• Journal of Astronomy and Space Sciences
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• v.32 no.3
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• pp.229-235
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• 2015

We estimated the orbit of the Communication, Ocean and Meteorological Satellite (COMS), a Geostationary Earth Orbit (GEO) satellite, through data from actual optical observations using telescopes at the Sobaeksan Optical Astronomy Observatory (SOAO) of the Korea Astronomy and Space Science Institute (KASI), Optical Wide field Patrol (OWL) at KASI, and the Chungbuk National University Observatory (CNUO) from August 1, 2014, to January 13, 2015. The astrometric data of the satellite were extracted from the World Coordinate System (WCS) in the obtained images, and geometrically distorted errors were corrected. To handle the optically observed data, corrections were made for the observation time, light-travel time delay, shutter speed delay, and aberration. For final product, the sequential filter within the Orbit Determination Tool Kit (ODTK) was used for orbit estimation based on the results of optical observation. In addition, a comparative analysis was conducted between the precise orbit from the ephemeris of the COMS maintained by the satellite operator and the results of orbit estimation using optical observation. The orbits estimated in simulation agree with those estimated with actual optical observation data. The error in the results using optical observation data decreased with increasing number of observatories. Our results are useful for optimizing observation data for orbit estimation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4317-4335
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• 2018

Semi-supervised multi-view latent space learning is gaining considerable popularity recently in many machine learning applications due to the high cost and difficulty to obtain the large amount of label information of data. Although some semi-supervised multi-view latent space learning methods have been presented, there is still much space for improvement: 1) How to learn latent discriminant intact feature representations by employing data of multiple views; 2) How to exploit the manifold structure of both labeled and unlabeled point in the learned latent intact space effectively. To address the above issues, we propose an approach called semi-supervised multi-view manifold discriminant intact space learning ($SM^2DIS$) for image classification in this paper. $SM^2DIS$ aims to seek a manifold discriminant intact space for data of different views by making use of both the discriminant information of labeled data and the manifold structure of both labeled and unlabeled data. Experimental results on MNIST, COIL-20, Multi-PIE, and Caltech-101 databases demonstrate the effectiveness and robustness of our proposed approach.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.501-503
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• 2006

We have processed the GPS data using several high quality GPS data processing softwares for last decade. Bernes and GIPSY II are some of them. Though these programs have different characteristics in terms of structures and processing philosophies, high quality results from these are still comparable. KASI Space Geodesy Research Division has developed several GNSS data processing softwares like the quasi real-time ionospheric parameter estimator, orbit propagator and estimator, and precision positioning estimator. However, we are currently in needs of our own comprehensive GNSS data processing software with the European Galileo system on the horizon. KASI team has worked on a preliminary pilot project for the software and is making block pieces for the software. The roadmap, the description, and brief results of KASIOPEA (KASI Orbit Propagator and EstimAtor) are presented in this paper.

• Journal of Astronomy and Space Sciences
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• v.37 no.4
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• pp.219-228
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• 2020

A CubeSat platform has become a popular choice due to inexpensive commercial off-the-shelf (COTS) components and low launch cost. However, it requires more power-efficient and higher-data rate downlink capability for space applications related to remote sensing. In addition, the platform is limited by the size, weight and power (SWaP) constraints as well as the regulatory issue of licensing the radio frequency (RF) spectrum. The requirements and limitations have put optical communications on promising alternatives to RF communications for a CubeSat platform, owing to the power efficiency and high data rate as well as the license free spectrum. In this study, we analyzed the performance of optical downlink communications compatible with CubeSat platforms in terms of data rate, bit error rate (BER) and outage probability. Mathematical models of BER and outage probability were derived based on not only the log-normal model of atmospheric turbulence but also a transmitter with a finite extinction ratio. Given the fixed slot width, the optimal guard time and modulation orders were chosen to achieve the target data rate. And the two performance metrics, BER and outage data rate, were analyzed and discussed with respect to beam divergence angle, scintillation index and zenith angle.

