Purpose DMIDR(Discovery Molecular Imaging Digital Ready, General Electric Healthcare, USA) is a PET/CT scanner designed to allow application of PSF(Point Spread Function), TOF(Time of Flight) and Q.Clear algorithm. Especially, Q.Clear is a reconstruction algorithm which can overcome the limitation of OSEM(Ordered Subset Expectation Maximization) and reduce the image noise based on voxel unit. The aim of this paper is to evaluate the performance of reconstruction algorithms and optimize the algorithm combination to improve the accurate SUV(Standardized Uptake Value) measurement and lesion detectability. Materials and Methods PET phantom was filled with $^{18}F-FDG$ radioactivity concentration ratio of hot to background was in a ratio of 2:1, 4:1 and 8:1. Scan was performed using the NEMA protocols. Scan data was reconstructed using combination of (1)VPFX(VUE point FX(TOF)), (2)VPHD-S(VUE Point HD+PSF), (3)VPFX-S (TOF+PSF), (4)QCHD-S-400((VUE Point HD+Q.Clear(${\beta}-strength$ 400)+PSF), (5)QCFX-S-400(TOF +Q.Clear(${\beta}-strength$ 400)+PSF), (6)QCHD-S-50(VUE Point HD+Q.Clear(${\beta}-strength$ 50)+PSF) and (7)QCFX-S-50(TOF+Q.Clear(${\beta}-strength$ 50)+PSF). CR(Contrast Recovery) and BV(Background Variability) were compared. Also, SNR(Signal to Noise Ratio) and RC(Recovery Coefficient) of counts and SUV were compared respectively. Results VPFX-S showed the highest CR value in sphere size of 10 and 13 mm, and QCFX-S-50 showed the highest value in spheres greater than 17 mm. In comparison of BV and SNR, QCFX-S-400 and QCHD-S-400 showed good results. The results of SUV measurement were proportional to the H/B ratio. RC for SUV is in inverse proportion to the H/B ratio and QCFX-S-50 showed highest value. In addition, reconstruction algorithm of Q.Clear using 400 of ${\beta}-strength$ showed lower value. Conclusion When higher ${\beta}-strength$ was applied Q.Clear showed better image quality by reducing the noise. On the contrary, lower ${\beta}-strength$ was applied Q.Clear showed that sharpness increase and PVE(Partial Volume Effect) decrease, so it is possible to measure SUV based on high RC comparing to conventional reconstruction conditions. An appropriate choice of these reconstruction algorithm can improve the accuracy and lesion detectability. In this reason, it is necessary to optimize the algorithm parameter according to the purpose.
An analytical method was developed for the determination of an antibiotic fungicide, kasugamycin, in agricultural products (hulled rice, potato, soybean, mandarin and green pepper) using liquid chromatographytandem mass spectrometry (LC-MS/MS). Samples were extracted with methanol adjusted to pH 13 using 1 N sodium hydroxide, and purified with a HLB (hydrophilic lipophilic balance) cartridge. Linearity of a matrix-matched calibration curve using seven concentration levels, from 0.001 to 0.1 mg/kg, was excellent with a correlation coefficient ($R^2$) of more than 0.9998. The limits of detection (LOD) and quantification (LOQ) of instrument were 0.0005 and $0.001{\mu}g/mL$, respectively, and the LOQ of analytical method calculated as 0.01 mg/kg. The average recoveries at three spiking levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n=5) were in the range of 71.2~95.4% with relative standard deviation of less than 12.1%. The developed method was simple and all optimized results was satisfied with the criteria ranges requested in the Codex guidelines and Food Safety Evaluation Department guidelines. The present study could be served as a reference for the establishment of maximum residue limits (MRL) of kasugamycin and be used as basic data for safety management relative to kasugamycin residues in imported and domestic agricultural products.
Journal of Korean Tunnelling and Underground Space Association
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v.21
no.1
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pp.61-77
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2019
If a new utility tunnel is planned for high density existing urban areas in Korea, a rational decision-making process such as the determination of optimum design capacity by using the feasibility evaluation system based on quantitative evaluation indexes and the economic evaluation is needed. Thus, the previous study presented the important weight of individual higher-level indexes (3 items) and sub-indexes (16 items) through a hierarchy analysis (AHP) for quantitative evaluation index items, considering the characteristics of each urban type. In addition, an economic evaluation method was proposed considering 10 benefit items and 8 cost items by adding 3 new items, including the effects of traffic accidents, noise reduction and socio-economic losses, to the existing items for the benefit cost analysis suitable for urban utility tunnels. This study presented a quantitative feasibility evaluation method using the important weight of 16 sub-index items such as the road management sector, public facilities sector and urban environment sector. Afterwards, the results of quantitative feasibility and economic evaluation were compared and analyzed in 123 main road sections of the Seoul. In addition, a comprehensive evaluation method was proposed by the combination of the two evaluation results. The design capacity optimization program, which will be developed by programming the logic of the quantitative feasibility and economic evaluation system presented in this study, will be utilized in the planning and design phases of urban community zones and will ultimately contribute to the vitalization of urban utility tunnels.
