• Journal of English Language & Literature
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• v.57 no.6
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• pp.1089-1109
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• 2011

In an attempt to demonstrate in context of Nietzsche's "overman" (ubermensch) and Heidegger's "Being-in-the-World" (Dasein) the collective human efforts to overcome humanism in crisis, I will provide the ground for the poetics of overcoming, the ground which are based upon the double movements of transhumanism and transnationalism. For this purpose, I will turn to the theories of two distinctive poets who reveal and disreveal their truths about the subjecthood or the subjectivity in terms of overcoming: Christopher Dewdney for posthuman transhumanity and Dionisio D. Martinez for transnational cultural contamination Transhumanism represented by Christopher Dewdney manifests an interfusion of outside and inside, thereby collapsing the boundary between the mind and the world, and provides a breakthrough from the limitedly defined mind to the transhuman perspective of overcoming by using terminalogy and techniques from science and technology. The emerging transhumanism reflects the growing interdependence between humans and bio technologies, and suggests a potential improvement of human beings. The main argument of transhumanism is that we humans can and should continue to develop in all possible directions, by overcoming our human limitations by shedding the body and having the disembodied consciousness which will liberate our mind. Kwame Anthony Appiah's "cultural contamination" is another form of overcoming as well as a way to otherness, a counter-ideal of cultural purity which sustains authentic culture, reversing the traditional binary opposition between enriching authenticity and threatening hybridization. Dionisio Martinez's poetry sublimates the negative side of Appiah's concept of contamination, by redeeming the value of the Appiah's list of the ideal of contamination such as hybridity, impurity, intermingling, the transformation that comes of new and unexpected combinations of human beings, a bit of this and a bit of that is how newness enters the world. When a poetic subject is doubly exiled and doubly homeless away from his/her native homeland and home of native language, one has no more identification with the authentic culture of both home and away, but rather anticipates a new identity as a transnational subject to cross the bridge beyond cultural authenticity and to enter into the field of cultural contamination.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.135-141
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• 2013

String matching is one of the key algorithms in network security and many areas could be benefit from a faster string matching algorithm. Based on the most efficient string matching algorithm in sual applications, the Boyer-Moore (BM) algorithm, a novel algorithm called RQS is proposed. RQS utilizes an improved bad character heuristic to achieve bigger shift value area and an enhanced good suffix heuristic to dramatically improve the worst case performance. The two heuristics combined with a novel determinant condition to switch between them enable RQS achieve a higher performance than BM both under normal and worst case situation. The experimental results reveal that RQS appears efficient than BM many times in worst case, and the longer the pattern, the bigger the performance improvement. The performance of RQS is 7.57~36.34% higher than BM in English text searching, 16.26~26.18% higher than BM in uniformly random text searching, and 9.77% higher than BM in the real world Snort pattern set searching.

• Journal of the Korean Professional Engineers Association
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• v.34 no.3
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• pp.33-40
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• 2001

Predict-Plan-Do is the main point to settle Safety management well, but we have neither Predict nor Plan. So just like the system of English CDM is necessary to be adapted in construction work which makes them work in full responsibility by clarifying the responsibility located step by step from planning to designing & constructing-To adapt this system needs more money for Safety than now, but this system makes companies earn maximum confidence & profit by accident prevention. Furthermore leads the nation and the society to earn large profit, then open the road to Welfare State. If you sees only the things such as money, profit, etc before your eyes, no more safety remains. That means no more respect of persons and no more welfare state.

• Journal of Industrial Convergence
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• v.18 no.4
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• pp.93-99
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• 2020

The Journal of Industrial Management Society in Republic of Korea. In order to explore the effect of overseas language training on the development of foreign language accuracy, this study investigates the errors in English compositions produced by 27 Korean university students who received overseas language training for 15 weeks. For data collection, students were made to take two tests, a pretest and a posttest, a semester apart. The differences in composition elements and errors between the two tests were examined and statistical analyses were performed. Results showed that while the average length of the compositions and sentences increased, the number of sentences decreased in the posttest. Also, more errors were found in the posttest where the students tried to construct more complex sentence structures. The students' ability to generate sentences were found to have improved, while their competence in using grammatical elements accurately within sentences did not see great improvement. This implies that overseas language training was not effective for aiding the development of one's grammatical accuracy of a foreign language over a 15-week period for the students.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.668-677
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• 2000

