• Knowledge Management Research
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• v.25 no.1
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• pp.155-172
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• 2024

This study investigates the effectiveness of foreign language learning through diverse treatments in virtual settings, particularly by differentiating virtual environments with three textual enhancement techniques. A 2 × 3 mixed-factorial design was used, treating virtual environments as within-subject factors and textual enhancement techniques as between-subject factors. Participants experienced two videos, each in different virtual learning environments with one of the random textual enhancement techniques. The results showed that the interaction between different virtual environments and textual enhancement techniques had a statistically significant impact on presence among groups. In examining main effects of virtual environments, significant differences were observed in flow and attitude toward pre-post learning. Also, main effects of textual enhancements notably influenced flow, intention to use, learning satisfaction, and learning confidence. This study highlights the potential of Metaverse in foreign language learning, suggesting that learner experiences and effects vary with different virtual environments.

• Smart Media Journal
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• v.13 no.4
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• pp.33-48
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• 2024

With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.

• Journal of Animal Science and Technology
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• v.66 no.2
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• pp.310-325
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• 2024

Glyconutrients help in the body's cell communication. Glyconutrients and synbiotics are promising options for improving immune function. Therefore, we hypothesized that combining synbiotics and glyconutrients will enhance pig nutrient utilization. 150 pigs (Landrace × Yorkshire × Duroc), initially weighing 58.85 ± 3.30 kg of live body weight (BW) were utilized to determine the effects of synbiotics-glyconutrients (SGN) on the pigs' performance, feed efficiency, gas emission, pork traits, and composition of fatty acids. The pigs were matched by BW and sex and chosen at random to 1 of 3 diet treatments: control = Basal diet; TRT1 = Basal diet + SGN 0.15%; TRT2 = Basal diet + SGN 0.30%%. The trials were conducted in two phases (weeks 1-5 and weeks 5-10). The average daily gain was increased in pigs fed a basal diet with SGN (p = 0.036) in weeks 5-10. However, the apparent total tract digestibility of dry matter, nitrogen, and gross energy did not differ among the treatments (p > 0.05). Dietary treatments had no effect on NH₃, H₂S, methyl mercaptans, acetic acids, and CO₂ emissions (p > 0.05). Improvement in drip loss on day 7 (p = 0.053) and tendency in the cooking loss were observed (p = 0.070) in a group fed basal diets and SGN at 0.30% inclusion level. The group supplemented with 0.30% of SGN had higher levels of palmitoleic acid (C16:1), margaric acid (C17:0), omega-3 fatty acid, omega-6 fatty acid, and ω-6: ω-3 ratio (p = 0.034, 0.020, 0.025, 0.007, and 0.003, respectively) in the fat of finishing pigs. Furthermore, group supplemented with 0.30% of SGN improved margaric acid (C17:0), linoleic acid (C18:2n6c), arachidic acid (C20:0), omega 6 fatty acid, omega-6 to omega-3 ratio, unsaturated fatty acid, and monounsaturated fatty acid (p = 0.037, 0.05, 0.0142, 0.036, 0.033, 0.020, and 0.045, respectively) in the lean tissues of finishing pigs compared to pigs fed with the control diets. In conclusion, the combination of probiotics, prebiotics, and glyconutrients led to higher average daily gain, improved the quality of pork, and more favorable fatty acid composition. Therefore, these results contributed to a better understanding of the potential of SGN combinations as a feed additive for pigs.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.251-268
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• 2024

Recently, with the implementation of the "e-Government Performance Management Guidelines," there is a growing demand for setting performance indicators for information systems. For systems that provide information services to the public, such as CODIL, it is not easy to set performance indicators. This study presented a research model that applies Monte Carlo simulation to set expected performance targets that can be achieved through CODIL based on objective evidence. Among the survey contents conducted from 2015 to 2023, the statistical characteristics of user satisfaction regarding the frequency of use of construction technology information provided by CODIL were designated as input variables. Future expected targets and confidence intervals from 2024 to 2026 were designated as outcome variables. The expected target value was measured by generating 5 simulation alternatives and 1,000 random numbers for each alternative. Next, the measured expected goals were interpreted and compared with the results of time series regression analysis measured in previous studies. Although, as in previous studies, the expected target value could not be predicted based on time series regression analysis that considers the correlation between years. However, compared to previous studies, this study can be considered a more accurate analysis result because it predicted the expected target value based on 5,000 input variables.

