• Korean Journal of Culture and Social Issue
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• v.28 no.3
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• pp.393-417
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• 2022

The current study analyzes the usage of social network services(SNS) according to one's collectivistic and individualistic tendency and the relationship with addiction. Additionally, the study attempted to controll intrapersonal variables such as gender, personalitly, and age, which affect SNS the usage. Also, Collectivistic-individualistic tendency in SNS and offline environment may not correspond to one another. Therefore, the study measured the collectivistic-individualistic tendency regarding of the two environment separately. For this purpose, we designed a new measurement scale to measure collectivistic-individualistic tendencies in for the SNS by involving a kin vs nonkin context. The sample consisted of 253 adolescents ranging from 13 to 15 years old and 246 adults ranging from 18 to 25 years old, which sums up to 499 samples in total. Results indicated that individualistic tendency within SNS showed a positive relationship with the amount of SNS usage and SNS addiction. Furthermore, female users spent more time on SNS and showed a higher level addiction than males. While adults had longer experience with SNS and spent more time on it daily than adolescents, they did not show a significant difference in regards to SNS addiction. The correlation analysis indicated that collectivistic-individualistic tendencies in SNS were weakly correlated to that of offline environments. The kin individualistic tendency in SNS significantly predicted SNS addiction after controlling for the effect of age, personality, gender, and offline collectivistic-individualistic tendency. Taken together, these findings indicate the need for an appropriate collectivistic-individualist tendency scale that correspond to the SNS context. The results also suggest that kin individualistic tendency in the SNS environment can be the main factor for SNS addiction.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.95-118
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• 2021

As the AI speaker business has risen significantly in recent years, the potential for numerous uses of AI speakers has gotten a lot of attention. Consumers have created an environment in which they can express and share their experiences with products through various channels, resulting in a large number of reviews that leave consumers with a variety of candid opinions about their experiences, which can be said to be very useful in analyzing consumers' thoughts. Using this review data, this study aimed to examine the factors driving the continued use of AI speakers. Above all, it was determined whether the seven characteristics associated with the intention to adopt AI identified in prior studies appear in consumer reviews. Based on customer review data on Amazon.com, text mining and social network analysis were utilized to examine Amazon eco-products. CONCOR analysis was used to classify words with similar connectivity locations, and Connection centrality analysis was used to classify the factors influencing the continuous use of AI speakers, focusing on the connectivity between words derived by classifying review data into positive and negative reviews. Consumers regarded personality and closeness as the most essential characteristics impacting the continued usage of AI speakers as a result of the favorable review survey. These two parameters had a strong correlation with other variables, and connectedness, in addition to the components established from prior studies, was a significant factor. Furthermore, additional negative review research revealed that recognition failures and compatibility are important problems that deter consumers from utilizing AI speakers. This study will give specific solutions for consumers to continue to utilize Amazon eco products based on the findings of the research.

• Journal of Korean Society of Disaster and Security
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• v.15 no.3
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• pp.101-113
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• 2022

This study is planned with the aim of developing a systematic construction process based on the scientific and engineering theory of the water-sealing grouting construction applied to the tunnel excavation process during the construction of the downtown underground traffic network, so that the construction quality of the relatively backward domestic tunnel water-sealing grouting construction is improved and continuously maintained no matter who constructs it. The main contents of the improved tunnel water-sealing grouting can be largely examined in the classification of tunnel water-sealing grouting application and the definition of grouting materials, the correlation analysis of groundwater pressure conditions with groundwater inflow, the study of the characteristic factors of bedrock, and the element technologies and injection management techniques required for grouting construction. Looking at the trends in global research, research in the field of theoretical-based science and engineering grouting is actively progressing in Nordic countries (Sweden, Finland, Norway, etc.), Japan, Germany, and the United States. Therefore, in this study, the algorithm is established through theoretical analysis of the elements of tunnel water-sealing grouting construction techniques to provide an integrated solution including a construction process that can effectively construct tunnel water-sealing grouting construction.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.187-192
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• 2023

