• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.369-378
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• 2013

This paper presents a vision/LiDAR integrated navigation system that provides accurate relative navigation performance on a general ground surface, in GNSS-denied environments. The considered ground surface during flight is approximated as a piecewise continuous model, with flat and slope surface profiles. In its implementation, the presented system consists of a strapdown IMU, and an aided sensor block, consisting of a vision sensor and a LiDAR on a stabilized gimbal platform. Thus, two-dimensional optical flow vectors from the vision sensor, and range information from LiDAR to ground are used to overcome the performance limit of the tactical grade inertial navigation solution without GNSS signal. In filter realization, the INS error model is employed, with measurement vectors containing two-dimensional velocity errors, and one differenced altitude in the navigation frame. In computing the altitude difference, the ground slope angle is estimated in a novel way, through two bisectional LiDAR signals, with a practical assumption representing a general ground profile. Finally, the overall integrated system is implemented, based on the extended Kalman filter framework, and the performance is demonstrated through a simulation study, with an aircraft flight trajectory scenario.

• Journal of Korea Water Resources Association
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• v.50 no.4
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• pp.263-275
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• 2017

Integrated numerical approaches with physically-based conceptualization are required for accurate urban inundation simulation. In this study, we described, applied and analyzed an integrated 1-dimensional (1D) sewerage system and 2-dimensional (2D) surface flow model, which was suggested by Lee et al. (2015). This model was developed based on dual-drainage concept, and uses storm drains as an discharge exchange spot rather than manholes so that interaction phenomena between surface flow and sewer pipe flow are physically reproduced. In addition, the building block concept which prevents inflows from outside structures is applied in order to consider building effects. The capability of the model is demonstrated via reproducing the past flooding event at the Sadang-cheon River catchment, Seoul, South Korea. The results show the plausible causes of the inundation could be analysed in detail by integrated 1D-2D modeling.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.339-351
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• 2020

In response to changes in Fourth Industrial Revolution in recent years, the field of education has focused on development of the human resources in the areas of artificial intelligence (AI: Artificial Intelligence) and industrial robot. Due to particular interest in these areas, the importance of developing integrated human resources equipped with artificial intelligence technology is emphasized in higher education and vocational competence development. In regards to rapid changing environment, this study created a program "Fostering personalized AI integrated human resource" and established an operational model correspond to latest personalized education trend. The established operational model was conducted twice using Delphi survey with experts in AI and innovative education in order to verify the suitability of program's basic structure, training process, and the sub-components of the operational strategy. The final training model was applied to the online vocational training platform (STEP) and a plan was proposed to establish a personalized training model to foster an AI integrated competent individual.

• Journal of Digital Convergence
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• v.13 no.7
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• pp.99-107
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• 2015

When new information communication technologies(ICTs) have appeared, researchers and praticitioners have explored how to spread the technologies. In e-commerce, social commerce has been introduced recently and attempts to understand social commerce have proposed diverse research models. This study proposed a hypothetical model which integrates technology readiness(TR), technology acceptance model(TAM), and theory of planned behavior(TPB). Through PLS path modeling, we found that every hypothesis except social norm-intention path alone proved significant. This result means that integrated model is useful to understand the adoption of new ICTs including social commerce. Finally, based on the findings, suggestions for future research were discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1100-1118
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• 2021

In a wide range of ML applications, the training data contains privacy-sensitive information that should be kept secure. Training the ML systems by privacy-sensitive data makes the ML model inherent to the data. As the structure of the model has been fine-tuned by training data, the model can be abused for accessing the data by the estimation in a reverse process called model inversion attack (MIA). Although, MIA has been applied to shallow neural network models of recognizers in literature and its threat in privacy violation has been approved, in the case of a deep learning (DL) model, its efficiency was under question. It was due to the complexity of a DL model structure, big number of DL model parameters, the huge size of training data, big number of registered users to a DL model and thereof big number of class labels. This research work first analyses the possibility of MIA on a deep learning model of a recognition system, namely a face recognizer. Second, despite the conventional MIA under the white box scenario of having partial access to the users' non-sensitive information in addition to the model structure, the MIA is implemented on a deep face recognition system by just having the model structure and parameters but not any user information. In this aspect, it is under a semi-white box scenario or in other words a gray-box scenario. The experimental results in targeting five registered users of a CNN-based face recognition system approve the possibility of regeneration of users' face images even for a deep model by MIA under a gray box scenario. Although, for some images the evaluation recognition score is low and the generated images are not easily recognizable, but for some other images the score is high and facial features of the targeted identities are observable. The objective and subjective evaluations demonstrate that privacy cyber-attack by MIA on a deep recognition system not only is feasible but also is a serious threat with increasing alert state in the future as there is considerable potential for integration more advanced ML techniques to MIA.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.89-97
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• 2013

After introducing iPhone in Korea, the craze for iPhone was perceived to be extraordinaire phenomenon and the mobile businesses and researchers paid attention to it. This research purposes to explore more predictive model that explain to adopt the smartphones in Korea. This research show that all of models, TPB, TAM and the integrated model, are significant to explain intention to use the smartphones. TPB explains the higher than TAM, and the integrated model explains the slightly higher than TPB. These results suggest that researcher explore and build the more predictive model that comprise social influences and personal attributes than TAM that is employed broad to study new information communication systems and devices.

• Ocean and Polar Research
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• v.43 no.3
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• pp.179-192
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• 2021

In this study, an integrated wave model from global to coastal scales was developed to improve the operational wave prediction performance of the Korean Meteorological Administration (KMA). In this system, the wave model was upgraded to the WaveWatch III version 6.07 with the improved parameterization of the source term. Considering the increased resolution of the wind input field and the introduction of the high-performance KMA 5^th Supercomputer, the spatial resolution of global and regional wave models has been doubled compared to the operational model. The physical processes and coefficients of the wave model were optimized for the current KMA global atmospheric forecasting system, the Korean Integrated Model (KIM), which is being operated since April 2020. Based on the sensitivity experiment results, the wind-wave growth parameter (β_max) for the global wave model was determined to be 1.33 with the lowest root mean square errors (RMSE). The value of β_max showed the lowest error when applied to regional/coastal wave models for the period of the typhoon season when strong winds occur. Applying the new system to the case of August 2020, the RMSE for the 48-hour significant wave height prediction was reduced by 13.4 to 17.7% compared to the existing KMA operating model. The new integrated wave prediction system plans to replace the KMA operating model after long-term verification.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.587-588
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• 2004

• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.1111-1112
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• 2004

• Proceedings of the Korean Nuclear Society Conference
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• 2005.10a
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• pp.624-625
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• 2005