• Journal of Environmental Health Sciences
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• v.36 no.5
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• pp.383-390
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• 2010

Exposure to fugitive dust can contribute to several respiratory health problems, and proper sampling of fugitive dust is necessary to assess exposure. However, field sampling of soil dust encounters problems from spatial and temporal differences in soil properties, field operations, and meteorological conditions. To minimize these problems, we designed a dust generator that simulates dust generation from soil. The dust generator consisted of a rotating chamber where soil samples were loaded and tumbled, and a settling chamber, where airborne soil dust samples were collected. As standard operating conditions, we decided on 2 g soil mass, 10 min sampling time, and 20 rpm rotating speed, with a flow rate of 30 l/min, based on three common soil textures of loam, sandy loam and silt loam. To evaluate optimal operating conditions, we used mixtures of Joomoonjin silica sand and clay. Although the average $PM_{10}$ concentration of Joomoonjin silica sand was low, dust concentrations were increased by an increased content of clay. The dust concentrations were consistent across repeated experiments, and showed similar concentration profiles during the sampling time with mixtures of clay and sand (coefficient of variation was $13.6{\pm}w;7.1%$). The results demonstrated that these standard operating conditions were suitable for the dust generator, which can be used to investigate variations in soil properties that affect dust production and potential potency of fugitive dust exposure.

• Journal of Soil and Groundwater Environment
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• v.19 no.3
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• pp.104-110
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• 2014

In order to study gross alpha analysis method using LSC, the efficiency tests with uranium standard materials were performed and then compared with the GPC method (US EPA 900.0 method) using 15 groundwater samples. For 15 groundwater samples, the average efficiencies of the GPC and LSC method were 7~11% and 90%, respectively. The average precisions of the GPC and LSC method were 16.16% and 6.00%, respectively. Also, The average standard deviations for 15 samples were 7.38 pCi/L and 2.95 pCi/L, respectively. The determination coefficient of the tested results by two methods was 0.9948. As a result, the LSC method tested in this study was applicable for the screening of the gross alpha and showed the advantages in the gross alpha measurement due to the simple measurement procedures.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.27-39
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• 2024

Soil texture is determined by the proportions of sand, silt, and clay within the soil, which influence characteristics such as porosity, water retention capacity, electrical conductivity (EC), and pH. Traditional classification of soil texture requires significant sample preparation including oven drying to remove organic matter and moisture, a process that is both time-consuming and costly. This study aims to explore an alternative method by developing an AI model capable of predicting soil texture from images of pre-sorted soil samples using computer vision and deep learning technologies. Soil samples collected from agricultural fields were pre-processed using sieve analysis and the images of each sample were acquired in a controlled studio environment using a smartphone camera. Color distribution ratios based on RGB values of the images were analyzed using the OpenCV library in Python. A convolutional neural network (CNN) model, built on PyTorch, was enhanced using Digital Image Processing (DIP) techniques and then trained across nine distinct conditions to evaluate its robustness and accuracy. The model has achieved an accuracy of over 80% in classifying the images of pre-sorted soil samples, as validated by the components of the confusion matrix and measurements of the F1 score, demonstrating its potential to replace traditional experimental methods for soil texture classification. By utilizing an easily accessible tool, significant time and cost savings can be expected compared to traditional methods.

• Economic and Environmental Geology
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• v.55 no.6
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• pp.717-726
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• 2022

This study was conducted to assess the geochemical contamination degree of As, Cd, Cu, Pb, Sb, and Zn in the soil and water samples from an abandoned gold mine. Enrichment Factor (EF), Geoaccumulation Index (Igeo), and Pollution Load Index (PLI) were carried out to assess the geochemical contamination degree of the soil samples. Variations of sulfate and heavy metals concentration in water samples were determined to identify the geochemical distribution with respect to the distance from the mine tailing dam. Geochemical pollution indices indicated significant contaminated with As, Cd, Pb, and Zn in the soil samples that areas close to the mine tailing dam, while, Sb showed similar indices in all soil samples. These results indicated that the As, Cd, Pb, and Zn dispersion has occurred via anthropogenic sources, such as mining activities. In terms of water samples, anomalies in the concentrations of As, Cd, Zn, and SO₄^2- was determined at specific area, in addition, the concentrations of the elements gradually decreased with distance. This result implies the heavy metals distribution in water has carried out by the weathering of sulfide minerals in the mine tailing and soil. The study area has been conducted the remediation of contaminated soil in the past, however, the geochemical dispersion of heavy metals was supposed to be occurred from the potential contamination source. Therefore, continuous monitoring of the soil and water is necessary after the completion of remediation.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.2
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• pp.115-124
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• 2016

