• 한국음향학회지
• /
• 제18권8호
• /
• pp.75-83
• /
• 1999

본 논문에서는 음성합성의 억양 제어를 위한 새로운 F0 궤적 모델을 제안한다. 제안한 모델은 발성된 문장의 F0 궤적을 중첩가산되는 사건들로 분해하고, 각 사건들을 가우시안 종모양의 사건함수로 모델링한다. 그리고 제안한 모델을 위한 파라미터 추정 알고리즘을 제시한다. 제안한 모델은 특정한 음운론적 지식에 기반하지 않았으며, F0 궤적의 분석단계와 합성단계에 모두 사용 가능하다. 제안한 모델의 성능평가를 위해 다양한 장르에서 추출한 여러 형태의 500문장의 코퍼스를 구축하고, 이를 전문 아나운서에게 발성하게 하여 구축한 음성코퍼스로 실험한 결과, 원음성의 F0 궤적과 제안한 모델에 의해 합성된 F0 궤적의 평균 제곱 오류근이 7.87Hz이었다.

• The Journal of Asian Finance, Economics and Business
• /
• 제7권11호
• /
• pp.83-93
• /
• 2020

This empirical research aims to modeling and improving the forecasting accuracy of the volatility pattern by employing the Saudi Arabia stock market (Tadawul)by studying daily closed price index data from October 2011 to December 2019 with a number of observations being 2048. In order to achieve significant results, this study employs many mathematical functions which are non-linear spectral model Maximum overlapping Discrete Wavelet Transform (MODWT) based on the best localized function (Bl14), autoregressive integrated moving average (ARIMA) model and generalized autoregressive conditional heteroskedasticity (GARCH) models. Therefore, the major findings of this study show that all the previous events during the mentioned period of time will be explained and a new forecasting model will be suggested by combining the best MODWT function (Bl14 function) and the fitted GARCH model. Therefore, the results show that the ability of MODWT in decomposition the stock market data, highlighting the significant events which have the most highly volatile data and improving the forecasting accuracy will be showed based on some mathematical criteria such as Mean Absolute Percentage Error (MAPE), Mean Absolute Scaled Error (MASE), Root Means Squared Error (RMSE), Akaike information criterion. These results will be implemented using MATLAB software and R- software.

• 한국자기공명학회논문지
• /
• 제22권4호
• /
• pp.82-90
• /
• 2018

The term "hangover" refers to symptoms such as headache, heartburn, nausea, and dizziness caused by acetaldehyde created through alcohol decomposition in the body after alcohol intake. Many scientists have conducted research on diverse drugs, foods, and medicinal herbs aimed at eliminating hangovers. However, research on metabolism to objectively verify or measure their effects on hangover symptoms has been lacking. Accordingly, in this study, deep sea water minerals were administered orally at varying concentrations to rats that consumed alcohol, and changes in the levels of amino acids in their bodies were measured using nuclear magnetic resonance spectroscopy to gauge the minerals' effects on hangover symptoms. Thus far, biochemical research on hangover cures has been confined to basic research measuring changes in the levels of alcohol dehydrogenase and acetaldehyde dehydrogenase as well as in the concentrations of ethanol, acetaldehyde, and acetate using spectroscopes such as enzyme-linked immunosorbent assay kits or gas chromatography-mass spectrometers. In comparison, this study presents pharmacokinetic research that simultaneously tracked biomaterials including amino acids and organic acids, metabolites associated with hangover, to clarify hangover mechanisms more specifically. In addition, this study examined hangover mechanisms without an external supply of tracked materials not overlapping with alcohol metabolism-related materials, such as external amino acids and sugars.

