• Journal of Positioning, Navigation, and Timing
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• v.6 no.3
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• pp.105-116
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• 2017

Several wireless localization algorithms are evaluated for the IR-UWB-based indoor location with the assumption that the ranging measurements contain the channelwise Non-Calibration Error (NCE). The localization algorithms can be divided into the Model-free Localization (MfL) methods and Model-based Kalman Filtering (MbKF). The algorithms covered in this paper include Iterative Least Squares (ILS), Direct Solution (DS), Difference of Squared Ranging Measurements (DSRM), and ILS-Common (ILS-C) methods for the MfL methods, and Extended Kalman Filter (EKF), EKF-Each Channel (EKF-EC), EKF-C, Cubature Kalman Filter (CKF), and CKF-C for the MbKF. Experimental results show that the DSRM method has better accuracy than the other MfL methods. Also, it demands smallest computation time. On the other hand, the EKF-C and CKF-C require some more computation time than the DSRM method. The accuracy of the EKF-C and CKF-C is, however, best among the 9 methods. When comparing the EKF-C and CKF-C, the CKF-C can be easily used. Finally, it is concluded that the CKF-C can be widely used because of its ease of use as well as it accuracy.

• Computers and Concrete
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• v.34 no.2
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• pp.247-265
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• 2024

Measuring the fracture toughness of concrete in laboratory settings is challenging due to various factors, such as complex sample preparation procedures, the requirement for precise instruments, potential sample failure, and the brittleness of the samples. Therefore, there is an urgent need to develop innovative and more effective tools to overcome these limitations. Supervised learning methods offer promising solutions. This study introduces seven machine learning algorithms for predicting concrete's effective fracture toughness (K-eff). The models were trained using 560 datasets obtained from the central straight notched Brazilian disc (CSNBD) test. The concrete samples used in the experiments contained micro silica and powdered stone, which are commonly used additives in the construction industry. The study considered six input parameters that affect concrete's K-eff, including concrete type, sample diameter, sample thickness, crack length, force, and angle of initial crack. All the algorithms demonstrated high accuracy on both the training and testing datasets, with R² values ranging from 0.9456 to 0.9999 and root mean squared error (RMSE) values ranging from 0.000004 to 0.009287. After evaluating their performance, the gated recurrent unit (GRU) algorithm showed the highest predictive accuracy. The ranking of the applied models, from highest to lowest performance in predicting the K-eff of concrete, was as follows: GRU, LSTM, RNN, SFL, ELM, LSSVM, and GEP. In conclusion, it is recommended to use supervised learning models, specifically GRU, for precise estimation of concrete's K-eff. This approach allows engineers to save significant time and costs associated with the CSNBD test. This research contributes to the field by introducing a reliable tool for accurately predicting the K-eff of concrete, enabling efficient decision-making in various engineering applications.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.345-346
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• 2023

As the shape and size of detectable objects diversifying recognition and segmentation algorithms have been developed to acquire accurate shape information. Although a high density of data captured by the repetition of scanning improves the accuracy of algorithms the high dense data decreases the efficiency due to its large size. This paper proposes standardization algorithms using the feature of structural members on indoor point cloud data to improve the process. First of all we determine the reduction rate of the density based on the features of the target objects then the data reduction algorithm compresses the data based on the reduction rate. Second the data arrangement algorithm rotates the data until the normal vector of data is aligned along the coordinate axis to allow the following algorithms to operate properly. Final the data arrangement algorithm separates the rotated data into their leaning axis. This allows reverse engineering of indoor point clouds to obtain the efficiency and accuracy of refinement processes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6A
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• pp.600-607
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• 2007

