• 음성과학
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• 제10권2호
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• pp.7-25
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• 2003

Predicting the right prosodic elements is a key factor in improving the quality of synthesized speech. Prosodic elements include break, pitch, duration and loudness. Pitch, which is realized by Fundamental Frequency (F0), is the most important element relating to the quality of the synthesized speech. However, the previous method for predicting the F0 appears to reveal some problems. If voiced and unvoiced sounds are not correctly classified, it results in wrong prediction of pitch, wrong unit of triphone in synthesizing the voiced and unvoiced sounds, and the sound of click or vibration. This kind of feature is usual in the case of the transformation from the voiced sound to the unvoiced sound or from the unvoiced sound to the voiced sound. Such problem is not resolved by the method of grammar, and it much influences the synthesized sound. Therefore, to steadily acquire the correct value of pitch, in this paper we propose a new model for predicting and classifying the voiced and unvoiced sounds using the CART tool.

• 한국가금학회지
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• 제28권2호
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• pp.155-163
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• 2001

Gene and cell transfer technique will serve as a powerful tool for the genetic improvement of the poultry and to yield useful products. For avian transgenesis, Japanese quail may serve as an excellent animal model because of its small body size and fast growth rate. Recent progress was described on the manipulation of quail embryos such as the introduction of foreign genes and cells, and the subsequent culturing of the manipulated embryos yielding hatchlings. Intraspecific donor-derived offspring have been available in quail, however, further investigation will be required to obtain interspecific offspring with the aim of rescuing endangered species. Trans genesis will also be useful for improving the profitability and quality of poultry stocks and for developing stocks with novel uses. Considerable progress should soon be made toward the production of transgenic poultry. The key feature of the procedure described here is that embryos are initially taken out from the shell for ease of manipulation and then placed back in culture in addition to various operations midway during culture.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2008년도 춘계학술대회 논문집
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• pp.293-296
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• 2008

Contract power conversion factor which is applied to estimate contract power of general customers IS an important standard to caculate transformer capacity. This paper shows a reasonable contract power conversion factor, that was made by the systematic and statistical way considering actual conditions, such as investigated contract power and peak power for the last 5 years of each customer for 132 office building customers as to AMR system. In this dissertation, it is necessary to analyze the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimun and thus it was carried the linear and nonlinear regression analysis. Therefore, this paper compared characteristics for a contract power conversion factor which is applied to calculate contract power with characteristics for a regression model for customers which maximum utilization factor of transformer is more than 60%.

• The Journal of the Acoustical Society of Korea
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• 제24권2E호
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• pp.67-70
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• 2005

To realize a traditional music recognition system, some characteristics pertinent to Far East Asian music should be found. Using Spectrogram, some distinct attributes of Korean traditional music are surveyed. Frequency distribution, beat cycle and frequency energy intensity within samples have distinct characteristics of their own. Experiment is done for pre-experimentation to realize Korean traditional music recognition system. Using characteristics of Korean traditional music, $94.5\%$ of classification accuracy is acquired. As Korea, Japan and China have the same musical roots, both in instruments and playing style, analyzing Korean traditional music can be helpful in the understanding of Far East Asian traditional music.

• 천문학회보
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• 제38권1호
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• pp.50.1-50.1
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• 2013

As part of the DIGIT key program, we observed GSS30-IRS1, a Class I object located in Ophiuchus (d=125 pc), with Herschel-PACS. More than 70 lines were detected: CO lines of $J=14{\rightarrow}13$ to $41{\rightarrow}40$, several $H_2O$ lines of Eu=100 to 1500 K, 16 OH lines, and two atomic [OI] lines at 63 and 145 ${\mu}m$. All lines, except for [OI], were detected only at the central spaxel of $9.4^{\prime\prime}{\times}9.4^{\prime\prime}$ while the [OI] emission is extended along the NE-SW direction. One interesting feature in GSS30-IRS1 is that the continuum is extended beyond PSF, unlike the line emission. For detail analysis, we apply the non-LTE LVG model, RADEX as well as simple rotational diagrams to the detected line fluxes. We will discuss about the physical conditions around GSS30-IRS1, learned by the line flux analysis.

