• Smart Structures and Systems
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• v.25 no.6
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• pp.751-764
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• 2020

Real-time monitoring of stiffness and strength in cement based system has received significant attention in past few decades owing to the development of advanced techniques. Also, use of environment friendly supplementary cementitious materials (SCM) in cement, though gaining huge interest, severely affect the strength gain especially in early ages. Continuous monitoring of strength- and stiffness- gain using an efficient technique will systematically facilitate to choose the suitable time of removal of formwork for structures made with SCM incorporated concrete. This paper presents a technique for monitoring the strength and stiffness evolution in hydrating fly ash blended cement systems using electro-mechanical impedance (EMI) based technique. It is important to observe that the slower pozzolanic reactivity of fly ash blended cement systems could be effectively tracked using the evolution of equivalent local stiffness of the hydrating medium. Strength prediction models are proposed for estimating the strength and stiffness of the fly ash cement system, where curing age (in terms of hours/days) and the percentage replacement of cement by fly ash are the parameters. Evaluation of strength as obtained from EMI characteristics is validated with the results from destructive compression test and also compared with the same obtained from commonly used ultrasonic wave velocity (UPV). Statistical error indices indicate that the EMI technique is capable of predicting the strength of fly ash blended cement system more accurate than that from UPV. Further, the correlations between stiffness- and strength- gain over the time of hydration are also established. From the study, it is found that EMI based method can be effectively used for monitoring of strength gain in the fly ash incorporated cement system during hardening.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.223-228
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• 2020

The stock price reflects people's psychology, and factors affecting the entire stock market include economic growth rate, economic rate, interest rate, trade balance, exchange rate, and currency. The domestic stock market is heavily influenced by the stock index of the United States and neighboring countries on the previous day, and the representative stock indexes are the Dow index, NASDAQ, and S & P500. Recently, research on stock price analysis using stock news has been actively conducted, and research is underway to predict the future based on past time series data through artificial intelligence-based analysis. However, even if the stock market is hit for a short period of time by the forecasting system, the market will no longer move according to the short-term strategy, and it will have to change anew. Therefore, this model monitored Samsung Electronics' stock data and news information through text mining, and presented a predictable model by showing the analyzed results.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.291-291
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• 2013

The interior vehicle noise due to the exterior aerodynamic field is an important topic in the acoustic design of a car. The air flow detached from the A-pillar and impacting the side windows are of particular interest as they are located close to the driver / passenger and provides a lower insulation index than the trimmed car body parts. HMC is interested in the numerical prediction of this aerodynamic noise generated by the car windows with the final objective of improving the products design and reducing this noise. The methodology proposed in this paper relies on two steps: the first step involves the computation of the exterior flow and turbulence induced non-linear acoustic field using the CAA(Computational aeroacoustics) solver CAA++. The second step consists in the computation of the vibro-acoustic transmission through the side window using the finite element vibro-acoustic solver Actran. The internal air cavity including trim component are included in the simulation. In order to validate the numerical process, an experimental set-up has been created based on a generic car shape. The car body includes the windshield and two side windows. The body is made of aluminum and trimmed with porous layers. First, this paper describes the method including the CAA and the vibro-acoustic models, from the boundary conditions to the different components involved, like the windows, the trims and the car cavity is detailed. In a second step, the experimental set-up is described. In the last part, the vibration of the windshield and windows, the total wind noise level results and the relative contributions of the different windows are then presented and compared to measurements. The influence of the flow yaw angle (different wind orientation) is also assessed.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.187-196
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• 1999

The increasing interest in the use of Automated Speed Enforcement (ASE) systems in Korea enables to enforce speed violation by National Police Agency. We have analyzed the mechanism of ASE systems on traffic safety throughout Korea. 1 The data collected on a 2km road-section of each 32 ASE stations during one rear period indicate significant safety improvement. The results were (a) a decrease in the total number of accidents of 28%, (b) a decrease in the number of fatalities of 60%. 2. The study also that ASE systems are effective to reduce average speed, speed variance, and short headway. 3. Based on the operational data collected at 15 locations, an aggregate safety prediction model is proposed as a multiple regressions form. The primary operational variables that appear to affect the frequencies of accident are : average speed, speed variance, and the number of vehicles exceeding 30km/h of posted speed limit.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.393-400
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• 2007

We present in this paper a novel power load prediction method using temporal pattern mining from AMR(Automatic Meter Reading) data. Since the power load patterns have time-varying characteristic and very different patterns according to the hour, time, day and week and so on, it gives rise to the uninformative results if only traditional data mining is used. Also, research on data mining for analyzing electric load patterns focused on cluster analysis and classification methods. However despite the usefulness of rules that include temporal dimension and the fact that the AMR data has temporal attribute, the above methods were limited in static pattern extraction and did not consider temporal attributes. Therefore, we propose a new classification method for predicting power load patterns. The main tasks include clustering method and temporal classification method. Cluster analysis is used to create load pattern classes and the representative load profiles for each class. Next, the classification method uses representative load profiles to build a classifier able to assign different load patterns to the existing classes. The proposed classification method is the Calendar-based temporal mining and it discovers electric load patterns in multiple time granularities. Lastly, we show that the proposed method used AMR data and discovered more interest patterns.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.87-87
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• 2019

