• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.47-53
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• 2022

Recently, with the change of the intelligent security paradigm, study to apply various information generated from various information security systems to AI-based anomaly detection is increasing. Therefore, in this study, in order to convert log-like time series data into a vector, which is a numerical feature, the CBOW and Skip-gram inference methods of deep learning-based Word2Vec model and statistical method based on the coincidence frequency were used to transform the published ADFA system call data. In relation to this, an experiment was carried out through conversion into various embedding vectors considering the dimension of vector, the length of sequence, and the window size. In addition, the performance of the embedding methods used as well as the detection performance were compared and evaluated through GRU-based anomaly detection model using vectors generated by the embedding model as an input. Compared to the statistical model, it was confirmed that the Skip-gram maintains more stable performance without biasing a specific window size or sequence length, and is more effective in making each event of sequence data into an embedding vector.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.15-25
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• 2004

This paper outlines a new convergence acceleration de-signed to solve scramjet flowfields with zones of re-circulation. Named the “marching-window”, the algorithm consists of performing pseudo-time iterations on a minimal width subdomain composed of a sequence of cross-stream planes of nodes. The upstream boundary of the subdomain is positioned such that all nodes upstream exhibit a residual smaller than the user-specified convergence threshold. The advancement of the downstream boundary follows the advancement of the upstream boundary, except in zones of significant streamwise ellipticity where a streamwise ellipticity sensor ensures its continuous progress. Compared to the standard pseudo-time marching approach, the march-ing-window is here seen to decrease the work required for convergence by up to 24 times for supersonic flows with little streamwise ellipticity and by up to 8 times for supersonic flows with large streamwise separated regions. The memory requirements are observed to be reduced sixfold by not allocating memory to the nodes not included in the computational subdomain. The marching-window satisfies the same convergence criterion as the standard pseudo-time stepping methods, hence resulting in the same converged solution within the tolerance of the user-specified convergence threshold. The extension of the marching-window to the weakly-ionized Navier-Stokes equations is also discussed.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.35-43
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• 2019

Template tracking refers to the procedure of finding the most similar image patch corresponding to the given template through an image sequence. In order to obtain more accurate trajectory of the template, the template requires to be updated to reflect various appearance changes as it traverses through an image sequence. To do that, appearance images are used to model appearance variations and these are obtained by the computation of the principal components of the augmented image matrix at every iteration. Unfortunately, it is prohibitively expensive to compute the principal components at every iteration. Thus in this paper, we suggest a new Sliding Window based truncated URV Decomposition (TURVD) algorithm which enables updating their structure by recycling their previous decomposition instead of decomposing the image matrix from the beginning. Specifically, we show an efficient algorithm for updating and downdating the TURVD simultaneously, followed by the rank-one update to the TURVD while tracking the decomposition error accurately and adjusting the truncation level adaptively. Experiments show that the proposed algorithm produces no-meaningful differences but much faster execution speed compared to the typical algorithms in template tracking applications, thereby maintaining a good approximation for the principal components.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2341-2348
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• 2009

An intrusion detection technique based on host consider system call sequence or system call arguments. These two ways are suitable when system call sequence or order and length of system call arguments are out of order. However, there are two disadvantages which a false positive rate and a false negative rate are high. In this paper we propose the T-N2SCD detection model based on Time Window in order to reduce false positive rate and false negative rate. Data for using this experiment is provided from DARPA. As experimental results, the proposed model showed that the false positive rate and the false negative rate are lowest at an interval of 1000ms than at different intervals.

• Korean Journal of Microbiology
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• v.34 no.1_2
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• pp.58-63
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• 1998

Fragment assembly problem is to reconstruct DNA sequence contigs from a collection of fragment sequences. We have developed an efficient X-window program, XFAP, for assembling DNA fragments. In the XFAP, the dimer frequency comparison method is used to quickly eliminate pairs of fragments that can not overlap. This method takes advantage of the difference of dimer frequencies within the minimum acceptable overlap length in each fragment pair. Hirschberg algorithm is applied to compute the maximal-scoring overlapping alignment in linear space. The perfomance of XFAP was tested on a set of DNA fragment sequences extracted from long DNA sequences of GenBank by a fragmentation program and showed a great improvement in execution time, especially as the number of fragments increases.