In this paper, we propose a MLKA (Multi-Level Keep-Alive) algorithm based on PRCG (Periodic In this paper, we propose a MLKA (Multi-Level Keep-Alive) algorithm based on PRCG (Periodic Ranging Code Group), in which periodic ranging codes are divided into groups. The AP (Access Point) performs this algorithm when a periodic ranging code arrives at the AP in a WiBro (Wireless Broadband Internet) system. In order to increase the traffic radio bandwidth resource efficiency in this system, we propose the multi-level keep-alive algorithm for finding abnormal AT (Access Terminal). From simulation results, it is verified our proposed MLKA algorithm based on PRCG can provide higher traffic radio resource efficiency compared to message-driven keep-alive algorithms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.4
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• pp.96-103
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• 2007

In this paper, we present a novel and numerically efficient algorithm for high resolution TOA(Time Of Arrival) estimation under indoor radio propagation channels. The proposed algorithm is not dependent on the structure of receivers, i.e, it can be used with either coherent or non-coherent receivers. The TOA estimation algorithm is based on a high resolution frequency estimation algorithm of Minimum-norm. The efficiency of the proposed algorithm relies on numerical analysis techniques in computing signal or noise subspaces. The algorithm is based on the two step procedures, one for transforming input data to frequency domain data and the other for estimating the unknown TOA using the proposed efficient algorithm. The efficiency in number of operations over other algorithms is presented. The performance of the proposed algorithm is investigated by means of computer simulations.. Throughout the analytic and computer simulation results, we show that the proposed algorithm exhibits superior performance in estimating TOA estimation with limited computational cost.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.4
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• pp.467-474
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• 2019

Recently, optical phased array(OPA) based laser detection and ranging(LADAR) has gained great interest to replace the traditional mechanical light detection and ranging technique(LiDAR). In OPA-based LADAR, it is well known that phases of laser pulses traveling through each of channels should be the same to obtain a narrow free-space single beam without noise-like ripples in the far field. However, it is difficult to provide such ideal condition due to the fabrication errors. To tackle this problem, any algorithms should be necessary to compensate the initial random phases of each channel in OPA antenna. In this paper, we propose a hill-climbing based phase calibration algorithm and evaluate the performance of the proposed algorithm.

• International Journal of Contents
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• v.1 no.2
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• pp.18-21
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• 2005

The following suggested algorithm is completed care report for the family medical history. Rn=$U\;Pnj+U\;Dn^i$ : (j=1,2,...,j), (i=1,2,...,i), (n=1,2,...,n) The Rn(completed care report) integrates comprehensive patients reports ranging from patient $P^2\;to\;P^j$ including $P^1$ (oneself) with the doctors' care reports up to the care No. no by i number of doctors ($D^1$ =doctor in charge, $D^{2,3...i}$=doctors on corporation program.) This approach, since a participation in a family membership effectuates all of family members, can minimize the membership fees, thus enabling inter-family health care on a home doctor basis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.4
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• pp.115-126
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• 2002

This paper deals with efficient algorithms for computing a product of n distinct powers in a group(called multi-exponentiation). Four different algorithms are presented and analyzed, each of which has its own range of n for best performance. Using the best performing algorithm for n ranging from 2 to several thousands, one can achieve 2 to 4 times speed-up compared to the baseline binary algorithm and 2 to 10 times speed-up compared to individual exponentiation.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.131-134
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• 2006

LiDAR(Light Detection And Ranging) 데이터 처리에 있어서 건물, 자동차, 수목 등의 비지면 객체와 지면을 분류하는 필터링 과정은 DEM(Digital Elevation Model) 구축을 위해서 중요하다. 도심지역의 건물추출 등의 필터링에 관한 연구는 활발히 진행되고 있으나 국내의 경우 수목에 대한 필터링은 비교적 연구가 미흡하였다. 따라서 이 연구에서는 기존에 다루어진 몇 가지 알고리즘을 분석하고 산림지역에 활용해 봄으로써 각 필터링에 관한 장단점을 비교하였다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.961-968
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• 1987

This paper describes an intelligent image compression system called AIIC which is capable of adjusting image compression ratios ranging from 1:1 to 12,000:1 depending on available bandwidth. This system utilizes not only conventional image compression algorithms but also intelligent techniques through understanding image contents to achieve ultra-high compression ratios. This system was simulated on a micro-computer network.