• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1233-1241
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• 2023

This paper investigates the efficient application of drone LiDAR technology for acquiring precise point cloud data in construction and civil engineering. A structured workflow encompassing data acquisition, processing, and accuracy verification is introduced. Practical testing on a construction site affirms that drone LiDAR surveying yields accurate and reliable data across various applications. With a focus on accuracy and verification, the results contribute to the progression of surveying methodologies in construction and civil engineering. The findings provide valuable insights into the dynamic technological landscape of these fields, establishing a foundation for more effective and precise surveying techniques. This study underscores the transformative potential of drone LiDAR technology in shaping the future of construction and civil engineering survey practices.

• Journal of Computing Science and Engineering
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• v.10 no.2
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• pp.39-50
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• 2016

In this paper, we present a comparative study of spatial domain features for writer identification and verification with different ink width conditions. The existing methods give high error rates, when comparing two handwritten images with different pen types. To the best of our knowledge, we are the first to design the feature with different ink width conditions. To address this problem, contour based features were extracted using a chain code method. To improve accuracy at higher levels, we considered histograms of chain code and variance in bins of histogram of chain code as features to discriminate handwriting samples. The system was trained and tested for 1,000 writers with two samples using different writing instruments. The feature performance is tested on our newly created dataset of 4,000 samples. The experimental results show that the histogram of chain code feature is good compared to other methods with false acceptance rate of 11.67%, false rejection rate of 36.70%, average error rates of 24.18%, and average verification accuracy of 75.89% on our new dataset. We also studied the effect of amount of text and dataset size on verification accuracy.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3943-3948
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• 2022

Single-photon emission computed tomography is one of the reliable pin-by-pin verification techniques for spent-fuel assemblies. One of the challenges with this technique is to increase the total fuel assembly verification speed while maintaining high verification accuracy. The aim of the present study, therefore, was to develop an artificial intelligence (AI) algorithm-based tomographic image analysis technique for partial-defect verification of fuel assemblies. With the Monte Carlo (MC) simulation technique, a tomographic image dataset consisting of 511 fuel-rod patterns of a 3 × 3 fuel assembly was generated, and with these images, the VGG16, GoogLeNet, and ResNet models were trained. According to an evaluation of these models for different training dataset sizes, the ResNet model showed 100% pattern estimation accuracy. And, based on the different tomographic image qualities, all of the models showed almost 100% pattern estimation accuracy, even for low-quality images with unrecognizable fuel patterns. This study verified that an AI model can be effectively employed for accurate and fast partial-defect verification of fuel assemblies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.4
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• pp.387-394
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• 2000

The biggest factor of errors which is constructed to the database of aerial photo image is happen to process of scanning with aerial photogrammetric scanner. For the quality assurance of aerial phto image database, we are need to the verification process of aerial photogrammetric scanner. This study is purposed to exhibit quality assurance method of aerial photo image database which is established to verification method of accuracy for aerial photogrammetric scanner. As the results of this study, we are established to verification method of accuracy for aerial photogrammetric scanner. And, the proposed methods according to this study are known to contributequality assurance of aerial photo image database.

• Journal of IKEEE
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• v.17 no.3
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• pp.346-351
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• 2013

Low-cost and low-power are important requirements in mobile systems. Thus, when a floating-point arithmetic unit is needed, 24-bit floating-point format can be more useful than 32-bit floating-point format. However, a 24-bit floating-point arithmetic unit can be risky because it usually has lower accuracy than a 32-bit floating-point arithmetic unit. Consecutive floating-point operations are performed in 3D graphic processors. In this case, the verification of the floating-point operation accuracy is important. Among 3D graphic arithmetic operations, the floating-point division is one of the most difficult operations to satisfy the accuracy of $10^{-5}$ which is the required accuracy in OpenGL ES 3.0. No 24-bit floating-point divider, whose accuracy is algebraically verified, has been reported. In this paper, a 24-bit floating-point divider is analyzed and it is algebraically verified that its accuracy satisfies the OpenGL requirement.

• Journal of KIBIM
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• v.3 no.2
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• pp.1-9
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• 2013

Currently, various studies and applications related BIM based quantity take-off have been attempted, because of the accuracy of cost estimating and reliability by using the BIM model information in automatical calculation. Finishing works that have a large number of various types and materials need the higher accuracy and reliability on the BIM-based quantity take-off. Therefore, this study compared and analyzed 2D and 3D based quantity through Test-bed and determine the cause of the quantity difference. This verified the accuracy and efficiency in the BIM-based quantity take-off for finishing works. Also this study has been proposed opinions for calculating the exact BIM-based quantity take-off.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.800-808
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• 2008

A fingerprint verification system based on a set of invariant moment features and a nonlinear Back Propagation Neural Network(BPNN) verifier is proposed. An image-based method with invariant moment features for fingerprint verification is used to overcome the demerits of traditional minutiae-based methods and other image-based methods. The proposed system contains two stages: an off-line stage for template processing and an on-line stage for testing with input fingerprints. The system preprocesses fingerprints and reliably detects a unique reference point to determine a Region-of-Interest(ROI). A total of four sets of seven invariant moment features are extracted from four partitioned sub-images of an ROI. Matching between the feature vectors of a test fingerprint and those of a template fingerprint in the database is evaluated by a nonlinear BPNN and its performance is compared with other methods in terms of absolute distance as a similarity measure. The experimental results show that the proposed method with BPNN matching has a higher matching accuracy, while the method with absolute distance has a faster matching speed. Comparison results with other famous methods also show that the proposed method outperforms them in verification accuracy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.725-729
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• 2000

This paper presented a new model of NC verification in ball end milling. The model verifies the over cut the under cut and the surface roughness using NC file generated from CAM and cutting condition. The model uses Z-map model to verify workpiece. In this paper, the model used the velocities of x, y and z direction and obtained a center point of a ball end mill for modeling Z-map of workpiece. To investigate the performance of the model simulation study was carried out. As the results, the model gave geometry accuracy of workpiece, the surface roughness and the chip loads in finish cutting that can predict tool chipping.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2213-2220
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• 2022

The maximum dose delivery at the end of the beam range provides the main advantage of using proton therapy. The range of the proton beam, however, is subject to uncertainties, which limit the clinical benefits of proton therapy and, therefore, accurate in vivo verification of the beam range is desirable. For the beam range verification in spot scanning proton therapy, a prompt gamma detection system, called as gamma electron vertex imaging (GEVI) system, is under development and, in the present study, the performance of the GEVI system in spot scanning proton therapy was predicted with Geant4 Monte Carlo simulations in terms of shift detection sensitivity, accuracy and precision. The simulation results indicated that the GEVI system can detect the interfractional range shifts down to 1 mm shift for the cases considered in the present study. The results also showed that both the evaluated accuracy and precision were less than 1-2 mm, except for the scenarios where we consider all spots in the energy layer for a local shifting. It was very encouraging results that the accuracy and precision satisfied the smallest distal safety margin of the investigated beam energy (i.e., 4.88 mm for 134.9 MeV).

• MALSORI
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• no.49
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• pp.145-158
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• 2004

This paper is aiming at implementation of real-time speaker verification system using DSP board. Dialog/4, which is based on microprocessor and DSP processor, is selected to easily control telephone signals and to process audio/voice signals. Speaker verification system performs signal processing and feature extraction after receiving voice and its ID. Then through computing the likelihood ratio of claimed speaker model to the background model, it makes real-time decision on acceptance or rejection. For the verification experiments, total 15 speaker models and 6 background models are adopted. The experimental results show that verification accuracy rates are 99.5% for using telephone speech-based speaker models.