• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.327-332
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• 2021

Materials used for education include SM20C, Al6061, and acrylic. SM20C materials are used a lot in certification tests and functional competitions as carbon steel, but they are also used in industrial sites. Al6061 is said to be a material that produces a lot of tools because it has lower hardness than carbon steel and is highly flexible. When practical guidance is given to students using acrylic materials, it is a material that causes vibration and tool damage due to excessive cutting. In this process, we examine how impact on the 5-axis equipment 2NC head can affect precision control. The weakest part of a five-axis equipment is the head that controls the AC axis. In the event of precision and cumulative tolerances in this area, the precision of all products is reduced. Thus, a key part of the 2NC head, the spindle housing was carried out using Al7075 T6 (U.S. Alcoasa) material and the entire body using FCD450 (spherical graphite cast iron). In the vibration and cutting process acting on these two materials, the analysis was carried out to determine the value of applying the force as a finite element analysis under extreme conditions. We hope that using these analytical data will help students see and understand the structure of 5-axis machining rather than 5-axis cutting.

• Journal of Korea Water Resources Association
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• v.52 no.7
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• pp.463-473
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• 2019

This study compared the characteristics of the optimization technique and the water supply and demand forecast using K-WEAP (Korea-Water Evaluation and Planning System) model and MODSIM (Modified SIMYLD) model considering wtaer supply priority. Currently, The national water resources plan applied same priority for municipal, industrial and agricultural demand. the K-WEAP model performs the ratio allocation to satisfy the maximum satisfaction rate, whereas the MODSIM model should be applied to the water supply priority of demands. As a result of applying the priority, water shortage decreased by an average of $1,035,000m^3$ than same prioritized results. It is due to the increase of the return flow rate as the distribution of Municipal and industrial water increases. Comparing the analysis results of K-WEAP and MODSIM applying the priorities, the relative error was within 5.3% and the coefficient of determination ($R^2$) was 0.9999. In addition, if both models provide reasonable water balance analysis results, K-WEAP is superior to GUI convenience for model construction and data processing. However, MODSIM is more effective in simulation time efficiency. It is expected that it will be able to carry out analysis according to various scenarios using the model.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.217-217
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• 2015

The objective of this study was mainly to evaluate the water resources potential of Lake Tana Basin (LTB) by using Soil and Water Assessment Tool (SWAT). From SWAT simulation of LTB, about 5236 km2 area of LTB is gauged watershed and the remaining 9878 km2 area is ungauged watershed. For calibration of model parameters, four gauged stations were considered namely: Gilgel Abay, Gummera, Rib, and Megech. The SWAT-CUP built-in techniques, particle swarm optimization (PSO) and generalized likelihood uncertainty estimation (GLUE) method was used for calibration of model parameters and PSO method were selected for the study based on its performance results in four gauging stations. However the level of sensitivity of flow parameters differ from catchment to catchment, the curve number (CN2) has been found the most sensitive parameters in all gauged catchments. To facilitate the transfer of data from gauged catchments to ungauged catchments, clustering of hydrologic response units (HRUs) were done based on physical similarity measured between gauged and ungauged catchment attributes. From SWAT land use/ soil use/slope reclassification of LTB, a total of 142 HRUs were identified and these HRUs are clustered in to 39 similar hydrologic groups. In order to transfer the optimized model parameters from gauged to ungauged catchments based on these clustered hydrologic groups, this study evaluates three parameter transfer schemes: parameters transfer based on homogeneous regions (PT-I), parameter transfer based on global averaging (PT-II), and parameter transfer by considering Gilgel Abay catchment as a representative catchment (PT-III) since its model performance values are better than the other three gauged catchments. The performance of these parameter transfer approach was evaluated based on values of Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The computed NSE values was found to be 0.71, 0.58, and 0.31 for PT-I, PT-II and PT-III respectively and the computed R2 values was found to be 0.93, 0.82, and 0.95 for PT-I, PT-II, and PT-III respectively. Based on the performance evaluation criteria, PT-I were selected for modelling ungauged catchments by transferring optimized model parameters from gauged catchment. From the model result, yearly average stream flow for all homogeneous regions was found 29.54 m3/s, 112.92 m3/s, and 130.10 m3/s for time period (1989 - 2005) for region-I, region-II, and region-III respectively.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.209-218
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• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

• Animal Bioscience
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• v.34 no.11
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• pp.1811-1821
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• 2021

