• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.8
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• pp.702-709
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• 2016

By means of the our satellite development for the past 20 years, it ensure us to obtain domestic independent development capabilities. In the case of practical-class Low-Earth Orbit(LEO) remote sensing satellites, we become a world-class developer. Furthermore, we acquire the technology to develop domestic-leading geostationary satellites, depending on the mission. Currently, we proceed with the next-generation mid-size satellite development program featuring standard bus for the expansion of the world market and has embarked on the development of lunar orbiter from this year.

• Proceedings of the KSRS Conference
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• v.2
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• pp.721-724
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• 2006

Among many sources of soil and water pollution, former mining regions also play an important role in distribution and scope of pollution. In response, KMRC has made an investigation into the status mine hazard at the abandoned metalliferous mine area in Korea. In this study, we analyzed distribution of mine hazards at abandoned metalliferous mines using GIS. We considered the distribution of mine hazards and its magnitude for each abandoned mine and displayed the mine hazard index (MHI) using GIS. We divided the MHI value for each mine into 5 classes, and displayed the first class as smallest point symbol and the last class as biggest point symbol. The biggest symbol shows the most serious status of mine hazards. This GIS function was included in the AMGIS system KMRS are running, and it would be helpful to make decision of reclamation priority at abandoned metalliferous mine area.

• Proceedings of the KSRS Conference
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• v.2
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• pp.647-650
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• 2006

Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed (1756 square miles) in Ohio, U.S.A., which is one of the largest hyperspectral image acquisition. For the development of a 4m-resolution land cover dataset, a hierarchical approach was employed using two different classification algorithms: 'Image Object Segmentation' for level-1 and 'Spectral Angle Mapper' for level-2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination. The land cover class members were lentic, lotic, forest, corn, soybean, wheat, dry herbaceous, grass, urban barren, rural barren, urban/built, and unclassified. The final phase of processing was completed after an extensive Quality Assurance and Quality Control (QA/QC) phase. With respect to the eleven land cover class members, the overall accuracy with a total of 902 reference points was 83.9% at 4m resolution. The dataset is available for public research, and applications of this product will represent an improvement over more commonly utilized data of coarser spatial resolution such as National Land Cover Data (NLCD).

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.378-381
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• 2008

The regulating and relaxing targets in the Land Use Regulation and Total Maximum Daily Loads are influenced by Land cover information. For the providing more accurate land information, this study attempted to generate an impervious surface map using KOMPSAT-2 image which a Korea manufactured high resolution satellite image. The classification progress of this study carried out by tasseled-cap spectral enhancement through each class extraction technique neither existing classification method. KOMPSAT-2 image of this study is enhanced by Soil Brightness Index(SBI), Green vegetation Index(GVI), None-Such wetness Index(NWI). Then ranges of extracted each index in enhanced image are determined. And then, Confidence Interval of classes was determined through the calculating Non-exceedance Probability. Spectral distributions of each class are changed according to changing of Control coefficient(${\alpha}$) at the calculated Non-exceedance Probability. Previously, Land cover classification map was generated based on established ranges of classes, and then, pervious and impervious surface was reclassified. Finally, impervious ratio of reclassified impervious surface map was calculated with blocks in the study area.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.195-200
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• 2008

The accuracy of classifying pixels in HIRIS images is usually degraded by noisy bands since noisy bands may deform the typical shape of spectral reflectance. Proposed in this paper is a statistical method for noisy band removal which mainly makes use of the correlation coefficients between bands. Considering each band as a random variable, the correlation coefficient measures the strength and direction of a linear relationship between two random variables. While the correlation between two signal bands is high, existence of a noisy band will produce a low correlation due to ill-correlativeness and undirectedness. The application of the correlation coefficient as a measure for detecting noisy bands is under a two-pass screening scheme. This method is independent of the prior knowledge of the sensor or the cause resulted in the noise. The classification in this experiment uses the unsupervised k-nearest neighbor algorithm in accordance with the well-accepted Euclidean distance measure and the spectral angle mapper measure. This paper also proposes a hierarchical combination of these measures for spectral matching. Finally, a separability assessment based on the between-class and within-class scatter matrices is followed to evaluate the performance.

