• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.441-447
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• 2022

This study describes a novel method for detecting and measuring partial discharge (PD) on an electrical facility such as an insulated power cable or switchgear using fiber optic sensing technology, and a distributed acoustic sensing (DAS) system. This method has distinct advantages over traditional PD sensing techniques based on an electrical method, including immunity to electromagnetic interference (EMI), long range detection, simultaneous detection for multiple points, and exact location. In this study, we present a DAS system for PD detection with performance evaluation and experimental results in a simulated environment. The results show that the system can be applied to PD detection.

• ETRI Journal
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• v.44 no.2
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• pp.300-312
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• 2022

Recently, public safety services have attracted significant attention for their ability to protect people from crimes. Rapid detection of dangerous situations (that is, abnormal situations where someone may be harmed or killed) is required in public safety services to reduce the time required to respond to such situations. This study proposes a novel danger detection technology based on multimodal data, which includes data from multiple sensors (for example, accelerometer, gyroscope, heart rate, air pressure, and global positioning system sensors), and multilog data, which includes contextual logs of humans and places (for example, contextual logs of human activities and crime-ridden districts) over time. To recognize human activity (for example, walk, sit, and punch), the proposed technology uses multimodal data analysis with an attitude heading reference system and long short-term memory. The proposed technology also includes multilog data analysis for detecting whether recognized activities of humans are dangerous. The proposed danger detection technology will benefit public safety services by improving danger detection capabilities.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.1-10
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• 2023

Open surface water body extraction is gaining popularity in recent years due to its versatile applications. Multiple techniques are used for water detection based on applications. Different applications of Radar as LADAR, Ground-penetrating, synthetic aperture, and sounding radars are used to detect water. Shortwave infrared, thermal, optical, and multi-spectral sensors are widely used to detect water bodies. A stereo camera is another way to detect water and different methods are applied to the images of stereo cameras such as deep learning, machine learning, polarization, color variations, and descriptors are used to segment water and no water areas. The Satellite is also used at a high level to get water imagery and the captured imagery is processed using various methods such as features extraction, thresholding, entropy-based, and machine learning to find water on the surface. In this paper, we have summarized all the available methods to detect water areas. The main focus of this survey is on water detection especially in small patches or in small areas. The second aim of this survey is to detect water hazards for unmanned vehicles and off-sure navigation.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.206-207
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• 2020

Accurate estimation of concrete strength development at early ages is a critical factor to secure structural stability as well as to speed up the construction process. The temperature generated from the heat of hydration is considered as a key parameter in predicting the early age strength. Conventionally, concrete temperature has been measured by temperature sensors installed inside concrete. However, considering the measurement on building structures with multiple floors, this method requires reinstallation and repositioning of hardware such as sensors, data loggers and routers for data transfer. This makes the temperature monitoring work cumbersome and inefficient. Concrete temperature monitoring by using thermal remote sensing can be an effective alternative to supplement those shortcomings. In this study, image processing was carried out through K-means clustering technique, which is a unsupervised learning method, and the classification results were analyzed accordingly. In the future, research will be conducted on how to automatically recognize concrete among various objects by using deep learning techniques.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.153-153
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• 2022

There is a growing need to develop ion sensors for agriculture. As a result, several technologies have been developed, such as colorimetry, spectrophotometry, and ion-selective electrode (ISE). Among them, ISE has some advantages compared to others. First, it does not require pre-treatment processes and expensive equipment. Second, it is possible for the portable detection system by introducing small-sized electrodes. Finally, real-time and multiple detections of several ions are pursued. It is well-known that N, P, and K nutrients are critical for crop growth. With the development of agriculture techniques, the importance of soil nutrient analysis has attracted much attention for cost-effective and eco-friendly agriculture. Among several issues, minimizing the use of fertilizers is significant through quantitative analysis of soil nutrients. As a result, it is highly important to analyze certain nutrients, such as N (ammonium ion, nitrate ion, nitrite ion), P (dihydrogen phosphate ion, monohydrogen phosphate ion), and K (potassium ion). Therefore, developing sensors for accurate analysis of soil nutrients is highly desired. n this study, several ISEs have been fabricated to detect N, P, and K. Their performance has been intensively studied, such as sensitivity, selectivity coefficient, and concentration range, and compared with commercialized ISEs. In addition, preliminary tests on the in-situ N, P, and K monitoring have been conducted inside the soil.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.259-266
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• 2023

The use of various adulterants and harmful chemicals is rapidly increasing in various sectors such as agriculture, food, and pharmaceuticals, and they are also present in our surroundings in the form of pollutants. The regular and repeated intake of harmful chemicals often adversely affects human health. The prolonged exposure of living beings to such adverse components can lead to severe health complications. To avoid the unlimited utilization of these chemical components, a sensing technology that is sensitive and reliable for low-concentration detection is beneficial. Surface-enhanced Raman spectroscopy (SERS) is a powerful method for identifying low-range concentrations of analytes, leading to great applications in molecular identification, including various diagnostic biomarkers. SERS in chemical, gas, and biological sensors can be an excellent approach in the sensing world to achieve rapid and multiple-analyte detection, leading to a new and efficient approach in healthcare monitoring.

