• Journal of Korean Neurosurgical Society
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• v.59 no.1
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• pp.17-25
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• 2016

Objective : Treatment of intracranial dural arteriovenous fistulas (dAVFs) remains a challenge. However, after introduction of Onyx, transarterial approach is the preferred treatment option in many centers. We report our experience of dAVFs embolization with special emphasis on transarterial approach. Methods : Seventeen embolization procedures were performed in 13 patients with dAVFs between Jan 2009 and Oct 2014. Clinical symptoms, location and type of fistulas, embolization methods, complications, radiological and clinical outcomes were evaluated using charts and PACS images. Results : All 13 patients had symptomatic lesions. The locations of fistulas were transverse-sigmoid sinus in 6, middle fossa dura in 4, cavernous sinus in 2, and superior sagittal sinus in 1 patient. Cognard types were as follows : I in 4, IIa in 2, IIa+IIb in 5, and IV in 2. Embolization procedures were performed ${\geq}2$ times in 3 patients. Nine patients were treated with transarterial Onyx embolization alone. One of these required direct surgical puncture of middle meningeal artery. Complete obliteration of fistulas was achieved in 11/13 (85%) patients. There were no complications except for 1 case of Onyx migration in cavernous dAVF. Modified Rankin scale score at post-operative 3 months were 0 in 11, and 3 in 2 patients. Conclusion : Transarterial Onyx embolization can be a first line therapeutic option in patients with dAVFs. However, transvenous approach should be tried first in cavernous sinus dAVF because of the risk of intracranial migration of liquid embolic materials. Furthermore, combined surgical endovascular approach can be considered as a useful option in inaccessible route.

• Current Research on Agriculture and Life Sciences
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• v.4
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• pp.50-54
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• 1986

The sorption characteristics of green tea were investigated at $20^{\circ}C$ with various relative humidities. Particle size showed little effect on the sorption behavior of green tea. At low relative humidities below 57%, the sorption equilibrium were easily attained, but a high relative humidities above 75%, the sorption equilibrium were not reached after 10 days. From the estimation of sorption rate at arbitrary humidities an empirical equation was obtained; $Ln{\frac{dw}{dt}}=nLn(t)+Lnc$ The monolayer moisture contents of green tea obtained by B.E.T. equation were found to be 7.87%(powder) and 7.01%(whole), respectively.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.55-65
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• 2015

Contrast enhancement methods for a single image applied to videos may cause flickering artifacts because these methods do not consider continuity of videos. On the other hands, methods considering the continuity of videos can reduce flickering artifacts but it may cause unnecessary fade-in/out artifacts when the intensity of videos changes abruptly. In this paper, we propose a robust method of video contrast enhancement for sudden illumination changes. The proposed method enhances each frame by Fast Gray-Level Grouping(FGLG) and considers the continuity of videos by an exponential smoothing filter. The proposed method calculates the smoothing factor of an exponential smoothing filter using a sigmoid function and applies to each frame to reduce unnecessary fade-in/out effects. In the experiment, 6 measurements are used for the performance analysis of the proposed method and traditional methods. Through the experiment. it has been shown that the proposed method demonstrates the best quantitative performance of MSSIM and Flickering score and show the adaptive enhancement under sudden illumination change through the visual quality comparison.

• Membrane and Water Treatment
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• v.9 no.2
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• pp.115-121
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• 2018

Artificial neural network (ANN) simulation is used to predict the dynamic change of permeate flux during wheat starch industry wastewater microfiltration with and without static turbulence promoter. The experimental program spans range of a sedimentation times from 2 to 4 h, for feed flow rates 50 to 150 L/h, at transmembrane pressures covering the range of $1{\times}10^5$ to $3{\times}10^5Pa$. ANN predictions of the wastewater microfiltration are compared with experimental results obtained using two different set of microfiltration experiments, with and without static turbulence promoter. The effects of the training algorithm, neural network architectures on the ANN performance are discussed. For the most of the cases considered, the ANN proved to be an adequate interpolation tool, where an excellent prediction was obtained using automated Bayesian regularization as training algorithm. The optimal ANN architecture was determined as 4-10-1 with hyperbolic tangent sigmoid transfer function transfer function for hidden and output layers. The error distributions of data revealed that experimental results are in very good agreement with computed ones with only 2% data points had absolute relative error greater than 20% for the microfiltration without static turbulence promoter whereas for the microfiltration with static turbulence promoter it was 1%. The contribution of filtration time variable to flux values provided by ANNs was determined in an important level at the range of 52-66% due to increased membrane fouling by the time. In the case of microfiltration with static turbulence promoter, relative importance of transmembrane pressure and feed flow rate increased for about 30%.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.363-363
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• 2019

