• Journal of Dental Anesthesia and Pain Medicine
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• 제22권1호
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• pp.39-47
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• 2022

Background: This was a randomized controlled clinical trial that aimed to evaluate the anesthetic efficacy of 2% lidocaine combined with different concentrations of epinephrine (plain, 1:200,000 and 1:80,000) during endodontic treatment of maxillary molars with symptomatic irreversible pulpitis. Methods: The trial included 144 adult patients who were randomly allocated to three treatment groups. All patients received buccal-plus-palatal infiltration. After 10 min, pulp sensibility testing was performed using an electric pulp test (EPT). If a tooth responded positively, anesthesia was considered to have failed. In the case of a negative EPT response, endodontic access was initiated under rubber dam isolation. The success of anesthesia was defined as having a pain score less than 55 on the Heft Parker visual analog scale (HP VAS), which was categorized as 'no pain' or 'faint/weak/mild' pain on the HP VAS. Baseline pre-injection and post-injection maximum heart rates were recorded. The Pearson chi-square test was used to analyze the anesthetic success rates at 5% significance. Results: Plain 2% lidocaine and 2% lidocaine with 1:200,000 epinephrine and 1:80,000 epinephrine had anesthetic success rates of 18.75%, 72.9%, and 82.3%, respectively. Statistical analysis indicated significant differences between the groups (P < 0.001, 𝛘² = 47.5, df = 2). The maximum heart rate increase was seen with 2% lidocaine solution with epinephrine. Conclusion: Adding epinephrine to 2% lidocaine significantly improves its anesthetic success rates during the root canal treatment of maxillary molars with symptomatic irreversible pulpitis.

• 한국자기공명학회논문지
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• 제25권4호
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• pp.58-63
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• 2021

Apolipoprotein B-100 (apo B-100), the main protein component that makes up LDL (Low density lipoprotein), consists of 4,536 amino acids and serves to combine with the LDL receptor. The oxidized LDL peptides by malondialdehyde (MDA) or acetylation in vivo act as immunoglobulin (Ig) antigens and peptide groups were classified into 7 peptide groups with subsequent 20 amino acids (P1-P302). The biomimetic peptide P143 (IALDD AKINF NEKLS QLQTY) out of C-group peptides carrying the highest value of IgG antigens were selected for structural studies that may provide antigen specificity. Experimental results show that P143 has β-sheet in Ile[1]-Asn[9] and α-helice in Gln[16]-Tyr[20] structure. Homonuclear 2D-NMR (COSY, TOCSY, NOESY) experiments were carried out for NMR signal assignments and structure determination for P143. On the basis of these completely assigned NMR spectra and proton distance information, distance geometry (DG) and molecular dynamic (MD) were carried out to determine the structures of P143. The proposed structure was selected by comparisons between experimental NOE spectra and back-calculated 2D NOE results from determined structure showing acceptable agreement. The total Root-Mean-Square-Deviation (RMSD) value of P143 obtained upon superposition of all atoms were in the set range. The solution state P143 has a mixed structure of pseudo α-helix and β-turn(Phe[10] to Glu[12]). These results are well consistent with calculated structure from experimental data of NOE spectra. Structural studies based on NMR may contribute to the prevent oxidation studies of atherosclerosis and observed conformational characteristics of apo B-100 in LDL using monoclonal antibodies.

• Geomechanics and Engineering
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• 제31권6호
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• 한국재료학회지
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• 제33권11호
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• pp.491-496
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• 2023

As the demand for p-type semiconductors increases, much effort is being put into developing new p-type materials. This demand has led to the development of novel new p-type semiconductors that go beyond existing p-type semiconductors. Copper iodide (CuI) has recently received much attention due to its wide band gap, excellent optical and electrical properties, and low temperature synthesis. However, there are limits to its use as a semiconductor material for thin film transistor devices due to the uncontrolled generation of copper vacancies and excessive hole doping. In this work, p-type CuI semiconductors were fabricated using the chemical vapor deposition (CVD) process for thin-film transistor (TFT) applications. The vacuum process has advantages over conventional solution processes, including conformal coating, large area uniformity, easy thickness control and so on. CuI thin films were fabricated at various deposition temperatures from 150 to 250 ℃ The surface roughness root mean square (RMS) value, which is related to carrier transport, decreases with increasing deposition temperature. Hall effect measurements showed that all fabricated CuI films had p-type behavior and that the Hall mobility decreased with increasing deposition temperature. The CuI TFTs showed no clear on/off because of the high concentration of carriers. By adopting a Zn capping layer, carrier concentrations decreased, leading to clear on and off behavior. Finally, stability tests of the PBS and NBS showed a threshold voltage shift within ±1 V.

