• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.45-56
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• 2015

In this paper, we present a method that can detect context-sensitive word errors and generate correction candidates. Spelling error detection is one of the most widespread research topics, however, the approach proposed in this paper is adjusted for an automated English scoring system. A common strategy in context-sensitive word error detection is using a pre-defined confusion set to generate correction candidates. We automatically generate a confusion set in order to consider the characteristics of sentences written by second-language learners. We define a word error that cannot be detected by a conventional grammar checker because of part-of-speech ambiguity, and propose how to detect the error and generate correction candidates for this kind of error. An experiment is performed on the English writings composed by junior-high school students whose mother tongue is Korean. The f1 value of the proposed method is 70.48%, which shows that our method is promising comparing to the current-state-of-the art.

• The Journal of Korean Association of Computer Education
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• v.7 no.2
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• pp.35-46
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• 2004

In this paper, I analyze error cases a learner made during learning using ICT, set up error types, and search for effective treatment methods in order to enhance the effects of ICT education. I search for error case to use the methodology of the study which is observation, interviews, and survey. I set up the error types which is the error type of confusion with functions, that of confusion with concepts, that of barriers in interface interpretation, that caused by psychological anxiety, that according to learner personality patterns, and habitual error type. The biggest frequency of errors was found in the error type of confusion with function and that of confusion with concepts, whose treatment methods were searched for using the web-based Q&A learning. Also, I apply the error treatment methods on the classroom and prove the effect.

• Journal of the Korean Society of Physical Medicine
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• v.15 no.3
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• pp.99-108
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• 2020

PURPOSE: This study examined the effects of the confusion level in performing dual tasks using smartphones while walking in subjects with chronic ankle instability (CAI). METHODS: Twenty subjects with CAI and 20 healthy subjects participated in the study. The spatial, temporal, spatial-temporal, and variability gait parameters were measured using GAITRite under four different conditions: general gait, web surfing during gait, texting during gait, and gaming during gait. Two-way repeated-measures analysis of variance was used to analyze the interaction according to the group (2) and confusion level in dual-tasks (4). One-way repeated-measures analysis of variance was used to compare the changes within the group according to the confusion level in dual-tasks. The changes between groups were compared using an independent t-test. The statistical significance level was set to p = .05. RESULTS: Significant interactions in the temporal and spatial-temporal gait parameters were found between the dual-task conditions and the other groups (p < .05). Significant within-group differences in the spatial, temporal, and spatial-temporal gait parameters were found according to the confusion level in dual tasks (p < .05). Significant between-group differences were observed in the temporal and spatial-temporal gait parameters according to the confusion level in dual tasks (p < .05). CONCLUSION: The effect of the confusion level in dual tasks was greater in subjects with CAI than in healthy individuals. This study suggests that to prevent reinjury to the ankle, subjects with CAI should avoid dual tasks such as using smartphones while walking.

• ETRI Journal
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• v.28 no.6
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• pp.811-814
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• 2006

In this letter, we introduce confusion-based confidence measures for detecting an impostor in speaker recognition, which does not require an alternative hypothesis. Most traditional speaker verification methods are based on a hypothesis test, and their performance depends on the robustness of an alternative hypothesis. Compared with the conventional Gaussian mixture model-universal background model (GMM-UBM) scheme, our confusion-based measures show better performance in noise-corrupted speech. The additional computational requirements for our methods are negligible when used to detect or reject impostors.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.73-83
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• 2007

An information retrieval system, using exact match, needs preprocessing or query expansion to generate transliteration variants in order to search foreign word transliteration variants in the documents. This paper proposes an effective method to generate other transliteration variants from a given transliteration. Because simple rewriting of confused characters produces too many false variants, the proposed method controls the generation priority by learning confusion patterns from real uses and calculating their probability. Especially, the left and right context of a pattern is considered, and local rewriting probability and global rewriting probability are calculated to produce more probable variants in earlier stage. The experimental result showed that the method was very effective by showing more than 80% recall with top 20 generations for a transliteration variants set collected from KT SET 2.0.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.238-239
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• 2015

set of building has to be amended by applying the provisions for matters relating to collateral responsibility to protect actively the owner of the induction of sets that were built to builder to rights and convenient improvement of set building, other laws are the same is applied to a set of building, for work of confusion is expected, in the present study, to understand the defect liability of recently revised set building method, and reasonable set of buildings through a comparative analysis of related laws by presenting the direction of defect liability is to be considered a countermeasure after presenting the effect of laws through survey.

