• Korean Journal of Remote Sensing
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• v.19 no.4
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• pp.291-305
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• 2003

The cost of deploying Geological and Environmental information gathering systems, especially when such systems obtain remote sensing and photographic data through the use of commercial satellites and aircraft. Besides the high cost equipment required, adverse weather conditions can further restrict a researcher's ability to collect data anywhere and anytime. To mitigate this problem, we have developed a compact, multi-spectral automatic Aerial photographic system. This system's Multi-spectral camera is capable of the visible (RGB) and infrared (NIR) bands (3032*2008 pixel). It consists of a thermal infrared camera and automatic balance control, and can be managed by a palm-top computer. Other features includes a camera gimbal system, GPS receiver, weather sensor among others. We have evaluated the efficiency of this system in several field tests at the following locations: Kyongsang-bukdo beach, Nakdong river (at each site of mulkeum-namji and koryung-gumi), and Kyungahn River. Its tested ability in aerial photography, weather data, as well as GPS data acquisition demonstrates its flexibility as a tool for environmental data monitoring.

• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.369-382
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• 2004

The purpose of this study is the investigation of applicability of LSMA(Linear Spectral Mixture Analysis) on the geological uses with different radiometric and spatial types of sensor images such as Terra ASTER and LANDSAT 7 ETM+. As for the actual application case, geologic mapping for mineral exploration using ASTER and ETM+ at the Mongolian plateau region was carried out. After the pre-processing such as the geometric corrections and calibration of radiance, 7 endmembers, as spectral classes for geologic rock types, related to spectral signature deviation for the given application was determined by the pre-surveyed geological mapping information and the correlation matrix analysis, and total 20 images of ASTER and ETM+ were used to LSMA processing. As the results, fraction maps showing individual mineral types in the study area are presented. It concluded that this approach based on LSMA using ETM+ and ASTER is regarded as one of the effective schemes for geologic remote sensing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.80-95
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• 2019

Recently, with the development of sensor and communication technology, researchers at home and abroad have actively conducted research on methodologies for determining maintenance through diagnosis and prediction techniques by collecting information on the status of equipment or systems. Based on the status of vehicle parts at this point in time, this study presented a system framework for making maintenance decisions by predicting the change in vehicle part status to a future date based on the current state of vehicle parts. In addition, condition diagnosis and predictive data adjustment was configured through tracking the status of vehicle parts before and after maintenance activities. We hope that the application of the results of this study will contribute a little to the safety of citizens using public buses and to the activation of the condition-based maintenance system of vehicles.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.787-796
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• 2019

In this paper, we propose the design and test measure of Ringer injection IoT system for controling the ringer injection status and notifying the server system of the collected status informations such as the completion of injection, the remaining liquid, the injection status, and the emergency alarming of the urgent patients. We design the circuit diagrams composed of linger injection sensors, switches, status indicators, wireless communication functionalities, and propose the controlling and monitoring algorithms for sensing the linger injection status and notifying the collected status informations to a server system. Furthermore, we derive the testing criteria, such as linger liquid sensing time, sensing distance, operating temperature, input power, power consumption, and wireless communication speed, and analyze the test results.

• Convergence Security Journal
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• v.17 no.5
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• pp.3-10
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• 2017

Standard Protocol Optimized for Resource-Constrained IoT Environment Constrained Application Protocol (CoAP) supports web-based communication between a sensor node in the IoT environment and a client on the Internet. The CoAP is a Request / Response model that responds to the client's CoAP Request message by responding with a CoAP Response message from the server. CoAP recommends the use of CoAP-DTLS for message protection. However, validation of the use of DTLS in the IoT environment is underway. We analyze CoAP and DTLS security mode, evaluate performance of secure channel creation time, security channel creation step time, and RAM / ROM consumption through Cooja simulator and evaluate the possibility of real environment application.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.7-12
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• 2019

In order to shoot underwater, the photographer must be equipped with shooting equipment and enter into the water. Since the photographer directly enters the water, safety accidents occur frequently due to various obstacles or deep water in the water. The proposed underwater stereo photography technique can solve the safety accident problem caused by the entry of the photographer into the water by using the drone for underwater photographing. In addition, this technique has the advantage of obtaining underwater images at low cost. In this study, the angle of the proposed cam for stereoscopic photography was analyzed and the condition that the proper stereoscopic image can be viewed was defined as the distance from the floor of 18cm to the floor distance of 41.4cm. This provision is proposed to be used to adjust the height of the shooting area descended by the elevation chain of the water surface hovering drones.

• The Journal of Korean Institute of Information Technology
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• v.17 no.8
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• pp.11-19
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• 2019

Against advanced image-related crimes, a high level of digital forensic methods is required. However, feature-based methods are difficult to respond to new device features by utilizing human-designed features, and deep learning-based methods should improve accuracy. This paper proposes a deep learning model to identify camera models based on DenseNet, the recent technology in the deep learning model field. To extract camera sensor features, a HPF feature extraction filter was applied. For camera model identification, we modified the number of hierarchical iterations and eliminated the Bottleneck layer and compression processing used to reduce computation. The proposed model was analyzed using the Dresden database and achieved an accuracy of 99.65% for 14 camera models. We achieved higher accuracy than previous studies and overcome their disadvantages with low accuracy for the same manufacturer.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.127-134
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• 2021

In this study, an anomaly detection (AD) algorithm was implemented to detect the failure of a marine air compressor. A lab-scale experiment was designed to produce fault datasets (time-series electric current measurements) for 10 failure modes of the air compressor. The results demonstrated that the temporal pattern of the datasets showed periodicity with a different period, depending on the failure mode. An AD model with a convolutional autoencoder was developed and trained based on a normal operation dataset. The reconstruction error was used as the threshold for AD. The reconstruction error was noted to be dependent on the AD model and hyperparameter tuning. The AD model was applied to the synthetic dataset, which comprised both normal and abnormal conditions of the air compressor for validation. The AD model exhibited good detection performance on anomalies showing periodicity but poor performance on anomalies resulting from subtle load changes in the motor.

• Journal of Space Technology and Applications
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• v.2 no.3
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• pp.221-229
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• 2022

This paper reports on the design and installation of a thermostat to keep the temperature of the fluxgate magnetometer constant and the data stability evaluation after installation. The thermostat was installed at the Icheon Geomagnetic Observatory operated by the Korean Space Weather Center of National Radio Research Agency. It was designed in consideration of stability of temperature control against safety incident, potential effects on magnetic field measurement, and the temperature control efficiency. After the temperature control device was installed, it was confirmed that the temperature was constantly maintained at the level of 20℃. Delta F and baseline values were used to evaluate geomagnetic data stability, and it was confirmed that delta F and baseline fluctuations were reduced after installation of the thermostat.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1353-1362
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• 2023

Various methods are being attempted to resolve the inconvenience of blood glucose meters used to check blood sugar levels. In this paper, we attempted to estimate blood sugar levels non-invasively using machine learning technology from spectral data acquired using a near-infrared sensor. The non-invasive blood glucose meter used in the study has a total of six near-infrared ray emitters, including visible rays, and a light receiver that receives them. It is a device created to collect spectral data on specific parts of the human body, such as the fingers. To verify whether there was a significant difference depending on blood sugar level, we attempted to estimate blood sugar level through machine learning algorithms. As a result of applying five machine learning algorithm techniques to the collected data and adjusting various hyper parameters, it was confirmed that the support vector regression algorithm showed the best performance.