• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.397-400
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• 1999

As the result of enhancement of CAD, Design Automation and manufacturing technology, it's on the increasing complexity, integration ratio, data signals, and pin count to IC chips. This brings about difficulties of testing, and incresing test time. Now One of the most cost-consuming procedure as integration ratio increases is the testing step. In this paper, we propose a new method, “Efficient TP(test point) assignment algorithm” using “input grouping”, This is helpful method to reducing test length without losing fault coverage. Experimental results show that proposed method reduces test length remarkably and doesn't miss fault coverage, with low hardware overhead Increasing.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.460-470
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• 2004

A computational analysis of engineering problems with moving domain or/and boundary according to either Lagrangian or Eulerian approach may encounter inherent numerical difficulties, the extreme mesh distortion in the former and the material boundary indistinctness in the latter. In order to overcome such defects in classical numerical approaches, the ALE(arbitrary Lagrangian Eulerian) method is widely being adopted in which the finite element mesh moves with arbitrary velocity. This paper is concerned with the ALE finite element formulation, aiming at the dynamic response analysis of baffled fuel-storage container in yawing motion, for which the coupled time integration scheme, the remeshing and smoothing algorithm and the mesh velocity determination are addressed. Numerical simulation illustrating theoretical works is also presented.

• Structural Engineering and Mechanics
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• v.73 no.1
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• pp.65-73
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• 2020

The present work describes a new time marching procedure for structural dynamics analyses. In this novel technique, time integration parameters are automatically evaluated according to the properties of the model. Such parameters are locally defined, allowing the user to input a numerical dissipation property for each element, which defines the amount of numerical dissipation to be introduced. Since the integration parameters are locally defined as a function of the structural element itself, the time marching technique adapts according to the model, providing enhanced accuracy. The new methodology is based on displacement-velocity relations and no computation of accelerations is required. Furthermore, the method is second order accurate, it has guaranteed stability, it is truly self-starting and it allows highly controllable algorithm dissipation in the higher modes. Numerical results are presented and compared to those provided by the Newmark and the Bathe methods, illustrating the good performance of the new time marching procedure.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3327-3334
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• 2021

Present electric grids are advanced to integrate smart grids, distributed resources, high-speed sensing and control, and other advanced metering technologies. Cybersecurity is one of the challenges of the smart grid and nuclear plant digital system. It affects the advanced metering infrastructure (AMI), for grid data communication and controls the information in real-time. The research article is emphasized solving the nuclear and smart grid hardware security issues with the integration of field programmable gate array (FPGA), and implementing the latest Time Authenticated Cryptographic Identity Transmission (TACIT) cryptographic algorithm in the chip. The cryptographic-based encryption and decryption approach can be used for a smart grid distribution system embedding with FPGA hardware. The chip design is carried in Xilinx ISE 14.7 and synthesized on Virtex-5 FPGA hardware. The state of the art of work is that the algorithm is implemented on FPGA hardware that provides the scalable design with different key sizes, and its integration enhances the grid hardware security and switching. It has been reported by similar state-of-the-art approaches, that the algorithm was limited in software, not implemented in a hardware chip. The main finding of the research work is that the design predicts the utilization of hardware parameters such as slices, LUTs, flip-flops, memory, input/output blocks, and timing information for Virtex-5 FPGA synthesis before the chip fabrication. The information is extracted for 8-bit to 128-bit key and grid data with initial parameters. TACIT security chip supports 400 MHz frequency for 128-bit key. The research work is an effort to provide the solution for the industries working towards embedded hardware security for the smart grid, power plants, and nuclear applications.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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• pp.186-196
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• 1999

The CPS provides data with long-term stability independent of passed time and the INS provides high-rate data with short-term stability. By integrating these complementary systems, a highly accurate navigation system can be achieved. In this paper, a loosely-coupled GPS/INS integration system is designed. It is a simple structure and is easy to implement and preserves independent navigation capability of GPS and INS. The integration system consists of a NCU, an IMU, a GPS receiver, and a monitoring system. The navigation algorithm in the NCU is designed under the multi-tasking environment based on a real-time kernel system and the monitoring system is designed using the Visual C++. The integrated Kalman filter is designed as a feedback formed 15-state filter, in which the states are position errors, velocity errors, attitude errors and sensor bias errors. The van test result shows that the integrated system provides more accurate navigation solution then the inertial or the GPS-alone navigation system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.37-45
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• 2015

In modern electronic warfare systems, a demand on the more accurate estimation method based on TDOA and FDOA has been increased. TDOA/FDOA localization consists of two-stage procedures: the extraction of information from signals and the estimation of emitter location. Various algorithms based on CAF(complex ambiguity function), which is known as a basic method, has been presented in the area of extractions. When we extract TDOA and FDOA information using a conventional method based on the CAF algorithm from communication signals, considerably long integration time is required for the accurate position estimation of an unknown emitter far from sensors more than 300 km. Such long integration time yields huge amount of transmission data from sensors to a central processing unit, resulting in heavy computiational complexity. Therefore, we theoretically analyze the integration time for TDOA/FDOA information using CRLB and propose a two-stage global optimization algorithm which can minimize the transmission time and a computational complexity. The proposed method is compared with the conventional CAF-based algorithms in terms of a computational complexity and the CRLB to verify the estimation performance.

• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.1
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• pp.72-79
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• 2011

Typical results obtained by a newly developed, nonlinear time domain hybrid method for simulating large amplitude motions of ships advancing with constant forward speed in waves are presented. The method is hybrid in the way of combining a time-domain transient Green function method and a Rankine source method. The present approach employs a simple double integration algorithm with respect to time to simulate the free-surface boundary condition. During the simulation, the diffraction and radiation forces are computed by pressure integration over the mean wetted surface, whereas the incident wave and hydrostatic restoring forces/moments are calculated on the instantaneously wetted surface of the hull. Typical numerical results of application of the method to the seakeeping performance of a standard containership, namely the ITTC S175, are herein presented. Comparisons have been made between the results from the present method, the frequency domain 3D panel method (NEWDRIFT) of NTUA-SDL and available experimental data and good agreement has been observed for all studied cases between the results of the present method and comparable other data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.559-568
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• 2016

For the economic management of photovoltaic power plants, it is necessary to regularly monitor the panels within the plants to detect malfunctions. Thermal infrared image cameras are generally used for monitoring, since malfunctioning panels emit higher temperatures compared to those that are functioning. Recently, technologies that observe photovoltaic arrays by mounting thermal infrared cameras on UAVs (Unmanned Aerial Vehicle) are being developed for the efficient monitoring of large-scale photovoltaic power plants. However, the technologies developed until now have had the shortcomings of having to analyze the images manually to detect malfunctioning panels, which is time-consuming. In this paper, we propose an automatic photovoltaic panel area extraction algorithm for thermal infrared images acquired via a UAV. In the thermal infrared images, panel boundaries are presented as obvious linear features, and the panels are regularly arranged. Therefore, we exaggerate the linear features with a vertical and horizontal filtering algorithm, and apply a modified hierarchical histogram clustering method to extract candidates of panel boundaries. Among the candidates, initial panel areas are extracted by exclusion editing with the results of the photovoltaic array area detection. In this step, thresholding and image morphological algorithms are applied. Finally, panel areas are refined with the geometry of the surrounding panels. The accuracy of the results is evaluated quantitatively by manually digitized data, and a mean completeness of 95.0%, a mean correctness of 96.9%, and mean quality of 92.1 percent are obtained with the proposed algorithm.

• Journal of Biosystems Engineering
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• v.36 no.2
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• pp.116-121
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• 2011

This study was conducted to develop a robust navigator which could be in positioning for precision farming through developing a plural GPS receiver with 4 sets of GPS antenna. In order to improve positioning accuracy by integrating GPS signals received simultaneously, the algorithm for processing plural GPS signal effectively was designed. Performance of the algorithm was tested using a simulation program and a fixed point on WGS 84 coordinates. Results of this study are aummarized as followings. 1. 4 sets of lower grade GPS receiver and signals were integrated by kalman filter algorithm and geometric algorithm to increase positioning accuracy of the data. 2. Prototype was composed of 4 sets of GPS receiver and INS components. All Star which manufactured by CMC, gyro compass made by KVH, ground speed sensor and integration S/W based on RTOS(Real Time Operating System)were used. 3. Integration algorithm was simulated by developed program which could generate random position error less then 10 m and tested with the prototype at a fixed position. 4. When navigation data was integrated by geometrical correction and kalman filter algorithm, estimated positioning erros were less then 0.6 m and 1.0 m respectively in simulation and fixed position tests.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1415-1429
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• 2019

Nowadays object tracking process becoming one of the most challenging task in Computer Vision filed. A CSR-DCF (channel spatial reliability-discriminative correlation filter) tracking algorithm have been proposed on recent tracking benchmark that could achieve stat-of-the-art performance where channel spatial reliability concepts to DCF tracking and provide a novel learning algorithm for its efficient and seamless integration in the filter update and the tracking process with only two simple standard features, HoGs and Color names. However, there are some cases where this method cannot track properly, like overlapping, occlusions, motion blur, changing appearance, environmental variations and so on. To overcome that kind of complications a new modified version of CSR-DCF algorithm has been proposed by integrating deep learning based object detection and CSRT tracker which implemented in OpenCV library. As an object detection model, according to the comparable result of object detection methods and by reason of high efficiency and celerity of Faster RCNN (Region-based Convolutional Neural Network) has been used, and combined with CSRT tracker, which demonstrated outstanding real-time detection and tracking performance. The results indicate that the trained object detection model integration with tracking algorithm gives better outcomes rather than using tracking algorithm or filter itself.