• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1209-1216
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• 2020

In this study, we propose a method for detecting coastal surface wastes using an UAV(Unmanned Aerial Vehicle) remote sensing method and an object detection algorithm based on deep learning. An object detection algorithm based on deep neural networks was proposed to detect coastal debris in aerial images. A deep neural network model was trained with image datasets of three classes: PET, Styrofoam, and plastics. And the detection accuracy of each class was compared with Darknet-53. Through this, it was possible to monitor the wastes landing on the shore by type through unmanned aerial vehicles. In the future, if the method proposed in this study is applied, a complete enumeration of the whole beach will be possible. It is believed that it can contribute to increase the efficiency of the marine environment monitoring field.

• Journal of IKEEE
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• v.26 no.2
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• pp.306-312
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• 2022

We investigated electrical properties and deep level traps in 4H-SiC merged PiN Schottky (MPS) diodes with different barrier heights by different PN ratios and metallization annealing temperatures. The barrier heights of MPS diodes were obtained in IV and CV characteristics. The leakage current increased with the lowering barrier height, resulting in 10 times larger current. Additionally, the deep level traps (Z_1/2 and RD_1/2) were revealed by deep level transient spectroscopy (DLTS) measurement in four MPS diodes. Based on DLTS results, the trap energy levels were found to be shallow level by 22~28% with lower barrier height It could confirm the dependence of the defect level and concentration determined by DLTS on the Schottky barrier height and may lead to incorrect results regarding deep level trap parameters with small barrier heights.

• Smart Media Journal
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• v.11 no.3
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• pp.62-73
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• 2022

Researches on the prediction of domestic apartment sales price have been continuously conducted, but it is not easy to accurately predict apartment prices because various characteristics are compounded. Prior to predicting apartment sales price, the analysis of major factors, influencing on sale prices, is of paramount importance to improve the accuracy of sales price. Therefore, this study aims to analyze what are the factors that affect the apartment sales price in Gwangju, which is currently showing a steady increase rate. With 6 years of Gwangju apartment transaction price and various social factor data, several maching learning techniques such as multiple regression analysis, random forest, and deep artificial neural network algorithms are applied to identify major factors in each model. The performances of each model are compared with RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and R² (coefficient of determination). The experiment shows that several factors such as 'contract year', 'applicable area', 'certificate of deposit', 'mortgage rate', 'leading index', 'producer price index', 'coincident composite index' are analyzed as main factors, affecting the sales price.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.17-25
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• 2023

As the range of use of urban unmanned aerial vehicles (UAV) expands, it is necessary to operate UAVs efficiently because of its limited battery capacity. For this, it is required to find the optimal flight profile with various simulations. Therefore, it is important to predict the power and energy consumption of the UAV battery. In this paper, we analyzed the relationship between the speed and acceleration of the UAV and power consumption during the flight. Then, we derived a linear model, which is easily utilized. In addition, we also derived an accurate power consumption model based on deep neural network learning. To find the efficient model, we used learning data as 1) the GPS 3-axis velocity and acceleration data, 2) the IMU 3-axis velocity only, and 3) the IMU 3-axis velocity and acceleration data. The final model shows 5.86% error rate for power consumption and 1.50% error rate for the cumulative energy consumption.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.455-462
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• 2022

This study attempted to examine the problems of the expression and format of native advertisements appearing on various platforms and to prepare a plan to regulate them. To this end, in-depth interviews were conducted to those in charge of advertising practice and examined. First, as a problem with the expression and format of native advertisements, it was considered that the congestion and deception of indiscriminate native advertisements appearing on various platforms could bring negative perceptions to consumers. For the second user's interaction, it was considered that customized advertising expressions through targeting by platform should be produced. Third, regarding the regulation of native advertisements, it was suggested that regulatory measures for consumer protection should be prepared and that market autonomy should be left to it. A strategic operation plan for native advertising according to various platforms should be prepared.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.277-287
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• 2022

