• Journal of Microbiology and Biotechnology
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• v.14 no.6
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• pp.1327-1332
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• 2004

The hemA gene encoding 5-aminolevulinic acid synthase (ALAS) was cloned from Rhodobacter capsulatus, and its nucleotide sequence was determined. DNA sequencing data revealed one open reading frame coding for a protein with 401 amino acids that displayed high similarity to the amino acid sequences of other known ALASs. The hemA gene was then cloned and expressed under the control of constitutive promotor in E. coli. The recombinant E. coli strain was able to accumulate 5-aminolevulinic acid to 21 mM in the liquid medium supplemented with 45 mM glycine and 120 mM succinate. In addition, a marked effect of the pH of the culture medium on ALA production was observed, and the optimum pH for culture medium was determined to be 5.8-6.3.

• Journal of Microbiology and Biotechnology
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• v.27 no.5
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• pp.939-942
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• 2017

The cellular composition and metabolic compounds of Leuconostoc mesenteroides ATCC 8293 were analyzed after cultivation in an anaerobic chemostat. The macromolecular composition was 24.4% polysaccharide, 29.7% protein, 7.9% lipid, 2.9% DNA, and 7.4% RNA. Its amino acid composition included large amounts of lysine, glutamic acid, alanine, and leucine. Elements were in the order of C > O > N > H > S. The metabolites in chemostat culture were lactic acid (73.34 mM), acetic acid (7.69 mM), and mannitol (9.93 mM). These data provide a first view of the cellular composition of L. mesenteroides for use in metabolic flux analysis.

• JSTS:Journal of Semiconductor Technology and Science
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• v.6 no.1
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• pp.10-15
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• 2006

Various sizes of erbium/platinum silicided n/p-type Schottky barrier metal-oxide-semiconductor field effect transistors (SB-MOSFETs) are manufactured from $20{\mu}m$ to 10nm. The manufactured SB-MOSFETs show excellent DIBL and subthreshold swing characteristics due to the existence of Schottky barrier between source and channel. It is found that the minimization of trap density between silicide and silicon interface and the reduction of the underlap resistance are the key factors for the improvement of short channel characteristics. The manufactured 10 nm n-type SBMOSFET showed $550{\mu}A/um$ saturation current at $V_{GS}-V_T$ = $V_{DS}$ = 2V condition ($T_{ox}$ = 5nm) with excellent short channel characteristics, which is the highest current level compared with reported data.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.08a
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• pp.73-73
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• 2010

Various organic- and bio-conjugated nanoparticles have been studied extensively for biological applications in medical diagnoses and drug delivery systems. Gold nanoparticles (AuNP) and poly(ethylene glycol) (PEG) are known biocompatible materials to be used in vivo and are becoming increasingly important in biomedical applications. In this work, we investigated the stability of PEG-conjugated AuNPs, dialysis and centrifuge effects after synthesis or pegylation of AuNPs as a function of elapsed time by using ToF-SIMS imaging technique along with dynamic light scattering (DLS), UV-visible absorption spectroscopic and statistical analyses. Roughly 15-nm-sized AuNPs were synthesized in a citrate-conjugated form, and then converted into the thiol-terminated PEG (O-[2-(3-Mercaptopropionylamino)ethyl]-O'-methylpolyethyleneglycol, M.W.=5 kDa) form. Based on our data, we will show that ToF-SIMS imaging analysis along with DLS, UV-visible absorption and statistical analyses would be a useful method to evaluate stability of PEG-conjugated AuNPs in various environmental conditions.

• Journal of Bio-Environment Control
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• v.23 no.3
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• pp.174-180
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• 2014

Standard weather data available to greenhouse environmental design are limited in most regions of the country. So, instead of using standard weather data, in order to find the method to build design weather data for greenhouse heating and cooling, design outdoor weather conditions were analyzed and compared by TAC method and frequency analysis using climatological normal and thirty years from 1981 to 2010 hourly weather data provided by KMA and standard weather data provided by KSES. Average TAC values of outdoor temperature, relative humidity and insolation using thirty years hourly weather data showed a good agreement with them using standard weather data. Therefore, in regions which are not available standard weather data, we suggest that design outdoor weather conditions should be analyzed using thirty years hourly weather data. Average of TAC values derived from every year hourly weather data during the whole period can be established as environmental design standards, and also minimum and maximum of them can be used as reference data.

