• Korean Journal of Materials Research
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• v.34 no.4
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• pp.185-193
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• 2024

In this study, NASICON-type Li_1+XGa_XTi_2-X(PO₄)₃ (x = 0.1, 0.3 and 0.4) solid-state electrolytes for all-solid-state batteries were synthesized through the sol-gel method. In addition, the influence on the ion conductivity of solid-state electrolytes when partially substituted for Ti⁴⁺ (0.61Å) site to Ga³⁺ (0.62Å) of trivalent cations was investigated. The obtained precursor was heat treated at 450 ℃, and a single crystalline phase of Li_1+XGa_XTi_2-X(PO₄)₃ systems was obtained at a calcination temperature above 650 ℃. Additionally, the calcinated powders were pelletized and sintered at temperatures from 800 ℃ to 1,000 ℃ at 100 ℃ intervals. The synthesized powder and sintered bodies of Li_1+XGa_XTi_2-X(PO₄)₃ were characterized using TG-DTA, XRD, XPS and FE-SEM. The ionic conduction properties as solid-state electrolytes were investigated by AC impedance. As a result, Li_1+XGa_XTi_2-X(PO₄)₃ was successfully produced in all cases. However, a GaPO₄ impurity was formed due to the high sintering temperatures and high Ga content. The crystallinity of Li_1+XGa_XTi_2-X(PO₄)₃ increased with the sintering temperature as evidenced by FE-SEM observations, which demonstrated that the edges of the larger cube-shaped grains become sharper with increases in the sintering temperature. In samples with high sintering temperatures at 1,000 ℃ and high Ga content above 0.3, coarsening of grains occurred. This resulted in the formation of many grain boundaries, leading to low sinterability. These two factors, the impurity and grain boundary, have an enormous impact on the properties of Li_1+XGa_XTi_2-X(PO₄)₃. The Li_1.3Ga_0.3Ti_1.7(PO₄)₃ pellet sintered at 900 ℃ was denser than those sintered at other conditions, showing the highest total ion conductivity of 7.66 × 10^-5 S/cm at room temperature. The total activation energy of Li-ion transport for the Li_1.3Ga_0.3Ti_1.7(PO₄)₃ solid-state electrolyte was estimated to be as low as 0.36 eV. Although the Li_1+XGa_XTi_2-X(PO₄)₃ sintered at 1,000 ℃ had a relatively high apparent density, it had less total ionic conductivity due to an increase in the grain-boundary resistance with coarse grains.

• Journal of Aerospace System Engineering
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• v.18 no.2
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• pp.64-70
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• 2024

The demand for safety certification of Light Unmanned Aerial Vehicles (LUAVs), weighing between 25kg and 150kg, is rapidly increasing in Korea. Unfortunately, the number of LUAV safety certification failures is also on the rise, with manufacturing quality issues being identified as the main culprit. However, there is a lack of quality system standards for manufacturers within the LUAV safety certification system. As a result, this paper aims to analyze the domestic safety certification system and the quality standards set by the American Society for Testing and Materials (ASTM) for small Unmanned Aerial Systems (sUAS). The goal is to establish quality system inspection standards specifically tailored for LUAV manufacturers. To achieve this, we propose additional inspection items that reflect the characteristics of the manufacturing quality system. These items will be identified through on-site inspections of LUAV manufacturers, ensuring that the resulting quality system standard aligns with the actual situation of domestic manufacturers. In order to gauge the feasibility and effectiveness of the proposed quality system standard, we conducted a survey of seven domestic LUAV manufacturers.

• Journal of IKEEE
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• v.28 no.2
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• pp.150-157
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• 2024

In this paper, we propose a novel algorithm for predicting the number of apples on an apple tree using a deep learning-based object detection model and a polynomial regression model. Measuring the number of apples on an apple tree can be used to predict apple yield and to assess losses for determining agricultural disaster insurance payouts. To measure apple fruit load, we photographed the front and back sides of apple trees. We manually labeled the apples in the captured images to construct a dataset, which was then used to train a one-stage object detection CNN model. However, when apples on an apple tree are obscured by leaves, branches, or other parts of the tree, they may not be captured in images. Consequently, it becomes difficult for image recognition-based deep learning models to detect or infer the presence of these apples. To address this issue, we propose a two-stage inference process. In the first stage, we utilize an image-based deep learning model to count the number of apples in photos taken from both sides of the apple tree. In the second stage, we conduct a polynomial regression analysis, using the total apple count from the deep learning model as the independent variable, and the actual number of apples manually counted during an on-site visit to the orchard as the dependent variable. The performance evaluation of the two-stage inference system proposed in this paper showed an average accuracy of 90.98% in counting the number of apples on each apple tree. Therefore, the proposed method can significantly reduce the time and cost associated with manually counting apples. Furthermore, this approach has the potential to be widely adopted as a new foundational technology for fruit load estimation in related fields using deep learning.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.28-53
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• 2024

