• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.124-131
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• 2015

In this paper, we proposed indoor positioning system using RSS(Received Signal Strength) positioning method and TSS(Transmission Signal Strength). The main point in the paper is to improve reliability of accuracy positioning with the area recognition algorithm and probabilistic algorithm, which can be effectively used indoor. In the test in 1-dimensional or 2-dimensional spaces, also we checked effective positioning system considered environment of propagation that is changed by reflection, refraction and multipath in according to space form. It is necessary to find place where urgent situation happen and quickly to respond the situation for patients or the weak. Therefore, we expect the positioning system proposed can apply to the field of traffic IT.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.152-159
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• 2010

Finding a head of a person in a scene is very important for taking a well composed picture by a robot photographer because it depends on the position of the head. So in this paper, we propose a robust head tracking algorithm using a hybrid of an omega shape tracker and local binary pattern (LBP) AdaBoost face detector for the robot photographer to take a fine picture automatically. Face detection algorithms have good performance in terms of finding frontal faces, but it is not the same for rotated faces. In addition, when the face is occluded by a hat or hands, it has a hard time finding the face. In order to solve this problem, the omega shape tracker based on active shape model (ASM) is presented. The omega shape tracker is robust to occlusion and illuminationchange. However, whenthe environment is dynamic,such as when people move fast and when there is a complex background, its performance is unsatisfactory. Therefore, a method combining the face detection algorithm and the omega shape tracker by probabilistic method using histograms of oriented gradient (HOG) descriptor is proposed in this paper, in order to robustly find human head. A robot photographer was also implemented to abide by the 'rule of thirds' and to take photos when people smile.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.612-628
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• 2020

This paper presents a new approach for detecting abnormal behaviors in complex surveillance scenes where anomalies are subtle and difficult to distinguish due to the intricate correlations among multiple objects' behaviors. Specifically, a cascaded probabilistic topic model was put forward for learning the spatial context of local behavior and the temporal context of global behavior in two different stages. In the first stage of topic modeling, unlike the existing approaches using either optical flows or complete trajectories, spatio-temporal correlations between the trajectory fragments in video clips were modeled by the latent Dirichlet allocation (LDA) topic model based on Markov random fields to obtain the spatial context of local behavior in each video clip. The local behavior topic categories were then obtained by exploiting the spectral clustering algorithm. Based on the construction of a dictionary through the process of local behavior topic clustering, the second phase of the LDA topic model learns the correlations of global behaviors and temporal context. In particular, an abnormal behavior recognition method was developed based on the learned spatio-temporal context of behaviors. The specific identification method adopts a top-down strategy and consists of two stages: anomaly recognition of video clip and anomalous behavior recognition within each video clip. Evaluation was performed using the validity of spatio-temporal context learning for local behavior topics and abnormal behavior recognition. Furthermore, the performance of the proposed approach in abnormal behavior recognition improved effectively and significantly in complex surveillance scenes.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.303-308
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• 2019

This study suggests a method for deriving earthquake response based on log-normal distribution in order to obtain realistic and reliable probability and statistical seismic response of structures. The development of three earthquake suites were presented, with a brief description of 2%, 10%, and 50% in 50 years probability of exceedance according the USGS Los Angeles probabilistic seismic hazard maps. In order to analyze the basic dynamic behavior, a Single-Degree-of-Freedom (SDOF) structure was selected and the seismic response spectrum representing the response of each natural period was plotted. Overall, the mean response values presented through the log-normal distribution is lower than the standard normal distribution. Thus, it is considered that the former method can be provided as the effective cost on performance-based seismic design more than the latter one.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.72-79
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• 2019

Autonomous locomotion has two essential functionalities: mapping builds and updates maps by uncertain position information and measured sensor inputs, and localization is to find the positional information with the inaccurate map and the sensor information. In addition, obstacle detection, avoidance, and path designs are necessarily required for autonomous locomotion by combining the probabilistic methods based on uncertain locations. The sensory inputs, which are measured by a metric-based scanner, have difficulties of distinguishing moving obstacles like humans from static objects like walls in given environments. This paper proposes the low resolution grid map combined with reinforcement learning, which is compared with the conventional recognition method for detecting static and moving objects to generate obstacle avoiding path. Finally, the proposed method is verified with experimental results.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.173-173
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• 2015

The flood water level in tidal river is determined by the joint effects of flood discharge and tidal water levels at downstream boundary. Due to the variable tidal boundary conditions, the evaluated design water levels associated with a certain flood event can be significantly different. To avoid determining of design water levels just by a certain tidal boundary condition and remove the influence of variability in boundary condition from the evaluation of design water levels, a probabilistic approach is considered in this study. This study focuses on the development of a method to evaluate the realistic design water levels in tidal river with taking into account the combined effects of river discharge and tidal level. The flood water levels are described by the joint probability of two driving forces, river discharge and tidal water levels. The developed method is applied to determine design water levels for the tidal reach of the Han River. An unsteady flow model is used to simulate the flow in the reach. To determine design water levels associated with a certain flood event, first, possible boundary conditions are obtained by sampling starting times of tidal level time series; then for each tidal boundary condition, corresponding peak water levels along the channel are computed; and finally, design water levels are determined by computing the expectations of the peak water levels. Two types of tides which are composed by different constituents are assumed (one is composed by $M_2$, and the other one is composed by $M_2$ and $M_2$) at downstream boundary, and two flood events with different maximum flood discharges are considered in this study. It is found that (a) the computed design water levels with two assumed tides have no significant difference for a certain flood event, though variability of peak water levels due to the tidal effect is considerably different; (b) tidal effect can reach to the Jamsil submerged weir and the effect is obvious in the downstream reach of the Singok submerged weir; (c) in the tidally affected reach, the variability of peak water levels due to the tidal effect is greater if the maximum flood discharge is smaller.