• Journal of Multimedia Information System
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• v.7 no.2
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• pp.165-174
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• 2020

This document outlines a new color image encryption technology development. After splitting the original image into 240-bit blocks and modifying the first block by an initialization vector, an improved Feistel circuit is applied, sponsored by a genetic crossover operator and then strong chaining between the encrypted block and the next clear block is attached to set up the confusion-diffusion and heighten the avalanche effect, which protects the system from any known attack. Simulations carried out on a large database of color images of different sizes and formats prove the robustness of such a system.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1122-1129
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• 2022

The concept of Digital Twin (DT) has been receiving an increasing amount of attention in the construction management and building engineering research domains. Although the benefits of DT are evident, confusion with regards to the concept of DTs and its relationship with others such as Cyber-Physical Systems (CPS), Building Information Modelling (BIM) and Internet of Things (IoT) remains. This paper aims to help allay this confusion through an in-depth analysis of the definition of DT and its unique characteristics. As such, a review of the past and current definitions of DT and CPS in various domains is performed. An analysis is then conducted to identify the overlaps between the definition of DT with CPS, as well as with BIM and IoT. Finally, given the relatively closer resemblances between DT and CPS, a set of four distinct dimensions enabling their comparative analysis and highlighting their shared and unique characteristics is discussed. This paper contributes to the existing literature by exploring the definition of DT and presenting two original conceptualizations that help further refine the concept of DT in the construction and management and building engineering domain.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.33-44
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• 2016

There are many situations that the outcome for clinical decision and credit assessment should be predicted more than two categories. Five kinds of statistics which are used the concordance are proposed and used for these polytomous problems. However, these statistics are defined without exact distinction of categories, so that we have difficulty to use both the pair and set approaches and it is hard to understand the meanings of these statistics. Hence, it is not possible to compare and analyze them. In this paper, the polytomous confusion matrix is standardized and the concordance statistic can be represented based on the confusion matrix. The five kinds of statistics by using the concordance are defined. With the methods proposed in this paper, we could not only explain their meanings but also compare and analyze these statistics. Based on various data sets, properties of these five statistics are explored and explained.

• Phonetics and Speech Sciences
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• v.7 no.3
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• pp.139-149
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• 2015

This paper aims to analyze pronunciation variations of loanwords produced by Korean and improve the performance of pronunciation modeling of loanwords in Korean by using syllable-based segmentation and phonological knowledge. The loanword text corpus used for our experiment consists of 14.5k words extracted from the frequently used words in set-top box, music, and point-of-interest (POI) domains. At first, pronunciations of loanwords in Korean are obtained by manual transcriptions, which are used as target pronunciations. The target pronunciations are compared with the standard pronunciation using confusion matrices for analysis of pronunciation variation patterns of loanwords. Based on the confusion matrices, three salient pronunciation variations of loanwords are identified such as tensification of fricative [s] and derounding of rounded vowel [ɥi] and [$w{\varepsilon}$]. In addition, a syllable-based segmentation method considering phonological knowledge is proposed for loanword pronunciation modeling. Performance of the baseline and the proposed method is measured using phone error rate (PER)/word error rate (WER) and F-score at various context spans. Experimental results show that the proposed method outperforms the baseline. We also observe that performance degrades when training and test sets come from different domains, which implies that loanword pronunciations are influenced by data domains. It is noteworthy that pronunciation modeling for loanwords is enhanced by reflecting phonological knowledge. The loanword pronunciation modeling in Korean proposed in this paper can be used for automatic speech recognition of application interface such as navigation systems and set-top boxes and for computer-assisted pronunciation training for Korean learners of English.