• Journal of the Korean Wood Science and Technology
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• v.36 no.3
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• pp.93-100
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• 2008

For investigation of adsoption properties of cadmium elimination by wood charcoal, $25m{\ell}$ aqueous cadmium solutions in various concentrations were treated with 0.2 g wood charcoal of Red Oak (Quercus mongolica) for 280 minutes. Almost 100% of cadmium elimination ratio was obtained in the solutions with initial concentration of 20 and 40 ppm in the treatment, whereas they were 75 and 50% in those of 80 and 160 ppm. In the effect of treatment time, the highest amount of cadmium ions was eliminated during the first ten minutes in each solution so that the elimination ratio of each case was over 70% of the maximum elimination value. From the analysis of adsorptive cadmium adsorption mechanism using the Langmuir adsorption isotherm, it was suggested that cadmium ion molecules were adsorbed at the active sites on the charcoal particle in form of one layer. The Gibbs free energy of the adsorption process was calculated in negative value for each solution. This means the adsorption processes are spontaneous which do not require the extra input energy.

• Clean Technology
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• v.24 no.4
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• pp.269-274
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• 2018

In this study, Life Cycle Assessment (LCA) of wet tissue manufacturing process was performed. The wet tissue manufacturing process consists of preparation of wetting agent (chemical liquid), impregnation of nonwoven fabric into wetting agent and primary and secondary packaging. Data and information were collected on the input and output of the actual process from a certain company and the database of the Korea Ministry of Environment and some foreign countries (when Korean unavailable) were employed to connect the upper and the lower process flow. Based on the above and the potential environmental impacts of the wet tissue manufacturing process were calculated. As a result of the characterization, Ozone Layer Depletion (OD) is 3.46.E-06 kg $CFC_{11}$, Acidification (AD) is 5.11.E-01 kg $SO_2$, Abiotic Resource Depletion (ARD) is $3.52.E+00\;1yr^{-1}$, Global Warming (GW) is 1.04.E+02 kg $CO_2$, Eutrophication (EUT) is 2.31.E-02 kg ${PO_4}^{3-}$, Photochemical Oxide Creation (POC) was 2.22.E-02 kg $C_2H_4$, Human Toxicity (HT) was 1.55.E+00 kg 1,4 DCB and Terrestrial Ecotoxicity (ET) was 5.82.E-04 kg 1,4 DCB. In order to reduce the environmental impact of the manufacturing process, it is necessary to improve the overall process as other general cases and change the raw materials including packaging materials with less environmental impact. Conclusively, the energy consumed in the manufacturing process has emerged as a major issue, and this needs to be reconsidered other options such as alternative energy. Therefore, it is recommended that a process system should be redesigned to improve energy efficiency and to change to an energy source with lower environmental impact. Due to the nature of LCA, the final results of this study can be varied to some extent depending on the type of LCI DB employed and may not represent of all wet tissue manufacturing processes in the current industry.

• Resources Recycling
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• v.28 no.4
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• pp.44-50
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• 2019

In the electric arc furnace process, the chemical energy such as the heat of oxidation reaction and the heat of carbon combustion etc. is consumed as 30% of the total input energy. In order to reduce $CO_2$ emission in EAF, it is necessary to decrease the use of electric power energy during scrap melting stage and increase the use of chemical energy. In general, when the carbon materials is individually charged into the molten steel, the carbon materials floated to the slag layer due to low density before it is dissolved in molten steel. When the concentration of carbon in the molten steel is high, the combustion energy of carbon by oxygen injection can lower the electric power energy and improve the chemical energy consumption. Therefore, an efficient charging methods of carbon material is required to increase the efficiency of carbon combustion heat. On the other hand, Al-dross, which is known as a by-product after Al smelting, includes over 25 mass% of metallic Al, and the oxidation heats of Al is lager than that of carbon. However, the recycling ratio fo Al-dross was very low and is almost landfilled. In order to effectively utilize the heats of oxidation of Al in Al-dross, it is necessary to study the application of Al-dross in the steel process. In this study, the dissolution efficiency of carbon and aluminum in molten steel was investigated by varying the reaction temperature and the mixing ratios of coke and Al-dross.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.3
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• pp.68-76
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• 2021