In this study, trends in ICT education were investigated by analyzing the frequency of appearance of keywords related to machine learning and using conversion of iteration correction(CONCOR) techniques. A total of 304 papers from 2018 to the present published in registered sites were searched on Google Scalar using "ICT education" as the keyword, and 60 papers pertaining to ICT education were selected based on a systematic literature review. Subsequently, keywords were extracted based on the title and summary of the paper. For word frequency and indicator data, 49 keywords with high appearance frequency were extracted by analyzing frequency, via the term frequency-inverse document frequency technique in natural language processing, and words with simultaneous appearance frequency. The relationship degree was verified by analyzing the connection structure and centrality of the connection degree between words, and a cluster composed of words with similarity was derived via CONCOR analysis. First, "education," "research," "result," "utilization," and "analysis" were analyzed as main keywords. Second, by analyzing an N-GRAM network graph with "education" as the keyword, "curriculum" and "utilization" were shown to exhibit the highest correlation level. Third, by conducting a cluster analysis with "education" as the keyword, five groups were formed: "curriculum," "programming," "student," "improvement," and "information." These results indicate that practical research necessary for ICT education can be conducted by analyzing ICT education trends and identifying trends.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.198-210
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• 2022

The southern strait of Jeju is a divergence point of the Tsushima Warm Current (TWC), and it is the starting point of the thermohaline circulation in the waters of the Korean Peninsula, affecting the size and frequency of marine disasters such as typhoons and tsunamis, and has a very important oceanographic impact, such as becoming a source of harmful organisms and radioactively contaminated water. Therefore, for an immediate response to these maritime disasters, real-time ocean observation is required. However, compared to other straits, in the case of southern Jeju, such wide area marine observations are insufficient. Therefore, in this study, surface current field of the southern strait of Jeju was calculated using High-Frequency radar (HF radar). the large surface current field is calculated, and post-processing and data improvement are carried out through APM (Antenna Pattern Measurement) and FOL (First Order Line), and comparative analysis is conducted using actual data. As a result, the correlation shows improvement of 0.4~0.7 and RMSE of about 1~19 cm/s. These high-frequency radar observation results will help solve domestic issues such as response to typhoons, verification of numerical models, utilization of wide area wave data, and ocean search and rescue in the future through the establishment of an open data network.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.334-343
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• 2023

Purpose: In this study, the cavity data found through ground cavity exploration was combined with underground facilities to derive a correlation, and the ground subsidence prediction map was verified based on the AI algorithm. Method: The study was conducted in three stages. The stage of data investigation and big data collection related to risk assessment. Data pre-processing steps for AI analysis. And it is the step of verifying the ground subsidence risk prediction map using the AI algorithm. Result: By analyzing the ground subsidence risk prediction map prepared, it was possible to confirm the distribution of risk grades in three stages of emergency, priority, and general for Busanjin-gu and Saha-gu. In addition, by arranging the predicted ground subsidence risk ratings for each section of the road route, it was confirmed that 3 out of 61 sections in Busanjin-gu and 7 out of 68 sections in Sahagu included roads with emergency ratings. Conclusion: Based on the verified ground subsidence risk prediction map, it is possible to provide citizens with a safe road environment by setting the exploration section according to the risk level and conducting investigation.

• 한국체육학회지인문사회과학편
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• v.55 no.6
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• pp.801-810
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• 2016

The purpose of the study was to conduct a text mining examining keywords related to the National Paralympics and provide the fundamental information that would be used to change perception of people without disabilities toward disabilities and to promote the social participation of people with and without disabilities in the National Paralympics. Social big data regarding the National Paralympics were retrieved from news articles and blog postings identified by search engines, Naver, Daum, and Google. The data were then analysed using R-3.3.1 Version Program. The analysing techniques were cloud analysis, correlation analysis and social network analysis. The results were as follows. First, news were mainly related to game results, sports events, team participation and host avenue of the 33rd ~ 36th National Paralympics. Second, search results about the 33rd ~ 36th National Paralympics between Naver, Daum, and Google were similar to one another. Thirds, the keywrods, National Paralympics, sports for the disabled, and sports, demonstrated a high close centrality. Further, degree centrality and betweenness centrality were associated in the keywords such as sports for all, participation, research, development, sports-disabled, research-disabled, sports for all-participation, disabled-participation, sports for all-disabled, and host-paralympics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5B
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• pp.397-408
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• 2009

