• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2966-2986
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• 2023

Climate change is a constant threat to human life, and it is important to understand the public perception of this issue. Previous studies examining climate change have been based on limited survey data. In this study, the authors used big data such as news articles and social media data, within which the authors selected specific keywords related to climate change. Using these natural language data, topic modeling was performed for discourse analysis regarding climate change based on various topics. In addition, before applying topic modeling, sentiment analysis was adjusted to discover the differences between discourses on climate change. Through this approach, discourses of positive and negative tendencies were classified. As a result, it was possible to identify the tendency of each document by extracting key words for the classified discourse. This study aims to prove that topic modeling is a useful methodology for exploring discourse on platforms with big data. Moreover, the reliability of the study was increased by performing topic modeling in consideration of objective indicators (i.e., coherence score, perplexity). Theoretically, based on the social amplification of risk framework (SARF), this study demonstrates that the diffusion of the agenda of climate change in public news media leads to personal anxiety and fear on social media.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1630-1648
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• 2021

Owing to the unprecedented COVID-19 pandemic, the pharmaceutical industry has attracted considerable attention, spurred by the widespread expectation of vaccine development. In this study, we collect relevant topics from news articles related to COVID-19 and explore their links with two South Korean pharmaceutical indices, the Drug and Medicine index of the Korea Composite Stock Price Index (KOSPI) and the Korean Securities Dealers Automated Quotations (KOSDAQ) Pharmaceutical index. We use generalized Dirichlet-multinomial regression (g-DMR) to reveal the dynamic topic distributions over metadata of index values. The results of our analysis, obtained using g-DMR, reveal that a greater focus on specific news topics has a significant relationship with fluctuations in the indices. We also provide practical and theoretical implications based on this analysis.

• Korean Journal of Social Welfare
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• v.69 no.1
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• pp.79-101
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• 2017

The purpose of this study is to identify the multicultural competence of university students majoring in social welfare studies and to verify the influence of human rights attitude and spiritual intelligence that affect multicultural competence using structural equation model. Spiritual intelligence was set as an independent variable and multicultural competence was set as a dependent variable. Human rights attitude was established as a mediating variable. Study subjects were 259 university students majoring in social welfare studies at 5 universities in the Daegu, Gyoungbuk area. Spiritual intelligence and human rights attitude appeared to have a significant effect on multicultural competence, indicating that a higher level of spiritual intelligence and human rights attitude were correlated with a higher level of human rights attitude. Also in the pathway of spiritual intelligence on multicultural competence, human rights attitude had a significant mediating effect. When the university student majoring in social welfare studies had a high level of spiritual intelligence including transcendence and meaning and purpose of life, their perspective on human rights which is important in the practice of social welfare affected the multicultural competence required to assist immigrants of various identities. Based on the findings of the study, it is recommended for the university students majoring in social welfare to have the "three-multi-sensitivities" including sensitivity of multicultural competence, sensitivity of spiritual intelligence, and sensitivity of human right attitude.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.113-122
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• 2015

Collective intelligence can be an influential factor of decision-making based on collaboration and information exchange between individuals. Our study explores whether collective intelligence can mitigate the loss aversion effect, bias and error in human judgment, and collective intelligence in online communities can reduce the loss aversion effect. Our community settings display both individual-level and group-level loss aversion effect, investigate effective collective intelligence characteristics like investment commitment, participant experience. Using a multi-method approach our research comprises a web-based experiment with 100 participants investing 3 situations from a real-world community, data from a survey measuring loss aversion behavior of participants. The results suggest the loss aversion effect mitigates under the online-circumstance. Overall, our results suggest that, while collective intelligence mitigates the loss aversion effect, participants do not transfer these results to other settings.