The objectives of this study were to evaluate the soil fertility about plastic film house, upland, and orchard in Gyeongbuk Province, Korea. The surface chemical properties of soil samples were investigated every 4 year from 2000 year at upland, 2001 year at orchard, and 2002 year at plastic film house. During 12 year's monitoring, mean soil pH was increased by 0.7 and 0.8 pH unit from pH 5.7 in upland and orchard, respectively, 0.5 pH unit from pH 6.5 in plastic film house. About 50% of all the field samples occupied within the recommended pH range (pH 6-7). Although soil organic matter (SOM) was gradually increased by about $10g\;kg^{-1}$ for 12 years, 40% of orchard, 49% of plastic film house, and 77% of upland soil samples were still below the 3% SOM. The mean concentration of available phosphate for 12 years in upland, orchard, and plastic film house were 530, 600, and $760mg\;kg^{-1}$, respectively. The relative frequencies exceeding the recommended available phosphate range ($300-550mg\;kg^{-1}$) were 43%, 53%, and 66% at upland, orchard, and plastic film house soils, respectively. $NH_4OAc$ exchangeable $K^+$ of upland, orchard, and plastic film house in the last soil test were 0.8, 0.9, and $1.6cmol_c\;kg^{-1}$, respectively. The relative frequencies above the recommended K level were 56% and 70% of orchard and plastic film house soil samples, respectively. The levels of crop nutrients except exchangeable Ca and Mg in upland soil were tended to increase gradually in the three fields. Exchangeable Mg, EC, available phosphate, organic matter and soil pH could be used as principle components to differentiate the chemical properties of three land fields. This analysis revealed that the soil fertility was affected by cropping method and field management, although additional research is needed to assess the importance of management on soil chemical properties and many fields indicate an opportunity for improvement in fertilizer management.

• Geomechanics and Engineering
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• v.28 no.5
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• pp.505-520
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• 2022

In recent years, geotextile-encased gravel columns (usually called stone columns) have become a popular method to increasing soil shear strength, decreasing the settlement, acceleration of the rate of consolidation, reducing the liquefaction potential and increasing the bearing capacity of foundations. The behavior of improved loose base-soil with gravel columns under shear loading and the shear stress-horizontal displacement curves got from large scale direct shear test are of great importance in understanding the performance of this method. In the present study, by performing 36 large-scale direct shear tests on sandy base-soil with different fine-content of zero to 30% in both not improved and improved with gravel columns, the effect of the presence of gravel columns in the loose soils were investigated. The results were used to predict the shear stress-horizontal displacement curve of these samples using support vector machines (SVM). Variables such as the non-plastic fine content of base-soil (FC), the area replacement ratio of the gravel column (Arr), the geotextile encasement and the normal stress on the sample were effective factors in the shear stress-horizontal displacement curve of the samples. The training and testing data of the model showed higher power of SVM compared to multilayer perceptron (MLP) neural network in predicting shear stress-horizontal displacement curve. After ensuring the accuracy of the model evaluation, by introducing different samples to the model, the effect of different variables on the maximum shear stress of the samples was investigated. The results showed that by adding a gravel column and increasing the Arr, the friction angle (ϕ) and cohesion (c) of the samples increase. This increase is less in base-soil with more FC, and in a proportion of the same Arr, with increasing FC, internal friction angle and cohesion decreases.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.5
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• pp.319-323
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• 2014

This study investigates the prediction of soil chemical properties (organic matter (OM), pH, Ca, Mg, K, Na, total acidity, cation exchange capacity (CEC)) on 688 Korean soil samples using the visible-near infrared reflectance (VIS-NIR) spectroscopy. Reflectance from the visible to near-infrared spectrum (350 to 2500 nm) was acquired using the ASD Field Spec Pro. A total of 688 soil samples from 168 soil profiles were collected from 2009 to 2011. The spectra were resampled to 10 nm spacing and converted to the 1st derivative of absorbance (log (1/R)), which was used for predicting soil chemical properties. Principal components analysis (PCA), partial least squares regression (PLSR) and regression rules model (Cubist) were applied to predict soil chemical properties. The regression rules model (Cubist) showed the best results among these, with lower error on the calibration data. For quantitatively determining OM, total acidity, CEC, a VIS-NIR spectroscopy could be used as a routine method if the estimation quality is more improved.