• Journal of the Korean institute of surface engineering
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• v.57 no.3
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• pp.208-213
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• 2024

With the development of industry, miniaturization and densification of semiconductor components are rapidly progressing. Particularly, as demand surges across various sectors, efficiency in productivity has emerged as a crucial issue in semiconductor component manufacturing. Maximizing semiconductor productivity requires real-time monitoring of semiconductor processes and continuous reflection of the results to stabilize processes. However, various unexpected variables and errors in judgment that occur during the process can cause significant losses in semiconductor productivity. Therefore, while the development of a reliable manufacturing system is important, the importance of developing sensor technology that can complement this and accurately monitor the process is also growing. In this study, conducted a basic research on the concept of diagnostic sensors for thickness based on the physical changes of thin films due to etching. It observed changes in resistance corresponding to variations in thin film thickness as etching processes progressed, and conducted research on the correlation between these physical changes and thickness variations. Furthermore, to assess the reliability of thin film thickness measurement sensors, it conducted multiple measurements and comparative analyses of physical changes in thin films according to various thicknesses.

• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.3 s.55
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• pp.101-109
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• 2009

An algorithm is proposed for estimating dynamic displacements of a bridge by using FBG sensors and by superposing some measurable low modes. Modal displacements are obtained from the beam theory and the generalized coordinates are deduced from the strains measured by FBG sensors. By considering flexural and torsional modes occurred in bridges only as flexural modes of a simply supported beam by separating a bridge into multiple girders or parts, the proposed algorithm can be applied to various types of bridges. Guidelines are provided theoretically for determining the number of modes and the number of strain gages to be used. The proposed algorithm has been examined through simulation studies on various types of bridges, laboratory experiments on a model bridge, and field tests on a simple span PC Box girder bridge. Through the simulation study, the effects of the error in the vibration modes and measurement noise on estimating the dynamic displacements are analyzed.

• Bulletin of the Korean Chemical Society
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• v.33 no.10
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• pp.3368-3372
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• 2012

The $Bi_2O_3$ nanowires are highly sensitive to low concentrations of $NO_2$ in ambient air and are almost insensitive to most other common gases. However, it still remains a challenge to enhance their sensing performance and detection limit. This study examined the influence of the encapsulation of ${\beta}-Bi_2O_3$ nanorods with $In_2O_3$ on the $NO_2$ gas sensing properties. ${\beta}-Bi_2O_3-core/In_2O_3-shell$ nanorods were fabricated by a two-step process comprising the thermal evaporation of $Bi_2O_3$ powders and sputter-deposition of $In_2O_3$. Multiple networked ${\beta}-Bi_2O_3-core/In_2O_3-shell$ nanorod sensors showed the responses of 12-156% at 1-5 ppm $NO_2$ at $300^{\circ}C$. These response values were 1.3-2.7 times larger than those of bare ${\beta}-Bi_2O_3$ nanorod sensors at 1-5 ppm $NO_2$. The enhancement in the response of ${\beta}-Bi_2O_3$ nanorods to $NO_2$ gas by the encapsulation by $In_2O_3$ can be accounted for based on the space-charge model.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.15-21
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• 2017

Following the successful launch of KOMPSAT-3 in May 2012, KOMPSAT-5 in August 2013, and KOMPSAT-3A in March 2015 have succeeded in launching the integrated operation of optical, radar and thermal infrared sensors in Korea. We have established a foundation to utilize the characteristics of each sensors. In order to overcome limitations in the range of application and accuracy of the application of a single sensor, multi-sensor image fusion techniques have been developed which take advantage of multiple sensors and complement each other. In this paper, we introduce the development of software (InFusion) for multi-sensor image fusion and valued-added product generation using KOMPSAT series. First, we describe the characteristics of each sensor and the necessity of fusion software development, and describe the entire development process. It aims to increase the data utilization of KOMPSAT series and to inform the superiority of domestic software through creation of high value-added products.