• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.235-237
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• 2003

GIS became increasingly important in information-oriented society as social indirect capital and many GIS data are developed. To use these data effectively standard format that enables easy to transport and store is needed. For this purpose, OGC developed GML based on XML as web standard format of geographical information. In this study, web based mapping with respect to digital geologic map and gravity anomaly map was accomplished using GML. While, styling methods were implemented in XSLT to make the visualizing suitable for the character of each layer, so it is possible to make dynamic maps in the SVG. GML-base map produced in this study can be transferred and represented without loss of the meaning and degrading on the web.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.88-91
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• 2003

Crystalline carbon nitride films have been attempted for an application of humidity sensors. The films were deposited on $Al_2O_3$ substrate having interdigitated electrodes by reactive RF magnetron sputtering system. The film revealed a good humidity-resistance characteristics as well as humidity-capacitance ones in the humidity range of $10\;{\sim}\;95\;RH(%)$. Temperature dependence was also investigated. These results suggest that carbon nitride film have a possibility for a new humidity-sensitive materials.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.9-9
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• 2000

For the planning of future land use for economic activities, an essential component is the identification of the vulnerable areas for natural hazard and environmental impacts from the activities. Also, exploration for mineral and energy resources is carried out by a step by step approach. At each step, a selection of the target area for the next exploration strategy is made based on all the data harnessed from the previous steps. The uncertainty of the selected target area containing undiscovered resources is a critical factor for estimating the exploration risk. We have developed not only spatial prediction models based on adapted artificial intelligence techniques to predict target and vulnerable areas but also validation techniques to estimate the uncertainties associated with the predictions. The prediction models will assist the scientists and decision-makers to make two critical decisions: (i) of the selections of the target or vulnerable areas, and (ii) of estimating the risks associated with the selections.

• Journal of Welding and Joining
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• v.16 no.3
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• pp.85-94
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• 1998

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding system, is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. In this paper, developed vision processing techniques are detailed, and their application in welding fabrication is covered. The software for joint tracking system is finally proposed.

• Journal of Electrochemical Science and Technology
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• v.10 no.3
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• pp.294-301
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• 2019

The quasi-solid-state hybrid electrolytes were synthesized by chemical cross-linking reaction of methacrylate-functionalized $SiO_2$ ($MA-SiO_2$) and tetra (ethylene glycol) diacrylate in aqueous electrolyte. A quasi-solid-state electrolyte synthesized by 6 wt.% $MA-SiO_2$ exhibited a high ionic conductivity of $177mS\;cm^{-1}$ at room temperature. The electrochemical $H_2$ sensor assembled with quasi-solid-state electrolyte showed relatively fast response and high sensitivity for hydrogen gas at ambient temperature, and exhibited better durability and stability than the liquid electrolyte-based sensor. The simple construction of the sensor and its sensing characteristics make the quasi-solid-state hydrogen sensor promising for practical application.

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.1-11
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• 2021

Soft robotics has attracted a huge amount of interest in the recent decade or so, be it either actuators or sensors. Recently, a soft optical waveguide sensor has proven its effectiveness for various sensing applications such as strain, force, and bending measurements. The operation principle of the waveguide is simple, but the present technology is far too much complex to manufacture the waveguide. The waveguide fails to attract various practical applications in comparison to other types of sensors despite its superior safety and ease working principle. This study pursues to develop the soft sensors based on the optical phenomena so that the waveguide can be easily manufactured and its design can be conducted. Several physical properties of the waveguide are confirmed through the repetitive experiments in the aspects of strain, force, and bending of the waveguide. Finally, the waveguide sensor is embedded inside the actuator to verify the effectiveness of the proposed waveguide as well as to extend the application fields of the waveguide sensor.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.6
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• pp.766-772
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• 1986

SnO2/Pt CO gas sensors operating at relatively low temperature were fabricated, and their performance characteristics were measured. When the mixing weight ratio of SnO2/Pt was 99.5/0.5, a good sensitivity to CO gas was obtained. And the experimental results were in consistent with the gas sensing model. The optimum operating, temperature range of the fabricated devices was 50-80\ulcorner and the response time was 15 sec. at 80\ulcorner in 1000 ppm CO ambient. The humidity dependence of sensitibity to CO gas could be reduced by adding hydrophokbic silica to the mixture of SnO2 and Pt. For the practical application of the fabricated devices, a CO gas alarming system has been developed.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.641-659
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• 2010

Structural Health Monitoring (SHM) gradually becomes a technique for ensuring the health and safety of civil infrastructures and is also an important approach for the research of the damage accumulation and disaster evolving characteristics of civil infrastructures. It is attracting prodigious research interests and the active development interests of scientists and engineers because a great number of civil infrastructures are planned and built every year in mainland China. In a SHM system the sheer number of accompanying wires, fiber optic cables, and other physical transmission medium is usually prohibitive, particularly for such structures as offshore platforms and long-span structures. Fortunately, with recent advances in technologies in sensing, wireless communication, and micro electro mechanical systems (MEMS), wireless sensor technique has been developing rapidly and is being used gradually in the SHM of civil engineering structures. In this paper, some recent advances in the research, development, and implementation of wireless sensors for the SHM of civil infrastructures in mainland China, especially in Dalian University of Technology (DUT) and Harbin Institute of Technology (HIT), are introduced. Firstly, a kind of wireless digital acceleration sensors for structural global monitoring is designed and validated in an offshore structure model. Secondly, wireless inclination sensor systems based on Frequency-hopping techniques are developed and applied successfully to swing monitoring of large-scale hook structures. Thirdly, wireless acquisition systems integrating with different sensing materials, such as Polyvinylidene Fluoride(PVDF), strain gauge, piezoresistive stress/strain sensors fabricated by using the nickel powder-filled cement-based composite, are proposed for structural local monitoring, and validating the characteristics of the above materials. Finally, solutions to the key problem of finite energy for wireless sensors networks are discussed, with future works also being introduced, for example, the wireless sensor networks powered by corrosion signal for corrosion monitoring and rapid diagnosis for large structures.

• Korean Journal of Remote Sensing
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• v.30 no.3
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• pp.341-350
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• 2014

Landsat images can monitor the snow-covered Earth surface variations with the ground resolution of 30m and the multi-spectral bands in the visible, NIR, SWIR and TIR spectral regions for the last 30 years. The Southern Volcanic Zone (SVZ) of Chile consists of many volcanoes, and all of the volcanoes are covered with snow at the top of mountain. Snow cover area in southern province of the SVZ of Chile (37 to $46^{\circ}S$) have been influenced by significant frontal retreats as well as eruptive activities. In this study, we have investigated the changes of the snow-cover area and snow-line elevation at Mt. Villarrica and Mt. Llaima, Chile from three Landsat images acquired on Feb. 1990, 2005 and 2011. The snow-cover areas are 13.42, 26.75 and $21.60km^2$ at Mt. Villarrica in 1990, 2005 and 2011, respectively, and 3.82, 25.12 and $8.89km^2$ at Mt. Llaima in 1990, 2005 and 2011, respectively. The snow-line elevations are 1871, 1738 and 1826m at Mt. Villarrica in 1990, 2005 and 2011, respectively, and 2007, 1822 and 1818m at Mt. Llaima in 1990, 2005 and 2011, respectively. The results indicate that both of the snow-cover and snow-line changes are strongly related with the volcanic activity change. The results demonstrate that the snow-cover area and snow-line elevation changes can be used as an indicator of the volcanic activity at Mt. Villarrica and Mt. Llaima, Chile.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.