• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.263-278
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• 2022

With the recent advent of IoT technology, automatic pet feeders are being distributed so that owners can feed their companion animals while they are out. However, due to behaviors of pets, the method of measuring weight, which is important in automatic feeding, can be easily damaged and broken when using the scale. The 3D camera method has disadvantages due to its cost, and the 2D camera method has relatively poor accuracy when compared to 3D camera method. Hence, the purpose of this study is to propose a deep learning approach that can accurately estimate weight while simply using a 2D camera. For this, various convolutional neural networks were used, and among them, the ResNet101-based model showed the best performance: an average absolute error of 3.06 grams and an average absolute ratio error of 3.40%, which could be used commercially in terms of technical and financial viability. The result of this study can be useful for the practitioners to predict the weight of a standardized object such as feed only through an easy 2D image.

• Phonetics and Speech Sciences
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• v.14 no.2
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• pp.67-76
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• 2022

This study aimed to examine Korean listeners' mode of perceiving sound duration as prolongation, whether dichotomous or continuous. Thirty-five Korean participants (17 men and 18 women) listened to the Korean segment /s/, which was lengthened by 0-980ms in 20-ms increments. Then, the participants were asked to rate each version of the sound based on a rating of one to 100 (the closer to 100, the more disfluent). To examine whether listeners perceived durational variations for the fricative segment dichotomously or continuously, a curve was estimated using the best-fitting regression model for the observed data with the highest adjusted R-squared value. The mode of perceiving durational variations for the segment was continuous (or gradient) rather than discontinuous (or dichotomous). No gender difference was found in the mode of perceiving prolongation. However, there was a significant gender difference in that men rated the most disfluent sounds higher than women. The findings of this study were further discussed in relation to the existing literature, and clinical implications for the assessment of stuttering were presented.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.3
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• pp.29-46
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• 2022

COVID-19 has radically changed the behavior of members of society for exchange. In particular, the strong contagiousness of the virus is increasing networking on online platforms while reducing people's networking in the real world. Recently, the metaverse, which strengthened the presence based on 3D technology, is attracting attention from members of society such as individuals and companies. We present a method to improve metaverse utilization from the perspective of organizations and employees who have introduced metaverse for work. In other words, we check the effect of metaverse social function and telepresence on the employee's intention to offer support by improving the trust of the metaverse participants. We obtained samples through questionnaires targeting employees of organizations that introduced metaverse to their work, and verified the research hypothesis by applying the structural equation model. As a result, social interactivity, reciprocal favor, and telepresence of metaverse partially affected metaverse trust (platform, peer, organization), and metaverse trust increased the intention to offer support. Our study suggests a strategic direction to improve the metaverse utilization and exchange level of employees of organizations who want to use the metaverse for business.

• Land and Housing Review
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• v.13 no.1
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• pp.23-38
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• 2022

As city tourism has recently been evaluated as a major indicator of urban competitiveness, strengthening the role of cities as tourist destinations has received more attention. However, industrialization and urbanization of many cities lead to population decline, extinction of traditional industries, and deterioration of living environments, weakening urban functions and competitiveness. Thus, it is essential for declining cities to build a measure to restore urban competitiveness by enhancing urban functions. Accordingly, this study focused on socio-cultural urban regeneration by exploring physical spaces for tourism destinations in declining cities. Different from general tourist destinations, tourism destinations of urban regeneration have a temporal perspective covering the past, present, and future. How does the temporal perspective of urban regeneration tourist destinations affect tourists' satisfaction and behavioral intention? In order to address these questions, this study conducts an empirical analysis based on structural equation modeling (SEM) using the sample of tourists who have visited urban regeneration tourism destinations. With SEM, this paper investigates structural relationships across variables by testing the hypothesis established in the proposed research model. The results show that precious memories of the past are the most important factor for tourists to visit urban regeneration tourist destinations. The empirical findings of this study will contribute to the research areas of urban tourism, urban regeneration tourism, and urban regeneration tourism destinations. In addition, this study can provide practical implications to develop socio-cultural contents of urban regeneration areas as tourism resources to establish plans for urban regeneration projects and achieve sustainable development strategies.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.481-494
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• 2022

This study proposed a evaluation of the monthly vulnerable period for groundwater level management in the Miho stream watershed and a technique for evaluating the vulnerable period for future groundwater level management using LSTM. Observation data from groundwater level and precipitation observation stations in the Miho stream watershed were collected, LSTM was constructed, predicted values for precipitation and groundwater levels from 2020 to 2022 were calculated, and future groundwater management was evaluated when vulnerable. In order to evaluate the vulnerable period of groundwater level management, the correlation between groundwater level and precipitation was considered, and weights were calculated to consider changes caused by climate change. As a result of the evaluation, the Miho stream watershed showed high vulnerability to underground water management in February, March, and June, and especially near the Cheonan Susin observation well, the vulnerability index for groundwater level management is expected to deteriorate in the future. The results of this study are expected to contribute to the evaluation of the vulnerable period of groundwater level management and the derivation of preemptive countermeasures to the problem of groundwater resources in the basin by presenting future prediction techniques using LSTM.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.168-178
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• 2022

In this study, the resistance test, the vertical static angle of the attack test and VPMM test will be conducted to estimate the maneuverability of underwater vehicles with ahead propeller. The vertical static test will be conducted within the range of -40deg to 40deg, to investigate the cross-flow drag at high incidence angles. The tests will be conducted by dividing the propeller rotation into a case in which the propeller rotates at a specific rpm, and a case in which the propeller rotates naturally, according to the towing speed. Hydrodynamic coefficients of vertical direction will be estimated by the captive model tests. Additionally, the vertical dynamic stability index based on estimated hydrodynamic coefficients will be calculated and the impact of the propeller revolution state on the index will be investigated. The results are expected to be used as reference test data for underwater vehicles with ahead propeller.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.27-35
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• 2022

The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.

• Journal of Environmental Impact Assessment
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• v.31 no.3
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• pp.184-199
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• 2022

Freshwater soundness can be broadly divided into the health of river ecosystems and social services for human water use, that is, water welfare. In this study the ecological soundness and water welfare index of rivers were calculated, and the freshwater comprehensive soundness was analyzed using the quadrant model for 14 basins in the Geum River basin. As for the ecological soundness of the river, the area upstream of the dam (based on Daecheong Dam) was evaluated as 'good', and the area downstream of the dam was evaluated as 'bad'. On the other hand as for water welfare, the area downstream of the dam with a large population was in a relatively 'good' condition, and the area upstream of the dam had a relatively 'poor' level of water welfare. In terms of freshwater comprehensive soundness, it was found that the basins of Mujunamdaecheon, Bocheongcheon and Daecheongdam showed good ecological soundness and water welfare, and the Geumganggongju, Nonsancheon and Geumganhagueon basins were all poor. The Gapcheon basin showed good results in 2014 due to continuous investment and systematic management. Therefore, it is necessary to find ways to utilize it for other watersheds through benchmarking.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.