• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.186-193
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• 2019

This paper presents and implements a simple programmable PCM encoder structure uisng the commutation method. In the telemetry system, information is required to assign each data to the channel in order to generate a frame format the data acpuired from the sensor. In this case, when the number of state information is large or the data type is various, there is a necessity to input a large amount of information to each channel. However, the more the number of channels and data, the more probability the error will occur. Therefore, in this paper, the channel information is created using the program. And PCM encoder was implemented to store channel information in ROM. The proposed PCM encoder architecture reduces the likelihood of errors. And it can improve the development speed. The validity of proposed structure is proved by simulation.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.194-199
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• 2019

Natural disasters destroy decades of human effort and investments, thereby placing new demands on society for reconstruction and rehabilitation. In most case, the natural phenomena triggering the disasters are beyond human control. In order to solve the problems that the information resources can not be shared among disaster management sectors and their work is hard to be coordinated in city, an idea of application of ubiquitous sense network and ICT technology to model the architecture of the disaster prevention system based on the analysis of characteristics of disasters. The proposed algorithm simulated that it is possible to locate the terminal by linking the direction angle and the estimated position that can be confirmed at the time of stopping, even if the movement direction of the terminal does not move in a certain direction with only a smaller number of mobile base stations. We also confirmed that the proposed algorithms analyzed through simulation are more efficient than existing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2148-2167
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• 2021

The proliferation of the Internet of Things (IoT) technologies and applications, especially the rapid rise in the use of mobile devices, from individuals to organizations, has led to the fundamental role of secure wireless networks in all aspects of services that presented with many opportunities and challenges. To ensure the CIA (confidentiality, integrity and accessibility) security model of the networks security and high efficiency of performance results in various resource-constrained applications and environments of the IoT platform, DDO-(data-driven operation) based constructions have been introduced as a primitive design that meet the demand of high speed encryption systems. Among of them, the TMN-family ciphers which were proposed by Tuan P.M., Do Thi B., etc., in 2016, are entirely suitable approaches for various communication applications of wireless mobile networks (WMNs) and advanced wireless sensor networks (WSNs) with high flexibility, applicability and mobility shown in two different algorithm selections, TMN64 and TMN128. The two ciphers provide strong security against known cryptanalysis, such as linear attacks and differential attacks. In this study, we demonstrate new probability results on the security of the two TMN construction versions - TMN64 and TMN128, by proposing efficient related-key recovery attacks. The high probability characteristics (DCs) are constructed under the related-key differential properties on a full number of function rounds of TMN64 and TMN128, as 10-rounds and 12-rounds, respectively. Hence, the amplified boomerang attacks can be applied to break these two ciphers with appropriate complexity of data and time consumptions. The work is expected to be extended and improved with the latest BCT technique for better cryptanalytic results in further research.

• The Journal of Korean Institute of Information Technology
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• v.17 no.7
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• pp.1-11
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• 2019

With the development of smartphones and wearable devices, researches related to platforms that collect lifelogs from these devices and the visualization of the lifelog results have also been advanced. However, the existed researches were impossible to collect data from various devices because they depended on a specific device and platform when transmitting or receiving lifelog data. In addition, they do not provide visualized analysis results of specialized lifelogs in specific areas, such as the users' location information. To resolve the problems, this paper analyzes user location information from the lifelog collection platform and develops the interface and visualization tools for lifelog collection. To do this, we define and analyze the requirements of developing the proposed system. Then, based on the analyzed requirements, this paper develops a lifelog visualization tool using various graphs, maps and the RESTful API interface and shows its implemented results.

