• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Journal of Institute of Convergence Technology
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• v.1 no.2
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• pp.1-5
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• 2011

It is known that as many as 15-20 in 10,000 children are diagnosed with autistic spectrum disorder. A framework of the treatment system for children with autism using affective computing technologies was proposed by Chung and Yoon. In this paper, a prototype for the framework is proposed. It consists of emotion stimulating module, multi-modal bio-signal sensing module, treatment module using virtual reality, and emotion recognition module. Primitive experiments on emotion recognition show the usefulness of the proposed system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11a
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• pp.459-464
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• 2001

Vibration control of a plate using an optical fiber sensor and a PZT actuator is considered in this study. An aluminum plate with attached Extrinsic Fabry-Perot Interferometer (EFPI) and PZT actuator is prepared for experimental investigation. Vibration level of EFPI that can represent the mechanical strain without severe distortion is validated by forced vibration experiment. A numerical model of the plate is constructed based on the experimentally obtained frequency responses, and an optimal controller is designed for the multi-modal vibration suppression. It is found that the vibration level of the first three modes can be greatly reduced. The effect of low-pass filtering used to eliminate high frequency noise on the stability and control performance is also considered.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.423-438
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• 2010

Wireless smart sensors enable new approaches to improve structural health monitoring (SHM) practices through the use of distributed data processing. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While much of the technology associated with smart sensors has been available for nearly a decade, there have been limited numbers of fulls-cale implementations due to the lack of critical hardware and software elements. This research develops a flexible wireless smart sensor framework for full-scale, autonomous SHM that integrates the necessary software and hardware while addressing key implementation requirements. The Imote2 smart sensor platform is employed, providing the computation and communication resources that support demanding sensor network applications such as SHM of civil infrastructure. A multi-metric Imote2 sensor board with onboard signal processing specifically designed for SHM applications has been designed and validated. The framework software is based on a service-oriented architecture that is modular, reusable and extensible, thus allowing engineers to more readily realize the potential of smart sensor technology. Flexible network management software combines a sleep/wake cycle for enhanced power efficiency with threshold detection for triggering network wide operations such as synchronized sensing or decentralized modal analysis. The framework developed in this research has been validated on a full-scale a cable-stayed bridge in South Korea.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.109-114
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• 2024

The bio-sensing properties of TE and TM guided modes in the coupled plasmon-waveguide resonance (PWR) configuration are investigated. The modal transmission-line theory (MTLT) is used for numerical analysis. The proposed PWR bio-sensor is composed of multi-layered configuration with N pairs of MgF2-Si3N4 layers to enhance the sensitivity of a conventional Ag-based surface plasmon resonance bio-sensor. The angular sensitivity of bio-sensor is numerically analyzed for a wide range of biological solutions (refractive index 1.33~1.37). Furthermore, the availability of sensor to detect cancer cells and blood plasma concentration is evaluated. Finally, the results indicate that the proposed bio-sensor is capable efficiently to detect various kinds of cancer cells and different glucose concentrations in urine.