• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• 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.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.2
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• pp.97-104
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• 2023

In order to maximize the utilization of recycled fine aggregate, high strength mortar made of 100 % recycled fine aggregate was prepared, and its physical properties were evaluated to determine the possibility of using recycled fine aggregate as structural aggregate. The effect caused by the amount of nanosilica on the physical properties of w/b 0.2 recycled fine aggregate mortar consisting of cement, silica fume, and blast furnace slag. To improve the dispersion of nanosilica inside mortar, an aqueously dispersed nanosilica solution by ultrasonic tip sonication was prepared, and incorporated into the mortar to evaluate changes in mortar flow, porosity and compressive strength depending on nanosilica content. According to the experimental results, mortar flow decreased as the replacement ratio of nano-silica increased. As the replacement ratio of nanosilica increased up to 0.75 %, the porosity decreased and the compressive strength increased, but, at a replacement ratio of 1 %, the porosity increased and the compressive strength decreased. It was confirmed that the nano-silica replacement ratio of 0.75 % was optimum proportion to maximize the mechanical performance of high-strength recycled fine aggregate mortar.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5A
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• pp.433-442
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• 2010

A control of chloride diffusion coefficient is very essential for service life of reinforced concrete (RC) structures exposed to chloride attack so that much studies have been focused on this work. The purpose of this study is to derive the intended diffusion coefficient which satisfies intended service life and propose a technique for optimum concrete mixture through genetic algorithm(GA). For this study, 30 data with mixture proportions and related diffusion coefficients are analyzed. Utilizing 27 data, fitness function for diffusion coefficient is obtained with variables of water to binder ratio(W/B), weight of cement, mineral admixture(slag, flay ash, and silica fume), sand, and coarse aggregate. 3 data are used for verification of the results from GA. Average error from fitness function is observed to 18.7% for 27 data for diffusion coefficient with 16.0% of coefficient of variance. For the verification using 3 data, a range of error for mixture proportions through GA is evaluated to 0.3~9.3% in 3 given diffusion coefficients. Assuming the durability design parameters like intended service life, cover depth, surface chloride content, and replacement ratio of mineral admixture, target diffusion coefficient, where exterior conditions like relative humidity(R.H.) and temperature, is derived and optimum design mixtures for concrete are proposed. In this paper, applicability of GA is attempted for durability mixture design and the proposed technique would be improved with enhancement of comprehensive data set including wider range of diffusion coefficients.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.2
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• pp.54-60
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• 2023

In this study, microstructure and basic property analysis of DG (Desulfurization gypsum) and CCMs (Carbondioxide conversion capture materials) made by reacting CO₂ with DG were conducted to analyze applicability as a cement admixture. The main crystalline phases of DG were CaO and CaSO₄, and CCMs were CaSO₄, CaCO₃, Ca(OH)₂ and CaSO₄·H₂O. As a result of particle size analysis, the difference in average particle sizes between the two materials was about 7 ㎛. No major heavy metals were detected in the CCMs, and as a result o f TGA, the CO₂ decomposition of CCMs was more than twice as high as that of DG. Therefore, it was judged that CCMs could be used as a cement admixture through optimization of manufacturing conditions. As a results of measuring the strength behavior of DG and CCMs mixture ratios, the long-term strength of CCMs-mixed mortar was higher, and this is due to the filler effect of CaCO₃ in CCMs.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.523-529
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• 2023

The aim of this study was to analyze the potential for timber harvesting in the Hongchoen Garisan Leading Forest Management Complex in the national forests, and to suggest an optimal target yield for sustainable timber harvesting. The potential for timber harvesting was assessed by analyzing the area available for timber harvesting using GIS spatial analysis, but excluding areas with a slope of more than 40° (topographical constraints), areas within 30 m on both sides of streams (environmental constraints), and areas more than 300 m away from forest roads (technical constraints). The analysis identified 3,298 ha (49%) of the total complex area of 6,679 ha as available for timber harvesting, yielding a potential harvesting volume of 608,613 m³. In the case of coniferous plantations, the potential harvesting volume was 409,721 m³, which was a very high level that accounted for 67.3% of the total. We also conducted an optimization analysis to minimize the differences in area between age classes, while maintaining sustainable timber harvesting for the next 50 years. An annual average of 41.9 ha (7,988 m³) was determined to be the optimal timber yield, and in this case, it was possible to convert the age class structure to a more stable structure after 50 years.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.91-98
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• 2023

