• Geomechanics and Engineering
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• v.36 no.5
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• pp.427-440
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• 2024

This study concentrates on the 301 comprehensive caving working face, notable for its considerable mining height. The roof model is established by integrating prior geological data and the latest borehole rock stratum's physical and mechanical parameters. This comprehensive approach enables the determination of lithology, thickness, and mechanical properties of the roof within 50 m of the primary mining coal seam. Utilizing the transfer rock beam theory and incorporating mining pressure monitoring data, the study delves into the geometric parameters of the direct roof, basic roof movement, and roof pressure during the initial mining process of the 301 comprehensive caving working face. The direct roof of the mining working face is stratified into upper and lower sections. The lower direct roof consists of 6.0 m thick coarse sandstone, while the upper direct roof comprises 9.2 m coarse sandstone, 2.6 m sandy mudstone, and 2.8 m medium sandstone. The basic roof stratum, totaling 22.1 m in thickness, includes layers such as silty sand, medium sandstone, sandy mudstone, and coal. The first pressure step of the basic roof is 61.6 m, with theoretical research indicating a maximum roof pressure of 1.62 MPa during periodic pressure. Extensive simulations and analyses of roof subsidence and advanced abutment pressure under varying working face lengths. Optimal roof control effect is observed when the mining face length falls within the range of 140 m-155 m. This study holds significance as it optimizes the working face length in thick coal seams, enhancing safety and efficiency in coal mining operations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.123-133
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• 2024

Existing autonomous driving technology has been developed based on sensors attached to the vehicles to detect the environment and formulate driving plans. On the other hand, it has limitations, such as performance degradation in specific situations like adverse weather conditions, backlighting, and obstruction-induced occlusion. To address these issues, cooperative autonomous driving technology, which extends the perception range of autonomous vehicles through the support of road infrastructure, has attracted attention. Nevertheless, the real-time analysis of the 3D centroids of objects, as required by international standards, is challenging using single-lens cameras. This paper proposes an approach to detect objects and estimate the centroid of vehicles using the fixed field of view of road infrastructure and pre-measured geometric information in real-time. The proposed method has been confirmed to effectively estimate the center point of objects using GPS positioning equipment, and it is expected to contribute to the proliferation and adoption of cooperative autonomous driving infrastructure technology, applicable to both vehicles and road infrastructure.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.353-360
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• 2006

This paper presents a robust algorithm for segmenting a vehicle license plate area from a road image. We consider the features of license plates in three aspects : 1) edges due to the characters in the plate, 2) colors in the plate, and 3) geometric properties of the plate. In the preprocessing step, we compute the thresholds based on each feature to decide whether a pixel is inside a plate or not. A statistical approach is applied to the sample images to compute the thresholds. For a given road image, our algorithm binarizes it by using the thresholds. Then, we select three candidate regions to be a plate by searching the binary image with a moving window. The plate area is selected among the candidates with simple heuristics. This algorithm robustly detects the plate against the transformation or the difference of color intensity of the plate in the input image. Moreover, the preprocessing step requires only a small number of sample images for the statistical processing. The experimental results show that the algorithm has 97.8% of successful segmentation of the plate from 228 input images. Our prototype implementation shows average processing time of 0.676 seconds per image for a set of $1280{\times}960$ images, executed on a 3GHz Pentium4 PC with 512M byte memory.

• Spatial Information Research
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• v.9 no.1
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• pp.51-72
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• 2001

It is frequently pointed out that the conventional field survey for natural environment has may limitations in terms of positional accuracy, real-time GIS data acquisition, and economic efficiency. The aim of this research was to develop an on site real-time mapping technique that enables the surveyor to input data in the field. The idea is based upon the recent trends in the field of Telecommunication and Information Technology that uses a GPS, wireless network computing, moving computing, etc. A virtual office approach has been adopted, in which a portable computer is linked to a GPS and field workers record data on the computer at the site and analyse data on site. This field mapping system has shown to be much less susceptible to the positional accuracy than that of th conventional approach. The Graphic User Interface, in particular, were ideally suited to combining positional information with attribute data which changes with every survey points. This interface allows users to interactively display and query GIS layers reproduced from the past survey results. The GIS database stored in the virtual office will serve to carry out a highly reliable survey since it could play a crucial role in identifying temporal and spatial changes occurred in the site. It is expected that integrated utilization of field data among the related agencies would be increased much more than before since the virtual office survey would be a powerful tool to ensure geometric fidelity in GIS database creation process. This paper also discusses the limitations and future direction of the present prototype research.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.281-285
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• 2008

Wireless sensor networks are closely related with the geometric environment in which they are deployed. We consider the probable case when a routing protocol runs on an environment with many complex obstacles like downtown surroundings. In addition, there are no unrealistic assumptions in order to increase practicality of the protocol. Our goal is to find a routing protocol for maximizing network lifetime by using only connectivity information in the complex sensor network environment. We propose a topology-based routing algorithm that accomplishes good performance in terms of network lifetime and routing complexity as measures. Our routing algorithm makes routing decision based on a weighted graph as topological abstraction of the complex network. The graph conduces to lifetime enhancement by giving alternative paths, distributing the skewed burden. An energy estimation method is used so as to maintain routing information without any additional cost. We show how our approach can be used to maximize network lifetime and by extensive simulation we prove that out approach gives good results in terms of both measures-network lifetime and routing complexity.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.11
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• pp.1307-1314
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• 2012

