• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.1
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• pp.3-7
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• 1998

The issue of data accuracy brings a different perspective to the issue of GIS modeling, calls into a question the usefulness of data models such as DEM. Accuracy can be determined by randomly checking positional and attribute accuracy within a GIS data layer. With the increasing availability of DEM and the software capable of processing them, it is worthwhile to call attention for data accuracy and error analysis as GIS application depends on the priori established spatial data. The purpose of this paper was to investigate methods for data accuracy measurement and error detection methodology with two types of DEM's: 1 to 24,000 and 1 to 250,000 DEM released by U.S. Geological Survey. Another emphasis was given to the development of methodology for processing DEM's to create Arc/Info and GRASS layers. Data accuracy analysis with DEM was applied to a 250 sq.km area and an error was detected at a scale of 1:24,000 DEM. There were two possible reasons for this error: gross errors and blunders.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4240-4258
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• 2016

A practical iterative channel estimation technique is proposed for the multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in the high-speed mobile environment, such as high speed railway scenario. In the iterative algorithm, the Kalman filter and data detection are jointed to estimate the time-varying channel, where the detection error is considered as part of the noise in the Kalman recursion in each iteration to reduce the effect of the detection error propagation. Moreover, the employed Kalman filter is from the canonical state space model, which does not include the parameters of the autoregressive (AR) model, so the proposed method does not need to estimate the parameters of AR model, whose accuracy affects the convergence speed. Simulation results show that the proposed method is robust to the fast time-varying channel, and it can obtain more gains compared with the available methods.

• Smart Structures and Systems
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• v.15 no.3
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• pp.717-733
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• 2015

Modal parameters of a structure are commonly used quantities for system identification and damage detection. With a limited number of studies on the statistics assessment of modal parameters, this paper presents procedures to properly account for the uncertainties present in the process of extracting modal parameters. Particularly, this paper focuses on how to deal with the measurement error in an ambient vibration test and the modeling error resulting from a modal parameter extraction process. A bootstrap approach is adopted, when an ensemble of a limited number of noised time-history response recordings is available. To estimate the modeling error associated with the extraction process, a model prediction expansion approach is adopted where the modeling error is considered as an "adjustment" to the prediction obtained from the extraction process. The proposed procedures can be further incorporated into the probabilistic analysis of applications where the modal parameters are used. This study considers the effects of the measurement and modeling errors and can provide guidance in allocating resources to improve the estimation accuracy of the modal data. As an illustration, the proposed procedures are applied to extract the modal data of a damaged beam, and the extracted modal data are used to detect potential damage locations using a damage detection method. It is shown that the variability in the modal parameters can be considered to be quite low due to the measurement and modeling errors; however, this low variability has a significant impact on the damage detection results for the studied beam.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.11-21
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• 2011

An embedded sensor is significantly influenced by its spatial environment, such as barriers or distance, through low power and signal strength. Due to these causes, noise data frequently occur in an embedded sensor. Because the information acquired from the embedded sensor exists in a time series, it is hard to detect an error which continuously takes place in the time series information on a realtime basis. In this paper, we proposes an error detection method based on time-series prediction that detects error signals of embedded sensors in real time in consideration of the physical characteristics of embedded devices. The error detection method based on time-series prediction proposed in this paper determines errors in generated embedded device signals using a stable distance function. When detecting errors by monitoring signals from an embedded device, the stable distance function can detect error signals effectively by applying error weight to the latest signals. When detecting errors by monitoring signals from an embedded device, the stable distance function can detect error signals effectively by applying error weight to the latest signals.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2126-2130
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• 2003