Journal of the Korean Applied Science and Technology
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v.36
no.1
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pp.324-332
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2019
Most countries including Korea and Indonesia have strong policy for implementing biofuels like biodiesel. Shortage of the oil feedstock is the main barrier for increasing the supply of biodiesel fuel. In this study, in order to improve the stability of feedstock supply and lower the biodiesel production cost, the feasibility of biodiesel production using two types of Indonesian tropical crop oils, pressed at different harvesting times, were investigated. R. Trisperma oils, a high productive non-edible feedstocks, were investigated to produce biodiesel by esterification and transesterification because of it's high impurity and free fatty acid contents. the kindly provided oils from Indonesia were required to perform the filtering and water removal process to increase the efficiency of the esterificaton and transesterification reactions. The esterification used heterogeneous acid catalyst, Amberlyst-15. Before the reaction, the acid value of two types oil were 41, 17 mg KOH/g respectively. After the pre-esterification reaction, the acid value of oils were 3.7, 1.8 mg KOH/g respectively, the conversions were about 90%. Free fatty acid content was reduced to below 2%. Afterwards, the transesterification was performed using KOH as the base catalyst for transesterification. The prepared biodiesel showed about 93% of FAME content, and the total glycerol content was 0.43%. It did not meet the quality specification(FAME 96.5% and Total glycerol 0.24%) since the tested oils were identified to have a uncommon fatty acid, generally not found in vegetable oils, ${\alpha}$-eleostearic acid with much contents of 10.7~33.4%. So, it is required to perform the further research on reaction optimization and product purification to meet the fuel quality standards. So if the biodiesel production technology using un-utilized non-edible feedstock oils is successfully developed, stable supply of the feedstock for biodiesel production may be possible in the future.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.2
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pp.139-147
/
2021
Livestock manure is used as an organic fertilizer to replace chemical fertilizers after sufficient fermentation in an aerobic bioreactor. On the other hand, liquid manure disposal problems occur repeatedly because soil spraying is restricted during the summer when the crops are growing. To use liquid fertilizer (LF) as an additional nutrient source for crops, it is necessary to reduce the amount of suspended solids (SS) in the liquid fertilizer and secure stability problems against pathogenic microorganisms. This study examined the effects of the simultaneous SS removal and E.coli sterilization in the LF using the microbubble (MB) generator (FeMgO catalyst insertion). The remaining SS were further removed using the integrated microbubble and microfilter system. During the floating process in the MB device, the SS were removed by 57.9%, and the coliform group was not detected (16,200→0 MPN/100 mL). By optimizing the HRT of the integrated system, the removal efficiency of the SS was improved by 92.9% under the 0.1h of HRT condition. After checking the properties of the treated LF, 64.5%, 70.1%, 54.9%, and 51.5% of the TCOD, SCOD, PO4-P, and TN, respectively, were removed. The treated effluent from such an integrated system has a lower SS content than that of the existing LF and does not contain coliforms; therefore, it can be used directly as an additional fertilizer.
Kim, Donggyu;Lee, Dongwook;Park, Jangwon;Oh, Sungwoo;Kwon, Sungjun;Lee, Inyong;Choi, Dongwon
Journal of Intelligence and Information Systems
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v.28
no.2
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pp.191-206
/
2022
Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.
Sung-Bean Chung;Min-Su Kim;Dae-Up Kim;Sung-Kil Hong
Journal of Korea Foundry Society
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v.42
no.6
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pp.337-346
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2022
In order to optimize the solution treatment conditions of Al-7Si-(0.3~0.5)Mg-(0~0.5)Cu alloys, a series of heat treatment experiments were conducted under various solution treatment times up to 7 hours at 545℃, followed by a microstructural analysis using optical microscopy, FE-SEM, and Brinell hardness measurements. Rapid coarsening of eutectic Si particles was observed in the alloys during the first 3 hours of solution treatment but the size of those Si particles did not change at longer solution treatment conditions. Meanwhile, the degree of spheroidisation of eutectic Si particles increased until the solution treatment time was increased up to 7 hours. Q-Al5Cu2Mg8Si6 andθ-Al2Cu were observed in as-cast Cu-containing Al alloys but the intermetallic compounds were dissolved completely after 3 hours of solution treatment at 545℃. Depending on the initial Mg composition of the Al alloys, π-Al8FeMg3Si either disappeared in the alloy with 0.3wt% of Mg content after 5 hours of solution treatment or remained in the alloy with 0.5wt% of Mg content after 7 hours of solution treatment time. Mg and Cu content in the primary-α phase of the Al alloys increased until the solution treatment time reached 5 hours, which was in accordance with the dissolution behavior of Mg or Cu-containing intermetallic compounds with respect to the solution treatment time. From the results of microstructural changes in the Al-7Si-Mg-Cu alloys during solution treatment, it was concluded that at least 5 hours of solution treatment at 545℃ is required to maximize the age hardening effect of the present Al alloys. The same optimal solution treatment conditions could also be derived from Brinell hardness values of the present Al-7Si-Mg-Cu alloys measured at different solution treatment conditions.
