• Title/Summary/Keyword: synthetic data

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A study on the stochastic generation of annual runoff (연유출량의 추계학적 모의발생에 관한 연구)

  • 이순혁;박명근;맹승진
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.37 no.2
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    • pp.31-40
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    • 1995
  • This study was conducted to get best fitting frequency distribution for the annual run- off and to simulate long series of annual flows by single-season first order Markov Model with comparison of statistical parameters which were derived from observed and synthetic flows at four watersheds in Seom Jin and Yeong San river systems. The results summarized through this study are as follows. 1. Hydrologic persistence of observed flows was acknowledged by the correlogram analysis. 2. A normal distribution of the annual runoff for the applied watersheds was confirmed as the best one among others by Kolmogorov-Smirnov test. 3. Statistical parameters were calculated from synthetic flows simulated by normal dis- tribution. In was confirmed that mean and standard deviation of simulated flows are much closer to those of observed data than except coefficient of skewness. 4. Hydrologic persistence between observed flows and synthetic flows simulated was also confirmed by the correlogram analysis. 5. It is to be desired that generation technique of synthetic flow in this study would be compared with other simulation techniques for the objective time series.

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Treatment Characteristics of Synthetic Wastewater using Immobilized Nitrobacteria, Denitrobacteria (고정화 질산균, 탈질균을 이용한 합성폐수의 처리 특성)

  • Won, Chan-Hee;Heo, Young-Duck;Yun, Jae-Seong
    • Journal of Korean Society of Water and Wastewater
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    • v.11 no.4
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    • pp.63-70
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    • 1997
  • The objectives of this study were to find out the optimum treatment conditions for removing nitrogen in a synthetic wastewater by using microorganisms immobilized with PVA-Freezing method. The samples used as influents to the laboratory scale treatment units were a synthetic wastewater. The experiments in this study were mainly directed to collect the data of nitrogen and organic matter removal efficiencies for the different hydraulic and internal recycle rates conditions, temperature and influent C/N ratios. The removal efficiencies of nitrogen and organic matters were investigated for the operating conditions of HRT 2~12hours, internal recycle rates 50~400%, temperatures $15{\sim}30^{\circ}C$ and C/N ratios 2.5~7.5. The adequate internal recycle rate for removing T-N and $BOD_5$ in the synthetic wastewater was found to be about 300% at the temperature of $30^{\circ}C$ when the ratio of carbon contents to the nitrogen (C/N) in the influent was around 5.5. Under these conditions, the final effluent concentrations of T-N and $BOD_5$ were 8.7 and 8.4 mg/l, respectively.

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Design and Verification of Spacecraft Pose Estimation Algorithm using Deep Learning

  • Shinhye Moon;Sang-Young Park;Seunggwon Jeon;Dae-Eun Kang
    • Journal of Astronomy and Space Sciences
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    • v.41 no.2
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    • pp.61-78
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    • 2024
  • This study developed a real-time spacecraft pose estimation algorithm that combined a deep learning model and the least-squares method. Pose estimation in space is crucial for automatic rendezvous docking and inter-spacecraft communication. Owing to the difficulty in training deep learning models in space, we showed that actual experimental results could be predicted through software simulations on the ground. We integrated deep learning with nonlinear least squares (NLS) to predict the pose from a single spacecraft image in real time. We constructed a virtual environment capable of mass-producing synthetic images to train a deep learning model. This study proposed a method for training a deep learning model using pure synthetic images. Further, a visual-based real-time estimation system suitable for use in a flight testbed was constructed. Consequently, it was verified that the hardware experimental results could be predicted from software simulations with the same environment and relative distance. This study showed that a deep learning model trained using only synthetic images can be sufficiently applied to real images. Thus, this study proposed a real-time pose estimation software for automatic docking and demonstrated that the method constructed with only synthetic data was applicable in space.

