• Journal of Korean Tunnelling and Underground Space Association
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• v.10 no.4
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• pp.349-360
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• 2008

In this paper, the modeling procedure of random field with an elasto-plastic finite element algorithm and probability of failure on closely-spaced tunnel were investigated. Local average subdivision (LAS) method which can generate discrete random variables fast and accurately as well as change the resolution in certain region was used. And correlated value allocating and weighted average method were suggested to implement geometrical characteristics of tunnel. After the probability of failure on the test problem was thoroughly investigated using random finite element method, the results were compared with the deterministic strength reduction factor method and single random variable method. Of particular importance in this work, is the conclusion that the probability of failure determined by simplified probabilistic analysis, in which spatial variability is ignored by assuming perfect correlation, can be estimated from the safety factor determined by strength reduction factor method. Also, single random variable method can lead to unconservative estimates of the probability of failure.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.1
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• pp.26-32
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• 2005

In this paper, the effect of various regression models is investigated on structural optimization using the central composite method. Three bar truss and the upper platform of a satellite are optimized using various regression models that are polynomial, exponential and log functions. Response surface method is non-gradient, semi-global, discrete and fast converging in optimization problem. Sampling points are extracted by the design of experiments using the central composite method. Response surface is generated using the various regression functions. Structural analysis for calculating constraints is executed to find static and dynamic responses. From this study, it is verified that the response surface method has advantage in optimum value and computation time in comparison to other optimization methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.55-62
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• 2005

This paper proposes a method to recognize a face using DCT/LDA where LDA is applied to DCT coefficients of an input face image. In the proposed method, SSS problem of LDA due to less number of training data than the size of feature space can be avoided by expressing an input image in low dimensional space using DCT coefficients. In terms of the recognition rate, both the proposed method and the PCA/LDA method have shown almost equal performance while the training time of the proposed method is much shorter than the other. This is because DCT has the fixed number of basis vectors while the property of energy compaction rate is similar to that of PCA. Although depending on the number of coefficients employed for the recognition, the experimental results show that the performance of the proposed method in terms of recognition rate is very comparable to PCA/LDA method and other DCT/LDA methods, and it can be trained 13,000 times faster than PCA/LDA method.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.93-103
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• 2023

The problem of reconstructing three-dimensional models of people and objects from color and depth images captured by low-cost RGB-D cameras has long been an active research area in computer graphics. Color and depth images captured by low-cost RGB-D cameras are represented as point clouds in three-dimensional space, which correspond to discrete values in a continuous three-dimensional space and require additional surface reconstruction compared to rendering using polygonal models. In this paper, we propose an effective ray-tracing based technique for visualizing point clouds rather than polygonal models. In particular, our method shows the possibility of an effective rendering method even in mobile environment which has limited performance due to processor heat and lack of battery.

• School Mathematics
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• v.16 no.1
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• pp.19-37
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• 2014

This study investigated the degree of understanding pre-service teachers' random variable concept, based on the attention and the importance for developing pre-service teachers' ability on statistical reasoning in statistics education. To accomplish this, the subject of this study was 70 pre-service teachers belonged to three universities respectively. The teachers were given to 7 tasks on random variable and requested to solve them in 40 minutes. The tasks consisted of three contents in large; 1) one was on the definition of random variables, 2) the other was on the understanding of random variables in different/diverse conditions, and 3) another was on problem solving relevant to random variable concept. The findings are as follows. First, while 20% of pre-service teachers understood the definition of random variable correctly, most teachers could not distinguish between random variable and variable or probability. Second, there was a significant difference in understanding random variables in different/diverse conditions. Namely, the degree of understanding on the continuous random variable was superior to that of discrete random variable and also the degree of understanding on the equal distribution was superior to that of unequality distribution. Third, three types of problems relevant to random variable concept dealt with in this study were finding a sample space and an elementary event, and finding a probability value. In result, the teachers responded to the problem on finding a probability value most correctly and on the contrary to this, they had the mot difficulty in solving the problem on finding a sample space.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.4
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• pp.261-269
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• 2019

This study investigates a method of designing pixel-type frequency selective surfaces(FSS) with flexibility while considering factors, such as polarization and incident angle. Among the various methods used to solve the discrete space problem when designing a pixel-type FSS, the binary particle swarm optimization(BPSO) algorithm is one of the most applicable techniques to determine the periodic structure pattern of an FSS. Therefore, a method of efficiently designing FSS with roll-off band pass characteristics using an improved BPSO algorithm is proposed. To solve the convergence problem in the fitness function design to induce particles in the desired solution, FSS with desired roll-off wave characteristics can be easily obtained by applying a fitness function using "slope" as an input parameter.