• Tunnel and Underground Space
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• v.31 no.1
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• pp.66-81
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• 2021

The effects of directional fracture tensor components and first invariant of fracture tensor on deformation moduli and shear moduli of fractured rock masses is analyzed based on regression analysis performed between 3-D fracture tensor parameters and deformability of DFN blocks. Using one or two deterministic joint sets, a total of 224 3-D discrete fracture network (DFN) cube blocks were generated with various configurations of deterministic density and probabilistic size distribution. The fracture tensor parameters were calculated for each generated DFN systems. Also, deformability moduli with respect to three perpendicular direction of the DFN cube blocks were estimated based on distinct element method. The larger the first invariant of fracture tensor, the smaller the values for the deformability moduli of the DFN blocks. These deformability properties present an asymptotic pattern above the certain threshold. It is found that power-law function describes the relationship between the directional deformability moduli and the corresponding fracture tensor components estimated in same direction.

• Structural Engineering and Mechanics
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• v.80 no.6
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• pp.645-655
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• 2021

Performance-based reliability analysis is a practical approach to investigate the seismic performance and stochastic nonlinear response of structures considering a random process. This is significant due to the uncertainties involved in every aspect of the analysis. Therefore, the present study aims to evaluate the performance-based reliability within a stochastic finite element (FE) framework for reinforced concrete (RC) shear walls that are considered as one of the most essential elements of structures. To accomplish this purpose, deterministic FE analyses are conducted for both squat and slender shear walls to validate numerical models through experimental results. The presented numerical analysis is performed by using the ABAQUS FE program. Afterwards, a random-effects investigation is carried out to consider the influence of different random variables on the lateral load-top displacement behavior of RC members. Using these results and through utilizing the Monte-Carlo simulation method, stochastic nonlinear analyses are also performed to generate random FE models based on input parameters and their probabilistic distributions. In order to evaluate the reliability of RC walls, failure probabilities and corresponding reliability indices are calculated at life safety and collapse prevention levels of performance as suggested by FEMA 356. Moreover, based on reliability indices, capacity reduction factors are determined subjected to shear for all specimens that are designed according to the ACI 318 Building Code. Obtained results show that the lateral load and the compressive strength of concrete have the highest effects on load-displacement responses compared to those of other random variables. It is also found that the probability of shear failure for the squat wall is slightly lower than that for slender walls. This implies that 𝛽 values are higher in a non-ductile mode of failure. Besides, the reliability of both squat and slender shear walls does not change significantly in the case of varying capacity reduction factors.

• Journal of the Korean Society of Safety
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• v.38 no.3
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• pp.102-109
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• 2023

Following the accident at Fukushima, the true impact of multi-unit accidents came to light. Accordingly, research related to multi-unit accident effect analysis, risk evaluation, and accident prevention/prevention technology has been conducted. Specific examples are mobile/fixed equipment such as multi-barrier accident coping strategy (MACST) and diverse and flexible coping strategies (FLEX), which have been introduced and installed in multi-units for preventing and mitigating multi-unit accidents. These strategies are useful for enhancing the safety of nuclear power plants (NPPs); however, a more efficient strategy is required in terms of the costs of physical and human resources. To effectively and efficiently mitigate an increase in multi-unit accidents, it is necessary to not only to utilize mobile/fixed equipment but to also use crosstie options with resources that already exist at NPPs. Therefore, we analyzed the current international and domestic status of crosstie systems technology and propose a method to evaluate feasibility alongside risk based on a multi-unit probabilistic safety assessment (PSA). To analyze the international and domestic status of crosstie systems technology, actual cases and related research were studied, and a list of potential crosstie safety resources was derived. Additionally, a case study was performed on crosstie cases of two systems within the assumed six units on-site under a multi-unit accident, and a multi-unit PSA-based risk evaluation method is proposed.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.161-171
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• 2010

Sensor Networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects forged reports into the network through compromised nodes. Such attacks by compromised sensors can cause not only false alarms but also the depletion of the finite amount of energy in a battery powered network. Ye et al. proposed the Statistical En-route Filtering scheme to overcome this threat. In statistical en-route filtering scheme, all the intermediate nodes perform verification as event reports created by center of stimulus node are forwarded to the base station. This paper applies a probabilistic verification method to the Static Statistical En-route Filtering for energy efficiency. It is expected that the farther from the base station an event source is, the higher energy efficiency is achieved.