In general, high-level radioactive waste (HLW) generated as a result of nuclear power generation should be disposed within the country. Determination of the disposal site and host rock for HLW deep geological repository is an important issue not only scientifically but also politically, economically, and socially. Considered host rock types worldwide for geological disposal include crystalline rocks, sedimentary rocks, volcanic rocks, and salt dome. However, South Korea consists of various rock types except salt dome. This paper not only analyzed the geological and rock mechanical characteristics on a nationwide scale with the preliminary results on various rock type studies for the disposal host rock, but also reviewed the characteristics and possibility of various rock types as a host rock through deep drilling surveys. Based on the nationwide screening for host rock types resulted from literature review, rock distributions, and detailed case studies, Jurassic granites and Cretaceous sedimentary rocks (Jinju and Jindong formations) were derived as a possible candidate host rock types for the geological disposal. However, since the analyzed data for candidate rock types from this study is not enough, it is suggested that the disposal rock type should be carefully determined from additional and detailed analysis on disposal depth, regional characteristics, multidisciplinary investigations, etc.

• Journal of IKEEE
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• v.28 no.3
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• pp.474-478
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• 2024

In this paper, we proposes a deep learning network for quality inspection in a multi-camera inline inspection system for pharmaceutical containers. The proposed deep learning network is specifically designed for pharmaceutical containers by using data produced in real manufacturing environments, leading to more accurate quality inspection. Additionally, the use of an inline-capable deep learning network allows for an increase in inspection speed. The development of the deep learning network for quality inspection in the multi-camera inline inspection system consists of three steps. First, a dataset of approximately 10,000 images is constructed from the production site using one line camera for foreign substance inspection and three area cameras for dimensional inspection. Second, the pharmaceutical container data is preprocessed by designating regions of interest (ROI) in areas where defects are likely to occur, tailored for foreign substance and dimensional inspections. Third, the preprocessed data is used to train the deep learning network. The network improves inference speed by reducing the number of channels and eliminating the use of linear layers, while accuracy is enhanced by applying PReLU and residual learning. This results in the creation of four deep learning modules tailored to the dataset built from the four cameras. The performance of the proposed deep learning network for quality inspection in the multi-camera inline inspection system for pharmaceutical containers was evaluated through experiments conducted by a certified testing agency. The results show that the deep learning modules achieved a classification accuracy of 99.4%, exceeding the world-class level of 95%, and an average classification speed of 0.947 seconds, which is superior to the world-class level of 1 second. Therefore, the effectiveness of the proposed deep learning network for quality inspection in a multi-camera inline inspection system for pharmaceutical containers has been demonstrated.

• Journal of the Korean Geotechnical Society
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• v.35 no.5
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• pp.5-19
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• 2019

