• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.95-102
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• 2020

For the purpose of developing a PE fiber-reinforced highly ductile cementitious composite having high tensile strain capacity more than 2% under the condition of containing aggregates with large particle size, this study investigated the tensile behavior of composites according to the particle size and distribution of aggregates in the composite. Compared with the mixture containing silica sand of which particle size is less than 0.6 mm, mixtures containing river sand and/or gravel with the maximum particle size of 2.36 mm, 4.75 mm, 5.6 mm, 6.7 mm were considered in the experimental design. The particle size distributions of aggregates were adjusted for the optimized distribution curves obtained from modified A&A model by blending different sizes of aggregates. All the mixtures presented clear strain-hardening behavior in the direct tensile tests. The mixtures with the blended aggregates to meet the optimum curves of aggregate size distributions showed higher tensile strain capacity than the mixture with silica sand. It was also found that the tensile strain capacity was improved as the maximum size of aggregate increased which resulted in wider particle size distribution. The mixtures with the maximum size of 5.6 mm and 6.7 mm presented very high tensile strain capacities of 4.83% and 5.89%, respectively. This study demonstrated that it was possible to use coarse aggregates in manufacturing highly ductile fiber-reinforced cementitous composite by adjusting the particle size distribution.

• Journal of IKEEE
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• v.25 no.4
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• pp.625-633
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• 2021

This paper describes a scalable architecture for flexible hardware implementation of Montgomery modular multiplication. Our scalable modular multiplier architecture, which is based on a one-dimensional array of processing elements (PEs), performs word parallel operation and allows us to adjust computational performance and hardware complexity depending on the number of PEs used, N_PE. Based on the proposed architecture, we designed a scalable Montgomery modular multiplier (sMM) core supporting eight field sizes defined in SEC2. Synthesized with 180-nm CMOS cell library, our sMM core was implemented with 38,317 gate equivalents (GEs) and 139,390 GEs for N_PE=1 and N_PE=8, respectively. When operating with a 100 MHz clock, it was evaluated that 256-bit modular multiplications of 0.57 million times/sec for N_PE=1 and 3.5 million times/sec for N_PE=8 can be computed. Our sMM core has the advantage of enabling an optimized implementation by determining the number of PEs to be used in consideration of computational performance and hardware resources required in application fields, and it can be used as an IP (intellectual property) in scalable hardware design of elliptic curve cryptography (ECC).

• Animal Bioscience
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• v.35 no.2
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• pp.184-195
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• 2022

Objective: In this study we aimed to evaluate the effect of dietary live yeast supplementation on ruminal pH pattern, fermentation characteristics and associated bacteria in beef cattle. Methods: This work comprised of in vitro and in vivo experiments. In vitro fermentation was conducted by incubating 0%, 0.05%, 0.075%, 0.1%, 0.125%, and 0.15% active dried yeast (Saccharomyces cerevisiae, ADY) with total mixed ration substrate to determine its dose effect. According to in vitro results, 0.1% ADY inclusion level was assigned in in vivo study for continuously monitoring ruminal fermentation characteristics and microbes. Six ruminally cannulated steers were randomly assigned to 2 treatments (Control and ADY supplementation) as two-period crossover design (30-day). Blood samples were harvested before-feeding and rumen fluid was sampled at 0, 3, 6, 9, and 12 h post-feeding on 30 d. Results: After 24 h in vitro fermentation, pH and gas production were increased at 0.1% ADY where ammonia nitrogen and microbial crude protein also displayed lowest and peak values, respectively. Acetate, butyrate and total volatile fatty acids concentrations heightened with increasing ADY doses and plateaued at high levels, while acetate to propionate ratio was decreased accordingly. In in vivo study, ruminal pH was increased with ADY supplementation that also elevated acetate and propionate. Conversely, ADY reduced lactate level by dampening Streptococcus bovis and inducing greater Selenomonas ruminantium and Megasphaera elsdenii populations involved in lactate utilization. The serum urea nitrogen decreased, whereas glucose, albumin and total protein concentrations were increased with ADY supplementation. Conclusion: The results demonstrated dietary ADY improved ruminal fermentation dose-dependently. The ruminal lactate reduction through modification of lactate metabolic bacteria could be an important reason for rumen pH stabilization induced by ADY. ADY supplementation offered a complementary probiotics strategy in improving gluconeogenesis and nitrogen metabolism of beef cattle, potentially resulted from optimized rumen pH and fermentation.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• Clean Technology
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• v.28 no.3
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• pp.227-231
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• 2022

The demand for high-voltage power devices is rising in various industries, but especially in the transportation industry due to autonomous driving and electric vehicles. IGBT module parts of 3.3 kV or more are used in the power propulsion control device of electric vehicles, and the procurement of these parts for new construction and maintenance is increasing every year. In addition, research to optimize high-voltage IGBT parts is urgently required to overcome their very high technology entry barrier. For the development of high-voltage IGBT devices over 3.3 kV, the resistivity range setting of the wafer and the optimal conditions for major unit processes are important variables. Among the manufacturing processes to secure the optimal junction depth, the optimization of the diffusion process, which is one step of the unit process, was examined. In the diffusion process, the type of gas injected, the injection time, and the injection temperature are the main variables. In this study, the range of wafer resistance (Ω cm) was set for the development of high voltage IGBT devices through unit process simulation. Additionally, the well drive in (WDR) condition optimization of the diffusion process according to temperature was studied. The junction depth was 7.4 to7.5 ㎛ for a ring pattern width of 23.5 to25.87 ㎛, which can be optimized for supporting 3.3 kV high voltage power devices.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.6
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• pp.631-638
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• 2022

