• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.289-289
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• 2018

하천의 유사는 이동 형태에 따라 소류사와 부유사로 분류되는데, 대부분의 자연하천에서 유사는 난류로 인해 부유사의 형태로 이송된다. 하천 흐름 내 부유사는 크기와 모양이 서로 다른 입자들로 구성되어 있으며, 부유사의 입도 분포는 유사의 특성 뿐 아니라 흐름의 유사 이동 능력과 같은 유수동역학적 특성 또한 함께 고려되어야 한다. 유사의 입도 분포는 통계적인 방법을 통해 결정되며, 일반적으로 모래 하천의 입도 분포는 로그 정규 분포를 따르는 것으로 알려져 있다. 이에 본 연구에서는 부유사의 입도 분포 모형을 이용하여 다양한 흐름 조건 하에서의 입도분포를 살펴본다. 비점착성 유사의 입도 분포 모형은 점착성 유사의 입도 분포 모형으로부터 얻어지며, 1차원 유사 이동 모형과의 결합을 통해 다양한 흐름 조건에서 부유된 유사의 입도 분포를 모의할 수 있다. 여러 연구결과를 분석한 결과, 부유사의 입도 분포는 최빈치가 하나인 단최빈 분포(Unimodal Distribution)가 대다수를 차지하였으나, 최대 빈도가 두 개 이상 나타나는 쌍최빈 분포(Bimodal Distribution) 또한 흔히 나타나는 것이 확인된다. 본 연구에서 개발된 비점착성 유사의 입도 분포모형은 단최빈 및 쌍최빈이 나타난 실험실 실험 자료를 이용하여 검증된다. 단최빈의 입도 분포를 나타내는 실험 결과 2가지와 쌍최빈의 입도 분포를 나타내는 실험 결과 2가지를 이용하였을 때, 총 4가지의 다양한 유수동역학적 조건 하에서 비점착성 유사의 입도 분포가 합리적으로 모의되는 것이 확인된다.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.355-363
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• 2021

The conventional Flow Duration Curve has limitations that it does not consider hydrologic persistence of daily discharge, that the daily discharge is greatly affected by the maximums or minimums, and that the date of occurrence and duration of a specific discharge cannot be known. In this study, we propose a Daily Mode Discharge Curve, which consists of aligning the daily discharge each year by the date of occurrence, calculating the daily mode discharge, and averaging them every 5 days. As a result of reviewing the long-term observational daily discharge data at 8 points upstream and downstream of the mainstream of the 4 major rivers in Korea, it was found that the daily discharge at all points shows hydrological persistence, and the distortion of it was alleviated by using Daily Mode Discharge Curve. We also suggest that the Daily Mode Discharge Curve is useful for utilizing reference discharge such as Drought, Low, Normal, Plentiful, and Flood Discharge.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.515-523
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• 2012

Most companies make efforts to maximize their profitability by improving loyalty to existing customers through customer relationship management (CRM). According to the Wikipedia, CRM is a widely implemented strategy for managing a company's interactions with customers, clients and sales prospects. And RFM is a method used for analyzing customer behavior and defining market segments. It is commonly used in database marketing and direct marketing and has received particular attention in retail. In general, one considers recency, frequency, and monetary for customer segmentation in RFM method. In this paper, we apply RFMP method added to the purchase period of advertising items in the traditional RFM model for real estate customer segmentation. We will be able to establish the differentiated marketing strategy by RFMP method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.33-39
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• 2018

An additive noise reduction algorithm for a mass spectrum analyzer is proposed. From the measured ion signal, we first used an estimated threshold from the mode of the measured signal to eliminate background noises with the white Gaussian characteristics. Also, a signal block corresponding to each mass index is constructed to perform a second order curve fitting and a linear approximation to signal block. In this process, the effective signal block composed of only the ion signal can be reconstructed by removing the impulsive noises and the sample signals which are insufficient to be viewed as normal ion signals. By performing curve fitting on the effective signal block, the noise-free mass spectrum can be obtained. To evaluate the performance of the proposed method, a simulation was performed using the signals acquired from the development equipment. Simulation results show the validity of the threshold setting from the mode and the superiority of the proposed curve fitting and linear approximation based noise canceling algorithm.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.14 no.3
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• pp.201-209
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• 2016

The object of this study was to evaluate the separation distance from a temporary storage facility satisfying the dose criteria. The calculation of ambient dose rates took into account cover soil thickness, facility size, and facility type by using MCNPX code. Shielding effects of cover soil were 68.9%, 96.9% and 99.7% at 10 cm, 30 cm and 50 cm respectively. The on-ground type of storage facility had the highest ambient dose rate, followed by the semi-ground type and the underground type. The ambient dose rate did not vary with facility size (except $5{\times}5{\times}2m\;size$) due to the self-shielding of decontamination waste in temporary storage. The separation distances without cover soil for a $50{\times}50{\times}2m\;size$ facility were evaluated as 14 m (minimum radioactivity concentration), 33 m (most probably radioactivity concentration), and 57 m (maximum radioactivity concentration) for on-ground storage type, 9 m, 24 m, and 45 m for semi-underground storage type, and 6 m, 16 m, and 31 m for underground storage type.

