• Journal of Veterinary Science
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• v.24 no.3
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• pp.40.1-40.6
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• 2023

Analysis of the VP1 gene sequence of the foot and mouth disease virus (FMDV) is critical to understanding viral evolution and disease epidemiology. A standard set of primers have been used for the detection and sequence analysis of the VP1 gene of FMDV directly from suspected clinical samples with limited success. The study validated VP1-specific degenerate primer-based reverse transcription polymerase chain reaction (RT-PCR) for the qualitative detection and sequencing of serotype O FMDV lineages circulating in India. The novel degenerate primer-based RT-PCR amplifying the VP1 gene can circumvent the genetic heterogeneity observed in viruses after cell culture adaptation and facilitate precise viral gene sequence analysis from clinical samples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2736-2754
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• 2015

Android dominates the mobile operating system market, which stimulates the rapid spread of mobile malware. It is quite challenging to detect mobile malware. System call sequence analysis is widely used to identify malware. However, the malware detection accuracy of existing approaches is not satisfactory since they do not consider correlation of system calls in the sequence. In this paper, we propose a new scheme called Artificial Neural Networks (ANNs) on Co-occurrence Matrices Droid (ANNCMDroid), using co-occurrence matrices to mine correlation of system calls. Our key observation is that correlation of system calls is significantly different between malware and benign software, which can be accurately expressed by co-occurrence matrices, and ANNs can effectively identify anomaly in the co-occurrence matrices. Thus at first we calculate co-occurrence matrices from the system call sequences and then convert them into vectors. Finally, these vectors are fed into ANN to detect malware. We demonstrate the effectiveness of ANNCMDroid by real experiments. Experimental results show that only 4 applications among 594 evaluated benign applications are falsely detected as malware, and only 18 applications among 614 evaluated malicious applications are not detected. As a result, ANNCMDroid achieved an F-Score of 0.981878, which is much higher than other methods.

• Journal of the Korea Computer Industry Society
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• v.9 no.4
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• pp.149-156
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• 2008

There is the temporal correlation of a animation sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the scene change detection algorithm for block matching using the temporal correlation of the animation sequence and the center-biased property of motion vectors. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate point on each search region. Simulation results show that the proposed algorithm has better detection performance, such as recall rate, then the existing method. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1361-1369
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• 1996

Motion estimation is one of the key components for high quality video coding. In this paper, a new motion estimation scheme for MPEG-like video coder is suggested. The proposed temporally adaptive motion estimation scheme consists of five functional blocks: Temporal subband analysis (TSBA), extraction of temporal information, scene change detection (SCD), picture type replacement (PTR), and temporally adapted block matching algorithm (TABMA). Here all the functional components are based on the temporal subband analysis. In this papre, we applied the analysis part of subband decompostion to the temporal axis of moving picture sequence, newly defined the temporal activity distribution (TAD) and average TAD, and proposed the temporally adapted block matching algorithm, the scene change detection algorithm and picture type replacement algorithm which employed the results of the temporal subband analysis. A new block matching algorithm TABMA is capable of controlling the block matching area. According to the temporal activity distribution of objects, it allocates the search areas nonuniformly. The proposed SCD and PTR can prevent unavailable motion prediction for abrupt scene changes. Computer simulation results show that the proposed motion estimation scheme improve the quality of reconstructed sequence and reduces the number of block matching trials to 40% of the numbers of trials in conventional methods. The TSBA based scene change detection algorithm can detect the abruptly changed scenes in the intentionally combined sequence of this experiment without additional computations.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.6
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• pp.42-48
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• 2010

Joint Tactical Information Distribution System (JTIDS) uses cyclic code shift keying (CCSK) for baseband symbol modulation, in which 5-bit information is mapped to one of thirty two 32-chip sequences. It is a kind of direct sequence based spread spectrum communication. In this paper, the performance of non-coherent detection of CCSK using non-orthogonal 32-chip sequence is evaluated. And a 32-chip sequence with better performance is also proposed and compared with the conventional one.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.9
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• pp.39-45
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• 2004

