• Journal of the Semiconductor & Display Technology
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• v.23 no.3
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• pp.39-45
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• 2024

The installation of arc circuit breakers is being strengthened to prevent accidents such as electric shock and fire caused by Arc. Among arcs, serial arcs are difficult to detect with general arc detectors because there is not much change in load current when an arc occurs. Therefore, in this paper, unlike the existing Arc Fault Circuit Interrupters method, arc detection hardware is implemented using the FFT algorithm. FFT is suitable for serial arc identification because it can efficiently analyze high-frequency signals generated outside of normal AC signals. This study explains ARC detection circuits and the 2048-FFT based on radix-2 and radix-4, and presents hardware implementation results using FPGA. The implemented system detects the arc up to the frequency range of 122,880 Hz. Through simulation and FPGA board testing, it was confirmed that ARC was detected.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.276-282
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• 2005

These studies developed system as well as its algorithm which can measure traffic flow and vehicle speed on the highway as well as road by using industrial television(ITV) system. This algorithm used the real time processing of dynamic images. The processing algorithm of dynamic images is developed and proved its validity by frame grabber. Frame grabber can process the information of a small number of sample points only instead of the whole pixel of the images. In the techniques of this algorithm, we made approximate contour of vehicle by allocating sampling points in cross-direction of image, and recognized top of contour of vehicle. Applying these technique, we measured the number of passing vehicles of one lane as well as multilane. Speed of each vehicle is measured by computing the time difference between a pair of sample points on two sample Points lines.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.1-10
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• 2013

In this paper, we implement the SIFT(Scale-Invariant Feature Transform) algorithm for feature point extraction using a many-core processor, and analyze the performance, area efficiency, and system area efficiency of the many-core processor. In addition, we demonstrate the potential of the proposed many-core processor by comparing the performance of the many-core processor with that of high-performance CPU and GPU(Graphics Processing Unit). Experimental results indicate that the accuracy result of the SIFT algorithm using the many-core processor was same as that of OpenCV. In addition, the many-core processor outperforms CPU and GPU in terms of execution time. Moreover, this paper proposed an optimal model of the SIFT algorithm on the many-core processor by analyzing energy efficiency and area efficiency for different octave sizes.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.3 s.309
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• pp.76-81
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• 2006

Recently, Finite field is applied the cryptography in the modern multimedia communication. Especially, block codes such as Elliptic Curve Cryptosystem and Reed-Solomon code among the error correcting codes are defined with finite field. Also, finite field algorithm is conducting the research actively because many kind of application parts need the real time operating ability therefore the exclusive hardware have been implementing. In this paper, we proposed the inverse finite field algorithm over GF($2^8$) using finite composite field and implemented in a hardware, and then compare this hardware with the currently used 'Itoh and Tsujii' hardware in respect to structure, area and computation time. Furthermore, this hardware was inserted into the AES SubBytes block and implemented on FPGA emulator board to confirm that the superiority of the proposed algorithm through the performance evaluation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.8
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• pp.16-23
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• 2010

In this paper, we propose an efficient estimation algorithm to find unknown location of an earth station for a geostationary satellite system. A cross ambiguity function (CAF), using time difference of arrival (TDOA) and frequency difference arrival (FDOA), is usually used to estimate the unknown location of an unauthorized earth station which may invoke interference to the existing satellite systems. However, a practical estimation of the location data requires tremendous computational time of CAF, and this prohibits direct utilization of CAF. For this reason, we propose a computationally efficient algorithm which utilizes characteristics of TDOA and FDOA within CAF. The proposed algorithm greatly enhances the computational efficiency without any performance degradation. In addition, we demonstrate the simulation results on the estimation performance by the resolution of the CAF estimation. The results provided in this paper will be utilized at the real system implementation.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.31-37
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• 2015

Data generated from sensors are exploding with recent development of IoT. This paradigm shift requires various industry fields that demand instant actions to analyze the arising data on a real-time basis, along with the real-time visualization analysis. As the existing visualization systems, however, perform visualization after storing data, the response time of the server cannot guarantee the ms-level processing that is close to real-time. They also have a problem of destroying data that can be major resources as they do not possess the process resources. Therefore, a smart gardening system that applies a real-time visualization algorithm using IoT sensing data under a gardening environment was designed and implement in this study. The response time of the server was measured to evaluate the performance of the suggested system. As a result, the response speed of the suggested real-time visualization algorithm was guaranteeing the ms-level processing close to real-time.