• 스마트미디어저널
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• 제12권11호
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• pp.134-144
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• 2023

Nowadays, Deep Learning (DL) technology is being used in several government departments. South Korea imports a lot of seafood. If the demand for fishery products is not accurately predicted, then there will be a shortage of fishery products and the price of the fishery product may rise sharply. So, South Korea's Ministry of Ocean and Fisheries is attempting to accurately predict seafood imports using deep learning. This paper introduces the solution for the fish import prediction in South Korea using the Long Short-Term Memory (LSTM) method. It was found that there was a huge gap between the sum of consumption and export against the sum of production especially in the case of two species that are Hairtail and Pollock. An import prediction is suggested in this research to fill the gap with some advanced Deep Learning methods. This research focuses on import prediction using Machine Learning (ML) and Deep Learning methods to predict the import amount more precisely. For the prediction, two Deep Learning methods were chosen which are Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM). Moreover, the Machine Learning method was also selected for the comparison between the DL and ML. Root Mean Square Error (RMSE) was selected for the error measurement which shows the difference between the predicted and actual values. The results obtained were compared with the average RMSE scores and in terms of percentage. It was found that the LSTM has the lowest RMSE score which showed the prediction with higher accuracy. Meanwhile, ML's RMSE score was higher which shows lower accuracy in prediction. Moreover, Google Trend Search data was used as a new feature to find its impact on prediction outcomes. It was found that it had a positive impact on results as the RMSE values were lowered, increasing the accuracy of the prediction.

• Journal of Astronomy and Space Sciences
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• 제34권4호
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• pp.271-280
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• 2017

This study presents the application of satellite laser ranging (SLR) to orbit determination (OD) of high-Earth-orbit (HEO) satellites. Two HEO satellites are considered: the Quasi-Zenith Satellite-1 (QZS-1), a Japanese elliptical-inclinedgeosynchronous-orbit (EIGSO) satellite, and the Compass-G1, a Chinese geostationary-orbit (GEO) satellite. One week of normal point (NP) data were collected for each satellite to perform the OD based on the batch least-square process. Five SLR tracking stations successfully obtained 374 NPs for QZS-1 in eight days, whereas only two ground tracking stations could track Compass-G1, yielding 68 NPs in ten days. Two types of station bias estimation and a station data weighting strategy were utilized for the OD of QZS-1. The post-fit root-mean-square (RMS) residuals of the two week-long arcs were 11.98 cm and 10.77 cm when estimating the biases once in an arc (MBIAS). These residuals were decreased significantly to 2.40 cm and 3.60 cm by estimating the biases every pass (PBIAS). Then, the resultant OD precision was evaluated by the orbit overlap method, yielding three-dimensional errors of 55.013 m with MBIAS and 1.962 m with PBIAS for the overlap period of six days. For the OD of Compass-G1, no station weighting strategy was applied, and only MBIAS was utilized due to the lack of NPs. The post-fit RMS residuals of OD were 8.81 cm and 12.00 cm with 49 NPs and 47 NPs, respectively, and the corresponding threedimensional orbit overlap error for four days was 160.564 m. These results indicate that the amount of SLR tracking data is critical for obtaining precise OD of HEO satellites using SLR because additional parameters, such as station bias, are available for estimation with sufficient tracking data. Furthermore, the stand-alone SLR-based orbit solution is consistently attainable for HEO satellites if a target satellite is continuously trackable for a specific period.

• 한국수산과학회지
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• 제28권4호
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• pp.451-456
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• 1995

CM-chitin 분자의 고유특성을 규명하기 위하여 물성학적 방법으로 저농도 용액에서의 CM-chitin의 고유특성인 사슬배좌와 전해질 거동에 대하여 조사하였다. 비교란 상태에서 CM-chitin 사슬의 양단간 거리는 $127{\AA}$효에서 $113{\AA}$으로 분자량이 작을수록 양단간 거리는 좁혀지는 경향을 보였다 회전반경의 경우에도 $52{\AA}$에서 $46{\AA}$으로 양단간 거리와 같은 경향을 보였다. 팽창인자는 분자량에 관계없이 거의 일정하게 나타났으며, 결합사슬의 길이는 $14.5{\AA}$이었다. 그리고 교란 상태에서 CM-chitin의 Flory 점도상수는 $2.35\times10^{21}$이었다. CM-chitin의 이온강도에 따른 고유점도의 변화에 있어서 이온강도가 0.02일 때 고유점도는 1.95d1/g이었으며, 이온강도 1.0일 때는 고유점도가 1.06dl/g로 이온강도가 증가함에 따라 고유점도는 감소하는 경향을 보여 CM-chitin이 전해질임이 확인되었다. 그리고 전하를 완전히 제거한 상태에서의 CM-chitin의 고유점도$([\eta]_\infty)$는 0.91dl/g이었다. 한편 사슬의 유연성은 k-carrageenan과 거의 같은 것으로 나타났다.

