• Journal of Microbiology and Biotechnology
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• v.32 no.6
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• pp.699-708
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• 2022

Antibiotic exposure during pregnancy have an adversely effects on offspring behavior and development. However, its mechanism is still poorly understood. To uncover this, we added ceftriaxone sodium to the drinking water of rats during pregnancy and conducted three-chamber sociability test, open-field test, and Morris water maze test in 3- and 6-week-old offspring. The antibiotic group offspring showed lower sociability and spatial learning and memory than control. To determine the role of the gut microbiota and their metabolites in the changes in offspring behavior, fecal samples of 6-week-old offspring rats were sequenced. The composition of dominant gut microbial taxa differed between the control and antibiotic groups. KEGG pathway analysis showed that S24-7 exerted its effects through the metabolic pathways including mineral absorption, protein digestion and absorption, Valine, leucine, and isoleucine biosynthesis. Correlation analysis showed that S24-7 abundance was negatively correlated with the level of VEGF, and metabolites associated with S24-7-including 3-aminobutanoic acid, dacarbazine, L-leucine, 3-ketosphinganine, 1-methylnicotinamide, and N-acetyl-L-glutamate-were also significantly correlated with VEGF levels. The findings suggest that antibiotic exposure during pregnancy, specifically ceftriaxone sodium, will adversely affects the behavior of offspring rats due to the imbalance of gut microbiota, especially S24-7, via VEGF and various metabolic pathways.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.443-450
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• 2022

The method of studying 3D-technologies abroad and in Ukraine is considered. The analysis of educational resources and experience of use of the equipment in branch is carried out. The didactic principles of the educational process for 3D-printing specialists are determined. The use of FDM technology and the ability to minimize the occurrence of defects in the future have been studied. An analysis of the international experience of the educational process of relevant specialists in the field. The content of training for 3D printing specialists has been developed. The experience of using 3D-technologies is described and the list of recommendations for elimination of defects during production of products by means of additive technologies is made. The recommendations will be useful not only for beginners, but also for experienced professionals in additive technologies. The need to study such experience is the main condition for the development of enterprises in Ukraine that plan to automate their own production. A 3D printing engineer must know the basics of economics and marketing, because his responsibilities include optimizing workflows to reduce the cost and speed up printing. Therefore, the knowledge gained from practical experience presented and in building for learning 3D printing engineers by the authors will be important.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.425-437
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• 2022

In this study, the role and function of Edutech, as well as the application and expectations in the field of future vocational competency development, were gathered to define Edutech as a comprehensive working definition. Based on this redefinition of Edutech, this study analyzes Edutech technology trends and examines the level of actual technology applied to education and vocational training based on written interviews with experts, and finds out significant implications from the point of view of vocational training. Finally we propose an Edutech-based Vocational Education and Training Model.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.379-384
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• 2022

In a wireless sensor network, a large number of sensor nodes are deployed in an environment where direct access is difficult. It is difficult to supply power, such as replacing the battery or recharging it. It is very important to use the energy with the sensor node. Therefore, an important consideration to increase the lifetime of the network is to minimize the energy consumption of each sensor node. If the energy of the wireless sensor node is exhausted and discharged, it cannot function as a sensor node. Therefore, it is a method proposed in various protocols to minimize the energy consumption of nodes and maintain the network for a long time. We consider the center point and residual energy of the cluster, and the plot point and K-means (WSN suggests optimal clustering). We want to evaluate the performance of the KOCED protocol. We compare protocols to which the K-means algorithm, one of the latest machine learning methods, is applied, and present performance evaluation factors.

• Journal of Korean society of Dental Hygiene
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• v.21 no.6
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• pp.813-820
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• 2021

Objectives: This study was conducted to verify the effectiveness of the VR-applied head and neck anatomy class and to be used as basic data for the development of a teaching method using VR in the basic dental hygiene field. Methods: A convenience sample was extracted from 128 students and graduates who completed the head and neck anatomy class at the department of dental hygiene at a university in Gwangju. From June 1 to July 31, 2021, an online survey was conducted on class attitude and satisfaction, and statistical analysis was performed using frequency analysis and independent sample t-test. Results: Class attitude (3.79), interest (3.64), attention (3.88), learning motivation (3.80), and achievement motivation (3.84) were all high in the head and neck anatomy VR application group (p<0.01). Satisfaction (3.99), relevance of class content (4.06) and class achievement (3.96) were high in the head and neck anatomy VR application group (p<0.01). The suitability of class attitude (3.65) and class content (sub-item of class satisfaction) (4.13) was high in the group with the 4th industrial revolution education experience (p<0.05). Conclusions: The effect of VR application in the head and neck anatomy class was confirmed to increase students' class attitude and satisfaction. In the basic dental hygiene curriculum, it will be necessary to develop and utilize teaching methods related to the 4th industrial revolution and VR application classes.

