• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.50-54
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• 2009

Recently, many researches have been conducted to develop 3D Indoor/Outdoor Spatial Data Models. The 3D data created based on these data models have complex data structures. In order to manage these data efficiently, it is better to use a DBMS. There have been many researches to maintain the 3D data in Geo-DBMS, such that Oosterom (2002) and Arens (2005) developed a method to store 3D Building model, geometric and topological data of coverage in DBMSa. In this study, we propose a method to store the CityGML data into the RDBMS, Oracle Spatial 11g.

• The International Journal of Costume Culture
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• v.6 no.1
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• pp.19-29
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• 2003

The 3D measurement data expected be useful to give appropriate garment fit and development of MTM(Made-to-Measure) CAD software. The researcher surveyed the need and use of national anthropometric data of the apparel industry. 17 Korean apparel manufacturers participated in the study. The need of anthropometric data at 5 different apparel business sectors was measured: men's suit, women's dress, casual-wear, underwear, and active sportswear. The result of the survey shows that height and bust, waist, hip circumferences are needed by all of the business sectors. The body measurements at the scye and upper arm area were need most by the men's suit manufacturers. The women's foundation garment manufacturers were well prepared for the use of the 3D body scan data and they expected the potential benefits of 3D body scan data would be great. The researcher also conducted a case study and found a pro and con of the using 3D body scan data for apparel product developing process. In the current stage of technical advance, a reasonable method was required to get nude like scan data for the women's foundation garment manufacturer. The researcher concluded that the apparel designer could use the 3D scan data for developing tremendous style garment design and pattern making.

• Atmosphere
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• v.32 no.4
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• pp.323-340
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• 2022

We analyzed the high-resolution wind data of Aircraft-Based Observation from the Mode-Selective Enhanced Surveillance (Mode-S EHS) data in Korea. For assessment of its quality, the Mode-S wind data was compared with the ECMWF ReAnalysis 5 (ERA5) reanalysis and Aircraft Meteorological Data Relay (AMDAR) data for more than 3-months from 7 May 2021 to 24 August 2021 near Incheon International Airport, Korea. Considering that the AMDAR reports are not provided by all commercial aircraft, total number of the Mode-S derived wind data with a second sampling rate was about twice larger than that of available AMDAR wind data. After the quality control procedures by removing erroneous samples, it was found that the root mean square errors (RMSEs) of the Mode-S retrieved winds are similar to that from the AMDAR winds. In particular, between 550 and 650 hPa levels, RMSE of the Mode-S (AMDAR) zonal wind against ERA5 data was about 2.3 m s^-1 (1.9 m s^-1), and those increased to 3.3 m s^-1 (2.4 m s^-1) in 200~500 hPa levels. A similar trend was found in the meridional wind, but a distinct positive mean bias of 2.16 m s^-1 was observed between 875 and 1,000 hPa levels. Winds retrieved from the Mode-S also showed a good agreement directly with AMDAR data. As the Mode-S provides a large amount of data with a reliable quality, it can be useful for both data assimilation in the numerical weather prediction model and situational awareness of wind and turbulence for aviation safety in Korea.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.109-114
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• 2024

In this paper, we design and implement a worker motion 3D visualization module based on human sensors. The three key modules that make up this system are Human Sensor Implementation, Data Set Creation, and Visualization. Human Sensor Implementation provides the functions of setting and installing the human sensor locations and collecting worker motion data through the human sensors. Data Set Creation offers functions for converting and storing motion data, creating near real-time worker motion data sets, and processing and managing sensor and motion data sets. Visualization provides functions for visualizing the worker's 3D model, evaluating motions, calculating loads, and managing large-scale data. In worker 3D model visualization, motion data sets (Skeleton & Position) are synchronized and mapped to the worker's 3D model, and the worker's 3D model motion animation is visualized by combining the worker's 3D model with analysis results. The human sensor-based worker motion 3D visualization module designed and implemented in this paper can be widely utilized as a foundational technology in the smart factory field in the future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.6
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• pp.609-614
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• 2009

The TT&C communication subsystem of STSAT-3 is consisted of communication link to send telemetry data of spacecraft to the ground station and receive command data from ground station. The S-band receiver is used to receive command data from ground station, Engineering Qualification Model of S-band receiver has been designed and manufactured. The Designed S-band Receiver uses a single conversion for a simple frequency conversion, including a DC-DC Converter and EMI Filter. Also, Digital demodulation part designed using FPGA and RS-422 data interface. The performance of S-band Receiver in functional and space environments test satisfies the requirements of STSAT-3.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.298-300
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• 2005