Microgrid, which enables the production and consumption of electricity to be done independently on a small scale, has been studied on one of the solutions of reinforcement for flexibility of electronic system. This study examined the application effect of new microgrid by applying hybrid battery in electric power storage device. We designed the system to highlight the advantage of each battery and complement the disadvantage by using hybrid system with Lithium-ion battery and interval Redox flow battery. It runs with lithium-ion battery during the initial startup while the Redox flow battery operates for a long time at the end of excessive period, and it enables a discharge of Lithium-ion and Redox flow battery at the same time when the load has a large output. We chose Maldives as a subject of this study for organizing and optimizing independent microgrid. Maldives is the country to accomplish 100% domestic electricity in South Asia, but the whole electric power is supplied through diesel generation imported fossil fuel. We organized and optimized microgrid for energy independence on Malahini island to solve Maldives energy cost problem and global energy environment matters. We analyzed the daily power supply and accumulated the power supply from September 18, 2018~February 11, 2019. The accumulated power supply was about 120.4 MWh and the daily power supply was about 800~1000 kWh. Based on the collected information, we divided the cases into three models which are only diesel generator, solar generator as well as diesel generator, and solar+ESS+diesel generator. We analyzed the amount of oil consumption compared to the cost of construction and power output. The result showed that solar+ESS+diesel generator was most economically feasible. As well, we obtained that our considering hybrid battery system reduced the fuel consumption for diesel power generation about 10~15%.

• Journal of Aerospace System Engineering
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• v.16 no.5
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• pp.62-69
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• 2022

EHA (Electro-Hydrostatic Actuator) is more energy efficiency than a centralized hydraulic system. In particular, the EHA used for aircraft has a redundant design in preparation for failure scenario. Also, due to the aircraft's internal space limitation, the actuator's length must be optimized. Therefore, a series configuration of double rod and single rod cylinder is advantageous. However, due to the asymmetry of the cross-sectional area of the piston, the force fighting phenomenon between the two cylinder areas occurs during redundant operation with a general control system. In this paper, the force fighting phenomenon of redundant EHA was simulated. A controller with load compensation and a force control-based position controller as a method to suppress its stimulation

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.44-44
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• 2003

As a basic measurement tool in the areas of animal models of human disease, gene expression and therapy, and drug discovery and development, small animal PET imaging is being used increasingly. An ideal small animal PET should have high sensitivity and high and uniform resolution across the field of view to achieve high image quality. However, the combination of long narrow pixellated crystal array and small ring diameter of small animal PET leads to the degradation of spatial resolution for the source located at off center. This degradation of resolution can be improved by determining the depth of interaction (DOI) in the crystal and by taking into account the information in sorting the coincident events. Among a number of 001 identification schemes, dual layer phsowich detector has been widely investigated by many research groups due to its practicability and effectiveness on extracting DOI information. However, the effects of each crystal length composing dual layer phoswich detector on DOI measurements and image qualities were not fully characterized. In order to minimize the DOI effect, the length of each layer of phoswich detector should be optimized. The aim of this study was to perform simulations using a simulation tool, GATE to design the optimum lengths of crystals composing a dual layer phoswich detector. The simulated small PET system employed LSO front layer LuYAP back layer phoswich detector modules and the module consisted of 8${\times}$8 arrays of dual layer crystals with 2 mm ${\times}$ 2 mm sensitive area coupled to a Hamamatsu R7600 00 M64 PSPMT. Sensitivities and variation of radial resolutions were simulated by varying the length of LSO front layer from 0 to 10 mm while the total length (LSO + LuYAP) was fixed to 20 mm for 10 cm diameter ring scanner. The radial resolution uniformity was markedly improved by using DOI information. There existed the optimal lengths of crystal layers to minimize the variation of radial resolutions. In 10 cm ring scanner configuration, the radial resolution was kept below 3.4 mm over 8 cm FOV while the sensitivity was higher than 7.4% for LSO 5 mm : LuYAP 15 mm phoswich detector. In this study, the optimal length of dual layer phoswich detector was derived to achieve high and uniform radial resolution.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.15-26
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• 2006

Although numerous investigations have been performed over the years to predict the behavior and bearing capacity of piles, the mechanisms are not yet entirely understood. The prediction of bearing capacity is a difficult task, because large numbers of factors affect the capacity and also have complex relationship one another. Therefore, it is extremely difficult to search the essential factors among many factors, which are related with ground condition, pile type, driving condition and others, and then appropriately consider complicated relationship among the searched factors. The present paper describes the application of Artificial Neural Network (ANN) in predicting the capacity including its components at the tip and along the shaft from dynamic load test of the driven piles. Firstly, the effect of each factor on the value of bearing capacity is investigated on the basis of sensitivity analysis using ANN modeling. Secondly, the authors use the design methodology composed of ANN and genetic algorithm (GA) to find optimal neural network model to predict the bearing capacity. The authors allow this methodology to find the appropriate combination of input parameters, the number of hidden units and the transfer structure among the input, the hidden and the out layers. The results of this study indicate that the neural network model serves as a reliable and simple predictive tool for the bearing capacity of driven piles.

• 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.