• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.303-310
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• 2009

Natural zeolite is widely used as sorbents and bio-media materials because it is cheap as well as it has efficient porous structures and large cation exchange. In this study, the effect of metal cations $(Na^+,\;Ca^{2+},\;Mg^{2+},\;Al^{3+})$ adsorbed to natural zeolite on the microorganism attachment was investigated. Metal-modified zeolites (MMZ) were prepared with 0.01 M, 0.02 M and 0.1 M NaCl, $CaCl_2$, $MgCl_2$ and $AlCl_3$ solutions respectively, which concentrations were equivalent to 10%, 20% and 100% of cation exchange capacity (CEC) of natural zeolite. Pseudomonas putida was used as microorganism which was cultivated in Beef Extract Medium at $26^{\circ}C$. The microorganism attachment to MMZ was increased more than natural zeolite. The amount of bacterial adhesion to MMZ and natural zeolite were $Mg^{2+}>natural>Na^+>Al^{3+}>Ca^{2+}$ under 10% of CEC, $Mg^{2+}>Ca^{2+}>Al^{3+}>natural>Na^+$ under 20% of CEC and $Ca^{2+}>Mg^{2+}>natural>Al^{3+}>Na^+$ under 100% of CEC. Especially, Mg-modified zeolite (Mg-MZ) showed the highest amount of bacterial adhesion, which increased the microorganism attachment 60% higher than natural zeolite under 10% of CEC. However, the amount of bacterial adhesion was decreased as the concentration of metal cations modified to zeolite were increased, showing that the increased amounts were 60% under 10% of CEC, 50% under 20% of CEC and 10% under 100% of CEC in Mg-MZ. Additionally, the effect of $Mg^{2+}$ in solution on the bacterial adhesion was investigated in order to compare it with the effect of $Mg^{2+}$ adsorbed to zeolite. The maximum quantity of bacterial adhesion to Mg-MZ was not different from the amount of microorganism attachment to the natural zeolite when $Mg^{2+}$ solution was added.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.4
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• pp.305-330
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• 2023

Unlike NATM tunnels, Shield TBM tunnels have split linings. Therefore, the stress distribution of the lining is different even if the lining is under the same load. Representative methods for analyzing the stress generated in lining in Shield TBM tunnels include Non-joint Mode that does not consider connections and a 2-ring beam-spring model that considers ring-to-ring joints and segment connections. This study is an analysis method by Break-joint Mode. However, we do not consider the structural role of segment lining connections. The effectiveness of the modeling is verified by analyzing behavioral characteristics against vibration loads by modeling with segment connection interfaces to which vertical stiffness and shear stiffness, which are friction components, are applied. Unlike the Non-joint mode, where the greatest stress occurs on the crown for static loads such as earth pressure, the stress distribution caused by contact between segment lining and friction stiffness produced the smallest stress in the crown key segment where segment connections were concentrated. The stress distribution was clearly distinguished based on segment connections. The results of static analysis by earth pressure, etc., produced up to seven times the stress generated in Non-joint mode compared to the stress generated by Break-joint Mode. This result is consistent with the stress distribution pattern of the 2-ring beam-spring model. However, as for the stress value for the train vibration load, the stress of Break-joint Mode was greater than that of Non-joint mode. This is a different result from the static mechanics concept that a segment ring consisting of a combination of short members is integrated in the circumferential direction, resulting in a smaller stress than Non-joint mode with a relatively longer member length.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.377-388
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• 2023

Carbon management is emerging as an important factor for global warming control, and land use change is considered one of the causes. To quantify the changes in carbon stocks due to development, this study attempted to calculate carbon storage by borrowing the formula of the InVEST Carbon Storage and Sequestration Model (InVEST Model). Before analyzing carbon stocks, a carbon pool was compiled based on previous studies in Korea. Then, we estimated the change in carbon stocks according to the development of Osong National Industrial Park (ONIP) and the application of alternatives. The analysis shows that 16,789.5 MgC will be emitted under Alternative 1 and 16,305.3 MgC under Alternative 2. These emissions account for 44.4% and 43.1% of the pre-project carbon stock, respectively, and shows that choosing Alternative 2 is advantageous for reducing carbon emissions. The difference is likely due to the difference in grassland area between Alternatives 1 and 2. Even if Alternative 2 is selected, efforts are needed to increase the carbon storage effect by managing the appropriate level of green cover in the grassland, creating multi-layered vegetation, and installing low-energy facilities. In addition, it is suggested to conserve wetlands that can be lost during the stream improvement process or to create artificial wetlands to increase carbon storage. The assessment of carbon storage using carbon pools by land cover can improve the objectivity of comparison and evaluation analysis results for land use plans in Environmental Impact Assessment and Strategic Environmental Impact Assessment. In addition, the carbon pool generated in this study is expected to be used as a basis for improving the accuracy of such analyses.

