• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.134-145
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• 1998

The purpose of this paper is to construct a computer simulation system which can analyze and design the hydraulic excavator Theoretical analyses are performed on the hydraulic circuit and attachment of excavator with load sensing system. Databases are constructed for control valve opening areas, horsepower control and for load sensing regulator. For hydraulic components modularized programming techniques are applied which is expected to be utilized for software development of fluid power system. Through simulation an information of any point in hydraulic circuit can be obtained.

• International Journal of Contents
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• v.5 no.4
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• pp.62-68
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• 2009

This paper presents a novel method to design and implement mobile u-health system by defining the essential elements of mobile healthcare services. We choose common service elements for the proposed u-healthcare scheme and design the service platform. Especially we focus on automatic feces or urine sensing u-care scheme to prove the effectiveness of our platform. We construct the system with sensing part with a manikin and a diaper wireless communication part with feces or urine sensing data, and coordinator system based on the u-health platform defined in this paper. Experimental results show that our scheme is useful in the area of u-care service for the handicapped, the elderly, and patients who can hardly move by themselves. In addition the designed scheme offers a realized u-care scheme with the purpose of advanced developing tools for application or service developers.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.52 no.4
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• pp.393-402
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• 2007

Remote sensing data can be integrated into crop models, making simulation improved. A crop model that uses remote sensing data was evaluated for its capability, which was performed through comparing three different methods of canopy measurement for cotton(Gossypium hirsutum L.). The measurement methods used were leaf area index(LAI), hand-held remotely sensed perpendicular vegetation index(PVI), and satellite remotely sensed PVI. Simulated values of cotton growth and lint yield showed reasonable agreement with the corresponding measurements when canopy measurements of LAI and hand-held remotely sensed PVI were used for model calibration. Meanwhile, simulated lint yields involving the satellite remotely sensed PVI were in rough agreement with the measured lint yields. We believe this matter could be improved by using remote sensing data obtained from finer resolution sensors. The model not only has simple input requirements but also is easy to use. It promises to expand its applicability to other regions for crop production, and to be applicable to regional crop growth monitoring and yield mapping projects.

• Journal of Magnetics
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• v.18 no.2
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• pp.90-94
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• 2013

We designed a model composed of a ring type magnet, a yoke, and a sensing coil embedded in a projectile for simulating the muzzle velocity. The muzzle velocity was obtained from the master curve for the induced voltage at sensing coil and the velocity as the projectile pass through the magnetic field. The induced voltage and the projectile's velocity are fitted by the $2^{nd}$ order polynomial. The skin effect difference between projectiles which consist of aluminum-aluminum and aluminum-steel was small. The projectile will surely be burst at the pre-determined target area using the flight time and the projectile muzzle velocity calculated from the voltage induced at the sensing coil on the projectile.

• Ceramist
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• v.22 no.1
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• pp.96-106
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• 2019

Semiconducting carbon-based nanomaterials including single-walled carbon nanotubes(SWCNTs), multi-walled CNT(MWCNTs), graphene(GR), graphene oxide(GO), and reduced graphene oxide(RGO), are very promising sensing materials due to their large surface area, high conductivity, and ability to operate at room temperature. Despite of these advantages, the semiconducting carbon-based nanomaterials intrinsically possess crucial disadvantages compared with semiconducting metal oxide nanomaterials, such as relatively low gas response, irreversible recovery, and poor selectivity. Therefore, in this paper, we introduce a variety of strategies to overcome these disadvantages and investigate principle parameters to improve gas sensing performances.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.687-689
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• 2003

High resolution satellite images have huge amount of pixels in common. Thus, an efficient method is required for the generation of orthoimages. Patch backprojection method is a feasible way to improve the efficiency with respect to the point-by-point patch backprojection. We will propose an Adaptive Patch that optimizes the patch size for different terrain variations. The essence of the patch optimization is quadrate structuring for terrain variations. The area of interest is, thus, sequentially subdivided to four quadrate tiles until a preset criterion is met. The experiment results indicated that the proposed method is efficient without losing accuracy.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.327-338
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• 2000

The forest conditions of North Korea has been a great concern since it was known to be closely related to many environmental problems of the disastrous flooding, soil erosion, and food shortage. To assess the long-term changes of forest area as well as the canopy conditions, several sources of multitemporal satellite data were applied to the study area near Kaesung. KOMPSAT-1 EOC data were overlaid with 1981 topographic map showing the boundaries of forest to assess the deforestation area. Delineation of the cleared forest was performed by both visual interpretation and unsupervised classification. For analyzing the change of forest canopy condition, multiple scenes of Landsat and SPOT data were selected. After preprocessing of the multitemporal satellite data, such as image registration and normalization, the normalized difference vegetation index (NDVI) was derived as a representation of forest canopy conditions. Although the panchromatic EOC data had radiometric limitation to classify diverse cover types, they can be effectively used t detect and delineate the deforested area. The results showed that a large portion of forest land has been cleared for the urban and agricultural uses during the last twenty years. It was also found that the canopy condition of remaining forests has not been improved for the last twenty years. It was also found that the canopy condition of remaining forests has not been improved for the last twenty years. Possible causes of the deforestation and the temporal pattern of canopy conditions are discussed.