Recently, according to development of artificial intelligence, a wide range of industry being automatic and optimized. Also we can find out some research of using supervised learning for deteceting defect of railway in domestic rail industry. However, there are structures other than rails on the track, and the fastener is a device that binds the rail to other structures, and periodic inspections are required to prevent safety accidents. In this paper, we present a method of reducing cost for labeling using semi-supervised and transfer model trained on rail fastener data. We use Resnet50 as the backbone network pretrained on ImageNet. At first we randomly take training data from unlabeled data and then labeled that data to train model. After predict unlabeled data by trained model, we adopted a method of adding the data with the highest probability for each class to the training data by a predetermined size. Futhermore, we also conducted some experiments to investigate the influence of the number of initially labeled data. As a result of the experiment, model reaches 92% accuracy which has a performance difference of around 5% compared to supervised learning. This is expected to improve the performance of the classifier by using relatively few labels without additional labeling processes through the proposed method.

• Industry Promotion Research
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• v.8 no.4
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• pp.267-276
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• 2023

Based on the tourism input-output data of five provinces and cities in China's Bohai Rim region from 2015~2021, this study analyzes the efficiency of regional tourism using DEA-BCC and DEA-Malmquist index, as well as its contribution to regional economic efficiency, and identifies factors influencing the comprehensive efficiency. The research results indicate that the comprehensive efficiency of the tourism industry in the China Bohai Sea region has reached an optimal level of 88.9%, but there is still room for improvement, with overall fluctuations. The overall productivity of the tourism industry exhibits a "U"-shaped fluctuating pattern, with growth mainly driven by technological advancements. Due to the impact of the COVID-19 pandemic, the region experienced a nearly 50% decrease in total factor productivity in 2019~2020. However, in 2021, with the implementation of various government stimulus policies, the tourism efficiency rapidly recovered to 80% of pre-pandemic levels. In terms of the impact of the tourism industry on the regional economy in the China Bohai Sea region, Hebei Province stands out as a significant contributor. Based on the aforementioned research findings, the following recommendations are proposed in three aspects: optimizing the supply structure, increasing innovation investment, and strengthening internal collaboration. These recommendations provide valuable insights for enhancing regional tourism efficiency and promoting regional synergy.

• Clean Technology
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• v.30 no.2
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• pp.113-122
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• 2024

In order to better understand carbon dioxide recycling, the carbon dioxide capture characteristics of six different alkaline industrial by-products, including incineration ash, desulfurized gypsum, low-grade quicklime, and steelmaking slag were investigated using a laboratory-scale direct aqueous carbonation reactor. In addition to the dissolution characteristics of each sample, the main reaction structure was confirmed through thermogravimetric analysis before and after the reaction, and the reactive CaO content was also defined through thermogravimetric analysis. The carbon dioxide capture capacity and efficiency of quicklime were determined to be 473 g/kg and 86.9%, respectively, and desulfurized gypsum and incineration ash were also evaluated to be relatively high at 51.1 to 131.7 g/kg and 51.2 to 87.7%, respectively. On the other hand, the capture efficiency of steelmaking slag was found to be less than 10% due to the influence of the production and post-cooling conditions. Therefore, in order to apply the carbonation process to steelmaking slag, it is necessary to optimize the slag production conditions. Through this study, it was confirmed that the carbon dioxide capture characteristics of incineration ash, quicklime, and desulfurized gypsum are at levels suitable for carbonation processes. Furthermore, this study was able to secure basic data for resource development technology that utilize carbon dioxide conversion to produce calcium carbonate for construction materials.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.3
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• pp.332-336
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• 2024

High-energy bandgap material silicon carbide (SiC) is gaining attention as a next-generation power semiconductor material, and in particular, SiC-based MOSFETs are developed as representative power semiconductors to increase the breakdown voltage (BV) of conventional planar structures. However, as the size of SJ (Super Junction) MOSFET devices decreases and the depth of pillars increases, it becomes challenging to uniformly form the doping concentration of pillars. Therefore, a structure with different doping concentrations segmented within the pillar is being researched. Using Silvaco TCAD simulation, a SJ VVD (vertical variation doping profile) MOSFET with three different doping concentrations in the pillar was studied. Simulations were conducted for the width of the pillar and the doping concentration of N-epi, revealing that as the width of the pillar increases, the depletion region widens, leading to an increase in on-specific resistance (R_on,sp) and breakdown voltage (BV). Additionally, as the doping concentration of N-epi increases, the number of carriers increases, and the depletion region narrows, resulting in a decrease in R_on,sp and BV. The optimized SJ VVD MOSFET exhibits a very high figure of merit (BFOM) of 13,400 KW/cm², indicating excellent performance characteristics and suggesting its potential as a next-generation highperformance power device suitable for practical applications.