• 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 Advanced Navigation Technology
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• v.24 no.6
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• pp.485-490
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• 2020

Recently, amid active research on domestic shipbuilding industry and IT convergence technology, with the development of satellite detection technology for ship safety operation, ships monitored the movement of ships with the mandatory long-range identification & tracking of vessels and automatic identification system. It is possible to help safe navigation, but it is necessary to develop safety device that alert the marine officer who rely on radar to correct conditions in case of weightlessness. Therefore, an ocean fog alarm system was developed to detect and inform using photo sensors. The fabricated ocean fog detect and alarm system consists of a small, low-power optical sensor transceiver and data sensing processing module. Through experiment, it is confirmed that the fabricated ocean fog detect and alarm system measure the corresponding concentration of ocean fog for fogless circumstance and fogbound circumstance, respectively. Furthermore, the fabricated system can control RPM of ship engine according to the concentration of ocean fog, and consequently, the fabricated system can be applied to assistant device for ship safety operation.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.83-101
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• 2022

Accurate atmospheric correction is essential for the analysis of land surface and environmental monitoring. Aerosol optical depth (AOD) information is particularly important in atmospheric correction because the radiation attenuation by Mie scattering makes the differences between the radiation calculated at the satellite sensor and the radiation measured at the land surface. Thus, it is necessary to use high-quality AOD data for an appropriate atmospheric correction of high-resolution satellite images. In this study, we examined the Second Simulation of a Satellite Signal in the Solar Spectrum (6S)-based atmospheric correction results for the Sentinel-2 images in South Korea using raster AOD (MODIS) and single-point AOD (AERONET). The 6S result was overall agreed with the Sentinel-2 level 2 data. Moreover, using raster AOD showed better performance than using single-point AOD. The atmospheric correction using the single-point AOD yielded some inappropriate values for forest and water pixels, where as the atmospheric correction using raster AOD produced stable and natural patterns in accordance with the land cover map. Also, the Sentinel-2 normalized difference vegetation index (NDVI) after the 6S correction had similar patterns to the up scaled drone NDVI, although Sentinel-2 NDVI had relatively low values. Also, the spatial distribution of both images seemed very similar for growing and harvest seasons. Future work will be necessary to make efforts for the gap-filling of AOD data and an accurate bi-directional reflectance distribution function (BRDF) model for high-resolution atmospheric correction. These methods can help improve the land surface monitoring using the future Compact Advanced Satellite 500 in South Korea.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.78-84
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• 2022

In this paper, we propose a closed-form based 3D localization method in the presence of multiple signal sources. General localization methods such as TDOA, AOA, and FDOA can estimate a location when a single signal source exists. When there are multiple unknown signal sources, there is a limit in estimating the location. The proposed method calculates a cross-correlation vector of signals received by sensors having an array antenna, and estimates TDOA and AOA values from the cross-correlation values. Then, the coordinate transformation is performed using the position of the reference sensor. Then, the coordinate rotation is performed using the estimated AOA value for the transformed coordinates, and then the three-dimensional position of each emitter is estimated. The proposed method verifies its performance through computer simulation.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.63-71
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• 2022

Barometers have been used to calculate altitude, and with the development of technology, barometer which had a large volume have now been reduced to about centimeter-level. The altitude calculation using barometer is proceeded using the relationship between reference sea level pressure and the pressure obtained by barometer, and for this, pre-calibration of the barometer is essential. In addition, the barometer has a certain level of bias from actual pressure due to production, and many smartphone manufacturers correct it during the manufacturing process, but it is difficult to correct errors caused by environmental variables. In this paper, we extended methodology of correcting barometer using static reference station to moving drone, and it was possible to calculate the altitude more accurately.

• Composites Research
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• v.35 no.4
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• pp.283-287
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• 2022

Stretchable strain sensors have been developed for potential future applications including wearable devices and health monitoring. For practical implementation of stretchable strain sensors, their stability and repeatability are one of the important aspects to be considered. In this work, we utilized 3D printed polymer structures having kirigami patterns to improve the stretchability and reduce the hysteresis. The polymer structures were coated with graphene/carbon nanofiber hybrids to make a robust electrical network. The stretchable strain sensors showed a high gauge of 36 at a strain of 32%. Because of the kirigami structures and the robust graphene/carbon nanofiber coating, the sensors also exhibited stable resistance responses at various strains ranging from 1% to 30%.