• Bulletin of the Korean Chemical Society
• /
• v.29 no.10
• /
• pp.2017-2022
• /
• 2008

Of the experiments to shorten NMR measuring time by sparse sampling, non-uniform sampling (NUS) is advantageous. NUS miminizes systematic errors which arise due to the lack of samplings by randomization. In this study, I report the real-time acquisition of 3D NMR data using NUS and maximum-entropy (MaxEnt) data processing. The real-time acquisition combined with NUS can reduce NMR measuring time much more. Compared with multidimensional decomposition (MDD) method, which was originally suggested by Jaravine and Orekhov (JACS 2006, 13421-13426), MaxEnt is faster at least several times and more suitable for the realtime acquisition. The designed sampling schedule of current study makes all the spectra during acquisition have the comparable resulting resolutions by MaxEnt. Therefore, one can judge the quality of spectra easily by examining the intensities of peaks. I report two cases of 3D experiments as examples with the simulated subdataset from experimental data. In both cases, the spectra having good qualitie for data analysis could be obtained only with 3% of original data. Its corresponding NMR measuring time was 8 minutes for 3D HNCO of ubiquitin.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.6
• /
• pp.688-692
• /
• 2010

Wireless sensor network system collects and analyzes real-time data that have been requested by the many application nodes. This paper has constructed a sensor network cluster with various elements in the Gunsan City area of Jeollabuk-do, S.korea. The purpose of this paper is to utilize the constructed system in order to illustrate the real-time data in a diagram and analyze it to deduce the change ratio. The resulting analysis contents allow simple data interpretation by illustrating the data in change ratio by time, space, and motional directions. This analytical method will offer great benefit to those users using the wireless sensor network.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.9
• /
• pp.2328-2340
• /
• 1996

Until now, the transmission of data for VOD(Video on Demenad) was based on a real time modelling of video data. Markow Modulated Fluid Sources(MMFS) and Markow Modulated Poisson Sources(MMPS) are the most widely used modelling methods. But the charactersitics of the VBR(Variable Bit Rate) signal prevents modelling from actually being "real-time". Also these methods call for the use of large buffers for the abolishment of cell loss. These modelling methods are, of course, useful i case of teleconferences where a real time modelling of video traffic is inevitable, but they are insufficient in cases where the characteristic infomation of video traffic can be obtained beforehand-cases such as VOD. Video data is speial in that if one file is preprocessed all other products can simply be copied from that onepreprocessed file. This characteristic helps reduce the overhead arising from the job of drawing out characteristic information to almost zero. But still, compared to the existing real time modelling method data transmission using characteristic information succeeds in raising the efficiency of data transmission. In tis paper we will outline a method of dta transmission which use the characteristic information of each video stream, and evaluate this method through some experiments.periments.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.8 no.5
• /
• pp.159-166
• /
• 2008

Recently, according to the rapid development of location positioning technology and wireless communications technology and increasement of usage of moving object data, many researches and developments on the real-time locating systems which provides real time service of moving object data stream are under proceeding. However, MO (Moving Object) DBMS used based system in the in these systems is the inefficient management of moving object data streams, and the existing DSMS (Data Stream Management System) has problems that spatio-temporal data are not handled efficiently. Therefore, in this thesis, we designed and implemented spatio-temporal DSMS for efficient real-time management of moving object data stream. This thesis implemented spatio-temporal DSMS based STREAM (STanford stREam dAta Manager) of Stanford University is supporting real-time management of moving object data stream and spatio-temproal query processing and filtering for reduce the input loading. Specifically, spatio-temporal operators of the spatio-temporal DSMS support standard interface of SQL form which extended "Simple Feature Specification for SQL" standard specifications presented by OGC for compatibility. Finally, implemented spatio-temporal DSMS in this thesis, proved the effectiveness of the system that as applied real-time monitoring areas that require real-time locating of object data stream DSMS.

• Journal of the Korean Solar Energy Society
• /
• v.30 no.3
• /
• pp.25-32
• /
• 2010

A real-time monitoring system was developed for transfer, receive, backup and analysis of wind power data at three wind farm(Hang won, Hankyung and Sung san) in Jeju. For this monitoring system a communication system analysis, a collection of data and transmission module development, data base construction and data analysis and management module was developed, respectively. These modules deal with mechanical, electrical and environmental problem. Especially, time series graphic is supported by the data analysis and management module automatically. The time series graphic make easier to raw data analysis. Also, the real-time monitoring system is connected with wind power forecasting system through internet web for data transfer to wind power forecasting system's data base.

