• Journal of Plant Biotechnology
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• v.41 no.1
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• pp.50-55
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• 2014

Plant-based vaccines possess some advantages over other types of vaccine biotechnology such as safety, low cost of mass vaccination programs, and wider use of vaccines for medicine. This study was undertaken to develop the transgenic maize as edible vaccine candidates for humans. The immature embryos of HiII genotype were inoculated with A. tumefaciens strain C58C1 containing the binary vectors (V662 or V663). The vectors carrying nptII gene as selection marker and scEDIII (V662) or wCTB-scEDIII (V663) target gene, which code EIII proteins inhibite viral adsorption by cells. In total, 721 maize immature embryos were transformed and twenty-two putative transgenic plants were regenerated after 12 weeks selection regime. Of them, two- and six-plants were proved to be integrated with scEDIII and wCTB-scEDIII genes, respectively, by Southern blot analysis. However, only one plant (V662-29-3864) can express the gene of interest confirmed by Northern blot analysis. These results demonstrated that this plant could be used as a candidated source of the vaccine production.

• Journal of the Speleological Society of Korea
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• no.88
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• pp.1-7
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• 2008

Recently, it is one of very interest technology of Human Computer Interaction(HCI). Nowadays, it is easy to find out that, for example, inside SF movies people has talking to computer. However, there are difference between CPU language and ours. So, we focus on connecting to CPU. For 30 years many scientists experienced in that technology. But it is really difficult. Our project goal is making that CPU could understand human voice. First of all the signal through a voice sensor will move to BCD (binary code). That elevator helps out people who wants to move up and down. This product's point is related with people's safety. Using a PWM for motor control by ATmega16, we choose a DC motor to drive it because of making a regular speed elevator. Furthermore, using a voice identification module the elevator driven by voice sensor could operate well up and down perfectly from 1st to 10th floor by PWM control with ATmega16. And, it will be clearly useful for high-rise vertical shift with voice recognition sensor driven.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3756-3777
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• 2019

Recent internet development is helping malware researchers to generate malicious code variants through automated tools. Due to this reason, the number of malicious variants is increasing day by day. Consequently, the performance improvement in malware analysis is the critical requirement to stop the rapid expansion of malware. The existing research proved that the similarities among malware variants could be used for detection and family classification. In this paper, a Cross-Platform Malware Variant Classification System (CP-MVCS) proposed that converted malware binary into a grayscale image. Further, malicious features extracted from the grayscale image through Combined SIFT-GIST Malware (CSGM) description. Later, these features used to identify the relevant family of malware variant. CP-MVCS reduced computational time and improved classification accuracy by using CSGM feature description along machine learning classification. The experiment performed on four publically available datasets of Windows OS and Android OS. The experimental results showed that the computation time and malware classification accuracy of CP-MVCS was higher than traditional methods. The evaluation also showed that CP-MVCS was not only differentiated families of malware variants but also identified both malware and benign samples in mix fashion efficiently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4300-4314
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• 2019

With the development of video-related applications, media content has increased dramatically through applications. There is a substantial amount of near-duplicate videos (NDVs) among Internet videos, thus NDVR is important for eliminating near-duplicates from web video searches. This paper proposes a novel NDVR system that supports large-scale retrieval and contributes to the efficient and accurate retrieval performance. For this, we extracted keyframes from each video at regular intervals and then extracted both commonly used features (LBP and HSV) and new image features from each keyframe. A recent study introduced a new image feature that can provide more robust information than existing features even if there are geometric changes to and complex editing of images. We convert a vector set that consists of the extracted features to binary code through a set of hash functions so that the similarity comparison can be more efficient as similar videos are more likely to map into the same buckets. Lastly, we calculate similarity to search for NDVs; we examine the effectiveness of the NDVR system and compare this against previous NDVR systems using the public video collections CC_WEB_VIDEO. The proposed NDVR system's performance is very promising compared to previous NDVR systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3654-3670
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• 2019

This paper proposes an Image Texture Median Filter (ITMF) to analyze and detect Android malware on Drebin datasets. We design a model of "ITMF" combined with Image Processing of Median Filter (MF) to reflect the similarity of the malware binary file block. At the same time, using the MAEVS (Malware Activity Embedding in Vector Space) to reflect the potential dynamic activity of malware. In order to ensure the improvement of the classification accuracy, the above-mentioned features(ITMF feature and MAEVS feature)are studied to train Restricted Boltzmann Machine (RBM) and Back Propagation (BP). The experimental results show that the model has an average accuracy rate of 95.43% with few false alarms. to Android malicious code, which is significantly higher than 95.2% of without ITMF, 93.8% of shallow machine learning model SVM, 94.8% of KNN, 94.6% of ANN.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.23-29
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• 2022

