• Journal of Adhesion and Interface
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• v.25 no.1
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• pp.157-161
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• 2024

Amphiphilic gold nanoparticles, synthesized by the simultaneous binding of hydrophilic and hydrophobic ligands on their surfaces, find diverse applications in energy, bio, optical, electronic technologies, and various other fields. Particularly, these amphiphilic gold nanoparticles possess both hydrophilic and hydrophobic characteristics, enabling them to activate interface at the interface of immiscible fluids and form organized structures. The surface properties of gold nanoparticles play a crucial role in influencing the behaviors of amphiphilic gold nanoparticles at the interface of two fluids. Therefore, this study investigated the adsorption behaviors of gold nanoparticles at the organic solvent-water interface based on the surface characteristics of amphiphilic gold nanoparticles and the type of organic solvents. It was observed that the amount of adsorbed gold nanoparticles at the interface increased with the length of hydrocarbon chains in hydrophobic ligands and increased with shorter hydrocarbon chains in the organic solvent. Furthermore, using the Langmuir isotherm model, the study confirmed the formation of a monolayer by amphiphilic gold nanoparticles and obtained significant thermodynamic parameters simultaneously.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.178-185
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• 2007

Myrionecta rubra Jankowski 1976(=Mesodinium rubrum Lohmann 1908), a mixotrophic ciliate, is very common and often causes recurrent red tides in diverse marine environments. Since the report on the first laboratory strain of this species in 2000, papers on its novel ecological role and evolutionary importance have been high lighted. This review paper is prepared to promote the de novo recognition M. rubra as a marine mixotrophic species. M. rubra is a ciliate which is able to photosynthesize using plastids originated from cryptophyte (including Teleaulax sp. and Geminigera sp.) prey cells (i.e. kleptoplastidic ciliate). Recently, novel bacterivory of M. rubra was firstly reported. Thus, the nutritional modes of M. rubra include photosynthesis, bacterivory, and algivory. In turn, M. rubra was reported as the prey species of metazoan predators such as calanoid copepods, mysids, larvae of ctenophore and anchovy, and spats of bivalves. In addition, it was reported that dinoflagellate Dinophysis causing diarrhetic shellfish poisoning is one among the predators of M. rubra. Thus, M. rubra, a marine mixotrophic ciliate, may play a pivotal role as a common linking ciliate for the flow of energy and organic material in pelagic food webs.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.835-840
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• 2023

RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.

• Animal Bioscience
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• v.37 no.8
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• pp.1474-1482
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• 2024

Objective: The experiment aimed to determine the standardized ileal digestibility (SID) of crude protein (CP) and amino acids (AA) in 10 brown rice samples fed to pigs, and to construct predictive models for SID of CP and AA based on the physical characteristics and chemical composition of brown rice. Methods: Twenty-two cannulated pigs (initial body weight: 42.0±1.2 kg) were assigned to a replicated 11×3 incomplete Latin square design, including an N-free diet and 10 brown rice diets. Each period included 5 d adaptation and 2 d ileal digesta collection. Chromic oxide was added at 0.3% to all the diets as an indigestible marker for calculating the ileal CP and AA digestibility. Results: The coefficients of variation of all detected indices for physical characteristics and chemical composition, except for bulk weight, dry matter (DM) and gross energy, in 10 brown rice samples were greater than 10%. The SID of CP, lysine (Lys), methionine, threonine (Thr), and tryptophan (Trp) in brown rice was 77.2% (62.6% to 85.5%), 87.5% (80.3% to 94.3%), 89.2% (78.9% to 98.9%), 55.4% (46.1% to 67.6%) and 92.5% (86.3% to 96.3%), respectively. The best prediction equations for the SID of CP, Lys, Thr, and Trp were as following, SID_CP = -664.181+8.484×DM (R² = 0.40), SID_Lys = 53.126+6.031×ether extract (EE)+0.893×thousand-kernel volume (R² = 0.66), SID_Thr = 39.916+7.843×EE (R² = 0.41), and SID_Trp = -361.588+4.891×DM+0.387×total starch (R² = 0.85). Conclusion: Overall, a great variation exists among 10 sources of brown rice, and the thousand-grain volume, DM, EE, and total starch can be used as the key predictors for SID of CP and AA.

• Structural Engineering and Mechanics
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• v.90 no.6
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• pp.611-633
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• 2024

This study intends to investigate the response of multi-cell (MC) beams to flexural loads in which the primary reinforcement is composed of both metallic and non-metallic materials. "Multi-cell" describes beam sections with multiple longitudinal voids separated by thin webs. Seven reinforced concrete MC beams measuring 300×200×1800 mm were tested under flexural loadings until failure. Two series of beams are formed, depending on the type of main reinforcement that is being used. A control RC beam with no openings and six MC beams are found in these two series. Series one and two are reinforced with metallic and non-metallic main reinforcement, respectively, in order to maintain a constant reinforcement ratio. The first crack, ultimate load, deflection, ductility index, energy absorption, strain characteristics, crack pattern, and failure mode were among the structural parameters of the beams under investigation that were documented. The primary variables that vary are the kind of reinforcing materials that are utilized, as well as the kind and quantity of mesh layers. The outcomes of this study that looked at the experimental and numerical performance of ferrocement reinforced concrete MC beams are presented in this article. Nonlinear finite element analysis (NLFEA) was performed with ANSYS-16.0 software to demonstrate the behavior of composite MC beams with holes. A parametric study is also carried out to investigate the factors, such as opening size, that can most strongly affect the mechanical behavior of the suggested model. The experimental and numerical results obtained demonstrate that the FE simulations generated an acceptable degree of experimental value estimation. It's also important to demonstrate that, when compared to the control beam, the MC beam reinforced with geogrid mesh (MCGB) decreases its strength capacity by a maximum of 73.33%. In contrast, the minimum strength reduction value of 16.71% is observed in the MC beams reinforced with carbon reinforcing bars (MCCR). The findings of the experiments on MC beams with openings demonstrate that the presence of openings has a significant impact on the behavior of the beams, as there is a decrease in both the ultimate load and maximum deflection.

