• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.122-128
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• 2014

Remote fourier transform infrared(FTIR) chemical imaging detection system allows detection and identification of gases in the atmosphere from long distances. In this paper, the appropriate field of view(FOV) of the FTIR imaging system was examined and the main performance of the system for the interferometer was described. For the determination of the FOV, simulations of gas dispersion range were performed with the NBC reporting and modeling software(NBC-RAMS) developed by ADD. As a result, minimum 192 mrad of FOV was required for the remote FTIR imaging system to visualize chemical warfare agents dispersed in several hundred meters. At the same time, 0.75 mrad of instantaneous field of view(IFOV) for a linear interferometer proper to take a FOV for the chemical agent imaging.

• Electronics and Telecommunications Trends
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• v.38 no.5
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• pp.71-80
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• 2023

With the rapid advancement of the Internet, the use of encrypted traffic has surged in order to protect data during transmission. Simultaneously, network attacks have also begun to leverage encrypted traffic, leading to active research in the field of encrypted traffic analysis to overcome the limitations of traditional detection methods. In this paper, we provide an overview of the encrypted traffic analysis field, covering the analysis process, domains, models, evaluation methods, and research trends. Specifically, it focuses on the research trends in the field of anomaly detection in encrypted network traffic analysis. Furthermore, considerations for model development in encrypted traffic analysis are discussed, including traffic dataset composition, selection of traffic representation methods, creation of analysis models, and mitigation of AI model attacks. In the future, the volume of encrypted network traffic will continue to increase, particularly with a higher proportion of attack traffic utilizing encryption. Research on attack detection in such an environment must be consistently conducted to address these challenges.

• International Journal of Automotive Technology
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• v.3 no.2
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• pp.53-56
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• 2002

A new generation of the BMW child seat and occupant detection system SBE2 far a smart airbag system is described. The SBE2 system consists of two subsystems: OC (Occupant Classification) and FDS (Field Detection System). The OC system is a force sensitive sensor array that measures a pressure profile. The FDS system detects child seat and occupant according to the change of electrical field generated by four capacitive plates. Combining the signals from both subsystems, the BMW SBE2 system can distinguish fully automatically between a child seat and a person.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.2
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• pp.92-97
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• 2003

This paper presents system to enable an efficient water vein detection using GPS and geomagnetic fields. Because the developed system in this paper can be automatically saved the data acquired from GPS and geomagenetic instrument into the database, it can decrease the number of detectors and save the time for water vein detection. The developed system can analyze the positions for the drilling correctly.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.6
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• pp.66-71
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• 2007

Development of a locomotive mechanism for the capsule type endoscopes will largely enhance their ability to diagnose disease of digestive organs. As a part of it, there should be provided a detection device of their position in human organs for the purpose of observation and motion control. In this paper, a permanent magnet outside human body was employed to project magnetic field on a capsule type endoscope, while its position dependent flux density was measured by three hall-effect sensors which were orthogonally installed inside the capsule. In order to detect the 2-D position data of the capsule with three hall-effect sensors including the roll, pitch and yaw angle, the permanent magnet was extra translated during the measurement. In this way, the 2-D coordinates and three rotation angles of a capsule endoscope on the same motion plane with the permanent magnet could be detected. The working principle and performance test results of the capsule position detection device were introduced in this paper showing that they could be also applied to 6-DOF position detection.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.28-35
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• 2019

Since guided missiles with the characteristics of the one-shot system remain stored throughout their entire life cycle, it is important to maintain their storage reliability until the launch. As part of maintaining storage reliability, period of preventive test is set up to perform preventive periodic test, in this case failure detection rate has a great effect on setting up period of preventive test to maintain storage reliability. The proposed method utilizes failure rate predicted by the software on the basis of MIL-HDBK-217F and failure mode analyzed through FMEA (Failure Mode and Effect Analysis) using data generated from the actual field. The failure detection rate of using the proposed method is applied to set periodic test of the actual guided missile. The proposed method in this paper has advantages in accuracy and objectivity because it utilizes a large amount of data generated in the actual field.

• Korean Journal of Veterinary Research
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• v.13 no.1
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• pp.39-46
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• 1973

Cultural method, dark field microscopy & fluorescent antibody technique were compared for their sensitivity of the detection of leptospires from experimentally infected mice. Two groups of mice were infected with L. icterohemorrhagiae (M20) and L. australis (Ballico), and the infected blood, urine and a number of organs were subjected to the bacterial isolation. The results obtained were summarized as follows: 1. L. icterohemorrhagiae (M20) and L. australis (Ballico) in blood, urine and various tissues of experimentally infected mice were detected with a negrigible non specificity, by the fluorescent antibody technique. 2. The fluorescent antibody technique, as applied to detection of leptospires in blood, urine and various infected tissue, proved to be better than cultural method and dark-field microscopy. 3. Early detection of leptospires by fluorescent antibody technique were possible in blood at 2 days after inoculation, whereas detection of organisms in liver, spleen, lung and kidney were observed later. By means of fluorescent antibody technique, the detection of leptospires in kidney and urine was possible up to 34 days postinoculation, whereas those in other parts were impossible. 4. Fluorescent antibody reaction of leptospires were highly specific to homologous antigen rather than to heterologous one. 5. Fluorescent antibody technique may be of value in the application for the demonstration of leptospira from clinical specimens.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.804-807
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• 2002

Edge of image have a many information about input image. There is a many applications to using a edge detection and uses by variable special effect. Edge detection is a field of image analysis, image segmentation using a pixel make the one field for decision of image construction. In this paper, image segmentation through many ways of edge detection for image segmentation. First of all, it analyze feature of image and extract by feature of each image, to adopt way of edge detection to selective. It realize edge detection efficiently, consider to feature of language through using a java image segmentation.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.5
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• pp.113-121
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• 2013

The road icing forecast and snow detection system using state evaluation algorithm of multi sensor optimizes snow melting system to control spread time and amount of chemical spread application This system operates integrated of contact/non-contact sensor and infrared camera. The state evaluation algorithm of the system evaluates road freezing danger condition and snowfall condition (snowfall intensity also) using acquired data such as temperature/humidity, moisture detection and result of image signal processing from field video footage. In the field experiment, it proved excellent and reliable evaluated result of snowfall state detection rate of 89% and wet state detection rate of 94%.

• Journal of KIBIM
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• v.13 no.3
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• pp.12-20
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• 2023

Deep learning-based anomaly detection technology is used in various fields such as computer vision, speech recognition, and natural language processing. In particular, this technology is applied in various fields such as monitoring manufacturing equipment abnormalities, detecting financial fraud, detecting network hacking, and detecting anomalies in medical images. However, in the field of construction and architecture, research on deep learning-based data anomaly detection technology is difficult due to the lack of digitization of domain knowledge due to late digital conversion, lack of learning data, and difficulties in collecting and processing field data in real time. This study acquires necessary data through IoT (Internet of Things) from the viewpoint of monitoring for environmental management of architectural spaces, converts them into a database, learns deep learning, and then supports anomaly patterns using AI (Artificial Infelligence) deep learning-based anomaly detection. We propose an implementation process. The results of this study suggest an effective environmental anomaly pattern detection solution architecture for environmental management of architectural spaces, proving its feasibility. The proposed method enables quick response through real-time data processing and analysis collected from IoT. In order to confirm the effectiveness of the proposed method, performance analysis is performed through prototype implementation to derive the results.