• Journal of Science and Technology Studies
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• v.19 no.2
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• pp.169-206
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• 2019

This article seeks to explore new relationships and ethics of human and technology by analyzing a cultural imaginary produced by artificial intelligence. Drawing on theoretical reflections of the Feminist Scientific and Technological Studies which understand science and technology as the matter of care(Puig de la Bellacas, 2011), this paper focuses on the fact that artificial intelligence and robots materialize cultural imaginary such as autonomy. This autonomy, defined as the capacity to adapt to a new environment through self-learning, is accepted as a way to conceptualize an authentic human or an ideal subject. However, this article argues that artificial intelligence is mediated by and dependent on invisible human labor and complex material devices, suggesting that such autonomy is close to fiction. The recent growth of the so-called 'assistant technology' shows that it is differentially visualizing the care work of both machines and humans. Technology and its cultural imaginary hide the care work of human workers and actively visualize the one of the machine. And they make autonomy and agency ideal humanness, leaving disabled bodies and dependency as unworthy. Artificial intelligence and its cultural imaginary negate the value of disabled bodies while idealizing abled-bodies, and result in eliminating the real relationship between man and technology as mutually dependent beings. In conclusion, the author argues that the technology we need is not the one to exclude the non-typical bodies and care work of others, but the one to include them as they are. This technology responsibly empathizes marginalized beings and encourages solidarity between fragile beings. Inspired by an art performance of artist Sue Austin, the author finally comes up with and suggests 'artificial intelligence in wheelchair' as an alternative figuration for the currently dominant 'autonomous artificial intelligence'.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.

• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.231-241
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• 2021

This study intended to present strategies and implications for attracting new students and customized education to university officials through research on the participation of workers' academic aspirations in university education. Thus, variables were derived by analyzing prior data, and causal settings between variables and questionnaires were developed. Subject to the survey, 331 workers interested in participating in university education were collected through interpersonal interviews. The collected data were dataized, and reliability and feasibility verification and frequency analysis were conducted. Finally, we validate the fit of the structural equation model and the causal relationship for each concept. Therefore, the results of the validation show the following implications. First, university officials should be motivated by a mentor and mentee system with experienced people who have switched to a suitable vocational group through university education. It will also be necessary to develop and disseminate programs so that they can continue to develop themselves for the future. To this end, it will be necessary to help them understand their aptitude and strengths through consultation with experts. Second, university officials should strengthen public relations so that prospective students can know the cases and information of the job transformation of the admitted workers through recommendations. It will also be necessary to develop university education programs that can self-develop, accept various ideas through "public contest", and provide accurate information about university education to workers through re-processing. Third, university officials should provide workers with a program that allows them to catch two rabbits: job transformation and self-improvement through university education. In other words, it is necessary to stimulate the motivation of workers by providing various information such as visiting advanced overseas companies, obtaining various certificates, moving between departments of blue-collar and white-collar, and transfer opportunities. Fourth, university officials should actively promote university education programs related to this by participating in university education and receiving systematic education and the flow of social environment. Finally, university officials will need to consult and promote workers so that they can self-develop when they participate in college education, and they will have to figure out what they need for self-development through demand surveys and analysis.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.5
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• pp.431-449
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• 2022