• Journal of Korean Society of Forest Science
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• v.90 no.6
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• pp.788-791
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• 2001

An improved double-cylinder hammer-driven sampling device was designed to extract undisturbed soil cores. The improvements consist of 1) separation of hammer from the driving head, 2) a split inside cylinder, and 3) a plastic sample holder. Pushing the sampler deep into the soil before hammering would result in less compression of the sample. Core samples should be taken in soils of medium moisture content. The improved soil core sampler provides sufficiently accurate volumetric soil samples with original soil layers and soil cores of 40cm in length and 5cm in diameter.

• Journal of Soil and Groundwater Environment
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• v.17 no.1
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• pp.47-54
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• 2012

When quicklime is added into soil for various purposes, abrupt changes in soil chemistry may affect essential ecological functions played by indigenous bacterial communities in soil. The magnitude of influence was estimated by observing changes in abundance and diversity of soil bacteria after quicklime treatment. When several soil samples were treated up to 20% (w/w) quicklime, plate count of viable cells ranged $10^2{\sim}10^3$ CFU $g^{-1}$, showing a reduction of more than $10^4$ times from viable counts of the untreated sample. Diversity of the bacterial isolates that survived after quicklime treatment was analyzed by conducting $GTG_5$ rep-PCR fingerprinting. There were only two types of fingerprints common to both 5% and 20% quicklime samples, implying that bacteria surviving at different strength of quicklime treatment differed depending on their tolerance to quicklime-treated condition. Isolates surviving the quicklime treatments were further characterized by Gram staining and endospore staining. All isolates were found to be Gram positive bacteria, and 85.4% of them displayed endospores state. In conclusion, most bacteria surviving quicklime treatment appear to be endospores. This finding suggests that most of ecological functions of bacteria in soil are lost with quicklime treatment.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.3
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• pp.393-398
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• 2012

We investigated the changes in chemical properties of paddy field soils at 300 different sampling sites containing 4 topography in Jeonbuk province, Korea. The soil samples were collected 43.0% from local valley and fans, 39.3% from fluvio-marine deposits, 15.0% from alluvial plains, and 2.7% from diluvium sites. The optimal values of soil properties in the total soil samples were as follows: 65.3% of total samples in soil pH value, 48.3% of total samples in cation exchange capacity (CEC) value, and 22.3% of total samples in available phosphorus content, whereas the deficient values of soil properties were 63.3% of total samples in soil organic matter (SOM) content, 75.7% of total samples in available silicate content, and 61.3%, 51.0%, and 59.3% of total samples in exchangeable $K^+$, $Ca^{2+}$, and $Mg^{2+}$ concentrations, respectively. There were different soil types in the paddy fields: that is, 34.4% immature paddy and 33.6% sandy paddy in the local valley and fans, 57.8% sandy paddy in the alluvial plains, 47.4% normal paddy in the fluvio-marine deposits, and 75.7% immature paddy in the diluvium. Soil textures were also different: 53.5% loam in the local valley and fans, 37.8% sandy loam in the alluvial plains, and 55.1% silty loam in the fluvio-marine deposits. Soil pH and SOM contents were not different among the different topographical sampling sites. However, the mean value of available phosphorus content, 224 mg $kg^{-1}$, was exceeded optimal values in the diluvium. The contents of exchangeable cations were optimal in all the sites, except exchangeable $Ca^{2+}$ contents in the local valley and fans. The contents of available silicate ranged between 112 and 127 mg $kg^{-1}$ in all the sites, which were lower than optimal value. In addition, soil pH values were proportionally correlated to the order of available silicate, exchangeable $Ca^{2+}$, $Mg^{2+}$, $Na^+$, CEC, and exchangeable $K^+$. The contents of SOM were proportionally correlated to the order of CEC, available $P_2O_5$, exchangeable $Ca^{2+}$, and available silicate. The contents of heavy metals, Cd, Cr, Cu, Ni, Pb, and Zn, were only 10% of the threshold levels of the metals, and As content was about 20 to 30% of the threshold level.