• Journal of Cardiovascular Imaging
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• v.30 no.3
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• pp.153-168
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• 2022

Recent studies have shown that sodium/glucose cotransporter 2 (SGLT2) inhibitors might exert favourable changes on cardiac parameters as observed on cardiovascular imaging. We conducted a systematic review and meta-analysis to determine the effects of SGLT2 inhibitors on cardiac imaging parameters. Four electronic databases (PubMed, Embase, Cochrane, Scopus) were searched for studies in which the effects of SGLT2 inhibitors on cardiac imaging parameters were examined. Studies in which a population was administered SGLT2 inhibitors and analysed by echocardiography and/or cardiac magnetic resonance (CMR) imaging were included. Random-effects pair-wise meta-analysis models were utilized to summarize the studies. A total of 11 randomized controlled trials was included with a combined cohort of 910 patients. Comparing patients receiving SGLT2 inhibitors with subjects receiving placebo, the mean change in CMR-measured left ventricular mass (LVM) was -3.87 g (95% confidence interval [CI], -7.77 to 0.04), that in left ventricular end-systolic volume (LVESV) was -5.96 mL (95% CI, -10.52 to -1.41) for combined LVESV outcomes, that in left atrial volume index (LAVi) was -1.78 mL/m² (95% CI, -3.01 to -0.55) for combined LAVi outcomes, and that in echocardiography-measured E/e' was -0.73 (95% CI, -1.43 to -0.03). Between-group differences were not observed in LVM and LVESV after indexation. The only between-group difference that persisted was for LAVi. Treatment with SGLT2 inhibitors resulted in reduction in LAVi and E/e' on imaging, indicating they might have an effect on outcomes associated with LV diastolic function.

• Journal of Korean Home Economics Education Association
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• v.35 no.3
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• pp.97-116
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• 2023

This study conducted a meta-analysis on the effectiveness of education for sustainable development (ESD) programs within home economics classes. Articles spanning from 2000 to April 2023 were sourced from the Korean Citation Index (KCI) using search terms such as 'environment', 'sustainable', 'ESD', 'green', 'ecology', and 'home economics' in conjunction with 'development', 'application', and 'effectiveness'. Out of the gathered articles, 41 were chosen for analysis. Using a random effects model, the overall effect size was measured at 0.51 (SE=.08), suggesting that ESD programs significantly enhance student achievement in home economics. Further analysis of the 62 effect sizes, categorized by research design, ESD area (society, environment, economy), content area, school level, and school location, revealed that the research design, content area, and school location functioned as moderating variables. The findings of this meta-analysis underscore the efficacy of ESD in home economics education. Additionally, this study paves the way for future research, highlighting the importance of integrating economic perspectives in ESD, such as sustainable production and consumption, corporate sustainability, and market economy within home economics classes.

• Journal of Music and Human Behavior
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• v.21 no.2
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• pp.51-75
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• 2024

This case study aimed to develop a therapeutic rap protocol based on narrative components for improving discourse skills of adolescents with mild intellectual disability (ID) and to explore its applicability. The protocol matched narrative elements (background, initiating event, internal response, attempts, and reaction) with rap components (verse, hook, and interjections), guiding participants to narrate their experiences in a connected discourse form. The protocol was also structured to gradually increase in difficulty, considering the developmental levels of adolescents with ID and it included steps for understanding discourse structures, applying narrative elements to content creation, and expanding narratives. Post-intervention analysis of the stories and rap lyrics created by participants to express their real-life experiences showed that participants increased the length of their stories and rap compositions, with notable improvements in rhythmicity and the inclusion of narrative elements. These findings suggest that, instead of constructing rap from random utterances, providing a structured framework reflecting discourse structure enhanced participants' understanding of event context and logical connections. Furthermore, the various elements and rhythmic features of rap can strengthen motivation and organization in discourse. This study highlights the therapeutic potential of rap in addressing the unique developmental needs of adolescents with mild ID, thereby diversifying and systematizing music therapy interventions for this population.

