• Bulletin of the Korean Chemical Society
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• v.33 no.1
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• pp.171-176
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• 2012

A novel chemiluminescence (CL) system was established for the determination of cytosine arabinoside (Ara-C) in pharmaceutical preparations. It was showed that a clear CL signal was observed when Eosin Y mixed with Fenton reagent. The CL intensity was decreased significantly when Ara-C was added to the reaction system and partially scavenged the hydroxyl radicals in the solution. The extent of decrease in the CL intensity had a good stoichiometrical relationship with the Ara-C concentration. Based on this, we developed a new method for the determination of Ara-C using a flow injection analysis (FIA) technique with CL detection. Under the optimal conditions, the linear range of Ara-C concentration was $6.0{\times}10^{-9}\sim1.0{\times}10^{-7}mol/L$ (R = 0.9982) with a detection limit of $7.6{\times}10^{-10}mol/L$ (S/N=3), the RSD was 5.6% for $6.0{\times}10^{-8}mol/L$ Ara-C (n = 11). The method was successfully applied to the determination of Ara-C in injection samples. The possible chemiluminescence reaction mechanism was discussed.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.741-746
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• 2004

As electronic commerce progresses, the temporal association rule is developed from partitioned data sets by time to offer personalized services for customer's interest. In this paper, we proposed a temporal association rule with exponential smoothing method that is giving higher weights to recent data than past data. Through simulation and case study, we confirmed that it is more precise than existing temporal association rules but consumes running time.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.611-622
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• 2018

Observed climate data are processed under the assumption that their time series are stationary, as in multi-step temperature and precipitation prediction, which usually leads to low prediction accuracy. If a climate system model is based on a single prediction model, the prediction results contain significant uncertainty. In order to overcome this drawback, this study uses a method that integrates ensemble prediction and a stepwise regression model based on a mean-valued generation function. In addition, it utilizes empirical mode decomposition (EMD), which is a new method of handling time series. First, a non-stationary time series is decomposed into a series of intrinsic mode functions (IMFs), which are stationary and multi-scale. Then, a different prediction model is constructed for each component of the IMF using numerical ensemble prediction combined with stepwise regression analysis. Finally, the results are fit to a linear regression model, and a short-term climate prediction system is established using the Visual Studio development platform. The model is validated using temperature data from February 1957 to 2005 from 88 weather stations in Guangxi, China. The results show that compared to single-model prediction methods, the EMD and ensemble prediction model is more effective for forecasting climate change and abrupt climate shifts when using historical data for multi-step prediction.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.375-382
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• 2002

Handwritten character recognition is classified into on-line handwritten character recognition and off-line handwritten character recognition. On-line handwritten character recognition has made a remarkable outcome compared to off-line hacdwritten character recognition. This method can acquire the dynamic written information such as the writing order and the position of a stroke by means of pen-based electronic input device such as a tablet board. On the contrary, Any dynamic information can not be acquired in off-line handwritten character recognition since there are extreme overlapping between consonants and vowels, and heavily noisy images between strokes, which change the recognition performance with the result of the preprocessing. This paper proposes a method that effectively extracts the stroke including dynamic information of characters for off-line Korean handwritten character recognition. First of all, this method makes improvement and binarization of input handwritten character image as preprocessing procedure using watershed algorithm. The next procedure is extraction of skeleton by using the transformed Lu and Wang's thinning: algorithm, and segment pixel array is extracted by abstracting the feature point of the characters. Then, the vectorization is executed with a maximum permission error method. In the case that a few strokes are bound in a segment, a segment pixel array is divided with two or more segment vectors. In order to reconstruct the extracted segment vector with a complete stroke, the directional component of the vector is mortified by using right-hand writing coordinate system. With combination of segment vectors which are adjacent and can be combined, the reconstruction of complete stroke is made out which is suitable for character recognition. As experimentation, it is verified that the proposed method is suitable for handwritten Korean character recognition.

• Journal of Microbiology
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• v.44 no.2
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• pp.155-161
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• 2006

Comparative analysis of microbial communities in a sequencing batch reactor which performed enhanced biological phosphorus removal (EBPR) was carried out using a cultivation-based technique and 16S rRNA gene clone libraries. A standard PCR protocol and a modified PCR protocol with low PCR cycle was applied to the two clone libraries of the 16S rRNA gene sequences obtained from EBPR sludge, respectively, and the resulting 424 clones were analyzed using restriction fragment length polymorphisms (RFLPs) on 16S rRNA gene inserts. Comparison of two clone libraries showed that the modified PCR protocol decreased the incidence of distinct fragment patterns from about 63 % (137 of 217) in the standard PCR method to about 34 % (70 of 207) under the modified protocol, suggesting that just a low level of PCR cycling (5 cycles after 15 cycles) can significantly reduce the formation of chimeric DNA in the final PCR products. Phylogenetic analysis of 81 groups with distinct RFLP patterns that were obtained using the modified PCR method revealed that the clones were affiliated with at least 11 phyla or classes of the domain Bacteria. However, the analyses of 327 colonies, which were grouped into just 41 distinct types by RFLP analysis, showed that they could be classified into five major bacterial lineages: ${\alpha},\;{\beta},\;{\gamma}-$ Proteobacteria, Actinobacteria, and the phylum Bacteroidetes, which indicated that the microbial community yielded from the cultivation-based method was still much simpler than that yielded from the PCR-based molecular method. In this study, the discrepancy observed between the communities obtained from PCR-based and cultivation-based methods seems to result from low culturabilities of bacteria or PCR bias even though modified culture and PCR methods were used. Therefore, continuous development of PCR protocol and cultivation techniques is needed to reduce this discrepancy.

