• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.2
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• pp.157-164
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• 2008

GPS baseline analysis is a mathematical procedure which estimates a baseline vector from carrier-phase double-differenced observations. Least squares technique is generally applied for the processing and integer ambiguities in the observations should be resolved to obtain maximum accuracy of the solution. In GPS control surveying, after assembling the baseline solutions into a network, adjustment is performed to derive final coordinate sets of unknown points. This paper deals with details of GPS baseline analysis for the $2^{nd}$ order national geodetic network adjustment. After reviewing GPS campaigns carried out by National Geographic Information Institute (NGII) and their observations. technical issues and considerations for the GPS baseline analysis are presented with emphasis of selecting the processing strategies and software. Finally, the analyzed results will be evaluated by examining the close of figures formed by joining the processed baseline vectors.

• Korean Journal of Geomatics
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• v.3 no.2
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• pp.141-148
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• 2004

This paper deals with the characteristics of strain pattern by using permanent GPS stations in Korea in terms of seismic activity and tectonics. Fourteen GPS stations involved in precise baseline vector solution and horizontal strain components were calculated using the differences of mean baseline from ten deily solutions during the time span of three years. The mean rate of maximum shear strain if 0.12 $\mu$/yr. The mean direction of principal axes of the compression is about $85^{\circ}$ N.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.3
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• pp.123-129
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• 2014

The real-time kinematic (RTK) is one of precise positioning methods using Global Positioning System (GPS) data. In the long baseline GPS RTK, the ionospheric and tropospheric delays are critical factors for the positioning accuracy. In this paper we present RTK algorithms for long baselines more than 100 km with estimating tropospheric delays. The state vector is estimated by the extended Kalman filter. We show the experimental results of GPS RTK for various baselines (162.10, 393.37, 582.29, and 1283.57 km) by using the Korea Astronomy and Space Science Institute GPS data and one International GNSS Service (IGS) reference station located in Japan. As a result, we present that long baseline GPS RTK can provide the accurate positioning for users less than few centimeters.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1675-1678
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• 1997

In this paper, an attitude determination system(ADS) for KOMPSAT using GPS LI carrier phase measurements is considered. The baseline vector is estimated by the Exetnded Kalman Filter (EKF) which used the double differenced carrier phased measuremenmts made by three GPS receivers mounted on the spaceraft. The attitude angles of three axes of spacecrat are computed by the estimated baseline vectors, directly. The proposed ADS is verified by the simulation results.

• Phonetics and Speech Sciences
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• v.2 no.1
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• pp.77-85
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• 2010

This paper proposes an efficient feature vector processing technique to guard the Speech Emotion Recognition (SER) system against a variety of noises. In the proposed approach, emotional feature vectors are extracted from speech processed by comb filtering. Then, these extracts are used in a robust model construction based on feature vector classification. We modify conventional comb filtering by using speech presence probability to minimize drawbacks due to incorrect pitch estimation under background noise conditions. The modified comb filtering can correctly enhance the harmonics, which is an important factor used in SER. Feature vector classification technique categorizes feature vectors into either discriminative vectors or non-discriminative vectors based on a log-likelihood criterion. This method can successfully select the discriminative vectors while preserving correct emotional characteristics. Thus, robust emotion models can be constructed by only using such discriminative vectors. On SER experiment using an emotional speech corpus contaminated by various noises, our approach exhibited superior performance to the baseline system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.2
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• pp.173-180
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• 2003

As the utility value of GPS in surveying field is on the increase after the conversion into the world geodetic system, most of the baseline processing programs seeking the relative baseline vector for the roving point based on the base point are dependent on the foreign software, and such dependence remains a stumbling block to its wide application. In this study an algorithm was established settling ambiguity through LAMBDA techniques and the baseline processing program was developed for Ll carrier phase using visual c＋＋ 6.0, which is an object-oriented language. And the developed program proved that it maintained a difference of less than 4.9 cm over the short baseline of 4.9 km or shorter when compared with other commercialized programs.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.16-22
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• 2012

In this paper, we proposed a method of baseline correction for analysis of Raman spectra of platelets from Alzheimer's disease (AD) transgenic mice. Measured Raman spectra include the meaningful information and unnecessary noise which is composed of baseline and additive noise. The Raman spectrum is divided into the local region including several peaks and the spectrum of the region is modeled by curve fitting using Gaussian model. The additive noise is clearly removed from the process of replacing the original spectrum with the fitted model. The baseline correction after interpolating the local minima of the fitted model with linear, piecewise cubic Hermite and cubic spline algorithm. The baseline corrected models extract the feature with principal component analysis (PCA). The classification result of support vector machine (SVM) and maximum $a$ posteriori probability (MAP) using linear interpolation method showed the good performance about overall number of principal components, especially SVM gave the best performance which is about 97.3% true classification average rate in case of piecewise cubic Hermite algorithm and 5 principal components. In addition, it confirmed that the proposed baseline correction method compared with the previous research result could be effectively applied in the analysis of the Raman spectra of platelet.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.146-148
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• 2007

CMDPS (COMS Meteorological Data Processing System) is the operational meteorological products extraction system for data observed from COMS (Communication, Ocean and Meteorological Satellite) meteorological imager. CMDPS baseline products consist of 16 parameters including cloud information, water vapor products, surface information, environmental products and atmospheric motion vector. Additionally, CMDPS includes the function of calibration monitoring, and validation mechanism of the baseline products. The main objective of CMDPS validation module development is near-real time monitoring for the accuracy and reliability of the whole CMDPS products. Also, its long time validation statistics are used for upgrade of CMDPS such as algorithm parameter tuning and retrieval algorithm modification. This paper introduces the preliminary design on CMDPS validation module.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.73-82
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• 2015

Understanding how the topic evolves is an important and challenging task. A topic usually consists of multiple related events, and the accurate identification of event evolution relationship plays an important role in topic evolution analysis. Existing research has used the traditional vector space model to represent the event, which cannot be used to accurately compute the semantic similarity between events. This has led to poor performance in identifying event evolution relationship. This paper suggests constructing a semantic aspect-based vector space model to represent the event: First, use hierarchical Dirichlet process to mine the semantic aspects. Then, construct a semantic aspect-based vector space model according to these aspects. Finally, represent each event as a point and measure the semantic relatedness between events in the space. According to our evaluation experiments, the performance of our proposed technique is promising and significantly outperforms the baseline methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.247-250
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• 2006

Maximizing the productivity in reactive ion etching, early detection of process equipment anomaly became crucial in current high volume semiconductor manufacturing environment. To address the importance of the process fault detection for productivity, support vector machines (SVMs) is employed to assist the decision to determine process faults in real-time. SVMs for eleven steps of etching runs are established with data acquired from baseline runs, and they are further verified with the data from controlled (acceptable) and perturbed (unacceptable) runs. Then, each SVM is further utilized for the fault detection purpose utilizing control limits which is well understood in statistical process control chart. Utilizing SVMs, fault detection of reactive ion etching process is demonstrated with zero false alarm rate of the controlled runs on a run to run basis.