• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.4
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• pp.324-330
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• 1990

In this paper, the hybrid ARQ system involving the single error correcting and double error detection (127, 119) cyclic Hamming codes and the SR(selective repeat) ARQ schemes with a finite receiver buffer has been designed and constructed. The system performance has been analyzed and simulated. As a result of the simulation, it has been shown that the transmitter retransmitted those data blocks that were detected in errors especially the request signal errors using two retransmission. The system performance was measured by throughput efficiency due to channel error effects.

• Steel and Composite Structures
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• v.52 no.6
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• pp.695-711
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• 2024

Suspension bridges are critical to urban transportation, but those in earthquake-prone areas face unique challenges. In the event of a moderate or strong earthquake, conventional linear theory-based approaches for detecting bridge damage become inadequate. This study presents an efficient method for identifying damage in suspension bridges using time history nonlinear inelastic analysis. A practical advanced analysis program is employed to model cable-supported bridges with low computational cost, generating a dataset for four hybrid models: PSO-DT, PSO-RF, PSO-XGB, and PSO-CGB. These models combine decision tree (DT), random forest (RF), extreme gradient boosting (XGB), and categorical gradient boosting (CGB) with particle swarm optimization (PSO) to capture nonlinear correlations between displacement response and damage. Principal component analysis reduces dataset dimensions, and PSO selects the optimal model. A numerical case study of a suspension bridge under simulated earthquake conditions identifies PSO-XGB as the best model for predicting stiffness reduction. The results demonstrate the method's robustness for nonlinear damage detection in suspension bridges under earthquake excitation.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.7-13
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• 2018

The methods for detecting copy move frogery (CMF) are divided into two categories, block-based methods and keypoint-based methods. Block-based methods have a high computational cost because a large number of blocks should be examined for CMF detection. In addition, the forgery detection may fail if a tampered region undergoes geometric transformation. On the contrary, keypoint-based methods can overcome the disadvantages of the block-based approach, but it can not detect a tampered region if the CMF forgery occurs in the low entropy region of the image. Therefore, in this paper, we propose a method to detect CMF forgery in all areas of image by combining keypoint-based and block-based methods. The proposed method first performs keypoint-based CMF detection on the entire image. Then, the areas for which the forgery check is not performed are selected and the block-based CMF detection is performed for them. Therefore, the proposed CMF detection method makes it possible to detect CMF forgery occurring in all areas of the image. Experimental results show that the proposed method achieves better forgery detection performance than conventional methods.

• Journal of IKEEE
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• v.27 no.3
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• pp.213-219
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• 2023

According to statistics from the National Police Agency, smishing crimes using texts or messengers have increased dramatically since COVID-19. In addition, most of the cases of impersonation of public institutions reported to agency were related to vaccination and reward, and many methods were used to trick people into clicking on fake URLs (Uniform Resource Locators). When detecting them, URL-based detection methods cannot detect them properly if the information of the URL is hidden, and content-based detection methods are slow and use a lot of resources. In this paper, we propose a system for URL-based detection using transformer for regular URLs and content-based detection using XGBoost for shortened URLs through the process of determining shortened URLs using GRU(Gated Recurrent Units). The F1-Score of the proposed detection system was 94.86, and its average processing time was 5.4 seconds.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.83-86
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• 2000

DS/CDMA 이동통신 환경에서 채널의 용량을 제한하는 가장 큰 요인은 다중 사용자 간섭 신호의 영향이다. 본 논문에서는 어레이 안테나와 적응 혼합 다중 사용자 검파기 구조 (MUD: Multi-User Detection)를 이용하여 이러한 문제를 제거한다. 어레이 안테나의 각각의 빔 형성기는 MUD에서 궤환되는 기준 신호를 이용하여 원하는 사용자의 방향으로 빔을 형성하고 간섭 신호 방향으로는 널을 형성하여 제거하게 된다. 수신 신호의 전력이 제어되지 못하여 원근 문제(near-far problem)가 발생할 경우, 제안한 MUD는 적응적으로 지배적인 상관 값에 대해서는 직렬형, 비슷한 크기의 신호들은 병렬형 간섭 제거기를 통하여 제거함으로써 기존의 고정형 간섭 제거기보다 우수한 성능을 나타내었다.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.55-67
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• 2015

An important problem in cluster analysis is the selection of variables that define cluster structure that also eliminate noisy variables that mask cluster structure; in addition, outlier detection is a fundamental task for cluster analysis. Here we provide an automated K-means clustering process combined with variable selection and outlier identification. The Automated K-means clustering procedure consists of three processes: (i) automatically calculating the cluster number and initial cluster center whenever a new variable is added, (ii) identifying outliers for each cluster depending on used variables, (iii) selecting variables defining cluster structure in a forward manner. To select variables, we applied VS-KM (variable-selection heuristic for K-means clustering) procedure (Brusco and Cradit, 2001). To identify outliers, we used a hybrid approach combining a clustering based approach and distance based approach. Simulation results indicate that the proposed automated K-means clustering procedure is effective to select variables and identify outliers. The implemented R program can be obtained at http://www.knou.ac.kr/~sskim/SVOKmeans.r.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.50 no.7
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• pp.346-350
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• 2001

We present a surface-micromachined polysilicon capacitive accelerometer using unevenly distributed comb electrodes. The unique features of the accelerometer include a perforated proof-mass and the inner and outer comb electrodes with uneven electrode gaps. The perforated proof-mass reduces stiction between the structure and the substrate and the unevenly distributed electrodes shorten the electrode length required for a given sensitivity. The polysilicon accelerometer has been fabricated by the conventional 6-mask surface-micromachining process and showes a sensitivity of 1.03mV/g with a hybrid detection circuitry.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.121-124
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• 2000

We propose an algorithm for almost unsupervised detection of linear structures, in particular, axes in road network and river, as seen in synthetics aperture radar (SAR) images. The first is local step and used to extract linear features from the speckle radar image, which are treated as road segment candidates. We present two local line detectors as well as a method for fusing Information from these detectors. The second is hybrid step, we Identify the real roads among the segment candidates by defining a Markov random field (MRF) on a set of segments, which introduces contextual knowledge about the shape of road objects.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1585-1601
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• 2017

With the rapid development of computer technologies, a number of image modification methods have emerged, which have great impacts on the security of image information. Therefore, it is necessary to protect the integrity and authenticity of digital images, and digital watermarking technique consequently becomes a research hotspot. An effort is made to survey and analyze advancements of image watermarking algorithms based on singular value decomposition (SVD) in recent years. In the first part, an overview of watermarking techniques is presented and then mathematical theory of SVD is given. Besides, SVD watermarking model, features, and evaluation indexes are demonstrated. Various SVD-based watermarking algorithms, as well as hybrid watermarking algorithms based on SVD and other transforms for copyright protection, tamper detection, location, and recovery are reviewed in the last part.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.911-917
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• 2021

As software gets an increasing amount of patches, lots of software bugs are increasingly caused by such software patches, collectively known as regression bugs. To proactively detect the regressions bugs, both industry and academia are actively searching for a way to augment fuzz testing, one of the most popular automatic bug detection techniques. In this paper, we investigate the status quo of the studies on augmenting fuzz testing for regression bug detection and, based on the limitations of current proposals, provide an outlook of the relevant research.