• The Journal of Engineering Geology
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• v.34 no.2
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• pp.279-294
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• 2024

Large-scale civil engineering structures such as dams require a systematic approach to jointed rock-mass grouting to prevent water leakage into the foundations and to ensure safe operation. In South Korea, rock grouting design often relies on the experience of field engineers that was gained in similar projects, highlighting the need for a more systematic and reliable approach. Rock-mass grouting is affected mainly by hydrogeology and the presence of discontinuities, involving factors such as the rock quality designation (RQD), joint spacing (Js), Lugeon value (Lu), and secondary permeability index (SPI). This study, based on data from field investigations of 14 domestic sites, analyzed the correlation between hydrogeological factors (Lu and SPI), discontinuity characteristics (RQD and Js), and grout take, and systematically established a design method for rock grouting. Analysis of correlation between the variables RQD, Js, Lu, and SPI yielded Pearson correlation (r) values as follows: Lu-SPI, 0.92; RQD-Lu, -0.75; RQD-Js, 0.69; RQD-SPI, -0.65; Js-Lu, -0.47; and SPI-Js, -0.41. The grout take increases with Lu and SPI values, but there is no significant correlation between RQD and Js. The proposed approach for grouting design based on SPI values was verified through analysis and comparison with actual curtain-grouting construction, and is expected to be useful in practical applications and future studies.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.437-449
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• 2024

Rainfall-runoff prediction studies using deep learning while considering catchment attributes have been gaining attention. In this study, we selected two models: the Transformer model, which is suitable for large-scale data training through the self-attention mechanism, and the LSTM-based multi-state-vector sequence-to-sequence (LSTM-MSV-S2S) model with an encoder-decoder structure. These models were constructed to incorporate catchment attributes and predict the inflow of 10 multi-purpose dam watersheds in South Korea. The experimental design consisted of three training methods: Single-basin Training (ST), Pretraining (PT), and Pretraining-Finetuning (PT-FT). The input data for the models included 10 selected watershed attributes along with meteorological data. The inflow prediction performance was compared based on the training methods. The results showed that the Transformer model outperformed the LSTM-MSV-S2S model when using the PT and PT-FT methods, with the PT-FT method yielding the highest performance. The LSTM-MSV-S2S model showed better performance than the Transformer when using the ST method; however, it showed lower performance when using the PT and PT-FT methods. Additionally, the embedding layer activation vectors and raw catchment attributes were used to cluster watersheds and analyze whether the models learned the similarities between them. The Transformer model demonstrated improved performance among watersheds with similar activation vectors, proving that utilizing information from other pre-trained watersheds enhances the prediction performance. This study compared the suitable models and training methods for each multi-purpose dam and highlighted the necessity of constructing deep learning models using PT and PT-FT methods for domestic watersheds. Furthermore, the results confirmed that the Transformer model outperforms the LSTM-MSV-S2S model when applying PT and PT-FT methods.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Magazine of the Korean Society of Agricultural Engineers
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• v.13 no.1
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• pp.2206-2217
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• 1971