As the application field of radar is expanded and the bandwidth increases, the number of radar sensors operating at the same frequency is continuously increasing. In this paper, we propose a method of analyzing interference when two pulse doppler radars are operated at the same frequency with different waveform which are designed independently. In addition, we show that even for a previously designed LFM waveforms, the interference can be suppressed without affecting the performance by changing the sign of the frequency slope by increasing/decreasing, or by modulating the pulses by the different codes. The interference suppression by different slopes is more effective for similar waveform and the suppression by the codes increases as the number of pulses increases. We expect this result can be extended to the cases where multiple radars are operated at the same frequency.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.2
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• pp.297-304
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• 2015

Zeus is one of the will-published malwares. Generally, it infects PC by executing a specific binary file downloaded on the internet. When infected, try to hook a particular Windows API of the currently running processes. If process runs hooked API, this API executes a particular code of Zeus and your private information is leaked. This paper describes techniques to detect and hook Windows API. We believe the technique should be able to detect modern P2P Zeus.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2208-2219
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• 2024

Kylin-2 is an advanced neutronics lattice code, developed by Nuclear Power Institute of China. High-precision multigroup cross section library is need for KYLIN-2 to carry out simulation of current pressurized water reactor (PWR) and advanced reactor. In this paper a multigroup cross section library generation system named TPAMS was developed, the methods in TPAMS dealing with resonance data such as subgroup parameters, lambda factor, resonance integral were discussed. Moreover, the depletion chain simplification method was studied. TPAMS can produce multigroup library in binary and ASIIC formats, including detailed data contents for resonance, transport and depletion calculations. A multigroup cross section library has been generated for KYLIN-2 based on TPAMS system. The multigroup cross section library was verified through the analysis of various criticality and burnup benchmarks, the values of multiplication factor and isotope density were compared with the experiment data. Numerical results demonstrate the accuracy of the multigroup cross section library and the reliability of the multigroup cross section library generation system TPAMS.

• Journal of Astronomy and Space Sciences
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• v.26 no.2
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• pp.141-156
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• 2009

Through the photometric observations of the near-contact binary, XZ CMi, new BV light curves were secured and seven times of minimum light were determined. An intensive period study with all published timings, including ours, confirms that the period of XZ CMi has varied in a cyclic period variation superposed on a secular period decrease over last 70 years. Assuming the cyclic change of period to occur by a light-time effect due to a third-body, the light-time orbit with a semi-amplitude of 0.0056d, a period of 29y and an eccentricity of 0.71 was calculated. The observed secular period decrease of $-5.26{\times}10^{-11}d/P$ was interpreted as a result of simultaneous occurrence of both a period decrease of $-8.20{\times}10^{-11}d/P$ by angular momentum loss (AML) due to a magnetic braking stellar wind and a period increase of $2.94{\times}10^{-11}d/P$ by a mass transfer from the less massive secondary to the primary components in the system. In this line the decreasing rate of period due to AML is about 3 times larger than the increasing one by a mass transfer in their absolute values. The latter implies a mass transfer of $\dot{M}_s=3.21{\times}10^{-8}M_{\odot}y^{-1}$ from the less massive secondary to the primary. The BV light curves with the latest Wilson-Devinney binary code were analyzed for two separate models of 8200K and 7000K as the photospheric temperature of the primary component. Both models confirm that XZ CMi is truly a near-contact binary with a less massive secondary completely filling Roche lobe and a primary inside the inner Roche lobe and there is a third-light corresponding to about 15-17% of the total system light. However, the third-light source can not be the same as the third-body suggested from the period study. At the present, however, we can not determine which one between two models is better fitted to the observations because of a negligible difference of $\sum(O-C)^2$ between them. The diversity of mass ratios, with which previous investigators were in disagreement, still remains to be one of unsolved problems in XZ CMi system. Spectroscopic observations for a radial velocity curve and high-resolution spectra as well as a high-precision photometry are needed to resolve some of remaining problems.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.1-8
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• 2020

Recently, the number of APT(Advanced Persistent Threats) attack using malware has been increasing, and research is underway to prevent and detect them. While it is important to detect and block attacks before they occur, it is also important to make an effective response through an accurate analysis for attack case and attack type, these respond which can be determined by analyzing the attack group of such attacks. Therefore, this paper propose a framework based on genetic algorithm for analyzing malware and understanding attacker group's features. The framework uses decompiler and disassembler to extract related code in collected malware, and analyzes information related to author through code analysis. Malware has unique characteristics that only it has, which can be said to be features that can identify the author or attacker groups of that malware. So, we select specific features only having attack group among the various features extracted from binary and source code through the authorship clustering method, and apply genetic algorithm to accurate clustering to infer specific features. Also, we find features which based on characteristics each group of malware authors has that can express each group, and create profiles to verify that the group of authors is correctly clustered. In this paper, we do experiment about author classification using genetic algorithm and finding specific features to express author characteristic. In experiment result, we identified an author classification accuracy of 86% and selected features to be used for authorship analysis among the information extracted through genetic algorithm.