• 대한방사선기술학회지:방사선기술과학
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• 제16권1호
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• pp.107-115
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• 1993

In this study, to develop highly sensitive radiation sensors, $CaSO_4$ : Tm phosphors and its disc-type TLD elements embedded PTFE(polytetrafluoroethylene) are fabricated. The highest sensitivity of $CaSO_4$ : Tm phosphors is obtained when phosphors have been doped with 0.5mol % Tm and sintered in atmosphere at $600^{\circ}C$ for two hours. Fabricated disc-type elements are made from a homogeneous mixture of phosphors and PTFE powder. They are first cold-pressed and then polymerized at $370^{\circ}C$ in air for one hour. The dose dependence of the prepared $CaSO_4$ : Tm TLD radiation sensors is linear within the range of $100{\mu}Gy{\sim}10Gy$ for X-rays and ${\gamma}-rays$. The response of $CaSO_4$ : Tm to 30keV X-rays is ten times higher than that of 1.25MeV $^{60}Co\;{\gamma}-rays$. The fading rate of the main peak is about 2% per a month. The spectral peaks of TL emission spectrum are at about 350nm and 475nm. The $CaSO_4$ : Tm TLD radiation sensors prepared in this work may be used as radiation dosimeter for personal and environmental monitoring because of their high sensitivity and little fading.

• 센서학회지
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• 제20권5호
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• pp.311-316
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• 2011

Monitoring the carbon dioxide concentration in arterial blood is vital for the evaluation and prevention of pulmonary disease. Yet, domestic pure arterial blood carbon dioxide sensor technologies are not being developed, instead all sensors are imported. In this paper, we develop a real time monitoring system for arterial blood partial pressure of carbon dioxide($pCO_2$) gas from the wrist by using a carbon micro-heater. The micro-heater was fabricated with a thickness of 0.3 ${\mu}m$ in order to collect the carbon dioxide under the skin. The micro-heater has been designed to perform temperature compensation in order to prevent damage to the skin. Two clinical trials of the system were undertaken. As a result, we demonstrated that a portable, transcutaneous carbon dioxide analysis($TcpCO_2$) device produced domestically is possible. In addition, this system reduced the analysis time significantly. Carbon films could reduce the unit price of these sensors by replacing the gold film used in foreign models. Also, we developed a real time monitoring system which can be used with optical biosensors for medical diagnostics as well as gas sensors for environmental monitoring.

• 센서학회지
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• 제17권3호
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• pp.203-209
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• 2008

Thick film formaldehyde (HCHO) gas sensors were fabricated by using $La_1_{-x}Sr_xMO_3$ (M= Fe, Co, Mn) ceramics. The powders of $La_1_{-x}Sr_xMO_3$ (M=Fe, Co, Mn) were synthesized by conventional solid-state reaction method. By using the $La_1_{-x}Sr_xMO_3$ (M=Fe, Co, Mn) paste, the thick-film formaldehyde sensors were prepared on the alumina substrate by silkscreen printing method. The experimental results revealed that $La_1_{-x}Sr_xMO_3$ (M= Fe, Co, Mn) ceramic powder has a perovskite structure and the thick-film sensor shows excellent gas-sensing characteristics to formaldehyde gas (sensitivity of $La_{0.8}Sr_{0.2}FeO_3$, S= 14.7 at operating temperature of $150^{\circ}C$ in 50 ppm HCHO ambient).

• 한국멀티미디어학회논문지
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• 제10권6호
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• pp.786-798
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• 2007

As we go about our daily lives, people often collect surrounding information and adapt to the situation. Computer development trends show that one wants computers to work like human beings, i.e. computers can sense its context and adapt corresponding to context changes. To implement this expectation, a context aware service layer is needed. In this layer, sensors capture its environment and send this information to the service center. Considering received information as its context, the service center seeks the suitable operation according to the context. Tills paper presents a context aware service which is applied in controlling air-conditioner. The air-conditioner includes sensors which are installed at some special positions in a room. Each of these sensors gathers comfort-influenced information like temperature, humidity and sends them to air-conditioner. The air-conditioner adapts its operation to the environment according to the sensed information. To control the air-conditioner effectively, we use a genetic algorithm which is suitable in adaptation issues. The simulation shows that the room condition can be maintained at a comfortable level by using context-aware services in the operation of the air-conditioning system.

• Structural Monitoring and Maintenance
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• 제4권1호
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• pp.1-15
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• 2017

Installation of sensors networks for continuous in-service monitoring of structures and their efficiency conditions is a current research trend of paramount interest. On-line monitoring systems could be strategically useful for road infrastructures, which are expected to perform efficiently and be self-diagnostic, also in emergency scenarios. This work researches damage detection in composite concrete-steel structures that are typical for highway overpasses and bridges. The techniques herein proposed assume that typical damage in the deck occurs in form of delamination and cracking, and that it affects the peak power spectral density of dynamic curvature. The investigation is performed by combining results of measurements collected by long-gauge fiber optic strain sensors installed on monitored structure and a statistic approach. A finite element model has been also prepared and validated for deepening peculiar aspects of the investigation and the availability of the method. The proposed method for real time applications is able to detect a documented unusual behavior (e.g., damage or deterioration) through long-gauge fiber optic strain sensors measurements and a probabilistic study of the dynamic curvature power spectral density.

