• Smart Structures and Systems
• /
• v.6 no.4
• /
• pp.349-362
• /
• 2010

Ultrasonic Guided Waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges and high sensitivity to small flaws. This paper describes a SHM method based on UGWs, discrete wavelet transform (DWT), and principal component analysis (PCA) able to detect and quantify the onset and propagation of fatigue cracks in structural waveguides. The method combines the advantages of guided wave signals processed through the DWT with the outcomes of selecting defect-sensitive features to perform a multivariate diagnosis of damage. This diagnosis is based on the PCA. The framework presented in this paper is applied to the detection of fatigue cracks in a steel beam. The probing hardware consists of a PXI platform that controls the generation and measurement of the ultrasonic signals by means of piezoelectric transducers made of Lead Zirconate Titanate. Although the approach is demonstrated in a beam test, it is argued that the proposed method is general and applicable to any structure that can sustain the propagation of UGWs.

• Korean Journal of Construction Engineering and Management
• /
• v.12 no.1
• /
• pp.85-96
• /
• 2011

The access monitoring and control system of vehicles involved in construction logistics has been evolved from paper-based through bar code-based and to RFID-based management with pursuing automatic data collection and management. However, existing management methods have a limit that they still need manpower allocation for access control of vehicles. Therefore this research has proposed an framework that includes devices and an information system for effective and efficient data collection for access control of vehicles for construction logistics. And the proposed framework has been verified through a laboratory test using a prototype system developed in this research. It is expected that the installation methods of RFID antenna and tag for the framework could be applied to not only the access control of construction site but also various RFID applications at construction sites.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.21 no.4
• /
• pp.75-86
• /
• 2018

This research was thereby made to study and analysis ecological, landscape, and stability qualities of roadside cut Slopes in expressways and national highways that went through revegetation works. Also, evaluation items and framework for integrated assessment of plant structure and restored state for the maintenance were suggested. Following is the summary of the result. firstly, for stabilization of introduced native plant species on roadside cut slops, assessment on the post-project environmental management through long-term monitoring and maintenance works must be made. It signifies a form of authentic recovery and restoration by the native plants. second, current evaluation framework on the test beds is well managed with clear evaluation standards and table while its method of assessing the post management with only test bed results lacks conformity with this study site. Newly developed evaluation framework on the post construction sites is estimated to be used as assessment standards on any roadside construction sites. Third, after site investigation distinction was observed among different revegetating construction types in the long-term perspective. Due to the different duration time of vegetation state between seed-spray measures(degraded in time) and layer-spray measure(maintained), the use of coarse straw-mat mulching work or Coir net was suggested in long term maintenance of cut slopes. forth, segmentation of post environmental assessment is organized into three large categories of "ecological", "stabile", and "landscape" qualities regarding post restoration quality and stability of slope through native plants with which categories marks 50, 30, 20 points of rates. fifth, components of the post environmental assessment were segmented in twelve categories driving results from former experimental construction and newly focused items on site. In the future, it is possible to propose a customized assessment method considering the location and location of construction work if the research on the application of post-environment assessment methods for road construction surface recording is conducted systematically.

• Smart Structures and Systems
• /
• v.24 no.6
• /
• pp.709-721
• /
• 2019

This paper investigates the framework of vision-based dense displacement and strain measurement of miter gates with the approach for the quantitative evaluation of the expected performance. The proposed framework consists of the following steps: (i) Estimation of 3D displacement and strain from images before and after deformation (water-fill event), (ii) evaluation of the expected performance of the measurement, and (iii) selection of measurement setting with the highest expected accuracy. The framework first estimates the full-field optical flow between the images before and after water-fill event, and project the flow to the finite element (FE) model to estimate the 3D displacement and strain. Then, the expected displacement/strain estimation accuracy is evaluated at each node/element of the FE model. Finally, methods and measurement settings with the highest expected accuracy are selected to achieve the best results from the field measurement. A physics-based graphics model (PBGM) of miter gates of the Greenup Lock and Dam with the updated texturing step is used to simulate the vision-based measurements in a photo-realistic environment and evaluate the expected performance of different measurement plans (camera properties, camera placement, post-processing algorithms). The framework investigated in this paper can be used to analyze and optimize the performance of the measurement with different camera placement and post-processing steps prior to the field test.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.3
• /
• pp.879-894
• /
• 2016