Construction and validation of a synthetic phage-displayed nanobody library

  • Minju Kim;Xuelian Bai;Hyewon Im;Jisoo Yang;Youngju Kim;Minjoo MJ Kim;Yeonji Oh;Yuna Jeon;Hayoung Kwon;Seunghyun Lee;Chang-Han Lee
    • The Korean Journal of Physiology and Pharmacology
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    • v.28 no.5
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    • pp.457-467
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    • 2024
  • Nanobodies derived from camelids and sharks offer unique advantages in therapeutic applications due to their ability to bind to epitopes that were previously inaccessible. Traditional methods of nanobody development face challenges such as ethical concerns and antigen toxicity. Our study presents a synthetic, phage-displayed nanobody library using trinucleotide-directed mutagenesis technology, which allows precise amino acid composition in complementarity-determining regions (CDRs), with a focus on CDR3 diversity. This approach avoids common problems such as frameshift mutations and stop codon insertions associated with other synthetic antibody library construction methods. By analyzing FDA-approved nanobodies and Protein Data Bank sequences, we designed sub-libraries with different CDR3 lengths and introduced amino acid substitutions to improve solubility. The validation of our library through the successful isolation of nanobodies against targets such as PD-1, ATXN1 and STAT3 demonstrates a versatile and ethical platform for the development of high specificity and affinity nanobodies and represents a significant advance in biotechnology.

Towards remote sensing of sediment thickness and depth to bedrock in shallow seawater using airborne TEM (항공 TEM 을 이용한 천해지역에서의 퇴적층 두께 및 기반암 심도 원격탐사에 관하여)

  • Vrbancich, Julian;Fullagar, Peter K.
    • Geophysics and Geophysical Exploration
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    • v.10 no.1
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    • pp.77-88
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    • 2007
  • Following a successful bathymetric mapping demonstration in a previous study, the potential of airborne EM for seafloor characterisation has been investigated. The sediment thickness inferred from 1D inversion of helicopter-borne time-domain electromagnetic (TEM) data has been compared with estimates based on marine seismic studies. Generally, the two estimates of sediment thickness, and hence depth to resistive bedrock, were in reasonable agreement when the seawater was ${\sim}20\;m$ deep and the sediment was less than ${\sim}40\;m$ thick. Inversion of noisy synthetic data showed that recovered models closely resemble the true models, even when the starting model is dissimilar to the true model, in keeping with the uniqueness theorem for EM soundings. The standard deviations associated with shallow seawater depths inferred from noisy synthetic data are about ${\pm}5\;%$ of depth, comparable with the errors of approximately ${\pm}1\;m$ arising during inversion of real data. The corresponding uncertainty in depth-to-bedrock estimates, based on synthetic data inversion, is of order of ${\pm}10\;%$. The mean inverted depths of both seawater and sediment inferred from noisy synthetic data are accurate to ${\sim}1\;m$, illustrating the improvement in accuracy resulting from stacking. It is concluded that a carefully calibrated airborne TEM system has potential for surveying sediment thickness and bedrock topography, and for characterising seafloor resistivity in shallow coastal waters.

Estimation of Design Flood Considering Time Distribution of Rainfall (강우 시간분포를 고려한 설계홍수량산정)

  • Park, Jae-Hyun;Ahn, Sang-Jin;Hahm, Chang-Hahk;Choi, Min-Ho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.1191-1195
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    • 2006
  • Now days, heavy storm occur to be continue. It is hard to use before frequency based on flood discharge for decision that design water pocket structure. We need to estimation of frequency based on flood discharge on the important basin likely city or basin that damage caused by flood recurrence. In this paper flood discharge calculated by Clark watershed method and SCS synthetic unit hydrograph method about upside during each minute of among time distribution method of rainfall, Huff method choosing Bocheong Stream basin that is representative basin of International Hydrologic Project (IHP) about time distribution of rainfall that exert big effect at flood discharge estimate to research target basin because of and the result is as following. Relation between probability flood discharge that is calculated through frequency analysis about flood discharge data and rainfall - runoff that is calculated through outward flow model was assumed about $48.1{\sim}95.9%$ in the case of $55.8{\sim}104.0%$, SCS synthetic unit hydrograph method in case of Clark watershed method, and Clark watershed method has big value overly in case of than SCS synthetic unit hydrograph method in case of basin that see, but branch of except appeared little more similarly with frequency flood discharge that calculate using survey data. In the case of Critical duration, could know that change is big area of basin is decrescent. When decide time distribution type of rainfall, apply upside during most Huff 1-ST because heavy rain phenomenon of upsides appears by the most things during result 1-ST about observation recording of target area about Huff method to be method to use most in business, but maximum value of peak flood discharge appeared on Huff 3-RD too in the case of upside, SCS synthetic unit hydrograph method during Huff 3-RD incidental of this research and case of Clark watershed method. That is, in the case of Huff method, latitude is decide that it is decision method of reasonable design floods that calculate applying during all $1-ST{\sim}4-TH$.