• 방송공학회논문지
• /
• 제18권3호
• /
• pp.481-490
• /
• 2013

본 논문에서는 실제 전장에서 전투수행 중인 병사의 개인화기 조준 능력 향상 관점에서 추적기법의 성능평가를 하였다. 실제 전장에서는 짧은 시간동안 전투를 하는 것뿐만 아니라 며칠에 걸쳐서 실시되는 경우도 있다. 이와 같이 장시간 지속되는 작전 중에서 다양한 요소에 의해서 지속적으로 병사의 신체능력이 감소된다. 이렇게 손실되는 신체능력을 보완하기 위하여 시각추적 기술을 화기의 조준경에 적용하여 적 병사 이동상황을 자동적으로 추적하고 이로 인해 감소된 조준능력을 향상시키기 위한 실험을 하였다. 최신영상 추적 기법들 중에서 최적의 것을 결정하기 위하여, 겹침 현상, 카메라 이동, 크기변화, 저대비 영상, 조명변화 등의 특징이 포함된 여러 실제 전장 영상으로 그 성능을 평가하였다. VTD (Visual Tracking Decomposition)[2]가 정확도에서 IVT (Incremental learning for robust Visual Tracking)[7]가 속도 평가에서 가장 우수하였으며 종합적으로는 MIL (Multiple Instance Learning)[1]이 가장 우수한 결과를 보여 주었다. 이러한 성능평가 결과는 시각추적기술이 적용된 조준경이 실제 전장에서 전투수행을 하면서 신체능력이 감소된 병사의 전투력을 보완할 가능성이 있다는 것을 보여 준다.

• 패션비즈니스
• /
• 제22권2호
• /
• pp.51-60
• /
• 2018

This research focuses on the development of upcycled denim fashion designs, whichis a more specific category within general upcycled fashion design. Characteristics of upcycled fashion design, which has been identified previously by researchers, include the following traits: environmentality, uniqueness, aesthetic appeal, availability, convertibility, and deconstructivity. The expression principles include recycling, substitution, recombination, and reduction. The result of the analysis of the denim fashion design characteristics, which is based on the theoretical analysis, has found. The external expression pattern consists of the deconstruction and reconstitution of materials, the avant-garde style and convertibility, the ability to mix and match materials and techniques, the production of zero waste, and the use of layering. The expression techniques used included decomposition, depaysement, weaving, cut-off, collage, assemblage, overlapping, connecting, attaching, and stitching. The inner meanings were identified as economicality through recycling, convertibility through rearranging, and the rarity and value of hand-made products. The result of the research applying the identified characteristics are as follows. First, developing and creating designs using modified denim and sub-materials with various expression patterns and techniques could provide completely new images unlike existing denim products. Second, modifying the details while maintaining the basic format of denim clothing could provide unique and new possibilities for upcycled denim fashion design. Third, environment-friendly models with creative designs were developed by recycling used denim materials. This reduced waste and energy while maximizing the use of resources. This study expects contribute to upcycled fashion design research by recognizing the unique characteristics and value of denim material.

• Smart Structures and Systems
• /
• 제17권2호
• /
• pp.209-230
• /
• 2016

The Canton Tower is a high-rise slender structure with a height of 610 m. A structural health monitoring system has been instrumented on the structure, by which data is continuously monitored. This paper presents an investigation on the identified modal properties of the Canton Tower using ambient vibration data collected during a whole day (24 hours). A recently developed Fast Bayesian FFT method is utilized for operational modal analysis on the basis of the measured acceleration data. The approach views modal identification as an inference problem where probability is used as a measure for the relative plausibility of outcomes given a model of the structure and measured data. Focusing on the first several modes, the modal properties of this supertall slender structure are identified on non-overlapping time windows during the whole day under normal wind speed. With the identified modal parameters and the associated posterior uncertainty, the distribution of the modal parameters in the future is predicted and assessed. By defining the modal root-mean-square value in terms of the power spectral density of modal force identified, the identified natural frequencies and damping ratios versus the vibration amplitude are investigated with the associated posterior uncertainty considered. Meanwhile, the correlations between modal parameters and temperature, modal parameters and wind speed are studied. For comparison purpose, the frequency domain decomposition (FDD) method is also utilized to identify the modal parameters. The identified results obtained by the Bayesian method, the FDD method and a finite element model are compared and discussed.

