• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5C
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• pp.483-489
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• 2006

Somani and Peleg proposed t/k-diagnosable system to diagonse more faults than t(dimension) by allowing upper bounded few number of units to be diagnosed incorrectly. Kranakis and Pelc showed that their adaptive diagnosis algorithm was more efficient than that of any previous ones, assuming that the number of faults does not exceed the hypercube dimension. We propose an adaptive diagnosis algorithm using the idea of t/k-diagnosable system on the basis of that of Kranakis and Pelc's. When the number of faults exceeds t, we allow a fault(k=1, 2, 3) to be diagnosed incorrectly. Based on this idea, we find that the performance of the proposed algorithm is nearly as efficient as any previously known strategies and detect above about double faults.

• Smart Structures and Systems
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• v.33 no.3
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• pp.227-241
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• 2024

Safety and structural integrity of civil structures, like bridges and buildings, can be substantially enhanced by employing appropriate structural health monitoring (SHM) techniques for timely diagnosis of incipient damages. The information gathered from health monitoring of important infrastructure helps in making informed decisions on their maintenance. This ensures smooth, uninterrupted operation of the civil infrastructure and also cuts down the overall maintenance cost. With an early warning system, SHM can protect human life during major structural failures. A real-time online damage localization technique is proposed using only the vibration measurements in this paper. The concept of the 'Degree of Scatter' (DoS) of the vibration measurements is used to generate a spatial profile, and fractal dimension theory is used for damage detection and localization in the proposed two-phase algorithm. Further, it ensures robustness against environmental and operational variability (EoV). The proposed method works only with output-only responses and does not require correlated finite element models. Investigations are carried out to test the presented algorithm, using the synthetic data generated from a simply supported beam, a 25-storey shear building model, and also experimental data obtained from the lab-level experiments on a steel I-beam and a ten-storey framed structure. The investigations suggest that the proposed damage localization algorithm is capable of isolating the influence of the confounding factors associated with EoV while detecting and localizing damage even with noisy measurements.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.228-242
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• 2005

The projected clustering seeks to find clusters in different subspaces within a high dimensional dataset. We propose an algorithm to discover near optimal projected clusters without user specified parameters such as the number of output clusters and the average cardinality of subspaces of projected clusters. The objective function of the algorithm computes projected energy, quality, and the number of outliers in each process of clustering. In order to minimize the projected energy and to maximize the quality in clustering, we start to find best subspace of each cluster on the density of input points by comparing standard deviations of the full dimension. The weighting factor for each dimension of the subspace is used to get id of probable error in measuring projected distances. Our extensive experiments show that our algorithm discovers projected clusters accurately and it is scalable to large volume of data sets.

• ETRI Journal
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• v.42 no.1
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• pp.78-89
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• 2020

Human activity recognition (HAR) has become effective as a computer vision tool for video surveillance systems. In this paper, a novel biometric system that can detect human activities in 3D space is proposed. In order to implement HAR, joint angles obtained using an RGB-depth sensor are used as features. Because HAR is operated in the time domain, angle information is stored using the sliding kernel method. Haar-wavelet transform (HWT) is applied to preserve the information of the features before reducing the data dimension. Dimension reduction using an averaging algorithm is also applied to decrease the computational cost, which provides faster performance while maintaining high accuracy. Before the classification, a proposed thresholding method with inverse HWT is conducted to extract the final feature set. Finally, the K-nearest neighbor (k-NN) algorithm is used to recognize the activity with respect to the given data. The method compares favorably with the results using other machine learning algorithms.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.213-218
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• 2009

This paper describes a classical algorithm carrying out dynamic 3D obstacle recognition for autonomous underwater vehicles (AUVs), Support Vector Machines (SVMs). SVM is an efficient algorithm that was developed for recognizing 3D object in recent years. A recognition system is designed using Support Vector Machines for applying the capabilities on appearance-based 3D obstacle recognition. All of the test data are taken from OpenGL Simulation. The OpenGL which draws dynamic obstacles environment is used to carry out the experiment for the situation of three-dimension. In order to verify the performance of proposed SVMs, it compares with Back-Propagation algorithm through OpenGL simulation in view of the obstacle recognition accuracy and the time efficiency.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.3
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• pp.92-99
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• 1999

