• Journal of Environmental Science International
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• v.30 no.12
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• pp.1053-1065
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• 2021

In this study, the prediction technology of Hydrological Quantitative Precipitation Forecast (HQPF) was improved by optimizing the weather predictors used as input data for machine learning. Results comparison was conducted using bias and Root Mean Square Error (RMSE), which are predictive accuracy verification indicators, based on the heavy rain case on August 21, 2021. By comparing the rainfall simulated using the improved HQPF and the observed accumulated rainfall, it was revealed that all HQPFs (conventional HQPF and improved HQPF 1 and HQPF 2) showed a decrease in rainfall as the lead time increased for the entire grid region. Hence, the difference from the observed rainfall increased. In the accumulated rainfall evaluation due to the reduction of input factors, compared to the existing HQPF, improved HQPF 1 and 2 predicted a larger accumulated rainfall. Furthermore, HQPF 2 used the lowest number of input factors and simulated more accumulated rainfall than that projected by conventional HQPF and HQPF 1. By improving the performance of conventional machine learning despite using lesser variables, the preprocessing period and model execution time can be reduced, thereby contributing to model optimization. As an additional advanced method of HQPF 1 and 2 mentioned above, a simulated analysis of the Local ENsemble prediction System (LENS) ensemble member and low pressure, one of the observed meteorological factors, was analyzed. Based on the results of this study, if we select for the positively performing ensemble members based on the heavy rain characteristics of Korea or apply additional weights differently for each ensemble member, the prediction accuracy is expected to increase.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.119-126
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• 2022

With the rise and rapid development of the "Internet+" economic model, the internet is deeply integrated with the social economy and penetrates every corner of life. Compared with expanding the scale of business operations through internal investment and capital accumulation, e-commerce companies are more inclined to directly gain control of other companies through efficient merger and acquisition (M&A). The purpose of this study is to analyze changes in financial performance before and after M&A of Alibaba, China's largest e-commerce company in the Internet era. To present the impact of M&A events on Alibaba's stock price and shareholder wealth more intuitively, this study selected the market model in the event study method to measure abnormal returns. The results show that an M&A event led to a reduction in Alibaba's shareholder wealth in the short term. This study presents the theoretical basis for the M&A performance of e-commerce companies.

• Composites Research
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• v.20 no.3
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• pp.50-54
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• 2007

The Ionic Polymer Metal Composite (IPMC), an electro-active polymer, has many advantages including bending actuation, low weight, low power consumption, and flexibility. These advantages coincide with the requirements of a bio-related application. Thus, IPMC is promising materials for bio-mimetic actuator and sensor applications. Before applying IPMC to actual application, basic mechanical properties of IPMC should be studied in order to utilize IPMC for practical uses. Therefore, IPMCs are fabricated to investigate the mechanical characteristics. Nafion is used as a base ionic polymer. Mason samples cast with various thicknesses are used to test the thickness effects of IPMC. Subsequently, IPMC is fabricated using the chemical reduction method. The deformation, blocking force and frequency response of the IPMC actuator are important properties. In this present study, the performances of the IPMC actuators, including the deformation, blocking force and natural frequency, are then obtained according to only the input voltage and IPMC dimensions. Finally, the empirical performance model and the equivalent stiffness model of the IPMC actuator are established using experiments results.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.13-20
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• 2023

In this paper, we propose a water temperature prediction method using feature extraction and reconstructed data based on LSTM-Autoencoder. We used multivariate time series data such as sea surface water temperature in the Naksan area of the East Sea where the cold water zone phenomenon occurred, and wind direction and wind speed that affect water temperature. Using the LSTM-Autoencoder model, we used three types of data: feature data extracted through dimensionality reduction of the original data combined with multivariate data of the original data, reconstructed data, and original data. The three types of data were trained by the LSTM model to predict sea surface water temperature and evaluated the accuracy. As a result, the sea surface water temperature prediction accuracy using feature extraction of LSTM-Autoencoder confirmed the best performance with MAE 0.3652, RMSE 0.5604, MAPE 3.309%. The result of this study are expected to be able to prevent damage from natural disasters by improving the prediction accuracy of sea surface temperature changes rapidly such as the cold water zone.

• Korean Journal of Culture and Social Issue
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• v.12 no.1
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• pp.15-33
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• 2006

There are less studies on the adult suicide even though it's steep increase and negative effect on person itself, family and society. The purpose of the present study was to investigate factors that influence on the adult suicide and to categorize it. Using a case-study approach, a total of 61 cases were analyzed. Specifically, on the basis of the stress-vulnerability model, I scrutinized vulnerability factors(classified personal, family-environment, and social-environment factors) and precipitating events(classified personal, interpersonal events) influencing on the adult suicide. As the results of this study, adult suicide classified into 3 types, that is, 'risk type suicide', 'event-response type suicide', 'complex type'. And then I discussed the characteristics of the suicidal types and the method for reduction of adult suicide.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.27-33
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• 2024

The environment of academic research is continuously changing due to the increase of information, which raises the need for an effective way to analyze and organize large amounts of documents. In this paper, we propose Performance Improvement of Topic Modeling using BART(Bidirectional and Auto-Regressive Transformers) based Document Summarization. The proposed method uses BART-based document summary model to extract the core content and improve topic modeling performance using LDA(Latent Dirichlet Allocation) algorithm. We suggest an approach to improve the performance and efficiency of LDA topic modeling through document summarization and validate it through experiments. The experimental results show that the BART-based model for summarizing article data captures the important information of the original articles with F1-Scores of 0.5819, 0.4384, and 0.5038 in Rouge-1, Rouge-2, and Rouge-L performance evaluations, respectively. In addition, topic modeling using summarized documents performs about 8.08% better than topic modeling using full text in the performance comparison using the Perplexity metric. This contributes to the reduction of data throughput and improvement of efficiency in the topic modeling process.

