• Phonetics and Speech Sciences
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• v.12 no.1
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• pp.51-63
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• 2020

Phonological awareness is a metalinguistic awareness ability of phonology and is known to predict language skills, such as reading and vocabulary skills. The purpose of this study was to investigate the relationship between phonological awareness, phonological processing, and language skills in 4- to 6-years-old typically developing (TD) children and children with language delay (LD). A total of 32 children (TD=18, LD=15) participated in this study. They performed a phonological awareness task consisting of counting, deletion, and discrimination at syllable level. Nonword Repetition, Digit Backward, Receptive & Expressive Vocabulary Test, and Grammaticality Judgment Task were performed to analyze the correlation between phonological awareness, phonological processing, and language ability. A multiple stepwise regression analysis was performed to examine the phonological awareness subtasks that predict language ability. In the TD group, the syllable categorization task significantly predicted the receptive vocabulary and the performance of the Grammaticality Judgment Task. The LD group showed that the syllable counting task significantly predicted the receptive vocabulary, the expressive vocabulary, and the performance of the Grammaticality Judgment Task. The results showed that the phonological awareness performance was significantly different between the two groups. Further, correlation analysis and regression analysis showed different results for each group. The result of the phonological awareness performance predicted the language ability of each group significantly, suggesting the importance of the meta-linguistic awareness ability of phonology.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.273-282
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• 2022

The narrative of the film, Sweet Smell of Success has a multi-layered structure. In Clifford Odets's scenario work, numerous lines for the main plot and subplots repeated a cycle of creation, decomposition, deletion, and modification to enhance the density of the story. As a result, whenever an actor spoke a line or paused, an action or an event that would trigger another line was created, giving depth and persuasiveness to the character's performance. The music of Sweet Smell of Success has multi-layered elements. The non-diegetic music was covered by the orchestral pieces performed by Elmer Bernstein's big band orchestra and the jazz pieces performed by Fred Katz's combo band. The diegetic music was mostly covered by the jazz pieces performed by the Chico Hamilton Quintet. The practical task of the film music was to reinforce or supplement the effect of the narrative driver, and the additional task was to realize the estrangement effect and the aesthetics of stagnation. The possibility and significance of intertextuality of subplots and double sound of this film are not simply confined to the limits of the film noir genre.

• Journal of Families and Better Life
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• v.26 no.4
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• pp.41-54
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• 2008

The purpose of this study was to investigate predictors concerning preschoolers' ability to read words, in terms of their sub-skills of alphabet knowledge, phonological awareness, and phonological processing. Fourteen literacy sub-tests and three types of reading tasks were administered to 289 kindergartners aged 4 to 6 in Busan. The main results are as follows. Sub-skills that predicted reading ability varied with children's age. Irrespective of children's age groups, knowledge of consonant names and digit naming speed commonly explained the reading of real words. In contrast, skills of syllable deletion and phoneme substitution and knowledge of alphabet composition principles were related to only 4-year-olds' reading skills. Exclusively included was digit memory in predicting 5-year-olds' reading abilities, and knowledge of vowel sounds in 6-year-olds' reading skills. The type of reading task also influenced reading ability. A few common variables such as knowledge of consonant names and vowel sounds, digit naming speed, and phoneme substitution skill explained all types of word reading. Syllable counting skills, however, had predictive value only for the reading of real words. Phoneme insertion skills and digit memory had predictive value for the reading of pseudo words and low frequency letters. Likewise, knowledge of consonant sounds and vowel stroke-adding principles were significant only for the reading of low frequency letters.

• Proceedings of the KIEE Conference
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• summer
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• pp.88-90
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• 2004

Data are a critical utility asset. Collecting correct data on site leads to accurate information. Data, when gathered with foresight & properly formatted, are useful to both existing database and easily transferable to newer, more comprehensive historical outage data. However, when investigating data items options, the task, can be an arduous one, often requiring the efforts of entire committees. This paper firstly discusses the KEPCO's past 10 years of historical outage data which include meterological data, and also by several elements of the National Weather Service, failure rate, outage duration, and probability classification, etc. Then, these collected data are automatically stored in an Outage Data Management System (ODMS), which allows for easy access and display. ODMS has a straight-forward and easy-to-use interface. It lets you to navigate through modules very easily and allows insertion, deletion or editing of data. In particular, this will further provide the KEPCO that not only helps with probabilistic security assessment but also provides a platform for future development of Probability Estimation Program (PEP).

