• Geosystem Engineering
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• 제21권5호
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• pp.262-272
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• 2018

The U-statistic method is one of the most important structural methods to separate the anomaly from background. It considers the location of samples and carries out the statistical analysis of the data without judging from a geochemical point of view and tries to separate subpopulations and determine anomalous areas. In the present study, 3D U-statistic method has been applied for the first time through the three-dimensional (3D) modeling of an ore deposit. In order to achieve this purpose, 3D U-statistic is applied on the data (Fe grade) resulted from the drilling network in Baghak mine, central part of the Sangan iron mines (in Khorassan Razavi Province, Iran). Afterward, results from applying 3D U-statistic method are used for 3D modeling of the iron mineralization. Results show that the anomalous values are well separated from background so that the determined samples as anomalous are not dispersed and according to their positioning, denser areas of anomalous samples could be considered as anomaly areas. And also, final results (3D model of iron mineralization) show that output model using this method is compatible with designed model for mining operation. Moreover, seen that U-statistic method in addition for separating anomaly from background, could be very efficient for the 3D modeling of different ore type.

• 식품보건융합연구
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• 제8권5호
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• pp.11-20
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• 2022

Honey was diluted with different percentages of water and was analysed rheologically at room temperature of 27℃. The rheological profiles of pure and impure honey samples were measured at low shear rates (0.01-4.16s^-1). This work developed a structural kinetic model, which correlated well with the rheological data. The new model was used to categorise honey samples using their average molecular weights as one of the distinctive properties. Also, the kinetics order in the new model predicts the number of active components in the "honey" undergoing deformation. Honey produced third order kinetics to depict the monomers, oligomers and water content in honey. Pure honey exhibits peculiar non-Newtonian rheological behaviour. The behaviour of water is Newtonian. Dilution of honey with different percentages of water turns the resulting fluid Newtonian from 10% dilution with water. This study analysed the antibacterial activities of honey and serially adulterated samples against Staphylococcus aureus and Pseudomonas aeruginosa. The antibacterial analyses of honey were conducted using Kirby Bauer's well diffusion method. The results indicated that pure honey exhibited a zone of inhibition against both organisms. Also, the diameter of the zone of inhibition decreased with increasing dilution of honey, suggesting a correlation with the rheological method.

• Journal of Information Processing Systems
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• 제17권6호
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• pp.1057-1070
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• 2021

Case-related news filtering is crucial in legal text mining and divides news into case-related and case-unrelated categories. Because case-related news originates from various fields and has different writing styles, it is difficult to establish complete filtering rules or keywords for data collection. In addition, the labeled corpus for case-related news is sparse; therefore, to train a high-performance classification model, it is necessary to annotate the corpus. To address this challenge, we propose topic-enhanced positive-unlabeled learning, which selects positive and negative samples guided by topics. Specifically, a topic model based on a variational autoencoder (VAE) is trained to extract topics from unlabeled samples. By using these topics in the iterative process of positive-unlabeled (PU) learning, the accuracy of identifying case-related news can be improved. From the experimental results, it can be observed that the F1 value of our method on the test set is 1.8% higher than that of the PU learning baseline model. In addition, our method is more robust with low initial samples and high iterations, and compared with advanced PU learning baselines such as nnPU and I-PU, we obtain a 1.1% higher F1 value, which indicates that our method can effectively identify case-related news.

• 한국정보시스템학회지:정보시스템연구
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• 제27권3호
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• pp.63-80
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• 2018

Purpose The purpose of this study is to build a machine learning-based customer classification model to promote customer expansion effect of the free sample promotion. Specifically, the proposed model classifies potential target customers who are expected to purchase the products included in the free sample promotion after receiving the free samples. Design/methodology/approach This study proposes to build a customer classification model for determining customers suitable for providing free samples by using various machine learning techniques such as logistic regression, multiple discriminant analysis, case-based reasoning, decision tree, artificial neural network, and support vector machine. To validate the usefulness of the proposed model, we apply it to a real-world free sample-based target marketing case of a Korean major cosmetic retail company. Findings Experimental results show that a machine learning-based customer classification model presents satisfactory accuracy ranging from 70% to 75%. In particular, support vector machine is found to be the most effective machine learning technique for free sample-based target marketing model. Our study sheds a light on customer relationship management strategies using free sample promotions.

• 급식외식위생학회지
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• 제2권2호
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• pp.84-90
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• 2021

This study was performed to assess the microbiological quality and safety of microgreen sampled from harvesting farms and food processing plant in Korea. The samples were analyzed for total viable counts, coliforms, Enterobacteriaceae, Escherichia coli, Salmonella spp., Listeria monocytogenes, Vibrio parahaemolyticus, Bacillus cereus, and Staphylococcus aureus. Total viable counts were highly contaminated in samples collected from farms (7.7~8.2 log CFU/g) and the final products (5.8~7.8 log CFU/g), respectively. B. cereus was detected less than 100 CFU/g, which was satisfied with Korean standards (<1,000 CFU/g) of fresh-cut produce. A predictive model was developed for the changes of total viable counts in microgreens during storage at 5~35℃. The predictive models were developed using the Baranyi model for the primary model and the square root model for the secondary model. The results obtained in this study can be useful to develop the safety management options along the food chain, including fresh-cut produce storage and distribution.

