• Journal of Satellite, Information and Communications
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• v.8 no.2
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• pp.88-93
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• 2013

The wideband chirp signal generator to enhance the resolution of synthetic aperture radar of obtaining the earth observation image is needed. This paper deals with designing, manufacturing and testing the wideband digital chirp signal generator having high resolution for LEO earth observation satellite. The wideband digital chirp signal generator is implemented with the memory-map based structure which is mostly applied in the satellite, and consists of the digital module to generate the digital chirp signal and the RF module to perform the quadrature modulation. The I/Q signals stored in the memory of the digital module are D/A converted and delivered to be quadrature modulated with the reference signal of 1275 MHz in the RF module. Furthermore, the test bench and GUI to validate the signal generator function are also developed. It is found that the requirement of 144 MHz bandwidth for the digital chirp signal generator is well met. Finally it is noteworthy that the distortion occurred in the chirp signal generator was compensated by the pre-distortion compensation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3666-3671
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• 2012

We evaluate the face detection and recognition of depth image that is obtained by infrared range sensor. and Face recognition was usually focused on accuracy aspect but it is not enough to evaluate the performance in testing for real world application. In this paper, we evaluate the overall performance like accuracy, training, test speed and memory use for the well known face recognition algorithm like PCA, LDA, ICA and SVM. This experiment evaluate the good results of depth and colored depth image compatible with the colored image although the file size of depth and colored depth image is 30%~40% less than the colored image. Whereas, LDA got the good accuracy performance next to the SVM and also shows the good performance in speed and the amount of memory.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.131-131
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• 2021

Deep learning models, especially those based on long short-term memory (LSTM), have presented their superiority in addressing time series data issues recently. This study aims to comprehensively evaluate the performance of deep learning models that belong to the supervised learning category in streamflow prediction. Therefore, six deep learning models-standard LSTM, standard gated recurrent unit (GRU), stacked LSTM, bidirectional LSTM (BiLSTM), feed-forward neural network (FFNN), and convolutional neural network (CNN) models-were of interest in this study. The Red River system, one of the largest river basins in Vietnam, was adopted as a case study. In addition, deep learning models were designed to forecast flowrate for one- and two-day ahead at Son Tay hydrological station on the Red River using a series of observed flowrate data at seven hydrological stations on three major river branches of the Red River system-Thao River, Da River, and Lo River-as the input data for training, validation, and testing. The comparison results have indicated that the four LSTM-based models exhibit significantly better performance and maintain stability than the FFNN and CNN models. Moreover, LSTM-based models may reach impressive predictions even in the presence of upstream reservoirs and dams. In the case of the stacked LSTM and BiLSTM models, the complexity of these models is not accompanied by performance improvement because their respective performance is not higher than the two standard models (LSTM and GRU). As a result, we realized that in the context of hydrological forecasting problems, simple architectural models such as LSTM and GRU (with one hidden layer) are sufficient to produce highly reliable forecasts while minimizing computation time because of the sequential data nature.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.214-217
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• 2022

In the maritime digital forensic part, it is very important and difficult process that analysis of data and information with vessel navigation system's binary log data for situation awareness of maritime accident. In recent years, analysis of vessel's navigation system's trajectory information is an essential element of maritime accident investigation. So, we made an experiment about corruption with various memory device in navigation system. The analysis of corruption test in seawater give us important information about the valid pulling time of sunken ship for acquirement useful trajectory information.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.471-478
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• 2013

This paper proposes a black-box based test case generation method for Simulink/Stateflow model utilizing the RRT algorithm which is a method to efficiently solve the path planning for complicated systems. The proposed method in the paper tries to solve the reachability problem with the RRT algorithm, which has to be solved for black-box based test case generations. A major problem of the RRT based test case generation algorithms is that the cost such as running time and required memory size is too much for complicated Stateflow model. The typical RRT algorithm expands rapidly-exploring random tree (RRT) in a single state space. But the proposed method expands it in dynamic state space based on the state of Simulink model, consequently reducing the cost. In the paper, a new definition of RRT state space, a distance measure and a test case generation algorithm are proposed. The performance of proposed method is verified through the experiment against Stateflow model.