• 대한원격탐사학회지
• /
• 제21권3호
• /
• pp.189-211
• /
• 2005

This paper makes an effort to compare the recently evolved soft classification method based on Linear Spectral Mixture Modeling (LSMM) with the traditional hard classification methods based on Iterative Self-Organizing Data Analysis (ISODATA) and Maximum Likelihood Classification (MLC) algorithms in order to achieve appropriate results for mapping, monitoring and preserving valuable coastal wetland ecosystems of southern India using Indian Remote Sensing Satellite (IRS) 1C/1D LISS-III and Landsat-5 Thematic Mapper image data. ISODATA and MLC methods were attempted on these satellite image data to produce maps of 5, 10, 15 and 20 wetland classes for each of three contrast coastal wetland sites, Pitchavaram, Vedaranniyam and Rameswaram. The accuracy of the derived classes was assessed with the simplest descriptive statistic technique called overall accuracy and a discrete multivariate technique called KAPPA accuracy. ISODATA classification resulted in maps with poor accuracy compared to MLC classification that produced maps with improved accuracy. However, there was a systematic decrease in overall accuracy and KAPPA accuracy, when more number of classes was derived from IRS-1C/1D and Landsat-5 TM imagery by ISODATA and MLC. There were two principal factors for the decreased classification accuracy, namely spectral overlapping/confusion and inadequate spatial resolution of the sensors. Compared to the former, the limited instantaneous field of view (IFOV) of these sensors caused occurrence of number of mixture pixels (mixels) in the image and its effect on the classification process was a major problem to deriving accurate wetland cover types, in spite of the increasing spatial resolution of new generation Earth Observation Sensors (EOS). In order to improve the classification accuracy, a soft classification method based on Linear Spectral Mixture Modeling (LSMM) was described to calculate the spectral mixture and classify IRS-1C/1D LISS-III and Landsat-5 TM Imagery. This method considered number of reflectance end-members that form the scene spectra, followed by the determination of their nature and finally the decomposition of the spectra into their endmembers. To evaluate the LSMM areal estimates, resulted fractional end-members were compared with normalized difference vegetation index (NDVI), ground truth data, as well as those estimates derived from the traditional hard classifier (MLC). The findings revealed that NDVI values and vegetation fractions were positively correlated ($r^2$= 0.96, 0.95 and 0.92 for Rameswaram, Vedaranniyam and Pitchavaram respectively) and NDVI and soil fraction values were negatively correlated ($r^2$ =0.53, 0.39 and 0.13), indicating the reliability of the sub-pixel classification. Comparing with ground truth data, the precision of LSMM for deriving moisture fraction was 92% and 96% for soil fraction. The LSMM in general would seem well suited to locating small wetland habitats which occurred as sub-pixel inclusions, and to representing continuous gradations between different habitat types.

• 한국토양비료학회지
• /
• 제20권3호
• /
• pp.251-259
• /
• 1987

7종(種)의 식물성(植物性) 유기물질(有機物質)을 부숙(腐熟)시키면서 경시적(經時的)으로 시료(試料)를 채취(採取)한 후 부식산(腐植酸)을 추출정제(抽出精製)하여 IR Spectrum의 특성(特性)을 규명(糾明)하였다. 이 Spectrum과 분석(分析)을 행해 Total acidity, Total hydroxyls, Carboxyl groups, Phenolic hydroxyls, Alcoholic hydroxyls, Carbonyl groups 그리고 Quinones 등(等)의 산소함유작용기(酸素含有作用基)의 함량(含量)을 정량(定量)하여 얻은 결과(結果)는 다음과 같다. 1. IR Spectrum을 크게 세 가지 유형(類型)으로 분류(分類)하였다. 볏짚, 보리짚 및 호밀짚등(等)의 곡물작물 재료의 부식산(腐植酸)을 Type I으로, 산야초(山野草)의 부식산(腐植酸)을 Type II, 그리고 활엽수(闊葉樹)잎과 침엽수(針葉樹)의 잎에서 추출(抽出)한 부식산(腐植酸)을 Type III으로 분류(分類)하였다. 2. 동일(同一)한 식물성(植物性) 유기물질(有機物質)에서 추출(抽出)한 부식산(腐植酸)은 부숙기간(腐熟期間)에 관계(關係)없이 IR Spectrum에는 차이(差異)가 없었다. 3. IR Spectrum에서 $3430cm^{-1}$의 흡수대(吸收帶)는 Hydroxyl groups 이며 이 중 phenolic hydroxyl groups가 대부분(大部分)을 구성(構成)하고 있었다. 4. Phenolic hydroxyl groups와 Total acidity 간(間)에, Carboxyl groups와 Total hydroxyl groups 간(間)에 그리고 Alcoholic hydroxyl groups와 Total hydroxyl groups 간(間)에는 밀접(密接) 관계(關係)가 있었다. 5. Carbonyl groups와 Quinones의 흡수대(吸收帶)가 중복(重復)되는 까닭으로 인(因)해 이 두 작용기(作用基)는 IR Spectrum으로는 구별(區別)하기 곤란(困難)하였다. 6. IR Spectrum에서 $995{\sim}1000cm^{-1}$의 흡수대(吸收帶)는 부식산(腐植酸)의 구성성분중(構成成分中) Non-aromatic cyclic hydrocarbon 화합물(化合物)임이 예증(例證)되었다.