The consumption of herbal medicine and related products (herbal products) have increased in South Korea. At the same time the quality, safety, and efficacy of herbal products is being raised. Currently, the herbal products are standardized and controlled according to the requirements of the Korean Pharmacopoeia, the National Institute of Health and the Ministry of Public Health and Social Affairs. The validation of herbal products and their medicinal component is important, since many of these herbal products are composed of two or more medicinal plants. However, there are no tools to support the validation process. Interest in deep learning has exploded over the past decade, for herbal medicine using algorithms to achieve herb recognition, symptom related target prediction, and drug repositioning have been reported. In this study, individual images of four herbs (Panax ginseng C.A. Meyer, Atractylodes macrocephala Koidz, Poria cocos Wolf, Glycyrrhiza uralensis Fischer), actually sold in the market, were achieved. Certain image preprocessing steps such as noise reduction and resize were formatted. After the features are optimized, we applied GoogLeNet_Inception v4 model for herb image recognition. Experimental results show that our method achieved test accuracy of 95%. However, there are two limitations in the current study. Firstly, due to the relatively small data collection (100 images), the training loss is much lower than validation loss which possess overfitting problem. Secondly, herbal products are mostly in a mixture, the applied method cannot be reliable to detect a single herb from a mixture. Thus, further large data collection and improved object detection is needed for better classification.

• Genomics & Informatics
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• v.18 no.4
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• pp.42.1-42.9
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• 2020

Chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-Seq) is a powerful technology to profile the location of proteins of interest on a whole-genome scale. To identify the enrichment location of proteins, many programs and algorithms have been proposed. However, none of the commonly used peak calling programs could accurately explain the binding features of target proteins detected by ChIP-Seq. Here, publicly available data on 12 histone modifications, including H3K4ac/me1/me2/me3, H3K9ac/me3, H3K27ac/me3, H3K36me3, H3K56ac, and H3K79me1/me2, generated from a human embryonic stem cell line (H1), were profiled with five peak callers (CisGenome, MACS1, MACS2, PeakSeq, and SISSRs). The performance of the peak calling programs was compared in terms of reproducibility between replicates, examination of enriched regions to variable sequencing depths, the specificity-to-noise signal, and sensitivity of peak prediction. There were no major differences among peak callers when analyzing point source histone modifications. The peak calling results from histone modifications with low fidelity, such as H3K4ac, H3K56ac, and H3K79me1/me2, showed low performance in all parameters, which indicates that their peak positions might not be located accurately. Our comparative results could provide a helpful guide to choose a suitable peak calling program for specific histone modifications.

• Atmosphere
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• v.29 no.2
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• pp.213-218
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• 2019

A valuation of air pollution is critical for relevant policy-making for the public and research direction. This study conducted a willingness-to-pay (WTP) survey using contingent valuation method (CVM) in Seoul Korea. In detail, this study puts an emphasis on its temporal changes referred on two surveys conducted in 2014 and 2019. In reference to the previous studies in 2002, our survey indicated that the public awareness of air pollution and interests on its sources and solutions increased noticeably. Our survey showed that WTP increased significantly from 2588 to 4827 and 8240 Korean Won $month^{-1}$ in 2002, 2014, and 2019, respectively. Moreover, the percentage of respondents to pay the WTP also increased from 48% to 68% and 79% in 2002, 2014, and 2019, respectively. Our analysis based on the number of Google search on particulate matters (PMs) strongly suggests that such the noticeable increases of the public attention to air pollution is well accorded with the moment of the announcement of a standard for ultra-fine particles and the start of PM prediction in late 2013. But the Google search rate grew about 16.7 times in 2009 compared to 2014, which is much larger than the growth rate of interest and WTP between 2014 and 2019. Our results shed light on policy decision for the right person in the right place on the right time in the era of air pollution.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.405-412
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• 2019

This paper aims to identify differences between the perception of the fourth industrial revolution of the disabled who use the IL center or the disabled in the community and its workers. It surveyed 178 disabled users and 173 workers at eight centers of the handicapped in Busan and South Gyeongsang-do and conducted an analysis on their interests in the fourth industry, awareness of the latest technology, and prediction of changes in the disabled welfare center. Although worker's interest in the fourth industry was higher than their users, their perception of the degree of preparation by the disabled welfare centers indicated that the worker's level of future institutional readiness was lower than that of the users. The results will be used to help set directions for future guidelines and plans for the welfare of the disabled.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.823-837
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• 2018

The objective of this study was to evaluate the firmness and the sweetness index (SI) of tomatoes with a hyperspectral imaging (HSI) technique within the wavelength range of 1000 - 1550 nm. The hyperspectral images of 95 tomatoes were acquired with a push-broom hyperspectral reflectance imaging system, from which the mean spectra of each tomato were extracted from the regions of interest. The reference firmness and sweetness index of the same sample was measured and calibrated with their corresponding spectral data by partial least squares (PLS) regression with different preprocessing methods. The calibration model developed by PLS regression based on the Savitzky-Golay second-derivative preprocessed spectra resulted in a better performance for both the firmness and the SI of the tomatoes compared to models developed by other preprocessing methods. The correlation coefficients ($R_{pred}$) were 0.82, and 0.74 with a standard error of prediction of 0.86 N, and 0.63, respectively. Then, the feature wavelengths were identified using a model-based variable selection method, i.e., variable importance in projection, from the PLS regression analyses. Finally, chemical images were derived by applying the respective regression coefficients on the spectral image in a pixel-wise manner. The resulting chemical images provided detailed information on the firmness and the SI of the tomatoes. The results show that the proposed HSI technique has potential for rapid and non-destructive evaluation of firmness and the sweetness index of tomatoes.