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3D LIDAR Based Vehicle Localization Using Synthetic Reflectivity Map for Road and Wall in Tunnel

  • Im, Jun-Hyuck;Im, Sung-Hyuck;Song, Jong-Hwa;Jee, Gyu-In
    • Journal of Positioning, Navigation, and Timing
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    • v.6 no.4
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    • pp.159-166
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    • 2017
  • The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

A Review on Deep-learning-based Phase Unwrapping Technique for Synthetic Aperture Radar Interferometry (딥러닝 기반 레이더 간섭 위상 언래핑 기술 고찰)

  • Baek, Won-Kyung;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.38 no.6_2
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    • pp.1589-1605
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    • 2022
  • Phase unwrapping is an essential procedure for interferometric synthetic aperture radar techniques. Accordingly, a lot of phase unwrapping methods have been developed. Deep-learning-based unwrapping methods have recently been proposed. In this paper, we reviewed state-of-the-art deep-learning-based unwrapping approaches in terms of 1) the approaches to predicting unwrapped phases, 2) deep learning model structures for phase unwrapping, and 3) training data generation. The research trend of the approaches to predicting unwrapped phases was introduced by categorizing wrap count segmentation, phase jump classification, phase regression, and deep-learning-assisted method. We introduced the case studies of deep learning model structure for phase unwrapping, and model structure optimization to relate the overall phase information. In addition, we summarized the research trend of the training data generation approaches in the views of phase gradient and noise in the main. And the future direction in deep-learning-based phase unwrapping was presented. It is expected that this paper is used as guideline for exploring future direction of deep-learning-based phase unwrapping research in Korea.

Arsenic Contamination of Groundwater a Grave Concern: Novel Clay-based Materials for Decontamination of Arsenic (V)

  • Amrita Dwivedi;Diwakar Tiwari;Seung Mok Lee
    • Applied Chemistry for Engineering
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    • v.34 no.2
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    • pp.199-205
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    • 2023
  • Arsenic is a highly toxic element, and its contamination is widespread around the world. The natural materials with high selectivity and efficiency toward pollutants are important in wastewater treatment technology. In this study, the mesoporous synthetic hectorite was synthesized by facile hydrothermal crystallization of gels comprising silica, magnesium hydroxide, and lithium fluoride. Additionally, the naturally available clay was modified using zirconium at room temperature. Both synthetic and modified natural clays were employed in the removal of arsenate from aquatic environments. The materials were fully characterized by scanning electron microscope (SEM), X-ray diffraction (XRD), and Fourier transform-infrared (FT-IR) analyses. The synthesized materials were used to remove arsenic (V) under varied physicochemical conditions. Both materials, i.e., Zr-bentonite and Zr-hectorite, showed high percentage removal of arsenic (V) at lower pH, and the efficiency decreased in an alkaline medium. The equilibrium-state sorption data agrees well with the Langmuir and Freundlich adsorption isotherms, and the maximum sorption capacity is found to be 4.608 and 2.207 mg/g for Zr-bentonite and Zr-hectorite, respectively. The kinetic data fits well with the pseudo-second order kinetic model. Furthermore, the effect of the background electrolytes study indicated that arsenic (V) is specifically sorbed at the surface of these two nanocomposites. This study demonstrated that zirconium intercalated synthetic hectorite as well as zirconium modified natural clays are effective and efficient materials for the selective removal of arsenic (V) from aqueous medium.

Analysis of Offshore Aquaculture Detection Techniques Using Synthetic Aperture Radar Images (레이더 영상을 이용한 연안 양식장 탐지 기법 분석)

  • Do-Hyun Hwang;Hahn Chul Jung
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1401-1411
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    • 2023
  • In the face of escalating utilization of the marine spatial domain, conflicts have emerged among stakeholders, necessitating effective management strategies beyond conventional government permits and regulations. Particularly within the domain of aquaculture, operational oversight relies on a localized licensing system, posing challenges in accurately assessing the prevailing circumstances. This research employs synthetic aperture radar (SAR) imagery as a tool to monitor coastal aquaculture fish farms, aimed at enhancing insights into management protocols. Leveraging Sentinel-1A imagery and time series SAR data integration, a superimposition technique is utilized, facilitating noise reduction while retaining crucial information regarding smaller-scale facilities, such as fish farms. Through analysis of VH polarization data, a detection overall accuracy of approximately 88% for coastal fish farms was achieved. The findings of this study offer potential applications in the continuous monitoring of aquaculture farms in correspondence with seasonal variations in aquaculture yields, thereby proposing frameworks for the establishment of effective management cycles for marine space utilization.