In Korea, spent fuel is temporarily stored in spent fuel pools at nuclear reactor sites and it is predicted to become saturated between 2020 and 2024. For this reason, four disposal alternatives (KRS-1, A-KRS-1, A-KRS-21, and A-KRS-22) have been developed in order to carry out the direct disposal of the CANDU spent fuel. The objective of this study is to conduct cost efficiency analysis of the disposal alternatives in consideration of price volatility for the radioactive waste repository. To derive future price volatility, this study used the ARIMA model. As a result, A-KRS-1 is the most efficient in terms of price per bundle using 2015 price. As for the results using ARIMA model, except in the case of KRS-1, the cost per bundle of A-KRS-1, A-KRS-21, and A-KRS-22 is decreased. Cost estimation using ARIMA model shows little change or decreases in cost while cost estimation using inflation rates for 2020 resulted in approximately 7.2% increases compared to 2015 for all options. As for the results of scenario analysis, A-KRS-1 earned 8,160 points, while A-KRS-22 followed closely behind with 7,980 points among the total 24,300 points. The results of this study provide invaluable policy data for any nation considering the construction of spent nuclear fuel repository.

In this paper voice quality of normal speech is qualitatively classified by five components of breathy, creaky, rough, nasal, and thin/thick voice. To determine whether a correlation exists between a subjective measure of voice and an objective measure of voice, each voice is perceptually evaluated using the 1/2/3 scale by speech processing specialists and acoustically analyzed using speech analysis tools such as the Praat, MDVP, and VoiceSauce. The speech parameters include features related to speech source and vocal tract filter. Statistical analysis uses a two-independent-samples non-parametric test. Experimental results show that statistical analysis identified a significant correlation between the speech feature parameters and the components of voice quality.

This study proposes a method to measure mental fatigue using speech technology, which has not been used in previous research and is easier than existing complex and difficult methods. It aims at establishing a relationship between the human voice and mental fatigue based on experiments to measure the influence of mental fatigue on the human voice. Two monotonous tasks of simple calculation such as finding the sum of three one digit numbers were used to measure the feeling of monotony and two sets of subjective questionnaires were used to measure mental fatigue. While thirty subjects perform the experiment, responses to the questionnaire and speech data were collected. Speech features related to speech source and the vocal tract filter were extracted from the speech data. According to the results, speech parameters deeply related to mental fatigue are a mean and standard deviation of fundamental frequency, jitter, and shimmer. This study shows that speech technology is a useful method for measuring mental fatigue.

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This paper deals with how mental fatigue has an effect on human voice. For this a monotonous task to increase the feeling of the fatigue and a set of subjective questionnaire for rating the fatigue were designed. From the experiments the designed task was proven to be monotonous based on the results of the questionnaire responses. To investigate a statistical relationship between speech features extracted from the collected speech data and fatigue, the T test for two-related-samples was used. Statistical analysis shows that speech parameters deeply related to the fatigue are the first formant bandwidth, Jitter, H1-H2, cepstral peak prominence, and harmonics-to-noise ratio. According to the experimental results, it can be seen that voice is changed to be breathy as mental fatigue proceeds.