• Smart Structures and Systems
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• v.15 no.1
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• pp.41-55
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• 2015

This study proposes a laser based impedance measurement system and impedance based pipe corrosion and bolt-loosening monitoring techniques under temperature variations. For impedance measurement, the laser based impedance measurement system is optimized and adopted in this paper. First, a modulated laser beam is radiated to a photodiode, converting the laser beam into an electric signal. Then, the electric signal is applied to a MFC transducer attached on a target structure for ultrasonic excitation. The corresponding impedance signals are measured, re-converted into a laser beam, and radiated back to the other photodiode located in a data interrogator. The transmitted impedance signals are treated with an outlier analysis using generalized extreme value (GEV) statistics to reliably signal off structural damage. Validation of the proposed technique is carried out to detect corrosion and bolt-loosening in lab-scale carbon steel elbow pipes under varying temperatures. It has been demonstrated that the proposed technique has a potential to be used for structural health monitoring (SHM) of pipe structures.

• Smart Structures and Systems
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• v.9 no.6
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• pp.489-504
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• 2012

For the safety of prestressed structures such as cable-stayed bridges and prestressed concrete bridges, it is very important to ensure the prestress force of cable or tendon. The loss of prestress force could significantly reduce load carrying capacity of the structure and even result in structural collapse. The objective of this study is to present a smart PZT-interface for wireless impedance-based prestress-loss monitoring in tendon-anchorage connection. Firstly, a smart PZT-interface is newly designed for sensitively monitoring of electro-mechanical impedance changes in tendon-anchorage subsystem. To analyze the effect of prestress force, an analytical model of tendon-anchorage is described regarding to the relationship between prestress force and structural parameters of the anchorage contact region. Based on the analytical model, an impedance-based method for monitoring of prestress-loss is conducted using the impedance-sensitive PZT-interface. Secondly, wireless impedance sensor node working on Imote2 platforms, which is interacted with the smart PZT-interface, is outlined. Finally, experiment on a lab-scale tendon-anchorage of a prestressed concrete girder is conducted to evaluate the performance of the smart PZT-interface along with the wireless impedance sensor node on prestress-loss detection. Frequency shift and cross correlation deviation of impedance signature are utilized to estimate impedance variation due to prestress-loss.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.689-709
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• 2010

In this paper, a low cost, low power but multifunctional wireless sensor node is presented for the impedance-based SHM using piezoelectric sensors. Firstly, a miniaturized impedance measuring chip device is utilized for low cost and low power structural excitation/sensing. Then, structural damage detection/sensor self-diagnosis algorithms are embedded on the on-board microcontroller. This sensor node uses the power harvested from the solar energy to measure and analyze the impedance data. Simultaneously it monitors temperature on the structure near the piezoelectric sensor and battery power consumption. The wireless sensor node is based on the TinyOS platform for operation, and users can take MATLAB$^{(R)}$ interface for the control of the sensor node through serial communication. In order to validate the performance of this multifunctional wireless impedance sensor node, a series of experimental studies have been carried out for detecting loose bolts and crack damages on lab-scale steel structural members as well as on real steel bridge and building structures. It has been found that the proposed sensor nodes can be effectively used for local wireless health monitoring of structural components and for constructing a low-cost and multifunctional SHM system as "place and forget" wireless sensors.

• Journal of the Korean Geophysical Society
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• v.9 no.2
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• pp.87-97
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• 2006

LIDAR(Light Detection and Ranging) is a new technology for obtaining DEM(Digital Elevation Model)ewith high density and high point acuracy. As LIDAR emerged, DEM could be developed in the earthsurface more efficiently and more economically, compared to the conventional aerial photogrametry.In this study, a digital camera is simultaneously used in combined LIDAR surveying, and acquired digitial image and DEM produce digital orthoimage. In this process, methods of combining sensor andorthoimage, GCPs determined by GPS surveying are used. Two digital orthoimage are produced; onewith a few GCP and the other without them. The produced maps can be used to corect or revised1:1,000 or 1:5,000 scale maps acordingly.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.209-214
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• 2021

Panoptic segmentation, which is now widely used in computer vision such as medical image analysis, and autonomous driving, helps understanding an image with holistic view. It identifies each pixel by assigning a unique class ID, and an instance ID. Specifically, it can classify 'thing' from 'stuff', and provide pixel-wise results of semantic prediction and object detection. As a result, it can solve both semantic segmentation and instance segmentation tasks through a unified single model, producing two different contexts for two segmentation tasks. Semantic segmentation task focuses on how to obtain multi-scale features from large receptive field, without losing low-level features. On the other hand, instance segmentation task focuses on how to separate 'thing' from 'stuff' and how to produce the representation of detected objects. With the advances of both segmentation techniques, several panoptic segmentation models have been proposed. Many researchers try to solve discrepancy problems between results of two segmentation branches that can be caused on the boundary of the object. In this survey paper, we will introduce the concept of panoptic segmentation, categorize the existing method into two representative methods and explain how it is operated on two methods: top-down method and bottom-up method. Then, we will analyze the performance of various methods with experimental results.

