• 대한음성학회:학술대회논문집
• /
• 대한음성학회 1996년도 10월 학술대회지
• /
• pp.430-431
• /
• 1996

Among the scholars of second language (L2) acquisition who have used prosodic considerations in syntactic analyses, pausing and intonation contours have been used to define utterances in the speech of second language learners (e.g., Sato, 1990). In recent research on conversational analysis, it has been found that lexically marked causal clause combining in the discourse of native speakers can be distinguished as "intonational subordination" and "intonational coordination(Couper-Kuhlen, Elizabeth, forthcoming.)". This study uses Pienemann's Processability Theory (1995) for an analysis of the speech of native speakers of Japanese (L1) learning English. In order to accurately assess the psycholinguistic stages of syntactic development, it is shown that pitch, loudness, and timing must all be considered together with the syntactic analysis of interlanguage speech production. Twelve Japanese subjects participated in eight fifteen minute interviews, ninety-six dyads. The speech analyzed in this report is limited to the twelve subjects interacting with two different non-native speaker interviews for a total of twenty-four dyads. Within each of the interviews, four different tasks are analyzed to determine the stage of acquisition of English for each subject. Initially the speech is segmented according to intonation contour arid pauses. It is then classified accoding to specific syntactic units and further analysed for pitch, loudness and timing. Results indicate that the speech must be first claasified prosodic ally and lexically, prior to beginning syntactic analysis. This analysis stinguishes three interlanguage lexical categories: discourse markers, coordinator $s_ordinators, and transfer from Japanese. After these lexical categories have been determined, the psycholinguistic stages of syntactic development can be more accurately assessed.d.

• 제어로봇시스템학회논문지
• /
• 제4권4호
• /
• pp.448-457
• /
• 1998

A neural network based control algorithm with fuzzy compensation is proposed for the automated adjustment in the production of electronic end-products. The process of adjustment is to tune the variable devices in order to examine the specified performances of the products ready prior to packing. Camcorder is considered as a target product. The required test and adjustment system is developed. The adjustment system consists of a NNC(neural network controller), a sub-NNC, and an auxiliary algorithm utilizing the fuzzy logic. The neural network is trained by means of errors between the outputs of the real system and the network, as well as on the errors between the changing rate of the outputs. Control algorithm is derived to speed up the learning dynamics and to avoid the local minima at higher energy level, and is able to converge to the global minimum at lower energy level. Many unexpected problems in the application of the real system are resolved by the auxiliary algorithms. As the adjustments of multiple items are related to each other, but the significant effect of performance by any specific item is not observed. The experimental result shows that the proposed method performs very effectively and are advantageous in simple architecture, extracting easily the training data without expertise, adapting to the unstable system that the input-output properties of each products are slightly different, with a wide application to other similar adjustment processes.

• 한국간호교육학회지
• /
• 제18권1호
• /
• pp.14-24
• /
• 2012

Purpose: This study was conducted to identify the effect of simulation-based education relevant to the care of patients with acute renal failure (ARF) for third-year nursing students. Methods: This study was a non-equivalent control pre-posttest design. Based on the clinical situation scenarios pertaining to patients with ARF, a simulation-based learning module was developed using Human Patient Simulator version 6 (HPS6) manufactured by Medical Education Technologies Inc. The pretest was conducted so as to evaluate the difference in prior knowledge and clinical competence between two groups. The control group consisted of 91 students during the 2010 academic year and the experimental group consisted of 94 students during the 2011 academic year. Data were analysed using SPSS/win 10.1. Results: In the experimental group, knowledge related to care for ARF patients was not significantly increased; however, clinical competence improved significantly for the experimental group. Conclusion: In conclusion, the simulation-based education program was effective in contributing towards the development of clinical competence. Increased development of clinical competence is vital for today's clinical environment where nursing professionals need the necessary knowledge, thinking, and performance skills to meet the needs of the hospital and their patients.

