• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.1-8
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• 2010

Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.1-17
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• 2008

Data mining is defined as the process of discovering meaningful and useful pattern in large volumes of data. In particular, finding associations rules between items in a database of customer transactions has become an important thing. Some data structures and algorithms had been proposed for storing meaningful information compressed from an original database to find frequent itemsets since Apriori algorithm. Though existing method find all association rules, we must have a lot of process to analyze association rules because there are too many rules. In this paper, we propose a new data structure, called a Frequent Pattern Network (FPN), which represents items as vertices and 2-itemsets as edges of the network. In order to utilize FPN, We constitute FPN using item's frequency. And then we use a clustering method to group the vertices on the network into clusters so that the intracluster similarity is maximized and the intercluster similarity is minimized. We generate association rules based on clusters. Our experiments showed accuracy of clustering items on the network using confidence, correlation and edge weight similarity methods. And We generated association rules using clusters and compare traditional and our method. From the results, the confidence similarity had a strong influence than others on the frequent pattern network. And FPN had a flexibility to minimum support value.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.521-521
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• 2012

우리나라는 산악지역이 국토의 대부분을 차지하고 있어 전체유역을 놓고 볼 때 대하천이 차지하는 부분보다는 중소하천이 차지하는 부분이 상대적으로 크고, 교량의 길이가 짧은 소교량이 수적으로 많은 부분을 차지하고 있다. 그중에서도 특히 중소하천의 유량은 시간적으로 매우 빠르게 변화하며 유속 또한 급속히 빨라져 하상의 변형이 순식간에 일어나고 있다. 이와 같은 시간적, 공간적인 호우특성과 지형특성으로 인하여 중소하천에 위치한 교량은 특히 세굴에 매우 취약함을 보여주고 있다. 하천에 건설되는 교량의 수명이나 안정성에 세굴이 미치는 영향은 매우 크며, 특히 우리나라와 같이 홍수 시 단기간에 걸쳐 유량이 급증하는 경우 유속에 의한 교량 기초의 급격한 세굴은 예상치 못한 교량 붕괴 사고를 초래할 수 있다. 현재 국내 소하천에 설치된 교량은 약 3,470개소(지방도 기준)로 다양한 하부구조로 설계되어 있다. 이렇게 하천 내에 세워진 교량과 같은 횡단 구조물들은 그 크기에 상관없이 하천의 형태에 영향을 미치게 된다. 그중에서 교량 세굴은 하천 횡단구조물로 인하여 발생되는 가장 중요한 문제 중의 하나로써 교량 건설 시 교각에 영향을 주는 세굴을 예측하고 방어하기 위하여 다양한 방정식을 통하여 신설교량의 교각세굴을 예측한다. 하지만 대부분의 교량 세굴 공식들은 실험실에서의 실험 결과를 토대로 개발되었기 때문에 이들 공식들이 산정한 국소 세굴량이 얼마나 정확한지는 실제 현장 관측 자료와의 비교를 통해서만 검증할 수 있다. 세굴 공식들의 산정 결과를 현장 실측자료와 비교하는 연구는 그 동안 다양하게 시도되었으나, 통일된 결론에는 도달하지 못하고 있다. 본 연구에서는 기존의 세굴깊이 산정 시 일반적으로 사용되어지고 있는 세굴공식들 중 소하천 교량 규모에 적용 가능한 공식들을 선별하고, 각 세굴심 추정공식에 속한 변수별 특성분석을 위하여, 5가지의 독립변수를 설정하여 국부세굴의 현장 측정값과 예측공식의 비교결과에 대하여 불일치율을 비교분석하였다. 그 결과, 모든 공식들의 불일치율의 기하 평균이 1보다 큰 것을 보여주고 있다. 즉, 모든 공식들이 과대 추정의 의미로 정확성면에서 우수한 공식들은 불일치율의 기하 평균이 1에 가깝고 기하 표준편차가 작은 공식들이 나타났으며, 이런 점에서 Froehlich 공식, Inglis-Poona II, Blench-Inglis I, Breusers 공식 등의 기하평균이 1에 가장 근접한 결과를 나타내었다. 각 세굴공식 세굴심 산정결과의 불일치율을 각각 5가지의 변수별로 도시하여 분석하였으며, 그 결과로 소하천에 대하여 적용 가능한 공식과 소하천에 적용 시에는 과다추정의 우려가 있는 공식으로 분류되어 면밀한 검토가 필요할 것으로 판단된다.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.48-63
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• 2015

