• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.135-147
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• 2023

Internet of things has revolutionaries every field of life due to the use of artificial intelligence within Machine Learning. It is successfully being used for the study of Radiation monitoring, prediction of Ultraviolet and Electromagnetic rays. However, there is no particular system available that can monitor and detect waves. Therefore, the present study designed in which IOT enables intelligence system based on machine learning was developed for the prediction of the radiation and their effects of human beings. Moreover, a sensor based system was installed in order to detect harmful radiation present in the environment and this system has the ability to alert the humans within the range of danger zone with a buzz, so that humans can move to a safer place. Along with this automatic sensor system; a self-created dataset was also created in which sensor values were recorded. Furthermore, in order to study the outcomes of the effect of these rays researchers used Support Vector Machine, Gaussian Naïve Bayes, Decision Trees, Extra Trees, Bagging Classifier, Random Forests, Logistic Regression and Adaptive Boosting Classifier were used. To sum up the whole discussion it is stated the results give high accuracy and prove that the proposed system is reliable and accurate for the detection and monitoring of waves. Furthermore, for the prediction of outcome, Adaptive Boosting Classifier has shown the best accuracy of 81.77% as compared with other classifiers.

• Spatial Information Research
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• v.16 no.1
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• pp.19-32
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• 2008

Usually in South Korea, land cover type and topographic undulation are frequently changed even in a narrow area. However, most of researches using aerial LIDAR(LIght Detection And Ranging) data in abroad had been acquired in the study areas to be changed infrequently. This research was performed to explore reconstruction methodologies of 3D surface models considering the distribution of land cover type and topographic undulation. Composed of variously undulatory forests, rocky river beds and man-made land cover such as streets, trees, buildings, parking lots and so on, an area was selected for the research. First of all, the area was divided into three zones based on land cover type and topographic undulation using its aerial ortho-photo. Then, aerial LIDAR data was clipped by each zone and different 3D modeling processes were applied to each clipped data before integration of each models and reconstruction of overall model. These kinds of processes might be effectively applied to landscape management, forest inventory and digital map composition. Besides, they would be useful to resolve less- or over-extracted problems caused by simple rectangle zoning when an usual data processing of aerial LIDAR.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.29-38
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• 2024

The Matched Field Processing (MFP) is an estimation method for a source range and depth based on the prediction of sound propagation. However, as the frequency increases, the prediction inaccuracy of sound propagation increases, making it difficult to estimate the source position. Recently proposed, the Frequency-Difference Matched Field Processing (FD-MFP) is known to be robust even if there is a mismatch by applying a frequency-difference autoproduct extracted from the auto-correlation of a high frequency signal. In this paper, in order to evaluate the performance of the FD-MFP using a horizontal line array, simulations were conducted in the environment of the East Sea of Korea. In the area of Bottom Bounce (BB) and Convergence Zone (CZ) where detection of a sound source is possible at a long range, and the results of localization were analyzed. According to the the FD-MFP simulations of horizontal line array, the accuracy of localization is similar or degraded compared to the conventional MFP due to diffracted field and mismatch of sound speed. There was no clear result from the simulations conforming that the FD-MFP was more robust to mismatch than the conventional MFP.

• Journal of the Korean Society for Railway
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• v.19 no.3
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• pp.304-313
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• 2016

It is necessary to receive telegrams transmitted by transponder tags installed along the track in order to detect the exact position of a high-speed train. In a high-speed railway environment, telegrams can be corrupted by the electromagnetic interference that comes from onboard electric train power equipment or wayside devices. In this study, we verified the railway environment compatibility of a high-speed transponder system developed as a train position detection system. We installed transponder tags on the Honam high-speed line and measured the number of error-free telegrams received from the transponder tag while the HEMU-430X was running at 268km/h~334km/h. Based on the measurement, we estimated the length of the contact zone formed between the transponder reader and tag. Field test results allow us to estimate how many error-free telegrams can be received when HEMU-430X is at speeds up to 400km/h.

• Computers and Concrete
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• v.10 no.2
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• pp.135-147
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• 2012

At mesoscale, concrete is considered as a three-phase composite material consisting of the aggregate particles, the cement matrix and the interfacial transition zone (ITZ). The reconstruction of the internal structures for concrete composites requires the identification of the boundary of the aggregate particles and the cement matrix using digital imaging technology followed by post-processing through MATLAB. A parameter study covers the subsection transformation, median filter, and open and close operation of the digital image sample to obtain the optimal parameter for performing the image processing technology. The subsection transformation is performed using a grey histogram of the digital image samples with a threshold value of [120, 210] followed by median filtering with a $16{\times}16$ square module based on the dimensions of the aggregate particles and their internal impurity. We then select a "disk" tectonic structure with a specific radius, which performs open and close operations on the images. The edges of the aggregate particles (similar to the original digital images) are obtained using the canny edge detection method. The finite element model at mesoscale can be established using the proposed image processing technology. The location of the crack determined through the numerical method is identical to the experimental result, and the load-displacement curve determined through the numerical method is in close agreement with the experimental results. Comparisons of the numerical and experimental results show that the proposed image processing technology is highly effective in reconstructing the internal structures of concrete composites.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.5
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• pp.20-30
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• 2007