• 정보처리학회논문지B
• /
• 제8B권3호
• /
• pp.231-236
• /
• 2001

일반적인 다층 신경망에서 가중치의 갱신 알고리즘으로 사용하는 오류 역전과 방식은 가중치 갱신 결과를 고정된(fixed) 한 개의 값으로 결정한다. 이는 여러 갱신의 가능성을 오직 한 개의 값으로 고정하기 때문에 다양한 가능성들을 모두 수용하지 못하는 면이 있다. 하지만 모든 가능성을 확률적 분포로 표현하는 갱신 알고리즘을 도입하면 이런 문제는 해결된다. 이러한 알고리즘을 사용한 베이지안 신경망 모형(Bayesian Neural Networks Models)은 주어진 입력값(Input)에 대해 블랙 박스(Black-Box)와같은 신경망 구조의 각 층(Layer)을 거친 출력값(Out put)을 계산한다. 이 때 주어진 입력 데이터에 대한 결과의 예측값은 사후분포(posterior distribution)의 기댓값(mean)에 의해 계산할 수 있다. 주어진 사전분포(prior distribution)와 학습데이터에 의한 우도함수(likelihood functions)에 의해 계산한 사후확률의 함수는 매우 복잡한 구조를 가짐으로 기댓값의 적분계산에 대한 어려움이 발생한다. 따라서 수치해석적인 방법보다는 확률적 추정에 의한 근사 방법인 몬테 칼로 시뮬레이션을 이용할 수 있다. 이러한 방법으로서 Hybrid Monte Carlo 알고리즘은 좋은 결과를 제공하여준다(Neal 1996). 본 논문에서는 Hybrid Monte Carlo 알고리즘을 적용한 신경망이 기존의 CHAID, CART 그리고 QUEST와 같은 여러 가지 분류 알고리즘에 비해서 우수한 결과를 제공하는 것을 나타내고 있다.

• 한국수학사학회지
• /
• 제23권4호
• /
• pp.83-100
• /
• 2010

본 연구는 2006년 8월에 고시된 수학과 개정교육과정의 그래프와 일차변환의 내용이 학교 현장에서 지도될 때 생길 수 있는 문제점들을 제시하고, 그 해결방안을 모색하는데 목적이 있다. 제 7차교육과정 이후의 두단원에 대한 선행연구들과 교육과정의 변천과정을 살펴보고, '수학I', '수학의 활용' 그리고 '기하와 벡터' 과목의 검인정 교과서 및 익힘책 전부(27종 전 54권)에 대하여 두 단원의 학습내용을 비교하여본다. 이러한 과정을 통하여 학교현장에서 두 단원에 대한 교사의 교육과정 이해도 제고와 교육과정 내용의 올바른 적용 적용 방안을 제언한다.

• 음성과학
• /
• 제13권4호
• /
• pp.187-200
• /
• 2006

The speech synthesis technology is widely used and its application area is also being broadened to an automatic response service, a learning system for handicapped person, etc. However, the sound quality of the speech synthesizer has not yet reached to the satisfactory level of users. To make a synthesized speech, the existing synthesizer generates rhythms only by the interval information such as space and comma or by several punctuation marks such as a question mark and an exclamation mark so that it is not easy to generate natural rhythms of people even though it is based on mass speech database. To make up for the problem, there is a way to select rhythms after processing language from a higher level information. This paper proposes a method for generating tags for controling rhythms by analyzing the meaning of sentence with speech situation information. We use the Systemic Functional Grammar (SFG) [4] which analyzes the meaning of sentence with speech situation information considering the sentence prior to the given one, the situation of a conversation, the relationship among people in the conversation, etc. In this study, we generate Semantic Speech Control Tag (SSCT) by the result of SFG's meaning analysis and the voice wave analysis.

