• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.279-285
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• 2020

The study on the temporal and spatial monitoring of passing vessels is important in terms of protection and management the marine ecosystem in the coastal area. In this paper, we propose the automatic detection technique of passing vessel by utilizing an artificial intelligence technology and broadband striation patterns which are characteristic of broadband noise radiated by passing vessel. Acoustic measurements to collect underwater noise spectrum images and ship navigation information were conducted in the southern region of Jeju Island in South Korea for 12 days (2016.07.15-07.26). And the convolution neural network model is optimized through learning and validation processes based on the collected images. The automatic detection performance of passing vessel is evaluated by precision (0.936), recall (0.830), average precision (0.824), and accuracy (0.949). In conclusion, the possibility of the automatic detection technique of passing vessel is confirmed by using an artificial intelligence technology, and a future study is proposed from the results of this study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.8
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• pp.510-517
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• 2014

Recently, Cable communications services are becoming the HDTV to 3DTV, UHDTV broadcasting and 100Mbps to 1Gbps Internet. however existing technologies are limited to provide high-quality broadband services in the HFC network. The network upgrade technologies have some problems that Up/Downsteam frequency extension, Cost of upgrading by using DOCSIS3.1, EPOC and Legacy STB compatibility, Cost of upgrading the network by RFoG, RF overlay PON. This paper propose the RF/PON based gigabit Transmission system in order to provide the 1Gbps internet without using frequency and the Multiscreen to IP devices. After the proposed RF/PON system was developed and implemented, this paper evaluate the performance of RF/PON system for simultaneously real-time braodcasting and 1Gbps internet, Multiscreen service, and so on.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.245-248
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• 2011

Voice over Internet protocol(VoIP) is call's contents using the existing internet. Thus, in common with the Internet service has the same vulnerability. In addition, unlike traditional PSTN remotely without physical access to hack through the eavesdropping is possible. Cyber terrorism by anti-state groups take place when the agency's computer network and telephone system at the same time work is likely to get upset. In this paper is penetration testing for security threats(Call interception, eavesdropping, misuse of services) set out in the NIS in the VoIP. In addition, scenario writing and penetration testing, hacking through the Voice over Internet protocol at the examination center will study discovered vulnerabilities. Vulnerability discovered in Voice over Internet protocol presents an attack and defense plan.

• Journal of Platform Technology
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• v.9 no.3
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• pp.63-69
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• 2021

Limited materials to make coins for countries and designs suitable for hand-carry make the shape, size, and color of coins similar. This similarity makes that it is difficult for visitors to identify each country's coins. To solve this problem, we propose the coin classification method using CNN effective to image processing. In our coin identification method, we collect the training data by using web crawling and use OpenCV for preprocessing. After preprocessing, we extract features from an image by using three CNN layers and classify coins by using two fully connected network layers. To show that our model designed in this paper is effective for coin classification, we evaluate our model using eight different coin types. From our experimental results, the accuracy for coin classification is about 99.5%.

• The Journal of Engineering Geology
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• v.31 no.1
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• pp.55-66
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• 2021

Hydraulic-mechanical (H-M) coupled numerical modeling was used to evaluate the evolution of hydrogeological properties in response to the installation and expansion of a borehole. A domain with a discrete fracture network was adopted for discontinuum modeling to simulate changes in fracture apertures. Comparison with real hydraulic test data shows that the effects of principal stress direction and expansion of borehole diameter were reasonably simulated by H-M coupled numerical modeling. The modeling confirmed that aperture changes depended on the principal stress direction, with an increase in aperture size due to vertical displacement being the dominant effect. A concentration of shear dilation around the borehole had an additional, subsidiary, effect on the hydrogeological evolution. These results show that the permeability of fractured rock can be increased by changing the hydraulic properties of a fracture through stress redistribution caused by the installation and expansion of a borehole.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.63-73
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• 2021

This paper presents a algorithm for automatic target recognition robust to the influence of the flame in order to track the target by EOTS(Electro-Optical Targeting System) equipped on UAV(Unmanned Aerial Vehicle) when there is aerial target or marine target with flame at the same time. The proposed method converts infrared images of targets and flames into a gradient vector field, and applies each gradient magnitude to a polynomial curve fitting technique to extract polynomial coefficients, and learns them in a shallow neural network model to automatically recognize targets and flames. The performance of the proposed technique was confirmed by utilizing the various infrared image database of the target and flame. Using this algorithm, it can be applied to areas where collision avoidance, forest fire detection, automatic detection and recognition of targets in the air and sea during automatic flight of unmanned aircraft.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.305-313
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• 2021

The upcoming warfare will be network-centric warfare with the acquiring and sharing of information on the battlefield through the connection of the entire weapon system. Therefore, the amount of information generated increases, but the technology of evaluating the information is insufficient. Threat assessment is a technology that supports a quick decision, but the information has many uncertainties and is difficult to apply to an advanced battlefield. This paper proposes a threat assessment based on artificial intelligence while removing the target uncertainty. The artificial intelligence system used was a fuzzy inference system and a multi-layer perceptron. The target was classified by inputting the unique characteristics of the target into the fuzzy inference system, and the classified target information was input into the multi-layer perceptron to calculate the appropriate threat value. The validity of the proposed technique was verified with the threat value calculated by inputting the uncertain target to the trained artificial neural network.

• Journal of IKEEE
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• v.25 no.1
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• pp.193-200
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• 2021

In order to prevent illegal fishing and reduce lost fishing gear, it is necessary to develop a constant and continuous fishing gear monitoring system in the marine environment. In this paper, we design a long-term operational, reliable system model with communication coverage of more than 25Km considering the reality of gradually expanding fishing activity due to the depletion of fishery resources and marine environments. The design results are implemented to verify the operability of the system by separating the communication success rate of SKT and private LoRa networks and verifying the control function of each control system through the collected location information, respectively.

• Journal of Korea Water Resources Association
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• v.54 no.1
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• pp.49-60
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• 2021

This study presents a methodology to estimate two distinct fractal dimensions of natural river basin by using fractal tree concept. To this end, an analysis is performed on fractal features of a complete drainage network which consists of all possible drainage paths within a river basin based on the growth process of fractal tree. The growth process of fractal tree would occur only within the limited drainage paths possessing stream flow features in a river basin. In the case of small river basin, the bifurcation process of network is more sensitive to the growth step of fractal tree than the meandering process of stream segment, so that various bifurcation structures could be generated in a single network. Therefore, fractal dimension of network structure for small river basin should be estimated in the form of a range not a single figure. Furthermore, the network structures with fractal tree from this study might be more useful information than stream networks from a topographic or digital map for analysis of drainage structure on small river basin.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.87-95
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• 2022

The geotechnical information constructed in the National Geotechnical Information DB System has been extensively used in design, construction, underground safety management, and disaster assessment. However, it is necessary to refine the geotechnical information because it has nearly 300,000 established cases containing a lot of missing or incorrect information. This research proposes a method for automatic quality control of geotechnical information using a fully connected neural network. Significantly, the anomalies in geotechnical information were detected using a database combining the standard penetration test results and strata information of Seoul. Consequently, the misclassification rate for the verification data is confirmed as 5.4%. Overall, the studied algorithm is expected to detect outliers of geotechnical information effectively.