• Journal of Life Science
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• v.33 no.6
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• pp.490-497
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• 2023

Pregnant women may need to take medications to treat preexisting diseases or diseases that develop during pregnancy. However, some drugs may be fetotoxic and lead to, for example, teratogenicity and growth retardation. Predicting the fetotoxicity of drugs is thus important for the health of the mother and fetus. The fetotoxicity of many drugs has not been established because various challenges hinder the ability of researchers to determine their fetotoxicity. The need exists for in silico-based fetotoxicity assessment models, as they can modernize the testing paradigm, improve predictability, and reduce the use of animals and the costs of fetotoxicity testing. In this study, we collected data on the fetotoxicity of drugs and constructed fetotoxicity prediction models based on various machine learning algorithms. We optimized the models for more precise predictions by tuning the hyperparameters. We then performed quantitative performance evaluations. The results indicated that the constructed machine learning-based models had high performance (AUROC >0.85, AUPR >0.9) in fetotoxicity prediction. We also analyzed the feature importance of our model's predictions, which could be leveraged to identify the specific features of drugs that are strongly associated with fetotoxicity. The proposed model can be used to prescreen drugs and drug candidates at a lower cost and in less time. It provides a predictive score for fetotoxicity risk, which may be beneficial in the design of studies on fetotoxicity in human pregnancy.

• Convergence Security Journal
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• v.22 no.2
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• pp.131-141
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• 2022

Future battlefield domains are expanding to ground, sea, air, space, and cyber, so future military operations are expected to be carried out simultaneously and complexly in various battlefield domains. In addition, the application of convergence technologies that create innovations in all fields of economy, society, and defense, such as artificial intelligence, IoT, and big data, is being promoted. However, since the current Korean military C4I system manages warfighting function DBs in one DB server, the efficiency of combat performance is reduced utilization and distribution speed of data and operation response time. To solve this problem, research is needed on how to apply the 4th industrial revolution technologies such as AI, IoT, 5G, big data, and cloud to the Korean military C4I system, but research on this is insufficient. Therefore, this paper analyzes the problems of the current Korean military C4I system and proposes to apply the 4th industrial revolution technology in terms of operational mission, network and data link, computing environment, cyber operation, interoperability and interlocking capabilities.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.825-834
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• 2023

The demands of people who purchase fashion products on Internet shopping are gradually increasing, and attempts are being made to provide user-friendly images with 3D contents and web 3D software instead of pictures and videos of products provided. As a reason for this issue, which has emerged as the most important aspect in the fashion web shopping industry, complaints that the product is different when the product is received and the image at the time of purchase has been heightened. As a way to solve this problem, various image processing technologies have been introduced, but there is a limit to the quality of 2D images. In this study, we proposed an automatic conversion technology that converts 2D images into 3D and grafts them to web 3D technology that allows customers to identify products in various locations and reduces the cost and calculation time required for conversion. We developed a system that shoots a mannequin by placing it on a rotating turntable using only 8 cameras. In order to extract only the clothing part from the image taken by this system, markers are removed using U-net, and an algorithm that extracts only the clothing area by identifying the color feature information of the background area and mannequin area is proposed. Using this algorithm, the time taken to extract only the clothes area after taking an image is 2.25 seconds per image, and it takes a total of 144 seconds (2 minutes and 4 seconds) when taking 64 images of one piece of clothing. It can extract 3D objects with very good performance compared to the system.

