• 제목/요약/키워드: Sequence-based rule

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하이브리드 신경회로망을 이용한 화자인식에 관한 연구 (A Study on Speaker Identification Using Hybrid Neural Network)

  • 신청호;신대규;이재혁;박상희
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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    • pp.600-602
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    • 1997
  • In this study, a hybrid neural net consisting of an Adaptive LVQ(ALVQ) algorithm and MLP is proposed to perform speaker identification task. ALVQ is a new learning procedure using adaptively feature vector sequence instead of only one feature vector in training codebooks initialized by LBG algorithm and the optimization criterion of this method is consistent with the speaker classification decision rule. ALVQ aims at providing a compressed, geometrically consistent data representation. It is fit to cover irregular data distributions and computes the distance of the input vector sequence from its nodes. On the other hand, MLP aim at a data representation to fit to discriminate patterns belonging to different classes. It has been shown that MLP nets can approximate Bayesian "optimal" classifiers with high precision, and their output values can be related a-posteriori class probabilities. The different characteristics of these neural models make it possible to devise hybrid neural net systems, consisting of classification modules based on these two different philosophies. The proposed method is compared with LBG algorithm, LVQ algorithm and MLP for performance.

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언어 정보가 반영된 문장 점수를 활용하는 삭제 기반 문장 압축 (Deletion-Based Sentence Compression Using Sentence Scoring Reflecting Linguistic Information)

  • 이준범;김소언;박성배
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제11권3호
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    • pp.125-132
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    • 2022
  • 문장 압축은 원본 문장의 중요한 의미는 유지하면서 길이가 축소된 압축 문장을 생성하는 자연어처리 태스크이다. 문법적으로 적절한 문장 압축을 위해, 초기 연구들은 사람이 정의한 언어 규칙을 활용하였다. 또한 시퀀스-투-시퀀스 모델이 기계 번역과 같은 다양한 자연어처리 태스크에서 좋은 성능을 보이면서, 이를 문장 압축에 활용하고자 하는 연구들도 존재했다. 하지만 언어 규칙을 활용하는 연구의 경우 모든 언어 규칙을 정의하는 데에 큰 비용이 들고, 시퀀스-투-시퀀스 모델 기반 연구의 경우 학습을 위해 대량의 데이터셋이 필요하다는 문제점이 존재한다. 이를 해결할 수 있는 방법으로 사전 학습된 언어 모델인 BERT를 활용하는 문장 압축 모델인 Deleter가 제안되었다. Deleter는 BERT를 통해 계산된 perplexity를 활용하여 문장을 압축하기 때문에 문장 압축 규칙과 모델 학습을 위한 데이터셋이 필요하지 않다는 장점이 있다. 하지만 Deleter는 perplexity만을 고려하여 문장을 압축하기 때문에, 문장에 속한 단어들의 언어 정보를 반영하여 문장을 압축하지 못한다. 또한, perplexity 측정을 위한 BERT의 사전 학습에 사용된 데이터가 압축 문장과 거리가 있어, 이를 통해 측정된 perplexity가 잘못된 문장 압축을 유도할 수 있다는 문제점이 있다. 이를 해결하기 위해 본 논문은 언어 정보의 중요도를 수치화하여 perplexity 기반의 문장 점수 계산에 반영하는 방법을 제안한다. 또한 고유명사가 자주 포함되어 있으며, 불필요한 수식어가 생략되는 경우가 많은 뉴스 기사 말뭉치로 BERT를 fine-tuning하여 문장 압축에 적절한 perplexity를 측정할 수 있도록 하였다. 영어 및 한국어 데이터에 대한 성능 평가를 위해 본 논문에서 제안하는 LI-Deleter와 비교 모델의 문장 압축 성능을 비교 실험을 진행하였고, 높은 문장 압축 성능을 보임을 확인하였다.

The Flocculation of Veegum Suspension by Electrolytes

  • Kwang Pyo Lee;Robert C. Mason;Ree Takiyue
    • 대한화학회지
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    • 제16권1호
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    • pp.25-32
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    • 1972
  • The effect on the apparent viscosity of 2 wt. % Veegum suspensions of different types of electrolytes and of different electrolyte concentrations was studied. Measurements were made with a Brookfield Synchro-Lectric Viscometer, using no.3 spindle at 30 R.P.M. at $24^{\circ}C$. As electriolyte concentration increased, the apparant viscosity was observed to increase to a maximum and then to decrease. Changes in viscosity were in general agreement with predicted results based on the Hofmeister sequence and the Schulze-Hardy rule. The observed electrolyte effect on the apparent viscosity was discussed in terms of the Verwey-Overbeek theory.