Spillway and discharge channel of reservoirs require the Control of Large volume of water under high pressure. The energies at the downstream end of spillway or discharge channel are tremendous. Therefore, Some means of expending the energy of the high-velocity flow is required to prevent scour of the riverbed, minimize erosion, and prevent undermining structures or dam it self. This may be accomplished by Constructing an energy dissipator at the downstream end of spillway or discharge channel disigned to dissipated the excessive energy and establish safe flow Condition in the outlet channel. There are many types of energy dissipators, stilling basins are the most familar energy dissipator. In the stilling basin, most energies are dissipated by hydraulic jump. stilling basins have some length to cover hydraulic jump length. So stilling basins require much concrete works and high construction cost. Flip bucket type energy dissipators require less construction cost. If the streambed is composed of firm rock and it is certain that the scour will not progress upstream to the extent that the safety of the structure might be endangered, flip backet type energy dissipators are the most recommendable one. Following items are tested and studied with bucket radius, $R=7h_2$,(medium of $4h_2{\geqq}R{\geqq}10h_2$). 1. Allowable upstream channel slop of bucket. 2. Adequate bucket lip angle for good performance of flip bucket. Also followings are reviwed. 1. Scour by jet flow. 2. Negative pressure distribution and air movement below nappe flow. From the test and study, following results were obtained. 1. Upstream channel slope of bucket (S=H/L) should be 0.25<H/L<0.75 for good performance of flip bucket. 2. Adequated lip angle $30^{\circ}{\sim}40^{\circ}$ are more reliable than $20^{\circ}{\sim}30^{\circ}$ for the safety of structures.

• Bangmulgwan gwa yeongu (The National Museum of Korea Journal)
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• v.1
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• pp.36-73
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• 2024

The Tomb of Jang Mui located in Bongsan-gun, Hwanghae-do Province has attracted much attention since its first investigation due to the inscribed bricks found there that have allowed the guessing of the name and official title of its occupant and construction date. Inscriptions on these bricks, such as the "Prefect of Daebang Commandery Jang Mui" and the "Mu" (戊, the fifth sign of the Chinese calendar), and "Sin" (申, the ninth sign of the Chinese zodiac), have become the basis for believing the location of the government office of Daebang Commandery to be in Bongsangun, Hwanghae-do Province rather than somewhere in the Hangang River region. From the early days of its investigation, the tomb was suggested as historic remains of the Daebang Commandery along with the Earthen Fortress in Jitap-ri. Inscribed bricks excavated from the Tomb of Jang Mui were featured in several books and articles in the form of photographs and rubbings, leading to a vast body of studies on its construction period and the characteristics of its occupant that drew upon interpretations of the inscriptions. However, the inscribed bricks themselves were not publicly available outside those held in the collection of the University of Tokyo, making it difficult to expect consistent research findings on the types of inscribed bricks and their contents. Following previous studies re-examining the structure of the tomb and the materials used for its construction, most scholars dated the Tomb of Jang Mui to 348, a period after the collapse of Daebang Commandery. However, there is still a lack of adequate examination of the bricks, which account for the majority of the artifacts excavated from the tomb. Among the bricks excavated from most brick chamber tombs, including the Tomb of Jang Mui, only those with inscriptions or designs have been collected. Moreover, among these, only those with inscriptions or designs on the stretcher faces have been documented. Accordingly, the bricks themselves have been notably understudied. This paper intends to reorganize the contents of the inscriptions on eleven types (out of sixty-one pieces) of bricks in the collection of the National Museum of Korea, which make up the majority of the bricks excavated from the Tomb of Jang Mui. It also classified them according to their shapes. Furthermore, it examined the bricks from the Tomb of Jang Mui as architectural materials by focusing on their production techniques, including their forming, drying, and firing. Taking a more specific approach, it then compared the results to other bricks from the second century through the fourth century: those from the brick chamber tombs of the Nangnang and Daebang Commanderies and those from the brick chamber tombs built after Nangnang and Daebang Commanderies were ousted. The examination of bricks from the Tomb of Jang Mui has revealed that these bricks were basically produced using the brick manufacturing techniques of Nangnang, but they incorporated new elements found in bricks from brick chamber tombs or brick-and-stone chamber tombs constructed around the mid-fourth century in terms of their size, the use of lime, and the number of inscribed bricks. This supports the prevailing view that the date of the construction of the Tomb of Jang Mui is 348. The Tomb of Jang Mui sustained the existing brick chamber tomb burial tradition, but its ceiling was finished with stone. It demonstrates a blending of the brick chamber tomb practice of the Nangnang and Daebang Commanderies by using bricks produced based on related techniques, but with new elements such as the addition of a lime layer to the bricks. This fusion reflects the political circumstances of its time, such as the expulsion of the Daebang Commandery and the advance of the Goguryeo Kingdom, leading to diverse interpretations. Given archaeological evidence such as the structure, materials, and location of the tomb, the Tomb of Jang Mui appears to be highly related to the Goguryeo Kingdom. However, the forms of the inscribed bricks and the contents of the inscriptions share similarities with brick chamber tombs constructed during the third and fourth centuries in the Jiangsu and Zhejiang regions in China. Further studies on whether the use of lime was an influence from Goguryeo or a continuation of the Daebang tradition and a comparative examination with contemporaneous stone ceiling tombs will provide a more refined understanding of the Tomb of Jang Mui.

