• Proceedings of the Korean Geotechical Society Conference
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• 1991.10a
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• pp.108-122
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• 1991

For the tunnel pattern of PD-3, a numerical analysis using the FEM program, MrSoil, was conducted with given geotechnical properties of surrounding rockmasses to verify the analysis results by comparing with other programs. The analyzed domain was extended to the far enough distance from the excavation surface to avoid the restrained effect by the boundary condition, and the construction sequence was employed in the analysis as calculation steps to simulate the time dependent 3 dimentional behavior of surrounding ground due to tunneling. Maximum 35 mm of the tunnel crown settlement and about 13 mm of the surface settlement were computed and the amount of settlement may not give any structural damage on the concrete structures on the ground surface. The shotcrete stress of 84 kg/cm2 and the rockbolt axial force of 9 ton as a maximum are within the allowable limit. The plastic zone was restricted near the excavation surface, but forepoling around the crown may be required to prevent rock falling. It is believed that the tunnel is designed reasonablely from the economical and safety points of view.

• Journal of KIISE
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• v.44 no.6
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• pp.607-612
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• 2017

This paper presents an attempt to apply Deep Learning technology to solve the problem of forecasting floods in urban areas. We employ Recurrent Neural Networks (RNNs), which are suitable for analyzing time series data, to learn observed data of river water and to predict the water level. To test the model, we use water observation data of a station in the Trinity river, Texas, the U.S., with data from 2013 to 2015 for training and data in 2016 for testing. Input of the neural networks is a 16-record-length sequence of 15-minute-interval time-series data, and output is the predicted value of the water level at the next 30 minutes and 60 minutes. In the experiment, we compare three Deep Learning models including standard RNN, RNN trained with Back Propagation Through Time (RNN-BPTT), and Long Short-Term Memory (LSTM). The prediction quality of LSTM can obtain Nash Efficiency exceeding 0.98, while the standard RNN and RNN-BPTT also provide very high accuracy.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.6
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• pp.231-236
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• 2014

The transit time of contrast agents and the parameters of time-intensity curves in ultrasonography are important factors to diagnose various diseases of a digestive organ. We have implemented an automatic parametric imaging method to overcome the difficulty of the diagnosis by naked eyes. However, the micro-bubble noise and the respiratory motions may degrade the reliability of the parameter images. In this paper, we introduce an optimization technique based on MRF(Markov Random Field) model to enhance the quality of the parameter images, and present an image tracking algorithm to compensate the image distortion by respiratory motions. A method to extract the respiration periods from the ultrasound image sequence has been developed. We have implemented the ROI(Region of Interest) tracking algorithm using the dynamic weights and a momentum factor based on these periods. An energy function is defined for the Gibbs sampler of the image enhancement method. Through the experiments using the data to diagnose liver lesions, we have shown that the proposed method improves the quality of the parametric images.

• Magazine of the Korea Concrete Institute
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• v.11 no.1
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• pp.231-242
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• 1999

This paper presents a numerical study on the flat plates in deep basements, subjected to out-of-plane floor load and in-plane compressive load due to soil and hydraulic lateral pressure. For nonlinear finite element analysis, a computer program addressing material and geometric nonlinearities is developed. The validity of the numerical model is established by comparison with existing experiments performed on plates simply supported on four edges. The flat plates to be studied are designed according to the Direct Design Method in Korean Building Code for Structural Concrete. Through numerical study on the effects of different load combinations and loading sequence, the load condition that governs the strength of the flat plates is determined. For the plates under the governing load condition, parametric studies are performed to investigate variations of the strength with reinforcement ratio, aspect ratio, concrete strength, and slenderness ratio. Based on the numerical results, the floor load magnification factor is proposed.

• Proceedings of the Korean Reliability Society Conference
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• 2000.04a
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• pp.239-246
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• 2000

This paper presents a new dynamic approach for assessing feasibility associated with the implementation of accident management strategies by the operators. This approach includes the combined use of both the concept of reliability physics and a dynamic event tree generation scheme. The reliability physics is based on the concept of a comparison between two competing variables, i.e., the requirement and the achievement parameter, while the dynamic event tree generation scheme on the continuous generation of the possible event sequences at every branch point up to the desired solution. This approach is applied to a cavity flooding strategy in a reference plant, which is to supply water into the reactor cavity using emergency fire systems in the station blackout sequence. The MAAP code and Latin Hypercube sampling technique are used to determine the uncertainty of the requirement parameter. It has been demonstrated that this combined methodology may contribute to assessing the success likelihood of the operator actions required during accidents and therefore to developing the accident management procedures.