• Atmosphere
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• v.17 no.2
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• pp.125-133
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• 2007

Cloud amount calculation algorithm was developed using MTSAT-1R satellite data. The cloud amount is retrieved at 5 km ${\times}$ 5 km over the Korean Peninsula and adjacent sea area. The algorithm consists of three steps that are cloud detection, cloud type classification, and cloud amount calculation. At the first step, dynamic thresholds method was applied for detecting cloud pixels. For using objective thresholds in the algorithm, sensitivity test was performed for TBB and Albedo variation with temporal and spatial change. Detected cloud cover was classified into 3 cloud types (low-level cloud, cirrus or uncertain cloud, and cumulonimbus type high-level cloud) in second step. Finally, cloud amount was calculated by the integration method of the steradian angle of each cloud pixel over $3^{\circ}$ elevation. Calculated cloud amount was compared with measured cloud amount with eye at surface observatory for the validation. Bias, RMSE, and correlation coefficient were 0.4, 1.8, and 0.8, respectively. Validation results indicated that calculated cloud amount was a little higher than measured cloud amount but correlation was considerably high. Since calculated cloud amount has 5km ${\times}$ 5km resolution over Korean Peninsula and adjacent sea area, the satellite-driven cloud amount could show the possibility which overcomes the temporal and spatial limitation of measured cloud amount with eye at surface observatory.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.774-777
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• 2005

Dengue Fever(DF) and Dengue haemorrhagic fever(DHF) has become a major international public health concern. Dengue Fever(DF) and Dengue haemorrhagic Fever (DHF) is also still the major health problem of Thailand, although many campaigns against it have been conducted throughout the country. GIS and Remotely Sensed data are used to evaluate the relationships between socio-spatial, environmental factors/indicators and the incidences of viral diseases. The aim of the study is to identify the spatial risk factors in Dengue and Dengue Haemorrhagic Fever in Sukhothai province, Thailand using statistical, spatial and GIS Modelling. Preliminary results demonstrated that physical factors derived from remotely sensed data could indicate variation in physical risk factors affecting DF and DHF. The present study emphasizes the potential of remotely sensed data and GIS in spatial factors affecting Dengue Risk Zone analysis. The relationship between land cover and the cases of incidence of DF and DHF by information value method revaluated that highest information value is obtained for Built-up area. A negative relationship was observed for the forest area. The relations between climate data and cases of incidence have shown high correlation with rainfall factors in rainy season but poor correlation with temperature and relative humidity. The present study explores the potential of remotely sensed data and GIS in spatial analysis of factors affecting Dengue epidemic, strong spatial analysis tools of GIS. The capabilities of GIS for analyst spatial factors influencing risk zone has made it possible to apply spatial statistical analysis in Disease risk zone.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2018.06a
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• pp.101-101
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• 2018

Quantitative measurement of chloride ion concentration has an important role in various fields of electrochemistry, medical science, biology, metallurgy, architecture, etc. Among them, its importance of architecture is ever-growing due to unexpected degradations of building structure. These situations are caused by corrosion of reinforced concrete (RC) structure of buildings. And chloride ions are the most powerful factors of RC structure corrosion. Therefore, precise inspection of chloride ion concentration must be required to increase the accuracy of durability monitoring. Multi-walled Carbon nanotubes (MWCNTs) have high chemical resistivity, large surface area and superior electrical property. Thus, it is suitable for the channels of electrical signals made by the sensor. Silver nanoparticles were added to giving the sensing property. CuBTC, one of the metal organic frameworks (MOFs), was employed as a material to improve the sensing property because of its hydrophilicity and high surface area to volume ratio. In this study, sensing element was synthesized by various chemical reaction procedures. At first, MWCNTs were functionalized with a mixture of sulfuric acid and nitric acid because of enhancement of solubility in solution and surface activation. And functionalized MWCNTs, silver nanoparticles, and CuBTC were synthesized on PTFE membrane, one by one. Electroless deposition process was performed to deposit the silver nanoparticles. CuBTC was produced by room temperature synthesis. Surface morphology and composition analysis were characterized by scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDS), respectively. X-ray photoelectron spectroscopy (XPS) was also performed to confirm the existence of sensing materials. The electrical properties of sensor were measured by semiconductor analyzer. The chloride ion sensing characteristics were confirmed with the variation of the resistance at 1 V.