• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.263-269
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• 2012

Code-Division Multiple-Access(CDMA) allows several users simultaneous access to a common channel by assigning a distinct pseudonoise sequence called spectrum code to each user. Each user in a CDMA system uses a assigned spectrum code to modulate their signal. Choosing the codes used to modulate the signal is very important in the performance of CDMA systems. The best performance will occur when there is good separation between the signal of a desired user and the signals of other users. The receiver synchronizes the code to recover the data. The use of an independent code allows multiple users to access the same frequency band at the same time. In this paper we propose a generalized model of non-linear binary sequence using trace function and analyze cross-correlation of these sequences. These sequences with low correlation, large linear span and large family size, in a direct-sequence spread spectrum communication system, help to minimize multiple access interference, increase security degree of system and enlarge user number.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.11
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• pp.637-644
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• 2014

This paper investigates the detection performance of fault location using STDR(sequence time domain reflectometry) and SSTDR(spread spectrum time domain reflectometry) with various length and types of sequences, and then, proposes an improved detection technique by eliminating the injected signal in SSTDR. The detection error rates are compared and analyzed in power line channel model with various fault locations, fault types, and spreading sequences such as m-sequence, binary Barker sequence, and 4-phase Frank sequence. It is shown that the proposed technique is able to improve the detection performance obviously when the reflected signal is weak or the fault location is extremely close.

• Korean Journal of Cognitive Science
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• v.18 no.1
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• pp.1-14
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• 2007

In a goal-oriented dialogue, speakers' intentions can be represented by domain actions that consist of pairs of a speech act and a concept sequence. Therefore, if we plan to implement an intelligent dialogue system, it is very important to correctly infer the domain actions from surface utterances. In this paper, we propose a statistical model to determine speech acts and concept sequences using conditional random fields at the same time. To avoid biased learning problems, the proposed model uses low-level linguistic features such as lexicals and parts-of-speech. Then, it filters out uninformative features using the chi-square statistic. In the experiments in a schedule arrangement domain, the proposed system showed good performances (the precision of 93.0% on speech act classification and the precision of 90.2% on concept sequence classification).

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.3
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• pp.273-279
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• 2015

A zero vector selection method to reduce switching losses for model predictive control (MPC) of voltage source inverter is proposed. A conventional MPC of voltage source inverter has not been proposed, and a method to select the redundancy of the zero vector is required for this study. In this paper, the redundancy of the zero vectors is selected with generating a zero sequence voltage to reduce switching losses. The zero vector of 2-level inverter is determined by determining sign of the zero sequence voltage. In the proposed method, the quality of the current is retained and switching loss can be reduced compared with the conventional method. This result was verified by P-sim simulation and experiments.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2001.06a
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• pp.77-80
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• 2001

A variety of different methods to generate diverse proteins, including random mutagenesis and recombination, are currently available, and most of them accumulate the mutations on the target gene of a protein, whose sequence space remains unchanged. On the other hand, a pool of diverse genes, which is generated by random insertions, deletions, and exchange of the homologous domains with different lengths in the target gene, would present the protein lineages resulting in new fitness landscapes. Here we report a method to generate a pool of protein variants with different sequence spaces by employing green fluorescent protein (GFP) as a model protein. This process, designated functional salvage screen (FSS), comprises the following procedures： a defective GFP template expressing no fluorescence is firstly constructed by genetically disrupting a predetermined region(s) of the protein, and a library of GFP variants is generated from the defective template by incorporating the randomly fragmented genomic DNA from E. coli into the defined region(s) of the target gene, followed by screening of the functionally salvaged, fluorescence-emitting GFPs. Two approaches, sequence-directed and PCR-coupled methods, were attempted to generate the library of GFP variants with new sequences derived from the genomic segments of E. coli. The functionally salvaged GFPs were selected and analyzed in terms of the sequence space and functional property. The results demonstrate that the functional salvage process not only can be a simple and effective method to create protein lineages with new sequence spaces, but also can be useful in elucidating the involvement of a specific region(s) or domain(s) in the structure and function of protein.

