• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(2)
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• pp.237-240
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• 2002

In this W, a NiSi technology suitable for sub-100nm CMOS sevice is proposed. It seems that capping layer has little effect on the sheet resistance and junction leakage current when there is no thermal treatment. However, there happened agglomeration and drastic increase of Junction leakage current without capping layer. In other word, capping layer especially TiN capping layer is highly effective in suppressing thermal effect. It is shown that the sheet resistance of 0.12${\mu}{\textrm}{m}$ linewidth and shallow p+/n junction with NiSi were stable up to 700 t /30 minute thermal treatment.

• 한국음향학회지
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• 제11권3호
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• pp.14-24
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• 1992

본 논문은 신경망을 이용한 자음인히기에 관한 연구이다. 우선 자음과 모음이 포함된 음성에서 자음부분을 분리하였다. 각각의 자음을 몇개의 집단으로 나누어서 자음구간대 영교차율을 조사하였다. 마지막으로 자음을 인식하기 위해 제어망과 몇개의 소규모 망으로 구성한 혼합 신경망을 제안한다. 제어망은 입력된 자음이 어느 집단에 속하는가를 결정하고, 소규모망에서는 각 집단에 속하는 자음을 인식한다.

• 대한음성학회지:말소리
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• 제58호
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• pp.35-44
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• 2006

Maximum likelihood linear regression (MLLR) adaptation experiences severe performance degradation with very tiny amount of adaptation data. Eigenspace- based MLLR, as an alternative to MLLR for fast speaker adaptation, also has a weak point that it cannot deal with the mismatch between training and testing environments. In this paper, we propose a simultaneous fast speaker and environment adaptation based on eigenspace-based MLLR. We also extend the sub-stream based eigenspace-based MLLR to generalize the eigenspace-based MLLR with bias compensation. A vocabulary-independent word recognition experiment shows the proposed algorithm is superior to eigenspace-based MLLR regardless of the amount of adaptation data in diverse noisy environments. Especially, proposed sub-stream eigenspace-based MLLR with bias compensation yields 67% relative improvement with 10 adaptation words in 10 dB SNR environment, in comparison with the conventional eigenspace-based MLLR.

• 충청수학회지
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• 제24권4호
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• pp.927-934
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• 2011

Invertible transformations over n-bit words are essential ingredients in many cryptographic constructions. When n is large (e.g., n = 64) such invertible transformations are usually represented as a composition of simpler operations such as linear functions, S-P networks, Feistel structures and T-functions. Among them we study T-functions which are probably invertible and are very useful in stream ciphers. In this paper we study some conditions on a T-function h(x) such that f(x) = x + h(x) has a single cycle on ${\mathbb{Z}}_{2^n}$.

• Journal of Applied and Pure Mathematics
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• 제4권1_2호
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• pp.27-36
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• 2022

An innovation diffusion model is proposed model consists of three classes, namely, a non-adopter class, adopter class innovation-I, and adopter class innovation-II in a partially competitive and cooperative market. The proposed model is analyzed with the help of the qualitative theory of a system of ordinary differential equations. Basic influence numbers associated with first and second innovation $R_{0_1}$ and $R_{0_2}$ respectively in the absence of each other are quantified. Then the overall basic influence number (R₀) of the system is assessed for analyzing stability in the market in different situations. Sensitivity analysis of basic influence numbers associated with first and second innovation in the absence of each other is carried out. Numerical simulation supports our analytical findings.