• Journal of Information Technology Applications and Management
• /
• v.17 no.3
• /
• pp.1-24
• /
• 2010

Most of enterprises depend on a data modeler during developing their management information systems. In formulating business requirements for information systems, they widely and naturally use the interview method between a data modeler and a field worker. But, the discrepancy between both parties would certainly cause information loss and distortion that lead to let the systems not faithful to real business works. To improve or avoid modeler-dependant data modeling process, many automated data design CASE tools have been introduced. However, since most of traditional CASE tools just support drawing works for conceptual data design, a data modeler could not generate an ERD faithful to real business works and a user could not use them without any knowledge on database. Although some CASE tools supported conceptual data design, they still required too much preliminary database knowledge for a user. Against these traditional CASE tools, we proposed a Requirement-Oriented Entity Relationship Model for automated data design tool, called ROERM. Based on Non-Stop Methodology, ROERM adopts inner systematic modules for complete and sound ERD that is faithful to real field works, where modules are composed of interaction modules with a user, rules of schema operations and sentence translations. In addition to structure design of ROERM, we also devise detailed algorithms and perform an experiment for a case study.

• Journal of Ocean Engineering and Technology
• /
• v.37 no.5
• /
• pp.198-204
• /
• 2023

In response to the complexity and time demands of conventional methods for estimating the hydrodynamic coefficients, this study aims to revolutionize ship maneuvering analysis by utilizing automatic identification system (AIS) data and the Support Vector Regression (SVR) algorithm. The AIS data were collected and processed to remove outliers and impute missing values. The rate of turn (ROT), speed over ground (SOG), course over ground (COG) and heading (HDG) in AIS data were used to calculate the rudder angle and ship velocity components, which were then used as training data for a regression model. The accuracy and efficiency of the algorithm were validated by comparing SVR-based estimated hydrodynamic coefficients and the original hydrodynamic coefficients of the Mariner class vessel. The validated SVR algorithm was then applied to estimate the hydrodynamic coefficients for real ships using AIS data. The turning circle test wassimulated from calculated hydrodynamic coefficients and compared with the AIS data. The research results demonstrate the effectiveness of the SVR model in accurately estimating the hydrodynamic coefficients from the AIS data. In conclusion, this study proposes the viability of employing SVR model and AIS data for accurately estimating the hydrodynamic coefficients. It offers a practical approach to ship maneuvering prediction and control in the maritime industry.

• Journal of the Korean Solar Energy Society
• /
• v.34 no.1
• /
• pp.8-18
• /
• 2014

Building simulation is used in a variety of sectors. In its early years, building simulation was mainly used in the design phase of a building for basic functions. Recently, however, it has become increasingly important during the operating phase, for commissioning and facility management. Most building simulation tools are used to estimate the thermal environment and energy consumption performance, and hence, they require the inputting of hourly weather data. A building simulation used for prediction should take into account the use of standard weather data. Weather data, which is used as input for a building simulation, plays a crucial role in the prediction performance, and hence, the selection of appropriate weather data is considered highly important. The present study proposed a technique for generating real-time weather data files, as opposed to the standard weather data files, which are required for running the building simulation. The forecasted weather elements provided by the Korea Meteorological Administration (KMA), the elements produced by the calculations, those utilizing the built-in functions of Energy Plus, and those that use standard values are combined for hourly input. The real-time weather data files generated using the technique proposed in the present study have been validated to compare with measured data and simulated data via EnergyPlus. The results of the present study are expected to increase the prediction accuracy of building control simulation results in the future.

• Journal of Technology Innovation
• /
• v.31 no.1
• /
• pp.65-103
• /
• 2023

With the recent surge in the share of data-based economic activities, there have been vibrant discussions on the data economy. Yet, few extant works provide a framework for systematically analyzing the transition to the data economy by major industries in Korea. By reviewing the existing literature, we first summarize the main characteristics of the data economy as building platforms, the greater importance of predictive power, and the increased use of new analytics. Next, based on such understanding, we provide a comparative analysis regarding the degree of data-based activities in Korea's financial, real estate, and medical sectors. We find that the speed at which, and the content of the data economy characteristics being realized were different for the different sectors. These findings suggest that differentiated policy approaches by major industrial sectors such as finance, real estate, and medical care are needed to improve economic productivity and increase welfare through the spread of the data economy.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.1127-1130
• /
• 2003

This paper introduces histogramic in-motion mapping for real-time map building with the Eyebot in motion. A histogram grid used in HIMM is updated through three PSD sensors. HIMM makes it possible to make fast map-building and avoid obstacles in real-time. Fast map-building allows the robot to immediately use the mapped information in real-time obstacle-avoidance algorithms. HIMM has been tested on the Eyebot. The Eyebot sends PSD data to computer and computer builds a 3D-Map based on PSD data.