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Reverse Iterative Image Encryption Scheme Using 8-layer Cellular Automata

  • Zhang, Xing;Zhang, Hong;Xu, Chungen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권7호
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    • pp.3397-3413
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    • 2016
  • Considering that the layered cellular automata (LCA) are naturally fit for representing image data in various applications, a novel reverse iterative image encryption scheme based on LCA is proposed. Specifically, the plain image is set as the final configuration of an 8-layer CA, and some sequences derived from a random sequence are set as the pre-final configuration, which ensure that the same plain image will never be encrypted in the same way when encrypted many times. Then, this LCA is backward evolved by following some reversible two order rules, which are generated with the aid of a newly defined T-shaped neighborhood. The cipher image is obtained from the recovered initial configuration. Several analyses and experimental results show that the proposed scheme possesses a high security level and executive performance.

비축대칭 디프 드로잉 제품에 대한 공정설계 시스템의 적용 (Application of Process Planning System for Non-Axisymmetric Deep Drawing Products)

  • 박동환;최병근;박상봉;강성수
    • 소성∙가공
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    • 제8권6호
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    • pp.591-603
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    • 1999
  • A computer-aided process planning system for rotationally symmetric deep drawing products has been developed. The application for non-axisymmetric components, however, has been reported yet. Therefore, this study investigates process sequence design in deep drawing process and constructs a computer-aided process planning system for non-axisymmetric motor frame products with elliptical shape. The system developed consists of three modules. The first one os a 3-dimensional modeling module to calculate surface area for non-axisymmetric products. The second one is a blank design module that creates an oval-shaped blank with the identical surface area. The third one is a process planning module based on production rules that play the best important roles in an expert system for manufacturing. The production rules are generated and upgraded by interviewing with field engineers. Especially, drawing coefficient, punch and die radii are considered as main design parameters. The constructed system for elliptical deep drawing products would be very useful to reduce lead time and improve accuracy for production.

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동적 Fault Tree 분석을 이용한 시스템 신뢰도 평가 (System Reliability Evaluation using Dynamic Fault Tree Analysis)

  • 변성일;이동익
    • 대한임베디드공학회논문지
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    • 제8권5호
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    • pp.243-248
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    • 2013
  • Reliability evaluation is important task in embedded system. It can avoid potential failures and manage the vulnerable components of embedded system effectively. Dynamic fault tree analysis is one of the reliability evaluation methods. It can represent dynamic characteristics of a system such as fault & error recovery, sequence-dependent failures. In this paper, the steering system, which is embedded system in vehicles, is represented using dynamic fault tree. We evaluate the steering system using approximation algorithm based on Simpson's rule. A set of simulation results shows that proposed method overcomes the low accuracy of classic approximation method without requiring no excessive calculation time of the Markov chain method.

건축문화유산의 공간경험 디자인 - 지능형 콘텐츠 서비스 플랫폼과 정보표현체계 - (Designing Augmented Spatial Experiences of Architectural Heritage - Information Modeling for Intelligent Content Service Platform -)

  • 장선영;김성준;김성아
    • 대한건축학회논문집:계획계
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    • 제35권4호
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    • pp.15-24
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    • 2019
  • Currently, museums and architectural heritage provide augmented user experiences by incorporating various media technologies. They still, however, suffer from the limitation of entertainment-based and the provision of location-based simple and repetitive contents. In addition, while acting as a key medium of experience for architectural heritage, the concept of space is not properly reflected in current services. The purpose of this study is to design user space experience considering such characteristics of architectural heritage. The spatial experience content and content production platform are defined. This software platform creates content that enhances the experience of the place by giving a context-based digital data associated with space and objects. The spatial experience content is designed as a series of experience sequences. The composition of the sequence borrows the method of film and narrative which segment and connect consecutive experiences on a scene basis considering user's detailed spatial experience. Therefore, content components can be combined and reproduced in various types. Augmented contents were extracted by using rule-based reasoning function of ontology at the moment. As a practical example of architectural heritage, the Seokjojeon Hall is used to reveal a spatial experience scenario.

