• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1287-1292
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• 2018

In case of fire, the information related with the fire need to be provided to fire fighters in order to extinguish the fire efficiently. However, existing fire detection systems have the problem not to provide the data of the fire to fire fighters visually. In this paper, we propose the fire spot system using a cloud server to solve this problem. In the proposed system, the sensors installed in a building collect the gas and temperature data and store them into the cloud database using a wireless network. For fire fighters in the field, the details and history of the fire spot are displayed visually on top of the blue print retrieved from the cloud database using a smart device.

• ETRI Journal
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• v.41 no.4
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• pp.494-505
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• 2019

In this paper, we propose a new framework for detecting the unauthorized dumping of garbage in real-world surveillance camera. Although several action/behavior recognition methods have been investigated, these studies are hardly applicable to real-world scenarios because they are mainly focused on well-refined datasets. Because the dumping actions in the real-world take a variety of forms, building a new method to disclose the actions instead of exploiting previous approaches is a better strategy. We detected the dumping action by the change in relation between a person and the object being held by them. To find the person-held object of indefinite form, we used a background subtraction algorithm and human joint estimation. The person-held object was then tracked and the relation model between the joints and objects was built. Finally, the dumping action was detected through the voting-based decision module. In the experiments, we show the effectiveness of the proposed method by testing on real-world videos containing various dumping actions. In addition, the proposed framework is implemented in a real-time monitoring system through a fast online algorithm.

• Journal of Platform Technology
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• v.8 no.1
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• pp.3-9
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• 2020

In Korea, 63% of the nation's land is made up of forests, and the average temperature of the earth has been increasing. Forest service has been operating a proactive control system for preventing the spread of forest pests such as Pine wilt disease. but there were some hurdles in timely control due to weather, topography and manpower management difficulties. In this paper, we propose a model for building fast, accurate and efficient control system by categorizing the damage and dead wood automatically based on the images acquired using small unmanned aerial vehicles based on information and communication technology. In particular, the proposed model establishes an effective response system for government affairs through cooperation in the private sector. It can also create new jobs in the unmanned aerial vehicle business and service industries.

• Current Optics and Photonics
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• v.6 no.4
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• pp.381-391
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• 2022

Two-photon-polymerization additive-manufacturing systems feature high resolution and precision. However, there are few reports on specific methods and possible problems concerning the use of small lasers to independently build such platforms. In this paper, a femtosecond-laser two-photon-polymerization additive-manufacturing system containing an optical unit, control unit, monitoring unit, and testing unit is built using a miniature femtosecond laser, with a detailed building process and corresponding control software that is developed independently. This system has integrated functions of light-spot detection, interface searching, micro-/nanomanufacturing, and performance testing. In addition, possible problems in the processes of platform establishment, resin preparation, and actual polymerization for two-photon-polymerization additive manufacturing are explained specifically, and the causes of these problems analyzed. Moreover, the impacts of different power levels and scanning speeds on the degree of polymerization are compared, and the influence of the magnification of the object lens on the linewidth is analyzed in detail. A qualitative analysis model is established, and the concepts of the threshold broadening and focus narrowing effects are proposed, with their influences and cooperative relation discussed. Besides, a linear structure with micrometer accuracy is manufactured at the millimeter scale.

• Smart Structures and Systems
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• v.28 no.6
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• pp.727-735
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• 2021

Recently, non-destructive health monitoring methods such as magnetic flux leakage (MFL) method, have become popular due to their advantages over destructive methods. Currently, numerical study on this field has been limited to simplified studies by only obtaining MFL instead of induced voltage inside coil sensor. In this study, it was proposed to perform a novel numerical simulation of MFL's coil sensor by considering vital parameters including specimen's motion with constant velocity and saturation status of specimen in time domain. A steel-rod specimen with two stepwise cross-sectional changes (i.e., 21% and 16%) was fabricated using low carbon steel. In order to evaluate the results of numerical simulation, an experimental test was also conducted using a magnetic probe, with same size specimen and test parameters, exclusively. According to comparative results of numerical simulation and experimental test, similar signal amplitude and signal pattern were observed. Thus, proposed numerical simulation method can be used as a reliable source to check efficiency of sensor probe when different size specimens with different defects should be inspected.

• ETRI Journal
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• v.45 no.3
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• pp.448-461
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• 2023

This article performs a detailed data scrutiny on a chronic kidney disease (CKD) dataset to select efficient instances and relevant features. Data relevancy is investigated using feature extraction, hybrid outlier detection, and handling of missing values. Data instances that do not influence the target are removed using data envelopment analysis to enable reduction of rows. Column reduction is achieved by ranking the attributes through feature selection methodologies, namely, extra-trees classifier, recursive feature elimination, chi-squared test, analysis of variance, and mutual information. These methodologies are ranked via Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) using weight optimization to identify the optimal features for model building from the CKD dataset to facilitate better prediction while diagnosing the severity of the disease. An efficient hybrid ensemble and novel similarity-based classifiers are built using the pruned dataset, and the results are thereafter compared with random forest, AdaBoost, naive Bayes, k-nearest neighbors, and support vector machines. The hybrid ensemble classifier yields a better prediction accuracy of 98.31% for the features selected by extra tree classifier (ETC), which is ranked as the best by TOPSIS.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.591-594
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• 2020

담화에서 의미를 전달하는 데 문제가 없을 경우에는 문장성분을 생략하여 표현한다. 생략된 문장성분을 무형대용어(zero anaphora)라고 한다. 무형대용어를 복원하기 위해서는 무형대용어 탐지와 무형대용어 해결이 필요하다. 무형대용어 탐지란 문장 내에서 생략된 필수성분을 찾는 것이고, 무형대용어 해결이란 무형대용어에 알맞은 문장성분을 찾아내는 것이다. 본 논문에서는 담화에서의 무형대용어 탐지 및 해결을 위한 말뭉치 생성 방법을 제안한다. 먼저 기존의 세종 구어 말뭉치에서 어휘지도를 이용하여 무형대용어를 복원한다. 이를 위해 본 논문에서는 동형이의어 부착과 어휘지도를 이용해서 무형대용어를 복원하고 복원된 무형대용어에 대한 오류를 수정하고 그 선행어(antecedent)를 수동으로 결정함으로써 무형대용어 해결 말뭉치를 생성한다. 총 58,896 문장에서 126,720개의 무형대용어를 복원하였으며, 약 90%의 정확률을 보였다. 앞으로 심층학습 등의 방법을 활용하여 성능을 개선할 계획이다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.617-623
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• 2023

Among the fire incidents in Korea over the past decade, building fires are the most common, and property and human casualties are the most common. However, the existing fire fighting system does not only inform the location of emergency exits and guide safe routes to help casualties evacuate smoothly. A system was proposed to help successful evacuation by distinguishing vertical and horizontal characteristics using spatial characteristics. In this study, an effective evacuation system was proposed by predicting fires using temperature detection sensors and smoke sensor values, and calculating the optimal evacuation path through the Dijkstra algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.131-132
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• 2022

We generate classifications and scenarios for intrusions based on 3D LiDAR Data. Research was conducted to analyze and diversify various actual intrusion cases to establish a system that can recognize objects and identify and guard data on intrusion. By generating and simulating basic scenarios for cars, people, animals, natural objects and etc, we create a classification scheme necessary to build and evaluate systems for intrusion. Based on the finally constructed scenario, we add variables for vehicles and surrounding objects to diversify scenarios, and lay the foundation for building accurate and automated alerting systems for future intrusions.