Storage racks have suffered huge losses due to earthquakes, but related research and regulations are relatively insufficient non-structural elements compared to the structural elements. In this study, we tried to experimentally analyze the behavioral characteristics of storage racks due to external force according to the fixing conditions of the column-foundations connection of storage racks. In general, the column-foundations connection of storage racks is installed according to the user's convenience without installation standards and regulations. For this reason, this study conducted a behavior analysis test on four full-scale storage racks with the condition of column-foundations connection of four typical storage racks. The behavior characteristics analysis test was performed by two-direction of the shake table with El-Centro seismic wave. To confirm the behavior characteristics according to the magnitude of the seismic load, 50% ~ 150% of the seismic waves were increased by 50% for each test. In addition, a resonance search test was conducted to confirm the natural frequency of each storage racks foundations fixing condition. Among the data obtained through the test, the displacement of the top layer and the permanent displacement after the test were compared for each condition to analyze the behavior characteristics of the column-foundations fixed conditions of the storage racks. As a result, the change of natural frequency was small in storage racks due to the change of the conditions of the foundations, and the behavior characteristics were changed due to the difference of the restoring force due to the change of the storage racks foundations condition rather than the influence of the natural frequency of the input load.

• Knowledge Management Research
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• v.22 no.4
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• pp.27-40
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• 2021

Click-Through Rate (CTR) prediction is a key function that determines the ranking of candidate items in the recommendation system and recommends high-ranking items to reduce customer information overload and achieve profit maximization through sales promotion. The fields of natural language processing and image classification are achieving remarkable growth through the use of deep neural networks. Recently, a transformer model based on an attention mechanism, differentiated from the mainstream models in the fields of natural language processing and image classification, has been proposed to achieve state-of-the-art in this field. In this study, we present a method for improving the performance of a transformer model for CTR prediction. In order to analyze the effect of discrete and categorical CTR data characteristics different from natural language and image data on performance, experiments on embedding regularization and transformer normalization are performed. According to the experimental results, it was confirmed that the prediction performance of the transformer was significantly improved when the L2 generalization was applied in the embedding process for CTR data input processing and when batch normalization was applied instead of layer normalization, which is the default regularization method, to the transformer model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.363-369
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• 2021

High-definition road maps are used as the basic infrastructure for autonomous vehicles, so the latest road information must be quickly reflected. However, the current drawing and structural editing process of high-definition road maps are manually performed. In addition, it takes the longest time to generate road lanes, which are the main construction targets. In this study, the point cloud of the road lane markings, in which color types(white, blue, and yellow) were predicted through the PointNet model pre-trained in previous studies, were used as input data. Based on the point cloud, this study proposed a methodology for automatically drawing and structural editing of the layer of road lane markings. To verify the usability of the 3D vector data constructed through the proposed methodology, the accuracy was analyzed according to the quality inspection criteria of high-definition road maps. In the positional accuracy test of the vector data, the RMSE (Root Mean Square Error) for horizontal and vertical errors were within 0.1m to verify suitability. In the structural editing accuracy test of the vector data, the structural editing accuracy of the road lane markings type and kind were 88.235%, respectively, and the usability was verified. Therefore, it was found that the methodology proposed in this study can efficiently construct vector data of road lanes for high-definition road maps.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.515-523
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• 2021

