• School Mathematics
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• v.14 no.4
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• pp.495-516
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• 2012

This study distinguished thinking related to statistical variability into six components - the noticing of variability, the explanation of variability, the control of variability, the modeling of variability, the understanding of samples, and the understanding of sampling distribution and investigated the relationships among the thinking components. This study found that this distinction of thinking components related to statistical variability is reasonable. The results showed that each correlation coefficient of the modeling of variability, the understanding of samples, and the understanding of sampling distribution with regard to the noticing of variability, the explanation of variability, and the control of variability is similar. Based on this results, new variable, the understanding of sampling, has been drawn. The results also showed that while the noticing of variability and the control of variability influence the understanding of sampling, the explanation of variability does not influence it.

• Journal of Educational Research in Mathematics
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• v.21 no.2
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• pp.201-220
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• 2011

This study investigates levels of thinking of elementary and middle school students doing their tasks of explaining and dealing with variability. According to results, on the task of explaining variability in the measurement settings five levels of thinking were identified: a lack of understanding of explanation of the causes, an insufficient understanding of the causes, an offer of physical causes, consideration of unexplained causes as the source of variability, and consideration of unexplained causes as quasi-chance variability. Also, in the chance settings five levels of thinking were identified: a lack of understanding of explanation of the causes, an insufficient understanding of the causes, an offer of physical causes, recognition of chance variability, and consideration of causes of distribution. On the task of dealing with variability in both the measurement and chance settings five levels of thinking were identified: a lack of understanding of dealing with variability, no physical control and improper statistical control, no physical control and proper statistical control, physical control and improper statistical control, and physical control and proper statistical control.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.65-68
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• 2003

본 논문에서는 대화체 연속음성인식 과정에서 사용되는 다중발음사전의 개념을 확장하여 대화체 발화에 빈번하게 나타나는 불규칙한 발음변이 현상을 포용하도록 한 확장된 발음사전의 방법을 적용하여 대화체 연속음성인식에서 인식성능의 향상을 가져오게 됨을 실험을 통해 보여준다. 대화체 음성에서 빈번하게 나타나는 음운축약 및 음운탈락, 전형적인 오발화, 양성음의 음성음화 등의 발음변이는 언어모델의 효율성을 떨어뜨리고 어휘 수를 증가시켜 음성인식의 성능을 저하시키고, 또한 음성인식 결과로 나타나는 출력형태가 정형화되지 못하는 단점을 가지고 있다. 이에 이러한 발음변이들을 발음사전에 수용할 때 각각의 대표어휘에 대한 변이발음으로 처리하고, 언어모델과 어휘사전은 대표어휘만을 이용해 구성하도록 한다. 그리고, 음성인식기의 탐색부에서는 각각의 변이발음의 발음열도 탐색하되 대표어휘로 언어모델을 참조하도록 하고, 인식결과를 출력하도록 하여 결과적으로 인식성능을 향상시키고, 정형화된 출력패턴을 얻도록 한다. 본 연구에서는 어절단위 뿐 아니라 의사형태소[2] 단위의 발음사전에도 발음변이를 포용하도록 하여 실험을 하였다. 실험을 통해 어절단위의 다중발음사전 구성을 통해 ERR 10.9％, 의사형태소 단위의 다중발음 사전의 구성을 통해 ERR 4.3％의 성능향상을 보였다.

• Journal of Educational Research in Mathematics
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• v.20 no.3
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• pp.339-356
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• 2010

It is important for children to develop statistical reasoning as they think through data. In particular, it is imperative to provide children instructional situations in which they are encouraged to consider variability in data because the ability to reason about variability is fundamental to the development of statistical reasoning. Many researchers argue that even highperforming mathematics students show low levels of statistical reasoning; interventions attending to pedagogical concerns about child ren's statistical reasoning are, thus, necessary. The purpose of this study was to investigate 15 gifted elementary students' various ways of understanding important statistical concepts, with particular attention given to 3 students' reasoning about data that emerged as they engaged in the process of generating and graphing data. Analysis revealed that in recognizing variability in a context involving data, mathematically gifted students did not show any difference from previous results with general students. The authors suggest that our current statistics education may not help elementary students understand variability in their development of statistical reasoning.

• School Mathematics
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• v.12 no.4
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• pp.455-471
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• 2010

Understanding of randomness is essential for learning and teaching of probability and statistics. Understanding of randomness prompts to understand natural and social phenomena from the point of view of mathematics, and plays a role of base in understanding of judgments based on rational interpretation on these phenomena. This study examined whether pre-service teachers recognize this, and they understand randomness included in various contexts. According to results, they did not have a understanding of randomness in the context related to measuring, while they grasped randomness in simple and joint events. This implies that they lack the understanding of variability which is essential in the context of measuring. This study, therefore, suggests that the settings of measuring should be introduced into probability and statistics education, especially that data from measuring should be analyzed focusing on the variability in the data set.

