• Korean Journal of Environmental Agriculture
• /
• v.29 no.3
• /
• pp.273-281
• /
• 2010

Concentration of antibiotics including a tetracycline group (TCs) of tetracycline (TC), chlortetracycline (CTC), and oxytetracycline (OTC), a sulfonamide group (SAs) of sulfamethoxazole (SMX), sulfathiazole (STZ), and sulfamethazine (SMT), an ionophore group (IPs) of lasalocid (LSL), monensin (MNS), and salinomycin (SLM), and a macrolide group (MLs) of tylosin (TYL) was determined from samples collected from the agricultural soil, stream water, and sediment. For the agricultural soil samples, the concentration of TCs had the highest value among all tested antibiotic's groups due to its high accumulation rate on the surface soils. The lower concentrations of SAs in the agricultural soils may be resulted from its lower usage and lower distribution coefficient (Kd) compared to TCs. The concentration of TCs in stream water was significantly increased through June to September. It would be likely due to soil loss during an intensive rainfall event and a reduction of water level after the monsoon season. A significant amount of TCs in the sediment was also detected due to its accumulation from runoff, which occurred by complexation of divalent cations, ion exchange, and hydrogen bonding among humic acid molecules. To ensure environmental or human safety, continuous monitoring of antibiotics residues in surrounding ecosystems and systematic approach to the occurrence mechanism of antibiotic resistant bacteria are required.

• The Bulletin of The Korean Astronomical Society
• /
• v.43 no.1
• /
• pp.64.1-64.1
• /
• 2018

SNe light curves have been used to understand the expansion history of the universe, and a lot of efforts have gone into understanding the overall shape of the radioactively powered light curve. However, we still have little direct observational evidence for the theorized SN progenitor systems. Recent studies suggest that the light curve of a supernova shortly after its explosion (< 1 day) contains valuable information about its progenitor system and can be used to set a limit on the progenitor size, R*. In order to catch the early light curve of SNe explosion and understand SNe progenitors, we are performing a ~8hr interval monitoring survey of nearby galaxies (d < 50 Mpc) with 1-m class telescopes around the world. Through this survey, we expect to catch the very early precursor emission as faint as R=21 mag (~0.1 Rsun for the progenitor). In this poster, we outline this project, and present a few scientific highlights, such as the early light curve of SN 2015F in NGC 2442.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.47 no.6
• /
• pp.10-21
• /
• 2010

In the cluster-tree network which covers wide area network and has many nodes for monitoring purpose traffic is concentrated around the sink. There are long transmit delay and high data loss due to the intensive traffic when IEEE 802.15.4 is adapted to the cluster-tree network. In this paper we propose Dynamic Channel Allocation algorithm which dynamically allocates channels to increase the channel usage and the transmission success rate. To evaluate the performance of DCA, we assumed the monitoring network that consists of a cluster-tree in which sensing data is transmitted to the sink. Analysis uses the traffic data which is generated around the sink. As a result, DCA is superior when much traffic is generated. During the experiment assuming the least amount of traffic, IEEE 802.15.4, has the minimum length of active period and 90% data transmission success rate. However DCA maintains 11.8ms of active period length and results in 98.9% data transmission success rate.

• Journal of Wetlands Research
• /
• v.20 no.4
• /
• pp.314-321
• /
• 2018

In order to quantify nonpoint source pollution, it was proposed to sample at regular intervals of 1 hour for the first 24 hours of storm runoff process by National Institute of Environmental Research for the mixed landuse watershed. However, high frequency sampling requires intensive laboratory analysis and labor costs. In order to investigate the effect of longer sampling interval on the load estimation compared to the 1 hour sampling method, analysis was conducted using monitoring data from rural subwatershed, urban subwatershed, and outlet of the Pungyeongjeongcheon watershed. Statistical analysis revealed that mean of load estimation was not significantly different up to 4 hour sampling frequency. However, 3 hour sampling interval was found to be appropriate for the BOD and TP when it is judged that 10% or less of the difference in loading amount between the 1 hour and other sampling interval is reasonable. The results of this study can be used to conduct an effective monitoring system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.6
• /
• pp.671-679
• /
• 2020

In order to increase the food self-sufficiency rate, monitoring and analysis of crop conditions in the cultivated area is important, and the existing measurement methods in which agricultural personnel perform measurement and sampling analysis in the field are time-consuming and labor-intensive for this reason inefficient. In order to overcome this limitation, it is necessary to develop an efficient method for monitoring crop information in a small area where many exist. In this study, RGB images acquired from unmanned aerial vehicles and vegetation index calculated using RGB image were applied as deep learning input data to classify complex upland crops in small farmland. As a result of each input data classification, the classification using RGB images showed an overall accuracy of 80.23% and a Kappa coefficient of 0.65, In the case of using the RGB image and vegetation index, the additional data of 3 vegetation indices (ExG, ExR, VDVI) were total accuracy 89.51%, Kappa coefficient was 0.80, and 6 vegetation indices (ExG, ExR, VDVI, RGRI, NRGDI, ExGR) showed 90.35% and Kappa coefficient of 0.82. As a result, the accuracy of the data to which the vegetation index was added was relatively high compared to the method using only RGB images, and the data to which the vegetation index was added showed a significant improvement in accuracy in classifying complex crops.

