• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.37 no.1
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• pp.45-51
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• 2001

In order to investigate the optimal design weight of sinkers for preventing cage net from deforming in current, the model experiment on 2 types of square cage nets with different S sub(n)/S, the ratio of total area of netting projected to the perpendicular to the water flow S sub(n) to wall area of netting S, and 4 kinds of sinkers was carried out in circulation water channel. The model cage nets were made in 1/10 scale and the total weight in water of 4 sinkers attached to each corner of their bottom frames was 18, 54, 90, and 126g, respectively equivalent to 0.1, 0.3, 0.5, and 0.7 kg per unit area of prototype net. The results obtained can be summarizes as follows; Due to the deformation of each net where it was lifted towards the surface in severe conditions, its volume was reduced. This depended highly on the weight of sinkers placed in the bottom corner of cage nets, even if the variation of S sub(n)/S had a little effect on their deformation in current less than 0.4 m/s. In addition, it was observed that the total weight of sinkers for preventing the net from deforming to the extent of less than 50% inside its initial volume was 31 to 245 kg in the range of 0.3 to 0.6 m/s and the adequate design weight of sinker was approximately 0.5 kg per its unit area.

• 대한공업교육학회지
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• v.39 no.2
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• pp.122-143
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• 2014

The purpose of this research were to develop program of elementary school technology education using history of technology and to learn about its effect. In order to accomplish the purpose of the research, we developed the program by referring to various records and perform the qualitative experiment study through several questionnaire, pictures and materials, to learn about the program effect. The research took the mixed-model design, consisted of collection of quantitative data by Likert scale and collection of qualitative data including the open-ended questions. And the research results were as below. First, development of elementary school technology education program using history of technology was developed as program for 12 hours, 12 themes, for the elementary levels. Second, seeing the result of program of elementary school technology education using history of technology, the program for history of technology for the primary school students, a majority of answers showed high satisfaction about the program, giving answers such as 'I want to do it again following hands on minds on activity.' Third, according to the analysis on the qualitiative evidence of the program, students were found to take pictures with hands on minds on activity camera obscura with much interest and curiosity. Many students are seen to complete the task on their own with a great a look of self-satisfaction, understanding the principle of camera.

• Journal of Korea Water Resources Association
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• v.49 no.11
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• pp.931-939
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• 2016

Bangudae Petroglopys of the national treasure No. 285 located in elevation of 53 m to 57 m have been damaged by repetition of submergence and exposure due to the Sayeon-dam of EL.60 m constructed in down stream. In this study, as a preservation plan of the petroglyphs from the contact with water, the construction of eco-levee was suggested and its effect was investigated in the views of hydraulic engineering. It was designed to be located aside of 80 m from Bangudae Petroglyphs with the length of 440 m in streamwise direction, and it was need to construct a new channel maintaining the original hydraulic capacity and conveyance. Hydraulic characteristics such as water surface elevations and velocities near Bangudae Petroglyphs were measured after the eco-levee was installed in the hydraulic model with the scale of 1:50. It showed that there were not much changes of water surface elevations and velocities between sayeon-dam spillway EL. 60 m (Suggestion 1) and EL. 54 m (Suggestion 2). It was concluded the eco-levee could be made of natural materials like soil, pebble, gravel in terms of allowable velocity and shear stresses. The slope of water surface at Suggestion 2 was steeper, and velocities near Bangudae Petroglyphs were also faster than Suggestion 1. As the vorties occured at the left side in Suggestion 2, more detailed study is required.

• Journal of the Korean earth science society
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• v.25 no.6
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• pp.418-427
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• 2004

Recently, urban planning with consideration of urban climate, represented by the concept of urban ventilation lane is widely practiced in many countries. The concept of urban ventilation lane is mainly aimed to improve the thermal comfort within urban area in summer season. It has also the aim to reduce the urban air pollution by natural cold air drainage flows which are to be intensified by a suitable alignment of buildings as well as use zonings based on scientific reasons. In this study, the prevailing wind ventilation lane of a local wind circulation and around Daegu for a typical summer days was investigated by using a numerical simulation. The transport of air pollutants by the local circulation winds was also investigated by using the numerical simulation model, the RAMS (Reasonal Atmospheric Model System).The domain of interest is the vicinity of Daegu metropolitan city (about 900 km2). The horizontal scale of the area is about 30 km. The simulations were conducted under a late spring synoptic condition with weak gradient wind and almost clear sky. From the numerical experiment, the following three conclusions were obtained: (1) The major wind passages of the local circulation wind generated by radiative cooling over the representative mountains of Daegu (Mt. Palgong and Mt. Ap) were found. The winds blow down along the valley axis over the eastern part of Daegu as a gravity flow during nighttime. (2) At the flatland, the winds blow toward the western part of Daegu through the city center. (3) As the results, the air pollutants were transported toward the western part of Daegu by the winds during nighttime.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.4
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• pp.265-280
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• 2021