• Geomechanics and Engineering
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• 제33권1호
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• pp.1-9
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• 2023

The unconfined compression strength (UCS) of soils is commonly used either before or during the construction of geo-structures. In the pre-design stage, UCS as a mechanical property is obtained through a laboratory test that requires cumbersome procedures and high costs from in-situ sampling and sample preparation. As an alternative way, the empirical model established from limited testing cases is used to economically estimate the UCS. However, many parameters affecting the 1D soil compression response hinder employing the traditional statistical analysis. In this study, gene expression programming (GEP) is adopted to develop a prediction model of UCS with common affecting soil properties. A total of 79 undisturbed soil samples are collected, of which 54 samples are utilized for the generation of a predictive model and 25 samples are used to validate the proposed model. Experimental studies are conducted to measure the unconfined compression strength and basic soil index properties. A performance assessment of the prediction model is carried out using statistical checks including the correlation coefficient (R), the root mean square error (RMSE), the mean absolute error (MAE), the relatively squared error (RSE), and external criteria checks. The prediction model has achieved excellent accuracy with values of R, RMSE, MAE, and RSE of 0.98, 10.01, 7.94, and 0.03, respectively for the training data and 0.92, 19.82, 14.56, and 0.15, respectively for the testing data. From the sensitivity analysis and parametric study, the liquid limit and fine content are found to be the most sensitive parameters whereas the sand content is the least critical parameter.

• 전자공학회논문지S
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• 제34S권1호
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• pp.94-104
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• 1997

Most color imaging devices often exhibit color distortions due to the differences in realizable color gamuts and nonlinear characteristics of their components. In order to minimize color differences, it is desirable to apply color correction techniques. Th efirst step of color correction is to select the subset of the color coordinates representing the input color space. Th eselected subset serves as so called color samples to model the color distortion of a given color imaging device. The effectiveness of color correction is determined by the color sampels utilized in the modeling as well as the applied color correction technique. This paper presents a new selection method for color samples based on gentic algorithm. In the proposed method, structure of strings are designed so that the selected color samples fully represent the characteristics of color imaging device and consist of distinct color coordinates. To evaluate the performance of the selected color samples, they ar etuilized for three different color correction experiments. The experimentsal results are comapred with the crresponding results obtianed with the equally spaced color samples.

• 한국대기환경학회지
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• 제16권6호
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• pp.565-572
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• 2000

To quantitatively estimate mass contribution of long-range transported yellow sand, their sources should be separated independently from various local soil sources having similar elemental compositions. While it is difficult to estimate total mass loadings of pure yellow sand by traditional bulk analysis, it can be clearly solved by an particle-by-particle analysis. To perform this study, two yellow sand samples and three local soil samples were collected by a mini-volume sampler. These samples were three analyzed using a scanning electron microscope(SEM) equipped with an energy dispersive x-ray analyser (EDX) was used to obtain basic chemical information of individual yellow san particles. A total of 19 elements in a single particle were measured to develop a source profile with newly created homogeneous particle classes (HPCs) as chemical variables. The present study showed that the yellow sand samples as well as three local soil samples were characterized with reasonably well created HPCs. Finally the mass fraction of each HPC in each sample was calculated and then compared each other.

• Bulletin of the Korean Chemical Society
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• 제12권1호
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• pp.52-57
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• 1991

To find optimum conditions necessary in converting physical properties of any resin into those of others, eleven kinds of HIPS (High-Impact Polystyrene) resins were prepared. First physical properties of eleven samples divided into three groups are analyzed by a torque rheometer (named Plasti-Corder, Model No.: PLD 651) and GPC (Gel Permeation Chromatography), and then optimum conditions on conversion among samples are obtained by calculation from computer simulation so that any sample subjected to each group can show physical properties of other samples in its group. Even though the kind of plasticizer of any sample is different with others in its group, once optimum conditions on conversion among samples are met, it is found that physical properties of any sample are identical or similar to those of others in each group.

• Advances in materials Research
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• 제8권1호
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• pp.1-10
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• 2019

Roll bonding (RB) process of bi-metal laminates as a new noble method of bonding has been widely used in the production of bimetal laminates. In the present study, asymmetric roll bonding process as a new noble method has been presented to produce Al/Cu bimetallic laminates with the thickness reduction ratios 10%, 20% and 30% together with mismatch rolling diameter ($\frac{R_2}{R_1}$) ratio 1:1, 1:1.1 and 1:1.2. ABAQUS as a finite element simulation software was used to model the deformation of samples. The main attention in this study focuses on the bonding properties of Al/Cu samples. The effect of the $\frac{R_2}{R_1}$ ratios was investigated to improve the bond strength. During the simulation, for samples produced with $\frac{R_2}{R_1}=1:1.2$, the vertical plastic strain of samples was reach the maximum value with a high quality bond. Moreover, the peeling surface of samples after the peeling test was investigated by the scanning electron microscopy (SEM).