• Proceedings of the KSR Conference
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• 2003.10b
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• pp.241-246
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• 2003

In this paper, necessity and application scope of the risk-analysis D/B which assesses the railway safety condition has been introduced. In addition, normalization of analysis work, which is one of the DB development procedures has been conducted. And the structure of accident data management has been introduced through the analysis on the classification scheme used in Korea. Also the improvement of railway accident classification and management scheme which is necessary to accident risk assesment has been presented by these procedures.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1137-1142
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• 2010

This paper studied the speech parameters less affected by the human emotion for the development of the robust speech recognition system. For this purpose, the effect of emotion on the speech recognition system and robust speech parameters of speech recognition system were studied using speech database containing various emotions. In this study, mel-cepstral coefficient, delta-cepstral coefficient, RASTA mel-cepstral coefficient and frequency warped mel-cepstral coefficient were used as feature parameters. And CMS (Cepstral Mean Subtraction) method were used as a signal bias removal technique. Experimental results showed that the HMM based speaker independent word recognizer using vocal tract length normalized mel-cepstral coefficient, its derivatives and CMS as a signal bias removal showed the best performance of 0.78% word error rate. This corresponds to about a 50% word error reduction as compare to the performance of baseline system using mel-cepstral coefficient, its derivatives and CMS.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.869-870
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• 2008

Illumination variation is the most significant factor affecting face recognition rate. In this paper, we propose adaptive smoothing based on combined most significant bit (CMSB) - plane and local entropy for robust face recognition in varying illumination. Illumination normalization is achieved based on Retinex method. The proposed method has been evaluated based on the CMU PIE database by using Principle Component Analysis (PCA).

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.11a
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• pp.253-256
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• 2009

To the success of the megaproject including various and complex facilities, it is needed to establish a database system. Developments in data collection, storage and extracting technology have enabled iPMIS to manage various and complex information about cost and time. Especially, when we consider that both the go and no go decision in feasibility, Cost is an important and clear criteria in megaproject. Thus, Cost data modeling is the basis of the system and is necessary process. This research is focus on the structure and definition about CBS data which is collected from sites. We used four tools which are Function Analysis in VE, Casual loop Diagram in System Dynamics, Decision Tree in Data-mining, and Normalization in SQL to identify its cause and effect relationship on CBS data. Cost data modeling provide iPMIS with helpful guideline.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.445-458
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• 2012

Image feature extraction is one of the basic works for biometric analysis. This paper presents the novel concept of application of ridgelets for iris recognition systems. Ridgelet transforms are the combination of Radon transforms and Wavelet transforms. They are suitable for extracting the abundantly present textural data that is in an iris. The technique proposed here uses the ridgelets to form an iris signature and to represent the iris. This paper contributes towards creating an improved iris recognition system. There is a reduction in the feature vector size, which is 1X4 in size. The False Acceptance Rate (FAR) and False Rejection Rate (FRR) were also reduced and the accuracy increased. The proposed method also avoids the iris normalization process that is traditionally used in iris recognition systems. Experimental results indicate that the proposed method achieves an accuracy of 99.82%, 0.1309% FAR, and 0.0434% FRR.

• Clean Technology
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• v.21 no.1
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• pp.33-38
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• 2015

In this research, life cycle inventory database (LCI DB) was developed for liquid CO₂ employing life cycle assessment (LCA) methodology. As are result of characterization and normalization process, production of liquid CO₂ puts on environmental impact in the order of resource depletion, global warming, acidification, eutrophication and photochemical oxidation, and among a wide variety of input, electricity contributes in most of the impact categories. Air emission plays a key role in the acidification and eutrophication while ammonia affects most on the ozone depletion. It is anticipated that development of liquid CO₂ LCI DB makes it possible for national environmental strategies to be more activated including environmental labeling scheme.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.61-74
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• 2004

In this paper, a contort- and speaker-dependent cepstrum extraction method and a channel normalization method for minimizing the loss of speaker characteristics in the cepstrum were proposed for a robust speaker recognition system over the channel. The proposed extraction method creates a cepstrum based on the pitch synchronous analysis using the inherent pitch of the speaker. Therefore, the cepstrum called the 〃pitch synchronous cepstrum〃 (PSC) represents the impulse response of the vocal tract more accurately in voiced speech. And the PSC can compensate for channel distortion because the pitch is more robust in a channel environment than the spectrum of speech. And the proposed channel normalization method, the 〃formant-broadened pitch synchronous CMS〃 (FBPSCMS), applies the Formant-Broadened CMS to the PSC and improves the accuracy of the intraframe processing. We compared the text-independent closed-set speaker identification on 56 females and 112 males using TIMIT and NTIMIT database, respectively. The results show that pitch synchronous km improves the error reduction rate by up to 7.7% in comparison with conventional short-time cepstrum and the error rates of the FBPSCMS are more stable and lower than those of pole-filtered CMS.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.9-16
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• 2006

In this paper, the acoustic model output of CSR(Continuous Speech Recognition) was used to analyze news data News database used in this experiment was consisted of 2,093 articles. Due to the low efficiency of language model, conventional Korean CSR is not appropriate to the analysis of news data. This problem could be handled successfully by introducing post-processing work of recognition result of acoustic model. The acoustic model more robust than language model in Korean environment. The result of post-processing work was made into KIF(Keyword information file). When threshold of acoustic model's output level was 100, 86.9% of whole target morpheme was included in post-processing result. At the same condition, applying length information based normalization, 81.25% of whole target morpheme was recognized. The purpose of normalization was to compensate long-length morpheme. According to experiment result, 75.13% of whole target morpheme was recognized KIF(314MB) had been produced from original news data(5,040MB). The decrease rate of absolute information met was approximately 93.8%.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.681-686
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• 2012

This paper studied the speech parameters less affected by the human emotion for the development of the robust emotional speech recognition system. For this purpose, the effect of emotion on the speech recognition system and robust speech parameters of speech recognition system were studied using speech database containing various emotions. In this study, mel-cepstral coefficient, delta-cepstral coefficient, RASTA mel-cepstral coefficient, root-cepstral coefficient, PLP coefficient and frequency warped mel-cepstral coefficient in the vocal tract length normalization method were used as feature parameters. And CMS (Cepstral Mean Subtraction) and SBR(Signal Bias Removal) method were used as a signal bias removal technique. Experimental results showed that the HMM based speaker independent word recognizer using frequency warped RASTA mel-cepstral coefficient in the vocal tract length normalized method, its derivatives and CMS as a signal bias removal showed the best performance.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.903-917
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• 1995

In most database systems images have been indexed indirectly using related texts such as captions, annotations and image attributes. But there has been an increasing requirement for the image database system supporting the storage and retrieval of images directly by content using the information contained in the images. There has been a few indexing methods based on contents. Among them, Pertains proposed an image indexing method considering spatial relationships and properties of objects forming the images. This is the expansion of the other studies based on '2-D string. But this method needs too much storage space and lacks flexibility. In this paper, we propose a more flexible index structure based on kd-tree using paging techniques. We show an example of extracting keys using normalization from the from the raw image. Simulation results show that our method improves in flexibility and needs much less storage space.