• Smart Structures and Systems
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• v.17 no.3
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• pp.445-470
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• 2016

In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.281-286
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• 2009

The proposed technique uses cyclic frame structure, where three periods such as beacon period (BP), mesh contention access period (MCAP) and slotted period (SP) are in a data frame. This paper studies on a mechanism to allow communication nodes (6lowpan) in a PAN with different logical channel for global healthcare applications monitoring technology. The proposed super framework structure system has installed 6lowpan sensor nodes to communicate with each other. The basic idea is to time share logical channels to perform 6lowpan sensor node. The concept of 6lowpan sensor node and various biomedical sensors fixed on the patient BAN (Body Area Network) for monitoring health condition. In PAN (hospital area), has fixed gateways that received biomedical data from 6lowpan (patient). Each 6lowpan sensor node (patient) has IP-addresses that would be directly connected to the internet. With the help of IP-address service provider can recognize or analyze patient data from all over the globe by the internet service provider, with specific equipments i.e. cell phone, PDA, note book. The NS-2.33 result shows the performance of data transmission delay and data delivery ratio in the case of hop count in a PAN (Personal Area Networks).

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.45-53
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• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• 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.

• International Area Studies Review
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• v.21 no.1
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• pp.303-324
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• 2017

Current methods to evaluate the performance of ROK military contingents to UN missions unnecessarily raises the issues of relevance, validity and reliability. Thus, this article aims to suggest how the result based evaluation (RBE) model which is widely adopted in the UN field missions as well as the international development community would be modified and applied to peace operation of the ROK contingent. As a result of the study, the model presents a framework that integrates the planning process and monitoring and evaluation with a logical framework, which entails a cycle of assessment of pre-deployment planning, monitoring and phased evaluation, and post-deployment evaluation. Secondly, according to measurement of RBE benchmarks to the present ROK's monitoring and evaluation system, factors in an evaluation unit and a logical framework approach are unmet or partly met to the benchmarks. In addition, ex-post impact evaluation has been rarely performed. Finally, the policy recommendations for resolution of the aforementioned challenges as well as a joint evaluation unit, participated by experts in a civilian, public, and a military domain are proposed.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.1
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• pp.43-55
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• 2006

In this paper, we present a framework which is used to develop, modify, maintain and extend a control and monitoring software easily for any kind of automatic instruments. The proposed framework is composed of three XML documents (IID, MAP, CMIML) and two tools (Virtual Instrument Wizard, Generator). Interface information of behaviors and states of instrument is written on IID. Mapping information between the interface information in IID and API of a real instrument driver is written on MAP Final information of the control and monitoring software is written on CMIML, IID, MAP and CMIML are written by XML format to provide a common usage and platform independence of the proposed framework. Vl Wizard generates CMIML intermediate platform independent document using IID and existing CMIML, and Generator generates the source code of a control and monitoring software platform dependent code automatically using CMIML and MAP. The suggested framework provides an easy development and maintenance because it automatically generates a control and monitoring software in GUI environment and it also provides common usage and platform independence in virtue of using description document of XML format. Also, reusability can be increased by reusing platform independent software description document and not reusing platform dependent software code.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1074-1081
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• 2011

As robotics systems are becoming more complex there is the need to promote component based robot development, where systems can be constructed as the composition and integration of reusable building block. One of the most important challenges facing component based robot development is safeguarding against software component failures and malfunctions. The health monitoring of the robot software is most fundamental factors not only to manage system at runtime but also to analysis information of software component in design phase of the robot application. And also as a lot of monitoring events are occurred during the execution of the robot software components, a simple data treatment and efficient memory management method is required. In this paper, we propose an efficient events monitoring and data management method by modeling robot software component and monitoring factors based on robot software framework. The monitoring factors, such as component execution runtime exception, Input/Output data, execution time, checkpoint-rollback are deduced and the detail monitoring events are defined. Furthermore, we define event record and monitor record pool suitable for robot software components and propose a efficient data management method. To verify the effectiveness and usefulness of the proposed approach, a monitoring module and user interface has been implemented using OPRoS robot software framework. The proposed monitoring module can be used as monitoring tool to analysis the software components in robot design phase and plugged into self-healing system to monitor the system health status at runtime in robot systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1203-1206
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• 2012

본 논문은 다양한 기기로 구성된 분산 IT 환경에서 보다 신속한 장애 탐지 및 원인 파악을 위한 Monitoring framework을 제안한다. 제안된 Framework은 전통적인 Event Correlation 기법과 전통적 기법의 문제점 해결을 위한 Probing 기법을 혼용한(Hybrid) 것인데, 이를 통해 각각의 기법이 지닌 한계를 극복하고, 장애탐지 능력을 향상시킨다. 즉, Event Correlation 기법은 임계영역에서 장애 판별이 어려운 문제점이 있는데, 이러한 경우 장애 여부를 확신하기 위해 Probe station을 이용하여 Probe를 실행함으로써 장애 판단 능력을 향상시켰다. 또한 Probing 기법은 복잡한 분산 IT 환경에서 Probe Set를 구성하는 어려움이 있는데, 이를 회피하는데 도움을 준다. 본 논문에서는 Web 기반 애플리케이션에서 User-Session을 기반으로 추출한 Http Packet를 Probe set으로 이용하여 구현하였다.

• Smart Structures and Systems
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• v.32 no.3
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• pp.179-193
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• 2023

This study explores an alternative to the existing centralized process for data anomaly detection in modern Internet of Things (IoT)-based structural health monitoring (SHM) systems. An edge intelligence framework is proposed for the early detection and classification of various data anomalies facilitating quality enhancement of acquired data before transmitting to a central system. State-of-the-art deep neural network pruning techniques are investigated and compared aiming to significantly reduce the network size so that it can run efficiently on resource-constrained edge devices such as wireless smart sensors. Further, depthwise separable convolution (DSC) is invoked, the integration of which with advanced structural pruning methods exhibited superior compression capability. Last but not least, quantization-aware training (QAT) is adopted for faster processing and lower memory and power consumption. The proposed edge intelligence framework will eventually lead to reduced network overload and latency. This will enable intelligent self-adaptation strategies to be employed to timely deal with a faulty sensor, minimizing the wasteful use of power, memory, and other resources in wireless smart sensors, increasing efficiency, and reducing maintenance costs for modern smart SHM systems. This study presents a theoretical foundation for the proposed framework, the validation of which through actual field trials is a scope for future work.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.106-113
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• 2009

Recently, due to many industrial accidents at construction sites, a variety of researches for structural health monitoring (SHM) of buildings are progressing. For real site application of SHM, one of the advanced technologies has blown as wireless sensor networks (WSN). In this paper, we proposed WIVA(WSN Monitoring framework based on 3D Visualization and Augmented Reality in Mobile Devices) system that applies 3D visualization and AR technology to mobile devices with camera based on WSN in order to expand the extent of information can observe. Moreover, we performed experiments to validate effectiveness in 3D and AR mode that utilize WSN data based on IEEE 802.15.4. In real implementation scenario, we demonstrated a fire occurrence test in 3-story building miniature.