As many tunnels generally have been constructed, various experiences and techniques have been accumulated for tunnel design as well as tunnel construction. Hence, there are not a few cases that, for some usual tunnel design works, it is sufficient to perform the design by only modifying or supplementing previous similar design cases unless a tunnel has a unique structure or in geological conditions. In particular, for a tunnel blast design, it is reasonable to refer to previous similar design cases because the blast design in the stage of design is a preliminary design, considering that it is general to perform additional blast design through test blasts prior to the start of tunnel excavation. Meanwhile, entering the industry 4.0 era, artificial intelligence (AI) of which availability is surging across whole industry sector is broadly utilized to tunnel and blasting. For a drill and blast tunnel, AI is mainly applied for the estimation of blast vibration and rock mass classification, etc. however, there are few cases where it is applied to blast pattern design. Thus, this study attempts to automate tunnel blast design by means of machine learning, a branch of artificial intelligence. For this, the data related to a blast design was collected from 25 tunnel design reports for learning as well as 2 additional reports for the test, and from which 4 design parameters, i.e., rock mass class, road type and cross sectional area of upper section as well as bench section as input data as well as16 design elements, i.e., blast cut type, specific charge, the number of drill holes, and spacing and burden for each blast hole group, etc. as output. Based on this design data, three machine learning models, i.e., XGBoost, ANN, SVM, were tested and XGBoost was chosen as the best model and the results show a generally similar trend to an actual design when assumed design parameters were input. It is not enough yet to perform the whole blast design using the results from this study, however, it is planned that additional studies will be carried out to make it possible to put it to practical use after collecting more sufficient blast design data and supplementing detailed machine learning processes.

• Journal of Christian Education in Korea
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• v.68
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• pp.345-374
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• 2021

This study is a paper which studies the fact that autobiographical writing in Christian educational books is an important channel for studying the identity of Christian educators. The identity of Christian educators is the background and foundation of the study of Christian education theory. It was found through research that the scholar's identity is more evident in autobiographical writing from a first-person perspective experienced by the author than in argumentative writing with objective and cognitive limitations. This study examined the concept and characteristics of autobiographical writing research, the relationship of autobiographical writing research and self-identity, the relationship between autobiographical writing and Christian education, and discovered autobiographical writing in Christian educational scholars' books. Through the autobiographical writing of Maria Harris' Teaching and Religious Imagination, Parker Palmer's The Courage to Teach, and Elizabeth Moore's Teaching as a Sacrament Act, we studied that the identity of Christian educators can meet, transform, and expand learners' identity as well. Through research, it has been confirmed that autobiographical writing takes the form of a story, but as a story distinct from the story, it becomes a place where the authors' identity and readers' identity can meet, wrestle and expand. Autobiographical writing has a relationship with story and self-identity. These characteristics are also linked to Christian educational goals that focus on the formation and transformation of self-identity. The autobiographical writing in Harris, Palmer, and Moore's writings shows the identity of a teacher, including scholars' theological perspectives and views on education. As the writing of Christian education books so far has become argumentative and objective writing, readers has felt a sense of disparity and disconnection. If autobiographical writing becomes educational books' style, it can invite readers to empathize with who the author is. Christian education will experience more fundamental changes with autobiographical writing.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.40 no.2
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• pp.24-33
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• 2022

The travel notes and nature poems found in historic literary men's works can be considered historical records related to scenic sites. Such travel notes and nature poems are based on the writers' personal characters, experiences, learning and etc. Such works clearly show the characters of each literature, information of the related objects and the writers' thoughts of the objects. This study, thus, looked into Euisang on Xīsāishān Mountain that could be the origin of Eobusa(漁父詞) loved and sung by Korean historic literary men, and found that the Korean and Chinese literary men's thoughts were shown through their ways to enjoy Xīsāishān Mountain and their Euisang on the mountain, which was different between the Korean and Chinese literary men depending on the geographical locations described in their poems. In detail, the study results are: 1. Such difference of the ways to enjoy Xīsāishān Mountain, the scenic site described in historic Korean and Chinese literary men's work is broadly classified into the ways to enjoy the scenic site by seeing it in person and the ways to enjoy it under the mental structure of speculation. 2. Xīsāishān Mountain in Wuxing is the background of Yújiāzi(漁家子) of the painting Zhāngzhìhé, is boasting its distinguished beautiful nature, and is the place where the Confucian Study of Hú(湖學) was originated. It is also the place known of its warmhearted climate. Therefore, Euisang on Xīsāishān Mountain under such beautiful and warmhearted circumstance are realized as the complete freedom and seclusion in Taoism and the satisfaction with the given environment and position in Confucianism. 3. Xīsāishān Mountain in Wǔchāng is a military strategic point with rugged mountain terrain and scenery that has been a historic ferocious battlefield and related with the loyal civil servant Qū Yuán. The Euisang on Xīsāishān Mountain in Wǔchāng, therefore, represents the nature scenery of a rugged fortress and patriotism of Confucianism. 4. The Korean literary men's way to enjoy Xīsāishān Mountain is Shinyu(神遊: spiritual travel), so that their Euisang is formed according to the direction of the writer's values. Especially it is noted that Korean Euisang on Xīsāishān Mountain is originally based on the painting Zhāngzhìhé that shows the complete free mood of Taoism; and the Euisang on Xīsāishān Mountain that came from the mindful image by the poet monk Qíjǐ of Tang dynasty and Kim Si-seup appears with such Buddhist ways to seek the truth as SakGongIlYeo(色空一如: Being full is essentially as same as being vacant) and GyeonSeongSeongBul(見性成佛: Everybody can become Buddha by enlightenment).

• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.139-150
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• 2023

This study started with the awareness of the need to explore various aspects of science education and was conducted according to the necessity of practical research on science cultural activities targeting adults. Accordingly, adults' book discussions of science fiction were selected as research cases, and science-related attitudes in science cultural activities were explored. There are four participants in the study, all of whom have engaged in a book club and have not majored or are working in science disciplines. Three science fictions were selected after establishing specific standards for the selection discussed with participants. For four months, a total of three unstructured book discussions of science fiction, post-interviews for each discussion, and in-depth individual interviews after the end of the entire activity were conducted. Various data such as recorded and transcribed reading discussion discourse, post- and in-depth individual interviews, researchers' observation records, and participants' book journals were collected and analyzed using a continuous comparison method. As a result of the study, as scientific thinking is illustrated in SF, the participants also demonstrated scientific attitudes during their discussions. In addition, the textual feature(storytelling) of science fiction was found to lessen cognitive overload and the burden of understanding science by providing scientific knowledge with context. Finally they demonstrated a shift in attitude toward science, valuing science cultural activities in themselves, rather than simply viewing science as a subject of understanding and learning. The conclusions and meanings of this study based on the above results are presented to enhance a positive attitude toward science for adults even after school education.

• Korean Journal of Culture and Social Issue
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• v.19 no.2
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• pp.285-318
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• 2013

The purpose of this research is to examine the self-concept in the cyberspace, self-efficacy, relationship with friends, subjective well-being and academic grade among adolescents who are addicted to Internet and those who are not addicted to Internet. A total of 1,057 adolescents (male=545, female=512), 326 from middle school, 361 from high school, and 370 from special education school, participated in the study. The results are as follows. First, qualitative analysis of the conception of self in the cyberspace indicates that those adolescents addicted to Internet reported that in the cyberspace they have fun, followed by they are the same as in real life, they spend time in cyberspace and they can become an imaginary person. Those adolescents not addicted to Internet reported that in the cyberspace they are the same as in real life, followed by they spend time in cyberspace and they can become an imaginary person. When they play Internet games, majority of adolescents in both groups reported that it is fun, followed by they become engrossed and they become aggressive. Second, those adolescents who are not addicted to Internet had higher scores on self-efficacy than those adolescents who are addicted to Internet, including self-regulatory efficacy for learning, relational efficacy, and resiliency of efficacy. Third, the number of friends and close friends that adolescents who are not addicted to Internet were not significantly different from those adolescents who are addicted to Internet. However, those adolescents who are not addicted to Internet were more likely receive social support from friends and were less likely to be social excluded than those adolescents who are addicted to Internet. Fourth, those adolescents who are not addicted to Internet had significantly higher scores on subjective well-being than those adolescents who are addicted to Internet. Fifth, those adolescents who are not addicted to Internet had significantly higher scores on both subjective and objective academic grade than those adolescents who are addicted to Internet.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.695-713
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• 2023

In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R² greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.