The Journal of Korean Society for Radiation Therapy
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v.34
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pp.51-60
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2022
Objectives: The purpose is to evaluate dosimetric performance and delivery efficiency of VMAT with Halcyon LINAC for double target spine SBRT Materials and Methods: 12 patients with spine oligometastases were retrospectively studied. Single-isocenter spine SBRT plans was established using Halcyon® with Dual Layer MLC and Truebeam® with High Definition MLC. All patients' plans were created in Eclipse TPS through the identical conditions and optimization. C.I, H.I, G.I (Gradient Index), maximal and volumetric doses to spinal cord and low dose area were evaluated for comparison of both plans. Also, total MU and BOT(Beam On Time) were evaluated. Results: Halcyon plans was no Statistical differences in C.I and H.I. However, the average of G.I was 4.64 for Halcyon, which decreased to 5.5% compared to Truebeam (P<0.001). Halcyon plans demonstrated statistically significant reduced G.I. The average of 50% and 25% isodose volume was 487.56 cc (-3.82%, P<0.001), 1859.45 cc (-4.75%, P<0.001) in Halcyon, respectively. Significantly reduced low dose spill were observed in Halcyon plans. In the evaluation of the spinal cord, the average of Dmean and V10 of Halcyon plans in the sample group with an overlap volume of less than 1 cc was 6.802 Gy (-3.504%, P=0.067), 5.766±1.683 cc (-8.199%, P=0.002), respectively. Halcyon plans demonstrated statistically significant reduced Dmean and V10. For delivery efficiency, MU and BOT(maximum dose rate for each machine), on average, increased in Halcyon plans. However, the average of BOT(800MU/min for each machine) was 648.33 sec for Halcyon (-1.74%, P<0.001). Conclusion: Halcyon plan for double-target spine SBRT demonstrated advantages in the low dose area with a steep dose gradient, while having dosimetrically equivalent target dose distribution and spinal cord protective effect. As a result, Halcyon LINAC produced a dosimetrically improved plan for double-target spine SBRT.
Korean Journal of Agricultural and Forest Meteorology
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v.25
no.2
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pp.80-98
/
2023
This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.
Young Jun Kim;Dukwon Bae;Jungho Im ;Sihun Jung;Minki Choo;Daehyeon Han
Korean Journal of Remote Sensing
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v.39
no.5_3
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pp.1043-1060
/
2023
An acceleration of climate change in recent years has led to increased attention towards 'blue carbon' which refers to the carbon captured by the ocean. However, our comprehension of marine ecosystems is still incomplete. This study classified and analyzed global marine eco-provinces using k-means clustering considering carbon cycling. We utilized five input variables during the past 20 years (2001-2020): Carbon-based Productivity Model (CbPM) Net Primary Production (NPP), particulate inorganic and organic carbon (PIC and POC), sea surface salinity (SSS), and sea surface temperature (SST). A total of nine eco-provinces were classified through an optimization process, and the spatial distribution and environmental characteristics of each province were analyzed. Among them, five provinces showed characteristics of open oceans, while four provinces reflected characteristics of coastal and high-latitude regions. Furthermore, a qualitative comparison was conducted with previous studies regarding marine ecological zones to provide a detailed analysis of the features of nine eco-provinces considering carbon cycling. Finally, we examined the changes in nine eco-provinces for four periods in the past (2001-2005, 2006-2010, 2011-2015, and 2016-2020). Rapid changes in coastal ecosystems were observed, and especially, significant decreases in the eco-provinces having higher productivity by large freshwater inflow were identified. Our findings can serve as valuable reference material for marine ecosystem classification and coastal management, with consideration of carbon cycling and ongoing climate changes. The findings can also be employed in the development of guidelines for the systematic management of vulnerable coastal regions to climate change.
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