• Journal of the Korean Chemical Society
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• v.53 no.6
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• pp.653-662
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• 2009

Developing effective tools for predicting absorption, distribution, metabolism, excretion properties and toxicity (ADME/T) of new chemical entities in the early stage of drug design is one of the most important tasks in drug discovery and development today. As one of these attempts, support vector machines (SVM) has recently been exploited for the prediction of ADME/T related properties. However, two problems in SVM modeling, i.e. feature selection and parameters setting, are still far from solved. The two problems have been shown to be crucial to the efficiency and accuracy of SVM classification. In particular, the feature selection and optimal SVM parameters setting influence each other, which indicates that they should be dealt with simultaneously. In this account, we present an integrated practical solution, in which genetic-based algorithm (GA) is used for feature selection and grid search (GS) method for parameters optimization. hERG ion-channel inhibitor classification models of ADME/T related properties has been built for assessing and testing the proposed GA-GS-SVM. We generated 6 different models that are 3 different single models and 3 different ensemble models using training set - 1891 compounds and validated with external test set - 175 compounds. We compared single model with ensemble model to solve data imbalance problems. It was able to improve accuracy of prediction to use ensemble model.

• Journal of Korea Trade
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• v.24 no.4
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• pp.1-17
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• 2020

Purpose - Since China has been South Korea's biggest export destination, uncertainty shocks originating from it would influence South Korea's exports. This paper evaluates the effects of China's economic policy uncertainty on Korea's exports to explore the transmission channels. Design/methodology - Incorporating endogeneities and nonlinearities, this study employs a quarterly time-varying parameters vector autoregressive model to investigate the relationships between China's economic policy uncertainty and Korea's exports, where the overparameterization due to time-varying specifications is overcome by a novel stochastic model specification search framework. According to previous theoretical studies, this paper assesses two channels, demand shock channel and exchange rate channel, through which foreign uncertainty affects Korea's exports. This paper identifies the primary drivers of Korea's aggregate exports and analyzes the rationales for the time-variant impacts of China's economic policy uncertainty on Korea's exports to China. Findings - Our empirical results reveal that Korea's aggregate exports are less responsive to China's economic policy uncertainty shocks and significantly move together with global demand. In contrast, its bilateral exports to China are highly responsive in a negative and time-variant way. Moreover, Chinese investment is an important channel through which China's economic policy uncertainty affects Korea's exports to China after 2010. Further, the time-variant effects of China's economic policy uncertainty on Korea's exports to China are related to changes in China's foreign trade policies, global economic conditions, and China's degree of economic freedom. Originality/value - Few previous studies touch the effects of external uncertainty shocks on South Korea's exports. This paper attempts to fill this gap and explicitly investigate the impacts of China's economic policy uncertainty on Korea's exports from a time-varying perspective. As Korea is an export-oriented economy, this study provides insights for the Korean government to understand the transmissions of external uncertainty better.

• Atmosphere
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• v.22 no.1
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• pp.1-12
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• 2012

The Atmospheric motion vectors (AMVs) derived using infrared (IR) channel imagery of geostationary satellites have been utilized widely for real-time weather analysis and data assimilation into global numerical prediction model. As the horizontal resolution of sensors on-board satellites gets higher, it becomes possible to identify atmospheric motions induced by convective clouds ($meso-{\beta}$ and $meso-{\gamma}$ scales). The National Institute of Meteorological Research (NIMR) developed the high resolution visible (HRV) AMV algorithm to detect mesoscale atmospheric motions including ageostrophic flows. To retrieve atmospheric motions smaller than $meso-{\beta}$ scale effectively, the target size is reduced and the visible channel imagery of geostationary satellite with 1 km resolution is used. For the accurate AMVs, optimal conditions are decided by investigating sensitivity of algorithm to target selection and correction method of height assignment. The results show that the optimal conditions are target size of 32 km ${\times}$ 32 km, the grid interval as same as target size, and the optimal target selection method. The HRV AMVs derived with these conditions depict more effectively tropical cyclone OMAIS than IR AMVs and the mean speed of HRV AMVs in OMAIS is slightly faster than that of IR AMVs. Optimized mesoscale AMVs are derived for 6 months (Feb. 2010-Jun. 2010) and validated with radiosonde observations, which indicates NIMR's HRV AMV algorithm can retrieve successfully mesoscale atmospheric motions.

• International Area Studies Review
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• v.15 no.3
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• pp.175-188
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• 2011

This study aims to examine how the U.S. economic shocks affect the Japanese economy. It is widely believed that the U.S. economy has a significant effect on the Japanese economy. Actually, the U.S. accounts for a considerable amount of Japan's exports and imports. To the economic policymakers, it is very important to know how economic disturbances generated by the U.S. are transmitted to the Japanese economy. A vector autoregression(VAR) model is employed to investigate the international transmission channel of economic disturbances. The interactions of the U.S.-Japansese economy are investigated by using variance decompositions(VDCs). The results of this study provided the evidence that the U.S. economic shocks were important for the Japanese economy during the sample period. This study supports the notion of economic dependence of smaller open economy such as Japan as compared with larger economy such as the U.S.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.376-381
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• 2018

