Seismic data denoising based on learning-type overcomplete dictionaries

The transform base function method is one of the most commonly used techniques for seismic denoising, which achieves the purpose of removing noise by utilizing the sparseness and separateness of seismic data in the transform base function domain. However, the effect is not satisfactory because it needs to pre-select a set of fixed transform-base functions and process the corresponding transform. In order to find a new approach, we introduce learning-type overcomplete dictionaries, i.e., optimally sparse data representation is achieved through learning and training driven by seismic modeling data, instead of using a single set of fixed transform bases. In this paper, we combine dictionary learning with total variation （TV） minimization to suppress pseudo-Gibbs artifacts and describe the effects of non-uniform dictionary sub-block scale on removing noises. Taking the discrete cosine transform and random noise as an example, we made comparisons between a single transform base, non-learning-type, overcomplete dictionary and a learning-type overcomplete dictionary and also compare the results with uniform and nonuniform size dictionary atoms. The results show that, when seismic data is represented sparsely using the learning-type overcomplete dictionary, noise is also removed and visibility and signal to noise ratio is markedly increased. We also compare the results with uniform and nonuniform size dictionary atoms, which demonstrate that a nonuniform dictionary atom is more suitable for seismic denoising.

An application of matching pursuit time-frequency decomposition method using multi-wavelet dictionaries

In the time-frequency analysis of seismic signals, the matching pursuit algorithm is an effective tool for non-stationary signals, and has high time-frequency resolution and a transient structure with local self-adaption. We expand the time-frequency dictionary library with Ricker, Morlet, and mixed phase seismic wavelets, to make the method more suitable for seismic signal time-frequency decomposition. In this paper, we demonstrated the algorithm theory using synthetic seismic data, and tested the method using synthetic data with 25% noise. We compared the matching pursuit results of the time-frequency dictionaries. The results indicated that the dictionary which matched the signal characteristics better would obtain better results, and can reflect the information of seismic data effectively.

On Translators and Dictionaries

This paper demonstrates the relationship between translators and dictionaries, and the proper approaches to using dictionaries. Dictionaries play an indispensable role in translation through providing definitions and showing various translation skills. However, translators should handle properly the dictionary definition for each word, and interpret within context with consideration of its target readers and the possible effect the translation will possibly have on them.

Analyzing verbs＇ definitions in learner＇s dictionaries based on the schema theory

The synthetic defining style, a predominant way used to define verbs in many dictionaries, is the main factor that makes dictionary definitions vague and incomplete. The present paper argues that instead of the synthetic defining mode, an analytical meaning-explaining way should be used in dictionaries designed for SLA learners. The analytical meanings of verbs are viewed as mini-narratives and form event schemata comprised of three sub-schemata, namely, participant schema, action schema and scenario schema. The three sub-schemata should be clearly fore-grounded in verbs＇ definitions in learners＇ dictionaries.

Comparison and Contrast of Paper-based and On-line Dictionaries

This paper explores the advantages and disadvantages of paper printed and on-line dictionaries in terms of macrostructure and microstructure,availability,portability and practicality etc.Different kinds of dictionaries have unique features that cannot be fully replaced by other kinds.

Low-Rank Sparse Representation with Pre-Learned Dictionaries and Side Information for Singing Voice Separation

At present, although the human speech separation has achieved fruitful results, it is not ideal for the separation of singing and accompaniment. Based on low-rank and sparse optimization theory, in this paper, we propose a new singing voice separation algorithm called Low-rank, Sparse Representation with pre-learned dictionaries and side Information (LSRi). The algorithm incorporates both the vocal and instrumental spectrograms as sparse matrix and low-rank matrix, meanwhile combines pre-learning dictionary and the reconstructed voice spectrogram form the annotation. Evaluations on the iKala dataset show that the proposed methods are effective and efficient for singing voice separation.

