• Journal of Korean Society of Environmental Engineers
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• v.35 no.6
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• pp.422-429
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• 2013

It is generally known that the increase of the Earth surface temperature due to the global warming together with the land desertification by rapid urban development has caused severe climate and weather change. In desert or desertification land, it is observed that there are always severe flooding phenomena, even if desert sand has the high porosity, which could be believed as the favorable condition of rain water infiltration into ground water. The high runoff feature causes possibly another heavy rain by quick evaporation with the depletion of underground water due to the lack of infiltration. The basic physics of desert flooding is reasonably assumed due to the thermal buoyancy of the higher temperature of the soil temperature than that of the rain drop. Considering the importance of this topic associated with water resource management and climate disaster prevention, no systematic investigation has, however, been reported in literature. In this study, therefore, a laboratory scale experiment together with the effort of numerical calculation have been performed to evaluate quantitatively the basic hypothesis of run-off mechanism caused by the increase of soil temperature. To this end, first, of all, a series of experiment has been made repeatedly with the change of soil temperature with well-sorted coarse sand having porosity of 35% and particle diameter, 2.0 mm. In specific, in case 1, the ground surface temperature was kept at $15^{\circ}C$, while in case 2 that was high enough at $70^{\circ}C$. The temperature of $70^{\circ}C$ was tested as this try since the informal measured surface temperature of black sand in California's Coachella Valley up to at 191 deg. $^{\circ}F$ ($88^{\circ}C$). Based on the experimental study, it is observed that the amount of runoff at $70^{\circ}C$ was higher more than 5% compared to that at $15^{\circ}C$. Further, the relative amount of infiltration by the decrease of the surface temperature from 70 to $15^{\circ}C$ is about more than 30%. The result of numerical calculation performed was well agreed with the experimental data, that is, the increase of runoff in calculation as 4.6%. Doing this successfully, a basic but important research could be made in the near future for the more complex and advanced topic for this topic.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.377-388
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• 2022

Laboratory-scale experiments were performed to identify the As removal mechanism of the residual slag generated after the mineral carbonation process. The residual slags were manufactured from the steelmaking slag (blast oxygen furnace slag: BOF) through direct and indirect carbonation process. RDBOF (residual BOF after the direct carbonation) and RIBOF (residual BOF after the indirect carbonation) showed different physicochemical-structural characteristics compared with raw BOF such as chemical-mineralogical properties, the pH level of leachate and forming micropores on the surface of the slag. In batch experiment, 0.1 g of residual slag was added to 10 mL of As-solution (initial concentration: 203.6 mg/L) titrated at various pH levels. The RDBOF showed 99.3% of As removal efficiency at initial pH 1, while it sharply decreased with the increase of initial pH. As the initial pH of solution decreased, the dissolution of carbonate minerals covering the surface was accelerated, increasing the exposed area of Fe-oxide and promoting the adsorption of As-oxyanions on the RDBOF surface. Whereas, the As removal efficiency of RIBOF increased with the increase of initial pH levels, and it reached up to 70% at initial pH 10. Considering the PZC (point of zero charge) of the RIBOF (pH 4.5), it was hardly expected that the electrical adsorption of As-oxyanion on surface of the RIBOF at initial pH of 4-10. Nevertheless it was observed that As-oxyanion was linked to the Fe-oxide on the RIBOF surface by the cation bridge effect of divalent cations such as Ca²⁺, Mn²⁺, and Fe²⁺. The surface of RIBOF became stronger negatively charged, the cation bridge effect was more strictly enforced, and more As can be fixed on the RIBOF surface. However, the Ca-products start to precipitate on the surface at pH 10-11 or higher and they even prevent the surface adsorption of As-oxyanion by Fe-oxide. The TCLP test was performed to evaluate the stability of As fixed on the surface of the residual slag after the batch experiment. Results supported that RDBOF and RIBOF firmly fixed As over the wide pH levels, by considering their As desorption rate of less than 2%. From the results of this study, it was proved that both residual slags can be used as an eco-friendly and low-cost As remover with high As removal efficiency and high stability and they also overcome the pH increase in solution, which is the disadvantage of existing steelmaking slag as an As remover.