A review of Chinese named entity recognition

  • Cheng, Jieren;Liu, Jingxin;Xu, Xinbin;Xia, Dongwan;Liu, Le;Sheng, Victor S.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권6호
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    • pp.2012-2030
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    • 2021
  • Named Entity Recognition (NER) is used to identify entity nouns in the corpus such as Location, Person and Organization, etc. NER is also an important basic of research in various natural language fields. The processing of Chinese NER has some unique difficulties, for example, there is no obvious segmentation boundary between each Chinese character in a Chinese sentence. The Chinese NER task is often combined with Chinese word segmentation, and so on. In response to these problems, we summarize the recognition methods of Chinese NER. In this review, we first introduce the sequence labeling system and evaluation metrics of NER. Then, we divide Chinese NER methods into rule-based methods, statistics-based machine learning methods and deep learning-based methods. Subsequently, we analyze in detail the model framework based on deep learning and the typical Chinese NER methods. Finally, we put forward the current challenges and future research directions of Chinese NER technology.

The extension of the largest generalized-eigenvalue based distance metric Dij1) in arbitrary feature spaces to classify composite data points

  • Daoud, Mosaab
    • Genomics & Informatics
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    • 제17권4호
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    • pp.39.1-39.20
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    • 2019
  • Analyzing patterns in data points embedded in linear and non-linear feature spaces is considered as one of the common research problems among different research areas, for example: data mining, machine learning, pattern recognition, and multivariate analysis. In this paper, data points are heterogeneous sets of biosequences (composite data points). A composite data point is a set of ordinary data points (e.g., set of feature vectors). We theoretically extend the derivation of the largest generalized eigenvalue-based distance metric Dij1) in any linear and non-linear feature spaces. We prove that Dij1) is a metric under any linear and non-linear feature transformation function. We show the sufficiency and efficiency of using the decision rule $\bar{{\delta}}_{{\Xi}i}$(i.e., mean of Dij1)) in classification of heterogeneous sets of biosequences compared with the decision rules min𝚵iand median𝚵i. We analyze the impact of linear and non-linear transformation functions on classifying/clustering collections of heterogeneous sets of biosequences. The impact of the length of a sequence in a heterogeneous sequence-set generated by simulation on the classification and clustering results in linear and non-linear feature spaces is empirically shown in this paper. We propose a new concept: the limiting dispersion map of the existing clusters in heterogeneous sets of biosequences embedded in linear and nonlinear feature spaces, which is based on the limiting distribution of nucleotide compositions estimated from real data sets. Finally, the empirical conclusions and the scientific evidences are deduced from the experiments to support the theoretical side stated in this paper.

컴퓨터 시각화 자료가 고등학생들의 수열 개념 이해에 미치는 영향 (A Study of the Effect of Computer's Visual Data about Understanding Concept of Sequence with High School Student)

  • 정인철;황운구;김택수
    • 한국학교수학회논문집
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    • 제10권1호
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    • pp.91-111
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    • 2007
  • 본 연구는 컴퓨터를 활용하여 동적이며 직관적인 시각화 자료를 활용하여 실험에 참가한 고등학교 학생들의 수열 개념에 대해서 수열의 합 공식에 대해 귀납 추론으로 공식을 학생 스스로가 추론할 수 있는지를 알아보고자 했다. 학생들은 스스로가 수열의 합 공식을 사용하지 않고 귀납 추론으로 공식을 유도할 수 있음을 보았다. 또한 무한급수에서의 무한의 오개념인 잠재적 무한의 개념을 가진 학생들이 본 실험 자료로 학습을 하였을 때에 무한의 올바른 개념인 실 무한의 개념을 이해하는데 도움을 주는지에 대하여 연구를 하였는데 실험에 참가한 실험 학생들은 잠재적 무한 개념을 가지고 있었고 동적이고 직관적인 시각화 자료를 가지고 수업 후 실 무한의 개념으로의 변화가 있었다. 이들 학생들은 또한 컴퓨터를 활용하여 동적이고 직관적인 시각화 자료에 대해서 매우 흥미를 느꼈고, 수학에 대한 태도에도 영향을 주었다.

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