• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.8 no.1
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• pp.124-132
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• 1998

The Korean-made passive samplers were evaluated at the working environment for field testing. Tested materials were n-hexane, toluene and trichloroethylene. The performance of passive samplers depended on types and concentrations of organic vapors. Sampling rates were not steady until certain concentrations. The optimum concentration for determination of airborne toluene by passive samplers was equal to or over 10 ppm which is 1/10 of the Korean occupational exposure limit. Optimum concentration of n-hexane was equal to and over 1 ppm which is 1/50 of Korean occupational exposure limit. But for trichloroehtylene, coefficient of variation was 53.5 %. Passive samplers may be used for determination of n-hexane. For other materials, further study on the performance of Korean-made passive samplers is required.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.1
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• pp.13-21
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• 2010

The prediction of contract cancellation of customers is essential in insurance companies but it is a difficult problem because the customer database is large and the target or cancelled customers are a small proportion of the database. This paper proposes a new data mining approach to the binary classification by handling a large-scale unbalanced data. Over-sampling, clustering, regularized logistic regression and boosting are also incorporated in the proposed approach. The proposed approach was applied to a real data set in the area of insurance and the results were compared with some other classification techniques.

• Environmental Engineering Research
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• v.10 no.6
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• pp.316-327
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• 2005

Constructed wetlands provide several benefits that are not solely limited to storm water management and are becoming common in storm water management. In this research, four recently constructed wetlands underwent in situ and laboratory water sampling to determine their efficiency in removing storm water pollutants over a 5-month period. From the sampling results, it was determined that each of the wetlands was able to reduce the concentration of pollutants in the stormwater. To aid in the assessment of the wetlands against each other, a model was developed to determine the extent of removal of stormwater pollutants over the length of the wetland. The results from this model complimented the data collected from the field. Improvements, such as increased amounts of vegetation were recommended for the wetlands with the aim of increasing the effectiveness. Further investigations into the wetlands will allow for better understanding of the wetland's performance.

• Transactions of the Society of Information Storage Systems
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• v.3 no.4
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• pp.154-159
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• 2007

본 논문에서는 확대, 축소, 회전 등과 같은 선형, 비선형 왜곡이 포함된 이미지에 대해, 이미지의 외곽선을 찾아서 이미지를 보정하고 싱크 마크(Sync. Mark)를 사용하여 데이터를 샘플링하는 알고리즘을 제안한다. 외곽선을 찾기 위한 방법으로 허프 변환(Hough Transform)을 사용하였으며, 찾아낸 외곽선을 이용하여 이미지의 영역을 인식하고, 이미지의 왜곡을 줄이기 위하여 이미지 와핑(warping) 기법을 적용하였다. 이미지의 비선형 왜곡을 보상하기 위하여 이미지의 싱크 마크(Sync. Mark)를 공분산(covariance)을 사용하여 인식하고 샘플링 위치를 보정하였다. 또한, 제안된 알고리즘은 Over Sampling 자체를 하나의 이미지 확대로 인식하여 처리하기 때문에 어떠한 Over Sampling 에도 적용 가능하다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2961-2975
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• 2022

The Location-Based Service (LBS) is one of the most well-known services on the Internet. Positioning is the primary association with LBS services. This study proposes an intelligent LoRa-based positioning system, called AI@LBS, to provide accurate location data. The fingerprint mechanism with the clustering algorithm in unsupervised learning filters out signal noise and improves computing stability and accuracy. In this study, data noise is filtered using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, increasing the positioning accuracy from 95.37% to 97.38%. The problem of data imbalance is addressed using the SMOTE (Synthetic Minority Over-sampling Technique) technique, increasing the positioning accuracy from 97.38% to 99.17%. A field test in the NTUST campus (www.ntust.edu.tw) revealed that AI@LBS system can reduce average distance error to 0.48m.