On Lexicographical Translation in Bilingual Dictionaries and its Multi-disciplinary Theoretical Basis

Traditionally, in the field of bilingual lexicography, the main task for lexicographers is to provide lexical equivalents in bilingual dictionaries by all possible means. And accordingly, how to provide appropriate or satisfying translation equivalents in bilingual dictionaries is always the centre of attention in bilingual metalexicography. However, the history of bilingual lexicography shows that it has never been an easy task, because of linguistic and cultural anisomorphism. The usual compromise made by most lexicographers is to introduce partial or explanatory equivalents. This recourse means that most bilingual lexicographers, unfortunately, more than often, fail to meet the needs of foreign language learners. Certain misconceptions about the translation equivalents emerge among the language learners, which explains the awkward situation that besets bilingual exicographers. The present contribution aims at perceiving lexicographical translation as a dynamic process by which an adequate semantic system in the target language would be set up to serve as a functionally equivalent defining system. By doing this, bilingual lexicographers should establish a powerful target language semantic network, in which lexicographical sections like verbal illustrations, usage notes and etymologies, etc. would be considered together with the translation equivalents as an integrated whole. This is an attempt to describe the essential features of lexicographical translation and its multi-disciplinary theoretical basis, in the hope that future practice in bilingual lexicography might be improved.

Presenting Knowledge System of International Trade Terms in Business English Learners＇ Dictionaries

Dictionaries should present business encyclopedic knowledge as well as business linguistic knowledge. This paper, taking Incoterms for international trade as an example （with ＂CIF＂ as the case for analysis）, introduces 7 types of dictionary structures （overall structure, frame stzucture/megastrncture, macrostructure, microstzucture, distribution structure, cross-reference stzucture/mediostrncture and access structure）, summarizes the knowledge system of international trade terms （consisting of ＂international trade＂, ＂sets of rules of international trade terms＂, ＂Incoterms 2010＂, and ＂CIF＂）, and illustrates the methods of systematically presenting the knowledge system of international trade terms through dictionary structures in an English-English-Chinese bilingualized business English learners＇ dictionary with Oxford Business English Dictionary for Learners of English （New Edition） as a reference. Such presentation is intended for enhancing business English learners as dictionary users to grasp the knowledge of international trade terms as a whole.

Application of a Web Search Engine in Translating Business Terms in English-Chinese Dictionaries

Web search engines are important tools for lexicography.This paper takes translation of business terms("e-commerce"and"e-business")as an example to illustrate the application of web search engines in English-Chinese dictionary translation,including the methods of(1)finding the potential Chinese equivalents of the English business terms,and(2)selecting typical and proper Chinese equivalents in accordance with the frequencies and the meanings of the English business terms respectively.

Scaffolding Information of Learner’s Dictionaries for L2 Writing: A User Perspective

As a major resource and tool of language learning, learner’s dictionaries have provided sufficient information forL2 writing, which serves as a good guide of peer feedback. Hence, learner’s dictionaries are an indispensable partof scaffolding in the L2 writing feedback system. However, the effects of dictionary use in L2 writing have longbeen ignored either in L2 writing pedagogy or in learner lexicography. By applying the concept of “scaffolding” topeer feedback as the theoretical framework, this study first clarifies three distinct types of scaffolding informationpresented in current English learner’s dictionaries, and then makes an investigation into EFL learners’ perceptionand practical use of scaffolding information in their English writing. Results show that most EFL learners havepositive attitudes towards scaffolding information and its role in motivating effective feedback in English writing.But their practical use of such information is not satisfactory owing to their inadequate skills and knowledge ofdictionary use. This reflects a high demand of a dictionary use course in universities, which will help to raise EFLlearners’ dictionary use efficiency as well as improve English teachers’ lexicographical expertise in English writingpedagogy.

