• International Journal of Contents
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• v.15 no.3
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• pp.32-38
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• 2019

We usually suffer from difficulties in treating or managing Big Data generated from various digital media and/or sensors using traditional mining techniques. Additionally, there are many problems relative to the lack of memory and the burden of the learning curve, etc. in an increasing capacity of large volumes of text when new data are continuously accumulated because we ineffectively analyze total data including data previously analyzed and collected. In this paper, we propose a general-purpose classifier and its structure to solve these problems. We depart from the current feature-reduction methods and introduce a new scheme that only adopts changed elements when new features are partially accumulated in this free-style learning environment. The incremental learning module built from a gradually progressive formation learns only changed parts of data without any re-processing of current accumulations while traditional methods re-learn total data for every adding or changing of data. Additionally, users can freely merge new data with previous data throughout the resource management procedure whenever re-learning is needed. At the end of this paper, we confirm a good performance of this method in data processing based on the Big Data environment throughout an analysis because of its learning efficiency. Also, comparing this algorithm with those of NB and SVM, we can achieve an accuracy of approximately 95% in all three models. We expect that our method will be a viable substitute for high performance and accuracy relative to large computing systems for Big Data analysis using a PC cluster environment.

• Food Science of Animal Resources
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• v.43 no.6
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• pp.949-960
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• 2023

This research aimed to validate a high-performance liquid chromatography method for the quantitative determination of bixin and norbixin in various foods. The Diode Array Detector (495 nm) technique was used. Method was validated for specificity, linearity, limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy, and the measurement uncertainty was assessed. The calibration curve showed excellent linearity (r²≥0.9999) over the tested concentration range of 0.2-25 mg/L. The LOD and LOQ were 0.03-0.11 and 0.02-0.05 mg/L for bixin and norbixin, respectively. The intra-and inter-day accuracies and precisions were 88.0±1.3-97.0±0.5% and 0.2%-2.6% relative SD (RSD) for bixin and 88.2±0.8-105.8±0.8% and 0.3%-2.7% RSD for norbixin, respectively. Inter-laboratory validation for accuracy and precision was conducted in three laboratories, and these results all met the AOAC guidelines. In addition, the relative expanded uncertainty (<22%) satisfied the CODEX recommendation. Furthermore, products distributed in Korea were monitored for annatto extracts using the proposed method to demonstrate its application. The developed analytical method is reliable for quantifying bixin and norbixin in various foods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.97-104
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• 2018

Recently, many studies have examined UAVs (unmanned aerial vehicles), which can replace and supplement existing surveying sensors, systems, and images. This study focused on the use of UAV images and assessed the possibility of utilization in areas where it is difficult to obtain GCPs (ground control points), such as disasters. Therefore, 3D (dimensional) pointcloud data were generated using UAV images and the absolute/relative accuracy of the generated model data using GCPs and without GCPs was assessed. The results showed the 3D shape pointcloud generated by UAV image matching was proven if the relative accuracy was set, regardless of whether GCPs were used or not; the quantitative measurement error rate was within 1%. Even if the absolute accuracy was low, the 3D shape pointcloud that had been post processed quickly was sufficient to be utilized when it is impossible to acquire GCPs or urgent analysis is required. In particular, the results can obtain quantitative measurements and meaningful data, such as the length and area, even in cases with the ground reference point surveying and post-process.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.12
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• pp.1175-1186
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• 2016

The relative distance estimation technique is important to Location-Based Service(: LBS) in a wireless communication environment. In this paper, we propose a scheme for measuring the relative distance by utilizing a frame structure of a physical layer in asynchronous Frequency Division Duplexing(: FDD) when the Internal and external infrastructure for position measurement cannot be used. The proposed method is suitable for continuous distance measurement. The test results showed that the proposed method has the accuracy of less than 10 meters on average.

• Computers and Concrete
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• v.21 no.1
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• pp.47-54
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• 2018

Artificial neural network models can be successfully used to simulate the complex behavior of many problems in civil engineering. As compared to conventional computational methods, this popular modeling technique is powerful when the relationship between system parameters is intrinsically nonlinear, or cannot be explicitly identified, as in the case of concrete behavior. In this investigation, an artificial neural network model was developed to assess the residual compressive strength of self-compacted concrete at elevated temperatures ($20-900^{\circ}C$) and various relative humidity conditions (28-99%). A total of 332 experimental datasets, collected from available literature, were used for model calibration and verification. Data used in model development incorporated concrete ingredients, filler and fiber types, and environmental conditions. Based on the feed-forward back propagation algorithm, systematic analyses were performed to improve the accuracy of prediction and determine the most appropriate network topology. Training, testing, and validation results indicated that residual compressive strength of self-compacted concrete, exposed to high temperatures and relative humidity levels, could be estimated precisely with the suggested model. As illustrated by statistical indices, the reliability between experimental and predicted results was excellent. With new ingredients and different environmental conditions, the proposed model is an efficient approach to estimate the residual compressive strength of self-compacted concrete as a substitute for sophisticated laboratory procedures.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1725-1732
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• 2024