• Industry Promotion Research
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• v.8 no.1
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• pp.111-117
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• 2023

Sampling inspection methods for quality control have been proposed a lot in the industry. However, the sampling inspection method for reliability, which is a quality over time, has been relatively less presented, and there are not many literatures that are clearly summarized. Therefore, this paper focuses on the reliability conformity test to verify that the reliability evaluation scale value of the target is satisfied during the reliability test. To this end, first, we look at the conditions that both consumers and producers can satisfy in terms of the OC curve and find out what sampling methods satisfy the desired level of producer risk and consumer risk. Next, two methods of the reliability sampling methods such as attribute and variable reliability sampling methods are examined. Specifically, the attribute reliability sampling method is a form of sampling plan where n samples are tested for a certain period of T hours and the lot is accepted if the number of failures is less than or equal to a certain number c. On the other hand, the variable reliability sampling method is a form of sampling plan where the lot is accepted if the reliability evaluation scale such as MTBF satisfies a certain standard. Both sampling plans may also use inspection tables.

• Journal of Environmental Science International
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• v.16 no.2
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• pp.187-195
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• 2007

Long-term passive diffusive samplers(PDS) have been used to measure $NO_2\;and\;SO_2$ concentrations at 21 sampling sites in Daejeon, Korea during the period of January 2000 - December 2002. The spatial distributions of annual $NO_2\;and\;SO_2$ concentrations were mapped. Average annual $NO_2$ concentration over the sampling period was $28.5{\pm}12.5\;ppb$, ranging from 1.2 to 81.7 ppb. Average annual $SO_2$ concentration over the sampling period was $7.7{\pm}4.8\;ppb$, ranging from 0.6 to 26.8 ppb. On average, $NO_2$ concentration was approximately 5.8%(1.6 ppb) larger in 2002. $SO_2$ concentration was decreased by 13%(1.1 ppb) during the sampling period. The seasonal variation of $NO_2\;and\;SO_2$ concentration was observed with a tendency to be higher in fall and winter. $NO_2\;and\;SO_2$, concentrations measured at different site types(patterns of land use) show significant difference. The observed difference in concentration was associated with difference in emissions of $NO_2$ from motor vehicles and $SO_2$ by non-traffic fuel consumption for heating.

• Asian Journal of Turfgrass Science
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• v.16 no.2
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• pp.97-106
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• 2002

The oriental beetle, Exomala orientalis, Is the most important insect pest of turfgrass in Korean golf courses. The study was carried out to get practical information on the sampling of E. orientalis in golf courses. Real numbers of E. orientalis larvae were compared with and observed numbers depending on sampling size (5$\times$5 cm, l0$\times$10 cm, 20$\times$20 cm, 30$\times$30 cm, and 40$\times$40 cm) and times (3 to 15 replicates) in Dongrae Benest Golf Club. Over 95% accuracy was obtained between real data and estimated data at the density of over 303 larvae/m$^2$ when the 20$\times$20 cm was sampled with 4 replications. Larval density of E. orientalis was different depending on year and course sites (tee, fairway, rough, green).

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.28-32
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• 2014

For a signal such as speech showing piece-wise linear shape in a very short time period, a nonuniform sampling method based on the inflection point detection (IPD) is proposed to reduce data rate. The method exploits the geometrical characteristics of signal further than the existing local maxima/minima detection (MMD) based sampling method. As results, the reconstructed signal by the interpolation of the IPD based sampled data resembles the original speech more. Computer simulation shows that the proposed IPD based method produces about 9~23 dB improvement over the existing MMD method. To show the usefulness of the IPD technique, it is applied to speech coding, and compared to the continuously variable slope delta modulation (CVSD). The nonuniformly sampled data is binary coded with one bit flag set "1". Noninflection samples are not sent, but only flag bits set 0 are sent. The method shows 0.3 ~ 9 dB SNR and 0.5 ~ 1.3 mean opinion score (MOS) improvements over the CVSD.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.19-27
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• 2020

In this paper, we propose a machine learning method for diagnosing the failure of a gas pressure regulator. Originally, when implementing a machine learning model for detecting abnormal operation of a facility, it is common to install sensors to collect data. However, failure of a gas pressure regulator can lead to fatal safety problems, so that installing an additional sensor on a gas pressure regulator is not simple. In this paper, we propose various machine learning approach for diagnosing the abnormal operation of a gas pressure regulator with only the flow rate and gas pressure data collected from a gas pressure regulator itself. Since the fault data of a gas pressure regulator is not enough, the model is trained in all classes by applying the over-sampling method. The classification model was implemented using Gradient boosting, 1D Convolutional Neural Networks, and LSTM algorithm, and gradient boosting model showed the best performance among classification models with 99.975% accuracy.