• 한국인터넷방송통신학회논문지
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• 제16권3호
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• pp.173-178
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• 2016

최근 드론과 원거리에 설치된 센서들의 협업을 통해 대상을 모니터링하는 연구가 활발하게 진행되고 있다. 이러한 모니터링 시스템에서는 고정된 센서를 통해 환경 데이터를 수집하고 이동이 가능한 드론을 통해 데이터를 수집한다. 지반 공학에서는 공사 현장의 안전성을 측정하기 위해서 인력을 사용하는 경우가 많으며 다수의 센서를 설치하여 네트워크를 구성하는 것은 비용문제 때문에 현실적인 대안이 될 수 없다. 본 논문에서는 이러한 지반관련 프로젝트 수행 시 소수의 센서를 구조물 주변에 설치하고 드론을 통해 데이터를 수집하는 시스템을 제안한다. 또한 실험을 통해서 제안 시스템의 가용성을 확인하고 인력을 활용할 때보다 시간과 비용을 줄일 수 있음을 검증하였다.

• Smart Structures and Systems
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• 제5권4호
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• pp.381-395
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• 2009

The paper presents a case study in which the structural condition assessment of the East Bay bridge in Gibsonton, Florida is evaluated with the help of remote health monitoring techniques. The bridge is a four-span, continuous, deck-type reinforced concrete structure supported on prestressed pile bents, and is instrumented with smart Fiber Optic Sensors. The sensors used for remote health monitoring are the newly emerged Fabry-Perot (FP), and are both surface-mounted and embedded in the deck. The sensing system can be accessed remotely through fast Digital Subscriber Lines (DSL), which permits the evaluation of the bridge behavior under live traffic loads. The bridge was open to traffic since March 2005, and the collected structural data have been continuously analyzed since. The data revealed an increase in strain readings, which suggests a progression in damage. Recent visual observations also indicated the presence of longitudinal cracks along the bridge length. After the formation of these cracks, the sensors readings were analyzed and used to extrapolate the values of the maximum stresses at the crack location. The data obtained were also compared to initial design values of the bridge under factored gravity and live loads. The study showed that the proposed structural health monitoring technique proved to provide an efficient mean for condition assessment of bridge structures providing it is implemented and analyzed with care.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.814-822
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• 2022

The deployment of sensors for Structural Health Monitoring requires a complicated network arrangement, ground truthing, and calibration for validating sensor performance periodically. Any conventional sensor on a structural element is also subjected to static and dynamic vertical loadings in conjunction with other environmental factors, such as brightness, noise, temperature, and humidity. A structural model with strain gauges was built and tested to get realistic sensory information. This paper investigates different deep learning architectures and algorithms, including unsupervised, autoencoder, and supervised methods, to benchmark blind drift calibration methods using deep learning. It involves a fully connected neural network (FCNN), a long short-term memory (LSTM), and a gated recurrent unit (GRU) to address the blind drift calibration problem (i.e., performing calibrations of installed sensors when ground truth is not available). The results show that the supervised methods perform much better than unsupervised methods, such as an autoencoder, when ground truths are available. Furthermore, taking advantage of time-series information, the GRU model generates the most precise predictions to remove the drift overall.

• 센서학회지
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• 제32권2호
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• pp.75-81
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• 2023

The significance of gas sensors has been emphasized in various industries and applications, owing to the growing significance of environmental, social, and governance (ESG) management in corporate operations. In particular, the monitoring of hazardous gas leakages and detection of fugitive emissions have recently garnered significant attention across several industrial sectors. As industrial workplaces evolve to ensure the safety of their working environments and reduce greenhouse gas emissions, the demand for high-performance gas sensors in industrial sectors dealing with toxic substances is on the rise. However, conventional gas-sensing systems have limitations in monitoring fugitive gas leakages at both critical and subcritical concentrations in complex environments. To overcome these difficulties, recent studies in the field of gas sensors have employed techniques such as mobile robotic olfaction, remote optical sensing, chemical grid sensing, and remote acoustic sensing. This review highlights the significant progress made in various technologies that have enabled accurate and real-time mapping of gas distribution and localization of hazardous gas sources. These recent advancements in gas-sensing technology have shed light on the future role of gas-detection systems in industrial safety.

• Computers and Concrete
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• 제31권5호
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• pp.457-468
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• 2023

Buildings, bridges, and dams are examples of civil infrastructure that play an important role in public life. These structures are prone to structural variations over time as a result of external forces that might disrupt the operation of the structures, cause structural integrity issues, and raise safety concerns for the occupants. Therefore, monitoring the state of a structure, also known as structural health monitoring (SHM), is essential. Owing to the emergence of the fourth industrial revolution, next-generation sensors, such as wireless sensors, UAVs, and video cameras, have recently been utilized to improve the quality and efficiency of building forensics. This study presents a method that uses a target-based system to estimate the dynamic displacement and its corresponding dynamic properties of structures using UAV-based video. A laboratory experiment was performed to verify the tracking technique using a shaking table to excite an SDOF specimen and comparing the results between a laser distance sensor, accelerometer, and fixed camera. Then a field test was conducted to validate the proposed framework. One target marker is placed on the specimen, and another marker is attached to the ground, which serves as a stationary reference to account for the undesired UAV movement. The results from the UAV and stationary camera displayed a root mean square (RMS) error of 2.02% for the displacement, and after post-processing the displacement data using an OMA method, the identified natural frequency and damping ratio showed significant accuracy and similarities. The findings illustrate the capabilities and reliabilities of the methodology using UAV to evaluate the dynamic properties of structures.