• Economic and Environmental Geology
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• v.51 no.2
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• pp.87-97
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• 2018

The cesium (Cs) removal from the contaminated water system has been considered to be difficult because the cesium likes to exist as soluble phases such as ion and complexes than the solid in water system. Many researches have focused on developing the breakthrough adsorbent to increase the cesium removal efficiency in water. In this study, the laboratory scale experiments were performed to investigate the feasibility of the adsorption process using the bamboo charcoal for the Cs contaminated water system. The Cs removal efficiency of the bamboo charcoal were measured and the optimal adsorption conditions were determined by the adsorption batch experiments. Total 5 types of commercialized bamboo charcoals in Korea were used to identify their surface properties from SEM-EDS and XRD analyses and 3 types of bamboo charcoals having large specific surface areas were used for the adsorption batch experiment. The batch experiments to calculate the Cs removal efficiency were performed at conditions of various Cs concentration (0.01 - 10 mg/L), pH (3 - 11), temperature ($5-30^{\circ}C$), and adsorption time (10 - 120 min.). Experimental results were fitted to the Langmuir adsorption isotherm curve and their adsorption constants were determined to understand the adsorption properties of bamboo charcoal for Cs contaminated water system. From results of SEM-EDS analyses, the surfaces of bamboo charcoal particles were composed of typical fiber structures having various pores and dense lamella structures in supporting major adsorption spaces for Cs. From results of adsorption batch experiments, the Cs-133 removal efficiency of C type bamboo charcoal was the highest among those of 3 bamboo charcoal types and it was higher than 75 % (maximum of 82 %) even when the initial Cs concentration in water was lower than 1.0 mg/L, suggesting that the adsorption process using the bamboo charcoal has a great potential to remove Cs from the genuine Cs contaminated water, of which Cs concentration is low (< 1.0 mg/L) in general. The high Cs removal efficiency of bamboo charcoal was maintained in a relatively wide range of temperatures and pHs, supporting that the usage of the bamboo charcoal is feasible for various types of water. Experimental results were similar to the Langmuir adsorption model and the maximum amount of Cs adsorption (qm:mg/g) was 63.4 mg/g, which was higher than those of commercialized adsorbents used in previous studies. The surface coverage (${\theta}$) of bamboo charcoal was also maintained in low when the Cs concentration in water was < 1.0 mg/L, investigating that the Cs contaminated water can be remediated up with a small amount of bamboo charcoal.

• Korean Journal of Environmental Agriculture
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• v.37 no.1
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• pp.15-20
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• 2018

BACKGROUND: The global mean surface temperature change for the period of 2016~2035 relative to 1986~2005 is similar for the four representative concentration pathway (RCP)'s and will likely be in the range of $0.3^{\circ}C$ to $0.7^{\circ}C$. Climate change inducing higher temperature could affect not only crop growth and yield, but also dynamics of carbon in paddy field. METHODS AND RESULTS: This study was conducted to evaluate the effect of elevated temperature on the carbon dynamics in paddy soil and rice growth. In order to control the elevated temperatures, the experiments were set up as the small scale rectangular open top chambers (OTCs) of $1m(width){\times}1m(depth){\times}1m(height)$ (Type 1), $1 m(W){\times}1m(D){\times}1.2m(H)$ (Type 2), and $1m(W){\times}1m(D){\times}1.4m(H)$ (Type 3). The average temperatures of Type 1, Type 2, and Type 3 from July 15 to October 30 were higher than the ambient temperatures at $0.4^{\circ}C$, $0.5^{\circ}C$, and $0.9^{\circ}C$, respectively. For the experiment, Wagner's pots (1/2,000 area) were placed inside chambers. The pots were filled with loamy soil, and chemical fertilizer and organic compost were applied as recommended after soil test. The pots were flooded with agricultural water and rice (Shindongjin-byeo) was planted. It was observed that TOC (total organic carbon) of the water increased by the elevated temperatures and the trend continued until the late growth stage of the rice. Soil TOC contents were reduced by the elevated temperatures. C/N ratios of the rice plant decreased by the elevated temperature treatments. Thus, it was assumed that the elevated temperatures induced to decompose soil organic matter. Elevated temperatures significantly increased the culm length (P<0.01) and culm weight (P<0.05) of rice, but the number and weight of rice panicle did not showed significant differences. CONCLUSION: Based on the results, it was suggested that the elevated temperatures had an effect on changes of soil and water carbons under the possible future climate change environment.

• Korean Chemical Engineering Research
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• v.47 no.3
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• pp.349-354
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• 2009

In this study, a bubbling fluidized-bed reactor was used to study $CO_2$ capture from flue gas using a potassium-based dry sorbent. A dry sorbent, manufactured by the Korea Electric Power Research Institute, consists of 35% of $K_2CO_3$ for $CO_2$ absorption and 65% of supporters for mechanical strength. $H_2O$, a reactant of the carbonation reaction, was supplied in the reactor as a form of saturated water vapor at a given temperature. The experiment of the regeneration reaction was performed by raising up to a given temperature using $N_2$ as a fluidization gas. It was indicated that sorption capacity and regenerability of dry sorbents showed high-efficiency at $1.97\;mol\;H_2O/mol\;CO_2$ and $400^{\circ}C$, respectively. The regenerated sorbent samples were analyzed by TGA to confirm the extent of the reaction. When the regeneration temperature was $150^{\circ}C$, the regenerability of dry sorbents was about 60%, which was capable of applying those sorbents to a two-interconnected fluidized-bed reactor system with continuous solid circulation. The results obtained in this study can be used as basic data for designing and operating a large scale $CO_2$ capture process with two fluidized-bed reactors.