A Study on the Compilation of Dictionaries for Teaching Chinese as a Foreign Language Based on the Second Language Acquisition Theory

This article intends to demonstrate the principles for dictionary compilation.To summarize,general rules are to be followed.At the same time,this article probes into the differences of Chinese to Chinese dictionary,Chinese to foreign language dictionary,dictionaries for the preparation of certain exams,learner’s dictionaries for reviewing errors,dictionaries with multimedia and dictionaries built via the Internet..In all,one of the key factors for dictionary compilation is the professionalism of editors and writers.The training of the people involved is vital,which would contribute to setting up a better order of the market.Acknowledgements should also be given to achievements in dictionary compilation.Revisions and polishing are required to improve the dictionaries on the market that have already won the acclaim so as to put their influence to the best display.

A Polish College Students＇ Use of Dictionaries in Text Production

The study, conducted in the academic year 2008, explores the potential differences in the use of a dictionary in support of a standard writing task by two student groups at two different proficiency levels. Fifty seven students working on a real classroom assignment were observed; in order to make sure that the subjects behaved as they normally would, they had not been informed that their dictionary behavior was to be observed. The study which shows that the need for a dictionary is smaller in the case of more advanced students may be of interest to those foreign language teachers who fear that giving a student an unlimited access to a dictionary may hamper the development of his expressive abilities. In turn, a marked preference on the part of more advanced students for an L I-L2, paralleled by a sustained interest in information categories typically placed in foreign learner＇s dictionaries suggests that advanced language learners writing in English would probably opt for a lexicographic product combining the best of both dictionary types： an LI-L2 and an MLD.

Understanding media and electronic dictionaries

As the first father and leading prophet of the electronic age,Marshall McLuhan's media theory can present us a completely new approach towards the understanding of electronic dictionaries.In this paper,the author attempts to explore the interrelationship between major concepts of Marshall McLuhan's media theory and electronic dictionaries.

基于数据挖掘的痛经用药规律研究

目的:基于数据挖掘技术分析《中医方剂大辞典》中治疗痛经方剂的用药规律。方法:根据纳入与排除标准筛选出《中医方剂大辞典》中治疗痛经的方剂,对其进行方药名称规范,运用Excel、IBM SPSS Modeler 18.0、IBM SPSS Statistics 26.0等进行频数统计、关联规则分析、聚类分析及因子分析。结果:共纳入151首治疗痛经的方剂,涉及中药191味;其中出现频次≥10的中药为当归、川芎、延胡索、白芍、香附、甘草等共36味,药效以补虚药、活血化瘀药、理气药为主,药性偏温、寒、平,药味则偏辛、苦、甘,多入肝、脾、心经。选取出现频次≥25的13味高频药物进行关联规则分析,得到“当归-川芎“”当归-香附-川芎“”当归-熟地黄-白芍-川芎”等常用药对21组,并通过提升关联规则的支持度得到“当归-川芎-白芍”核心组合。进行高频药物聚类分析得出4类药物组合,C1:白芍、熟地黄、川芎、当归;C2:牡丹皮、茯苓;C3:香附、甘草;C4:桃仁、红花,因子分析得到5个公因子。结论《:中医方剂大辞典》中治疗痛经以补血活血、化瘀散结、疏肝理气为主。

基于知识图谱的多特征融合谣言检测方法

为了解决谣言检测中由于缺乏外部知识而导致模型难以感知内隐信息,进而限制了模型挖掘深层信息的能力这个问题,提出了基于知识图谱的多特征融合谣言检测方法(KGMRD)。首先,对于每个事件,将帖子和评论共同构建为一个文本序列,并利用分类器从中提取情感特征,利用ConceptNet基于文本构造其知识图谱,将知识图谱中的实体表示利用注意力机制与文本的语义特征进行聚合,进而得到增强的语义特征表示;其次,在传播结构方面,对于每个事件,基于帖子的传播转发关系构建传播结构图,使用DropEdge对传播结构图进行剪枝,从而得到更有效的传播结构特征;最后,将得到的特征进行融合处理得到一个新的表示。在Weibo、Twitter15和Twitter16三个真实数据集上,使用SVM-RBF等七个模型作为基线进行了对比实验。结果表明:对比当前效果最好的基线,KGMRD方法在Weibo数据集的ACC指标提升了1.1%;在Twitter15和Twitter16数据集的ACC指标上提升了2.2%,证明了KGMRD方法是合理的、有效的。