A design method is proposed for the sequence detection with fixed decision delay with less hardware complexity using the concept of the Voronoi diagram and its dual, the Delaunay tessellation. This detector design is based on the Fixed Delay Tree Search (FDTS) detection. The FDTS is a computationally efficient sequence detection algerian and has been shown to achieve near-optimal performance in the severe Intersymbol Interference (ISI) channels when combined with decision feedback equalization and the appropriate channel coding. In this approach, utilizing the information contained in the Voronoi diagram or equivalently the Delaunay tessellation, the relative location of the detector input sequence in the multi-dimensional Euclidean space is found without any computational redundancy, which leads to a reduced complexity implementation of the detector.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.620-627
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• 2016

This paper proposes an advanced detection technique for cable fault by eliminating the sign of reference signal in STDR(sequence time-domain reflectometry) and SSTDR(spread-spectrum time-domain reflectometry). The proposed fault-detection technique can eliminate the reference signal more effectively than the conventional one since the sign detector can approximately recover the distorted reference signal by cable and connector, and consequently, can detect the reflected signal by fault more effectively than the conventional one. Especially, it is shown that the error rate of proposed technique can be significantly lower than the conventional one in the case of far fault simulation.

• Journal of Satellite, Information and Communications
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• v.7 no.1
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• pp.21-26
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• 2012

For the last 20 years, our country has been pointing to a great power for digital information technology, but quantum information technology which is already researched in many forefront nations lags significantly behind other countries. Recently, quantum information management, quantum computing and quantum communication based on the quantum mechanics have been researching actively in many fields such as cryptology. On the basis of these background, in this paper, to efficient data transmission and detection for quantum data, we apply the orthogonal sequence to quantum communication system. The performance of proposed scheme is analyzed in terms of auto and cross correlation performance.

• The Plant Pathology Journal
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• v.35 no.2
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• pp.164-171
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• 2019

An assay for detecting Apple scar skin viroid (ASSVd) was developed based on nucleic acid sequence based amplification (NASBA) in combination with realtime detection during the amplification process using molecular beacon. The ASSVd specific primers for amplification of the viroid RNA and molecular beacon for detecting the viroid were designed based on highly conserved regions of several ASSVd sequences including Korean isolate. The assay had a detection range of $1{\times}10^4$ to $1{\times}10^{12}$ ASSVd RNA $copies/{\mu}l$ with reproducibility and precision. Following the construction of standard curves based on time to positive (TTP) value for the serial dilutions ranging from $1{\times}10^7$ to $1{\times}10^{12}$ copies of the recombinant plasmid, a standard regression line was constructed by plotting the TTP values versus the logarithm of the starting ASSVd RNA copy number of 10-fold dilutions each. Compared to the established RT-PCR methods, our method was more sensitive for detecting ASSVd. The real-time quantitative NASBA method will be fast, sensitive, and reliable for routine diagnosis and selection of viroid-free stock materials. Furthermore, real-time quantitative NASBA may be especially useful for detecting low levels in apple trees with early viroid-infection stage and for monitoring the influence on tree growth.

• Journal of KIISE
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• v.44 no.8
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• pp.774-781
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• 2017

Mention detection systems use nouns or noun phrases as a head and construct a chunk of text that defines any meaning, including a modifier. The term "mention detection" relates to the extraction of mentions in a document. In the mentions, a coreference resolution pertains to finding out if various mentions have the same meaning to each other. A pointer network is a model based on a recurrent neural network (RNN) encoder-decoder, and outputs a list of elements that correspond to input sequence. In this paper, we propose the use of mention detection using pointer networks. Our proposed model can solve the problem of overlapped mention detection, an issue that could not be solved by sequence labeling when applying the pointer network to the mention detection. As a result of this experiment, performance of the proposed mention detection model showed an F1 of 80.07%, a 7.65%p higher than rule-based mention detection; a co-reference resolution performance using this mention detection model showed a CoNLL F1 of 52.67% (mention boundary), and a CoNLL F1 of 60.11% (head boundary) that is high, 7.68%p, or 1.5%p more than coreference resolution using rule-based mention detection.