Korean has the characteristics that case postpositions determine the syntactic roles of phrases and a postposition may have more than one meanings. In particular, the adverbial postpositions make translation from Korean to English difficult, because they can have various meanings. In this paper, we describe a method for resolving such semantic ambiguities of Korean adverbial postpositions using decision trees. The training examples for decision tree induction are extracted from a corpus consisting of 0.5 million words, and the semantic roles for adverbial postpositions are classified into 25 classes. The lack of training examples in decision tree induction is overcome by clustering words into classes using a greedy clustering algorithm. The cross validation results show that the presented method achieved 76.2% of precision on the average, which means 26.0% improvement over the method determining the semantic role of an adverbial postposition as the most frequently appearing role.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.63-77
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• 2021

This study aims to explore the differential effects of teacher support on Chinese EFL students' listening ability in a blended learning environment. 87 third-year English-major students in a Chinese university participated in this study and they were randomly divided into an autonomy group (n=22), an emotional group (n=22), a cognitive group (n=22) and a control group (n=21). Each experimental group received relevant teacher support during their 17-week course learning while the control group did not. To confirm the effects of teacher support, pre- and post- listening tests were conducted. The results of the paired t-tests demonstrated that all groups showed statistically significant improvement in their English listening ability. The results of the one-way ANOVA for the post-test revealed that autonomy support and cognitive support were more effective than emotional support in improving students' listening ability. Based on the findings, this study hopes to provide insights for EFL teachers in designing and arranging the activities in a blended course.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.34-41
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• 2021

The purpose of this study is to explore any effects of primary English language learners' affective factors and satisfaction through AI-based speaking activity. In order to answer these questions, a total number of 46 ELLs from a public elementary school participated in this research. Survey questionnaire on affective factors and learning satisfaction were distributed and the results were analyzed quantitatively. The findings are as follows. First, participants could expand their knowledge on AI-based activity towards its educational advantages and capability. Second, overall affective factors of the participants on AI-based activity changed positively, with the improvement of the mean score. The paired samples t-test showed that there was a significant difference among interest, value and attitude. Third, the satisfaction degree on AI-based learning escalated, particularly in the sense of efficacy, academic achievement and involvement. Lastly, it was revealed that the satisfaction degree was correlated with learners' self-confidence, interest and attitude.

• Journal of Digital Convergence
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• v.16 no.3
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• pp.37-45
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• 2018

The purpose of this study was to understand language learning strategies use, language learning beliefs, and listening achievement of Korean EFL learners. The participants was sixty-nine university students who enrolled in blended learning classes for English listening. Data was collected and analyzed to see if there were any differences in strategies and beliefs between students who improved their listening test score and those who did not. The results showed that students showing improvement at the post-test used more language learning strategies and had a high level of motivation. Statistically significant correlation was found between motivation and strategies such as cognitive and meta-cognitive strategies.

• Phonetics and Speech Sciences
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• v.13 no.4
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• pp.47-53
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• 2021

Autoregressive Text-to-Speech (TTS) models suffer from inference instability and slow inference speed. Inference instability occurs when a poorly predicted sample at time step t affects all the subsequent predictions. Slow inference speed arises from a model structure that forces the predicted samples from time steps 1 to t-1 to predict the sample at time step t. In this study, an end-to-end non-autoregressive fast text-to-speech model is suggested as a solution to these problems. The results of this study show that this model's Mean Opinion Score (MOS) is close to that of Tacotron 2 - WaveNet, while this model's inference speed and stability are higher than those of Tacotron 2 - WaveNet. Further, this study aims to offer insight into the improvement of non-autoregressive models.

• Annual Conference on Human and Language Technology
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• 2009.10a
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• pp.186-190
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• 2009

품사 부착은 각종 자연어처리의 기본적인 요소이며, 크게 규칙 기반 방법과, 통계 기반 방법으로 나눌 수 있다. 대부분은 통계 기반의 기계학습을 이용하고 있으며, 대개 95% 이상의 성능을 보여주고 있다. 그러나 미등록어에 대해서는 성능이 그다지 높지 않다. 이 논문에서는 단어의 접사 정보를 이용해서 미등록어에 대한 품사 부착의 성능을 높이는 방법을 제안한다. 제안된 시스템은 CRF(Conditional Random Fields)를 이용하며, 그 자질의 일부로 접사 정보를 이용한다. 그 결과 미등록어에 대해서 약 40%의 성능이 개선되었다. 앞으로 미등록어에 적합한 자질을 연구하고 개발할 필요가 있을 것으로 생각된다.