• Journal of Korean Elementary Science Education
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• v.40 no.1
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• pp.22-35
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• 2021

In order to investigate the trends in science education research using AR (Augmented Reality) and derive implications for elementary science education, we analyzed 71 research articles on AR application in science education published in both Korea and abroad from 2010 to August 2020. In quantitative aspects, the number of published articles has steadily increased. For domestic researches, the number of papers targeting for elementary school students was higher than that of middle & high school students. In the research method aspects, qualitative methods were most frequently used. In particular, papers regarding the development of AR program and verification of its effectiveness were most frequently published. The researches using mixed method in domestic field were smaller in number than that of the research in abroad. There were similar trends in research targeting elementary school students. In the aspects of the contents, more researches were performed on biology and earth science areas than others. In case of researches for elementary school students, the proportion of researches on biology and earth science was even higher. Domestically the proportion of studies on the convergence of science and non-science subjects was higher than that of foreign studies. The number of researches exploring the effectiveness on 'non-scientific attitude domain', 'cognitive domain', and 'program domain' were relatively higher than that on 'inquiry & practice domain' and 'science-related attitude domain'. For types of AR contents, 'observation manipulation type' was mostly studied, followed by 'experimental activity type', and 'learning guide type'. In case of studies on elementary school students, the ratio of 'observation manipulation type' contents was higher than that of others, whereas studies on 'field problem solving type' were relatively less reported than others. In addition, studies on 'simple interaction' were most frequently reported. Particularly, there were relatively few studies on 'linear and nonlinear interactions' in domestic field. As a result of analyzing key words, we found that the key words related to the characteristics and implementation of AR frequently occurred, and the key words related to elementary education and the merits of AR had many direct connections with other key words.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.378-390
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• 2022

With the recent development of deep composite multiplication neural network learning, deep learning techniques applied to single-image super-resolution have shown good results, and the strong expression ability of deep networks has enabled complex nonlinear mapping between low-resolution and high-resolution images. However, there are limitations in applying it to real-time or low-power devices with increasing parameters and computational amounts due to excessive use of composite multiplication neural networks. This paper uses blocks that extract hierarchical characteristics little by little using information distillation and suggests the Recursive Distillation Super Resolution Network (RDSRN), a lightweight network that improves performance by making more accurate high frequency components through high frequency residual purification blocks. It was confirmed that the proposed network restores images of similar quality compared to RDN, restores images 3.5 times faster with about 32 times fewer parameters and about 10 times less computation, and produces 0.16 dB better performance with about 2.2 times less parameters and 1.8 times faster processing time than the existing lightweight network CARN.

• Journal of Bio-Environment Control
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• v.31 no.2
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• pp.98-103
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• 2022

Non-destructive estimation of leaf area is a more efficient and convenient method than leaf excision. Thus, several models predicting leaf area have been developed for various horticultural crops. However, there are limited studies on estimating the leaf area of strawberry plants. In this study, we predicted the leaf areas via nonlinear regression analysis using the leaf lengths and widths of three-compound leaves in five domestic strawberry cultivars ('Arihyang', 'Jukhyang', 'Keumsil', 'Maehyang', and 'Seollhyang'). The coefficient of determination (R²) between the actual and estimated leaf areas varied from 0.923 to 0.973. The R² value varied for each cultivar; thus, leaf area estimation models must be developed for each cultivar. The leaf areas of the three cultivars 'Jukhyang', 'Seolhyang', and 'Maehyang' could be non-destructively predicted using the model developed in this study, as they had R² values over 0.96. The cultivars 'Arihyang' and 'Geumsil' had slightly low R² values, 0.938 and 0.923, respectively. The leaf area estimation model for each cultivar was coded in Python and is provided in this manuscript. The estimation models developed in this study could be used extensively in other strawberry-related studies.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.136-145
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• 2020

Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that directly influences crop production. The fluctuating amount of rainfall per year has led to the adoption of irrigation systems in most farms. The absence of smart sensors, monitoring methods and control, has led to low harvests and draining water sources. In this research paper, we introduce a 433 MHz Radio Frequency and 2G based Smart Irrigation Meter System and a water prepayment system for rural areas of Tanzania with no reliable internet coverage. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, a solenoid valve, and a prepayment system. To achieve high precision in linear and nonlinear regression and to improve classification and prediction, this work cascades a Dynamic Regression Algorithm and Naïve Bayes algorithm.

• Journal of the Korean GEO-environmental Society
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• v.24 no.9
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• pp.15-24
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• 2023

The behavior of buried pipes is directly influenced by the nonlinearity and complex characteristics of the surrounding soil. However, the simplified beam-spring model, which ignores the nonlinearity and complex behavior of soil, is commonly used in practice. In response, several studies have employed continuum analysis methods to account for the nonlinear and complex behavior of the soil. This paper presents various numerical continuum analysis techniques and verifies their comparison with full-scale tests. The study found that reaction force results close to the full-scale test could be obtained by applying contact surface characteristics that take into account the interaction between the ground and the buried pipe. In the case of sharing pipe and soil node method and ignoring the interaction between pipe and soil, excessive reaction force was derived, and the failure shapes were different. In addition, this study applied the dynamic explicit analysis method, ALE method, and CEL method. It was confirmed that the displacement-reaction relationship and failure shape are similar to those of the static analysis.

