• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.37-51
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• 2023

The ground roll is the most common coherent noise in land seismic data and has an amplitude much larger than the reflection event we usually want to obtain. Therefore, ground roll suppression is a crucial step in seismic data processing. Several techniques, such as f-k filtering and curvelet transform, have been developed to suppress the ground roll. However, the existing methods still require improvements in suppression performance and efficiency. Various studies on the suppression of ground roll in seismic data have recently been conducted using deep learning methods developed for image processing. In this paper, we introduce three models (DnCNN (De-noiseCNN), pix2pix, and CycleGAN), based on convolutional neural network (CNN) or conditional generative adversarial network (cGAN), for ground roll suppression and explain them in detail through numerical examples. Common shot gathers from the same field were divided into training and test datasets to compare the algorithms. We trained the models using the training data and evaluated their performances using the test data. When training these models with field data, ground roll removed data are required; therefore, the ground roll is suppressed by f-k filtering and used as the ground-truth data. To evaluate the performance of the deep learning models and compare the training results, we utilized quantitative indicators such as the correlation coefficient and structural similarity index measure (SSIM) based on the similarity to the ground-truth data. The DnCNN model exhibited the best performance, and we confirmed that other models could also be applied to suppress the ground roll.

• Clinical and Experimental Pediatrics
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• v.45 no.12
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• pp.1559-1570
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• 2002

Purpose : There has been no exact answer to the question of when to discontinue antiepileptic drugs(AEDs) in children with well-controlled epilepsy for a long period. This study is about the risk factors of relapse after withdrawal of AEDs in seizure(Sz)-free patients to show a guideline for discontinuation of AEDs. Methods : One hundred and sixty-nine children were diagnosed as epileptic at the Pediatric Dept. of Kyung-Hee Univ. between 1993 to 1998, in whom AEDs had been withdrawn after at least two years of Sz-free period. Univariate analysis using Kaplan-Meier survival analysis and multivariate analysis using Cox-proportional hazard model were performed for sixteen risk factors. Results : Forty-nine of the 169 patients(28.9%) had recurrence of Szs. The mean follow-up after withdrawal of AEDs was 4.1 years, mean treatment period was 4.1 years, and the mean Sz-free period was 3.3 years. Factors associated with an increased risk of relapse were young age at onset, symptomatic Sz, Sz type in West and Lennox-Gastaut syndrome, neurologic deficit, longer Sz-controlling period, shorter total treatment period, number of AEDs used(more than one drug), age at withdrawal of AEDs, and Sz-free period less than two years in univariate analysis using Kaplan-Meier mothod. From multivariate analysis, the factors indicating a significantly higher relapse risk were pre-treatment period after first Sz attack, Sz-controlling period, Sz-free period, number of AEDs used, neurologic abnormalities. Conclusion : For epileptic children who were Sz-free for more than two years, and were more than six-years-old, the discontinuation of AEDs should be considered positively, according to age of onset, Sz type, age at withdrawal of AEDs, total treatment period, Sz-controlling period, number of AEDs used, etiology, neurologic deficit, and the wishes of the patients and the their parents.

• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.448-462
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• 2020

Dietary nutrition is a critical lifestyle factor that can reduce the risk of future cognitive impairments caused by dementia. Accumulating evidence suggests that dietary supplementation with Sulforaphane may help the prevention of cognitive impairments and dementia. Thus, Sulforaphane-enriched broccoli extract would hold promise to improve cognitive impairments of dementia patients. Here, we have used broccoli extracts, prepared from broccoli cultivated in Magma Seawater, to test if the broccoli extracts can be dietary supplement to improve cognitive impairments. Magma Seawater originated from Jeju Island, Korea is unique in terms of containing high concentrations of usable minerals (Zinc, Vanadium and Germanium etc.). Broccoli, grown in Magma Seawater, would contain Sulforaphane and the extra amount of usable minerals. The chemical compositions of the broccoli extracts were analyzed using LC-Q-orbitrap to detect Sulforaphane and Glucoraphanin. Analysis method based on HPLC was developed for measurement of sulforaphane levels in the broccoli extracts. We have tested if the broccoli extracts have anti-apoptotic and anti-inflammatory effects on neuron-like SH-SY5Y cells. In addition, we examined if the broccoli extracts are able to upregulate expression of synaptic plasticity-associated proteins (BDNF and phospho-CREB) and to inhibit acetylcholine esterase (AchE) activity. We have shown that the broccoli extracts inhibited the apoptotic pathway and inflammatory responses. Finally, we present evidence showing that AchE activity was inhibited by the broccoli extracts, but expression of BDNF and phospho-CREB was upregulated. Taken together, these findings suggest that the broccoli extracts from Magma Seawater-grown broccoli would be a good source of dietary nutrition to improve cognitive impairments in the future.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.