• Phonetics and Speech Sciences
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• v.10 no.1
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• pp.39-48
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• 2018

A typical statistical parametric speech synthesis (text-to-speech, TTS) system consists of separate modules, such as a text analysis module, an acoustic modeling module, and a speech synthesis module. This causes two problems: 1) expert knowledge of each module is required, and 2) errors generated in each module accumulate passing through each module. An end-to-end TTS system could avoid such problems by synthesizing voice signals directly from an input string. In this study, we implemented an end-to-end Korean TTS system using Google's Tacotron, which is an end-to-end TTS system based on a sequence-to-sequence model with attention mechanism. We used 4392 utterances spoken by a Korean female speaker, an amount that corresponds to 37% of the dataset Google used for training Tacotron. Our system obtained mean opinion score (MOS) 2.98 and degradation mean opinion score (DMOS) 3.25. We will discuss the factors which affected training of the system. Experiments demonstrate that the post-processing network needs to be designed considering output language and input characters and that according to the amount of training data, the maximum value of n for n-grams modeled by the encoder should be small enough.

• Korean Journal of Cognitive Science
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• v.18 no.2
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• pp.179-191
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• 2007

In a goal-oriented dialogue, spoken' intentions can be represented by domain actions that consist of pairs of a speech art and a concept sequence. The domain action prediction of user's utterance is useful to correct some errors that occur in a speech recognition process, and the domain action prediction of system's utterance is useful to generate flexible responses. In this paper, we propose a model to predict a domain action of the next utterance using a neural network. The proposed model predicts the next domain action by using a dialogue history vector and a current domain action as inputs of the neural network. In the experiment, the proposed model showed the precision of 80.02% in speech act prediction and the precision of 82.09% in concept sequence prediction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.76-77
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• 2022

In this paper, we propose a method to stabilize the 3D pose estimation result of a 3D volumetric data sequence by matching the pose estimation results from multi-view. Draw a circle centered on the volumetric model and project the model from the viewpoint at regular intervals. After performing Openpose 2D pose estimation on the projected 2D image, the 2D joint is matched to localize the 3D joint position. The tremor of 3D joints sequence according to the angular spacing was quantified and expressed in graphs, and the minimum conditions for stable results are suggested.

• Molecules and Cells
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• v.22 no.3
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• pp.300-307
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• 2006

Brassica rapa ssp. pekinensis (Chinese cabbage) is an economically important crop and a model plant for studies on polyploidization and phenotypic evolution. To gain an insight into the structure of the B. rapa genome we analyzed 12,017 BAC-end sequences for the presence of transposable elements (TEs), SSRs, centromeric satellite repeats and genes, and similarity to the closely related genome of Arabidopsis thaliana. TEs were estimated to occupy 14% of the genome, with 12.3% of the genome represented by retrotransposons. It was estimated that the B. rapa genome contains 43,000 genes, 1.6 times greater than the genome of A. thaliana. A number of centromeric satellite sequences, representing variations of a 176-bp consensus sequence, were identified. This sequence has undergone rapid evolution within the B. rapa genome and has diverged among the related species of Brassicaceae. A study of SSRs demonstrated a non-random distribution with a greater abundance within predicted intergenic regions. Our results provide an initial characterization of the genome of B. rapa and provide the basis for detailed analysis through whole-genome sequencing.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1132-1139
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• 2006

Railway risk is evaluated by a method of linking event trees and fault trees as the general PSA(Probabilistic Safety Assessment) model for the risk assessment of complex systems. Accident scenarios causing undesirable events are modeled by event trees comprised of several accident sequences. Each branch located in the accident progression of the event tree is modeled by an fault tree or can be represented by some value too simply. We usually evaluate the frequency of the whole sequence by adding them after calculating the frequency of each sequence at a time. However, since there are quite a number of event trees and fault trees in the railway risk assessment model, the number of sequence to evaluate increases and preparation for the risk assessment costs much time all the more. Also, it may induce errors when analysts perform the work of quantification. Therefore, the systematic maintenance and control of event trees and fault trees will be essential for the railway risk assessment. In this paper we introduce an integrated assessment method using one-top model and develop a risk assessment tool for the maintenance and control of the railway risk model.