활성화 함수(activation function)는 기계학습(machine learning)의 학습과정에 비선형성을 도입하여 심층적인 학습을 용이하게 하고 예측의 정확도를 높이는 중요한 요소 중 하나이다(Roy et al., 2019). 일반적으로 기계학습에서 사용되고 있는 활성화 함수의 종류에는 계단 함수(step function), 시그모이드 함수(sigmoid 함수), 쌍곡 탄젠트 함수(hyperbolic tangent function), ReLU 함수(Rectified Linear Unit function) 등이 있으며, 예측의 정확도 향상을 위하여 다양한 형태의 활성화 함수가 제시되고 있다. 본 연구에서는 기계학습을 통하여 수위예측 시 정확도 향상을 위하여 Hybrid 활성화 함수를 제안하였다. 연구대상지는 조수간만의 영향을 받는 한강을 대상으로 선정하였으며, 2009년 ~ 2018년까지 10년간의 수문자료를 활용하였다. 수위예측 알고리즘은 Python 내 Tensorflow의 RNN (Recurrent Neural Networks) 모델을 이용하였으며, 강수량, 수위, 조위, 댐 방류량, 하천 유량의 수문자료를 학습시켜 3시간 및 6시간 후의 수위를 예측하였다. 예측정확도 향상을 위하여 입력 데이터는 정규화(Normalization)를 시켰으며, 민감도 분석을 통하여 신경망모델의 은닉층 개수, 학습률의 최적 값을 도출하였다. Hybrid 활성화 함수는 쌍곡 탄젠트 함수와 ReLU 함수를 혼합한 형태로 각각의 가중치($w_1,w_2,w_1+w_2=1$)를 변경하여 정확도를 평가하였다. 그 결과 가중치의 비($w_1/w_2$)에 따라서 예측 결과의 RMSE(Roote Mean Square Error)가 최소가 되고 NSE (Nash-Sutcliffe model Efficiency coefficient)가 최대가 되는 지점과 Peak 수위의 예측정확도가 최대가 되는 지점을 확인할 수 있었다. 본 연구는 현재 Data modeling을 통한 수위예측의 정확도 향상을 위해 기초가 되는 연구이나, 향후 다양한 형태의 활성화 함수를 제안하여 정확도를 향상시킨다면 예측 결과를 통하여 침수예보에 대한 의사결정이 가능할 것으로 기대된다.

• Advances in environmental research
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• v.5 no.1
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• pp.19-35
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• 2016

The phytoextraction of some toxic heavy metals from municipal waste dump soil by castor plant (Ricinus communis) was tested under natural and single or mixed chelant-assisted scenarios in pot microcosms. A sandy loam with total metal contents (mg/kg): Cd (84.5), Cu (114.5), Ni (70.3), Pb (57.8), and Zn (117.5), was sampled from an active dumpsite in Calabar, Nigeria and used for the study. Castor (small seed variety) was grown under natural phytoextraction or single/binary chelant (citric acid, oxalic acid, and EDTA) applications (5-20 mmol/kg soil) for 63 days. Castor exhibited no visual phytotoxic symptoms with typically sigmoid growth profiles at the applied chelant doses. Growth rates, however, decelerated with increase in chelant dose. Post-harvest biomass yields were higher under chelant application than for natural phytoextraction. Both root and shoot metal concentrations (mg/kg) increased quasilinearly and significantly ($p{\leq}0.05$) with increase in chelant dose, furnishing maximum levels as: Cd (55.6 and 20.9), Cu (89.5 and 58.4), Ni (49.8 and 19.6), Pb (32.1 and 12.1), and Zn (99.5 and 46.6). Ranges of translocation factors, root and shoot bioaccumulation factors were 0.21-3.49, 0.01-0.89 and 0.01-0.51, respectively. Overall, the binary chelant treatments were less toxic for R. communis growth and enhanced metal accumulation in shoots to a greater extent than the single chelant scenarios, but more so when EDTA was present in the binary combination. This suggests that the mixed chelants could be considered as alternative treatments for enhanced phytoextraction and revegetation of degraded waste dump soils.