Satellite payload on-board date compression unit are use for saving date storage space and reducing time to transmit payload data to the ground station. The KOMPSAT-3 payload will generate higher data rate than KOMPSAT-2 due to its better ground sample distance capacity. High input data rate and limited output transmission data rate might lead excessive compression and degraded image quality. This paper presents a trade-off study about data storage capacity and compression parameters for estimated KOMPSAT-3 system.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.103-110
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• 2018

Studies on artificial intelligence have been developed for the past couple of decades. After a few periods of prosperity and recession, a new machine learning method, so-called Deep Learning, has been introduced. This is the result of high-quality big- data, an increase in computing power, and the development of new algorithms. The main targets for deep learning are 1D audio and 2D images. The application domain is being extended from a discriminative model, such as classification/segmentation, to a generative model. Currently, deep learning is used for processing 3D data. However, unlike 2D, it is not easy to acquire 3D learning data. Although low-cost 3D data acquisition sensors have become more popular owing to advances in 3D vision technology, the generation/acquisition of 3D data remains a very difficult problem. Moreover, it is not easy to directly apply an existing network model, such as a convolution network, owing to the variety of 3D data representations. In this paper, we summarize the 3D deep learning technology that have started to be developed within the last 2 years.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.141-152
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• 2017

This paper presents a technical method for flood estimation based on satellite rainfall and satellite rainfall correction method for watersheds lacking measurement data. The study area was the Sebou Watershed, Morocco. The Integrated Flood Analysis System(IFAS) and Grid-based Rainfall-Runoff Model(GRM) were applied to estimate watershed runoff. Daily rainfall from ground gauges and satellite-derived hourly data were used. In the runoff simulation using satellite rainfall data, the composites of the daily gauge rainfall and the hourly satellite data were applied. The Shuttle Radar Topographic Mission Digital Elevation Model(SRTM DEM) with a 90m spatial resolution and 1km resolution data from Global map land cover and United States Food and Agriculture Organization(US FAO) Harmonized World Soil Database(HWSD) were used. Underestimated satellite rainfall data were calibrated using ground gauge data. The simulation results using the revised satellite rainfall data were $5,878{\sim}7,434m^3/s$ and $6,140{\sim}7,437m^3/s$ based on the IFAS and GRM, respectively. The peak discharge during flooding of Sebou River Watershed in 2009~2010 was estimated to range from $5,800m^3/s$ to $7,500m^3/s$. The flood estimations from the two hydrologic models using satellite-derived rainfall data were similar. Therefore, the calibration method using satellite rainfall suggested in this study can be applied to estimate the flood discharge of watersheds lacking observational data.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.237-239
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• 2004

Wireless LAN Voice over IP(VoIP) equipment needs Quality-of-Service(QoS) with priority for processing real-time traffic. This paper shows transmit function implementation of wireless LAN(WLANs) media access control(MAC) support VoIP, and it has an advantage of guarantee of QoS and is adaptable to VoIP or mobile wireless equipment. The IEEE 802.11e standard in progress has four queues according to four access categories(AC) for transmit and the MAC transmits the data based on EDCA. The value of AC is from AC0 to AC3 and AC3 has the highest priority. The transmit method implemented at this paper ensure QoS using one transmit FIFO in hardware since real-time traffic data and non real-time traffic data has the different priority. The device driver classifies real-time data and non real-time data and transmit data to hardware with information about data type. The hardware conducts shorter backoff and selects faster AIFS slot for real-time data than it for non real-time data. Therefor It make give the real-time traffic data faster channel access chance than non real-time data and enhances QoS.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.73-78
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• 2021

As interest in beauty has increased, various studies have been conducted, and related companies have considered the anthropometric data handled between humans and interfaces as an important factor. However, owing to the nature of 3D human body scanners used to extract anthropometric data, it is difficult to accurately analyze a user's body shape until a service is provided because the user only scans and extracts data. To solve this problem, the body shape of several users was analyzed, and the collected anthropometric data were obtained using a 3D human body scanner. After processing the extracted data and the anthropometric data, a custom deep learning model was designed, the designed model was learned, and the user's body shape information was predicted to provide a service suitable for the body shape. Through this approach, it is expected that the user's body shape information can be predicted using a 3D human body scanner, based upon which a beauty service can be provide.