• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.315-321
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• 2023

Long-span bridges are flexible structures with low natural frequencies and damping ratios, making them susceptible to vibrational serviceability problems. However, the current design guideline of South Korea assumes a uniform threshold of wind speed or vibrational amplitude to assess the occurrence of harmful vibrations, potentially overlooking the complex vibrational patterns observed in long-span bridges. In this study, we propose a pointwise vortex-induced vibration (VIV) detection method using a deep-learning-based signalsegmentation model. Departing from conventional supervised methods of data acquisition and manual labeling, we synthesize training data by generating sinusoidal waves with an envelope to accurately represent VIV. A Fourier synchrosqueezed transform is leveraged to extract time-frequency features, which serve as input data for training a bidirectional long short-term memory model. The effectiveness of the model trained on synthetic VIV data is demonstrated through a comparison with its counterpart trained on manually labeled real datasets from an actual cable-supported bridge.

• Journal of the Korean earth science society
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• v.26 no.6
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• pp.469-476
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• 2005

The objective of this study is to investigate the effects of a new learning method called, 'e-Learning,' by applying this method on a middle school science curriculum and study the influence it has on the students’ short and long term memory. The study was performed on two classes of sixth grade students at 'K middle school' in Yangsan. By handing out structured study assignment in e-Learning, I was able to observe how it affected the learners’ short and long term retention. The results of the study were as follows: First, classes that underwent studies using e-Learning did not show any influence on short term retention. Second, e-Learning had positive influence on long term retention. Third, learners who experienced e-Learning had positive cognition on e-Learning.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.4
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• pp.109-118
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• 2022

The data of the missing section among the vertex surface sea temperature observation data was imputed using the Bidirectional Recurrent Neural Network(BiRNN). Among artificial intelligence techniques, Recurrent Neural Networks (RNNs), which are commonly used for time series data, only estimate in the direction of time flow or in the reverse direction to the missing estimation position, so the estimation performance is poor in the long-term missing section. On the other hand, in this study, estimation performance can be improved even for long-term missing data by estimating in both directions before and after the missing section. Also, by using all available data around the observation point (sea surface temperature, temperature, wind field, atmospheric pressure, humidity), the imputation performance was further improved by estimating the imputation data from these correlations together. For performance verification, a statistical model, Multivariate Imputation by Chained Equations (MICE), a machine learning-based Random Forest model, and an RNN model using Long Short-Term Memory (LSTM) were compared. For imputation of long-term missing for 7 days, the average accuracy of the BiRNN/statistical models is 70.8%/61.2%, respectively, and the average error is 0.28 degrees/0.44 degrees, respectively, so the BiRNN model performs better than other models. By applying a temporal decay factor representing the missing pattern, it is judged that the BiRNN technique has better imputation performance than the existing method as the missing section becomes longer.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1213-1229
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• 2016

Cho and Shin (2016) recently demonstrated that an integrated HAR model has a forecast advantage over the HAR model of Corsi (2009). Recalling that realized volatilities of financial assets have asymmetries, we add a leverage term to the integrated HAR model, yielding the LIHAR model. Out-of-sample forecast comparisons show superiority of the LIHAR model over the HAR and IHAR models. The comparison was made for all the 20 realized volatilities in the Oxford-Man Realized Library focusing specially on the DJIA, the S&P 500, the Russell 2000, and the KOSPI. Analysis of the realized volatility data sets reveal apparent long-memory and asymmetry. The LIHAR model takes advantage of the long-memory and asymmetry and produces better forecasts than the HAR, IHAR, LHAR models.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.3
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• pp.37-58
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• 1997

An AI approach with tabu search is designed to solve multi-level knapsack problems. The approach performs intelligent actions with memories of historic data and learning effect. These action are developed ont only by observing the attributes of the optimal solution, the solution space, and its corresponding path to the optimal, but also by applying human intelligence, experience, and intuition with respect to the search strategies. The approach intensifies, or diversifies the search process appropriately in time and space. In order to create a good neighborhood structure, this approach uses two powerful choice rules that emphasize the impact of candidate variables on the current solution with respect to their profit contribution. "Pseudo moves", similar to "aspirations", support these choice rules during the evaluation process. For the purpose of visiting as many relevant points as possible, strategic oscillation between feasible and infeasible solutions around the boundary is applied. To avoid redundant moves, short-term (tabu-lists), intemediate-term (cycle-detection), and long-term (recording frequency and significant solutions for diversfication) memories are used. Test results show that among the 45 generated problems (these problems pose significant or insurmountable challenges to exact methods) the approach produces the optimal solutions in 39 cases.lutions in 39 cases.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.295-304
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• 2015