• Korean Chemical Engineering Research
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• 제43권4호
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• pp.495-502
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• 2005

무전해 도금 용액을 이용하여 구리를 직접 텅스텐(Tungsten, W) 기판 위에 도금하였다. 도금 용액의 농도는 각각 $CuSO_4$ 7.615 g/L, EDTA 10.258 g/L, glyoxylic acid 7 g/L로 하였다. 도금 용액의 pH는 11.0에서 12.8까지 변화시켰으며, 용액의 온도는 $60^{\circ}C$로 유지하였다. 도금된 필름의 특성을 조사하기 위하여 X선 회절분석기, 전계 방출 주사 전자 현미경, 주사형 원자력 현미경, X선 광전자 분석기 및 Rutherford backscattering spectroscope(RBS)를 사용하였다. 구리 도금을 위한 가장 좋은 pH 조건은 11.8이였다. 이 용액에서 10분 동안 도금한 경우 둥근 모양의 구리 입자가 균일하게 도금되었으며, 불순물 peak이 없는 순수 구리 peak이였고, 근평균 제곱 표면 거칠기는 약 11 nm가 되었다. 또한, pH 11.8에서 12분 동안 도금한 필름의 두께는 140 nm이었고 도금속도는 약 12 nm/min였다. 무전해 도금 용액의 pH를 12.8로 증가시키면 도금된 구리 필름은 Cu peak 이외에 불순물 peak인 $Cu_2O$가 나타나고 구리 입자 모양도 기다란 직사각형 모양으로 변하였다. 순수 구리의 도금을 위해서는 도금 용액에서 적당한 pH를 유지하여야 한다. 도금된 구리의 농도는 RBS로 측정한 결과 99 atom％였다. 또한, Cu/W 필름은 전기 도금하는 동안 합금 형태를 이루기 때문에 접착성도 좋았다.

• 한국해안·해양공학회논문집
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• 제32권4호
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• pp.203-210
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• 2020

반무한방파제 전면 및 후면에서 회절파 진폭의 공간적인 변화에 대해 Penney and Price(1952)의 해석해를 활용하여 분석하였다. 방파제 전면에 회절파의 영향으로 입사파와 반사파를 합친 중복파의 파력보다 더 큰 파력이 발생한다. 좀 자세히 알아보면, 회절파는 방파제의 선단 (x, y) = (0, 0)을 기존으로 동심원 형태로 위상 변화가 발생하는 반면 입사파와 반사파는 평면 형태로 위상 변화가 발생한다. 따라서, 입사파(또는 반사파)와 회절파가 중첩에 의한 파의 진폭은 에너지 불연속선에서부터 떨어진 곳에서는 항상 요동치게 된다. 방파제 전면 및 후면 (x, y) = (0, y) 지점은 회절파 파봉선을 따라 에너지 불연속선 지점에서부터 y(π/2 - β) 만큼 떨어져 있다. 회절파 에너지의 감쇠의 정도는 회절파 파봉선을 따라 에너지 불연속선 지점에서 떨어진 거리에 비례한다. 따라서, 방파제 전면 및 후면(x, y) = (0, y) 지점에서의 회절파의 진폭은 y(π/2 - β)의 제곱근에 반비례한다.

• 대한조선학회지
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• 제27권3호
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• pp.38-46
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• 1990

본 보에서는 축대칭포텐시얼유동에 대한 경계적분방정식의 해법이 제시된다. 이 문제는 고리용출점과 고리보오텍스에 의해서 표시되는데 이들의 세기는 한 구간내에서 매개변수 $\zeta$의 선형함수로 근사된다. 물체의 형상은 3차 B-spline으로 표시된다. 속도가 계산되는 점이 고리용출점이나 고리보오텍스에 접근할 때의 극한표현식이 $\zeta{ln}\zeta$항까지 유도된다. 수치계산에서 양 옆구간에 의한 주치적분은 정확하게 서로 상쇄되기 때문에 특이점에 의한 유기속도중 $\(\frac{1}{\zeta}\)$에 비례하는 항은 계산에서 제외된다. 그리고 ${ln}\zeta$에 비례하는 항과 $\zeta{ln}\zeta$에 비례하는 항은 해석적으로 적분이 가능하기 때문에 수치계산에서 이에 비례하는 항을 빼고 계산한 후 해석적으로 계산한 값을 더해 준다. 기타 수치적분은 4점 Gaussian Quadrature 공식에 의해서 수행되었다. 수렴률을 정하기 위하여 구간의 개수에 따른 평균자승근오차를 조사하였으며, 이 방법의 수렴률은 2에 접근점이 밝혀졌다.