• 대한예방의학회:학술대회논문집
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• 2004.10a
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• pp.29.2-30
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• 2004

• Resources Recycling
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• v.27 no.1
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• pp.84-91
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• 2018

In this study, a novel soft information based most probable classification scheme is proposed for sorting recyclable metal alloys with laser induced breakdown spectroscopy (LIBS). Regression analysis with LIBS captured spectrums for estimating concentrations of common elements can be efficient for classifying unknown arbitrary metal alloys, even when that particular alloy is not included for training. Therefore, partial least square regression (PLSR) is employed in the proposed scheme, where spectrums of the certified reference materials (CRMs) are used for training. With the PLSR model, the concentrations of the test spectrum are estimated independently and are compared to those of CRMs for finding out the most probable class. Then, joint soft information can be obtained by assuming multi-variate normal (MVN) distribution, which enables to account the probability measure or a prior information and improves classification performance. For evaluating the proposed schemes, MVN soft information is evaluated based on PLSR of LIBS captured spectrums of 9 metal CRMs, and tested for classifying unknown metal alloys. Furthermore, the likelihood is evaluated with the radar chart to effectively visualize and search the most probable class among the candidates. By the leave-one-out cross validation tests, the proposed scheme is not only showing improved classification accuracies but also helpful for adaptive post-processing to correct the mis-classifications.

• Korean Journal of Ecology and Environment
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• v.55 no.2
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• pp.145-155
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• 2022

Koreoleptoxis nodifila (Martens, 1886) is an endangered species only living in the central and north streams of South Korea. However, there is a lack of information on physical habitat characteristics of K. nodifila. We aimed to determine preference ranges for water depth, current velocity, streambed substrate of K. nodifila. The weibull model was used to estimate the habitat suitability based on distribution of individual abundance by physical factors. Optimal depth preferences ranged from 0.53~17.17 cm, current preferences ranged from 48.40~81.03 cm s^-1 and substrate (𝜱_m) preferences ranged from -4.36~ -2.26. Median values of central tendency were determined as follows: water depth 16.73 cm, current velocity 65.23 cm s^-1, substrate -3.51. Mean values of central tendency were determined as follows: water depth 21.32 cm, current velocity 65.65 cm s^-1, substrate -3.63. Mode values of central tendency were determined as follows: water depth 5.17 cm, current velocity 64.77 cm s^-1, substrate -3.24. Based on the habitat suitability analysis, the microhabitat types of K. nodifila were determined as riffle and coarse-grained streambed.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.245-255
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• 2013

The object of study is to propose a method for grouping R, F, and M in RFM model. Our model uses 6 levels using standard normal distribution. First level is upper 2.5% and second level next 13.5%, third level next 34%, fourth level next 34%, fifth level next 13.5%, sixth level next 2.5%. Values are symmetric and limits are clear. We compare proposed model with traditional 5 level model and 10 level model using NDSL data of KISTI. Proposed model divides most clearly the distribution of the RFM function for all cases of weights, because it uses the distribution of customers. Comparison studies of our model with grouping using cluster analysis and studies on weights of RFM model are needed.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.38-49
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• 2021

This study analyzed the trend of the term 'false and exaggerated advertisement' in 5,141 newspaper articles from 1990 to 2019 using text mining methodology. First of all, we identified the most frequent keywords of false and exaggerated advertisements through frequency analysis for all newspaper articles, and understood the context between the extracted keywords. Next, to examine how false and exaggerated advertisements have changed, the frequency analysis was performed by separating articles by 10 years, and the tendency of the keyword that became an issue was identified by comparing the number of academic papers on the subject of the highest keywords of each year. Finally, we identified trends in false and exaggerated advertisements based on the detailed keywords in the topic using the topic modeling. In our results, it was confirmed that the topic that became an issue at a specific time was extracted as the frequent keywords, and the keyword trends by period changed in connection with social and environmental factors. This study is meaningful in helping consumers spend wisely by cultivating background knowledge about unfair advertising. Furthermore, it is expected that the core keyword extraction will provide the true purpose of advertising and deliver its implications to companies and related employees who commit misconduct.