This paper considers the problem of estimation of the Hurst parameter H ${\in}$ (1/2, 1) from longitudinal data with the error term of a fractional Brownian motion with Hurst parameter H that gives the amount of the long memory of its increment. We provide a new estimator of Hurst parameter H using a two scale sampling method based on $A{\ddot{i}}t$-Sahalia and Jacod (2009). Asymptotic behaviors (consistent and central limit theorem) of the proposed estimator will be investigated. For the proof of a central limit theorem, we use recent results on necessary and sufficient conditions for multi-dimensional vectors of multiple stochastic integrals to converges in distribution to multivariate normal distribution studied by Nourdin et al. (2010), Nualart and Ortiz-Latorre (2008), and Peccati and Tudor (2005).

• Journal of Physiology & Pathology in Korean Medicine
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• v.21 no.6
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• pp.1543-1548
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• 2007

Recent experiments investigating the analgesic or anti-stress effects of electro-acupuncture provide extensive evidence that opioid or stress hormone system is involved in those effects, respectively. It has been also suggested that opioid or stress hormones modulate long-term memory consolidation or retrieval in animals and human subjects. This article reviews the possibilitythat electroacupuncture can modulate memory consolidation or retrieval. The release of serum cortisol is enhanced or reduced by high-frequency or low-frequency electroacupuncture, respectively. Also the release of beta endorphin and enkephalin is enhanced by low-frequency electroacupuncture and the release of dynorphin is enhanced by high-frequency electroacupunture. The memory consolidation is enhanced by post-training injection of Glucocorticoids, Naloxone or Dynorphin. So this review suggests strongly that memory consolidation can be modulated by electroacupuncture.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.12
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• pp.665-672
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• 2000

This paper described the measurement technology to analyze the partial discharge characteristics for long term aging of insulations. This system was consisted of high voltage generation and measurement part, PD detection part, digital conversion and signal processing part. We used the VXI system for digital conversion and signal processing part. In the digital conversion part, we studied the error of partial discharge magnitude and memory capacity for reading digital signal with the sampling rate. In the signal processing part, we showed the program algorithm to count pulses and read peak values of partial discharge. The allowable minimum sampling rate of digizer was decided to 250kS/s through analyzing test. We confirmed that this system was very useful in the study of $\phi-q-n$ characteristics of long term PD experiments with specimens being consisted of internal void defects and CIGRE II electrodes.

• The Korean Journal of Archival Studies
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• no.10
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• pp.27-62
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• 2004

As the penetration of information technology into everyday life is accelerated day by day, virtually all kinds of human representation of knowledge and arts are produced and distributed in the digital form. It is problematic, however, because digital objects are so volatile that it is not easy to keep them in fixed form. The fatal fragility makes it extremely tricky to preserve the digital heritage of our time for the next generation. The present paper aims to introduce current endeavors made at the international and the national levels and to provide with suggestions for Korean national strategy of digital preservation. It starts with reviewing the global trends of digital archiving and long-term preservation, focusing on standardization, preservation strategies and current experiments and projects being conducted for preserving various digital objects. It then sketches national strategies of several leading countries. Based on the sketch, twofold suggestions for Korean national strategy are proposed: establishing a central coordinating agency and accommodating the digital preservation issue in the legislative and regulatory framework for the information society. The paper concludes with the necessity of cooperation among heritage organizations, including libraries, archives, museums. They should cooperate with each other because they have traditionally been trusted with the custodianship of collective memory of humankind and the digital heritage cannot be passed onto the next generation without their endeavor. They should also work together because any single institution, or any single nation could cover what it takes to complete the task of long-term preservation of our digital heritage.

• Anxiety and mood
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• v.6 no.2
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• pp.102-108
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• 2010

Objective : Although studies have explored responses to fear had been assessed using various psychophysiological methods, results have been inconsistent. The present study examined psychophysiological responses in healthy subjects after viewing fear stimuli in a video clip for set up future fear related psychophysiological studies. Methods : We monitored three psychophysiological variables (electroencephalography, skin temperature, and heart rate variability) in adults who watched either a control stimulus movie clip or a fear-inducing movie clip. Results : In 16 healthy adults, theta activity decreased significantly after the fear stimulus as compared to the normal stimulus. However the participants showed no differences in heart rate variability or skin temperature between the fear and normal control stimulus situations. Conclusion : In the limbic area, theta activity corresponds with information processing, integration into previous memories and long-term potentiation. In this study, we suggest decreased theta activity represents amygdalo-hippocampal activity, associated with fear, short-term memory, and memory extinction in the healthy adults. Further studies are needed to evaluate the interaction of fear, memory, and the pathophysiology of anxiety disorder in patient with anxiety disorders.