Environmental Conservation Value Assessment Map (ECVAM) is the class map to divide the national land into conservation areas and development areas based on legal and ecological assessment criteria. It contributes to enhancements of the efficiency and the scientificity when framing a policy in various fields including the environment. However, it is impossible to understand the multiphase vegetation structure as data on judging the national forest class in ECVAM are restricted to areal information of Ecological Nature Status, Degree of Green Naturality and Forest Map. This point drops the reliability of ECVAM. Therefore we constructed vegetation information using LiDAR (Light Detection And Raging) technology. We generated Biomass Class Maps as final results of this study, to introduce the new forest assessment criterion in ECVAM that alternates or makes up for existing forest assessment criteria. And then, we compared these with Forest Map and Landsat TM NDVI image. As a result, biomass classes are generally higher than stand age classes and DBH classes of Vegetation Map, and lower than NDVI of Landsat TM image because of the difference of time on data construction. However distributions between these classes are mostly similar. Therefore we estimates that it is possible to apply the biomass item to the new forest assessment criterion of ECVAM. The introduction of the biomass in ECVAM makes it useful to detect the vegetation succession, to adjust the class of the changed zone since the production of Vegetation Map and to rectify the class error of Vegetation Map because variations on tree heights, forest area, gaps between trees, vegetation vitality and so on are acquired as interim findings in process of computing biomass.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1085-1086
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• 2008

Shunt active filter can compensate harmonic current of utility results from non-linear loads such as rectifiers, cycloconverters and arc furnaces. It has the same structure as photovoltaic(PV) generation system. So, It was proposed the system that generates PV power and also has active filter function. It is called PV-AF(Photovoltaic and Active Filter) power generation system. Islanding can be occurred in an inverter based dispersed generation system, when the system disconnected from utility and loads are entirely supplied by PV system only. Islanding may result in interference to grid protection devices, equipment damage, and even personnel safety hazards. Therefore, islanding has to be detected and protected. The conventional anti-islanding methods have NDZ(None-Detection Zone) or power quality degradation. But PV-AF power generation system has the function of not only shunt active filter but also anti-islanding method without NDZ. In this paper, a novel anti-islanding method for PV-AF system is proposed and analysed in detail.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.281-286
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• 2004

The wear process of end mill is a so complicated process that a more reliable technique is required for the monitoring and controling the tool life and its performance. This research presents a new tool wear monitoring method based on the sound signal generated on the machining. The experiment carried out continuous-side-milling for using the high-speed steel end mill under wet condition. The sound pressure was measured at 0.5m from the cutting zone by a dynamic microphone, and was analyzed at frequency domain. The tooth passing frequency appears as a harmonics form, and end mill wear is related with the first harmonic. It can be concluded from the result that the tool wear is correlate with the intensity of the measured sound at tooth passing frequency estimation of end mill wear using sound is possible through frequency analysis at tooth passing frequency under the given circumstances.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.246-253
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• 2003

The initiation and growth of short fatigue cracks in the simulated aircraft structure with a series of rivet holes was detected by acoustic emission (AE). The location and the size of short tracks were determined by AE source location techniques and the measurement with traveling microscope. AE events increased intermittently with the initiation and growth of short cracks to form a stepwise increment curve of cumulative AE events. For the precise determination of AE source locations, a region-of-interest (ROI) was set around the rivet holes based on the plastic zone size in fracture mechanics. Since the signal-to-noise ratio (SNR) was very low at this early stage of fatigue cracks, the accuracy of source location was also enhanced by the wavelet transform do-noising. In practice, the majority of AE signals detected within the ROI appeared to be noise from various origins. The results showed that the effort of structural geometry and SNR should be closely taken into consideration for the accurate evaluation of fatigue damage in the structure.

• Geosystem Engineering
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• v.21 no.5
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• pp.243-250
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• 2018

This study investigated nitrite ($NO_2{^-}$) accumulation due to FA (Free Ammonia: $NH_3$) inhibition in an anaerobic-aerobic-anoxic (AOA) process reactor to mainly treat wastewater containing 302-610 mg/L of $NH_3/NH_4{^+}-N$. Based on an experimental operation focusing on the nitrification, it was observed that $NO_2{^-}$ was accumulated in the aerobic nitrification zone as pH increased, due to inhibition of $NO_2{^-}$ conversion to $NO_3{^-}$ by FA. This result implied FA inhibition to NOB ($NO_2{^-}$-Oxidizing Bacteria) for converting $NO_2{^-}$ to $NO_3{^-}$. The objective of this study is to develop a feasible monitoring procedure for early detection of the FA inhibition toward $NO_2{^-}$ accumulation and poor nitrification. Thus, in order to rapidly assess FA concentrations, an $NH_3$ probe was utilized to measure $NH_3$ concentrations together with applying a simple model prediction using the measured $NH_4{^+}$ concentrations, the Henry's law constant of $NH_3$ and measured pH. The predictive model $NH_3$ levels were verified by a good correlation (89%) with the corresponding measured data, but the model prediction underestimated FA concentrations at less than 7.4 and a little overestimated at pH above 7.5. Interestingly, accumulated $NO_2{^-}$ levels were roughly correlated with FA levels that were observed at delayed time points. This reflects the detected FA levels can be good indicators of $NO_2{^-}$ levels with some delayed time. $NO_2{^-}$ accumulation started at measured FA concentrations of higher than approximately 3 mg/L and ceased below that FA level.