Considering the natural phenomenon in which steep slopes ($65^{\circ}{\sim}85^{\circ}$) consisting of rock mass remain stable for decades, slopes steeper than 1:0.5 (the standard of slope angle for blast rock) may be applied in geotechnical conditions which are similar to those above at the design and initial construction stages. In the process of analysing the stability of a good to fair continuum rock slope that can be designed as a steep slope, a general method of estimating rock mass strength properties from design practice perspective was required. Practical and genealized engineering methods of determining the properties of a rock mass are important for a good continuum rock slope that can be designed as a steep slope. The Genealized Hoek-Brown (H-B) failure criterion and GSI (Geological Strength Index), which were revised and supplemented by Hoek et al. (2002), were assessed as rock mass characterization systems fully taking into account the effects of discontinuities, and were widely utilized as a method for calculating equivalent Mohr-Coulomb shear strength (balancing the areas) according to stress changes. The concept of calculating equivalent M-C shear strength according to the change of confining stress range was proposed, and on a slope, the equivalent shear strength changes sensitively with changes in the maximum confining stress (${{\sigma}^{\prime}}_{3max}$ or normal stress), making it difficult to use it in practical design. In this study, the method of estimating the strength properties (an iso-angle division method) that can be applied universally within the maximum confining stress range for a good to fair continuum rock mass slope is proposed by applying the H-B failure criterion. In order to assess the validity and applicability of the proposed method of estimating the shear strength (A), the rock slope, which is a study object, was selected as the type of rock (igneous, metamorphic, sedimentary) on the steep slope near the existing working design site. It is compared and analyzed with the equivalent M-C shear strength (balancing the areas) proposed by Hoek. The equivalent M-C shear strength of the balancing the areas method and iso-angle division method was estimated using the RocLab program (geotechnical properties calculation software based on the H-B failure criterion (2002)) by using the basic data of the laboratory rock triaxial compression test at the existing working design site and the face mapping of discontinuities on the rock slope of study area. The calculated equivalent M-C shear strength of the balancing the areas method was interlinked to show very large or small cohesion and internal friction angles (generally, greater than $45^{\circ}$). The equivalent M-C shear strength of the iso-angle division is in-between the equivalent M-C shear properties of the balancing the areas, and the internal friction angles show a range of $30^{\circ}$ to $42^{\circ}$. We compared and analyzed the shear strength (A) of the iso-angle division method at the study area with the shear strength (B) of the existing working design site with similar or the same grade RMR each other. The application of the proposed iso-angle division method was indirectly evaluated through the results of the stability analysis (limit equilibrium analysis and finite element analysis) applied with these the strength properties. The difference between A and B of the shear strength is about 10%. LEM results (in wet condition) showed that Fs (A) = 14.08~58.22 (average 32.9) and Fs (B) = 18.39~60.04 (average 32.2), which were similar in accordance with the same rock types. As a result of FEM, displacement (A) = 0.13~0.65 mm (average 0.27 mm) and displacement (B) = 0.14~1.07 mm (average 0.37 mm). Using the GSI and Hoek-Brown failure criterion, the significant result could be identified in the application evaluation. Therefore, the strength properties of rock mass estimated by the iso-angle division method could be applied with practical shear strength.

• Applied Chemistry for Engineering
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• v.27 no.1
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• pp.92-100
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• 2016

Low-temperature conversion of nitrogen oxides using plasma-assisted hydrocarbon selective catalytic reduction of (HC-SCR) was investigated. Plasma was created in the catalyst-packed bed so that it could directly interact with the catalyst. The effect of the reaction temperature, the shape of catalyst, the concentration of n-heptane as a reducing agent, the oxygen content, the water vapor content and the energy density on $NO_x$ removal was examined. $NO_x$ conversion efficiencies achieved with the plasma-catalytic hybrid process at a temperature of $250^{\circ}C$ and an specific energy input (SIE) of $42J\;L^{-1}$ were 83% and 69% for one-dimensional Ag catalyst ($Ag\;(nanowire)/{\gamma}-Al_2O_3$) and spherical Ag catalyst ($Ag\;(sphere)/{\gamma}-Al_2O_3$), respectively, whereas that obtained with the catalyst-alone was considerably lower (about 30%) even with $Ag\;(nanowire)/{\gamma}-Al_2O_3$ under the same condition. The enhanced catalytic activity towards $NO_x$ conversion in the presence of plasma can be explained by the formation of more reactive $NO_2$ species and partially oxidized hydrocarbon intermediates from the oxidation of NO and n-heptane under plasma discharge. Increasing the SIE tended to improve $NO_x$ conversion efficiency, and so did the increase in the n-heptane concentration; however, a further increase in the n-heptane concentration beyond $C_1/NO_x$ ratio of 5 did not improve the $NO_x$ conversion efficiency any more. The increase in the humidity affected negatively the $NO_x$ conversion efficiency, resulting in lowering the $NO_x$ conversion efficiency at the higher water vapor content, because water molecules competed with $NO_x$ species for the same active site. The $NO_x$ conversion efficiency increased with increasing the oxygen content from 3 to 15%, in particular at low SIE values, because the formation of $NO_2$ and partially oxidized hydrocarbon intermediates was facilitated.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.2
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• pp.158-164
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• 2006