• Economic and Environmental Geology
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• v.57 no.4
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• pp.353-362
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• 2024

This study examined the spectral characteristics of sediments according to moisture content using an unmanned aerial vehicle (UAV)-based hyperspectral sensor and evaluated the efficiency of moisture content detection at different flight altitudes. For this purpose, hyperspectral images in the 400-1000nm wavelength range were acquired and analyzed at altitudes of 40m and 80m for sediment samples with various moisture contents. The reflectance of the sediments generally showed a decreasing trend as the moisture content increased. Correlation analysis between moisture content and reflectance showed a strong negative correlation (r < -0.8) across the entire 400-900nm range. The moisture content detection model constructed using the Random Forest technique showed detection accuracies of RMSE 2.6%, R² 0.92 at 40m altitude and RMSE 2.2%, R² 0.95 at 80m altitude, confirming that the difference in accuracy between altitudes was minimal. Variable importance analysis revealed that the 600-700nm band played a crucial role in moisture content detection. This study is expected to be utilized in efficient sediment moisture management and natural disaster prediction in the field of environmental monitoring in the future.

• Science of Emotion and Sensibility
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• v.27 no.2
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• pp.81-90
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• 2024

In this study, we aimed to determine the effect on cerebral blood vessels of various stimulus intensities using transcutaneous electrical nerve stimulation (TENS). In particular, we wanted to monitor changes in blood flow and structural changes in the blood vessels in the common carotid artery (CCA) through low-intensity electrical stimulation that can cause non-perceptual sensory stimulation. Twenty-four healthy adults in their 20s participated in this study. Three stimulus intensities (below the sensory threshold, at the sensory threshold, and above the sensory threshold) were applied in random order. Changes in blood flow velocity according to the intensity of TENS stimulus were measured by placing the Doppler ultrasound transducer 1 cm below the CCA bifurcation, and the vascular structure was measured using B-mode imaging. C-mode Doppler and B-mode images were acquired before, during, and after the intervention for each stimulus, and changes in blood pressure were measured in each session. As a result, it was confirmed that peak systolic velocity (PSV) decreased significantly after the intervention in non-perceived sensory stimulation below the threshold, compared to other thresholds (p = .008). In particular, the PSV decreased by 3.04% on average compared to before stimulation (p = .011). However, there was no significant change in the CCA diameters before and after stimulation at all intensities. It was found that short-term, non-perceptual sensory stimulation was effective in reducing the blood flow rate without causing significant changes in either the blood vessel diameter or blood pressure. This change appears to be caused by a decrease in blood flow due to the effect of subtle vasodilation at non-perceptual sensory stimulation, and at stimulation intensity higher than that, the sympathetic nerves in the blood vessels are stimulated excessively and the blood vessels constrict. Therefore, this study can be rated as an important attempt to control blood flow through stimulation without such a psychological burden and sensory discomfort in the carotid area.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.236-244
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• 2024

A representative problem in domestic chestnut industry is the high loss of flesh due to excessive knife peeling in order to increase the peeling rate, resulting in a decrease in production efficiency. In this study, a prediction model for weight loss rate of chestnut by stage of knife peeling process was developed as undergarment study to optimize conditions of the machine. 51 control conditions of the two-stage blade peeler used in the experiment were derived and repeated three times to obtain a total of 153 data. Machine learning(ML) models including artificial neural network (ANN) and random forest (RF) were implemented to predict the weight loss rate by chestnut peel stage (after 1st peeling, 2nd peeling, and after final discharge). The performance of the models were evaluated by calculating the values of coefficient of determination (R), normalized root mean square error (nRMSE), and mean absolute error (MAE). After all peeling stages, RF model have better prediction accuracy with higher R values and low prediction error with lower nRMSE and MAE values, compared to ANN model. The final selected RF prediction model showed excellent performance with insignificant error between the experimental and predicted values. As a result, the proposed model can be useful to set optimum condition of knife peeling for the purpose of minimizing the weight loss of domestic chestnut flesh with maximizing peeling rate.