• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.367-376
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• 2022

In this study, the user experience was analyzed from the learner's point of view, focusing on the metaverse platform 'Spatial'. SUS(System Usability Scale) was used to evaluate the usability of the metaverse platform 'Spatial' in a college class, and the Magnitude estimation technique was used to evaluate the immersion and satisfaction with the class. In addition, a questionnaire survey was used to collect user experience opinions on the use of 'Spatial' as a teaching tool. Looking at the usability evaluation results of the 'Spatial' system, the students evaluated the usability, immersion, and satisfaction quite positively. Looking at the user experience of metaverse platform 'Spatial', it was found that students highly valued Metaverse as an educational tool that can provide a place for many people to gather and communicate even in a non-face-to-face space. Compared to other online platforms, metaverse has advantages in ease of use, interaction, immersion, and interest. In particular, in addition to keyboard, touch, and display, interaction using the five senses such as voice, motion, and gaze was recognized as a great advantage. On the other hand, it was found that high openness, freedom, and interest factors can both promote learning and inhibit learning. Nevertheless, it is judged that the metaverse platform 'Spatial' can be effectively applied in college classes because it enables various interactions between instructor and learner or between learner and learner.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.255-260
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• 2022

This study aimed to develop a service model that uses a deep learning algorithm for detecting diseases and pests in strawberries through image data. In addition, the pest detection performance of deep learning models was further improved by proposing segmented image data sets specialized in disease and pest symptoms. The CNN-based YOLO deep learning model was selected to enhance the existing R-CNN-based model's slow learning speed and inference speed. A general image data set and a proposed segmented image dataset was prepared to train the pest and disease detection model. When the deep learning model was trained with the general training data set, the pest detection rate was 81.35%, and the pest detection reliability was 73.35%. On the other hand, when the deep learning model was trained with the segmented image dataset, the pest detection rate increased to 91.93%, and detection reliability was increased to 83.41%. This study concludes with the possibility of improving the performance of the deep learning model by using a segmented image dataset instead of a general image dataset.

• Journal of Family Resource Management and Policy Review
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• v.26 no.4
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• pp.25-38
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• 2022

This study aims to analyze everyday caring activities of young working single-person households. To collect the data, we interviewed 10 working single-person households. The topics are composed of 3 parts: 1) the everyday life of single-person households; 2) caring activities and household labor; 3) the experience of caring activities. The results are as follows : In comparison with families living together, single-person households carry out everyday caring activities alone, so they found a new meaning in caring activities and household labor. In particular, they were fully aware of the importance of everyday caring activities even though they sometimes felt the caring activities were uncomfortable. On the other hand, they improved their technique and ability for caring activities, and they felt satisfied with the caring activities. We found the meaning of everyday caring activities to be an essential condition for the independence of single-person households.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.315-324
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• 2022

The experimental data obtained in a wave flume were analyzed using machine learning techniques to establish a model that predicts the input wave height of the wavemaker based on the waves that have experienced wave shoaling and to verify the performance of the established model. For this purpose, artificial neural network (NN), the most representative machine learning technique, and Gaussian process regression (GPR), one of the non-parametric regression analysis methods, were applied respectively. Then, the predictive performance of the two models was compared. The analysis was performed independently for the case of using all the data at once and for the case by classifying the data with a criterion related to the occurrence of wave breaking. When the data were not classified, the error between the input wave height at the wavemaker and the measured value was relatively large for both the NN and GPR models. On the other hand, if the data were divided into non-breaking and breaking conditions, the accuracy of predicting the input wave height was greatly improved. Among the two models, the overall performance of the GPR model was better than that of the NN model.

• Nuclear Engineering and Technology
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• v.26 no.3
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• pp.401-410
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• 1994

Validation study of two radionuclide migration models for single fracture developed in geologic medium the hydrodynamic dispersion diffusion model(HDDM) and the channeling dispersion diffusion model(CDDM), was studied by migration experiment of tracers through an artificial granite fracture on the labolatory scale. The tracers used were Uranine and Sodium lignosulfonate know as nonsorbing material. The flow rate ranged 0.4 to 1.5 cc/min. Related parameters for the models were estimated by optimization technique. Theoretical breakthrough curves with experimental data were compared. In the experiment, it was deduced that the surface sorption for both tracers did not play an important role while the diffusion of Uranine into the rock matrix turned out to be an important mass transfer mechanism. The parameter characterizing the rock matrix diffusion of each model agreed well The simulated result showed that the amount of flow rate could not tell the CDDM from the HDDM quantitatively. On the other hand, the variation of fracture length gave influence on the two models in a different degree. The dispersivity of breakthrough curve of the CDDM was more amplified than that of the CDDM when the fracture length was increased. A good agreement between the models and experimental data gave a confirmation that both models were very useful in predicting the migration system through a single fracture.

