• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.341-349
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• 2020

Recently, interest in ground subsidence in urban areas has increased after a large sinkhole occurred near the high-story building area in Jamsil, Seoul, Korea, in 2014. If a massive sinkhole occurs in an urban area, it is crucial to assess its risk rapidly. Access to humans for on-site safety diagnosis may be difficult because of the additional risk of collapse in the disaster area. Generally, inspection using drones equipped with high-speed lidar sensors can be utilized. However, if the sinkhole is created vertically to a depth of 100 m, similar to the sinkhole in Guatemala, the drone cannot be applied because of the wireless communication limit and turbulence inside the sinkhole. In this study, a three-dimensional (3D) scanning system was fabricated and operated using a towed cable in a massive vertical sinkhole to a depth of 200 m. A high-speed lidar sensor was used to obtain a continuous cross-sectional shape at a certain depth. An inertial-measuring unit was applied to compensate for the error owing to the rotation and pendulum movement of the measuring unit. A reconstruction algorithm, including the compensation scheme, was developed. In a vertical hole with a depth of 180 m in the mining area, the fabricated system was applied to scan 0-165 m depth. The reconstructed shape was depicted in a 3D graph.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.967-971
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• 2009

The histogram equalization algorithm is the most crucial algorithm for image enhancement. Since its direct hardware implementation always requires a divider or multiplier, its implementation cost tends to increas as the image resolution is increased or diverse image resolutions are handled. In this paper, we propose a divider-free reconstruction of histogram equalization algorithm and the corresponding hardware architecture. The logic synthesis results show that the proposed scheme can reduce the logic gate count by 84.2% compared to the conventional implementation example when the UXGA resolution is considered.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10C
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• pp.605-613
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• 2011

In most digital communication systems over the noisy channel, some form of forward error correction scheme is employed for reliable communications. If one wants to recover the transmitted message without any knowledge of the error correcting codes employed, it is of utmost importance to figure out and reconstruct the error correcting codes. In this paper, we propose two algorithms of reconstructing linear cyclic codes from the corrupted received bit sequence, one for general linear binary cyclic codes and the other for Reed-Solomon codes. For two algorithms, we ran computer simulations and the performances are shown to be superior to those with the conventional LWM method.

• Journal of Ocean Engineering and Technology
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• v.16 no.1
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• pp.8-15
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• 2002

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamic, and the basis function vector of network is constructed according to th AUV's physical properties. A sliding mode control scheme is introduced to attenuate the effect of the neural network's reconstruction errors and the disturbances in AUV's dynamics. Using Lyapunov theory, the stability of the presented control system is guaranteed as well as the uniformly boundedness of tracking errors and neural network's weights estimation errors. Finally, numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.380-387
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• 2009

In this paper, optical image encryption using integral imaging and pixel-scrambling technologies is proposed. In the encryption process, we use pixel scrambling to change the order of subsections into which the cover image is divided, and the utilize the integral imaging scheme to obtain the elemental image from the scrambled image. In order to achieve higher security, we reuse pixel scrambling to the elemental image. In the decryption process, we employ optical integral imaging reconstruction technique and inverse pixel scrambling methode. Computer simulation results prove the feasibility of the proposed method and robustness against data loss and noise.

• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.4
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• pp.263-273
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• 2011

The diffuse interface model of Saurel et al. (2008) is used for the computation of compressible cavitating flows around underwater missiles. Such systems use gas injection and natural cavitation to reduce drag effects. Consequently material interfaces appear separating liquid and gas. These interfaces may have a really complex dynamics such that only a few formulations are able to predict their evolution. Contrarily to front tracking or interface reconstruction method the interfaces are computed as diffused numerical zones, that are captured in a routinely manner, as is done usually with gas dynamics solvers for shocks and contact discontinuity. With the present approach, a single set of partial differential equations is solved everywhere, with a single numerical scheme. This leads to very efficient solvers. The algorithm derived in Saurel et al. (2009) is used to compute cavitation pockets around solid bodies. It is first validated against experiments done in cavitation tunnel at CNU. Then it is used to compute flows around high speed underwater systems (Shkval-like missile). Performance data are then computed showing method ability to predict forces acting on the system.