• Resources Recycling
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• v.32 no.3
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• pp.3-8
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• 2023

This study discussed production, demand, and future prospects of rubidium, which is an alkali group metal that is highly reactive to various media and requires carefulness in handling, but no significant environmental hazard of rubidium has been reported yet. Rubidium is used in various fields such as optoelectronic equipment, biomedical, and chemical industries. Because of difficulty in production as well as limited demand, the transaction price of rubidium is relatively high, but its detail information such as market status and potential growth is uncertain. However, if the mass production of versatile ultra-high-performance equipment such as quantum computers and the necessity of rubidium use in the equipment are confirmed, there is a possibility that the rubidium market will expand in the future. Rubidium is often found together with lithium, beryllium, and cesium, and may be present in granite containing minerals such as lepidolite and pollucite, as well as in seawater and industrial waste. Several technologies such as acid leaching, roasting, solvent extraction, and adsorption are used to recover rubidium. The maximum recovery efficiency of the rubidium from the sources and the processing above is generally high, but, in many practices, rubidium is not the main recovery target, and therefore the actual recovery effects should depend on presence of other valuable components or impurities, together with recovery costs, energy consumption, environmental issues, etc. In conclusion, although the current production and consumption of rubidium are limited, with consideration of the possible market fluctuations according to the emergence of large-scale demand sources, etc., further investigations by related institutions should be necessary.

• Smart Media Journal
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• v.12 no.5
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• pp.36-45
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• 2023

Recently, in digital agriculture, the types and utilization of greenhouses based on IoT are spreading, and greenhouses are being modernized, enlarged, and even factoryized using smart technology. However, a specific standardization plan has not been proposed according to the equipment for data collection in the smart greenhouse and the size or shape of the greenhouse. In other words, there is a lack of standard data for facility equipment, such as the type and number of sensors and equipment according to the size of the greenhouse, the type of greenhouse construction film and materials suitable for crops and carbon neutrality. Therefore, in this study, the suitability of the implementation, installation and quantity of IoT equipment for data collection was tested, and some standard technologies were presented through the implementation of data collection and communication methods. In addition, impact strength, tensile, tear, elongation, light transmittance, and lifespan issues for PE, PVC, and EVA, which account for about 90% of existing greenhouses, were presented, and the shape, size, and environmental problems of greenhouses made of films were presented. presented in the text. In this research paper, a standardized carbon-neutral modular smart greenhouse using nano-material film was implemented as a solution to environmental problems such as greenhouse size, farm crop type, greenhouse lifespan, and film, and its performance with existing greenhouses was analyzed and presented. Through this, we propose a modularized greenhouse that can be expanded or reduced freely without distinction in the size of the greenhouse or the shape of farmhouse crops, and the lifespan is extended and standardized. Finally, the average characteristics of greenhouses using existing PE, PVC, and EVA films and the characteristics of greenhouses using new carbon-neutral nanomaterials are compared and reviewed, and a plan to implement an expandable IoT greenhouse that supports carbon neutrality is proposed.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.63-65
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• 2023

BIM and AR technologies have been assessed as a means of enhancing productivity within the construction industry, through the provision of effortless access to critical data on site, achieved via the projection of 3D models and associated information onto actual structures. However, most of the previous researches for applying AR technology in construction quality management has been performed for construction projects in general, resulting in only overall on-site management solutions. Also, a few previous researches for the application of AR in the quality management of specific elements like reinforcements focused only on simple projection, so conducting specific quality inspection was impossible. Hence, this study aimed to develop a practically applicable BIM-based AR quality management system targeted for reinforcements. For the development of this system, the reinforcement inspection items on the quality checklist used at railway construction sites were analyzed, and four types of AR functions that can effectively address these items were developed and installed. The validation result of the system for the actual railway bridge showed a degradation of projection stability. This problem was solved through model simplification and enhancement of the AR device's hardware performance, and then the normal operation of the system was validated. Subsequently, the final developed reinforcement quality inspection system was evaluated for practical applicability by on-site quality experts, and the efficiency of inspection would significantly increase when using the AR system compared to the current inspection method for reinforcements.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.863-870
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• 2023

