement the problem of transforming cadastral maps into World Geodetic Coordinate system. First, it is possible to determine adjusted coordinate of common points that match each other over a wide area. Second, calculations that focus on specific points can be performed. Third, a solution that maintains the shape of the regional network can be obtained through constraints. Thus, the point coordinates can be determined appropriately for the survey system. In addition, heterogeneous survey results that span regions with different coordinate origins can be calculated on a single origin coordinate. This improves the efficiency of the workflow in tranforming cadastral maps into World Geodetic Coordinate System.

• The Mathematical Education
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• v.63 no.2
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• pp.295-318
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• 2024

This narrative review explores the transformative potential of immersive virtual reality (IVR) in enhancing high school students' mathematics competence, viewed through the lens of the technological, pedagogical, and content knowledge (TPACK) framework. This review comprehensively illustrates how IVR technologies have not only fostered a deeper understanding and engagement with mathematical concepts but have also enhanced the practical application of these skills. Through the careful examination of seminal papers, this study carefully explores the integration of IVR in high school mathematics education. It highlights significant contributions of IVR in improving students' computational proficiency, problem-solving skills, and spatial visualization abilities. These enhancements are crucial for developing a robust mathematical understanding and aptitude, positioning students for success in an increasingly technology-driven educational landscape. This review emphasizes the pivotal role of teachers in facilitating IVR-based learning experiences. It points to the necessity for comprehensive teacher training and professional development to fully harness the educational potential of IVR technologies. Equipping educators with the right tools and knowledge is essential for maximizing the effectiveness of this innovative teaching approach. The findings also indicate that while IVR holds promising prospects for enriching mathematics education, more research is needed to elaborate on instructional integration approaches that effectively overcome existing barriers. This includes technological limitations, access issues, and the need for curriculum adjustments to accommodate new teaching methods. In conclusion, this review calls for continued exploration into the effective use of IVR in educational settings, aiming to inform future practices and contribute to the evolving landscape of educational technology. The potential of IVR to transform educational experiences offers a compelling avenue for research and application in the field of mathematics education.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.19-20
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• 2023

The pre-qualification system related to floor impact noise is considered ineffective, and thus, the introduction of a post-verification system is being prepared. This is because the performance, which was notarized in the qualification test due to various reasons, was not uniformly confirmed on building construction fields. Industry practitioners perceive that this is due to the influence of factors such as the flatness, levelness and/or thickness of the floor. However, it is very difficult to confirm such facts in a short period of time on the fields, and since the practical application of technology to measure and evaluate quantitatively and the establishment of a system are insufficient, it cannot be said to be a problem that can be brought to the surface. In fact, even when considering the conventional measurement of the dynamic modulus of elasticity, measurements are performed under controlled variables, such as placing a 200mm×200mm buffer material on a flat test-floor. However, in the fields, it is common to lay down larger productions(for example, 900mm×600mm) on the bare floor where significant variables are not controlled, and to construct finishing layers corresponding to the pre-qualified floor system without separately confirming the realization of the dynamic modulus of elasticity in the field conditions. In this study, spatial information of the bare floor on the field was measured and evaluated through a laser scanner. Technical methods for assessing the smoothness, flatness, and thickness of construction surfaces were reviewed, providing key insights for grading the quality of construction based on these criteria. Through further detailed and thorough investigations, it is expected that results suitable for practical application and systematization will be derived.

• Smart Structures and Systems
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• v.33 no.4
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• pp.291-300
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• 2024

Uncertainty of the model, system delay and drive dynamics can be considered as normal uncertainties, and the main source of uncertainty in the seismic control system is related to the nature of the simulated seismic error. In this case, optimizing the management strategy for one particular seismic record will not yield the best results for another. In this article, we propose a framework for online management of active structural management systems with seismic uncertainty. For this purpose, the concept of reinforcement learning is used for online optimization of active crowd management software. The controller consists of a differential controller, an unplanned gain ratio, the gain of which is enhanced using an online reinforcement learning algorithm. In addition, the proposed controller includes a dynamic status forecaster to solve the delay problem. To evaluate the performance of the proposed controllers, thousands of ground motion data sets were processed and grouped according to their spectrum using fuzzy clustering techniques with spatial hazard estimation. Finally, the controller is implemented in a laboratory scale configuration and its operation is simulated on a vibration table using cluster location and some actual seismic data. The test results show that the proposed controller effectively withstands strong seismic interference with delay. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results is believed to achieved in the near future by the ongoing development of AI and control theory.

• Journal of KIISE:Databases
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• v.31 no.5
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• pp.468-478
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• 2004

It is essential in various application areas of data mining and bioinformatics to effectively retrieve the occurrences of interesting patterns from sequence databases. For example, let's consider a network event management system that records the types and timestamp values of events occurred in a specific network component(ex. router). The typical query to find out the temporal casual relationships among the network events is as fellows: 'Find all occurrences of CiscoDCDLinkUp that are fellowed by MLMStatusUP that are subsequently followed by TCPConnectionClose, under the constraint that the interval between the first two events is not larger than 20 seconds, and the interval between the first and third events is not larger than 40 secondsTCPConnectionClose. This paper proposes an indexing method that enables to efficiently answer such a query. Unlike the previous methods that rely on inefficient sequential scan methods or data structures not easily supported by DBMSs, the proposed method uses a multi-dimensional spatial index, which is proven to be efficient both in storage and search, to find the answers quickly without false dismissals. Given a sliding window W, the input to a multi-dimensional spatial index is a n-dimensional vector whose i-th element is the interval between the first event of W and the first occurrence of the event type Ei in W. Here, n is the number of event types that can be occurred in the system of interest. The problem of‘dimensionality curse’may happen when n is large. Therefore, we use the dimension selection or event type grouping to avoid this problem. The experimental results reveal that our proposed technique can be a few orders of magnitude faster than the sequential scan and ISO-Depth index methods.hods.