• Journal of Acupuncture Research
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• v.31 no.2
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• pp.135-144
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• 2014

Objectives : This study was designed to compare the effects of Jungsongouhyul pharmacopuncture treatment with bee venom pharmacopuncture treatment in hospitalized patients with peripheral facial paralysis. Methods : This study was done on a total of 41 patients with peripheral facial paralysis who were admitted into the Korean Medicine Hospital from February 1st, 2013 to April 30th, 2014. Wedivided patients into two groups. The Jungsongouhyul group was treated by Jungsongouhyul pharmacopuncture once a day and the bee venom group was treated by bee venom pharmacopuncture once a day. To compare the therapeutical effects of the two treatments, we used Yanagihara's unweighted grading system, House-Brachmann grading system, lip-length & snout indices and facial disablity index twice - before initial treatment and after final treatment. Results : Both Yanagihara's score and House-Brachmann grading system score improved in each group. However, there were no significant differences in improvement between the bee venom group and the Jungsongouhyul group. Conclusions : Jungsongouhyul pharmacopuncture treatment appears to be as effective as bee venom pharmacopuncture treatment to improve symptoms of peripheral facial paralysis.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.2
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• pp.88-95
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• 1996

It is inevitable for local systems to have deviations which represent interactions and modeling errors originated from the decomposition process of a large scale system. This paper presents a decentralized control scheme for interconnected systems using local linear models and a neuro-coordinator. In the proposed method, the local system is composed of a linear model and unknown deviations caused by linearizing the subsystems around operating points or by estimating parameters of the subsystems. Because the local system has unmeasurable deviations we define a local reference model which consists of a local linear model and a neural network to estimate the deviations indirectly. The reference model is reformed into a linear model which has no deviations through a transformation of input variables and we obtain an optimum feedback control law which minimizes a local performance index. Finally, we derive a decentralized feedback control law which consists of local linear states and neural network outputs. In the decentralized control, the neuro-coordinator generates a corrective control signal to cancel the effect of deviations through backpropagation learning with the errors obtained from the differences of the local system outputs and reference model outputs. Also, the stability of local system is proved by the degree of learning of the neural network under an assumption on a neural network learning index. It is shown by computer simulations that the proposed control scheme can be applied successfully to the control of a biased two-link planar robot manipulator.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.295-296
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• 2016

본 연구에서는 LED 광 자극이 뇌의 어느 영역을 자극하여 신경신호를 전달하는지에 관해서 관찰하고자 연구를 진행하였다. 광 자극에 의한 뇌 영역의 활성변화를 관찰하기 위하여 실험용 소동물과 영상장비인 9.4T MRI를 이용하여 연구를 수행 하였다. 실험용 소동물은 Balb/c 마우스를 이용하였으며 기능적 자기공명영상 획득 방법 중 하나인 에코평면영상 기법을 이용하여 뇌 영상을 획득 하였다. 획득한 영상을 바탕으로 뇌 영역의 자극 정도를 확인해보기 위해 영상처리기법인 재편성(realignment), 일치(co-registration), 표준화(normalization), 평활화(smoothing) 방법으로 영상을 전처리 하고, statistical parametric map (SPM12)을 사용하여 분석하였다. 본 연구에서는 광자극이 소동물 뇌 영역 중 하나인 상구(Superior colliculus)영역과 대뇌의 시각피질 (visual cortex, V1) 영역에서 자극을 일으키는 것을 확인할 수 있었다.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.49-54
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• 2020

The purpose of this study was to investigate the correlation between sports incidence and heart rate variability in nationa lfemale judo athletes. Participants measured heart rate variability using the Autonomic Nervous System(SA-6000). Based on the average incidence of injury, sports injury incidence was classified into upper and lower groups. In addition, Pearson's Product Moment Correlation was performed to examine the correlation between the independent T-test, the number of sports injuries, and the heart rate variability. Heart rate variability was significantly different in total power and low frequency, and there was also significant difference in otal power and low frequency in the correlation analysis of heart rate variability according to the number of sports injuries. These data are expected to be useful as basic data for developing prevention injury programs.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.981-989
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• 2011

In this paper, we performed radar target classification for the five scale models using ultra-wideband measured signal. In order to compare the performance, the 2 GHz(2~4 GHz), 4 GHz(2~6 GHz), and 6 GHz(2~8 GHz) bandwidth were used. Short time Fourier transform(STFT) and continuous wavelet transform(CWT) are used for target feature extraction. Extracted feature vectors are used as input for the multi-layerd perceptron(MLP) neural network classifier. The results show that as the bandwidth is wider, the performance is better.

• Journal of Physiology & Pathology in Korean Medicine
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• v.27 no.5
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• pp.672-676
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• 2013

The purpose of this study is to report that a patient suffered from Common Peroneal Neuropathy (CPN) caused by ankle sprain was improved by acupuncture plus electro-acupuncture. In this study, the patient was diagnosed with magnetic resonance image(MRI) and electomyography(EMG). We treated at acupoints ST36, ST41, SP9, GB34, GB39 and LR3 by acupuncture plus electro-acupuncture twice a day for 16 days; a total of 30 times. We used evaluation scale including muscle manual testing(MMT) and visual analogue scale (VAS). MMT changed from Grade 0 to Grade 5 and VAS changed from 10 to 2 after treatment for 16days with hospitalization. Though it is a case report, these results suggest that acupuncture and electrical acupuncture might have valid effect on CPN in controlled environment.