• Journal of the Korean Wood Science and Technology
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• v.2 no.2
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• pp.32-34
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• 1974

The important results which have been obtained in the investigation can be recapitulated as follows. 1. As demonstrated by the experimental results and analyses concerning their effects in the on-ground type mushroom house, the constructions in relation to the side wall and ceiling of the experimental house showed a sufficient heat insulation on effect to protect insides of the house from outside climatic conditions. 2. As the effect on the solar type experimental mushroom house which was constructed in a half basement has been shown by the experimental results and analyses, it has been proved to be effective for making use of solar heat. However there were found two problems to be improved for putting solar house to practical use in the farm mushroom growing: (1) the construction of the roof and ceiling should be the same as for the on ground type house, and (2) the solar heat generating system should be reconstructed properly. 3. Among several ventilation systems which have been studied in the experiments, the underground earthen pipe and ceiling ventilation, and vertical side wall and ceiling ventilation systems have been proved to be most effective for natural ventilation. 4. The experimental results have shown that ventilation systems such as the vertical side wall and underground ventilation systems are suitable to put to practical use as natural ventilation systems for farm mushroom house. These ventilation systems can remarkably improve the temperature of fresh air which is introduced into the house by heat transfers within the ventilation passages, so as to approach to the desired temperature of the house without any cooling or heating operation. For example, if it is assuming that X is the outside temperature and Y is the amount of temperature adjustment made by the influence of the ventilation system, the relationships that exist between X and Y can be expressed by the following regression lines. Underground iron pipe ventilation system. Y=0.9X-12.8 Underground earthen pipe ventilation system. Y=0.96X-15.11 Vertical side wall ventilation system. Y=0.94X-17.57 5. The experimental results have 8hown that the relationships existing between the admitted and expelled air and the $CO_2$ concentration can be described with experimental regression lines or an exponent equation as follows: 5.1 If it is assumed that X is an air speed cm/sec. and Y is an expelled air speed in cm/sec. in a natural ventilation system, since the Y is a function of the X, the relationships that exist between X and Y can be expressed by the regression lines shown below: 5.2 If it IS assumed that X is an admitted volume of air in $m^3$/hr. and Y is an expelled volume of air in $m^3$/hr. in a natural ventilation system, since the Y is a function of the X, the relationships that exist between X and Y can be expressed by the regression lines shown below. 5.3 If it is assumed that expelled air speed in emisec. and replacement air speed in cm/sec. at the bed surface in a natural ventilation system are shown as X and Y. respectively, since the Y is a function of the X. the relationships that exist between X and Y can be expressed by the following regression line: GE(100%)-CV (50%) ventilation system. Y=-0.54X+0.84 5.4 If it is assumed that the replacement air speed in cm/sec. at the bed surface is shown as X, and $CO_2$ concentration which is expressed by multiplying 1000 times the actual value of $CO_2$ % is shown as Y, in a natural ventilation system, since the Y is a function of the X, the relationships that exist between X and Y can be expressed by the following regression line: GE(100%)-CV(50%) ventilation system. Y=114.53-6.42X 5.5 If it is assumed that the expelled volume of air is shown as X and the $CO_2$ concencration which is expressed by multiplying 1000 times the actual of $CO_2$% is shown as Y in a natural ventilation system, since the Y is a function of the X, the relationships that exist between X and Y can be expressed by the following exponent equation: GE(100%)-CV(50%) ventilation system. Y=$127.18{\times}1.0093^{-x}$ 5.6 The experimental results have shown that the ratios of the cross sectional area of the GE and CV vent to the total cubic capacity of the house, required for providing an adequate amount of air in a natural ventilation system, can be estimated as follows: GE(admitting vent of the underground ventilation) 0.3-0.5% (controllable) CV(expelling vent of the ceiling ventilation) 0.8-1.0% (controllable) 6. Among several heating devices which were studied in the experiments, the hot-water boilor which wasmodified to be fitted both as hot-water boiler and as a pressureless steam-water was found most suitable for farm mushroom growing.