• Journal of Korean Association for Spatial Structures
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• v.7 no.3 s.25
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• pp.49-55
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• 2007

In this paper, always monitoring system of fiber Bragg Crating(FBG)Sensor is described and FBGs are well suited for measuring the movement in the part of the spatial structure(for example, cable, membrane and so on)under the pressure conditions. In order to measure the movement of long span structure, we need the measurable equipment that takes in many spots to measure. In the result of experiment, the fiber sensors showed good response to the pressure conditions. Therefore, We could calculate the movement of spatial structure and be possible health monitoring of the spatial structure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.169-176
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• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.940-944
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• 2014

In this research, we designed representative motion patterns that possibly occurred in sleep situation and evaluated the feasibility of the smartphone based movement recording technique. For this, we designed 7 motions such as posture change, head movement, arm movement (vertical, horizontal), leg movement and hand movement (flipping, folding). Movement was recorded by using the smartphone and the actimetry device simultaneously for comparing the feasibility of smartphone based recording. As a result of experiment, we found that the smartphone based movement recording well reflects the body movement, however, it shows the limitation in recording the small local movement such as hand motion compared with the reference actimetry device, Actiwatch.

• Applied Biological Chemistry
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• v.41 no.8
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• pp.583-586
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• 1998

Porous ceramic cups are used for monitoring ion concentration in soil solutions in various time course and depth. A soil solution sampler was constructed in laboratory by inserting pliable perfluoroalkoxy(PFA) tubings into porous cup through holes in PVC rod segment which plugged top opening of the porous cup. The system was installed in drip irrigated soil in a vertical position, and nitrogen movement below the drip basin was monitored. To collect soil solution, vacuum in the cup was applied with a hand vacuum pump. The samples obtained were sufficient enough to run quantitative analyses for a number of chemicals. Nitrogen transformation and movement could be well defined, and the system seemed to be relevant to the other soil solution samplers in monitoring chemical movement in soil. Although this system has general deficiencies found in the other samplers using ceramic cup, it could be easily constructed at a low cost. Since the tubing was pliable, the cups could be installed in horizontal position, and this allows installations of the cups at more precise depth increments and also more precise samplings of soil solution at each depth.

• Journal of the Korean Geophysical Society
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• v.7 no.4
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• pp.325-330
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• 2004

For the monitoring of structures, it is desirable for the measurement system to deliver equal precision in all components. When using GPS the accuracy, availability, reliability and integrity of the position solutions is very dependent on the number and geometric distribution of the available satellites. Therefore the positioning precision is not the same in all there component, and large variations (in positioning) precision can be expected during a 24-hour period. This situation becomes worse when the line-of-sight to GPS satellites becomes obstructed, such as in urban environments. Pseudolites can be sed to augment GPS and improve a geometrically weak satellite constellation. The use of pseudolites as supplement(s) of GPS for the movement measurement of bridges is demonstrated in this paper. It is shown that pseudollites can improve the vertical position components.

• Smart Structures and Systems
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• v.15 no.6
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• pp.1543-1567
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• 2015

In this study, a wireless crack sensor is developed for monitoring cracks propagating in two dimensions. This sensor is developed by incorporating a laser-based optical navigation sensor board (ADNS-9500) into a smart wireless platform (Imote2). To measure crack propagation, the Imote2 sends a signal to the ADNS-9500 to collect a sequence of images reflected from the concrete surface. These acquired images can be processed in the ADNS-9500 directly (the navigation mode) or sent to Imote2 for processing (the frame capture mode). The computed crack displacement can then be transmitted wirelessly to a base station. The design and the construction of this sensor are reported herein followed by some calibration tests on one prototype sensor. Test results show that the sensor can provide sub-millimeter accuracy under sinusoidal and step movement. Also, the two modes of operation offer complementary performance as the navigation mode is more accurate in tracking large amplitude and fast crack movement while the frame capture mode is more accurate for small and slow crack movement. These results illustrate the feasibility of developing such a crack sensor as well as point out directions of further research before its actual implementation.

• Structural Engineering and Mechanics
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• v.50 no.1
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• pp.105-119
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• 2014

This study presents a steel container crane movement analysis and assessment based on structural health monitoring (SHM). The accelerometers are used to monitor the dynamic crane behavior and a 3-D finite element model (FEM) was designed to express the static displacement of the crane under the different load cases. The multi-input single-output nonlinear autoregressive neural network with external input (NNARX) model is used to identify the crane dynamic displacements. The FEM analysis and the identification model are used to investigate the safety and the vibration state of the crane in both time and frequency domains. Moreover, the SHM system is used based on the FEM analysis to assess the crane behavior. The analysis results indicate that: (1) the mean relative dynamic displacement can reveal the relative static movement of structures under environmental load; (2) the environmental load conditions clearly affect the crane deformations in different load cases; (3) the crane deformations are shown within the safe limits under different loads.

• Journal of Auto-vehicle Safety Association
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• v.13 no.1
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• pp.38-44
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• 2021

This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the real-world driving study, 52 drivers drove approximately 11.0 km of rural road (about 20 min), 7.9 km of urban road (about 25 min), and 20.8 km of highway (about 20 min). The results suggested that the appropriate number of blinks during the last 60 seconds was 4 times, and the head movement interval was 35 seconds. The results from drowsy driving data will be presented in another paper - part 2.

• Environmental Analysis Health and Toxicology
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• v.23 no.4
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• pp.231-245
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• 2008

Various methods for detecting changes in response behaviors of indicator specimens are presented for monitoring effects of toxic treatments. The movement patterns of individuals are quantitatively characterized by statistical (i.e., ANOVA, multivariate analysis) and computational (i.e., fractal dimension, Fourier transform) methods. Extraction of information in complex behavioral data is further illustrated by techniques in ecological informatics. Multi-Layer Perceptron and Self-Organizing Map are applied for detection and patterning of response behaviors of indicator specimens. The recent techniques of Wavelet analysis and line detection by Recurrent Self-Organizing Map are additionally discussed as an efficient tool for checking time-series movement data. Behavioral monitoring could be established as new methodology in integrative ecological assessment, tilling the gap between large-scale (e.g., community structure) and small-scale (e.g., molecular response) measurements.

• Korean Journal of Ecology and Environment
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• v.55 no.3
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• pp.251-257
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• 2022

Monitoring and assessing aquatic ecosystems using the behavior of organisms is essential for sustainable ecosystem management. Oligochaetes, which inhabit various freshwater ecosystems, are frequently used to evaluate the environmental conditions of freshwater ecosystems. Tubifex tubifex (Müller, 1774) (Oligochaeta, Tubificidae) is tolerant to organic pollution and has been used to evaluate the toxicity of toxicants, including heavy metals. We studied the behavioral responses of T. tubifex to three different copper concentrations (0.1, 0.5, and 1.0 mg L^-1). The specimens were exposed to copper in an observation cage containing 150 mL of dechlorinated water. Movement behavior (diameter, speed, acceleration, meander, and turning rate) was continuously observed for two hours before and after the copper treatments. After the treatments, the diameter shrank and showed rapid twisting movement under all the copper conditions. The turning rate had a positive correlation with meander and acceleration both before and after treatment at all three concentrations, whereas speed and meander had a negative correlation. Length and turning rate also showed a negative correlation. The correlation coefficient between speed and acceleration in the highest copper concentration changed from positive before treatment (r=0.64) to negative (r= -0.52) after treatment. Our results present the possibility of using behavioral parameters to detect copper contamination in freshwater ecosystems.