• Asia pacific journal of information systems
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• v.32 no.4
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• pp.916-944
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• 2022

Artificial Intelligence has been a conceptual area for several decades. It has been studied extensively through experiments by the Information Systems community. When Information Systems supported with Information Technology became all pervasive in business and other allied areas, gradually the advancements in Artificial Intelligence also emerged as innovations across domains. Artificial Intelligence by definition is expected to substitute Human Intelligence, thereby making a huge space for innovation. In fact, all processes effected by human intelligence are liable to be replaced by AI which in itself is a massive innovation space. This paper will study the publication's repository (Scopus and Google Scholar from 1983 till 2021) in the area of Artificial Intelligence and innovation, then analyze the trend to gain insight into the evolution of AI as a vehicle for innovation.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.152-158
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• 2022

As various mobile robots and manipulator robots have been commercialized, robots that can be used by individuals in their daily life have begun to appear. With the development of robots that support daily life, the interaction between robots and humans is becoming more important. Manipulator robots that support daily life must perform tasks such as pressing buttons or picking up objects safely. In many cases, this requires expensive multi-axis force/torque sensors to measure the interaction. In this study, we introduce a low-cost two-axis pressure sensor that can be applied to manipulators for education or research. The proposed system used three force sensitive resistor (FSR) sensors and the structure was fabricated by 3D printing. An experimental device using a load cell was constructed to measure the biaxial pressure. The manufactured prototype was able to distinguish the +-x-axis and the +-y-axis pressures.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.144-150
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• 2023

With progressive advancements in Man-made consciousness (computer based intelligence) and Profound Learning (DL), contributing altogether to Normal Language Handling (NLP), the precision and nature of Machine Interpretation (MT) has worked on complex. There is a discussion, but that its no time like the present the human interpretation became immaterial or excess. All things considered, human flaws are consistently dealt with by its own creations. With the utilization of brain networks in machine interpretation, its been as of late guaranteed that keen frameworks can now decipher at standard with human interpreters. In any case, simulated intelligence is as yet not without any trace of issues related with handling of a language, let be the intricacies and complexities common of interpretation. Then, at that point, comes the innate predispositions while planning smart frameworks. How we plan these frameworks relies upon what our identity is, subsequently setting in a one-sided perspective and social encounters. Given the variety of language designs and societies they address, their taking care of by keen machines, even with profound learning abilities, with human proficiency looks exceptionally far-fetched, at any rate, for the time being.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.177-182
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• 2019

As progress of technology, Artificial Intelligence is applied in various fields of industry such as finance, production, medical treatment, service, art by changing the way they look continuously. As AI is progressive area, We have to know what kind of changing is merged in human society by AI. In this paper, through the investigations of Artificial Intelligence's concept and the way Artificial Intelligence's technology is implemented in modern industry, we studied positive effect and negative effect of AI. By this study, In conclusion, by realizing how close Artificial Intelligence had come to our life, we can prepare to seek a foothold to deal with this Artificial Intelligence.

• Korean Journal of Human Ecology
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• v.10 no.2
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• pp.141-151
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• 2001

The purpose of this study was to investigate impact mother's personality and children's educational experience on children's intelligence. Subjects were 90 children and their mothers in Daejeon, Korea. The main results of this study were as follows; First, there were significant differences between the children's intelligence and mother's educational level and family income. Second, there were significant difference between children's intelligence and mother's personality. Third, there was significant difference between children's intelligence and children's early educational experience. Fourth, the influenced variables on children's intelligence were mother's educational level, early educational experience, and educational experience with parent and child at home.

• Child Health Nursing Research
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• v.13 no.4
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• pp.427-435
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• 2007

Purpose: This study presents the findings of various research on human intelligence and Multiple Intelligence Theory and suggested the implications of Multiple Intelligence Theory-based approach to the nursing education for the ill children. Method: Research objectives were accomplished by conducting a literature review. The main areas of the literature review included the Multiple Intelligence Theory, and it's application case for the children with learning disorder. Results: Dissatisfaction with traditional IQ tests has led to the development of a number of alternative theories, all of which suggest that intelligence is the result of a number of independent abilities that uniquely contribute to human performance. Among them, Multiple Intelligences Theory led to break intelligence down into at least eight different components: logical, linguistic, spatial, musical, kinesthetic, naturalist, intra-personal and interpersonal intelligences. In addition, Multiple Intelligence Theory and it's application case believes that every topic can be effectively taught and achieved using six entry points framework. Conclusions: The educational implications of Multiple Intelligence Theory in view of the health education and education in the children's hospital school should be considered for the ill children2's better education in a hospital setting.