• 벤처창업연구
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• 제3권3호
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• pp.67-88
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• 2008

Innovation has become a key distinct feature of modern industrial society. It is generally recognized that new knowledge and technology are one of the most important sources of innovation. However, because of their limited resources, firms can not pursue all the promising new knowledge and technology that have possibilities to be developed into critical innovation. In this article, using the stakeholder theory, we try to establish a new conceptual model that can be used for understanding knowledge creation and innovation in society. In a society, there exist diverse socio-economic groups that have conflicting values and interests. Our stakeholder theory perspective on innovation claims that innovation can occur only when new solutions can satisfy their idiosyncratic stakeholder' values and interests better than current existing solutions. From the viewpoint of stakeholder innovation theory, there could be three different types of innovation: value improvement innovation, non-traditional value Innovation, and innovation for non-traditional stakeholder.

• Wind and Structures
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• 제24권3호
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• pp.249-265
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• 2017

An efficient and accurate algorithm is proposed to estimate flutter safety factor of suspension bridges satisfying prescribed reliability levels. Uncertainties which arise from the basic wind speed at the bridge deck location, critical flutter velocity, the wind conversion factor from a scaled model to the prototype structure and the gust speed factor are incorporated. The proposed algorithm integrates the concepts of the inverse reliability method and the calculation method of the critical flutter velocity of suspension bridges. The unique feature of the proposed method is that it offers a tool for flutter safety assessment of suspension bridges, when the reliability level is specified as a target to be satisfied by the designer. Accuracy and efficiency of this method with reference to three example suspension bridges is studied and numerical results validate its superiority over conventional deterministic method. Finally, the effects of various parameters on the flutter safety factor of suspension bridges are also investigated.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회B
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• pp.2070-2075
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• 2008

Identification of steady-state is the first step in developing a fault detection and diagnosis (FDD) system. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representing measurements were selected as key features for steady-state detection. The optimized moving window size and the feature thresholds was suggested through startup transient test and no-fault steady-state test. Performance of the steady-state detector was verified during indoor load change test. From the research, the general methodology to design a moving window steady-state detector was provided for vapor compression applications.

• ETRI Journal
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• 제45권4호
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• pp.627-635
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• 2023

In vehicular edge computing (VEC) networks, the rapid expansion of intelligent transportation and the corresponding enormous numbers of tasks bring stringent requirements on timely task offloading. However, many tasks typically appear within a short period rather than arriving simultaneously, which makes it difficult to realize effective and efficient resource scheduling. In addition, some key information about tasks could be learned due to the regular data collection and uploading processes of sensors, which may contribute to developing effective offloading strategies. Thus, in this paper, we propose a model that considers the deterministic demand of multiple tasks. It is possible to generate effective resource reservations or early preparation decisions in offloading strategies if some feature information of the deterministic demand can be obtained in advance. We formulate our scenario as a 0-1 programming problem to minimize the average delay of tasks and transform it into a convex form. Finally, we proposed an efficient optimal offloading algorithm that uses the interior point method. Simulation results demonstrate that the proposed algorithm has great advantages in optimizing offloading utility.

• Computers and Concrete
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• 제33권4호
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• pp.409-423
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• 2024

Using an extensive database, a sensitivity analysis across fifteen machine learning (ML) classifiers was conducted to evaluate the impact of various data manipulation techniques, evaluation metrics, and explainability tools. The results of this sensitivity analysis reveal that the examined models can achieve an accuracy ranging from 72-93% in predicting the fire-induced spalling of concrete and denote the light gradient boosting machine, extreme gradient boosting, and random forest algorithms as the best-performing models. Among such models, the six key factors influencing spalling were maximum exposure temperature, heating rate, compressive strength of concrete, moisture content, silica fume content, and the quantity of polypropylene fiber. Our analysis also documents some conflicting results observed with the deep learning model. As such, this study highlights the necessity of selecting suitable models and carefully evaluating the presence of possible outcome biases.