• Proceedings of the Korea Concrete Institute Conference
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• 1998.04a
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• pp.353-358
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• 1998

The strain localization is a discontinuous phenomenon that addresses the formation of jumps of the field variables across a singularity surface. It has become widely accepted that the localization may occur as the result of discontinuous bifurcation which corresponds to the loss of ellipticity of the governing differential equations for elasto-plastic continua. In this paper, condition for strain localization in concrete based on bifurcation theory is studied and localization tensor analysis algorithm is employed to determine the directions of localization of deformations in concrete. By applying a plasticity model of concrete into the algorithm, localization analysis is performed concrete under uniaxial tension, pure shear and uniaxial compression.

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.1-8
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• 2015

This paper proposes a study for accurate surface localization system using DWT(Discrete Wavelet Transform) and GPS/INS fusion algorithm. Because the propagation in the underwater is not passed by characteristics of the medium unlike the ground, the sonar system like DVL is used instead of GPS. But since these systems are installed on the seafloor and operated, a long time is required for installation and navigation systems are limited outside of the range area. And it is difficult to estimate position in a three-dimensional considering the depth in actual marine environment. In this paper, before the development of underwater localization system, precisely estimated position system is proposed in a two-dimensional by developing surface localization system using removing noise and disturbance with DWT and relatively inexpensive GPS and INS sensor.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.117-123
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• 2014

Localization is one of the essential tasks necessary to achieve autonomous navigation of a mobile robot. One such localization technique, Monte Carlo Localization (MCL) is often applied to a digital surface model. However, there are differences between range data from laser rangefinders and the data predicted using a map. In this study, commonly observed from air and ground (COAG) features and candidate selection based on the shape of sensor data are incorporated to improve localization accuracy. COAG features are used to classify points consistent with both the range sensor data and the predicted data, and the sample candidates are classified according to their shape constructed from sensor data. Comparisons of local tracking and global localization accuracy show the improved accuracy of the proposed method over conventional methods.

• Journal of Microbiology and Biotechnology
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• v.10 no.5
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• pp.714-720
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• 2000

Antigens of Herpes simplex virus type 1 (HSV-1) strain F were immunoblotted to identify the most immunodominant one, and the localization of this antigen was then studied using immunoelectron microscopy. The 67.8 kDa antigen appeared to be the most immunodominant one in a mouse model, and it showed randomly scattered and partially clustered distribution on the surface of the virion. The localization study was performed using immunogold with polyclonal anti-HSV-1 sera produced from BALB/c mice, and immunofluorescence demonstrated that the viral products in the HSV-2 infected Vero cells were distributed throughout the infected host cell, however, mainly on the surface of the host membrane.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.183-189
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• 2020

In emergency rescue situations, the localization accuracy of the rescue requestor is a very important factor in determining the success or failure of the rescue. Indoors where Global Navigation Satellite System (GNSS) is not operated, there is no choice but to use Wi-Fi or LTE signals. However, the performance of the current emergency rescue system utilizing those RF signals is exceedingly low. In this study, the effectiveness of the surface correlation technology using the accumulated signal pattern of RF signals was verified in relation to the emergency localization technology. To validate the proposed system, we configured and tested an emergency rescue scenario in multi-floors building. When the emergency rescue was requested, it was confirmed that the initial localization error was large owing to the short length of the accumulated signal pattern. However, the localization error decreased over time, which eventually led to the accurate location information being delivered to the rescuer.

• Journal of Ocean Engineering and Technology
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• v.19 no.2 s.63
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• pp.74-81
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• 2005

A 3-D localization method of an autonomous underwater vehicle (AUV) has been developed, which can solve the limitations oj the conventional localization, such as LBL or SBL that reduces the flexibility and availability of the AUV. The system is composed of a mother ship (small unmanned marine prober) on the surface of the water and an unmanned underwater vehicle in the water. The mother ship is equipped with a digital compass and a GPS for position information, and an extended Kalman filter is used for position estimation. For the localization of the AUV, we used only non-inertial sensors, such as a digital compass, a pressure sensor, a clinometer, and ultrasonic sensors. From the orientation and velocity information, a priori position of the AUV is estimated by applying the dead reckoning method. Based on the extended Kalman filter algorithm, a posteriori position of the AUV is, then, updated by using the distance between the AUV and a mother ship on the surface of the water, together with the depth information from the pressure sensor.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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• pp.130-135
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• 2004

This paper presents a 3-D localization of an autonomous underwater vehicle(AUV). Conventional methods of localization, such as LBL or SBL, require additional beacon systems, which reduces the flexibility and availability of the AUV We use a digital compass, a pressure sensor, a clinometer and ultrasonic sensors for localization. From the orientation and velocity information, a priori position of the AUV is estimated based on the dead reckoning. With the aid of extended Kalman filter algorithm, a posteriori position of the AUV is estimated by using the distance between the AUV and a mother ship on the surface of the water together with the water depth information from the pressure sensor. Simulation results show the possibility of practical application of the method to autonomous navigation of the AUV.

• Smart Media Journal
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• v.12 no.9
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• pp.45-59
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• 2023

Weakly supervised object localization (WSOL) is a task of localizing an object in an image using only image-level labels. Previous studies have followed the conventional class activation mapping (CAM) pipeline. However, we reveal the current CAM approach suffers from problems which cause original CAM could not capture the complete defects features. This work utilizes a convolutional neural network (CNN) pretrained on image-level labels to generate class activation maps in a multi-scale manner to highlight discriminative regions. Additionally, a vision transformer (ViT) pretrained was treated to produce multi-head attention maps as an auxiliary detector. By integrating the CNN-based CAMs and attention maps, our approach localizes defective regions without requiring bounding box or pixel-level supervision during training. We evaluate our approach on a dataset of apple images with only image-level labels of defect categories. Experiments demonstrate our proposed method aligns with several Object Detection models performance, hold a promise for improving localization.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.747-752
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• 1998

Ultrasonic sensors have been widely used to recognize the working environment for a mobile robot. However, their intrinsic problems, such as specular reflection, wide beam angle, and slow propagation velocity, require an excessive number of sensors to be integrated for achieving the sensing goal. This paper proposes a new measurement scheme which uses only two sets of ultrasonic sensors to determine the location and the type of a target surface. By measuring the time difference between the returned signals from the target surface, which are generated by two transmitters with 1 ㎳ difference, it classifies the type and determines the size of the target surface. Since the proposed sensor system uses only two sets of ultrasonic sensors to recognize and localize the target surface, it significantly simplifies the sensing system and reduces the signal processing time so that the working environment can be recognized in real time.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.443-451
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• 2020

A futuristic locomotion system called Hyperloop is projected for driving at ulta-high speed, levitated in the tube. In hyperloop localization of pods on the linear synchronous motor is essential for pod driving. precision localization is required for acceleration and deceleration of pods driving at speed above 1,000km/h, and also required for adjusting the pod speed driving at this very-high speed to maintain inter-vehicle distance. In this work, a new scale of localization is challenged by modified laser surface velocimeter. In acceleration the speed of a virtual pod is calculated along its displacement measured by laser reflection. Under the requirement of precise localization of the pod driving at ultra-high speed, a displacement measurement device, which detects the difference in reflections from tiles passing by the pod, is developed and evaluated through performance test. Tests of pod speeds below 500km/h have showed exact localization results of the precision in centimeters, and tests of pod speeds above 500km/h have showed localization with very low error rates under 0.1%. For the measurement above 500km/h, future works would pursue the error rate converges to zero.