• Journal of Korean Association for Spatial Structures
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• v.23 no.2
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• pp.29-36
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• 2023

Reinforcement learning (RL) is widely applied to various engineering fields. Especially, RL has shown successful performance for control problems, such as vehicles, robotics, and active structural control system. However, little research on application of RL to optimal structural design has conducted to date. In this study, the possibility of application of RL to structural design of reinforced concrete (RC) beam was investigated. The example of RC beam structural design problem introduced in previous study was used for comparative study. Deep q-network (DQN) is a famous RL algorithm presenting good performance in the discrete action space and thus it was used in this study. The action of DQN agent is required to represent design variables of RC beam. However, the number of design variables of RC beam is too many to represent by the action of conventional DQN. To solve this problem, multi-agent DQN was used in this study. For more effective reinforcement learning process, DDQN (Double Q-Learning) that is an advanced version of a conventional DQN was employed. The multi-agent of DDQN was trained for optimal structural design of RC beam to satisfy American Concrete Institute (318) without any hand-labeled dataset. Five agents of DDQN provides actions for beam with, beam depth, main rebar size, number of main rebar, and shear stirrup size, respectively. Five agents of DDQN were trained for 10,000 episodes and the performance of the multi-agent of DDQN was evaluated with 100 test design cases. This study shows that the multi-agent DDQN algorithm can provide successfully structural design results of RC beam.

• Korean Journal of Cognitive Science
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• v.24 no.3
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• pp.271-300
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• 2013

Human and animals are born with an intuitive ability to determine approximate numerosity. This ability is termed approximate number sense (hereafter, number sense). Evolutionarily, number sense is thought to be an essential ability for hunting, gathering and survival. According to previous research, children with mathematical learning disability have impaired number sense. On the other hand, individuals with more accurate number sense have higher mathematical achievement. These results support the hypothesis that number sense provides a basis for the development of mathematical cognition. Recently, researchers have been examining whether number sense training can lead to enhancement in mathematical achievement and changes in brain activity in relation to mathematical problem solving. Numerosity which basically represents discontinuous quantity is expected to be closely related to continuous quantity such as representations of space and time. A theory of magnitude (ATOM) states that processing of number, space and time is based on a common magnitude system in the posterior parietal cortex, especially the intraparietal sulcus. The present paper introduces current literature and future directions for the study of the common magnitude system.

• Tunnel and Underground Space
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• v.15 no.2 s.55
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• pp.119-128
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• 2005

Although the evaluation of the mechanical properties and behavior of jointed rock masses is very important for the design of tunnel and underground openings, it has always been considered the most difficult problem. One of the difficulties in describing the rock mass behavior is the selection of the appropriate constitutive model. This limitation may be overcome with the progress in discrete element software such as PFC, which does not need the user to prescribe a constitutive model for rock mass. In this paper, a 30\;m\;\times\;30\;m\;\times\;30\;m m jointed rock mass of road tunnel site was analyzed. h discrete fracture network was developed from the joint geometry obtained from core logging and surface survey. Using the discontinuities geometry from the DFN model, PFC simulations were carried out, starting with the intact rock and systematically adding the joints and the stress-strain response was recorded for each case. With the stress-strain response curves, the mechanical properties of jointed rock masses were determined. As expected, the presence of joints had a pronounced effect on mechanical properties of the rock mass. More importantly, getting the mechanical response of the PFC model doesn't require a user specified constitutive model.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.5
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• pp.232-242
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• 2005

This paper concerns automatic hardware synthesis from data flow graph (DFG) specification for fast HW/SW cosynthesis. A node in BFG represents a coarse grain block such as FIR and DCT and a port in a block may consume multiple data samples per invocation, which distinguishes our approach from behavioral synthesis and complicates the problem. In the presented design methodology, a dataflow graph with specified algorithm can be mapped to various hardware structures according to the resource allocation and schedule information. This simplifies the management of the area/performance tradeoff in hardware design and widens the design space of hardware implementation of a dataflow graph compared with the previous approaches. Through experiments with some examples, the usefulness of the proposed technique is demonstrated.