• Journal of Radiation Protection and Research
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• v.22 no.1
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• pp.47-58
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• 1997

The conversion coefficients of effective dose per unit air kerma and equivalent dose per unit fluence were calculated by MCNP4A code for antero-posterior(AP) and postero- anterior(PA) incidence of broad, unidirectional beams of photons into anthropomorphic MIRD phantom. Calculations have been performed for 20 monoenergetic photons of energy ranging from 0.03 to 10 MeV. The conversion coefficients showed a good agreement with the corresponding values given in the draft publication of joint task group of ICRP and ICRU within 10%. The deviations may arise from the differences of geometry in the MIRD phantom and the ADAM/EVE phantoms, and the differences in the codes and cross-section data used. Inclusion of a specific oesophagus model results in effective dose slightly different(5% at most) from the effective doses obtained by adopting the equivalent doses for the thymus or pancreas. Deletion of the ULI from the remainder organ appeared not to be significant for the cases of photon dosimetry covered in this study.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.706-711
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• 2010

In the applications of a human speech interface, reducing the error rate in recognition is the one of the main research issues. Many previous studies attempted to correct errors using post-processing, which is dependent on a manually constructed corpus and correction patterns. We propose an automatically learnable post-processing method that is independent of the characteristics of both the domain and the speech recognizer. We divide the entire post-processing task into two steps: error detection and error correction. We consider the error detection step as a classification problem for which we apply the conditional random fields (CRFs) classifier. Furthermore, we apply transformation-based learning (TBL) to the error correction step. Our experimental results indicate that the proposed method corrects a speech recognizer's insertion, deletion, and substitution errors by 25.85%, 3.57%, and 7.42%, respectively.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.4
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• pp.75-82
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• 2018

BIM(Building Information Modeling) based design process can initiatively conduct a task through all phases from early design step to construction and maintenance step. Also BIM efficiently manage the building's energy by reflecting 3D design and construction life cycle. This paper proposes an efficient process to build AHU's BIM-based library. This study involves analyzing an AHU model for development of design module, and making the template model using the same 12 parts including the shapes of ducts, doors and frames. In consideration of each shape's direction and the status of existence, which are detailed shapes of parts upon making the template model, all the shapes of the AHU model can be expressed. By applying parametric modeling to the template model, a quick and precise modification and transformation can be conducted, thus the efficiency is enhanced. A user selects an AHU model from a 2D model selection program, and extracts shape information. The final AHU shape is completed through the automation work of unnecessary shape deletion by bringing the extracted shape information to the template model. This enables the user to build efficient AHU's BIM-based library, since the quick and precise modification and transformation of the template model are possibile, and all AHU model shapes can be expressed.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.125-132
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• 2022

Sentence compression is a natural language processing task that generates concise sentences that preserves the important meaning of the original sentence. For grammatically appropriate sentence compression, early studies utilized human-defined linguistic rules. Furthermore, while the sequence-to-sequence models perform well on various natural language processing tasks, such as machine translation, there have been studies that utilize it for sentence compression. However, for the linguistic rule-based studies, all rules have to be defined by human, and for the sequence-to-sequence model based studies require a large amount of parallel data for model training. In order to address these challenges, Deleter, a sentence compression model that leverages a pre-trained language model BERT, is proposed. Because the Deleter utilizes perplexity based score computed over BERT to compress sentences, any linguistic rules and parallel dataset is not required for sentence compression. However, because Deleter compresses sentences only considering perplexity, it does not compress sentences by reflecting the linguistic information of the words in the sentences. Furthermore, since the dataset used for pre-learning BERT are far from compressed sentences, there is a problem that this can lad to incorrect sentence compression. In order to address these problems, this paper proposes a method to quantify the importance of linguistic information and reflect it in perplexity-based sentence scoring. Furthermore, by fine-tuning BERT with a corpus of news articles that often contain proper nouns and often omit the unnecessary modifiers, we allow BERT to measure the perplexity appropriate for sentence compression. The evaluations on the English and Korean dataset confirm that the sentence compression performance of sentence-scoring based models can be improved by utilizing the proposed method.