• Tunnel and Underground Space
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• v.8 no.4
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• pp.287-295
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• 1998

Limit equilibrium method is widely used for the stability analysis of soil slopes. In jointed rock slopes however, the failure of the slope is largely dependent upon the strength and deformability of the joints in the rock mass and quite often failure occurs along the joints. This paper describes the use of ubiquitous joint model for the stability analysis of the jointed rock slopes. This model is essentially an anisotropic elasto-plastic model and can simulate two sets of joint in arbitrary orientations. Validation of the developed with the factor of safety equal to unity was selected when the shape of the failure plane is assumed log spiral. Then the factor of safety of the rock slope having two perpendicular joint sets was calculated while rotating joint orientations. Rusults were compared with limit equilibrium solutions on soil slopes having equivalent soil properties when plane sliding was assumed. Developed model predicted the factor of safety of jointed rock slope in a reasonable accuracy when joint spacing is sufficiently small.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.3
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• pp.95-105
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• 2009

Spam call is one of the main security threat in VoIP services. In this paper, we have designed simulation model for performance evaluation of VoIP spam defense mechanism. The simulation model has functions for performance evaluation such as calls generation and input/output comparison. Four representative caller models have been developed for performance evaluation and each model has its own characteristics as statistical parameters. The target mechanism of performance evaluation is SPIT(Spam over Internet Telephony) level decision algorithm, and we have derived SPIT levels of caller models. The performance evaluation model is designed using the DEVS formalism and DEVSJAVA$^{TM}$ is exploited for development and execution of simulation models.

• Smart Media Journal
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• v.10 no.4
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• pp.21-27
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• 2021

Recently, the importance of counseling is increasing due to the Corona Blue caused by COVID-19. Also, with the increase of non-face-to-face services, researches on chatbots that have changed the counseling media are being actively conducted. In non-face-to-face counseling through chatbot, it is most important to accurately understand the client's emotions. However, since there is a limit to recognizing emotions only in sentences written by the client, it is necessary to recognize the dimensional emotions embedded in the sentences for more accurate emotion recognition. Therefore, in this paper, the vector and sentence VAD (Valence, Arousal, Dominance) generated by learning the Word2Vec model after correcting the original data according to the characteristics of the data are learned using a deep learning algorithm to learn the multi-dimensional We propose an emotion recognition model. As a result of comparing three deep learning models as a method to verify the usefulness of the proposed model, R-squared showed the best performance with 0.8484 when the attention model is used.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.357-364
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• 2022

This study aims to design a humanities model for preliminary universities using an online platform to develop and expand humanities thinking of preliminary university students. P University Expert Focus Group Interview and student surveys are conducted, and based on the analysis results, a preliminary university model suitable for the humanities field is proposed. Expert FGI suggested the necessity of human resources education to build an online platform-based preliminary university model and improve humanities capabilities. As a result of the student survey, it was found that a majority of the respondents had high interest in humanities and recognized the need for a humanities preliminary university. This study proposes a humanities-based preliminary university model that enables interactive communication in virtual space using the cross-platform Photo Server. The implication of this study is that it contributes to strengthening the humanities capabilities of preliminary university students by presenting an online platform preliminary university model that can respond to changes in the external environment. Since this study has a limitation in that it does not present examples of preliminary universities, it is necessary to verify the educational effect of platform-based ppreliminary university management in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.158-158
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• 2021

도시에 불투수면적이 증가하고, 기후변화가 극심해져감에 따라 홍수 및 열섬현상과 같은 도시의 물 문제가 발생하고 있다. 이를 해결하기 위한 정책의 일환으로 우리나라의 녹색건축인증제도(Green Standard for Energy and Environmental Design, G-SEED)에서는 물순환 관리를 평가하고 있다. 하지만, 현재 G-SEED의 평가방법을 살펴보면 빗물관리시설의 설치 정도로 평가하고 있고, 강우 특성 또한 고려되고 있지 않다. 그러므로 본 연구에서는 G-SEED의 빗물관리 및 이용 항목에 대해 수문 모델을 통해 효과를 정량화함으로써 성능에 따라 평가할 수 있는 방법을 제안하였다. 빗물관리 항목에서는 유출저감률을, 빗물이용 항목에서는 빗물이용률을 평가지표로 선정하였고, 각 평가인자를 산출하기 위하여 개념모델을 적용하였다. 빗물이용시설의 경우 초기우수배제장치 용량과 필터 효율에 따른 빗물유입량의 변화와 급수인원에 따른 수요량 변화를 고려한 수문모델을 개발하였고, 수요량과 빗물저장조 용량에 따른 유출저감률과 빗물이용률을 알아보기 위해 MATLAB을 이용하여 모의해보았다. 또한, 옥상녹화의 경우에는 강우, 저류, 증발산, 유출을 고려한 수문흐름모델을 적용하였고, 토층의 두께와 배수(저장) 층의 용량에 따라 모의하여 평가기준을 선정하였다. 제안된 수문모델의 검증을 위하여 서울대학교 기숙사와 35동 옥상녹화의 실측데이터를 비교하였고, 적용성 평가를 위해 RMSE(Root Mean Square Error)와 NSE(Nash-Sutcliffe Efficiency)를 이용하였다. 본 연구에서 제안된 방법을 통해 빗물관리시설의 수문학적 성능에 따른 평가가 가능해질 것이며 설계자와 건축가들로 하여금 실질적인 효과를 내는 시설을 설치하게끔 유도할 수 있을 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.27-27
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• 2021