In this study, we introduce various hyperspectral data processing techniques for the monitoring of shallow and coastal waters to enlarge the application range and to improve the accuracy of the end results in Korea. Unlike land, more accurate atmospheric correction is needed in coastal region showing relatively low reflectance in visible wavelengths. Sun-glint which occurs due to a geometry of sun-sea surface-sensor is another issue for the data processing in the ocean application of hyperspectal imagery. After the preprocessing of the hyperspectral data, a semi-analytical algorithm based on a radiative transfer model and a spectral library can be used for bathymetry mapping in coastal area, type classification and status monitoring of benthos or substrate classification. In general, semi-analytical algorithms using spectral information obtained from hyperspectral imagey shows higher accuracy than an empirical method using multispectral data. The water depth and quality are constraint factors in the ocean application of optical data. Although a radiative transfer model suggests the theoretical limit of about 25m in depth for bathymetry and bottom classification, hyperspectral data have been used practically at depths of up to 10 m in shallow and coastal waters. It means we have to focus on the maximum depth of water and water quality conditions that affect the coastal applicability of hyperspectral data, and to define the spectral library of coastal waters to classify the types of benthos and substrates.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.450-450
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• 2018

최근 기후변화와 수온상승으로 인한 녹조발생이 빈번하게 나타나며, 녹조발생에 관한 관심은 꾸준히 증가하고 있는 추세이다. 본 연구는 효율적인 녹조관리를 위하여 모델트리를 활용하여 클로로필-a 단기조류예측 기법을 개발하였다. 대상지역으로 영산강수계의 죽산보를 선정하였으며, 2013년 1월부터 2016년 12월까지 나주 수질자동측정망의 일 단위자료와 동일기간 광주 기상청의 일별 기상자료를 이용하였다. 상관 분석을 통해 T-N, T-P, N/Pratio와 클로로필-a, 수온, 일사량, 강수량을 독립변수로, 단기(t+1일, t+3일, t+5일, t+7일) 클로로필-a를 종속변수로 선정하여 단기조류예측기법을 개발하였다. 수집한 자료의 데이터세트는 격일 간격으로 Training, Testing 기간으로 구분하여 적용한 결과, 상관계수는 1일 예측 시, Training 기간에 0.89, Testing 기간에 0.91, 3일 예측 시, Training 기간에 0.74, Testing 기간에 0.68, 5일 예측 시, Training 기간에 0.70, Testing 기간에 0.66, 7일 예측 시, Training 기간에 0.63, Testing 기간에 0.62로 나타났다. RMSE(Root Mean Square Error)는 1일 예측 시, Training 기간에 13.96, Testing 기간에 12.22, 3일 예측 시, Training 기간에 20.03, Testing 기간에 22.14, 5일 예측 시, Training 기간에 21.32, Testing 기간에 22.57, 7일 예측 시, Training 기간에 23.52, Testing 기간에 23.45로 나타났다. 예측주기에 따라 모델트리와 회귀식에서 활용한 독립변수는 1일 예측 시, 모델트리는 N/Pratio, 클로로필-a, 회귀식은 클로로필-a로 다르게 나타났다. 반면, 3일, 5일, 7일 예측 시, 모델트리와 회귀식에 활용된 변수는 같게 나타났다. 클로로필-a, 수온, 일사량은 5일 예측 시 활용된 변수로, 3일 예측 시에는 기상항목인 강수량이, 7일 예측 시에는 수질항목인 T-N, N/Pratio가 추가되었다. 특히 1일 예측 시 일 때, 높은 예측정도와 활용된 변수의 수가 적게 나타나는 것을 확인하였으며, 예측기간이 길어질수록 예측의 정확성이 낮아지고, 활용된 변수의 수가 많아지는 것을 확인하였다. 향후 적정한 예측기간을 판단하고 예측가능성을 높이기 위해서는 지속적인 자료취득 및 개선이 필요하며, 이를 바탕으로 적절한 단기조류예측이 가능할 것으로 판단된다.