• Journal of Engineering Education Research
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• v.25 no.5
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• pp.85-93
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• 2022

Capstone Design, a project-based learning technique, is the most important curriculum that clarifying major knowledge and cultivating the ability to apply through the process of solving problems in the industrial field centered on the student project team. Accordingly, various and extensive studies are being conducted for the successful implementation of capstone design courses. Unlike previous studies, this study aimed to quantitatively analyze the opinions that recorded the experiences and feelings of students who performed capstone design, and used text mining methodologies such as frequency analysis, correlation analysis, topic modeling, and sentiment analysis. As a result of examining the overall opinions of the latter period through frequency analysis and correlation analysis, there was a difference between the languages used by the students in the opinions according to gender and project results. Through topic modeling analysis, 'topic selection' and 'the relationship between team members' showed an increase in occupancy or high occupancy, and topics such as 'presentation', 'leadership', and 'feeling what they felt' showed a tendency to decreasing occupancy. Lastly, sentiment analysis has found that female students showed more neutral emotions than male students, and the passed group showed more negative emotions than the non-passed group and less neutral emotions. Based on these findings, students' practical recognition of the curriculum was considered and implications for the improvement of capstone design were presented.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.77-87
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• 2023

Currently, due to Covid-19, non-face-to-face activities are underway in various fields, and non-face-to-face education is also necessary in the education field. In this paper, we develop and utilize a metaverse-based realistic education platform that combines the latest realistic 3D technology and XR interactive technology to enhance students' understanding of the latest technology and strengthen their educational capabilities. To this end, we understand the main technologies of metaverse in terms of education, investigate contents and application cases of education using metaverse, and compare them with the proposed realistic educational platform. In the future, non-face-to-face education is expected to account for an important portion, and more effective learning is expected through the metaverse-based realistic educational platform developed in this paper when instructor lectures the MZ generation in a virtual world called metaverse.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.365-372
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• 2022

The accurate object recognition is important for the precise and accurate manipulation. To enhance the recognition performance, we can use various types of sensors. In general, acquired data from sensors have a high sampling rate. So, in the past, the RNN-based model is commonly used to handle and analyze the time-series sensor data. However, the RNN-based model has limitations of excessive parameters. CNN-based model also can be used to analyze time-series input data. However, CNN-based model also has limitations of the small receptive field in early layers. For this reason, when we use a CNN-based model, model architecture should be deeper and heavier to extract useful global features. Thus, traditional methods like RN N -based and CN N -based model needs huge amount of learning parameters. Recently studied result shows that Fast Fourier Convolution (FFC) can overcome the limitations of traditional methods. This operator can extract global features from the first hidden layer, so it can be effectively used for feature extracting of sensor data that have a high sampling rate. In this paper, we propose the algorithm to recognize objects using tactile sensor data and the FFC model. The data was acquired from 11 types of objects to verify our posed model. We collected pressure, current, position data when the gripper grasps the objects by random force. As a result, the accuracy is enhanced from 84.66% to 91.43% when we use the proposed FFC-based model instead of the traditional model.

• Human Ecology Research
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• v.60 no.1
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• pp.1-20
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• 2022

This paper presents a social network analysis of changes in Home Economics education content loaded on YouTube before and after the outbreak of COVID-19. From January 1, 2008 to June 30, 2021, a basic analysis was conducted of 761 Home Economics education videos loaded on YouTube, using NetMiner 4.3 to analyze important keywords and the centrality of video titles and full texts. Before COVID-19, there were 164 Home Economics education videos posted on YouTube, increasing significantly to 597 following the emergence of the pandemic. In both periods, there was more middle school content than high school content. The content in the child-family field was the most, and the main keywords were youth and family. Before COVID-19, a performance evaluation indicated that the proportion of student content was high, whereas after the outbreak of the disease, teacher content increased significantly due to the effect of distance learning. However, compared with video use, the self-expression and participation of users were lower in both periods. The centrality analysis indicated that in the title, 'family' exhibited a high degree of both centrality and eigenvector centrality over the entire period. Degree centrality of the video title was found to be high in the order of class, online, family, management, etc. after the outbreak of COVID-19, and the connection of keywords was strong overall. Eigenvector centrality indicated that career, search, life, and design were influential keywords before COVID-19, while class, youth, online, and development were influential keywords after COVID-19.

• Advances in nano research
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• v.12 no.6
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• pp.549-566
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• 2022

Mining of ore minerals (sfalerite, cinnabar, and chalcopyrite) from the old mine has led in significant environmental effects as contamination of soils and plants and acidification of water. Also, nanoparticles (NP) have obtained global importance because of their widespread usage in daily life, unique properties, and rapid development in the field of nanotechnology. Regarding their usage in various fields, it is suggested that soil is the final environmental sink for NPs. Nanoparticles with excessive reactivity and deliverability may be carried out as amendments to enhance soil quality, mitigate soil contaminations, make certain secure land-software of the traditional change substances and enhance soil erosion control. Meanwhile, there's no record on the usage of Nano superior substances for mine soil reclamation. In this study, five soil specimens have been tested at 4 sites inside the region of mine (<100 m) to study zeolites, and iron sulfide nanoparticles. Also, through using Artificial Neural Network (ANN) and Extreme Learning Machine (ELM), this study has tried to appropriately estimate the mechanical properties of soil under the effect of these Nano particles. Considering the RMSE and R2 values, Zeolite Nano materials could enhance the mine soil fine through increasing the clay-silt fractions, increasing the water holding capacity, removing toxins and improving nutrient levels. Also, adding iron sulfide minerals to the soils would possibly exacerbate the soil acidity problems at a mining site.