• Journal of KIISE:Databases
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• v.34 no.2
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• pp.119-132
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• 2007

In molecular biology, approximate subsequence search is one of the most important operations. In this paper, we propose an accurate and efficient method for approximate subsequence search in large DNA databases. The proposed method basically adopts a binary trie as its primary structure and stores all the window subsequences extracted from a DNA sequence. For approximate subsequence search, it traverses the binary trie in a breadth-first fashion and retrieves all the matched subsequences from the traversed path within the trie by a dynamic programming technique. However, the proposed method stores only window subsequences of the pre-determined length, and thus suffers from large post-processing time in case of long query sequences. To overcome this problem, we divide a query sequence into shorter pieces, perform searching for those subsequences, and then merge their results. To verify the superiority of the proposed method, we conducted performance evaluation via a series of experiments. The results reveal that the proposed method, which requires smaller storage space, achieves 4 to 17 times improvement in performance over the suffix tree based method. Even when the length of a query sequence is large, our method is more than an order of magnitude faster than the suffix tree based method and the Smith-Waterman algorithm.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.513-520
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• 2006

In this paper, we propose a novel real-time frame-layer rate control algorithm using sliding window method for low bit rate video coding. The proposed rate control method performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. A new frame-layer rate-distortion model is derived, and a non-iterative optimization method is used for low computational complexity. In order to reduce the quality fluctuation, we use a sliding window scheme which does not require the pre-analysis process. Therefore, the proposed algorithm does not produce time delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better visual and PSNR performance than the existing TMN8 rate control method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10A
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• pp.949-957
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• 2005

In this paper, the performances of a single-user DS-UWB system applying two simple proposed channel estimation schemes are introduced, according to the newly updated DS-UWB PHY Layer standard from IEEE P802.15.3a. The performances of error control coding, different combining schemes in selective Rake receiver for DS-UWB system are analyzed. Both of the two channel estimation schemes using data-independent structure work well in DS-UWB system with few pilot bits. For the purpose of channel estimation and reduces the number of pilot bits, we apply a pilot symbol spreaded with $2{^8}-1\;or\;2{^9}-1$ periods of m-sequence for different channel estimation schemes.

• Genomics & Informatics
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• v.8 no.1
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• pp.58-61
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• 2010

CpG is the pair of nucleotides C and G, appearing successively, in this order, along one DNA strand. It is known that due to biochemical considerations CpG is relatively rare in most DNA sequences. However, in particular subsequences, which are a few hundred to a few thousand nucleotides long, the couple CpG is more frequent. These subsequences, called CpG islands, are known to appear in biologically more significant parts of the genome. The ability to identify CpG islands along a chromosome will therefore help us spot its more significant regions of interest, such as the promoters or 'start' regions of many genes. In this respect, I developed the CpG islands search tool, CpG Islands Detector, which was implemented in JAVA to be run on any platform. The window-based graphical user interface of CpG Islands Detector may facilitate the end user to employ this tool to pinpoint CpG islands in a genomic DNA sequence. In addition, this tool can be used to highlight potential genes in genomic sequences since CpG islands are very often found in the 5' regions of vertebrate genes.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1392-1405
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• 2019

The cathode voltage of aluminum electrolytic cell is relatively stable under normal conditions and fluctuates greatly when it has an anomaly. In order to detect the abnormal range of cathode voltage, an anomaly detection algorithm based on sliding window was proposed. The algorithm combines the time series segmentation linear representation method and the k-nearest neighbor local anomaly detection algorithm, which is more efficient than the direct detection of the original sequence. The algorithm first segments the cathode voltage time series, then calculates the length, the slope, and the mean of each line segment pattern, and maps them into a set of spatial objects. And then the local anomaly detection algorithm is used to detect abnormal patterns according to the local anomaly factor and the pattern length. The experimental results showed that the algorithm can effectively detect the abnormal range of cathode voltage.