To reduce the effects of clutters with subsurface inhomogenities in ground-penetrating radar(GPR) images, an eigenimage based signal-processing technique is presented. If the conventional eigenimage filtering technique is applied to B-scan images of a GPR survey, relatively homogeneous clutters such as antenna ringing, direct coupling between transmitting and receiving antennas, and soil-surface reflection, can be removed sufficiently. However, since random clutters of subsurface inhomogenities still remain in the images, target signals are distorted and obscured by the clutters. According to a comparison of the eigenimage filtering results, there is different coherency between subsurface clutters and target signals. To reinforce the pixels with high coherency and reduce the pixels with low coherency, the pixel-by-pixel geometric-mean process after the eigenimage filtering is proposed here. For the validity of the proposed approach, GPR survey for detection of a metal target in a randomly inhomogeneous soil is numerically simulated by using a random media generation technique and the finite-difference time-domain(FDTD) method. And the proposed signal processing is applied to the B-scan data of the GPR survey. We show that the proposed approach provides sufficient enhancement of target signals as well as remarkable reduction of subsurface inhomogeneous clutters in comparison with the conventional eigenimage filtering.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.9
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• pp.479-490
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• 2001

In this paper, we consider the method of partitioning a sphere into faces with a set of spherical convex polygons $\Gamma$=$｛P_1...P_n｝$ for determining the maximum of minimum intersection. This problem is commonly related with five geometric problems that fin the densest hemisphere containing the maximum subset of $\Gamma$, a great circle separating $\Gamma$, a great circle bisecting $\Gamma$ and a great circle intersecting the minimum or maximum subset of $\Gamma$. In order to efficiently compute the minimum or maximum intersection of spherical polygons. we take the approach of edge-based partition, in which the ownerships of edges rather than faces are manipulated as the sphere is incrementally partitioned by each of the polygons. Finally, by gathering the unordered split edges with the maximum number of ownerships. we approximately obtain the centroids of the solution faces without constructing their boundaries. Our algorithm for finding the maximum intersection is analyzed to have an efficient time complexity O(nv) where n and v respectively, are the numbers of polygons and all vertices. Furthermore, it is practical from the view of implementation, since it computes numerical values. robustly and deals with all the degenerate cases, Using the similar approach, the boundary of a general intersection can be constructed in O(nv+LlogL) time, where : is the output-senstive number of solution edges.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.63-70
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• 2009

Recently, in the security token based authentication system, there is an increasing trend of using fingerprint for the token holder verification, instead of passwords. However, the security of the fingerprint data is particularly important as the possible compromise of the data will be permanent. In this paper, we propose an approach for secure fingerprint verification by distributing both the secret and the computation based on the fuzzy vault(a cryptographic construct which has been proposed for crypto-biometric systems). That is, a user fingerprint template which is applied to the fuzzy vault is divided into two parts, and each part is stored into a security token and a server, respectively. At distributing the fingerprint template, we consider both the security level and the verification accuracy. Then, the geometric hashing technique is applied to solve the fingerprint alignment problem, and this computation is also distributed over the combination of the security token and the server in the form of the challenge-response. Finally, the polynomial can be reconstructed from the accumulated real points from both the security token and the server. Based on the experimental results, we confirm that our proposed approach can perform the fuzzy vault-based fingerprint verification more securely on a combination of a security token and a server without significant degradation of the verification accuracy.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.95-109
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• 1993

In this study, the optimal configuration of arch structure has been tested by a decomposition technique. The object of this study is to provide the method of optimizing the shapes of both two hinged and fixed arches. The problem of optimal configuration of arch structures includes the interaction formulas, the working stress, and the buckling stress constraints on the assumption that arch ribs can be approximated by a finite number of straight members. On the first level, buckling loads are calculated from the relation of the stiffness matrix and the geometric stiffness matrix by using Rayleigh-Ritz method, and the number of the structural analyses can be decreased by approximating member forces through sensitivity analysis using the design space approach. The objective function is formulated as the total weight of the structures, and the constraints are derived by including the working stress, the buckling stress, and the side limit. On the second level, the nodal point coordinates of the arch structures are used as design variables and the objective function has been taken as the weight function. By treating the nodal point coordinates as design variable, the problem of optimization can be reduced to unconstrained optimal design problem which is easy to solve. Numerical comparisons with results which are obtained from numerical tests for several arch structures with various shapes and constraints show that convergence rate is very fast regardless of constraint types and configuration of arch structures. And the optimal configuration or the arch structures obtained in this study is almost the identical one from other results. The total weight could be decreased by 17.7%-91.7% when an optimal configuration is accomplished.