• International Journal of Automotive Technology
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• v.7 no.7
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• pp.827-832
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• 2006

Occupant classification and position detection have been significant research areas in intelligent safety systems in the automotive field. The detection and classification of seat occupancy open up new ways to control the safety system. This paper deals with a novel algorithm development, hardware implementation and testing of a prototype intelligent safety system for occupant classification and position detection for in-vehicle environment. Borland C++ program is used to develop the novel algorithm interface between the sensor and data acquisition system. MEMS strain gauge hermatic pressure sensor containing micromachined integrated circuits is installed inside the passenger seat. The analog output of the sensor is connected with a connector to a PCI-9111 DG data acquisition card for occupancy detection, classification and position detection. The algorithm greatly improves the detection of whether an occupant is present or absent, and the classification of either adult, child or non-human object is determined from weights using the sensor. A simple computation algorithm provides the determination of the occupant's appropriate position using centroidal calculation. A real time operation is achieved with the system. The experimental results demonstrate that the performance of the implemented prototype is robust for occupant classification and position detection. This research may be applied in intelligent airbag design for efficient deployment.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.3_4
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• pp.168-185
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• 2003

This paper presents a progressive algorithm that not only can narrow down the search domain in the course of face identification but also can fast reconstruct various 3D objects from a sketch drawing. The sketch drawing, edge-vertex graph without hidden line removal, which serves as input for reconstruction process, is obtained from an inaccurate freehand sketch of a 3D wireframe object. The algorithm is executed in two stages. In the face identification stage, we generate and classify potential faces into implausible, basis, and minimal faces by using geometrical and topological constraints to reduce search space. The proposed algorithm searches the space of minimal faces only to identify actual faces of an object fast. In the object reconstruction stage, we progressively calculate a 3D structure by optimizing the coordinates of vertices of an object according to the sketch order of faces. The progressive method reconstructs the most plausible 3D object quickly by applying 3D constraints that are derived from the relationship between the object and the sketch drawing in the optimization process. Furthermore, it allows the designer to change viewpoint during sketching. The progressive reconstruction algorithm is discussed, and examples from a working implementation are given.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.137-145
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• 2004

In this paper, a new algorithm for the segmentation of the multi moving objects at the 3 dimension space and the method of measuring the distance from the camera to the moving object by using stereo video monitoring system is proposed. It get the input image of left and right from the stereo video monitoring system, and the area of the multi moving objects segmented by using adaptive threshold and PRA(pixel recursive algorithm). Each of the object segmented by window mask, then each coordinate value and stereo disparity of the multi moving objects obtained from the window masks. The distance of the multi moving objects can be calculated by this disparity, the feature of the stereo vision system and the trigonometric function. From the experimental results, the error rate of a distance measurement be existed within 7.28％, therefore, in case of implementation the proposed algorithm, the stereo security system, the automatic moving robot system and the stereo remote control system will be applied practical application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2911-2916
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• 2015

The CCTV is limited by weather conditions. To overcome this limitation, we develop a monitoring program that can sense the approach or recede of two or more objects within a surveillance system that uses a continuous-wave (CW) Doppler radar, and we proposed an algorithm to efficiently detect the approach or recede information of the object. The proposed algorithm separates the signal received by the CW Doppler radar into the real and imaginary parts using Fast Fourier Transform (FFT), and sums the amplitudes for each frequency to determine whether the objects are approaching or receding, using their locations. The algorithm is verified by simulations and experiments, which confirms that it successfully detects the approach or recede of two objects.