• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1800-1817
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• 2022

With the development of the economy and the improvement of living standards, the hot issues in the subject area have become the main research direction, and the mining of the hot issues in the subject currently has problems such as a large amount of data and a complex algorithm structure. Therefore, in response to this problem, this study proposes a method for extracting hot keywords in scientific journals based on the improved BERT model.It can also provide reference for researchers,and the research method improves the overall similarity measure of the ensemble,introducing compound keyword word density, combining word segmentation, word sense set distance, and density clustering to construct an improved BERT framework, establish a composite keyword heat analysis model based on I-BERT framework.Taking the 14420 articles published in 21 kinds of social science management periodicals collected by CNKI(China National Knowledge Infrastructure) in 2017-2019 as the experimental data, the superiority of the proposed method is verified by the data of word spacing, class spacing, extraction accuracy and recall of hot keywords. In the experimental process of this research, it can be found that the method proposed in this paper has a higher accuracy than other methods in extracting hot keywords, which can ensure the timeliness and accuracy of scientific journals in capturing hot topics in the discipline, and finally pass Use information technology to master popular key words.

• Journal of the Korean earth science society
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• v.43 no.4
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• pp.511-519
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• 2022

Given the significant social and economic impact caused by heat waves, there is a pressing need to predict them with high accuracy and reliability. In this study, we analyzed the real-time forecast data from six models constituting the Subseasonal-to-Seasonal (S2S) prediction project, to elucidate the key mechanisms contributing to the prediction of the recent record-breaking Korean heat wave event in 2018. Weekly anomalies were first obtained by subtracting the 2017-2020 mean values for both S2S model simulations and observations. By comparing four Korean heat-wave-related indices from S2S models to the observed data, we aimed to identify key climate processes affecting prediction accuracy. The results showed that superior performance at predicting the 2018 Korean heat wave was achieved when the model showed better prediction performance for the anomalous anticyclonic activity in the upper troposphere of Eastern Europe and the cyclonic circulation over the Western North Pacific (WNP) region compared to the observed data. Furthermore, the development of upper-tropospheric anticyclones in Eastern Europe was closely related to global warming and the occurrence of La Niña events. The anomalous cyclonic flow in the WNP region coincided with enhancements in Madden-Julian oscillation phases 4-6. Our results indicate that, for the accurate prediction of heat waves, such as the 2018 Korean heat wave, it is imperative for the S2S models to realistically reproduce the variabilities over the Eastern Europe and WNP regions.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.314-314
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• 2023

Extreme climate events can have a large impact on human life by hampering social, environmental, and economic development. Global circulation models (GCMs) are the widely used numerical models to understand the anticipated future climate change. However, different GCMs can project different future climates due to structural differences, varying initial boundary conditions and assumptions about the physical phenomena. The multi-model ensemble (MME) approach can improve the uncertainties associated with the different GCM outcomes. In this study, a comprehensive rating metric was used to select the best-performing GCMs out of 11 CMIP5 and 13 CMIP6 GCMs, according to their skills in terms of four temporal and five spatial performance indices, in replicating the 21 extreme climate indices during the baseline (1975-2017) in South Korea. The MME data were derived by averaging the simulations from all selected GCMs and three top-ranked GCMs. The random forest (RF) algorithm was also used to derive the MME data from the three top-ranked GCMs. The RF-derived MME data of the three top-ranked GCMs showed the highest performance in simulating the baseline extreme climate which was subsequently used to project the future extreme climate indices under both the representative concentration pathway (RCP) and the socioeconomic concentration pathway scenarios (SSP). The extreme cold and warming indices had declining and increasing trends, respectively, and most extreme precipitation indices had increasing trends over the period 2031-2100. Compared to all scenarios, RCP8.5 showed drastic changes in future extreme climate indices. The coasts in the east, south and west had stronger warming than the rest of the country, while mountain areas in the north experienced more extreme cold. While extreme cold climatology gradually declined from north to south, extreme warming climatology continuously grew from coastal to inland and northern mountainous regions. The results showed that the socially, environmentally and agriculturally important regions of South Korea were at increased risk of facing the detrimental impacts of extreme climatology.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.143-153
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• 2022

With the development of networks and the increase in the number of network devices, the number of cyber attacks targeting them is also increasing. Since these cyber-attacks aim to steal important information and destroy systems, it is necessary to minimize social and economic damage through early detection and rapid response. Many studies using machine learning (ML) and artificial intelligence (AI) have been conducted, among which payload learning is one of the most intuitive and effective methods to detect malicious behavior. In this study, we propose a preprocessing method to maximize the performance of the model when learning the payload in term units. The proposed method constructs a high-quality learning data set by eliminating unnecessary noise (stopwords) and preserving important features in consideration of the machine language and natural language characteristics of the packet payload. Our method consists of three steps: Preserving significant special characters, Generating a stopword list, and Class label refinement. By processing packets of various and complex structures based on these three processes, it is possible to make high-quality training data that can be helpful to build high-performance ML/AI models for security monitoring. We prove the effectiveness of the proposed method by comparing the performance of the AI model to which the proposed method is applied and not. Forthermore, by evaluating the performance of the AI model applied proposed method in the real-world Security Operating Center (SOC) environment with live network traffic, we demonstrate the applicability of the our method to the real environment.