In this study, a stochastic precipitation generation framework for simultaneous simulation of daily precipitation at multiple sites is presented. The precipitation occurrence at individual sites is generated using hybrid-order Markov chain model which allows higher-order dependence for dry sequences. The precipitation amounts are reproduced using Anscombe residuals and gamma distributions. Multisite spatial correlations in the precipitation occurrence and amount series are represented with spatially correlated random numbers. The proposed model is applied for a network of 17 locations in the middle of Korean peninsular. Evaluation statistics are reported by generating 50 realizations of the precipitation of length equal to the observed record. The analysis of results show that the model reproduces wet day number, wet and dry day spell, and mean and standard deviation of wet day amount fairly well. However, mean values of 50 realizations of generated precipitation series yield around 23% Root Mean Square Errors (RMSE) of the average value of observed maximum numbers of consecutive wet and dry days and 17% RMSE of the average value of observed annual maximum precipitations for return periods of 100 and 200 years. The provided model also reproduces spatial correlations in observed precipitation occurrence and amount series accurately.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.40-48
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• 2023

In this paper, a sensor-based monitoring system was established to analyze the long-term behavioral characteristics of the caisson quay wall, a representative structural type in port facilities. Data was collected over a period of approximately 10 months. Based on existing literature, anomalous behaviors of port facilities were classified, and a measurement system was selected to detect them. Monitoring systems were installed on-site to periodically collect data. The collected data was transmitted and stored on a server through LTE network. Considering the site conditions, inclinometers for measuring slope and crack meters for measuring spacing and settlement were installed. They were attached to two caissons for comparison between different caissons. The correlation among measured data, temperature, and tidal level was examined. The temperature dominated the spacing and settlement data. When the temperature changed by approximately 50 degrees, the spacing changed by 10 mm, the settlement by 2 mm, and the slope by 0.1 degrees. On the other hand, there was no clear relationship with tidal level, indicating a need for more in-depth analysis in the future. Based on the characteristics of these collected database, it will be possible to develop algorithms for detecting abnormal states in gravity-type quay walls. The acquisition and analysis of long-term data enable to evaluate the safety and usability of structures in the event of disasters and emergencies.

• IMMUNE NETWORK
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• v.23 no.2
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• pp.17.1-17.16
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• 2023

Latent membrane protein 2A (LMP2A), a latent Ag commonly expressed in Epstein-Barr virus (EBV)-infected host cells, is a target for adoptive T cell therapy in EBV-associated malignancies. To define whether individual human leukocyte antigen (HLA) allotypes are used preferentially in EBV-specific T lymphocyte responses, LMP2A-specific CD8⁺ and CD4⁺ T cell responses in 50 healthy donors were analyzed by ELISPOT assay using artificial Ag-presenting cells expressing a single allotype. CD8⁺ T cell responses were significantly higher than CD4⁺ T cell responses. CD8⁺ T cell responses were ranked from highest to lowest in the order HLA-A, HLA-B, and HLA-C loci, and CD4⁺ T cell responses were ranked in the order HLA-DR, HLA-DP, and HLA-DQ loci. Among the 32 HLA class I and 56 HLA class II allotypes, 6 HLA-A, 7 HLA-B, 5 HLA-C, 10 HLA-DR, 2 HLA-DQ, and 2 HLA-DP allotypes showed T cell responses higher than 50 spot-forming cells (SFCs)/5×105 CD8⁺ or CD4⁺ T cells. Twenty-nine donors (58%) showed a high T cell response to at least one allotype of HLA class I or class II, and 4 donors (8%) had a high response to both HLA class I and class II allotypes. Interestingly, we observed an inverse correlation between the proportion of LMP2A-specific T cell responses and the frequency of HLA class I and II allotypes. These data demonstrate the allele dominance of LMP2A-specific T cell responses among HLA allotypes and their intra-individual dominance in response to only a few allotypes in an individual, which may provide useful information for genetic, pathogenic, and immunotherapeutic approaches to EBV-associated diseases.