The inspection unit which is developed and used in this study, is processed the shape data from the CCD camera to seek welding bite section shape, and then calculated as a real dimension from measuring the value of each inspection item. The reason of measuring with the real in this study is came out from the image method which used for a long time, which is extricated the characteristic as the dimension of pixel by recognize pixel. The measurement method of the section shape is that we decide the thresholding value after we drew the histogram to binarizate the object. After that, we make flat the object to get rid of the noise and measure the shape of welded part through the boundarization of the object. The shape measurement is that measure the value of the welding part to adapt the actual operation program from using the ratio between the actual dimension of the standard specimen and the dimension of image, to measure the ratio between the actual product and the camera image. The inspection algorithm which estimates the quality of welded product is developed and also, the software GUI(Graphic User Interface) which processes the automatic test function of the inspection system is developed. We make the foundation of the inspection automatic system and we will help to apply other welding machine.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.539-544
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• 2013

In this paper, we was designed three-dimensional face recognition algorithm using polynomial based RBFNNs and proposed method to calculate the recognition performance. In case of two-dimensional face recognition, the recognition performance is reduced by the external environment like facial pose and lighting. In order to compensate for these shortcomings, we perform face recognition by obtaining three-dimensional images. obtain face image using three-dimension scanner before the face recognition and obtain the front facial form using pose-compensation. And the depth value of the face is extracting using Point Signature method. The extracted data as high-dimensional data may cause problems in accompany the training and recognition. so use dimension reduction data using PCA algorithm. accompany parameter optimization using optimization algorithm for effective training. Each recognition performance confirm using PSO, DE, GA algorithm.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.139-142
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• 2000

$\mu$BGA(Ball Grid Array) is growing in response to a great demand for smaller and lighter packages for the use in laptop, mobile phones and other evolving products. However it is not easy to find its defect by human visual due to in very small dimension. From this point of view, we are interested its development of a vision based automated inspection algorithm. For this, first a 2D view of $\mu$BGA is described under a special blue illumination. Second, a notation-invariant 2D inspection algorithm is developed. Finally a 3D inspection algorithm is proposed for the case of stereo vision system. As a simulation result, it is shown that 3D defect not easy to find by 2D algorithm can be detected by the proposed inspection algorithm.

• Journal of computational fluids engineering
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• v.1 no.1
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• pp.26-34
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• 1996

The performance of the SIMPLE, SIMPLE-C and PISO algorithms for the treatment of the pressure-velocity coupling in fluid flow problems were examined by comparing the computational effort required to obtain the same level of the convergence. Example problems are circular duct and 90-degree bent square-duct. For circular duct case, laminar and turbulent flow were computed. For 90-degree bent square-duct case, laminar flow was simulated by the time-marching method as well as the iterative method. The convergence speed of the other two algorithms are not always superior to SIMPLE algorithm. SIMPLE algorithm is faster than SIMPLE-C algorithm in the simple laminar flow calculations. The application of the PISO algorithm in three dimensional general coordinates is not so effective as in two-dimensional ones. Since computational time of PISO algorithm is increased at each time step(or iterative step) in three dimension, the total convergence speed is not decreased. But PISO algorithm is stable for large time step by using time marching method,.

• Journal of the Korean Society of Safety
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• v.8 no.4
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• pp.54-60
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• 1993

The purpose of this study is to develop a CAD/CAM system for automatic creation and manufacturing of three dimension objects. The computer system used in this study made RAM 2M, CPU 80386, VGA graphic card. The results in this paper are as follows ; 1. By interconnect PC(personal computer) and NC(numerical control) milling machine with RS232C connector, we was constructed with CAD/CAM system. 2. The developed algorithm in this study is able to be design of three dimension object on the computer CRT and manufacturing of NC milling machine. 3. Because of design and modifying on the PC of objects, we can be saving time, cost and improvable precision of objects. 4. Essentially, we expect industrial accident to reduse according as we takes advantage of CAD/CAM system.