• Polymer(Korea)
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• v.32 no.6
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• pp.509-515
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• 2008

The aminated polypropylene melt blown ion exchange fibers were synthesized with acrylic acid monomer onto polypropylene melt blown fibers by radiation-induced polymerization and subsequent amination. Degree of grafting was increased with increasing the acrylic acid monomer concentration and total dose. The highest degree of grafting was obtained 140% at a monomer concentration of 20 v/v% acrylic acid and total dose of 4 kGy. Optimum condition of Mohr's salt was 5.0 $\times10^{-3}$ M. Degree of amination was increased with increasing degree of grafting. Water content was about 1.5 times higher than that of trunk polymer. The maximum ion-exchange capacity was 7.3 meq/g which was 2$\sim$3 times higher than a commercial ion exchange fiber. The average pore size was decreased and BET surface area was increased in order of PPmb, PPmb- g- AAc and APPmb- g- AAc. The average pore size and BET surface area of synthesised fibers were $366.1\;{\AA},\;3.71m^2/g,\;143.3\;{\AA},\;4.94m^2/g,\;40.97\;{\AA},\;8.98m^2/g$, respectively.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.7-8
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• 2010

The surface conductive layer (SCL) of chemical vapor deposition (CVD) diamonds has attracting much interest. However, neither photoemission electron microscopic (PEEM) nor micro-spectroscopic (PEEMS) information is available so far. Since SCL retains in an ultra-high vacuum (UHV) condition, PEEM or PEEMS study will give an insight of SCL, which is the subject of the present study. The sample was made on a Ib-type HTHP diamond (001) substrate by non-doping CVD growthin a DC-plasma deposition chamber. The SCL properties of the sample in air were; a few tens K/Sq. in sheet resistance, ${\sim}180\;cm^2/vs$ in Hall mobility, ${\sim}2{\times}10^{12}/cm^2$ in carrier concentration. The root-square-mean surface roughness (Rq) of the sample was ~0.2nm as checked by AFM. A $2{\times}1$ LEED pattern and a sheet resistance of several hundreds K/Sq. in UHV were checked in a UHV chamber with an in-situ resist-meter [1]. The sample was then installed in a commercial PEEM/S apparatus (Omicron FOCUS IS-PEEM) which was composed of electro-static-lens optics together with an electron energy-analyzer. The presence of SCL was regularly monitored by measuring resistance between two electrodes (colloidal graphite) pasted on the two ends of sample surface. Figure 1 shows two PEEM images of a same area of the sample; a) is excited with a Hg-lamp and b) with a Xe-lamp. The maximum photon energy of the Hg-lamp is ~4.9 eV which is smaller that the band gap energy ($E_G=5.5\;eV$) of diamond and the maximum photon energy of the Xe-lamp is ~6.2 eV which is larger than $E_G$. The image that appear with the Hg-lamp can be due to photo-excitation to unoccupied states of the hydrogen-terminated negative electron affinity (NEA) diamond surface [2]. Secondary electron energy distribution of the white background of Figs.1a) and b) indeed shows that the whole surface is NEA except a large black dot on the upper center. However, Figs.1a) and 1b) show several features that are qualitatively different from each other. Some of the differences are the followings: the two main dark lines A and B in Fig.1b) are not at all obvious and the white lines B and C in Fig.1b) appear to be dark lines in Fig.1a). A PEEMS analysis of secondary electron energy distribution showed that all of the features A-D have negative electron affinity with marginal differences among them. These differences can be attributed to differences in the details of energy band bending underneath the surface present in SCL [3].