• Journal of Preventive Medicine and Public Health
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• v.56 no.3
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• pp.282-290
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• 2023

Objectives: This study aimed to evaluate the potential interaction between kidney function and the non-linear association between serum calcium levels and cardiovascular disease (CVD) mortality. Methods: This study included 8927 participants enrolled in the Dong-gu Study. Albumin-corrected calcium levels were used and categorized into 6 percentile categories: <2.5th, 2.5-25.0th, 25.0-50.0th, 50.0-75.0th, 75.0-97.5th, and >97.5th. Restricted cubic spline analysis was used to examine the non-linear association between calcium levels and CVD mortality. Cox proportional hazard regression was used to estimate hazard ratios (HRs) for CVD mortality according to serum calcium categories. All survival analyses were stratified by the estimated glomerular filtration rate. Results: Over a follow-up period of 11.9±2.8 years, 1757 participants died, of whom 219 died from CVD. A U-shaped association between serum calcium and CVD mortality was found, and the association was more evident in the low kidney function group. Compared to the 25.0-50.0th percentile group for serum calcium levels, both low and high serum calcium tended to be associated with CVD mortality (<2.5th: HR, 6.23; 95% confidence interval [CI], 1.16 to 33.56; >97.5th: HR, 2.56; 95% CI, 0.76 to 8.66) in the low kidney function group. In the normal kidney function group, a similar association was found between serum calcium levels and CVD mortality (<2.5th: HR, 1.37; 95% CI, 0.58 to 3.27; >97.5th: HR, 1.65; 95% CI, 0.70 to 3.93). Conclusions: We found a non-linear association between serum calcium levels and CVD mortality, suggesting that calcium dyshomeostasis may contribute to CVD mortality, and kidney function may modify the association.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.371-381
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• 2017

This paper presents a methodology for creating abstract animation based on the human movement theories originating from the work of dance theorist Rudolf von Laban. Laban Movement Analysis is a method and language for describing, visualizing, interpreting and documenting all varieties of human movement, and Choreutics is based on universal patterns of nature and of human as part of a universal design. Laban defines the space of movements in a profoundly dualistic way. Outwardly, his objective and scientific definitions provide a concrete base for generating human movements in computer graphics in terms of geometric and motion primitives such as points, lines, planes, polygons, linear and nonlinear movements. On the other hand, he also offers a system for understanding the subtle characteristics about the way a movement is dynamically done with respect to inner intention. Laban's interpretations of human motion can be utilized potentially in plastic arts and computer arts. Our work was inspired by those physical and psychological analyses and computer algorithms have been developed for creating abstract animation. We presented our computer animation works entitled "Choreography" in the exhibitions: a special section in "2015 Craft Trend Fair" and "Make Your Movement" held in the Korean Cultural Centre in UK, 2016. In this paper, we describe our ideas and methods for creating abstract object movements based on the Laban's motion representations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3C
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• pp.187-196
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• 2008

An earthquake of magnitude 5.0 occurred at Ssang-gye-sa, a Buddhist temple in Jirisan, located near the southern border of the Korean peninsula on 4 July 1936. It resulted in severe damage of several buildings and structures in Ssang-gye-sa. Particularly, the top component of a five-story stone pagoda in the temple was tipped over and fell down during the earthquake. This earthquake damage case would be usefully applied to estimating the intensity of ground motion in the Korean peninsula, a moderate seismicity region, where strong motion has never been recorded with the exception of historic seismic events. In order to estimate the local site effects and the corresponding ground motion at Ssang-gye-sa site, intensive site investigations including borehole drilling and in-situ seismic tests such as crosshole and SASW tests were performed in the temple area. Based on the site characteristics, site-specific seismic response analyses using various input motions were conducted for a representative Ssang-gye-sa site by means of both one-dimensional equivalent-linear and nonlinear methods with six input rock outcrop acceleration levels ranging from 0.044g to 0.220g. The resultant site-specific seismic responses indicated the amplified ground motions in the short-period range near the site period of Ssang-gye-sa. Furthermore, the intensity on rock outcrop of the 1936 Jirisan earthquake was estimated by making a comparison between the site responses analysis results in this study and the full-scaled seismic test of pagoda model in the prior study.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.2
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• pp.43-52
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• 2024

In this study, we evaluated the seismic performance of a masonry building that was not designed to be earthquake-resistant and attempted to improve the seismic performance by adopting a seismic reinforcement method on the exterior of the building. In addition, the building seismic design standards and commentary(KDS 41 17 00:2019) and existing facility(building) seismic performance evaluation methods were applied to evaluate seismic performance, and a pushover analysis was performed using non-linear static analysis. As the result of this study, it was determined that seismic reinforcement was urgent because the distribution rate of earthquake-resistant design of houses in Korea was low and masonry structures accounted for a large proportion of houses. When reinforcing the steel beam-column+brace frame in a masonry building, the story drift angle was 0.043% in the X direction and 0.047% in the Y direction, indicating that it satisfied the regulations. The gravity load resistance capacity by performance level was judged to be a safe building because it was habitable in both X and Y directions. In conclusion, it is believed that the livability and convenience of the house can be secured by reinforcing the exterior of the building and the seismic performance and behavior of the structure can be clearly predicted.