• Journal of the Korea Society for Simulation
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• v.26 no.3
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• pp.73-86
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• 2017

Environmental data plays an important role to enhance the reliability of experimental results in M&S(Modeling and Simulation). Especially in Military M&S, extreme weather events can be used for virtual training and simulation importantly. However, the environmental data is huge and it is dispersed among multiple organizations. It is difficult for M&S operators to select the date and area where the weather phenomenon occurs in the real environmental data and to acquire them. Environmental data retrieval technology based on Fuzzy criteria is one of the important technologies for developing Environmental Scenario Generator. As a result of this study, a fuzzy retrieval algorithm composed of four main parameters(RV, MF, FRA, and MRV) was presented. This study suggests that the RV can be used as 14 m/s for wind speed and 80 mm/d for precipitation to search the date of storm accompanied by high wind. The MF, the FRA, and MRV can be used sigmoid, 0.2, and 1 respectively. The algorithm proposed in this study is expected to be very useful for searching the date on which weather phenomena necessary for simulation occurred.

• Imaging Science in Dentistry
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• v.51 no.3
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• pp.271-278
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• 2021

Purpose: This study aimed to investigate the panoramic imaging features of cleidocranial dysplasia (CCD) with a relatively large sample. Materials and Methods: The panoramic radiographs of 40 CCD patients who visited Seoul National University Dental Hospital between 2004 and 2018 were analyzed. Imaging features were recorded based on the consensus of 2 radiologists according to the following criteria: the number of supernumerary teeth and impacted teeth; the shape of the ascending ramus, condyle, coronoid process, sigmoid notch, antegonial notch, and hard palate; the mandibular midline suture; and the gonial angle. Results: The mean number of supernumerary teeth and impacted teeth were 6.1 and 8.3, respectively, and the supernumerary teeth and impacted teeth were concentrated in the anterior and premolar regions. Ramus parallelism was dominant (32 patients, 80.0%) and 5 patients (12.5%) showed a mandibular midline suture. The majority of mandibular condyles showed a rounded shape (61.2%), and most coronoid processes were triangular (43.8%) or round (37.5%). The mean gonial angle measured on panoramic radiographs was 122.6°. Conclusion: Panoramic radiographs were valuable for identifying the features of CCD and confirming the diagnosis. The presence of numerous supernumerary teeth and impacted teeth, especially in the anterior and premolar regions, and the characteristic shapes of the ramus, condyle, and coronoid process on panoramic radiographs may help to diagnose CCD.

• Korean Journal of Environmental Agriculture
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• v.38 no.3
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• pp.133-138
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• 2019

BACKGROUND: Production function gives the equation that shows the relationship between the quantities of productive factors used and the amount of product obtained, and can answer a variety of questions. This study was carried out to evaluate the relationship between irrigation water used for rice production and rice productivity by the production function which shows the mathematical relation between input and output. METHODS AND RESULTS: The statistical data on rice production and on the amount of irrigation water were used for the production function analysis. The analysis period was separated for 1966-1981 and 1982-2011, based on goal's change on agriculture from 'increasing food' to 'complex farming'. The relation between irrigation and yield considering production function is a short-term production function both before and after 1982. These results can be expressed by the sigmoid relation. When comparing the graphs of the two analyzed periods, there are differences in quantity between the maximum point and the minimum point during the same analysis period, which can be called an 'Irrigation Effect' by the difference of irrigation, and 'Technical Effect' by the difference by inputs like as fertilizers etc. CONCLUSION: The results could be useful as information for assessing the relationship between agricultural water and the productivity of rice and predicting rice productivity by irrigation water in Korea.

• Journal of Auto-vehicle Safety Association
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• v.13 no.2
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• pp.35-41
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• 2021

In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.