The purpose of this study is to investigate price transmissions between wholesale and retail markets regarding Jeju tangerines by employing co-integration analysis and vector error correction model. The results of this study are summarized as follows: First, the long-run equilibrium relationship was found among wholesale and retail markets in time series for level by distribution channel. Second, a short-run causality relationship was observed between wholesale and retail markets. Third, the long-run causality relationship between wholesale market and retail markets was found bidirectional and feedback effect. These results imply that the wholesale price performs a central role in establishing price in the tangerine market, and the wholesale market influences tangerine price. In conclusion, for the development of a competitive tangerine industry, it is necessary to aggressively promote the policy of supply and demand control of tangerine production through organizing producers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.631-653
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• 2020

Sign language is a natural, visually oriented and non-verbal communication channel between people that facilitates communication through facial/bodily expressions, postures and a set of gestures. It is basically used for communication with people who are deaf or hard of hearing. In order to understand such communication quickly and accurately, the design of a successful sign language translation system is considered in this paper. The proposed system includes object detection and classification stages. Firstly, Single Shot Multi Box Detection (SSD) architecture is utilized for hand detection, then a deep learning structure based on the Inception v3 plus Support Vector Machine (SVM) that combines feature extraction and classification stages is proposed to constructively translate the detected hand gestures. A sign language fingerspelling dataset is used for the design of the proposed model. The obtained results and comparative analysis demonstrate the efficiency of using the proposed hybrid structure in sign language translation.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1097-1109
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• 2016

Fault detection and isolation are related to system monitoring, identifying when a fault has occurred, and determining the type of fault and its location. Fault detection is utilized to determine whether a problem has occurred within a certain channel or area of operation. Fault detection and diagnosis have become increasingly important for many technical processes in the development of safe and efficient advanced systems for supervision. This paper presents an integrated technique for fault diagnosis and classification for open- and short-circuit faults in three-phase inverter circuits. Discrete wavelet transform and principal component analysis are utilized to detect the discontinuity in currents caused by a fault. The features of fault diagnosis are then extracted. A fault dictionary is used to acquire details about transistor faults and the corresponding fault identification. Fault classification is performed with a fuzzy logic system and relevance vector machine (RVM). The proposed model is incorporated with a set of optimization techniques, namely, evolutionary particle swarm optimization (EPSO) and cuckoo search optimization (CSO), to improve fault detection. The combination of optimization techniques with classification techniques is analyzed. Experimental results confirm that the combination of CSO with RVM yields better results than the combinations of CSO with fuzzy logic system, EPSO with RVM, and EPSO with fuzzy logic system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.997-1006
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• 2019

To overcome the difficulties and inefficiencies of the existing power analysis attack, we try to extract the secret key embedded in a cryptographic device using attack model based on MLP(Multi-Layer Perceptron) method. The target of our proposed power analysis attack is the AES-128 encryption module implemented on an 8-bit processor XMEGA128. We use the divide-and-conquer method in bytes to recover the whole 16 bytes secret key. As a result, the MLP-based power analysis attack can extract the secret key with the accuracy of 89.51%. Additionally, this MLP model has the 94.51% accuracy when the pre-processing method on power traces is applied. Compared to the machine leaning-based model SVM(Support Vector Machine), we show that the MLP can be a outstanding method in power analysis attacks due to excellent ability for feature extraction.

• The KSFM Journal of Fluid Machinery
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• v.13 no.5
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• pp.43-53
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• 2010

This study investigates a design optimization of a rotating two-pass rectangular cooling channel with staggered arrays of pin-fins. The radial basis neural network method is used as an optimization technique with Reynolds-averaged Navier-Stokes analysis of fluid flow and heat transfer with shear stress transport turbulent model. The ratio of the diameter to height of the pin-fins and the ratio of the streamwise spacing between the pin-fins to height of the pin-fin are selected as design variables. The optimization problem has been defined as a minimization of the objective function, which is defined as a linear combination of heat transfer related term and friction loss related term with a weighting factor. Results are presented for streamlines, velocity vector fields, and contours of Nusselt numbers, friction coefficients, and turbulent kinetic energy. These results show how fluid flow in a two-pass square cooling channel evolves a converted secondary flows due to Coriolis force, staggered arrays of pin-fins, and a $180^{\circ}$ turn region. These results describe how the fluid flow affects surface heat transfer. The Coriolis force induces heat transfer discrepancy between leading and trailing surfaces, having higher Nusselt number on the leading surface in the second pass while having lower Nusselt number on the trailing surface. Dean vortices generated in $180^{\circ}$ turn region augment heat transfer in the turning region and in the upstream region of the second pass. As the result of optimization, in comparison with the reference geometry, thermal performance of the optimum geometry shows the improvement by 30.5%. Through the optimization, the diameter of pin-fin increased by 14.9% and the streamwise distance between pin-fins increased by 32.1%. And, the value of objective function decreased by 18.1%.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.1
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• pp.89-95
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• 2011

In this study, We modeled the deck house of the container ship like the representative bluff body and made the model ship. By using the PIV technique, the exhaust gas anti-reflux effect of the deck house backward according to open and close of the Sunken Deck and installation of the deflector in deck house side were measured in circulating water channel. The experiment system consists of hi-speed camera, laser, image board, host computer. The mean velocity vector and time mean axial velocity were found in deck house backward and the results were compared each case.