• Conservation Science in Museum
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• v.29
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• pp.153-162
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• 2023

Clay figure of Baekje, produced by forming and molding various shapes using clay, are mainly excavated from temple sites and provide essential information for studying the Buddhist art of Baekje. Research on clay figures of Baekje primarily focuses on the characteristics of Baekje-era temples in which such figures are excavated, as well as the role and production techniques of clay figures, by comparing regional and morphological characteristics. In particular, research on the manufacturing method of clay figures is mainly carried out by visual observation, whereas precise scientific analysis is required to understand production techniques and characteristics of raw materials in greater detail. In this study, to confirm such production techniques and material characteristics, computed tomography (CT) scans were conducted on the Clay Bodhisattva excavated from the Neungsan-ri Temple site in Buyeo. As a result, it was found that the Clay Bodhisattva was made using a cylindrical core of fine clay, tied together with several thin branches or reeds with straws. The clay used in the figure bore traces indicating the presence of herbaceous plants, which increase adhesion between clay and prevent cracks in the contraction process. On the other hand, the density of the fine clay differs on the inside and outside of the clay figure. Based on this, it is presumed that the clay was applied around the cylindrical core to shape the Clay Bodhisattva. The clay was reapplied on top of the figure to express the detailed shape and pattern.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.610-620
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• 2022

An acoustic vector sensor can simultaneously receive vector quantities, such as particle velocity and acceleration, as well as acoustic pressure at one location, and thus it can be used as a single input multiple output receiver in underwater acoustic communication systems. On the other hand, vector signals received by a single vector sensor have different channel characteristics due to the azimuth angle between the source and receiver and the difference in propagation angle of multipath in each component, producing different communication performances. In this paper, we propose a channel parameter-based weighting method to improve the performance of an acoustic communication system using a single vector sensor. To verify the proposed method, we used communication data collected from the experiment conducted during the KOREX-17 (Korea Reverberation Experiment). For communication demodulation, block-based time reversal technique which is robust against time-varying channels were utilized. Finally, the communication results showed that the effectiveness of the channel parameter-based weighting method for the underwater communication system using a single vector sensor was verified.

• Journal of Korea Trade
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• v.26 no.8
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• pp.21-36
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• 2022

Purpose - Carbon emission standards are based on the "production-based carbon emissions" generated by the production of goods in the relevant country which were the existing measurement methods. However, can such carbon emissions measurement standards be established international? For example, some of the goods produced in developing countries are produced for the demand of developed countries. The method of measuring carbon emission based on the final demand of a certain country is called "consumption-based carbon emissions." This study compares productionand consumption-based CO₂ emissions according to economic growth in ninety-three countries categorized by income level. Design/methodology - Our empirical model considers the difference between production- and consumption-based CO₂ emissions according to economic growth. Also, our model investigated whether the EKC hypothesis in most of the previous studies that had been based on production-based emissions was also established in the consumption-based emission model. Considering the continuous characteristics of CO₂, we utilized the generalized method of moments (GMM), specifically a system GMM econometric technique because CO₂ in the previous period can affect CO₂ in the present period. Findings - Our main findings can be summarized as follows: The results show that for the consumption-based CO₂ emissions model, CO₂ continuously increases as economic growth increases in the upper-middle income countries. The inverted U-shaped result was found in the case of the production-based model. However, in the lower-income countries, an inverted-U shape in which CO₂ emissions decrease at some point as the economy grows in the production-based model does not appear. On the other hand, in the consumption-based model, an inverted U-shaped result was obtained when estimating with system-GMM. Additionally, the proportion of manufacturing, energy imports, and energy consumption had an effect on both the production- and the consumption-based model regardless of the group's CO₂ emissions. On the basis of such assessments, policymakers need to consider not only production- but also consumption-based options. Originality/value - Previous studies have mainly focused on production-based CO₂ emissions, with most of them revolving around economic growth or the effect of various social and economic factors on CO₂ emissions. However, this study considers the relationship with economic growth using consumption-based emissions as a dependent variable by classifying ninety-three countries by income level.

• Conservation Science in Museum
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• v.30
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• pp.101-126
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• 2023

Bogjeon chongtong, a military firearm from the Joseon Dynasty, remains undocumented with extant ones only discovered relatively recently. This study examined the structural and material characteristics of the bogjeon chongtong by comparing the specifications, shapes, inscriptions, and components of 12 pieces of bogjeon chongtong, which have not been described in detail to date. Bogjeon chongtong has certain set properties in terms of its specifications and shapes. This study also estimated the number of projectiles fired at once by comparing the specifications and records. In terms of design, the handle slot has an outline engraved in relief along with the name of the artifact. The inscribed outline is the most notable feature of the bogjeon chongtong that is not seen in other chongtong artifacts. Therefore, this study analyzed the inscription techniques used in the production process. The main ingredients of bogjeon chongtong are copper and tin, with a tin content of 6wt%. It was confirmed that this is highly similar to the average composition of bronze gunpowder weapons of the Joseon Dynasty as identified in prior research, and that it is also similar to the bronze gunmetal of medieval Europe. These conclusions were drawn in consideration of the material properties required for gunpowder weapons, which allows the inference that the materials used for firearms were selected by prioritizing functionality based on the alloy ratio.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.167-175
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• 2024

Due to the Fourth Industrial Revolution, ICT(Information and Communication Technology) industry is becoming more important and sophisticated than ever. In B2B based ICT industry demand forecasting by analyzing the previous customer data is so important. RFM, one of customer relationship management models is a marketing technique that evaluates Recency, Frequency and Monetary value to predict customers behavior. RFM model has been studied focusing on the B2C based industry. On the other hand there is a lack of research on B2B based technology industry. Therefore this study applied it to B2B based high technology industry and considered T(technology collaboration) value, which are identified as important factors in the technology industry. To present an improved model for market performance in B2B technology industry, an empirical study was conducted on comparing the accuracy of the traditional RFM model and the improved RFM-T model. The objective of this study is to contribute to market performance by presenting an improved model in B2B based high technology industry.