An integrated underground spatial map consists of underground facilities, underground structures, and ground information, and is periodically updated. In this paper, we design and implement a system for detecting and extracting only changed ground objects to shorten the map update speed. To find the changed objects, all the objects are compared, which are included in the newly input map and the reference map in the integrated map. Since the entire process of comparing objects and generating results is classified by function, the implemented system is composed of several modules such as object comparer, changed object detector, history data manager, changed object extractor, changed type classifier, and changed object saver. We use two metrics: detection rate and extraction rate, to evaluate the performance of the system. As a result of applying the system to boreholes, ground wells, soil layers, and rock floors in Pyeongtaek, 100% of inserted, deleted, and updated objects in each layer are detected. In addition, it provides the advantage of ensuring the up-to-dateness of the reference map by downloading it whenever maps are compared. In the future, additional research is needed to confirm the stability and effectiveness of the developed system using various data to apply it to the field.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.373-380
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• 2022

This paper presents a deep learning based group synchronization that supports networked immersive interactions between remote users. The goal of group synchronization is to enable all participants to synchronously interact with others for increasing user presence Most previous methods focus on NTP-based clock synchronization to enhance time accuracy. Moving average filters are used to control media playout time on the synchronization server. As an example, the exponentially weighted moving average(EWMA) would be able to track and estimate accurate playout time if the changes in input data are not significant. However it needs more time to be stable for any given change over time due to codec and system loads or fluctuations in network status. To tackle this problem, this work proposes the Deep Group Synchronization(DeepGroupSync), a group synchronization based on deep learning that models important features from the data. This model consists of two Gated Recurrent Unit(GRU) layers and one fully-connected layer, which predicts an optimal playout time by utilizing the sequential playout delays. The experiments are conducted with an existing method that uses the EWMA and the proposed method that uses the DeepGroupSync. The results show that the proposed method are more robust against unpredictable or rapid network condition changes than the existing method.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.429-440
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• 2021

With the recent development of deep convolutional neural network learning, deep learning techniques applied to single image super-resolution are showing good results. One of the existing deep learning-based super-resolution techniques is RDN(Residual Dense Network), in which the initial feature information is transmitted to the last layer using residual dense blocks, and subsequent layers are restored using input information of previous layers. However, if all hierarchical features are connected and learned and a large number of residual dense blocks are stacked, despite good performance, a large number of parameters and huge computational load are needed, so it takes a lot of time to learn a network and a slow processing speed, and it is not applicable to a mobile system. In this paper, we use the residual dense structure, which is a continuous memory structure that reuses previous information, and the residual dense channel attention block using the channel attention method that determines the importance according to the feature map of the image. We propose a method that can increase the depth to obtain a large receptive field and maintain a concise model at the same time. As a result of the experiment, the proposed network obtained PSNR as low as 0.205dB on average at 4× magnification compared to RDN, but about 1.8 times faster processing speed, about 10 times less number of parameters and about 1.74 times less computation.

• Journal of Marine Life Science
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• v.4 no.2
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• pp.53-62
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• 2019

Heterotrophic bacteria are a major member of the microbial loop in the marine ecosystem and play an important role in the biogeochemical cycle decomposing organic matter. Therefore study of bacterial variation is important to understand the material cycle and energy flow of marine ecosystems. We investigated the monthly variations of bacteria and environmental factors in the Youngsan River estuary, and the correlation between bacteria and phytoplankton biomass (chlorophyll-a) including size-structure. As a result, bacteria of the Youngsan River estuary were higher in the surface than in the bottom layer, and higher in the summer than in winter. And the closer to the dike, the abundance increased, and it increased to the peaks in August, September, and June 2019 at the station closest to the dike. The chlorophyll-a also increases at the stations and time when the bacterial abundance was high and they correlates positively displaying no difference between size fractions. The results indicate that organic matter derived from phytoplankton has an effect on bacterial variation but no size-dependent effects. In addition, the seasonal pattern of bacteria increasing in proportion to the water temperature suggests the effect of water temperature on the growth of bacteria. No association of bacterial abundance variation with nutrient supply due to freshwater input was observed. In this study, dissolved oxygen was depleted and hypoxia was observed for a short time when a strong stratification was not developed. This may be resulted from the supply of organic matter from phytoplankton and the consumption of oxygen due to bacterial decomposition.