• Journal of the Korea Organic Resources Recycling Association
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• v.25 no.2
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• pp.41-48
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• 2017

A vertical multi-stage ammonia stripping reactor using E-PFR, which has been proved to be superior in anaerobic and aerobic treatment, was developed and a lab scale experiment was conducted. According to the change of stage number condition, the removal rate of the ammonia nitrogen in the reactor with 0-stage was about 52.5% after 8 hours (pH 10, temperature $35^{\circ}C$, and the air/liquid ratio $3min^{-1}$) However, in the reactor with 5-stage, the removal efficiency was about 62.6%. According to the change of pH condition, the removal rate of ammonia nitrogen was about 42.6% at pH 9 after 8 hours, and was about 74.4% at pH 11 (5-stage reactor, temperature $35^{\circ}C$, and the air/liquid ratio $3min^{-1}$). According to the change of temperature condition, the removal rate of the ammonia nitrogen was about 51% at $25^{\circ}C$ after 8 hours (5-stage reactor, pH 10, and the air/liquid ratio $3min^{-1}$), and was about 87.2% at $45^{\circ}C$. According to the change of air injection volume condition, the removal rate of the ammonia nitrogen was about 45.8% at $2min^{-1}$ after 8 hours (5-stage reactor, pH 10, and at $35^{\circ}C$). and was about 75% at $4min^{-1}$. Based on these results, we will follow up the applicability of the actual plant in the future through continuous operation evaluation.

• Journal of Animal Environmental Science
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• v.16 no.1
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• pp.21-28
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• 2010

The odor problem in the livestock is increasing by 7% annually. Most importantly, the livestock odor problem in swinery accounts for the maximum ratio (54%). In this study, we reviewed the possibility of deodorizing swinery using an odor reduction device that can be used with the water washing system. First, the study confirmed that the solubility of odor gas, which was hydrogen sulfide, was very low regardless of the contact time with solvent, but the solubility of methyl mercaptan was found to increase along with the increase in time. The solubility of other odor gases, such as dimethyl sulfide, dimethyl disulfide and ammonia, was considerably high. Consequently, it is considered that if the odor reduction device for the water washing system deodorization is used in a swinery, the time during which the exhaust gas is in contact with usable water must be extended, or solvent quantity must be expanded. However, it is predicted that although hydrogen sulfide is easily generated in the anaerobic condition, it is difficult to expect high odor reduction efficiency because this gas has low solubility in water, especially in case it is used in the deodorization of the water washing system. The result of the solubility experiment using the bench-scale device practically manufactured represented the higher odor reduction ratio than expected. This result was possible because the removal efficiency of dust particles could be reached up to 93%. Therefore, it is judged that also the odor gas absorbed on dust particles could be removed by removal of dust. Consequently, it is expected that the higher order reduction ratio will be possible by structural improvement for increasing contact with water and odor gas.

• Economic and Environmental Geology
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• v.55 no.5
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• pp.511-519
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• 2022

In order to develop an air-stripping based remediation process to remove the TOC (Total Organic Carbon) in groundwater around the underground LPG storage cavern, the laboratory scale experiments at various conditions (change of air injection volume and temperature, the application of ultrasonic treatment, etc.) for two types of groundwater (initial TOC concentration of 608 mg/L and 153 mg/L, respectively). From results of experiment, as the air injection rate for stripping into groundwater increased from 2 L/min to 11 L/min and as the air-stripping time increased from 1 hour to 24 hour, the TOC removal efficiency of air-stripping increased. However, the TOC concentration of treated groundwater was higher than the discharge tolerance limit (100 mg/L) even after 24 hour stripping at the maximum air injection rate of 11 L/min. The main compounds of the TOC in groundwater were identified as methanol and propane and the long stripping time (more than 24 hour) was needed to separate the methanol from groundwater because of the affinity between water and methanol. At 20℃ and 4 L/min of air injection, the TOC removal efficiency increased to 59.1% after 24 hour air-stripping. When the temperature of groundwater increased to 30℃ and 40℃, the TOC removal efficiency increased up to 80.0% and 82.8%, suggesting that more than 24 hour air-stripping at 40℃ is needed to lower the TOC concentration to below 100 mg/L and the additional TOC removal process as well as the air-stripping is necessary. When the temperature increased to 60℃ and the ultrasonic treatment was conjugated with the air-stripping, the TOC removal efficiency increased to 87.8% within 5 hour stripping and the final TOC concentration (72.4 mg/L) was satisfied with the TOC discharge tolerance limit. The TOC removal efficiency for groundwater having low TOC concentration (153 mg/L) also showed similar removal efficiency of 89.7% (the final TOC concentration: 18.9 mg/L). Results in this study supported that the air-stripping conjugated with the ultrasonic treatment could remove successfully the TOC in groundwater around the underground LPG strorage cavern.