Recent trends in sharing online video contents show that vlogging on everyday life can cause meaningful changes in viewers' perception of mediated characters and their own lifestyles. We explored that flourishing everyday life video contents online are intertwined with viewers' psychological engagement such as empathy and social presence, let alone self-enhancing motivations such as self-reflection and psychological empowerment. Survey analysis results suggest that between contents types of vlog (everyday life vs. in-depth information), watching in-depth information videos significantly affected viewers' psychological engagement and self-enhancing motivations. Compared to celebrity's online videos, daily videos starring laypeople showed significantly positive impacts on viewers' engagement such as empathy, social presence, and self-enhancement such as self-reflection, psychological empowerment.

• Journal of the Korean Geosynthetics Society
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• v.21 no.2
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• pp.21-30
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• 2022

Shear strength is the most important indicator in the evaluation of rock slope stability. It is generally estimated by comparing the results of existing literature data, back analysis, experiments and etc. There are additional variables related to the state of discontinuity to consider in the shear strength of the rock slope. It is difficult to determine whether these variables exist through drilling, and it is also difficult to find an exact relationship with shear strength. In this study, the data calculated through back analysis were used. The relationship between previously considered variables was applied to deep learning and the possibility for estimating shear strength of rock slope was explored. For comparison, an existing simple linear regression model and a deep learning algorithm, a deep neural network(DNN) model, were used. Although each analysis model derived similar prediction results, the explanatory power of DNN was improved with a small differences.

• Tunnel and Underground Space
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• v.33 no.2
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• pp.83-94
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• 2023

Unlike the conventional triaxial test cells for cylindrical specimens, which impose uniform lateral confining pressures, the GREAT (Geo-Reservoir Experimental Analogue Technology) cell can exert differential radial stresses using eight independently-controlled pairs of lateral loading elements and thereby generate horizontal stress fields with various magnitudes and orientations. In the preceding companion paper, GREAT cell tests were numerically simulated under different mechanical loading conditions and the validity of the numerical model was investigated by comparing experimental and numerical results for circumferential strain. In the present study, we simulated GREAT cell tests for an artificial sample containing a fracture under both mechanical loading and fluid flow conditions. The numerical simulation was carried out by varying the mechanical properties of the fracture surface, which were unknown. The numerical responses (circumferential strains) of the sample were compared with experimental data and a good match was found between the numerical and experimental results under certain mechanical conditions of the fracture surface. Additionally, the effect of fluid flow conditions on the mechanical behavior of the sample was investigated and discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2C
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• pp.77-84
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• 2010

In planning underground roadway foundation on soft ground, deep cement mixing method (DCM) is employed. The proper mixing ratio using batch test and replacement rates that meet strength criteria are used for deep cement mixing column. Stiffness ratio and distance between deep cement mixing columns (C.T.C) are varied to find out influences on stress, displacement, and differential settlement. The replacement ratios that meet settlement criteria are 10~35%. As stiffness varies, stress reaches at 769.kPa that exceed criteria due to stress concentration when stiffness ratio difference is over 30. Also, when C.T.C is 5 m, stress spreads to soils, so C.T.C need to be considered carefully. The vertical displacement is 0.6~1.56 cm, and angular distortion is 1/909~1/510.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.391-395
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• 2023

There are countless possibilities lying ahead of us, and while predicting the future may be challenging, it does not render the act of forecasting meaningless. Predicting various possibilities allows us to be flexible in coping with unforeseen circumstances. This study was conducted to explore extreme events (X-events) in the population sector in South Korea. To achieve this, focus group interviews were conducted with 32 emergency planning officers in government and public services. Based on these interviews, significant research findings were derived, indicating that population issues such as population decline and aging could have substantial impacts on various fields, including the economy and national defense. With this study as a catalyst, we anticipate a more active discussion and discourse on X-events that could occur in our society.