• Structural Engineering and Mechanics
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• v.88 no.1
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• pp.53-65
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• 2023

With the gradual implementation of long-span suspension bridges into high-speed railway operations, the main beam's bending stiffness contribution to the live load response permanently grows. Since another critical control parameter of railway suspension bridges is the beam-end rotation angle, it should not be ignored by treating the main beam deflection as the only deformation response. To this end, the current study refines the existing method of the main cable shape and simply supported beam bending moment analogy. The bending stiffness of the main beam is considered, and the main beam's analytical expressions of deflection and rotation angle in the whole span are obtained using the cable-beam deformation coordination relationship. Taking a railway suspension bridge as an example, the effectiveness and accuracy of the proposed analytical method are verified by the finite element method (FEM). Comparison of the results by FEM and the analytical method ignoring the main beam stiffness revealed that the bending stiffness of the main beam strongly contributed to the live load response. Under the same live load, as the main beam stiffness increases, the overall deformation of the structure decreases, and the reduction is particularly noticeable at locations with original larger deformations. When the main beam stiffness is increased to a certain extent, the stiffening effect is no longer pronounced.

• Smart Structures and Systems
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• v.10 no.3
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• pp.253-269
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• 2012

A split spectrum processing (SSP) method is proposed to accurately determine the time-of-flight (ToF) of damage-scattered waves by comparing the instantaneous amplitude variation degree (IAVD) of a wave signal captured from a damage case with that from the benchmark. The fundamental symmetrical ($S_0$) mode in aluminum plates without and with a notch is assessed. The efficiency of the proposed SSP method and Hilbert transform in determining the ToF of damage-scattered $S_0$ mode is evaluated for damage identification when the wave signals are severely contaminated by noise. Broadband noise can overwhelm damage-scattered wave signals in the time domain, and the Hilbert transform is only competent for determining the ToF of damage-scattered $S_0$ mode in a noise-free condition. However, the calibrated IAVD of the captured wave signal is minimally affected by noise, and the proposed SSP method is capable of determining the ToF of damage-scattered $S_0$ mode accurately even though the captured wave signal is severely contaminated by broadband noise, leading to the successful identification of damage (within an error on the order of the damage size) using a triangulation algorithm.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.794-803
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• 2021

The instantaneous acceleration affects the performance of the water-jet pump obviously. Here, based on the user-defined function, the method to simulate the inner flow in water-jet pumps under acceleration conditions was established. The effects of two different acceleration modes (linear acceleration and exponential acceleration) and three kinds of different acceleration time (0.5s, 1s and 2s) on the performance of the water-jet pump were analyzed. The results show that the thrust and the pressure pulsation under exponential acceleration are lower than that under linear acceleration at the same time; the vapor volume fraction in the impeller under linear acceleration is 27.3% higher than that under exponential acceleration. As the acceleration time increases, the thrust gradually increases and the pressure pulsation amplitude at the impeller inlet and outlet gradually decreases, while the law of pressure pulsation is the opposite at the diffuser outlet. The main frequency of pressure pulsation at the impeller outlet is different under different acceleration time. The research results can provide some reference for the optimal design of water-jet pumps.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.450-465
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• 2021

In this study, an attempt has been made to investigate the water-entry characteristics of the high-speed parallel projectile numerically. The shear stress transport k-𝜔 turbulence model and the Zwart-Gerber-Belamri cavitation model based on the Reynolds-Averaged Navier-Stokes method were used. The grid independent inspection and grid convergence index is carried out and verified. The influences of the parallel water-entry on flow filed characteristics, trajectory stability and drag reduction performance for different values of initial water-entry speed (𝜈₀ = 280 m/s, 340 m/s, 400 m/s) and clearance between the parallel projectiles (L_p = 0.5D, 1.0D, 2.0D, 3.0D) are presented and analyzed in detail. Under the condition of the parallel water-entry, it can be found that due to the intense interference between the parallel projectiles, the distribution of cavity is non-uniform and part of the projectile is exposed to water, resulting in the destruction of the cavity structure and the decline of trajectory stability. In addition, the parallel projectile suffers more severe lateral force that separates the two projectiles. The drag reduction performance is impacted and the velocity attenuation is accelerated as the clearance between the parallel projectiles reduces.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.665-675
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• 2022

The safety problems of giant hydraulic structures such as dams caused by terrorist attacks, earthquakes, and wars often have an important impact on a country's economy and people's livelihood. For the national defense department, timely and effective assessment of damage to or impending damage to dams and other structures is an important issue related to the safety of people's lives and property. In the field of damage assessment and vulnerability analysis, it is usually necessary to give the damage assessment results within a few minutes to determine the physical damage (crack length, crater size, etc.) and functional damage (decreased power generation capacity, dam stability descent, etc.), so that other defense and security departments can take corresponding measures to control potential other hazards. Although traditional numerical calculation methods can accurately calculate the crack length and crater size under certain combat conditions, it usually takes a long time and is not suitable for rapid damage assessment. In order to solve similar problems, this article combines simulation calculation methods with machine learning technology interdisciplinary. First, the common concrete gravity dam shape was selected as the simulation calculation object, and XFEM (Extended Finite Element Method) was used to simulate and calculate 19 cracks with different initial positions. Then, an LSTM (Long-Short Term Memory) machine learning model was established. 15 crack paths were selected as the training set and others were set for test. At last, the LSTM model was trained by the training set, and the prediction results on the crack path were compared with the test set. The results show that this method can be used to predict the crack propagation path rapidly and accurately. In general, this article explores the application of machine learning related technologies in the field of mechanics. It has broad application prospects in the fields of damage assessment and vulnerability analysis.