• Journal of Gifted/Talented Education
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• v.23 no.3
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• pp.387-406
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• 2013

This study compared levels of mathematically talented students' statistical thinking with those of non-talented students in the noticing of statistical variability. t tests were conducted to test for statistically significant differences between mathematically gifted students and non-gifted students. Results for the t-test shows that there is no difference between the TE students' and NE students' noticing of variability in the measurement settings. Meanwhile, the t-test results also show that there is a difference between the TM students' and NM students' noticing of variability in the both measurement and chance settings. Table of frequencies of each level, however, shows that levels of mathematically gifted students' thinking were not distributed at the high levels but were overlapped with those of non-gifted students. These results are thought-provoking results in statistics instruction for mathematically talented students.

• Journal of Educational Research in Mathematics
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• v.21 no.1
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• pp.17-32
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• 2011

This study investigated pre-service teachers' understanding of statistical sampling. The researchers categorized major topics related to sampling into representativeness of samples, sampling variability, and sampling distribution, and selected concepts connected to each topic. Findings on this study are as follows: Even though most of the pre-service teachers considered the random sampling bringing unbiased outcomes as a proper sampling method, only 64% of them recognized that sample is a quasi-proportional, small-scale version of population; Few pre-service teachers understood that more important is the size of sample, not the portion of sample to population, and half of them appreciated that the number of sampling has a powerful effect on drawing of reliable results than the size of sample; Few pre-service teachers understood that sampling distribute is irrelevant to the shape of population and has a symmetrical bell-shape.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.229-231
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• 2003

일반적으로 음성은 시간함수로 표현되며 음성인식에서 표준모델을 모델링하는 것은 매우 중요한 문제이다. 음절 단어, 연속음성을 발성할 때 자음과 모음에 따라 발성시간에 차이가 있으며 이를 잘 모델링하는 것 또한 음성인식에서는 중요한 문제라고 할 수 있다. 따라서 본 연구에서는 강건한 음향모델을 학습하기 위해 시간의 변화와 상태분할과정에서의 모델의 변화를 고려하여 다양한 구조의 초기모델을 작성하였다. 각 초기모델에 의한 HM-Net 문맥의존 음향모델은 음소결정트리 기반 SSS 알고리즘(PDT-SSS)을 이용하였다. PDT-SSS 알고리즘은 미지의 문맥정보를 해결하기 위해 문맥방향과 시간방향으로 목표 상태수에 도달할 때까지 상태분할을 수행하여 모델을 작성하는 방법이다. 음성의 시간변이를 고려한 강건한 문맥의존 음향모델을 작성하기 위해 설정한 각 모델의 구조에 대한 유효성을 확인하기 위해 국어공학센터의 452 단어를 대상으로 음소와 단어인식 실험을 수행한 결과. 음소인식의 경우 상태수 2000개에서 2상태 구조의 모델에 비해 4상태 구조가 약 11.4% 향상된 인식성능과 39.2초의 인식시간을 단축할 수 있었다. 또한 단어인식의 경우 상태수 2000개에서 1상태 구조의 모델에 비해 4상태 구조가 약 5% 향상된 인식성능과 4상태 구조에서 한 단어를 인식하는데 평균 0.8초가 소요되었다. 따라서 강건한 문맥의존 음향모델을 작성하기 위해 수행한 초기모델의 구조에 관한 연구가 향후 음성인식 시스템을 구축하는데 유효함을 확인할 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1380-1386
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• 2003

Speech recognition performance is degraded by the variation in vocal tract length among speakers. In this paper, we have used a vocal tract length normalization method wherein the frequency axis of the short-time spectrum associated with a speaker's speech is scaled to minimize the effects of speaker's vocal tract length on the speech recognition performance In order to normalize vocal tract length, we tried several frequency warping functions such as linear and piece-wise linear function. Variable interval piece-wise linear warping function is proposed to effectively model the variation of frequency axis scale due to the large variation of vocal tract length. Experimental results on TIDIGITS connected digits showed the dramatic reduction of word error rates from 2.15% to 0.53% by the proposed vocal tract normalization.

• Journal of Food Hygiene and Safety
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• v.14 no.4
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• pp.386-396
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• 1999

Commonly eaten fish, meat and other protein-containing foods show some level of mutagenic activity following normal cooking such as broiling, frying, grilling, roasting etc. The main food mutagens found in cooked products are“heterocyclic aromatic amines”. Several of them have been shown to be carcinogenic in rodent and suggested to be relevant for human cancer etiology. This review summarizes the chemistry, formation, occurrence and toxicity of food-borne heterocyclic aromatic amines. Factors that influence the formation of them are also discussed with special emphasis on dietary factors. From a health safety point of view, it is desirable to estimate the intake of heterocyclic amines via foods, and reduce or prevent the formation of food mutagens.