• 한국공간정보시스템학회:학술대회논문집
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• 2002.03a
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• pp.45-52
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• 2002

Artificial neural networks (ANN) have been successfully used for classifying remotely sensed imagery. However, ANN still is not the preferable choice for classification over the conventional classification methodology such as the maximum likelihood classifier commonly used in the industry production environment. This can be attributed to the ANN characteristic built-in stochastic process that creates difficulties in dealing with unequally represented training classes, and its training performance speed. In this paper we examined some practical aspects of training classes when using a back propagation neural network model for remotely sensed imagery. During the classification process of remotely sensed imagery, representative training patterns for each class are collected by polygons or by using a region-growing methodology over the imagery. The number of collected training patterns for each class may vary from several pixels to thousands. This unequally populated training data may cause the significant problems some neural network empirical models such as back-propagation have experienced. We investigate the effects of training over- or under- represented training patterns in classes and propose the pattern repopulation algorithm, and an adaptive alpha adjustment (AAA) algorithm to handle unequally represented classes. We also show the performance improvement when input patterns are presented in random fashion during the back-propagation training.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.37-37
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• 2003

Rice is one of the most important crop in the world and is a major export of Thailand. Optical sensors are not useful for rice monitoring, because most cultivated areas are often obscured by cloud during the growing period, especially in South East Asia. Spaceborne Synthetic Aperture Radar (SAR) such as RADARSAT, can see through regardless of weather condition which make it possible to monitor rice growth and to retrieve rice acreage, using the unique temporal signature of rice fields. This paper presents the result of a study of examining the backscatter behavior of rice using multi-temporal RADARSAT dataset. Ground measurements of paddy parameters and water and soil condition were collected. The ground truth information was also used to identify mature rice crops, orchard, road, residence, and aquaculture ponds. Land use class distributions from the RADARSAT image were analyzed. Comparison of the mean DB of each land use class indicated significant differences. Schematic representation of temporal backscatter of rice crop were plotted. Based on the study carried out in Pathum Thani Province test site, the results showed variation of sigma naught from first tillering vegatative phase until ripenning phase. It is suggested that at least, three radar data acquisitions taken at 3 stages of rice growth circle namely; those are at the beginning of rice growth when the field is still covered with water, in the ear differentiation period, and at the beginning of the harvest season, are required for rice monitoring. This pilot project was an experimental one aiming at future operational rice monitoring and potential yield predicttion.

• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.267-274
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• 2024

One challenge with teaching practical programming classes is the standardization of development tools on student computers. This is particularly true when a complicated setup process is required before beginning to code, or in remote classes, such as those necessitated by the COVID-19 pandemic, where the instructor cannot provide individual troubleshooting assistance. In such cases, students who encounter problems during the setup process may give up on the class altogether before even beginning to code. Therefore, this paper recommends using GitHub Codespaces as a tool for implementing standardized student development environments from day one. Codespaces provides Docker containers that an instructor can configure in such a way as to enable students to practice installing various coding tools within a controlled space, while also providing a language-specific, fully optimized development environment. In addition, Codespaces may be used more effectively in collaboration with GitHub Classroom, which helps instructors manage both the starter code and coding environment in which students work. In this paper, we compare two semesters of university Node.JS programming classes that utilized different development environments: one localized on student computers, the other containerized in Codespaces online. Then, we discuss how GitHub Codespaces and GitHub Classroom can be used to increase the effectiveness of practical programming classes while also increasing student engagement and programming confidence in class.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.215-227
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• 2021

The purpose of this study was to propose an efficient management strategy for untact real-time early childhood physical education(ECPE). The studay method was used in-depth interview, non-participant observation. The results of the study ar as follows. First, factors to be considered for untact real-time ECPE are 'location', 'communication', 'program', facilities' and 'equipment.' Second, for the effective untact real-time ECPE management, 'class design', 'class preparation', 'remote manager', and 'teaching ability.' are the sub-factors. The more of research on untact real-time ECPE are needed. Based on this study, it is hoped that an effective operation plan for untact real-time ECPE classes will be prepared.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.107-119
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• 2021

The cross-flow turbine is one of the most famous and widely used hydraulic power systems for a long time. The cross-flow turbine is especially popular in many countries and remote regions where off-grided because of its many benefits such as low cost, high efficiency at low head, simple structure, and easy maintenance. However, most modern turbines, including the cross-flow turbine, are unsuitable for the ultra-low head situation, known as less than 3m water head or zero head with over 0.5m/s flow velocity. In this study, we demonstrated a 20kW class inverted-type cross-flow turbine's performance. First, we reevaluated our previous studies and introduced how to design the inverted-type cross-flow turbine. Secondly, we fabricated the 20kW class inverted-type cross-flow turbine for the performance test. And then, we designed a testbed and installed the turbine system in the demonstration facility. In the end, we compare the demonstration with its previous CFD results. The comparing result shows that both CFD and real model fitted on guide vane angle at 10 degrees. At the demonstration, we achieved 42% turbine efficiency at runner speed 125 RPM.