세굴은 유체와 유사의 상호작용으로 발생하는 중요한 자연 현상 중 하나로, 구조 및 지반 붕괴, 홍수, 생태계 파괴 등의 문제를 야기할 수 있다. 이러한 세굴 현상을 예측하기 위해 많은 수치적 연구가 진행되어왔지만, 대부분의 연구가 기존 격자기반방법인 유한체적법 (FVM)과 개별요소법 (DEM)이 연성된 모델을 이용하였고, 이는 격자 의존도로 인한 정확도와 효율성의 문제점을 보였다. 해결책으로 입자기반 유체해석 방법인 약압축성 SPH (WCSPH)와 개별요소법의 결합모델을 이용한 모의가 연구되어 왔지만, 단순 밀도차를 활용한 유체해석방법이 압력의 불안정성을 야기하여 유사의 운동에도 영향을 주는 결과를 보였다. 또한, 개별요소법의 특성상 모의 입자의 크기를 실제 실험 입자의 크기와 동일하게 설정하면서 입자수가 지나치게 증가해 계산의 효율성이 현저히 낮아지게 되었고, 이로 인해 실제 자연 지형에 적용하는데 어려움을 보여주었다. 본 연구에서는 향상된 세굴 수치모의해석을 위해 반복법을 통해 안정적인 유체 압력을 계산하는 비압축성 SPH (ISPH)와 개별요소법을 연성한 ISPH-DEM 모델을 사용하였다. 또한, 계산속도 향상을 위해 하나의 입자가 다수의 작은 입자의 움직임을 대표하는 Coarse-grained 방법을 적용하여 기존 모델을 개선하였다. 개선된 모델을 NFLOW ISPH PURPLE 소프트웨어를 이용하여 세굴 현상을 수치 모의하였고 실험 결과와 검증을 진행한 결과, 세굴의 깊이, 너비, 형상 등을 비교하였을 때 약 10% 이내의 오차를 보였고, Coarse-grained 방법을 통한 입자 수 감소로 최소 13배 증가된 해석 속도를 보였다. 이를 통해 본 연구에서 제시된 모델이 실제 자연 지형에서의 적용가능성을 확인할 수 있었다.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.273-283
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• 2020

Quantitative forecasting of groundwater levels for the assessment of groundwater variation and vulnerability is very important. To achieve this purpose, various time series analysis and machine learning techniques have been used. In this study, we developed a prediction model based on LSTM (Long short term memory), one of the artificial neural network (ANN) algorithms, for predicting the daily groundwater level of 11 groundwater wells in Hankyung-myeon, Jeju Island. In general, the groundwater level in Jeju Island is highly autocorrelated with tides and reflected the effects of precipitation. In order to construct an input and output variables based on the characteristics of addressing data, the precipitation data of the corresponding period was added to the groundwater level data. The LSTM neural network was trained using the initial 365-day data showing the four seasons and the remaining data were used for verification to evaluate the fitness of the predictive model. The model was developed using Keras, a Python-based deep learning framework, and the NVIDIA CUDA architecture was implemented to enhance the learning speed. As a result of learning and verifying the groundwater level variation using the LSTM neural network, the coefficient of determination (R²) was 0.98 on average, indicating that the predictive model developed was very accurate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.374-383
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• 2020

This study verified the difference in the influence on the value principles held by the consumers while examining the influence of the characteristics of the online shopping mall on the purchase intent by using a TAM2 model. First, the characteristics of online shopping malls were proven to have a positive effect on the perceived ease of use and perceived utility. Second, a look at the effect of the online shopping mall characteristics on the emotional response shows that only the system quality and product quality variables had a positive effect on the emotional response. Third, the perceived ease of use, perceived utility and emotional response of online shopping mall users had a positive effect on their perceived value. Fourth, multi-group analysis was conducted to examine the difference between utilitarian goods and hedonic goods by categorizing what was purchased at online shopping malls. The results showed differences between the groups. This study is attempted to investigate various influencing factors on consumers' intention to revisit online shopping malls. In addition, the author also attempted to understand the behavior of online shopping mall visitors by dealing with more than the technical attributes and emotional aspects of shopping malls.

• Information Systems Review
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• v.19 no.3
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• pp.1-21
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• 2017

The Internet of Things (IoT) analysis aims to verify the technical characteristics, performance expectations, and adoption intentions of IoT. This work refers to IoT data from foreign and domestic publications and websites as well as aims to benefit related organizations by referring to reports from agencies. The literature review summarizes the relevant theories and background of the unified theory of acceptance and use of technology. The SPSS 22.0 software and structural equation models (smart PLS 2.0) are used in the data analysis. Technical statistics analysis, reliability analysis, validity analysis, structural equation models, and statistical methods are employed to test the research hypotheses, that is, the technical characteristics of IoT will have positive effects on its performance expectations. This study introduces the characteristics and expected performance of IoT to present relevant IoT guidelines for companies that aim to adopt such technology.

• Journal of the Korea Computer Graphics Society
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• v.26 no.3
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• pp.49-59
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• 2020

In this paper, we propose a speech animation synthesis specialized in Korean through a rule-based co-articulation model. Speech animation has been widely used in the cultural industry, such as movies, animations, and games that require natural and realistic motion. Because the technique for audio driven speech animation has been mainly developed for English, however, the animation results for domestic content are often visually very unnatural. For example, dubbing of a voice actor is played with no mouth motion at all or with an unsynchronized looping of simple mouth shapes at best. Although there are language-independent speech animation models, which are not specialized in Korean, they are yet to ensure the quality to be utilized in a domestic content production. Therefore, we propose a natural speech animation synthesis method that reflects the linguistic characteristics of Korean driven by an input audio and text. Reflecting the features that vowels mostly determine the mouth shape in Korean, a coarticulation model separating lips and the tongue has been defined to solve the previous problem of lip distortion and occasional missing of some phoneme characteristics. Our model also reflects the differences in prosodic features for improved dynamics in speech animation. Through user studies, we verify that the proposed model can synthesize natural speech animation.