• 한국수학교육학회지시리즈A:수학교육
• /
• 제55권1호
• /
• pp.73-89
• /
• 2016

The purpose of this study was to analyze middle school students' problem posing types and strategies. we analyzed problems posed by 120 middle school students during mathematics class focused on problem posing activities in various aspects. Students' posed problems were classified into five types: not a problem(NP), non-math(NM), impossible(IM), insufficient(IN), sufficient(SU) and each of the posed problems. Students used three kinds of problem posing strategies such as goal manipulation(GM), assumption manipulation(AM), and condition manipulation(CM), and in posing one problem, one or more than two strategies were used. According to the prior studies, problem posing can contributes to the development of students' problem solving ability, creativity, mathematical aptitude, and a broader understanding of mathematical concepts. However, we found that some students had difficulties in posing problems or limited understandings of that. We hope the results of the study contribute to encouraging problem posing activities in mathematics instruction.

• ETRI Journal
• /
• 제41권6호
• /
• pp.771-781
• /
• 2019

We propose the VS³-NET model to solve the task of question answering questions with machine-reading comprehension that searches for an appropriate answer in a given context. VS³-NET is a model that trains latent variables for each question using variational inferences based on a model of a simple recurrent unit-based sentences and self-matching networks. The types of questions vary, and the answers depend on the type of question. To perform efficient inference and learning, we introduce neural question-type models to approximate the prior and posterior distributions of the latent variables, and we use these approximated distributions to optimize a reparameterized variational lower bound. The context given in machine-reading comprehension usually comprises several sentences, leading to performance degradation caused by context length. Therefore, we model a hierarchical structure using sentence encoding, in which as the context becomes longer, the performance degrades. Experimental results show that the proposed VS³-NET model has an exact-match score of 76.8% and an F1 score of 84.5% on the SQuAD test set.

• 한국초등과학교육학회지:초등과학교육
• /
• 제39권3호
• /
• pp.353-368
• /
• 2020

This study analyzed the teacher's perception for influence of behavioral characteristics of scientifically-gifted students on general students in elementary school science class. To do this, we selected the eight elementary school teachers who were conducting the regular science classes including scientifically-gifted students belonging to the gifted education institutes in Seoul and conducted individual in-depth interviews. The analysis of the results reveal that the teachers mentioned seven behavioral characteristics of scientifically-gifted students in general elementary school science classes.: 'excellent in designing and performing experiments', 'playing a leading role in experiments', 'expressing their abundant prior knowledge frequently', 'attempting their tasks with curiosity and persistence', 'displaying scientific creativity', 'often asking scientific questions in detail', and 'expressing their opinions logically'. These behavioral characteristics of scientifically-gifted students had positive effects on general students, such as 'providing them with a successful experience in conducting experiments', 'improving understanding of science class contents', 'developing scientific thinking and reflective thinking', and 'improving their students' positive experiences about science'. However, the excessive learning-driven behaviors of scientifically-gifted students had negative effects on general students, such as 'limiting opportunities for general students to participate in classes', 'conducting passive exploration centered on results', and 'causing conflicts with general students'. Educational implications of these findings are discussed.

• 융합보안논문지
• /
• 제11권3호
• /
• pp.3-10
• /
• 2011

최근 들어 연이어 발생하고 있는 DDoS 공격의 영향으로 정부, 기관, 기업의 보안대책과 관련 법규 제도가 강화되고 있다. 하지만 대규모 네트워크 침해사고 및 서비스 방해공격들을 앞으로도 다시 발생할 가능성이 많으며 이를 예방하기 위해선 미리 취약성을 예측할 수 있는 연구가 이루어져야 한다. 기존의 연구 방법들은 어떤 데이터를 기반으로 예측하였는지가 명확하지 않아 복잡하거나 모호하다는 한계가 있다. 따라서 본 논문은 공신력 있는 기관에서 제공하는 취약점 데이터를 기반으로 예측에 관련된 기계 학습 기술을 이용하여 이전에 발생했던 취약점을 토대로 향후 발생할 수 있는 취약점에 대해 미리 예측할 수 있는 방법을 제안하고, 실험을 통하여 효율성을 검증하였다.