• Journal of Soil and Groundwater Environment
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• v.18 no.1
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• pp.46-56
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• 2013

Laboratory scale experiments to remove benzene in solution by using the bio-carrier composed of dead biomass have been performed. The immobilized bio-carrier with dead Bacillus drentensis sp. and polysulfone was manufactured as the biosorbent. Batch sorption experiments were performed with bio-carriers having various quantities of biomass and then, their removal efficiencies and uptake capacities were calculated. From results of batch experiments, 98.0% of the initial benzene (1 mg/L) in 1 liter of solution was removed by using 40 g of immobilized bio-carrier containing 5% biomass within 1 hour and the biosorption reaction reached in equilibrium within 2 hours. Benzene removal efficiency slightly increased (99.0 to $99.4%{\pm}0.05$) as the temperature increased from 15 to $35^{\circ}C$, suggesting that the temperature rarely affects on the removal efficiency of the bio-carrier. The removal efficiency changed under the different initial benzene concentration in solution and benzene removal efficiency of the bio-carrier increased with the increase of the initial benzene concentration (0.001 to 10 mg/L). More than 99.0% of benzene was removed from solution when the initial benzene concentration ranged from 1 to 10 mg/L. From results of fitting process for batch experimental data to Langmuir and Freundlich isotherms, the removal isotherms of benzene were more well fitted to Freundlich model ($r^2$=0.9242) rather than Langmuir model ($r^2$=0.7453). From the column experiment, the benzene removal efficiency maintained over 99.0% until 420 pore volumes of benzene solution (initial benzene concentration: 1 mg/L) were injected in the column packed with bio-carriers, investigating that the immobilized carrier containing Bacillus drentensis sp. and polysulfone is the outstanding biosorbent to remove benzene in solution.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.5
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• pp.247-255
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• 2018

In this research, the effect of normal load, sliding velocity, and texture density on thefriction coefficient of surfaces micro-textured on AISI 4140 under paraffin oil lubrication were investigated. The predicted tribological behavior by numerical calculation can be serves as guidance for the designer during the machine development stage. Therefore, in this research friction coefficient prediction model based on response surface methodology (RSM), support vector machine (SVM), and artificial neural network (ANN) were developed. The experimental result shows that the variation of load, speed and texture density were influence the friction coefficient. The RSM, ANN and SVM model was successfully developed based on the experimental data. The ANN model can effectively predict the tribological characteristics of micro-textured AISI 4140 in paraffin oil lubrication condition compare to RSM and SVM.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.255-260
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• 2022

This study aimed to develop a service model that uses a deep learning algorithm for detecting diseases and pests in strawberries through image data. In addition, the pest detection performance of deep learning models was further improved by proposing segmented image data sets specialized in disease and pest symptoms. The CNN-based YOLO deep learning model was selected to enhance the existing R-CNN-based model's slow learning speed and inference speed. A general image data set and a proposed segmented image dataset was prepared to train the pest and disease detection model. When the deep learning model was trained with the general training data set, the pest detection rate was 81.35%, and the pest detection reliability was 73.35%. On the other hand, when the deep learning model was trained with the segmented image dataset, the pest detection rate increased to 91.93%, and detection reliability was increased to 83.41%. This study concludes with the possibility of improving the performance of the deep learning model by using a segmented image dataset instead of a general image dataset.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.433-441
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• 2007

The bio-Sensors, which are sensing the vital signs of human bodies, are largely used by the medical equipment. Recently, the sensor network technology, which composes of the sensor interface for small-seize hardware, processor, the wireless communication module and battery in small sized hardware, has been extended to the area of bio-senor network systems due to the advances of the MEMS technology. In this paper we have suggested a design and implementation of a health care information system(called u-EMS) using a bio-sensor network technology that is a combination of the bio-sensor and the sensor network technology. In proposed system, we have used the following vital body sensors such as EKG sensor, the blood pressure sensor, the heart rate sensor, the pulse oximeter sensor and the glucose sensor. We have collected various vital sign data through the sensor network module and processed the data to implement a health care measurement system. Such measured data can be displayed by the wireless terminal(PDA, Cell phone) and the digital-frame display device. Finally, we have conducted a series of tests which considered both patient's vital sign and context-awared information in order to improve the effectiveness of the u-EMS.

• Journal of Biosystems Engineering
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• v.32 no.5
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• pp.324-331
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• 2007

The purpose of this study is to analysis effects of defect factors of combine header for cutting speed of combine header, feeding depth of straw, and cylinder speed of thresher. Measurement system for defect factors was consists of sensors to monitor the combine operation and I/O interface to convert the signals. Cutting speed of combine header, feeding depth of straw, cylinder speed of thresher were measured and analyzed. The data were collected from three paddy field during rice harvesting. The tests were conducted at different grounding speeds, lug troubles, and cutter condition. The one way ANOVA and the multiple comparison tests were performed. The results showed that the measured data were useful to monitor the defect factors of combine during harvesting. The faults conditions of grounding speeds, lug troubles, and cutter conditions affected cutting speeds, feeding depths and cylinder speeds of the combine. The data seem to be useful to analysis the faults conditions of combine header.