Ship capsize accidents are common in coastal waters, particularly involving small fishing boats. To prevent there overturing accidents in small fishing boats, their stabilities must be assessed at the initial design step. However, the available information during the initial design step is limited, posing challenges in performing a reliable stability evaluation. Therefore, this study presents a plan to estimate the transverse metacenter (GM) of small fishing boats using parameters such as KM, KG, and TRIM that can be determined at the initial design step. Stability was evaluated by comparing GM with the minimum transverse metacenter (GMmin) specified in the standard safety evaluation criteria for fishing boats. To calculate the required trim value for hydrostatic characteristics using K-SHIP, a stability assessment program provided by the Korea Maritime Safety and Transportation Corporation, the initial trim state is estimated based on the ship lines using the commercial CFD program STAR-CCM+. GM is then calculated by assessing the hydrostatic characteristics in relation to the boat lines using K-SHIP. Furthermore, the stability of the fully loaded state is compared by subtrcating GM from GMmin. One constructed ship is designated as the standard ship, and the stability assessment method proposed in this study is applied to evaluate stability and validate its effectiveness. Consequently, the representative line of a 4.99-ton fishing boat and nine modular lines models derived from it were evaluated, ultimately identifying a relatively superior stability.

• Informatization Policy
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• v.30 no.4
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• pp.40-61
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• 2023

The adoption of smart factories and smart manufacturing as strategies to enhance competitiveness and stimulate growth in the manufacturing sector is vital for a country's future competitiveness and industrial transformation. The government has consistently pursued smart manufacturing innovation policies starting with the Manufacturing Innovation 3.0 strategy in the Ministry of Industry. This study aims to identify policy areas for smart factories and smart manufacturing based on technical standards. Analyzing policy areas at the current stage where the establishment and support of domestic standards aligning with international technical standards are required is crucial. By prioritizing smart manufacturing process areas within the industry, policymakers can make well-informed decisions to advance smart manufacturing without blindly following international standardization in already well-established areas. To achieve this, the study utilizes a hierarchical analysis method including expert interviews and importance-performance analysis for the five major process areas. The findings underscore the importance of proactive participation in standardization for emerging technologies, such as data and security, instead of solely focusing on areas with extensive international standardization. Additionally, policymakers need to consider carbon emissions, energy costs, and global environmental challenges to address international trends in export and digital trade effectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.185-190
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• 2023

Recently, tracking radar requires the development of millimeter wave tracking radar to acquire target information with high resolution in various environments. The development of millimeter wave tracking radar requires the development of transmission and receiving components that can be applied to the millimeter wave tracking radar, as well as verification of the applicability of the tracking radar. In order to verify the applicability of the developed transmitting and receiving components, it is necessary to develop a signal acquisition device that can control the transmitting and receiving components using the operating concept of a tracking radar and check the status of the received signal. In this paper, we implemented a signal acquisition device that can confirm the applicability of components developed for millimeter wave tracking radar. The signal acquisition device was designed to process in real time the OOOMHz center frequency and OOMHz bandwidth signals input from 4 channels to verify the received signal. In addition, component control applying the tracking radar operation concept was designed to be controlled by communication such as RS422, RS232, and SPI and generation of control signals for the transmission and receiving time. Lastly, the implemented signal acquisition device was verified through a signal acquisition device performance test.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1125-1134
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• 2023

Out of the total 17,000 reservoirs in Korea, 13,600 small agricultural reservoirs do not have hydrological measurement facilities, making it difficult to predict water storage volume and appropriate operation. This paper examined univariate and multivariate long short-term memory (LSTM) modeling to predict the storage rate of agricultural reservoirs using remote sensing and artificial intelligence. The univariate LSTM model used only water storage rate as an explanatory variable, and the multivariate LSTM model added n-day accumulative precipitation and date of year (DOY) as explanatory variables. They were trained using eight years data (2013 to 2020) for Idong Reservoir, and the predictions of the daily water storage in 2021 were validated for accuracy assessment. The univariate showed the root-mean square error (RMSE) of 1.04%, 2.52%, and 4.18% for the one, three, and five-day predictions. The multivariate model showed the RMSE 0.98%, 1.95%, and 2.76% for the one, three, and five-day predictions. In addition to the time-series storage rate, DOY and daily and 5-day cumulative precipitation variables were more significant than others for the daily model, which means that the temporal range of the impacts of precipitation on the everyday water storage rate was approximately five days.