• Journal of Forest and Environmental Science
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• v.35 no.3
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• pp.181-188
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• 2019

This study was performed to construct tree species classification map according to three information types (spectral information, texture information, and spectral and texture information) by altitude (30 m, 60 m, 90 m) using the unmanned aerial vehicle images and the object-based classification method, and to evaluate the concordance rate through field survey data. The object-based, optimal weighted values by altitude were 176 for 30 m images, 111 for 60 m images, and 108 for 90 m images in the case of Scale while 0.4/0.6, 0.5/0.5, in the case of the shape/color and compactness/smoothness respectively regardless of the altitude. The overall accuracy according to the type of information by altitude, the information on spectral and texture information was about 88% in the case of 30 m and the spectral information was about 98% and about 86% in the case of 60 m and 90 m respectively showing the highest rates. The concordance rate with the field survey data per tree species was the highest with about 92% in the case of Pinus densiflora at 30 m, about 100% in the case of Prunus sargentii Rehder tree at 60 m, and about 89% in the case of Robinia pseudoacacia L. at 90 m.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1689-1701
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• 2019

In recent years, personal videos have been shared online due to the popular uses of portable devices, such as smartphones and action cameras. A recent report predicted that 80% of the Internet traffic will be video content by the year 2021. Several studies have been conducted on the detection of main video events to manage a large scale of videos. These studies show fairly good performance in certain genres. However, the methods used in previous studies have difficulty in detecting events of personal video. This is because the characteristics and genres of personal videos vary widely. In a research, we found that adding a dataset with the right perspective in the study improved performance. It has also been shown that performance improves depending on how you extract keyframes from the video. we selected frame segments that can represent video considering the characteristics of this personal video. In each frame segment, object, location, food and audio features were extracted, and representative vectors were generated through a CNN-based recurrent model and a fusion module. The proposed method showed mAP 78.4% performance through experiments using LSVC data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.185-190
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• 2008

The devices for the digital home in ubiquitous environment aim at providing multimedia services which are not limited to the time and space. However, it does not ensure the fair use of digital contents and causes damage to the contents providers because of indiscriminate distribution of digital contents and the use of illegal contents. DRM system for solving this problems cannot protect the license stored on digital home devices and manage license by redistribution of contents. In this paper, digital forensic model that enables the misuse detection and previous interception of large-scale illegal distribution for contents and license, and also enables the creation and management of digital evidence for legal countermeasure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4395-4412
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• 2020

The multisource image fusion has become an active topic in the last few years owing to its higher segmentation rate. To enhance the accuracy of multimodal pig-body feature segmentation, a multisource image fusion method was employed. Nevertheless, the conventional multisource image fusion methods can not extract superior contrast and abundant details of fused image. To superior segment shape feature and detect temperature feature, a new multisource image fusion method was presented and entitled as NSST-GF-IPCNN. Firstly, the multisource images were resolved into a range of multiscale and multidirectional subbands by Nonsubsampled Shearlet Transform (NSST). Then, to superior describe fine-scale texture and edge information, even-symmetrical Gabor filter and Improved Pulse Coupled Neural Network (IPCNN) were used to fuse low and high-frequency subbands, respectively. Next, the fused coefficients were reconstructed into a fusion image using inverse NSST. Finally, the shape feature was extracted using automatic threshold algorithm and optimized using morphological operation. Nevertheless, the highest temperature of pig-body was gained in view of segmentation results. Experiments revealed that the presented fusion algorithm was able to realize 2.102-4.066% higher average accuracy rate than the traditional algorithms and also enhanced efficiency.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.24-37
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• 2021

China's "One Belt and One Road" initiative has brought multiple opportunities to the development of tourism in Guangdong, Guangxi and Hainan provinces and the implementation of the Beibu Gulf Urban Agglomeration Development Plan hasset clear goalsforfurther accelerating the coordinated development, in-depth cooperation of the three. This study takes the Beibu Gulf Urban Agglomeration as the research object and utilized the data envelopment analysis (DEA) procedure to estimate the technical efficiency, pure technical efficiency, and scale efficiency scores for each city and Malmquist index was subsequently used to analyze dynamically, then tries to offer an adequate inclusion of sustainable factors in overall tourism development efficiency results through the detection and estimation of potential sources of efficiency. In order to complete the task, data collection was focused on Guangdong, Guangxi and Hainan provinces of China over the period from 2016 to 2018. The results in the first phase show relatively high efficiency scores, particularly in the case of the Beibu Gulf Urban Agglomeration and with room for improvement in the case of other cities of Guangdong, Guangxi and Hainan provinces. The second stage results present several aspects that should be carefully considered in order to analysis tourism efficiency of the Beibu Gulf Urban Agglomerations vertically according to the changes of the frontier.