• Journal of the Optical Society of Korea
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• v.18 no.2
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• pp.146-150
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• 2014

We propose an experimental holographic imaging scheme combining compressive sensing (CS) theory with digital holography in phase-shifting conditions. We use the Mach-Zehnder interferometer for hologram formation, and apply the compressive sensing (CS) approach to the holography acquisition process. Through projecting the hologram pattern into a digital micro-mirror device (DMD), finally we will acquire the compressive sensing measurements using a photodiode. After receiving the data of two holograms via conventional communication channel, we reconstruct the original object using certain signal recovery algorithms of CS theory and hologram reconstruction techniques, which demonstrated the feasibility of the proposed method.

• Korean Journal of Computational Design and Engineering
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• v.12 no.4
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• pp.255-262
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• 2007

In the finite element analysis of forming process, objects are described with a finite number of elements and nodes and the approximated solutions can be obtained by the variational principle. One of the shortcomings of a finite element analysis is that the structure of mesh has become inefficient and unusable because discretization error increases as deformation proceeds due to severe distortion of elements. If the state of current mesh satisfies a certain remeshing criterion, analysis is stopped instantly and resumed with a reconstructed mesh. In the study, a new remeshing algorithm using tetrahedral elements has been developed, which is adapted to the desired mesh density. In order to reduce the discretization error, desired mesh sizes in each lesion of the workpiece are calculated using the Zinkiewicz and Zhu's a-posteriori error estimation scheme. The pre-constructed mesh is constructed based on the modified point insertion technique which is adapted to the density function. The object domain is divided into uniformly-sized sub-domains and the numbers of nodes in each sub-domain are redistributed, respectively. After finishing the redistribution process of nodes, a tetrahedral mesh is reconstructed with the redistributed nodes, which is adapted to the density map and resulting in good mesh quality. A goodness and adaptability of the constructed mesh is verified with a testing measure. The proposed remeshing technique is applied to the finite element analyses of forging processes.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.4
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• pp.436-442
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• 2016

An electroencephalogram (EEG)-connectome processor to monitor and diagnose mental health is proposed. From 19-channel EEG signals, the proposed processor determines whether the mental state is healthy or unhealthy by extracting significant features from EEG signals and classifying them. Connectome approach is adopted for the best diagnosis accuracy, and synchronization likelihood (SL) is chosen as the connectome feature. Before computing SL, reconstruction optimizer (ReOpt) block compensates some parameters, resulting in improved accuracy. During SL calculation, a sparse matrix inscription (SMI) scheme is proposed to reduce the memory size to 1/24. From the calculated SL information, a small world feature extractor (SWFE) reduces the memory size to 1/29. Finally, using SLs or small word features, radial basis function (RBF) kernel-based support vector machine (SVM) diagnoses user's mental health condition. For RBF kernels, look-up-tables (LUTs) are used to replace the floating-point operations, decreasing the required operation by 54%. Consequently, The EEG-connectome processor improves the diagnosis accuracy from 89% to 95% in Alzheimer's disease case. The proposed processor occupies $3.8mm^2$ and consumes 1.71 mW with $0.18{\mu}m$ CMOS technology.

• Smart Structures and Systems
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• v.25 no.6
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• pp.733-749
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• 2020

This study presents a computer vision-based approach for representing time evolution of structural damages leveraging a database of inspection images. Spatially incoherent but temporally sorted archival images captured by robotic cameras are exploited to represent the damage evolution over a long period of time. An access to a sequence of time-stamped inspection data recording the damage growth dynamics is premised to this end. Identification of a structural defect in the most recent inspection data set triggers an exhaustive search into the images collected during the previous inspections looking for correspondences based on spatial proximity. This is followed by a view synthesis from multiple candidate images resulting in a single reconstruction for each inspection round. Cracks on concrete surface are used as a case study to demonstrate the feasibility of this approach. Once the chronology is established, the damage severity is quantified at various levels of time scale documenting its progression through time. The proposed scheme enables the prediction of damage severity at a future point in time providing a scope for preemptive measures against imminent structural failure. On the whole, it is believed that the present study will immensely benefit the structural inspectors by introducing the time dimension into the autonomous condition assessment pipeline.