• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.323-326
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• 1999

This paper describes a point matching method that is based on an expansion of the electromagnetic field in terms of a series of Bessel and modified Bessel functions multiplied by trigonometric functions. In this method, the electric and magnetic fields inside the waveguide core are matched to those outside the core at matching points on the boundary to yield matrix equations. As an example applying this method, the paper presents the results of the computation in the form of curves of the propagation constants in a semicircular optical waveguide, be formed by annealing for reduced insertion(radiation) loss when connected to optical fiber. The propagation curves are presented in a form of refractive index independent. Also, it presents relative energy distributions between inside the core and outside the core of various modes and presents field distributions.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1960-1963
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• 2003

For applications such as video surveillance and human computer interface, we propose an efficiently integrated method to detect and track faces. Various visual cues are combined to the algorithm: motion, skin color, global appearance and facial pattern detection. The ICA (Independent Component Analysis)-SVM (Support Vector Machine based pattern detection is performed on the candidate region extracted by motion, color and global appearance information. Simultaneous execution of detection and short-term tracking also increases the rate and accuracy of detection. Experimental results show that our detection rate is 91％ with very few false alarms running at about 4 frames per second for 640 by 480 pixel images on a Pentium IV 1㎓.

• Journal of Life Science
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• v.9 no.5
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• pp.531-536
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• 1999

As an attempt to preserve resources in marine biological organisms, we first constructed a cDNA library from the red alga Porphyra yezoensis. The library construction method from P. yezoensis consists of three steps; those include protoplast presparation, RNA isolation, and phage library construction. Protoplast was prepared in order to remove much of the carbohydrate compounds which are characteristics of algal cell walls. Carbohydrate contamination in the purified RNA may inhibit further enzyme reactions, those carbohydrates should be removed. RNA samples prepared from protoplast still seemed to contain residual amount of carbohydrate because mRNA isolation with conventional method failed. We therefore developed a method with Poly ATtract mRNA isolation system. The constructed phage library was tested by analyzing cDNA insert in phage vector from randomly picked ten independent white plagues. All of the phages contained cDNA inserts with sizes ranging 0.5kb and 2.0kb.

• Phonetics and Speech Sciences
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• v.10 no.2
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• pp.7-14
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• 2018

The paper investigates the acoustic characteristics of English fricatives in the TIMIT corpus, with a special focus on the role of voicing in rendering fricatives in American English. The TIMIT database includes 630 talkers and 2,342 different sentences, and comprises more than five hours of speech. Acoustic analyses are conducted in the domain of spectral and temporal properties by treating gender, voicing, and place of articulation as independent factors. The results of the acoustic analyses revealed that acoustic signals interact in a complex way to signal the gender, place, and voicing of fricatives. Classification experiments using a multiclass support vector machine (SVM) revealed that 78.7% of fricatives are correctly classified. The majority of errors stem from the misclassification of /θ/ as [f] and /ʒ/ as [z]. The average accuracy of gender classification is 78.7%. Most errors result from the classification of female speakers as male speakers. The paper contributes to the understanding of the effects of voicing and gender on fricatives in a large-scale speech corpus.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.898-902
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• 2003

In this paper we proposes a new technique for identification of breast cancer by classification of proteome pattern generated from 2-D polyacrylamide gel electrophoresis (2-D PAGE) and development of cancer diagnosis system : HABIT. Proteome patterns reflect the underlying pathological state of a human organ and it is believed that the anomalies or diseases of human organs are identified by the analysis or classification of the patterns. Proteome patterns consist of quantitative information of the spots such as their size, position, and density in the proteome image produced from 2-D PAGE, for the Image mining of proteome pattern, SVM(support vector machine) and GA(genetic algorithm) are used to generate a decision model for the identification of breast cancer The decision model was then used to classify an independent set of test proteome patterns into the affecter and unaffecter classes. The proposed technique was tested by actual clinical test samples and showed a good performance of a hit ratio of 90%.

• Geomechanics and Engineering
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• v.29 no.3
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• pp.219-228
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• 2022

The most widely used parameter to represent rock abrasiveness is the Cerchar abrasivity index (CAI). The CAI value can be applied to predict wear in TBM cutters. It has been extensively demonstrated that the CAI is affected significantly by cementation degree, strength, and amount of abrasive minerals, i.e., the quartz content or equivalent quartz content in rocks. The relationship between the properties of rocks and the CAI is investigated in this study. A database comprising 223 observations that includes rock types, uniaxial compressive strengths, Brazilian tensile strengths, equivalent quartz contents, quartz contents, brittleness indices, and CAIs is constructed. A linear model is developed by selecting independent variables while considering multicollinearity after performing multiple regression analyses. Machine learning-based regression methods including support vector regression, regression tree regression, k-nearest neighbors regression, random forest regression, and artificial neural network regression are used in addition to multiple linear regression. The results of the random forest regression model show that it yields the best prediction performance.

