• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.12
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• pp.83-90
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• 2004

This paper proposes an efficient scan testing method for compression of test input data and reduction of test power for SOC. The proposed method determines whether some parts of a test response can be reused as a part of next input test data on the analysis of deterministic test data and its response. Our experimental results show that benchmark circuits have a high similarity between un-compacted deterministic input test data and its response. The proposed testing method achieves the average of 29.4% reduction of power dissipation based on the number of test clock and 69.7% reduction of test data for ISCAS'89 benchmark circuits.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.169-176
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• 1994

This paper describes an efficient parallel evaluation algorithm for accelerating fault simulation, which can be applied to combinational circuits. The method is based on a combination of all the advantages in parallel, deductive and concurrent schemes in terms of evaluation and propagation of fautly gates for achieving high performance and handling multi-valued signal. We also propose a new fault grouping procedure to increase parallel operation of fault bits by packing active faults which occur in the same signal line densely into the same fault group. The algorithm has been implemented in C language on a Sun 3/260, and experimental results for ISCAS'85 benchmark circuits have been shown that this algorithm is 2.6 to 8.2 times faster than the conventional cocurrent fault simulation algorithm.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.559-566
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• 2005

ALTIBASE is the relational main memory DBMS that enables us to develop the high performance and fault tolerant applications. It guarantees the short and predictable execution time as well as the basic functionality of conventional disk-based DBMS. We present the overview of system architecture and the performance analysis with respect to the various design choices. The assorted experiments are performed under the various environments. The results of TPC-H and Wisconsin benchmark tests are described. We illustrate the various performance comparisons under the various index mechanisms, the replication models, the transaction durabilities, and the application structures. A performance study shows the ALTIBASE system can be applied to the wide area of industrial DBMS fields.

• Smart Structures and Systems
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• v.5 no.1
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• pp.95-117
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• 2009

In this paper, the time series based damage detection algorithms developed by Nair, et al. (2006) and Nair and Kiremidjian (2007) are applied to the benchmark experimental data from the National Center for Research on Earthquake Engineering (NCREE) in Taipei, Taiwan. Both acceleration and strain data are analyzed. The data are modeled as autoregressive (AR) processes, and damage sensitive features (DSF) and feature vectors are defined in terms of the first three AR coefficients. In the first algorithm developed by Nair, et al. (2006), hypothesis tests using the t-statistic are applied to evaluate the damaged state. A damage measure (DM) is defined to measure the damage extent. The results show that the DSF's from the acceleration data can detect damage while the DSF from the strain data can be used to localize the damage. The DM can be used for damage quantification. In the second algorithm developed by Nair and Kiremidjian (2007) a Gaussian Mixture Model (GMM) is used to model the feature vector, and the Mahalanobis distance is defined to measure damage extent. Additional distance measures are defined and applied in this paper to quantify damage. The results show that damage measures can be used to detect, quantify, and localize the damage for the high intensity and the bidirectional loading cases.

• Geomechanics and Engineering
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• v.11 no.6
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• pp.805-820
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• 2016

A fully coupled non-linear effective stress response finite difference (FD) model is built to survey the counter-intuitive recent findings on the reliance of pore water pressure ratio on foundation contact pressure. Two alternative design scenarios for a benchmark problem are explored and contrasted in the light of construction emission rates using the EFFC-DFI methodology. A strain-hardening effective stress plasticity model is adopted to simulate the dynamic loading. A combination of input motions, contact pressure, initial vertical total pressure and distance to foundation centreline are employed, as model variables, to further investigate the control of permanent and variable actions on the residual pore pressure ratio. The model is verified against the Ghosh and Madabhushi high acceleration field test database. The outputs of this work are aimed to improve the current computer-aided seismic foundation design that relies on ground's packing state and consistency. The results confirm that on seismic excitation of shallow foundations, the likelihood of effective stress loss is greater in deeper depths and across free field. For the benchmark problem, adopting a shallow foundation system instead of piled foundation benefitted in a 75% less emission rate, a marked proportion of which is owed to reduced materials and haulage carbon cost.