• Tunnel and Underground Space
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• v.23 no.3
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• pp.169-179
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• 2013

Well testing in unconventional reservoirs, such as tight or shale gas formations, presents considerable challenges. It is difficult to estimate the reservoir properties in ultra-low permeability formation because of poor inflow prior to stimulation and excessive test duration. Moreover, radial flow may not develop in hydraulically fractured horizontal wells. For these reasons, the cost of test is high and the accuracy is relatively low. Accordingly, industry is turning to an alternate testing method, diagnostic fracture injection test (DFIT), which is conducted prior to the main hydraulic fracture treatments. Nowadays, DFIT are regarded as the most practical way to obtain good estimates of reservoir properties in unconventional reservoirs. Various methods may be used for interpreting DFIT data. This paper gives an explanation of those methods in detail and examines three actual field data. These show how various analysis methods can be applied to consistently interpret fracture closure pressure and time, as well as before and after closure flow regimes and reservoir properties from field data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4460-4467
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• 2010

Recent advances in computer technology have brought more dependence on software to railway systems and changed to computer systems. Hence, the reliability and safety assurance of the vital software running on the embedded railway system is going to tend toward very critical task. Accordingly, various software test and validation activities are highly recommended in the international standards related railway software. In this paper, we presented an automated analysis tool and standard for software testing coverage in railway system, and presented its result of implementation. We developed the control flow analysis tool estimating test coverage as an important quantitative item for software safety verification in railway software. Also, we proposed judgement standards due to railway S/W Safety Integrity Level(SWSIL) based on analysis of standards in any other field for utilizing developed tool widely at real railway industrial sites. This tool has more advantage of effective measuring various test coverages than other countries, so we can expect railway S/W development and testing technology of real railway industrial sites in Korea.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1573-1587
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• 2021

A Drone image is an ultra-high-resolution image that is several or tens of times higher in spatial resolution than a satellite or aerial image. Therefore, drone image-based remote sensing is different from traditional remote sensing in terms of the level of object to be extracted from the image and the amount of data to be processed. In addition, the optimal scale and size of data used for model training is different depending on the characteristics of the applied deep learning model. However, moststudies do not consider the size of the object to be found in the image, the spatial resolution of the image that reflects the scale, and in many cases, the data specification used in the model is applied as it is before. In this study, the effect ofspatial resolution and image size of drone image on the accuracy and training time of the semantic segmentation deep learning model of six wintering vegetables was quantitatively analyzed through experiments. As a result of the experiment, it was found that the average accuracy of dividing six wintering vegetablesincreases asthe spatial resolution increases, but the increase rate and convergence section are different for each crop, and there is a big difference in accuracy and time depending on the size of the image at the same resolution. In particular, it wasfound that the optimal resolution and image size were different from each crop. The research results can be utilized as data for getting the efficiency of drone images acquisition and production of training data when developing a winter vegetable segmentation model using drone images.

• Korean Journal of Food Science and Technology
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• v.51 no.1
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• pp.90-96
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• 2019

Unripe astringent persimmon (Diospyros kaki Thunb. cv. Cheongdo-Bansi) is a by-product produced when thinning out the superfluous fruit of persimmon. We investigated whether unripe astringent persimmon has antioxidative and anti-inflammatory effects. Unripe astringent persimmon extract was fractionated sequentially in n-hexane, chloroform, ethyl acetate, n-butanol, and water. The ethyl acetate fraction had the highest total phenolic content, total flavonoid content, and antioxidant capacity compared to those of the other fractions. Pretreatment of lipopolysaccharide-stimulated RAW 264.7 macrophages with the ethyl acetate fraction reduced nitric oxide, interleukin-6, and intracellular oxidative stress in a dose-dependent manner. Ultra-high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry analysis revealed gallic acid, protocatechuic acid, 4-hydroxybenzoic acid, quercetin-3-O-glucoside, quercetin, and p-coumaric acid as the phenolic compounds of the ethyl acetate fraction. Collectively, these findings suggest that unripe astringent persimmon is a source of functional materials that can promote antioxidative and anti-inflammatory effects.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.115-123
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• 2018