• Journal of Appropriate Technology
• /
• v.5 no.2
• /
• pp.70-81
• /
• 2019

The garment industry is one of the most labor-intensive manufacturing industries, with its sewing process relying almost entirely on manual labor. Its costs highly depend on the efficiency of this production line and thus is crucial to determine the production rate in real-time for line balancing. However, current production tracking methods are costly and make it difficult for many Small and Medium-sized Enterprises (SMEs) to implement them. As a result, their reliance on manual counting of finished products is both time consuming and prone to error, leading to high manufacturing costs and inefficiencies. In this paper, a production tracking system that uses the sewing machines' energy consumption data to track and count the total number of sewing tasks completed through Convolutional Neural Network (CNN) classifiers is proposed. This system was tested on two target sewing tasks, with a resulting maximum classification accuracy of 98.6%; all sewing tasks were detected. In the developing countries, the garment sewing industry is a very important industry, but the use of a lot of capital is very limited, such as applying expensive high technology to solve the above problem. Applied with the appropriate technology, this system is expected to be of great help to the garment industry in developing countries.

• Smart Structures and Systems
• /
• v.32 no.4
• /
• pp.267-279
• /
• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

• Tuberculosis and Respiratory Diseases
• /
• v.57 no.4
• /
• pp.329-335
• /
• 2004

Background : The Sequential Organ Failure Assessment (SOFA) score can help to assess organ failure over time and is useful to evaluate morbidity. The aim of this study is to evaluate the performance of SOFA score as a descriptor of multiple organ failure in critically ill patients in a local unit hospital, and to compare with APACHE III scoring system. Methods : This study was carried out prospectively. A total of ninety one patients were included who admitted to the medical intensive care unit (ICU) in Chuncheon Sacred Heart Hospital from May 1 through June 30, 2000. We excluded patients with a length of stay in the ICU less than 2 days following scheduled procedure, admissions for ECG monitoring, other department and patients transferred to other hospital. The SOFA score and APACHE III score were calculated on admission and then consecutively every 24 hours until ICU discharge. Results : The ICU mortality rate was 20%. The non-survivors had a higher SOFA score within 24 hours after admission. The number of organ failure was associated with increased mortality. The evaluation of a subgroup of 74 patients who stayed in the ICU for at least 48 hours showed that survivors and non-survivors followed a different course. In this subgroup, the total SOFA score increased in 81% of the non-survivors but in only 21% of the survivors. Conversely, the total SOFA score decreased in 48% of the survivors compared with 6% of the non-survivors. The non-survivors also had a higher APACHE III score within 24 hours and there was a correlation between SOFA score and APACHE III score. Conclusion : The SOFA score is a simple, but effective method to assess organ failure and to predict mortality in critically ill patients. Regular and repeated scoring enables patient's condition and clinical course to be monitored and better understood. The SOFA score well correlates with APACHE III score.

• Pediatric Infection and Vaccine
• /
• v.28 no.3
• /
• pp.133-143
• /
• 2021

Purpose: This study aimed to determine the incidence of central line-associated bloodstream infection (CLABSI) in the neonatal intensive care unit (NICU), evaluate the patients' clinical characteristics, and identify the etiologic agents for guidance in prevention and treatment. Methods: A retrospective chart review study of infants classified as having CLABSI was conducted at the NICU of Seoul National University Bundang Hospital from January 2016 to December 2020. Results: Of the 45 infants, 53 had CLABSIs within a follow-up period of 18,622 catheter days. The incidence of CLABSIs was 2.85 per 1,000 catheter days. The most common catheter type was a peripherally inserted central catheter (n=47, 81%). A total of 57 pathogens were isolated, of which 57.9% (n=33) were Gram-positive bacteria, 36.8% (n=21) were Gram-negative bacteria, and 5.3% (n=3) were Candida spp. The most common pathogens were Staphylococcus aureus (n=12, 21%) and coagulase-negative staphylococci (n=12, 21%), followed by Klebsiella aerogenes (n=8, 14%). The median duration of bacteremia was 2 days, and 19 episodes showed bacteremia for 3 days or more. The mortality rate of infants within 14 days of CLABSI was 13.3% (n=6). Conclusions: This study analyzed the incidence of CLABSI and the distribution of pathogens in the NICU. Continuous monitoring of CLABSI based on active surveillance serves as guidance for empiric antibiotic use and also serves as a tool to assess the necessity for implementation of prevention strategies and their impact.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.13 no.1
• /
• pp.1-14
• /
• 2008

Eight comprehensive oceanographic cruises on a squared $30{\times}30\;km$ area have been made to investigate the short and long-term impacts on the water qualities due to the sand mining operations at Exclusive Economic Zone (EEZ) in the central Yellow Sea from 2004 to 2007. The area was categorized to 'Sand Mining Zone', 'Potentially Affected Zone', and 'Reference Zone'. The investigation covered suspended solids, nutrients (nitrate, nitrite, ammonium, phosphate), and chlorophyll-a in seawater and several parameters such as water temperature, salinity, pH, and ORP. Additionally, several intensive water collections were made to trace the suspended solids and other parameters along the turbid water by sand mining activities. The comprehensive investigation showed that suspended solids, nitrate, chlorophyll-a and ORP be sensitively responding parameters of seawater by sand mining operations. The intensive collection of seawater near the sand mining operation revealed that each parameter show different distribution pattern: suspended solids showed an oval-shaped distribution of the north-south direction of 8 km wide and the east-west direction of 5 km wide at the surface and bottom layers. On the other hand, phosphate showed so narrow distribution not to traceable. Also ammonium showed a limited distribution, but its boundary was connected to the high nitrate and chlorophyll-a concentrations with high N/P ratios. From the last 4 years of the comprehensive and intensive investigations, we found that suspended solids, ammonium, nitrate, chlorophyll-a, and ORP revealed the sensitive parameters of water quality for tracing the sand mining operations in seawater. Especially suspended solids and ORP would be useful tracers for monitoring the water qualities of remote area like EEZ in Yellow Sea.