• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.336-340
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• 2003

The frame synchronization should be acquired before performing other data-aided receiving algorithms, such as data-aided channel equalizing, beam-forming and phase, symbol timing, and frequency synchronizing, since all of them are using preamble or training sequence to estimate the amount of error from the received signal. In this paper, we present a new frame synchronization scheme for underwater ultrasonic image burst transmission system, which computes the correlation between received symbol sequence and one CAZAC sequence, composed of the latter half of the first CAZAC sequence of preamble and the first half of the second CAZAC sequence of preamble and then compares a threshold value. If the correlation value is bigger than the threshold value, the frame detector determines that the frame synchronization is achieved at that sample.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.605-608
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• 1999

In this paper, we proposed several scene analysis algorithms. These algorithms using image difference and histogram operate on the sequence of DC coefficient which is extracted from Motion JPEG or MPEG without full-frame decompression. Since DC sequence has the most information of full frame while it has reduced data. Experimental results show less than 1/64 of full frame analysing complexity and exactly analyze scene changes and extract key frames.

• Kyungpook Mathematical Journal
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• v.56 no.3
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• pp.793-806
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• 2016

G-vector-valued sequence space frames and g-Banach frames for Banach spaces are introduced and studied in this paper. Also, the concepts of duality mapping and ${\beta}$-dual of a BK-space are used to define frame mapping and synthesis operator of these frames, respectively. Finally, some results regarding the existence of g-vector-valued sequence space frames and g-Banach frames are obtained. In particular, it is proved that if X is a separable Banach space and Y is a Banach space with a Schauder basis, then there exist a Y-valued sequence space $Y_v$ and a g-Banach frame for X with respect to Y and $Y_v$.

• The Journal of the Acoustical Society of Korea
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• v.24 no.8
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• pp.462-468
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• 2005

In this paper, we present a frame synchronization scheme for high oversampling rate based QPSK receiver system in the underwater acoustic burst transmission. The proposed frame synchronization scheme determines the frame synchronization by comparing a threshold value with the correlation between the received symbol sequence and rotated 16-symbol length CAZAC sequence, which is made by dividing into two 8-symbol length sequences and then concatenating the latter sequence and the former one. If the correlation value is bigger than the threshold value, the frame detector determines that the frame synchronization is achieved at that sample. Also, the approximated performance of designed frame detector is derived and it is well fit the simulated result.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.195-196
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• 2006

Frame synchronization is an critical factor for an effective operation of OFDM (orthogonal frequency division multiplexing) based communication systems. In this paper, we present and analyze an efficient frame synchronization method based on m-sequence for OFDM-based mobile multimedia communication systems. The cyclic extension preceding OFDM frames is of decisive importance for this method. The m-sequence is added directly to cyclic extension signal in the time domain. By utilizing the autocorrelation characteristics of m-sequence, efficient frame synchronization can be achieved. And we also consider frequency offset estimation simultaneously. The proposed frame synchronization method can be applied to the OFDM-based mobile multimedia communication systems.

• International Journal of Contents
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• v.12 no.1
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• pp.1-5
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• 2016

To manipulate large video contents, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-wise user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm that extracts key frames using color histograms and matches the video sequences using edge features. To effectively match video sequences with a low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with real sequence show that the proposed video sequence matching algorithm using edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.3
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• pp.1-5
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• 2007

We give an elementary proof of a necessary and sufficient condition for integer translates {${\phi}(t-{\alpha})\;:\;{\alpha}{\in}{\mathbb{Z}}^d$} of ${\phi}$(t) in $L^2({\mathbb{R}}^d)$ to be a frame sequence.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.209-215
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• 2014

Sequence tagging is the task of predicting frame-wise labels for a given input sequence and has important applications to diverse domains. Conventional methods such as maximum likelihood (ML) learning matches global features in empirical and model distributions, rather than local features, which directly translates into frame-wise prediction errors. Recent probabilistic sequence models such as conditional random fields (CRFs) have achieved great success in a variety of situations. In this paper, we introduce a novel discriminative CRF learning algorithm to minimize local feature mismatches. Unlike overall data fitting originating from global feature matching in ML learning, our approach reduces the total error over all frames in a sequence. We also provide an efficient gradient-based learning method via gradient forward-backward recursion, which requires the same computational complexity as ML learning. For several real-world sequence tagging problems, we empirically demonstrate that the proposed learning algorithm achieves significantly more accurate prediction performance than standard estimators.

• Proceedings of the Botanical Society of Korea Conference
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• 1999.04a
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• pp.18-18
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• 1999

We characterized a cDNA clone for a low molecular weight heat-shock protein (LMW HSP) from tobacco named TLHS-l. Nucleotide sequence determination of TLHS-1 identified an open reading frame for 159 amino acids. To the upstream of the open reading frame, a sequence of 124 nucleotides was determined. To the 3' downstream of the open reading frame, 212 nucleotides were identified which carried poly(A)-tail. Comparison of the open reading frame and hydropathy plot of TLHS-1 with the previously reported class I LMW HSPs showed high identity which classified TLHS-1 as a class I LMW HSP cDNA clone. We proposed that there are six consensus regions in class I LMW HSPs. RNA blot hybridization for TLHS-1 showed a typical expression pattern of heat-shock-inducible gene from three common tobacco cultivars. The open reading frame of TLHS-1 was overexpressed in Escherichia coli. TLHS-1 protein confers thermal protection of other proteins in vitro and in vivo. Thermal induced aggregation of citrate synthase was reduced by purified TLHS-1 protein, and thermal death rate at $50^{\circ}C$ was reduced in E. coli expressing TLHS-l. From these data, we can expect that TLHS-1 acts as a molecular chaperone.perone.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.45-52
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• 2004

According tothe development of digital media technologies various algorithms for video sequence matching have been proposed to match the video sequences efficiently. A large number of video sequence matching methods have focused on frame-wise query, whereas a relatively few algorithms have been presented for video sequence matching or video shot matching. In this paper, we propose an efficientalgorithm to index the video sequences and to retrieve the sequences for video sequence query. To improve the accuracy and performance of video sequence matching, we employ the Cauchy function as a similarity measure between histograms of consecutive frames, which yields a high performance compared with conventional measures. The key frames extracted from segmented video shots can be used not only for video shot clustering but also for video sequence matching or browsing, where the key frame is defined by the frame that is significantly different from the previous fames. Several key frame extraction algorithms have been proposed, in which similar methods used for shot boundary detection were employed with proper similarity measures. In this paper, we propose the efficient algorithm to extract key frames using the cumulative Cauchy function measure and. compare its performance with that of conventional algorithms. Video sequence matching can be performed by evaluating the similarity between data sets of key frames. To improve the matching efficiency with the set of extracted key frames we employ the Cauchy function and the modified Hausdorff distance. Experimental results with several color video sequences show that the proposed method yields the high matching performance and accuracy with a low computational load compared with conventional algorithms.