• Clinical and Experimental Reproductive Medicine
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• v.51 no.2
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• pp.112-119
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• 2024

Objective: Endometriosis is a common gynecological disease among reproductive-age women. Numerous hypotheses exist regarding the pathogenesis of endometriosis. In Turkey, the consumption of Allium cepa (commonly known as the "onion cure") is a popular treatment employed to alleviate a variety of gynecological disorders. Methods: In this study, our objective was to assess the therapeutic mechanisms of the onion bulb A. cepa using an autologous endometriosis model in Sprague-Dawley rats. Previous research has shown that A. cepa possesses anti-inflammatory, antioxidant, and antiapoptotic properties. We evaluated the pathological condition of endometriotic implants by employing hematoxylin-eosin staining and Ki67 immunohistochemistry analysis. Transforming growth factor-beta 1 (TGF-β1) and alpha-smooth muscle actin (α-SMA) have been identified as profibrotic markers that are highly overexpressed in endometriotic tissues relative to eutopic endometrial tissue. Furthermore, TGF-β1 influences the differentiation and progression of endometriosis. To quantify profibrotic activity, we measured TGF-β1 and α-SMA using the immunosorbent assay method. Results: Lower histologic evaluation scores for endometriotic implants were observed in the group receiving high-dose A. cepa relative to the other groups. Ki67 expression was reduced following the high-dose A. cepa regimen, which consisted of 30% A. cepa and 70% normal feed. However, no statistically significant differences in TGF-β1 or α-SMA levels were observed among the groups (p=0.7 and p=0.778, respectively). Conclusion: The findings suggest that A. cepa could serve as a therapeutic agent in endometriosis treatment, as evidenced by the reduction in proliferative potential. Nevertheless, A. cepa was not associated with significantly lower levels of endometriosis-associated TGF-β1 or α-SMA.

• Journal of the Korean Geotechnical Society
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• v.40 no.4
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• pp.179-188
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• 2024

Nondestructive pile integrity tests are used to confirm the construction of drilled shafts as the foundation of many facilities. However, the safety of the foundation is determined only by the presence or absence of defects, and the location and scale of defects are not considered. In this study, we propose an analysis model for the lateral bearing capacity and section force connected building information modeling (BIM) by extracting the cross-sectional characteristics of the defect in piles and reviewing the safety of piles with defects. Defects at the top of piles had more effect on the change in the deflection of the pile head. Moreover, the decrease in the axial force-bending moment interaction diagram due to cross-sectional reduction increased the risk of destruction of the piles more than the change in the bending moments due to defects. The proposed method can help review the comprehensive safety of piles.

• 산업혁신연구
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• v.34 no.4
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• pp.231-254
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• 2018

The purpose of this study is to analyze and remedy the irregular rework problems in shipbuilding industry. We collected and refined the rework event log of the SAP (ERP) outsourcing company of SPP shipbuilding. The process discovery and analysis were performed by fuzzy mining, pattern analysis and bottle neck analysis among process mining methods. The reworking of SPP shipbuilding was found to cause production rework and design change rework as ship owner 's requirement, design improvement, and field work were also causes of immaturity. In addition, method of case analysis result should be carried out in order to prevent PB(ship painting)-2A(ship owner request)-P1(re-work of production) which is the most common pattern in rework process. First, in the shipbuilding industry, the reworking process model and the analysis of the cause of rework contributed to prevention and minimization of rework, productivity improvement and cost reduction. Second, the process mining methodology is analyzed and the guidelines for future research are presented. Finally, it has a significance in that it contributes to improvement of business ability by systematically showing process model, problems and causes to enterprise managers.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.33 no.1
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• pp.73-79
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• 2001

Stricter environmental demands have increased the need to replace conventional C/D bleaching sequence by chlorine-free sequence. Permanganate is well known as a powerful oxidant and have been used industrially in variable fields. However, it has considered to be difficult to use permanganate as a bleaching reagent because of its strong oxidative effect decreasing the viscosity of pulps extremely. We have tried to use permanganate as a bleaching reagent for KP under the mild condition and it was clear that pernanganate oxidized lignin remained in pulps selectively and increased pulp brightness decreasing K number of pulps with small degradation of cellulose. We have employed the neutral condition in the permanganate bleaching process in this study. In this case, permanganate was converted to manganese dioxide after bleaching reaction. The manganese dioxide is remained in the treated pulp fibers because of its insolublity in water. So it was required to reduction the manganese oxide to manganese ion by using reductants with acid. In this paper, we proposed to use oxalic acid as a reducing reagent converting manganese oxide to manganese ion after bleaching reaction. Oxalic acid plays the role as a reductant and a acid, so post-treatment after bleaching became to be easy by using oxalic acid. On the study using lignin model compounds, it was clear that permaganate react with phenols firstly, after that oxalic acid reduce the manganese oxide to manganese ion in the mixture of permanganate, phenols and oxalic acid. Several lignin model compounds ($\textit{p}$-hydroxybenzaldehyde, vanillin, syringaldehyde, veratraldehyde) are selected to elucidate the effect of substituents on reaction rate and its mechanism with permanganate including oxalic acid in this study. Except for veratraldehyde, the rate of oxidative degradation of phenolic compounds by permanganate with oxalic acid are higher than neutral condition. Especially, the degradation rate of $\textit{p}$-hydroxybenzaldehyde are strongly dependent on pH of reaction mixture. On the other hand, the degradation rate of veratraldehyde are decreased with decreasing pH and main degradation product is veratric acid. This result indicate that pH of bleaching liquor should be kept over 2 to degrade of non-phenolic lignin in the pulps effectively in permanganate bleaching.