• Journal of Microbiology and Biotechnology
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• v.10 no.4
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• pp.544-546
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• 2000

Grb2 is an important adaptor protein in the mitogenic Ras signaling pathway of receptor tyrosine kinases, and contains one SH2 domain and two SH3 domains. The SH2 domain binds to specific phosphotyrosine motifs on receptors or adaptor proteins such as Shc. The SH2 domain antagonists may lead to blocking of the oncogenic Ras signals and to developing new antitumor agents. In the course of screening SH2 antagonists from natural sources, cslerotiorin (1) and isochromophilone IV (2) were isolated from a strain, Penicillium multicolor F1753, and their structures were established by NMR spectral data. The metabolites significantly inhibited the binding between the Grb2-SH2 domain and phosphopeptide derived from the Shc protein, with $IC_{50}$ values of $22{\;}\mu\textrm{M}{\;}and{\;}48{\;}\mu\textrm{M}$ for (1) and (2), respectively. The compounds are the first nonpeptidic inhibitors of the SH2 domain from a natural source.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.438-449
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• 2005

In this paper, we describes the information-theoretic approaches to sensor selection and sensor placement in sensor net­works for target localization and tracking. We have developed a sensor selection heuristic to activate the most informative candidate sensor for collaborative target localization and tracking. The fusion of the observation by the selected sensor with the prior target location distribution yields nearly the greatest reduction of the entropy of the expected posterior target location distribution. Our sensor selection heuristic is computationally less complex and thus more suitable to sensor networks with moderate computing power than the mutual information sensor selection criteria. We have also developed a method to compute the posterior target location distribution with the minimum entropy that could be achieved by the fusion of observations of the sensor network with a given deployment geometry. We have found that the covariance matrix of the posterior target location distribution with the minimum entropy is consistent with the Cramer-Rao lower bound (CRB) of the target location estimate. Using the minimum entropy of the posterior target location distribution, we have characterized the effect of the sensor placement geometry on the localization accuracy.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05b
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• pp.336-343
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• 1998

An iteration method has been developed for determining crack growth and fracture resistance cure (J-R curve) from the load versus load-line displacement record only. In this method, the hardening curve, the load versus displacement curve at a given crack length, is assumed to be a power-law function, where the exponent varies with the crack length. The exponent is determined by an iterative calculation method with the assumption that the exponent varies linearly with the load-line displacement. The proposed method was applied to the static J-R tests using compact tension(CT) specimens, a three-point bend (TPB) specimen, and a cracked round bar (CRB) specimen as well as it was applied to the quasi-dynamic J-R tests using CT specimens. The J-R curves determined by the proposed method were compared with those obtained by the conventional testing methodologies. The results showed that the J-R curves could be determined directly by the proposed iteration method with sufficient accuracy in the specimens from SA508, SA533, and SA516 pressure vessel steels and SA312 Type 347 stainless steel.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.6
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• pp.830-836
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• 2011

Most of pitch/yaw reducers consist of several planetary geartrains. Planetary geartrains make gearboxes to be small and light, low noise and good efficiency. Most important thing in the planetary geartrain is load distribution on the gear tooth flank. In this study, the effect of output shaft bearings on the load distribution of gear tooth flank has been investigated. The commercial software was employed to compare the load distribution of two models depending on the bearing type. The spherical roller bearing(SRB) and the cylindrical roller bearing(CRB) were used as output shaft bearings in the $1^{st}$ model, and two taper roller bearings(TRB) were used in the $2^{nd}$ model. As a result, it was found that the $2^{nd}$ model. showed better performances on the load distribution of gear tooth flank, this results stated that the output shaft bearing system could be important consideration when designing reducers for wind turbine systems.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.169-172
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• 2019

Frequency-modulated continuous wave(FMCW) radars with array antennas are widely used because of their light weight and relatively high resolution. A usual approach for the joint range and angle estimation of a target using an array FMCW radar is to create a range-angle matrix with the deramped received signal, and subsequently apply two-dimensional(2D) frequency estimation methods such as 2D fast Fourier transform on the range-angle matrix. However, such frequency estimation approaches cause bias errors since the frequencies in the range-angle matrix are not independent. Therefore, we propose a new maximum likelihood-based algorithm for joint range and angle estimation of targets using array FMCW radar, and demonstrate that the proposed algorithm achieves the Cram?r-Rao bounds, both for range as well as angle estimation.