• Information Systems Review
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• v.23 no.4
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• pp.127-146
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• 2021

Fake news isexpanded and reproduced rapidly regardless of their authenticity by the characteristics of modern society, called the information age. Assuming that 1% of all news are fake news, the amount of economic costs is reported to about 30 trillion Korean won. This shows that the fake news isvery important social and economic issue. Therefore, this study aims to develop an automated detection model to quickly and accurately verify the authenticity of the news. To this end, this study crawled the news data whose authenticity is verified, and developed fake news prediction models using word embedding (Word2Vec, Fasttext) and deep learning algorithms (LSTM, BiLSTM). Experimental results show that the prediction model using BiLSTM with Word2Vec achieved the best accuracy of 84%.

• Korean Journal of Medicinal Crop Science
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• v.24 no.5
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• pp.341-350
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• 2016

Background: Prenatal exposure to infectious and/or inflammatory insults can increase the risk of developing neuropsychiatric disorder such as bipolar disorder, autism, and schizophrenia later in life. We investigated whether Valeriana fauriei (VF) treatment alleviates prepulse inhibition (PPI) deficits and social interaction impairment induced by maternal immune activation (MIA). Methods and Results: Pregnant mice were exposed to polyriboinosinic-polyribocytidilic acid (5 mg/kg, viral infection mimic) on gestational day 9. The adolescent offspring received daily oral treatment with VF (100 mg/kg) and injections of clozapine (5 mg/kg) for 30 days starting on the postnatal day 35. The effects of VF extract treatment on behavioral activity impairment and protein expression were investigated using the PPI analysis, forced swim test (FST), open field test (OFT), social interaction test (SIT), and immunohistochemistry. The MIA-induced offspring showed deficits in the PPI, FST, OFT, and SIT compared to their non MIA-induced counterparts. Treatment with the VF extract significantly recovered the sensorimotor gating deficits and partially recovered the aggressive behavior observed in the SIT. The VF extract also reversed the downregulation of protein expression induced by MIA in the medial prefrontal cortex. Conclusions: Our results provide initial evidence of the fact that the VF extract could reverse MIA-induced behavioral impairment and prevent neurodevelopmental disorders such as schizophrenia.

• Korean Journal of Culture and Social Issue
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• v.28 no.3
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• pp.419-439
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• 2022

The purpose of this study was to examine the relationship between failure mindset of the mother and adolescent, along with the mediating effects of mother's happiness and mother-adolescents (first and second-year middle school students in Seoul) open communication. For this study, self-reported data of 270 mother-adolescent dyads were analyzed using SPSS and Process macro Model 6. The results revealed that the mother's failure mindset directly predicted their adolescent's failure mindset. The mediating effect of the mother-adolescent open communication was significant, but the mediating effect of the mother's happiness was not significant. However, the mediation effect of the mother's failure mindset on the adolescent's failure mindset through mother's happiness and mother-adolescent open communication was significant. These results suggest that "failure-is-enhancing" mindset of mothers improve their positive affect and parenting skills, which contributes to developing adolescent's belief system about failure. Putting the results together, this study is significant in that it identified the intergenerational relationship of the failure mindset. Besides, the study results serve as a foundation for intervening on the adolescent's failure mindset by verifying the developmental mechanism of the failure mindset.

• Proceedings of the Korea Association of Information Systems Conference
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• 2003.05a
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• pp.55-73
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• 2003

As the development of wireless technologies continue, mobile stock trading has become a new channel for companies to reach their customers. This study examines the factors affecting customer acceptance of mobile stock trading services. The research model based on the previous studies was established and the research hypotheses were generated. The sample was divided into users and nonuser groups. The test results show that relative advantage and social influence are positively related to intention to accept mobile services as well as in intention to reuse, security risk is negatively related to intention to reuse, frequency of trading is positively related to intention to reuse, cost burden is negatively related to the probability of using mobile stock trading services, and social influence is positively related to the probability of using mobile services. The results also support that information quality and response time are positively related to relative advantage, and interface quality is negatively related to complexity. It is considered that the study results may help managers to increase customer use of mobile stock trading services.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.83-88
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• 2011

Rapid transition to aging society faces many problems. Also there are so many issues related people with disabilities. Disabled and elderly population growth is causing serious social problems. The purpose of this study is to solve the graying society-problem and improve old people's quality of life as well as the disabled's. The main goal of this study is the design of the master plan for ubiquitous-city by referring the 'Ubiquitous urban planning guidelines' of MLTM(Ministry of Land, Transport and Maritime Affairs). For research and development, there is divided by a spatial scope and content scope. As reference model-type, the spatial scope is to pursue maximum function by using minimum system organization and virtual city-set. The content scope consists of services for the disabled and aged, information management, construction management, compatible & connection and Executive Management. The result of this study will contribute to solve the social problems with aged and disabled and advance ubiquitous-environment by improving people's quality of life.

• The Journal of Korean Association of Computer Education
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• v.9 no.1
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• pp.19-28
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• 2006

In this paper, we have developed electronic textbooks for social studies centering on contents of a public educational process so that primary schools can use them as a text book. Also, we conducted a survey to find out how teachers perceived electronic textbooks in respect to site accessibility and utility, instructional design, progress of lesson, validity and accuracy of learning content, interface design, and web-based multimedia. In this paper, we presented a new model for electronic textbooks development, which is expected to be useful in developing electronic textbooks as a main text book, unlike other existing models. We applied the navigation utilizing book metaphors to the user interface, on the basis of the results from the analysis of the existing electronic textbooks. In addition, we provided affluent multi-media materials as well as hyperlink, a strong point of on-lines. Experimental results show that the academic achievement was high in knowledge-understanding areas and functional areas in the perspective of academic achievements of the learners.