In the integrated systems, that is integrated digital TV(DTV) internet and home automation, like home server, is needed integration of digital TV video signal and computer graphic signal. The graphic signal is operating at the high speed and has time-divide-stream. So the re-request of data is not easy at the time of error detection. therefore EDAC algorithm is efficient. In this paper, we show a scheme, that is integration of graphic and dtv format signal for DTV monitor display. This paper also presents the efficiency error detection auto correction(EDAC) for conversion of graphics signal to DTV video signal. A presented EDAC algorithms use the modified hamming code for enhancing video quality and reliability. A EDAC algorithm of this paper can detect single error, double error, triple error and more error for preventing from incorrect correction. And it is not necessary an additional memory. In this paper The comparison between digital TV video signal and graphic signal, a EDAC algorithm and a design of conversion graphic signal to DTV signal with EDAC function in DTV system is described.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.638-642
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• 2002

User in video data utilization of high-capacity can grasp whole video data at a look. Offer frame list that summarize information of video data to do so that can remake video from branch that want when need. Need index process of video data for effective video retrieval. This treatise wishes to propose effective method about scene change point detection of video that is been based on contents base index. Proposed method video data so that can grasp whole structure of video detection color value of schedule pixel for diagonal line direction in image sampling do. Data that get into sampling could grasp scene change point on one eye. Color value of pixel that detection in each frame is i frame number by i$\times$j procession to procession A, j stores to reflex height of frame. Introduce MSE and calculate mean error of each frame. If exceed mean error and schedule critical value, wish to detect the frame for scene change point.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.45-56
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• 2015

In this paper, we present a method that can detect context-sensitive word errors and generate correction candidates. Spelling error detection is one of the most widespread research topics, however, the approach proposed in this paper is adjusted for an automated English scoring system. A common strategy in context-sensitive word error detection is using a pre-defined confusion set to generate correction candidates. We automatically generate a confusion set in order to consider the characteristics of sentences written by second-language learners. We define a word error that cannot be detected by a conventional grammar checker because of part-of-speech ambiguity, and propose how to detect the error and generate correction candidates for this kind of error. An experiment is performed on the English writings composed by junior-high school students whose mother tongue is Korean. The f1 value of the proposed method is 70.48%, which shows that our method is promising comparing to the current-state-of-the art.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.9 no.1
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• pp.47-54
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• 1991

In this study, the accuracy of three dimensional location was improved by self calibration bundle method with additional parameter, which is to correct systematic error through detection and elimination of the gross error from updated reference variance for observation values in photogram-metry. In this study, with the result of comparing accuracy of each method, correcting systematic error is more effective after gross error detection and when observation values are contained more than two gross error the point with maximum correlation value is detected by masking effect of least square adjustment.

• Smart Media Journal
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• v.13 no.4
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• pp.48-56
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• 2024

In the livestock industry, detecting environmental outliers and predicting data are crucial tasks. Outliers in livestock environment data, typically gathered through time-series methods, can signal rapid changes in the environment and potential unexpected epidemics. Prompt detection and response to these outliers are essential to minimize stress in livestock and reduce economic losses for farmers by early detection of epidemic conditions. This study employs two methods to experiment and compare performances in setting thresholds that define outliers in livestock environment data outlier detection. The first method is an outlier detection using Mean Squared Error (MSE), and the second is an outlier detection using a Dynamic Threshold, which analyzes variability against the average value of previous data to identify outliers. The MSE-based method demonstrated a 94.98% accuracy rate, while the Dynamic Threshold method, which uses standard deviation, showed superior performance with 99.66% accuracy.

• Journal of IKEEE
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• v.18 no.4
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• pp.509-516
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• 2014

CRC feature in a high-speed semiconductor memory devices such as DDR4/GDDR5 increases the data reliability. Conventional CRC method have a massive area overhead and long delay time. It leads to insufficient internal timing margins for CRC calculation. This paper, presents a CRC code method that provides error detection and a real-time matrix type CRC. If there are errors in the data, proposed method can alert to the system in a real-time manner. Compare to the conventional method(XOR 6 stage ATM-8 HEC code), the proposing method can improve the error detection circuits up to 60% and XOR stage delay by 33%. Also the real-time error detection scheme can improve the error detection speed to agerage 50% for the entire data bits(UI0~UI9).