Objective: A trial was conducted to investigate the effects of supplemental levels of Mn provided by organic and inorganic trace mineral supplements on growth, tissue mineralization, mineral balance, and antioxidant status of growing broiler chicks. Methods: A total of 500 male chicks (8-d-old) were used in 10-day feeding trial, with 10 treatments and 10 replicates of 5 chicks per treatment. A 2×5 factorial design was used where supplemental Mn levels (0, 25, 50, 75, and 100 mg Mn/kg diet) were provided as MnSO₄·H₂O or MnPro. When Mn was supplied as MnPro, supplements of zinc, copper, iron, and selenium were supplied as organic minerals, whereas in MnSO₄·H₂O supplemented diets, inorganic salts were used as sources of other trace minerals. Performance data were fitted to a linearbroken line regression model to estimate the optimal supplemental Mn levels. Results: Manganese supplementation improved body weight, average daily gain (ADG) and feed conversion ratio (FCR) compared with chicks fed diets not supplemented with Mn. Manganese in liver, breast muscle, and tibia were greatest at 50, 75, and 100 mg supplemental Mn/kg diet, respectively. Higher activities of glutathione peroxidase and superoxide dismutase (total-SOD) were found in both liver and breast muscle of chicks fed diets supplemented with inorganic minerals. In chicks fed MnSO₄·H₂O, ADG, FCR, Mn balance, and concentration in liver were optimized at 59.8, 74.3, 20.6, and 43.1 mg supplemental Mn/kg diet, respectively. In MnPro fed chicks, ADG, FCR, Mn balance, and concentration in liver and breast were optimized at 20.6, 38.0, 16.6, 33.5, and 62.3 mg supplemental Mn/kg, respectively. Conclusion: Lower levels of organic Mn were required by growing chicks for performance optimization compared to inorganic Mn. Based on the FCR, the ideal supplemental levels of organic and inorganic Mn in chick feeds were 38.0 and 74.3 mg Mn/kg diet, respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.141-148
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• 2021

In some intersections or busy traffic roads, there are more pedestrians in a specific period of time, and there are many traffic accidents caused by road congestion. Especially at the intersection where there are schools nearby, it is particularly important to protect the traffic safety of students in busy hours. In the past, when designing traffic lights, the safety of pedestrians was seldom taken into account, and the identification of motor vehicles and traffic optimization were mostly studied. How to keep the road smooth as far as possible under the premise of ensuring the safety of pedestrians, especially students, will be the key research direction of this paper. This paper will focus on person, motorcycle, bicycle, car and bus recognition research. Through investigation and comparison, this paper proposes to use YOLO v4 network to identify the location and quantity of objects. YOLO v4 has the characteristics of strong ability of small target recognition, high precision and fast processing speed, and sets the data acquisition object to train and test the image set. Using the statistics of the accuracy rate, error rate and omission rate of the target in the video, the network trained in this paper can accurately and effectively identify persons, motorcycles, bicycles, cars and buses in the moving images.

• Economic and Environmental Geology
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• v.53 no.6
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• pp.703-713
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• 2020

In many geological fields, including hydrogeology, it is of great importance to determine the heterogeneity of the subsurface media. This study briefly introduces the concept and theory of the method that can estimate the hydraulic properties of the media constituting the aquifer, which was recently introduced by Park (2020). After the introduction, the method was applied to the synthetic aquifer to demonstrate the practicality, from which various implications were drawn. The introduced technique uses a global optimization technique called the covariance matrix adaptation evolution strategy (CMA-ES). Conceptually, it is a methodology to characterize the aquifer heterogeneity by assimilating the groundwater level time-series data due to the imposed hydraulic stress. As a result of applying the developed technique to estimate the hydraulic conductivity of a hypothetical aquifer, it was confirmed that a total of 40000 unknown values were estimated in an affordable computational time. In addition, the results of the estimates showed a close numerical and structural similarity to the reference hydraulic conductivity field, confirming that the quality of the estimation by the proposed method is high. In this study, the developed method was applied to a limited case, but it is expected that it can be applied to a wider variety of cases through additional development of the method. The development technique has the potential to be applied not only to the field of hydrogeology, but also to various fields of geology and geophysics. Further development of the method is currently underway.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.148-159
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• 2021

This study focused on searching for optimal locations for general high schools by considering the minimum move distance and the maximum student capacity upon starting a common curriculum based on a high school credit system by taking Seoul as an illustration. The main results were as follows. First, the results from P-median showed that the students' average move distance was below 625m when more than 30% of general high schools offer the common curriculum courses. In addition, the results from MCLP indicated that it was possible to hold all the students. Second, although all the universities located in Seoul open the common curriculum courses, it would not be available to hold all students. On the other hand, when more than 20% of the universities open the courses, MCLP indicated that it was possible to hold the same capacity. In addition, the Office of Education should support moving to the universities offering courses for students affiliated with high schools located in the southeastern area of Seoul and in poor transportation areas. It is expected that by suggesting a problem solving framework regarding space with a spatial optimization method, the study results can be used as a basic data for selecting schools offering common curriculum courses.

• Explosives and Blasting
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• v.38 no.4
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• pp.16-25
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• 2020

Multi-setting smart-investigation of the ground and large uncharged hole boring (MSP) method to reduce the blast-induced vibration in a tunnel excavation is carried out over 50m of long-distance boring in a horizontal direction and thus has been accompanied by deviations in boring alignment because of the heavy and one-directional rotation of the rod. Therefore, the deviation has been adjusted through the boring machine's variable setting rely on the previous construction records and expert's experience. However, the geological characteristics, machine conditions, and inexperienced workers have caused significant deviation from the target alignment. The excessive deviation from the boring target may cause a delay in the construction schedule and economic losses. A deep learning-based prediction model has been developed to discover an ideal initial setting of the MSP machine. Dropout, early stopping, pre-training techniques have been employed to prevent overfitting in the training phase and, significantly improved the prediction results. These results showed the high possibility of developing the model to suggest the boring machine's optimum initial setting. We expect that optimized setting guidelines can be further developed through the continuous addition of the data and the additional consideration of the other factors.