In nuclear power plants, reactor coolant leakage can occur due to various reasons. Early detection of leaks is crucial for maintaining the safety of nuclear power plants. Currently, a detection system is being developed in Korea to identify reactor coolant system (RCS) leakage of less than 0.5 gpm. Typically, RCS leaks are detected by monitoring temperature, humidity, and radioactivity in the containment, and a water level in the sump. However, detecting small leaks proves challenging because the resulting changes in the containment humidity and temperature, and the sump water level are minimal. To address these issues and improve leak detection speed, it is necessary to quantify the leaks and develop an artificial intelligence-based leak detection system. In this study, we employed bidirectional long short-term memory, which are types of neural networks used in artificial intelligence, to predict the relative humidity in the leakage area for leak quantification. Additionally, an optimization technique was implemented to reduce learning time and enhance prediction performance. Through evaluation of the developed artificial intelligence model's prediction accuracy, we expect it to be valuable for future leak detection systems by accurately predicting the relative humidity in a leakage area.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.74-74
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• 2002

This paper describes a corner matching technique for automatic relative orientation. Automatically matched corner points from stereo aerial images are used to a data set and help to improve automation of relative orientation process. A general corner matching process of overall image to image has very heavy operation and repetitive computation, so very time-consuming. But aerial stereo images are approximately seventy percent overlapped and little rotated. Based this hypothesis, we designed a sectional corner matching technique calculating correlation section by section between stereo images. Although the overlap information is not accurate, if we know it approximately, the matching process can be lighter. Since the size of aerial image is very large, corner extraction process is performed hierarchically by creating image pyramid, and corners extracted are refined at the higher level image. Extracted corners at the final step are matched section by section. Matched corners are filtered using positional information and their relation and distribution. Filtering process is applied over several steps because the thing affecting to get good result-good relative orientation parameter- is not the number of matched corner points but the accuracy of them. Filtered data is filtered one more during the process calculating relative orientation parameters. When the process is finished, we can get the well matched corner points and the refined Von-Gruber areas besides relative orientation parameters. This sectional corner matching technique is efficient by decreasing unnecessarily repetitive operations and contributes to improve automation for relative orientation.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.41-49
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• 2022

Documents often contain relative time expressions, and it is important to define a schema of the relative time information and develop a system that extracts such information from corpus. In this study, to deal with the relative time expressions, we propose seven additional attributes of timex3: year, month, day, week, hour, minute, and second. We propose a way to represent normalized values of the relative time expressions such as before, after, and count, and also design a set of rules to extract the relative time information from texts. With a new corpus constructed using the new attributes that consists of dialog, news, and history documents, we observed that our rule-set generally achieved 70% accuracy on the 1,041 documents. Especially, with the most frequently appeared attributes such as year, day, and week, we got higher accuracies compared to other attributes. The results of this study, our proposed timex3 attributes and the rule-set, will be useful in the development of services such as question-answer systems and chatbots.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.7 no.5
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• pp.384-394
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• 1996

The propagation properties of square and Gaussian pulse signals on the microstrip line are investigated by using proper conventional models to meet the frequency range of a pulse, accuracy, and geometrical requirements of the microstrip line. Numerical integration technique which has its accuracy and is easily simulated, is used to obtain the time domain response of pulse signals. The dispersion of pulse signals is analyzed regarding to the relative permittivity $\varepsilon_r$, substrate height h, strip width w of the microstrip line and pulse width $\tau$ of signal pulse. The simulation results show that small relative permittivity and small rationale of w/h are advantageous for the dispersion of the pulse signals, and that pulse signals with small bandwidth cause smaller dispersion. The results of this paper are compatible to the trade-off determination of relative permittivity, substrate height, strip width and pulse width of signal pulse when a design of MIC and MMIC is necessary.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.529-536
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• 2008

Researches about 3-D Positioning system using GPS were carried out many-sided by national organs, laboratories, the worlds of science. And most of researches were development of relative positioning algorithm and its applications. Relative positioning has a merit, which can eliminate error in received signals. But its error increase due to distance of baseline. GPS absolute positioning is a method that decides the position independently by the signals from the GPS satellites which are received by a receiver at a certain position. And it is necessary to correct various kinds of error(clock error, effect of ionosphere and troposphere, multi-path etc.). In this study, results of PPP(Precise Point Positioning) used Bernese GPS software was compared with notified coordinates by the NGII(National Geographic Information Institute) in order to analyze the positional accuracy of permanent GPS sites. And the results were compared with results of AUSPOS - Online GPS Processing Service for comparison with relative positioning.