• International Journal of Industrial Entomology and Biomaterials
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• v.2 no.1
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• pp.19-26
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• 2001

Transformed Spodoptera frugiperda (Sf9) cells expressing baculovirus very late factor (VLF-1) were constructed by using Autograha nuclear polyhedrosis virus (AcNPV) immediate earthy gene (ie1). Neomycin-resistance gene as a selectable marker was introduced under the control of AcNPV ie1 promoter, and Bombyx mori nuclear polyhedrosis (BmNPV-K1) vlf-1 gene was introduced under the control of the Drosophila heat shock protein gene (hspr70) promoter to yield dual expression plasmid with two independent transcription units. It was transfected into Sf9 cells and cell clones expressing vlf-1 were selected by G4l8 treatment. Genomic DNA from transformed cells was isolated and integration of AcNPV iel harboring vlf-1 was confirmed by PCR using AcNPV iel-specific primers and Southern blot analysis. The transformed cells expressing VLF-1 in an infection-independent manner expressed foreign gene product of recombinant baculovirus in the earlier stage of infection compared with control Sf9 cells. These results suggest the possible to develop highly efficient transformed insect cells for baculovirus expression vector system.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2
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• pp.96-100
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• 2006

Kim et al. Proposed Normalized Confidence Measure (NCM) [1-2] and it was successfully used for rejecting mis-recognized words in isolated word recognition. However their experiments were performed on the fixed word speech recognition. In this Paper we apply NCM to the domain of vocabulary independent speech recognition (VISP) and shows the rejection Performance of NCM in VISP. Specialty we Propose vector quantization (VQ) based method for overcoming the problem of unseen triphones. It is because NCM uses the statistics of triphone confidence in the case of triphone-based normalization. According to speech recognition experiments Phone-based normalization method shows better results than RLJC[3] and also triphone-based normalization approach. This results are different with those of Kim et al [1-2]. Concludingly the Phone-based normalization shows robust Performance in VISP domain.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.1
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• pp.41-50
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• 2024

Korea is facing a significant problem with historically low fertility rates, which is becoming a major social issue affecting the economy, labor force, and national security. This study analyzes the factors contributing to the regional gap in fertility rates and derives policy implications. The government and local authorities are implementing a range of policies to address the issue of low fertility. To establish an effective strategy, it is essential to identify the primary factors that contribute to regional disparities. This study identifies these factors and explores policy implications through machine learning and explainable artificial intelligence. The study also examines the influence of media and public opinion on childbirth in Korea by incorporating news and online community sentiment, as well as sentiment fear indices, as independent variables. To establish the relationship between regional fertility rates and factors, the study employs four machine learning models: multiple linear regression, XGBoost, Random Forest, and Support Vector Regression. Support Vector Regression, XGBoost, and Random Forest significantly outperform linear regression, highlighting the importance of machine learning models in explaining non-linear relationships with numerous variables. A factor analysis using SHAP is then conducted. The unemployment rate, Regional Gross Domestic Product per Capita, Women's Participation in Economic Activities, Number of Crimes Committed, Average Age of First Marriage, and Private Education Expenses significantly impact regional fertility rates. However, the degree of impact of the factors affecting fertility may vary by region, suggesting the need for policies tailored to the characteristics of each region, not just an overall ranking of factors.

• KIEE International Transactions on Electrophysics and Applications
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• v.2C no.5
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• pp.246-252
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• 2002

Two-dimensional steady state simulations of planar type radio frequency inductively coupled plasma (RFICP) have been performed. The characteristics of RFICP were investigated in terms of power transfer efficiency, equivalent circuit analysis, spatial distribution of plasma density and electron temperature. Plasma density and electron temperature were determined from the equations of ambipolar diffusion and energy conservation. Joule heating, ionization, excitation and elastic collision loss were included as the source terms of the electron energy equation. The electromagnetic field was calculated from the vector potential formulation of ampere's law. The peak electron temperature decreases from about 4eV to 2eV as pressure increases from 5 mTorr to 100 mTorr. The peak density increases with increasing pressure. Electron temperatures at the center of the chamber are almost independent of input power and electron densities linearly increase with power level. The results agree well with theoretical analysis and experimental results. A single turn, edge feeding antenna configuration shows better density uniformity than a four-turn antenna system at relatively low pressure conditions. The thickness of the dielectric window should be minimized to reduce power loss. The equivalent resistance of the system increases with both power and pressure, which reflects the improvement of power transfer efficiency.