• Journal of the Korean Geosynthetics Society
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• v.23 no.1
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• pp.9-16
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• 2024

In order to evaluate the relationship between the ground confining pressure and the shear characteristics of the pile-soil interface, this study described the comparative results of the existing experimental results and the FEA results using the strength reduction factor. The strength reduction factor was applied to simulate the shear behavior of the pile-soil interface in finite element analysis(FEA). The analysis results showed that the maximum pullout resistance decreased due to the influence of low confining pressure, as the fines content increased. This trend was similar to the previous experimental research, and this FEA model simulated with the interface strength reduction factor was evaluated as reasonable. The analysis results of the variation in the interface strength reduction factor clearly showed that the interface strength reduction factor clearly increased at a high fines content when the confining pressure was 50kPa. However, it was found that the increase rate was low when the confining pressure was 100kPa and 150kPa. Therefore, confining pressure and fines content need to be considered in FEA to evaluate the shear behavior of the pile-soil interface.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.403-409
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• 2024

In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.

• Resources Recycling
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• v.33 no.3
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• pp.38-47
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• 2024

Molybdenite is the primary molybdenum resource and is extracted via flotation due to its unique hydrophobic surface. Meanwhile, the grade and crystal size of mined molybdenite are decreasing. As a result, the size of the molybdenum ore required for liberation is decreasing, and the flotation process's feed size input is also decreasing. Therefore, in order to secure molybdenum, it is necessary to perform research on the flotation for the fine molybdenite. In this study, we developed a method to enhance the flotation efficiency of fine molybdenite particles in the range of 5-30 ㎛. The methodology involved implementing bubble size reduction and particle aggregation. Through simulations of bubble-particle collision probability and flotation experiments, we were able to find the ranges of bubble size and particle aggregate size that make fine particles float more effectively. This range provided the conditions for effective flotation of fine molybdenite particles. Therefore, we will implement the flotation conditions established in this study for fine molybdenum ore to improve the flotation process in molybdenum mineral processing plants in the future.

• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.2 s.54
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• pp.215-222
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• 2009

In this study, steel and FRP jackets are used to confine concrete cylinders. The FRP jacket behaviors compositely with concrete since there is bonding between them. However, the used steel jacket in this study do not behavior compositely with concrete since there is not an adhesive between them. The steel jackets are attached by external forces and the welding. This study suggests the measuring method of the axial strain for the confined concrete cylinders showing noncomposite behavior with the jackets and the correcting method of the measured strain for the composite-behavior jackets. For the noncomposite-behavior steel jacket, the axial strain of the steel surface does not represent the axial strain of the concrete inside. Also, a compressormeter can not be used. Thus, the two rigid plates at the top and bottom of a cylinder are placed and the distance of the two plates are measured and used for estimating the axial strain of the concrete. For the composite-behavior FRP jacket, the vertical strain measured on the FRP surface can be used for estimating the axial strain of the concrete. However, the vertical strain on the FRP surface contains the tensile strain due to the bulge of the concrete and, thus, the tensile strain should be corrected from the vertical strain. The corrected verticals strains compared with the measured strain or a existing constitute model; the result is satisfactory. The uncorrected stress-strain curves have the potential to under estimate the ductile behavior and the energy-dissipation-capacity of the composite-behavior FRP jackets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.2028-2042
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• 1994

Properly defining signal and noise in a self-organizing system like ART(Adaptive Resonance Theory) neural network model raises a number of subtle issues. Pattern context must enter the definition so that input features, treated as irrelevant noise when they are embedded in a given input pattern, may be treated as informative signals when they are embedded in a different input pattern. The ATR automatically self-scales their computational units to embody context and learning dependent definitions of a signal and noise and there is no problem in categorizing input pattern that have features similar in nature. However, when we have imput patterns that have features that are different in size and nature, the use of only one vigilance parameter is not enough to differentiate a signal from noise for a good categorization. For example, if the value fo vigilance parameter is large, then noise may be processed as an informative signal and unnecessary categories are generated: and if the value of vigilance parameter is small, an informative signal may be ignored and treated as noise. Hence it is no easy to achieve a good pattern categorization. To overcome such problems, a Coupled-ART neural network capable of modularized categorization of patterns is proposed. The Coupled-ART has two layer of tightly coupled modules. the upper and the lower. The lower layer processes the global features of a pattern and the structural features, separately in parallel. The upper layer combines the categorized outputs from the lower layer and categorizes the combined output, Hence, due to the modularized categorization of patterns, the Coupled-ART classifies patterns more efficiently than the ART1 model.