• The Journal of Bigdata
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• v.4 no.1
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• pp.83-97
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• 2019

With sensor and communication technology development, spatial data related to business activities is exploding. Spatial data is now evolving into atypical data about space over three dimensions, away from two-dimensional geographic data. In addition to the Fourth Industrial Revolution, which connects the virtual space with the real space, there is a great opportunity for companies to utilize it. The analysis of recent overseas cases shows that it is possible to analyze customized services by understanding the situation of customers and objects located in the space, to manage risk, and furthermore to innovate business processes by analyzing spatial data. In the future, business innovation that combines spatial data from various sources and real-time analysis of relationships and situations between people and objects in space is expected to expand in all business fields.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.349-363
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• 2024

Compositional data refers to data where the sum of the values of the components is a constant, hence the sample space is defined as a simplex making it impossible to apply statistical methods developed in the usual Euclidean vector space. A natural approach to overcome this restriction is to consider an appropriate transformation which moves the sample space onto the Euclidean space, and log-ratio typed transformations, such as the additive log-ratio (ALR), the centered log-ratio (CLR) and the isometric log-ratio (ILR) transformations, have been mostly conducted. However, in scenarios with sparsity, where certain components take on exact zero values, these log-ratio type transformations may not be effective. In this work, we mainly suggest an alternative transformation, that is the square-root transformation which moves the original sample space onto the directional space. We compare the square-root transformation with the log-ratio typed transformation by the simulation study and the real data example. In the real data example, we applied both types of transformations to the USG% data obtained from NBA, and used a density based clustering method, DBSCAN (density-based spatial clustering of applications with noise), to show the result.

• Journal of Astronomy and Space Sciences
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• v.27 no.4
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• pp.309-318
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• 2010

We introduce a technical approach for reducing three-dimensional infrared (IR) spectroscopic data generated by integral field spectroscopy or slit-scanning observations. The first part of data reduction using IRAF presents a guideline for processing spectral images from long-slit IR spectroscopy. Multichannel image reconstruction, Image Analysis and Display (MIRIAD) is used in the later part to construct and analyze the data cubes which contain spatial and kinematic information of the objects. This technic has been applied to a sample data set of diffuse 2.1218 ${\mu}m$ $H_2$ 1-0 S(1) emission features observed by slit-scanning around Sgr A East in the Galactic center. Details of image processing for the high-dispersion infrared data are described to suggest a sequence of contamination cleaning and distortion correction. Practical solutions for handling data cubes are presented for survey observations with various configurations of slit positioning.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.10-18
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• 2018

For the information services supporting requests of data items from a great number of mobile clients, wireless data broadcasting is an effective way because it can accommodate any number of clients. In the wireless data broadcasting, various air indexing schemes and data scheduling schemes have been developed in order to enable the clients to access their desired data items efficiently. The broadcasting system needs a method to simulate newly designed air indexing and scheduling schemes of the system, and to evaluate the performance parameters of the schemes. In this paper, we design an expandable and efficient simulation framework for the wireless data broadcasting based on the partition of data ID space. The framework can adopt regular and irregular space partition and evaluate various performance parameters of the broadcasting system. We implement a testbed of the broadcasting system using the framework, that adopts IIP, GDI and EXP as its air indexing schemes. We simulate the system using the testbed and evaluate the performance parameters of the system. Thus, we show the efficiency and expandability of the designed and implemented framework.

• Korean Institute of Interior Design Journal
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• v.23 no.5
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• pp.157-164
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• 2014

The subject specialization room will be able to support university library users who are inclined to use the general reading room. This study is the research of the area planning for university library's subject specialization room. For the evaluation, 431 users from 15 university libraries in 14 universities located across Seoul were surveyed. Statistical analysis was performed using SPSS. Frequency, percentage, mean, t-test, f-test were used. Results of the study are as follow. Subject specialization rooms in university libraries can be classified via the analysis of spatial characteristics. According to the area ratio of data space and reading space in a subject specialization room, the subject room can be separated into data-loaning and data-reading types. Old libraries are more likely to be data-loaning types, where reading room is small and there are a lot of bookshelves. The annual increase in library collections causes space for bookshelves to decrease. As a result, space for reading has been gradually transformed into space for stacking data. It is necessary to introduce ways to maintain enough space for both reading and stacking data. One way includes movable compact shelving, which can partially replace existing fixed shelves.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.252-255
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• 1997

In this paper, we will propose the methodology of data analysis using the fuzzy property set model. In real world, the data can be represented with the object. $\theta$. and the property, $\pi$, and its has-property relation, P. Then, the conceptual space can be defined with the chosen properties. Each object has a unique location in the conceptual space. In Fuzzy mode, the fuzzy property, and fuzzy conceptual space can be redefined. To analyze data using the fuzzy property set model, the rough set need to be defined in the fuzzy conceptual space.