• Composites Research
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• v.33 no.3
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• pp.140-146
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• 2020

The purpose of this paper is to examine the possibility of weight reduction by changing the partition panel of vehicle from an existing aluminum material to carbon fiber reinforced plastics. Three weaving methods (plain, twill and satin) were used in the manufacture of composite materials, and they were produced and tested to derive their material properties. The analysis model of composite partition panel for torsional conditions was developed and the structural stability and system stiffness were evaluated according to Tsai-Hill failure criteria. With design variables for fiber orientation angles and stacking sequence, evolutional optimal algorithm was performed and as the results, the optimal composite partition panel was designed. In addition, the structural analysis results for strength and specific stiffness were compared with aluminum partition panels and composite partition panels to verify the possibility of weight reduction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.121-132
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• 2005

In the formation of images in a camera, the exposure time is appropriately adjusted to obtain a good image. Hence for a successful alignment of a sequence of images to the same scene, it is required to compensate the different exposure times. If we have no knowledge regarding the exposure time, then we should develop an algorithm that can compensate an image with respect to a reference image without using any camera formation models. In this paper, an exposure compensation is performed by designing predictors based on the conditional expectation between the reference and input images. Further, an adaptive predictor design is conducted to manage the irregular exposure or histogram problem. In order to alleviate the blocking artifact and the overfitting problems in the adaptive scheme, a smoothing technique, which uses the pixels of the adjacent blocks, is proposed. We successfully conducted the exposure compensation using real images obtained from digital cameras and the transmission electron microscopy.

• Journal of the Korea Computer Graphics Society
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• v.15 no.4
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• pp.1-11
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• 2009

In this paper, we present a prism-based mesh culling method to improve effectiveness of continuous collision detection which is a major bottleneck in a simulation using polygonal mesh models. A prism is defined based on two matching triangles between a sequence of times m a polygonal model. In order to detect potential colliding set(PCS) of prism between two polygonal models in a unit time, we apply the visibility test based on the occlusion query to two sets of prisms which are defined from two polygonal models in a unit time. Moreover, we execute the narrow band culling based on SAT(Separating Axis Test) to define potential colliding prism pairs from PCS of prisms extracted as a result of the visibility test. In the SAT, we examine one axis to be perpendicular to a plane which divides a 3D space into two half spaces to include each prism. In the experiments, we applied the proposed culling method to pairs of polygonal models with the different size and compared the number of potential colliding prism pairs with the number of all possible prism pairs of two polygonal models. We also compared effectiveness and performance of the visibility test-based method with those of the SAT-based method as the second narrow band culling. In an experiment using two models to consist of 2916 and 2731 polygons, respectively, we got potential colliding prism pairs with 99 % of culling rate.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.29-40
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• 2022

This study uses the bidet 4D double diamond design process model to propose an improvement for "senior-oriented bidet product service design" that reflects the characteristics and needs of seniors. This study was based on the product service system concept. To this end, qualitative research on seniors was conducted to derive user value factors, and, based on this, product service ideas were discovered, and a prototype reflecting the usefulness review of a working-level expert group was proposed. First, a "smart application service for user-customized function setting guide" was proposed. A bidet incorporating Internet of Things technology and a smart phone are linked to provide an app service that automatically interprets user characteristic information and information on bidet products to guide customized functions. Second, a control panel and remote control user interface to "user-oriented product service interface" was proposed. In consideration of the usability and cognitive ability of seniors, a simple and intuitive physical user interface such as a configuration centered on main functions, button arrangement according to task sequence, and a touch screen remote control was presented. Third, we proposed a "bidet care service linked with products and health/hygiene care" that provides a wide range of services such as user health and hygiene, cleanliness, entertainment, etc., in addition to regular bidet product service. This study proposed a product-based service design methodology that can improve user experience and relationship quality by discovering and improving the pain points and needs of users (seniors) in the process of using bidet products (before, during, and after use).

• KIISE Transactions on Computing Practices
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• v.23 no.12
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• pp.698-702
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• 2017

Since the introduction of Deep Neural Networks to the Natural Language Processing field, two major approaches have been considered for modeling text. One method involved learning embeddings, i.e. the distributed representations containing abstract semantics of words or sentences, with the textual context. The other strategy consisted of composing the embeddings trained by the above to get embeddings of longer texts. However, most studies of the composition methods just adopt word embeddings without consideration of the optimal embedding unit and the optimal method of composition. In this paper, we conducted experiments to analyze the optimal embedding unit and the optimal composition method for modeling longer texts, such as documents. In addition, we suggest a new discourse-based composition to overcome the limitation of the sequential composition method on composing sentence embeddings.