• The Journal of Advanced Prosthodontics
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• v.13 no.3
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• pp.136-143
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• 2021

Purpose. This study aimed to evaluate the effect of repeated use of an implant handpiece under an implant placement torque (35 Ncm) and overloading torque condition (50 Ncm) on an output torque. Materials and Methods. Two types of implant handpiece systems (Surgicpro/X-DSG20L [NSK, Kanuma, Japan] and SIP20/CRB46LN [SAESHIN, Daegu, South Korea]) were used. The output torque was measured using a digital torque gauge. The height and angle (x, y, and z axes) of the digital torque gauge and implant handpiece were adjusted through a jig for passive connection. The experiment was conducted under the setting torque value of 35 Ncm (implant placement torque) and 50 Ncm (overloading torque condition) and 30 times per set; a total of 5 sets were performed (N = 150). For statistical analysis, the difference between the groups was analyzed using the Mann-Whitney U test and the Friedman test was used to confirm the change in output torque (α=.05). Results. NSK and SAESHIN implant handpieces showed significant differences in output torque results at the setting torques of 35 Ncm and 50 Ncm (P<.001). The type of implant handpiece and repeated use influenced the output torque (P<.001). Conclusion. There may be a difference between the setting torque and actual output torque due to repeated use, and the implant handpiece should be managed and repaired during long-term use. In addition, for successful implant results in dental clinics, the output torque of the implant handpiece system should be checked before implant placement.

• Journal of Microbiology and Biotechnology
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• v.32 no.10
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• pp.1245-1252
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• 2022

Induced pluripotent stem cells (iPSCs) can be generated from somatic cells using Oct4, Sox2, Klf4, and c-Myc (OSKM). Small molecules can enhance reprogramming. Licochalcone D (LCD), a flavonoid compound present mainly in the roots of Glycyrrhiza inflata, acts on known signaling pathways involved in transcriptional activity and signal transduction, including the PGC1-α and MAPK families. In this study, we demonstrated that LCD improved reprogramming efficiency. LCD-treated iPSCs (LCD-iPSCs) expressed pluripotency-related genes Oct4, Sox2, Nanog, and Prdm14. Moreover, LCD-iPSCs differentiated into all three germ layers in vitro and formed chimeras. The mesenchymal-to-epithelial transition (MET) is critical for somatic cell reprogramming. We found that the expression levels of mesenchymal genes (Snail2 and Twist) decreased and those of epithelial genes (DSP, Cldn3, Crb3, and Ocln) dramatically increased in OR-MEF (OG2^+/+/ROSA26^+/+) cells treated with LCD for 3 days, indicating that MET effectively occurred in LCD-treated OR-MEF cells. Thus, LCD enhanced the generation of iPSCs from somatic cells by promoting MET at the early stages of reprogramming.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.4
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• pp.33-43
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• 2013

Comparing to the constant-increasing number of vehicles, road facilities supply such as road construction has already reached the uppermost limit. As one of the most serious issues that the public would personally deal with every day, such is some road traffic problem to be solved instantly. Median exclusive bus lane is now being conducted as a way to enhance efficiency of the public transportation system in Transportation System Management, and with a main arterial that connects Kyeryong-ro (Wolpyeong 3~West Daejeon 4, 6.3km) and Daedeok-daero (Daedeok Bridge 4~Kyeryong 4, 2.6km) in Daejeon adopted as a research target, the study analyzed effects of the arterial by VISSIM the microsimulation. During the analysis, the study focused on figuring out effects of owner-drivers' transport mode choice to take a bus a public transit. According to the simulation results, as people take a bus at the median exclusive bus lane not crb bus lane, traffic for general vehicles has been negatively effected with less drive ways for the vehicles. However, when it comes to the bus traffic, the new transport mode choice appeared to have a quite positive influence after all. A binary logit model analysis reported that owner-drivers might take a bus more often when they earn lower incomes, when they do not travel far, when poor parking is expected and lastly, when they are familiar with using the median exclusive bus lane.