• Korean Journal of Food Science and Technology
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• v.51 no.5
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• pp.425-431
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• 2019

Selected leafy vegetables, widely used for Korean Namul dishes, were heat-treated in different ways and their folate retention was investigated. The Lactobacillus casei method was applied for folate estimation and validated to ensure reliability of analytical data. The folate content in Namul highly varied, from 29.7 to $293.4{\mu}g/100g$, depending on the heating methods and the types of vegetables. Most of the Namul variants showed increased folate content on heat treatment. Frying yielded higher folate retention than the other cooking methods (blanching, steaming, baking, and panfrying), and pig weed showed the highest folate retention (3.3 times, $293.4{\mu}g/100g$). L. casei assay for folate estimation showed 95.7% recovery and relative standard deviations less than 2% for both reproducibility and repeatability, indicating good accuracy and precision. Quality of the folate assay was assured by monitoring a quality control chart and a proficiency test (z-score= -0.1) during the entire of study.

• Journal of IKEEE
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• v.25 no.3
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• pp.485-492
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• 2021

In this paper, we propose the development of a defect inspection system for polygonal containers. Embedded board consists of main part, communication part, input/output part, etc. The main unit is a main arithmetic unit, and the operating system that drives the embedded board is ported to control input/output for external communication, sensors and control. The input/output unit converts the electrical signals of the sensors installed in the field into digital and transmits them to the main module and plays the role of controlling the external stepper motor. The communication unit performs a role of setting an image capturing camera trigger and driving setting of the control device. The input/output unit converts the electrical signals of the control switches and sensors into digital and transmits them to the main module. In the input circuit for receiving the pulse input related to the operation mode, etc., a photocoupler is designed for each input port in order to minimize the interference of external noise. In order to objectively evaluate the accuracy of the development of the proposed polygonal container defect inspection system, comparison with other machine vision inspection systems is required, but it is impossible because there is currently no machine vision inspection system for polygonal containers. Therefore, by measuring the operation timing with an oscilloscope, it was confirmed that waveforms such as Test Time, One Angle Pulse Value, One Pulse Time, Camera Trigger Pulse, and BLU brightness control were accurately output.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.215-224
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• 2019

The objective of study was to identify perceived medication administration Competence of senior nursing students. A total of 128 students were recruited. The instruments for this study were self-efficacy for drug dosage calculation, anxiety for drug dosage calculation and perceived medication administration competence. The data were collected from November 2018 to January 2019, analyzed by descriptive analysis, chi-square, t-test, Scheffe test, correlation coefficients, and multiple regression using the SPSS 25.0 program. The main predictors of perceived medication administration competence were identified as confidence in drug dosage calculation (${\beta}=.463$, p<.001), Attitude of participation at clinical practice (${\beta}=.168$, p=.040). These two factors explained about 29% of variance in perceived medication administration competence (F=26.93, p<.001). It can contribute to improve their ability to administrate medication in practice, with the accuracy of prescription, recalculation of prescribed drug dose, and observation of adverse reactions in clinical practice and simulation with collaborative approach.

• Journal of Korea Technology Innovation Society
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• v.21 no.3
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• pp.992-1020
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• 2018

The purpose of this study is to investigate the ways to enhance the creativity of R & D teams of government-funded research institutes through systematic empirical studies. For this purpose, a research model was established based on existing research on group creativity and verified through empirical studies. Specifically, This study first attempts to investigate the influence that team diversity, team cohesion, team autonomy and team efficacy have on team creativity. Second, it intends to verify the mediating effects of team efficacy between team characteristics and team creativity. An empirical study was conducted on 102 R & D teams of government-funded research institutes. In the team creativity measurement, the evaluation by the leaders and the self evaluation of the members were performed in parallel. This is to increase the accuracy of the evaluation and to compare the differences of the viewpoints of the two subjects. The result of the analysis demonstrated that team cohesion among the others had a positive influence on team creativity, and that team efficacy possessed certain positive qualities in mediating the relationship between team diversity, team autonomy, and team creativity. Based on these findings, this study discussed its academic implications as well as its practical limitations, and made suggestions on future research tasks that remain.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.249-256
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• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.