Various types of robots running on power transmission lines have been developed for the purpose of line patrol monitoring. They usually have complex mechanism to run and avoid obstacles on the power line, but nevertheless did not show satisfactory performance for going over the obstacles. Moreover, they were so heavy that they could not be easily installed on the lines. To compensate these problems, flying robots have been developed and recently, multi-copter drones with flight stability have been used in the electric power industry. The drones could be remotely controlled by human operators to monitor power distribution lines. In the case of transmission line patrol, however, transmission towers are huge and their spans are very long, and thus, it is very difficult for the pilot to control the patrol drones with the naked eye from a long distance away. This means that the risk of a drone crash onto electric power facilities always resides. In addition, there exists another danger of electromagnetic interference with the drones on autopilot waypoint tracking under ultra-high voltage environments. This paper presents a patrol monitoring plan of autopilot drones for power transmission lines and its field tests. First, the magnetic field effect on an autopilot patrol drone is investigated. Then, how to build the flight path to avoid the magnetic interference is proposed and our autopilot drone system is introduced. Finally, the effectiveness of the proposed patrol plan is confirmed through its field test results in the 154 kV, 345 kV and 765 kV transmission lines in Chungcheongnam-do.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.777-785
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• 2021

Many utility lines are buried underground to provide various functions of the city. Because historical records are not managed systematically, damage has occurred during excavation. In addition, the demand for an underground facility management system is increasing as the aerial underground project is progressing. By attaching an electronic recognition sensor to an underground facility, such as pipelines, the management history and site conditions can be carefully managed. Therefore, in this study, electronic recognition sensors, such as BLE Beacon, UHF RFID, geomagnetic sensor, and commercial marker, were tested to analyze the strengths, weaknesses, and field applicability through a pilot project. According to the limited research results collected through two pilot projects, the installation depth is most important to demonstrate the performance of the electronic reader. In addition, because it should be used in urban areas, the influence of environmental interference should be minimized, and there should be no performance degradation over time. In the case of the geomagnetic recognizer, the effect of environmental interference was large, and performance degradation occurred over time using the BLE Beacon. In the field situation, where the installation depth can be controlled to less than 40cm, the utility of the battery-free UHF RFID was the best.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.11-18
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• 2021

Nano bubble water is used in various washing processes, including cleaning of solar panels, salt rejection of roads, and cleaning precision parts of machines. High cleaning efficiency and water conservation are obtained by applying nano bubbles during pretreatment of the marine waste cleaning system. This study compared the salt rejection of nano bubble water, and it was revealed that marine waste was produced by wood immersed in 200,000 mg/L NaCl solution. Using tap water and nano bubble water for washing, comparisons of the surface salt concentrations of wood were determined according to the nozzle, orifice diameter, pump speed and washing time. Decreased surface salt concentration was observed on the wood surface with increasing washing time. Water consumption was optimal between 5- and 10-seconds washing time. Increasing orifice diameter of the nozzle reduced the spraying pressure, with consequent increase in the wood surface salt concentration, thereby establishing the importance of orifice diameter of the nozzle. Compared to levels obtained with tap water, salt concentration of the wood surface after washing with nano bubble water was 2.2% lower with sector nozzle, and 30.9% lower with circular nozzle. In the washing experiment using nano bubble water, the salt concentration on the wood surface was about 9.5 mg/L lower when washed with sector nozzle than the circular nozzle.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1379-1391
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• 2020

UAV in the agricultural application are capable of collecting ultra-high resolution image. It is possible to obtain timeliness images for phenological phases of the crop. However, the UAV uses a variety of sensors and multi-temporal images according to the environment. Therefore, it is essential to use normalized image data for time series image application for crop monitoring. This study analyzed the variability of UAV reflectance and vegetation index according to Aviation Image Making Environment to utilize the UAV multispectral image for agricultural monitoring time series. The variability of the reflectance according to environmental factors such as altitude, direction, time, and cloud was very large, ranging from 8% to 11%, but the vegetation index variability was stable, ranging from 1% to 5%. This phenomenon is believed to have various causes such as the characteristics of the UAV multispectral sensor and the normalization of the post-processing program. In order to utilize the time series of unmanned aerial vehicles, it is recommended to use the same ratio function as the vegetation index, and it is recommended to minimize the variability of time series images by setting the same time, altitude and direction as possible.