Offensive odor from CAFO(concentrated animal feeding operation) and its control have become a significant issue in Korea. Control of odors from the CAFO requires to identify major odorant and their generation mechanisms. In this study, an easy method to collect gas sample and to quantify its odorants is proposed. The method involves on-site odorant extraction with solid-phase microextraction and quantitation with GC/MSD or GC/FID. Analytes of the current study include: trimethylamine(TMA), carbon disulfide($CS_2$), dimethyl sulfide(DMS), dimethyl disulfide(DMDS), acetic acid(AA), propionic acid(PA) and n-butyric acid(BA). The resulting linearity($R^2$) of calibration curve for each analyte was good over the range from several ppbv to ppmv; 0.984 for TMA(0.056-1.437), 0.996 for $CS_2$(0.039-0.999), 0.994 for DMS(0.029-0.756), 0.995 for DMDS(0.024-0.623), 0.992 for AA(0.068-1.314), 0.955 for PA(0.047-0.940), and 0.976 for BA(0.036-0.712). Method detection limits were 5.67, 6.39, 5.78, 25.2, 0.098, 0.363 and 0.099 ppbv for AA, PA, BA, TMA, DMS, $CS_2$, and DMDS, respectively. With the developed method, odorants from poultry, swine, and cattle barns were analysed. All the compounds but DMDS were detected from the sample collected in the poultry barn, and their levels exceeded the representative published human olfactory threshold.

• Journal of Soil and Groundwater Environment
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• v.10 no.3
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• pp.38-45
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• 2005

The feasibility of stimulating in situ aerobic cometabolic activity of indigenous microorganisms was investigated in a trichloroethylene (TCE)-contaminated aquifer. A series of single-well natural drift tests (SWNDTs) was conducted by injecting site groundwater amended with a bromide tracer and combinations of toluene, oxygen, nitrate, ethylene and TCE into an existing monitoring well and by sampling the same well over time. Three field tests, Push-pull Transport Test, Drift Biostimulation Test, and Drift Surrogate Activity Test, were performed in sequence. Initial rate of toluene degradation was much faster than the rate of bromide dilution resulting from natural groundwater drift, indicating stimulation of indigenous toluene-oxidizing microorganisms. Transformation of ethylene, a surrogate probing overall activity of TCE transformation, was also observed, and its transformation results in the production of ethylene oxide, suggesting that some tolueneoxidizing microorganisms stimulated may express a orthomonooxygenase enzyme. Also in situ transformation of TCE was confirmed by greater retardation of TCE than bromide after the stimulation of toluene-oxidizing microorganisms. These results indicate that, in this environment, toluene and oxygen additions stimulated the growth and aerobic cometabolic activity of indigenous microorganisms expressing orthomonooxygenase enzymes. The simple, low-cost field test method presented in this study provides an effective method for conducting rapid field assessments and pilot testing of aerobic cometabolism, which has previously hindered application of this technology to groundwater remediation.

• Proceedings of the KACD Conference
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• 2008.05a
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• pp.246-257
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• 2008

The purpose of this study was to investigate the influence of various occlusal loading sites and directions on the stress distribution of the cervical composite resin restorations of maxillary second premolar, using 3 dimensional (3D) finite element (FE) analysis. Extracted maxillary second premolar was scanned serially with Micro-CT (SkyScan1072; SkyScan, Aartselaar, Belgium). The 3D images were processed by 3D-DOCTOR (Able Software Co., Lexington, MA, USA). HyperMesh (Altair Engineering. Inc., Troy, USA) and ANSYS (Swanson Analysis Systems. Inc., Houston, USA) was used to mesh and analyze 3D FE model. Notch shaped cavity was filled with hybrid (Z100, 3M Dental Products, St. Paul, MN, USA) or flowable resin (Tetric Flow, Viva dent Ets., FL-9494-Schaan, Liechtenstein) and each restoration was simulated with adhesive layer thickness ($40{\mu}m$). A static load of 200 N was applied on the three points of the buccal incline of the palatal cusp and oriented in $20^{\circ}$ increments, from vertical (long axis of the tooth) to oblique $40^{\circ}$ direction towards the buccal. The maximum principal stresses in the occlusal and cervical cavosurface margin and vertical section of buccal surfaces of notch-shaped class V cavity were analyzed using ANSYS. As the angle of loading direction increased, tensile stress increased. Loading site had little effect on it. Under same loading condition. Tetric Flow showed relatively lower stress than Z100 overall, except both point angles. Loading direction and the elastic modulus of restorative material seem to be important factor on the cervical restoration.