• Smart Structures and Systems
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• v.30 no.6
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• pp.557-569
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• 2022

Vibration-based structural health monitoring (SHM) is crucial for the dynamic maintenance of civil building structures to protect property security and the lives of the public. Analyzing these vibrations with modern artificial intelligence and deep learning (DL) methods is a new trend. This paper proposed an unsupervised deep learning method based on a convolutional autoencoder (CAE), which can overcome the limitations of conventional supervised deep learning. With the convolutional core applied to the DL network, the method can extract features self-adaptively and efficiently. The effectiveness of the method in detecting damage is then tested using a benchmark model. Thereafter, this method is used to detect damage and instant disaster events in a rubber bearing-isolated gymnasium structure. The results indicate that the method enables the CAE network to learn the intact vibrations, so as to distinguish between different damage states of the benchmark model, and the outcome meets the high-dimensional data distribution characteristics visualized by the t-SNE method. Besides, the CAE-based network trained with daily vibrations of the isolating layer in the gymnasium can precisely recover newly collected vibration and detect the occurrence of the ground motion. The proposed method is effective at identifying nonlinear variations in the dynamic responses and has the potential to be used for structural condition assessment and safety warning.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.756-768
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• 2023

Neutron transport calculations are extremely challenging due to the high computational cost of large and complex problems. A multilevel octree grid algorithm (MLTG) of discrete ordinates method was developed to improve the modeling accuracy and simulation efficiency on 3-D Cartesian grids. The Balakovo-3 VVER-1000 neutron dosimetry benchmark is calculated to verify and validate this numerical technique. A simplified S₂ synthetic acceleration is used in the MLTG calculation method to improve the convergence of the source iterations. For the triangularly arranged fuel pins, we adopt a source projection algorithm to generate pin-by-pin source distributions of hexagonal assemblies. MLTG provides accurate geometric modeling and flexible fixed source description at a lower cost than traditional Cartesian grids. The total number of meshes is reduced to 1.9 million from the initial 9.5 million for the Balakovo-3 model. The numerical comparisons show that the MLTG results are in satisfactory agreement with the conventional S_N method and experimental data, within the root-mean-square errors of about 4% and 10%, respectively. Compared to uniform fine meshing, approximately 70% of the computational cost can be saved using the MLTG algorithm for the Balakovo-3 computational model.

• Smart Structures and Systems
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• v.31 no.5
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• pp.437-454
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• 2023

Real-time hybrid simulation (RTHS), which has the advantages of a substructure pseudo-dynamic test, is widely used to investigate the rate-dependent mechanical response of structures under earthquake excitation. However, time delay in RTHS can cause inaccurate results and experimental instabilities. Thus, this study proposes a model-based adaptive control strategy using a Kalman filter (KF) to minimize the time delay and improve RTHS stability and accuracy. In this method, the adaptive control strategy consists of three parts-a feedforward controller based on the discrete inverse model of a servohydraulic actuator and physical specimen, a parameter estimator using the KF, and a feedback controller. The KF with the feedforward controller can significantly reduce the variable time delay due to its fast convergence and high sensitivity to the error between the desired displacement and the measured one. The feedback control can remedy the residual time delay and minimize the method's dependence on the inverse model, thereby improving the robustness of the proposed control method. The tracking performance and parametric studies are conducted using the benchmark problem in RTHS. The results reveal that better tracking performance can be obtained, and the KF's initial settings have limited influence on the proposed strategy. Virtual RTHSs are conducted with linear and nonlinear physical substructures, respectively, and the results indicate brilliant tracking performance and superb robustness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.33-38
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• 1999

This paper proposes a translation approach for PLCs (Programmable logic controllers) converting ladder diagrams directly to native codes, and describes detailed steps of the method followed by performance evaluation. A general-purpose DSP (Digital signal processor) based implementation validates the approach as well. A benchmark test shows that the Proposed translation framework fairly speeds up execution in comparison with the existing interpretation approach.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.55-58
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• 2000

To achieve high performance by exploiting instruction level parallelism(ILP) aggressively in superscalar processors, value prediction is used. Value prediction is a technique that breaks data dependences by predicting the outcome of an instruction and executes speculatively it's data dependent instruction based on the predicted outcome. In this paper, the performance of a hybrid value prediction scheme with dynamic classification mechanism is measured and analyzed by using execution-driven simulator for SPECint95 benchmark set.