• Korean Journal of Materials Research
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• v.27 no.11
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• pp.590-596
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• 2017

We demonstrated a CNT synaptic transistor by integrating 6,6-phenyl-C61 butyric acid methyl ester(PCBM) molecules as charge storage molecules in a polyimide(PI) dielectric layer with carbon nanotubes(CNTs) for the transistor channel. Specifically, we fabricated and compared three different kinds of CNT-based synaptic transistors: a control device with $Al_2O_3/PI$, a single PCBM device with $Al_2O_3/PI:PCBM$(0.1 wt%), and a double PCBM device with $Al_2O_3/PI:PCBM$(0.1 wt%)/PI:PCBM(0.05 wt%). Statistically, essential device parameters such as Off and On currents, On/Off ratio, device yield, and long-term retention stability for the three kinds of transistor devices were extracted and compared. Notably, the double PCBM device exhibited the most excellent memory transistor behavior. Pulse response properties with postsynaptic dynamic current were also evaluated. Among all of the testing devices, double PCBM device consumed such low power for stand-by and its peak current ratio was so large that the postsynaptic current was also reliably and repeatedly generated. Postsynaptic hole currents through the CNT channel can be generated by electrons trapped in the PCBM molecules and last for a relatively short time(~ hundreds of msec). Under one certain testing configuration, the electrons trapped in the PCBM can also be preserved in a nonvolatile manner for a long-term period. Its integrated platform with extremely low stand-by power should pave a promising road toward next-generation neuromorphic systems, which would emulate the brain power of 20 W.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.47-58
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• 1999

As the performance of processors improves, cache memories are used to overcome the difference of speed between processors and main memories. Generally cache memories are embedded and small sizes, fault coverage is a more important factor than test time in testing point of view. A new test algorithm and a new BIST architecture are developed to detect various fault models with a relatively small overhead. The new concurrent BIST architecture uses the comparator of cache management blocks as response analyzers for tag memories. A modified scan-chain is used for pre-testing of comparators which can reduce test clock cycles. In addition several boundary scan instructions are provided to control the internal test circuitries. The results show that the new algorithm can detect SAFs, AFs, TFs linked with CFs, CFins, CFids, SCFs, CFdyns and DRFs models with O(12N), where N is the memory size and the new BIST architecture has lower overhead than traditional architecture by about 11%.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.5
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• pp.493-500
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• 2001

The detection of axial cracks using conventional MFL pig is a significant challenge in the gas pipeline inspection. In this study, a technique using interaction of circumferentially induced torrents with axial stress corrosion crack is presented. The feasibility of this technique is investigated using finite element modeling. Finite element analysis of such interaction is a difficult problem in terms of both computation time and memory requirements. The challenges arise due to the nonlinearity of material properties, the small sire of tight cracks relative to that of the magnetizer, and also time stepping involved in modeling velocity effects. This paper presents an approach based on perturbation methods. The overall analysis procedure is divided into 4 simple steps that can be performed sequentially. Modeling results show that this technique can effectively detect colonies of SCC as well as single SCC.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.337-351
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• 2004

Our laboratory originally developed the compact, multi-spectral, automatic aerial photographic system PKNU3 to allow greater flexibility in geological and environmental data collection. We are currently developing the PKNU3 system, which consists of a color-infrared spectral camera capable of simultaneous photography in the visible and near-infrared bands; a thermal infrared camera; two computers, each with an 80-gigabyte memory capacity for storing images; an MPEG board that can compress and transfer data to the computers in real-time; and the capability of using a helicopter platform. Before actual aerial photographic testing of the PKNU3, we experimented with each sensor. We analyzed the lens distortion, the sensitivity of the CCD in each band, and the thermal response of the thermal infrared sensor before the aerial photographing. As of September 2004, the PKNU3 development schedule has reached the second phase of testing. As the result of two aerial photographic tests, R, G, B and IR images were taken simultaneously; and images with an overlap rate of 70% using the automatic 1-s interval data recording time could be obtained by PKNU3. Further study is warranted to enhance the system with the addition of gyroscopic and IMU units. We evaluated the PKNU 3 system as a method of environmental remote sensing by comparing each chlorophyll image derived from PKNU 3 photographs. This appraisement was backed up with existing study that resulted in a modest improvement in the linear fit between the measures of chlorophyll and the RVI, NDVI and SAVI images stem from photographs taken by Duncantech MS 3100 which has same spectral configuration with MS 4000 used in PKNU3 system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1225-1236
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• 2020

Fuzzing is an automated software testing methodology that dynamically tests the security of software by inputting randomly generated input values outside of the expected range. KISA is releasing open source for standard cryptographic algorithms, and many crypto module developers are developing crypto modules using this source code. If there is a vulnerability in the open source code, the cryptographic library referring to it has a potential vulnerability, which may lead to a security accident that causes enormous losses in the future. Therefore, in this study, an appropriate security policy was established to verify the safety of block cipher source codes such as SEED, HIGHT, and ARIA, and the safety was verified using differential fuzzing. Finally, a total of 45 vulnerabilities were found in the memory bug items and error handling items, and a vulnerability improvement plan to solve them is proposed.