• Earthquakes and Structures
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• v.9 no.6
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• pp.1153-1179
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• 2015

This paper focuses on presenting modeling considerations and insight into the performance of typical straight, curved, and skewed box-girder bridges in California which form the bulk of the bridge inventory in the state. Three case study bridges are chosen: Meloland Road Overpass, Northwest Connector of Interstate 10/215 Interchange, and Painter Street Overpass, having straight, curved, and skewed superstructures, respectively. The efficacy of nonlinear dynamic analysis is established by comparing the response from analytical models to the recorded strong motion data. Finally insights are provided on the component behavioral characteristics and shift in vulnerability for each of the bridge types considered.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.961-968
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• 2018

Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.

• Computers and Concrete
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• v.31 no.5
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• pp.405-417
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• 2023

The submerged floating tunnel (SFT) is tethered by mooring lines anchored to the seabed, therefore, the structural integrity of the anchor should be sensitively managed. Despite their importance, reaction forces cannot be simply measured by attaching sensors or load cells because of the structural and environmental characteristics of the submerged structure. Therefore, we propose an effective method for estimating the reaction forces at the seabed anchor of a submerged floating tunnel using a structural pattern model. First, a structural pattern model is established to use the correlation between tunnel motion and anchor reactions via a deep learning algorithm. Once the pattern model is established, it is directly used to estimate the reaction forces by inputting the tunnel motion data, which can be directly measured inside the tunnel. Because the sequential characteristics of responses in the time domain should be considered, the long short-term memory (LSTM) algorithm is mainly used to recognize structural behavioral patterns. Using hydrodynamics-based simulations, big data on the structural behavior of the SFT under various waves were generated, and the prepared datasets were used to validate the proposed method. The simulation-based validation results clearly show that the proposed method can precisely estimate time-series reactions using only acceleration data. In addition to real-time structural health monitoring, the proposed method can be useful for forensics when an unexpected accident or failure is related to the seabed anchors of the SFT.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.23-34
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• 2023

Wearable technology for military applications has received considerable attention as a means of personal status check and monitoring. Among many, an implementation to recognize specific motion states of a human is promising in that allows active management of troops by immediately collecting the operational status and movement status of individual soldiers. In this study, as an extension of military wearable application research, a new ankle wearable device is proposed that can glean the information of a soldier on the battlefield on which action he/she takes in which environment. Presuming a virtual situation, the soldier's upper limbs are easily exposed to uncertainties about circumstances. Therefore, a sensing module is attached to the ankle of the soldier that may always interact with the ground. The obtained data comprises 3-axis accelerations and 3-axis rotational velocities, which cannot be interpreted by hand-made algorithms. In this study, to discern the behavioral characteristics of a human using these dynamic data, a data-driven model is introduced; four features extracted from sliced data (minimum, maximum, mean, and standard deviation) are utilized as an input of the model to learn and classify eight primary military movements (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). As a result, the proposed device could recognize a movement status of a solider with 95.16% accuracy in an arbitrary test situation. This research is meaningful since an effective way of motion recognition has been introduced that can be furtherly extended to various military applications by incorporating wearable technology and artificial intelligence.

• Journal of the Earthquake Engineering Society of Korea
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• v.2 no.2
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• pp.87-94
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• 1998

Behavioral characteristics of shallow circular arches with dynamic loading and different end conditions are analysed. Geometric nonlinearity is modelled using Lagrangian description of the motion. The finite element analysis procedure is used to solve the dynamic equation of motion, and the Newmark method is adopted in the approximation of time integration. The behavior of arches is analysed using the buckling criterion and non-dimensional time, load and shape parameters which Humphreys suggested. But a new deflection-ratio formula including the effect of horizontal displacement plus vertical displacement is presented to apply for the non-symmetric buckling problems. Through the model analysis, it's confirmed that fix-ended arches have higher buckling stability than hinge-ended arches, and arches with the same shape parameter have the same deflection ratio at the same time parameter when loaded with the same parametric load.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.207-215
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• 2013

In this paper, we address the challenging computer vision problem of obtaining a reliable facial expression analysis from a naturally interacting person. We propose a system that combines a 3D generic face model, 3D head tracking, and 2D tracker to track facial landmarks and recognize expressions. First, we extract facial landmarks from a neutral frontal face, and then we deform a 3D generic face to fit the input face. Next, we use our real-time 3D head tracking module to track a person's head in 3D and predict facial landmark positions in 2D using the projection from the updated 3D face model. Finally, we use tracked 2D landmarks to update the 3D landmarks. This integrated tracking loop enables efficient tracking of the non-rigid parts of a face in the presence of large 3D head motion. We conducted experiments for facial expression recognition using both framebased and sequence-based approaches. Our method provides a 75.9% recognition rate in 8 subjects with 7 key expressions. Our approach provides a considerable step forward toward new applications including human-computer interactions, behavioral science, robotics, and game applications.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1887-1895
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• 2013

In this study, physical experiments were performed in a two-dimensional wave flume to investigate the hydraulic and structural performance of a SFT model. The experiments were made by generating regular waves of different heights and periods under various conditions of buoyancy to weight ratio (BWR) and water depth as well. Through the analysis of the experimental data, it was clarified that the sway and heave motions of the tunnel body linearly increased with wave height and period. In contrast, the roll motion was rather insignificant unless wave height and period were comparatively large as the design wave. Similarly proportional relationship with respect to wave height and period was obtained in case of the maximum tensile force acting on the tension legs and the wave loads on the tunnel body. Regarding the change of water depth or BWR conditions, generally decreasing trend was obtained according to increase of water depth but decrease of BWR for both of the magnitudes of structural behaviors or wave loadings on the SFT structure.