• 전기전자학회논문지
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• 제25권4호
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• pp.625-633
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• 2021

몽고메리 모듈러 곱셈의 유연한 하드웨어 구현을 위한 확장 가능형 아키텍처를 기술한다. 처리요소 (processing element; PE)의 1차원 배열을 기반으로 하는 확장 가능형 모듈러 곱셈기 구조는 워드 병렬 연산을 수행하며, 사용되는 PE 개수 N_PE에 따라 연산 성능과 하드웨어 복잡도를 조정하여 구현할 수 있다. 제안된 아키텍처를 기반으로 SEC2에 정의된 8가지 필드 크기를 지원하는 확장 가능형 몽고메리 모듈러 곱셈기(scalable Montgomery modular multiplier; sMM) 코어를 설계했다. 180-nm CMOS 셀 라이브러리로 합성한 결과, sMM 코어는 N_PE=1 및 N_PE=8인 경우에 각각 38,317 등가게이트 (GEs) 및 139,390 GEs로 구현되었으며, 100 MHz 클록으로 동작할 때, N_PE=1인 경우에 57만회/초 및 N_PE=8인 경우에 350만회/초의 256-비트 모듈러 곱셈을 연산할 수 있는 것으로 평가되었다. sMM 코어는 응용분야에서 요구되는 연산성능과 하드웨어 리소스를 고려하여 사용할 PE 수를 결정함으로써 최적화된 구현이 가능하다는 장점을 가지며, ECC의 확장 가능한 하드웨어 설계에 IP (intellectual property)로 사용될 수 있다.

• 가정과삶의질연구
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• 제26권4호
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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.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2001년도 춘계학술대회 논문집
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• pp.225-230
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• 2001

Intensity of background noise is a factor significantly affecting both subjective evaluation of experienced stress level and associated electroencephalographic (EEG) responses during mental load in noisy environments. In the study on 27 subjects we analyzed the influence of the background white noise (WN) intensity on psychophysiological responses during a word recognition test. Electrocortical activity were recorded during baseline resting state and 40 s long performance on 3 similar Korean word recognition tests with different intensities of background WN (55, 70 and 85 dB).. An important finding in terms of physiological reactivity was similarity of all physiological response profiles between 55 and 70dB WN, i.e., none of physiological variables differentiated the two conditions, while 85dB WN resulted in a significantly different profile of reactions (higher fast beta power in EEG spectra). This condition was characterized by highest subjective rating of experienced stress, had more fast beta activity and had tendency of right hemisphere dominance, emphasizing the role of brain lateralization in negative affect control.

• 동아시아경상학회지
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• 제11권1호
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• pp.53-71
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• 2023

Purpose - This study aims to find clues necessary for the direction of leadership development suitable for the current situation by exploring the direction in which leadership has been studied from the perspective of domestic researchers, along with the arrangement of leadership theories studied in various ways. Research design, data, and methodology - A total of 7,425 papers were obtained due to the search, and 5,810 papers with English abstracts were used for analysis. For analysis, word frequency analysis, word clouding, and co-occurrence were confirmed using Python 3.7. In addition, after classifying topics related to research trends through BERTopic and LDA, trends were identified through dynamic topic modeling and OLS regression analysis. Result - As a result of the BERTopic, 14 topics such as 'Leadership management and performance' and 'Sports leadership' were derived. As a result of conducting LDA on 1,976 outliers, five topics were derived. As a result of trend analysis on topics by year, it was confirmed that five topics, such as 'military police leadership' received relative attention. Conclusion - Through the results of this study, a study on the reinterpretation of past leadership studies, a study on LMX with an expanded perspective, and a study on integrated leadership sub-factors of modern leadership theory were proposed.

• Communications for Statistical Applications and Methods
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• 제30권5호
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• pp.485-499
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• 2023

This study aimed to predict the number of meals served in a group cafeteria using machine learning methodology. Features of the menu were created through the Word2Vec methodology and clustering, and a stacking ensemble model was constructed using Random Forest, Gradient Boosting, and CatBoost as sub-models. Results showed that CatBoost had the best performance with the ensemble model showing an 8% improvement in performance. The study also found that the date variable had the greatest influence on the number of diners in a cafeteria, followed by menu characteristics and other variables. The implications of the study include the potential for machine learning methodology to improve predictive performance and reduce food waste, as well as the removal of subjective elements in menu classification. Limitations of the research include limited data cases and a weak model structure when new menus or foreign words are not included in the learning data. Future studies should aim to address these limitations.