探寻中国译学话语的发展之路写在《中国译学大辞典》(第二版)出版之前

一部术语史就是一部专业话语的历史。术语是专业话语的基本要素,术语系统的建设是反映相关学科进步和走向的一面镜子。本文概述了《中国译学大辞典》(第二版)的编纂思想,介绍了该辞典的编辑方针、收选原则和编辑实践,从中可以看出我国译学术语的积累与译学话语体系的完善是同步的。这部辞典见证了翻译学科酝酿-诞生-发展的过程。

压缩感知字典迁移重构的小样本轴承故障诊断

针对实际应用中智能轴承故障诊断面临标签样本严重不足的问题,提出一种结合压缩感知、字典学习和迁移的数据增强算法,用于小样本故障诊断研究。首先,利用源域标签数据通过小波包字典学习和优化方法生成特定源域字典,并得到共享表示系数,获取故障内在信息;之后采用少量目标域信号微调共享表示系数,并更新源域字典生成迁移字典;最后通过共享表示系数和迁移字典生成大量具有目标域特征的新样本,实现数据增强。采用常用的深度故障诊断网络对该数据增强算法进行了诊断性能验证,结果表明该方法产生的信号具有故障的有效信息,用于模型训练和识别能够取得较好的诊断性能。该方法为小样本故障诊断问题提出了新的思路。

融媒辞书的理论方法与实践演化

从20世纪80年代电子词典出现,到2019年中国辞书学会提出融媒辞书概念,辞书界认识到,辞书从“多媒体”到“融媒体”的演化,不只是“媒体”量的增加,而是涉及媒体与模态之间和模态与模态之间的融合机制等问题;媒体形式的融合应促进模态内容的融合,释义和注释内容的融合才是融媒辞书的核心。模态是被释义词的指称通过认知感官反映在人们大脑中的心理映像,意义在多模态语境中更易于理解。融媒辞书应根据语词释义的需要,把相关的媒介、媒体、模态融合为一体,使之共同参与语义的表征过程,成为重要的释义元素。本文意在厘清融媒辞书的核心内涵、融合要素、融合路径、模态元素和理论基础,将融媒辞书编纂的文本特征概括为:两极化、数据化、模态化、平台化、网络化;并结合实例,从融媒辞书的制作资源、知识文本和数字技术3个方面来考察现有数字词典的融媒特征如何实现及其状况。

基于聚类与稀疏字典学习的近似消息传递

基于传统字典学习的近似消息传递(approximate message passing,AMP)算法对训练样本数量的需求较高,且运算成本较高。本文引入双稀疏模型,构建基于稀疏字典学习的AMP框架,降低迭代过程中字典学习对训练样本数量的需求,提高压缩感知图像重建的质量与效率。进一步,提出基于聚类与稀疏字典学习的AMP算法,在迭代过程中依据图像块特征进行分类,并为各类图像块分别学习稀疏字典,实现自适应去噪。与基于传统字典学习的AMP算法相比,基于聚类与稀疏字典学习的AMP算法能够将重建图像的峰值信噪比提高0.20~1.75 dB,并且能够将运算效率平均提高89%。

汉语词典学研究70年

从词典学理论与价值研究、词典编纂与修订研究、词典编纂的个案研究、词典编纂的方法创新四个方面梳理汉语词典学研究70年来的发展脉络,回顾汉语词典学的研究情况,继而得出词典学研究具有以编纂实践为基础、研究阶段特点明显和期刊发表阵地集中的特点,同时分析汉语词典学的研究趋势,并对其未来发展提出若干建议。