In micro-fluid systems, fluids are injected into extremely narrow polymer channels in small amounts such as micro-, nano-, or pico-liter scales. These channels themselves are embedded on tiny chips. Various specialized structures in the chips including pumps, valves, and channels allow the chips to accept different types of fluids to be entered the channel and along with flowing through the channels, exert their effects in the framework of different reactions. The chips are generally crystal, silicon, or elastomer in texture. These highly organized structures are equipped with discharging channels through which products as well as wastes of the reactions are secreted out. A particular advantage regarding the use of fluids in micro-scales over macro-scales lies in the fact that these fluids are much better processed in the chips when they applied as micro-scales. When the laboratory is miniaturized as a microchip and solutions are injected on a micro-scale, this combination makes a specialized construction referred to as "lab-on-chip". Taken together, micro-fluids are among the novel technologies which further than declining the costs; enhancing the test repeatability, sensitivity, accuracy, and speed; are emerged as widespread technology in laboratory diagnosis. They can be utilized for monitoring a wide spectrum of biological disorders including different types of cancers. When these microchips are used for cancer monitoring, circulatory tumor cells play a fundamental role.

• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.181-193
• /
• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Economic and Environmental Geology
• /
• v.24 no.3
• /
• pp.309-318
• /
• 1991

Analysis for landslides was studied in framework of Chungju dam right abutment, 6.5km northeast of Chungju city. $5.5{\times}10^6m^3$ landslide materials were excavated during dam construction for safety of the Chungju dam. Geology of study area is composed mainly of meta sediments such as dolomitic limestone, quartzite and schist which are dipping toward the Nam Han river. Scanline survey of discontinuities was performed for slope stability, resistivity exploration was performed for the evaluation of potential failure plane, and direct shear strength test of rocks and soils was performed for the effect on landslide. Monitoring systems of tiltmeter, tensiometer, ground water observation hole and level monument were installed during dam construction and interpreted for the evaluation of slope instability. Kinematic solution of the geological structure and evaluation using safety factor for slope may prove the failure of the slope.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.9
• /
• pp.4089-4094
• /
• 2015

The purpose of the research was to determine the effect of home care service on the quality of life in patients with gynecological cancer. This randomized case control study was carried out in a womans hospital between September 2011 and February 2012. Women undergoing gynecological cancer treatment were separated into intervention and control groups, of 35 patients each. The intervention group was provided with nursing care service through hospital and home visits ($1^{st}$, $12^{th}$ weeks) within the framework of a specifically developed nursing care plan. The control group was monitored without any intervention through the hospital routine protocols ($1^{st}$, $12^{th}$ weeks). Data were collected using An Interview Form, Home Visit Monitoring Form and Quality of Life Scale/Cancer Survivors. Effects of home care service on the quality of life in gynecological cancer patients were investigated using chi-square tests, McNemar's test, independent t-test and ANOVA. This study found that the intervention group receiving home care service had a moderately high quality of life (average mean: $6.01{\pm}0.64$), while the control group had comparatively lower quality (average mean: $4.35{\pm}0.79$) within the 12 week post-discharge period (p<0.05). This study found home care services to be efficient in improving the quality of life in patients with gynecological cancer.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.16 no.2
• /
• pp.1-11
• /
• 2008

Increasing demand for improved reliability and survivability of mission-critical systems is driving the development of health monitoring and Automated Contingency Management (ACM) systems. An ACM system is expected to adapt autonomously to fault conditions with the goal of still achieving mission objectives by allowing some degradation in system performance within permissible limits. ACM performance depends on supporting technologies like sensors and anomaly detection, diagnostic/prognostic and reasoning algorithms. This paper presents the development of a generic prototype test bench software framework for developing and validating ACM systems for advanced propulsion systems called the Propulsion ACM (PACM) Test Bench. The architecture has been implemented for a Monopropellant Propulsion System (MPS) to demonstrate the validity of the approach. A Simulink model of the MPS has been developed along with a fault injection module. It has been shown that the ACM system is capable of mitigating the failures by searching for an optimal strategy. Furthermore, the concepts of Validation and Verification (V&V) of such systems are introduced with relevant examples.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.5
• /
• pp.1197-1207
• /
• 2018

PowerShell is command line shell and scripting language, built on the .NET framework, and it has several advantages as an attack tool, including built-in support for Windows, easy code concealment and persistence, and various pen-test frameworks. Accordingly, malwares using PowerShell are increasing rapidly, however, there is a limit to cope with the conventional malware detection technique. In this paper, we propose an improved monitoring method to observe commands executed in the PowerShell and a deep learning based malware classification model that extract features from commands using Convolutional Neural Network(CNN) and send them to Recurrent Neural Network(RNN) according to the order of execution. As a result of testing the proposed model with 5-fold cross validation using 1,916 PowerShell-based malwares collected at malware sharing site and 38,148 benign scripts disclosed by an obfuscation detection study, it shows that the model effectively detects malwares with about 97% True Positive Rate(TPR) and 1% False Positive Rate(FPR).