Population density due to urbanization is making people interested in underground space development and much interest in TBM construction with low vibration and noise. This led to a lot of research on TBM. However, research on the characteristics of the cutterhead opening of the TBM equipment being occluded under the ground conditions under which it is excavated is insufficient. Accordingly, a study was conducted to investigate clogging of the cutterhead opening during the shield TBM rolling. To identify the clogging of cutterhead openings in SHIELD TBM equipment, the reduced model experiment was divided into clay rate (10%, 30%, 50%, 60%), cutterhead opening rate (30%, 50%, 60%), and cutterhead rotation direction (one-way, two-way) and rotational speed (3 RPM) and conducted in 36 cases. Results of scale model test on shield TBM clogging, it was analyzed that the ground condition containing clay soil increased the clogging effect in both directions than the unidirectional rotation, and that the lower the rotational speed of the cutterhead, the less the clogging effect. Accordingly, the direction of cutterhead rotation, rotational speed and opening rate are calculated by taking into account ground conditions during ground excavation, the clogging effect can be reduced. It is believed to be effective in saving air as the clogging effect is reduced. Therefore, this study is expected to be an important material for domestic use of shield TBM.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.639-650
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• 2022

In areas where large-scale sediment transport occurs, it is important to apply appropriate countermeasure method because the phenomenon tends to accelerate by time duration. Among the various countermeasure methods applied so far, beach nourishment needs to be reviewed as an erosion prevention measure because the erosion pattern is mitigated and environmentally friendly depending on the particle size. In the case of beach nourishment. a detailed review is required to determine the size, range, etc., of an appropriate particle diameter. In this study, we investigated the characteristics of the related topographic change using the change in the particle size of nourishment materials, the application of partial area, and the condition under the coexistence of waves and wind as variables because those factors are hard to be analyzed and interpreted within results and limitation of that the existing numerical models are not able to calculate and result out so that it is required that phenomenon or efforts are reviewed at the same time through physical model experiments, field monitoring and etc. So we attempt to reproduce the tendency of beach erosion and deposition and predict possible phenomena in the future using machine learning techniques for phenomena that it is not able to be interpreted by numerical models. we used the hydraulic experiment results for the training data, and the accuracy of the prediction results according to the change in the training method was simultaneously analyzed. As a result of the study it was found that topographic changes using machine learning tended to be similar to those of previous studies in short-term predictions, but we also found differences in the formation of scour and sandbars.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.2
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• pp.255-268
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• 2018

Subsea tunnel can be highly vulnerable to seawater intrusion due to unexpected high-water pressure during construction. An artificial ground freezing (AGF) will be a promising alternative to conventional reinforcement or water-tightening technology under high-water pressure conditions. In this study, the freezing energy and required time was calculated by the theoretical model of the heat flow to estimate the total amount of refrigerant required for the artificial ground freezing. A lab-scale freezing chamber was devised to investigate changes in the thermal and mechanical properties of sandy soil corresponding to the variation of the salinity and water pressure. The freezing time was measured with different conditions during the chamber freezing tests. Its validity was evaluated by comparing the results between the freezing chamber experiment and the numerical analysis. In particular, the freezing time showed no significant difference between the theoretical model and the numerical analysis. The amount of refrigerant for artificial ground freezing was estimated from the numerical analysis and the freezing efficiency obtained from the chamber test. In addition, the energy ratio for maintaining frozen status was calculated by the proposed formula. It is believed that the energy ratio for freezing will depend on the depth of rock cover in the subsea tunnels and the water temperature on the sea floor.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.309-316
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• 2022

This study is a study on the YouTube e-learning advanced service plan in the non-face-to-face era. The trends in education change were examined through literature research and prior research, and improvement measures were suggested through online surveys and in-depth interviews. As for the research method, the first online survey was conducted based on the Honeycomb model and the Likert 5-point scale targeting 90 MZ generation who have experience learning on YouTube for a total of 14 days from October 15 to 28, 2021. A second in-depth interview was conducted with 6 people who answered that the frequency of learning through YouTube is high. As a result of the experiment, users thought that there was an improvement point according to the purpose of learning, and they were able to derive elements that felt a problem in common. In addition, I proposed a new YouTube learning platform through additional questions. Through this study, it is expected that YouTube e-learning service reference materials can be used to respond to the post-non-face-to-face era.

• Smart Media Journal
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• v.9 no.4
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• pp.26-35
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• 2020

Attempts to predict future stock prices have been studied steadily since the past. However, unlike general time-series data, financial time-series data has various obstacles to making predictions such as non-stationarity, long-term dependence, and non-linearity. In addition, variables of a wide range of data have limitations in the selection by humans, and the model should be able to automatically extract variables well. In this paper, we propose a 'sliding time step normalization' method that can normalize non-stationary data and LSTM autoencoder to compress variables from all variables. and 'moving transfer learning', which divides periods and performs transfer learning. In addition, the experiment shows that the performance is superior when using as many variables as possible through the neural network rather than using only 100 major financial variables and by using 'sliding time step normalization' to normalize the non-stationarity of data in all sections, it is shown to be effective in improving performance. 'moving transfer learning' shows that it is effective in improving the performance in long test intervals by evaluating the performance of the model and performing transfer learning in the test interval for each step.