Method to Remove Handwritten Texts Using Smart Phone

To remove handwritten texts from an image of a document taken by smart phone,an intelligent removal method was proposed that combines dewarping and Fully Convolutional Network with Atrous Convolutional and Atrous Spatial Pyramid Pooling(FCN-AC-ASPP).For a picture taken by a smart phone,firstly,the image is transformed into a regular image by the dewarping algorithm.Secondly,the FCN-AC-ASPP is used to classify printed texts and handwritten texts.Lastly,handwritten texts can be removed by a simple algorithm.Experiments show that the classification accuracy of the FCN-AC-ASPP is better than FCN,DeeplabV3+,FCN-AC.For handwritten texts removal effect,the method of combining dewarping and FCN-AC-ASPP is superior to FCN-AC-ASP alone.

A Comparative Study of Artificial Intelligence and Translation Software in Chinese-English Translation:A Focus on Literary and Technical Texts

In recent years,the domain of machine translation has experienced remarkable growth,particularly with the emergence of neural machine translation,which has significantly enhanced both the accuracy and fluency of translation.At the same time,AI also showed its tremendous advancement,with its capabilities now extending to assisting users in a multitude of tasks,including translation,garnering attention across various sectors.In this paper,the author selects representative sentences from both literary and scientific texts,and translates them using two translation software and two AI tools for comparison.The results show that all four translation tools are very efficient and can help with simple translation tasks.However,the accuracy of terminology needs to be improved,and it is difficult to make adjustments based on the characteristics of the target language.It is worth mentioning that one of the advantages of AI is its interactivity,which allows it to modify the translation according to the translator’s needs.

Study on the Textual Coherence Function of Conjunctions in Political Texts and Their Translation Reconstruction

The assessment of translation quality in political texts is primarily based on achieving effective communication.Throughout the translation process,it is essential to not only accurately convey the original content but also effectively transform the structural mechanisms of the source language.In the translation reconstruction of political texts,various textual cohesion methods are often employed,with conjunctions serving as a primary means for semantic coherence within text units.

Short-Term Memory Capacity across Time and Language Estimated from Ancient and Modern Literary Texts. Study-Case: New Testament Translations

We study the short-term memory capacity of ancient readers of the original New Testament written in Greek, of its translations to Latin and to modern languages. To model it, we consider the number of words between any two contiguous interpunctions Ip, because this parameter can model how the human mind memorizes “chunks” of information. Since IP can be calculated for any alphabetical text, we can perform experiments—otherwise impossible— with ancient readers by studying the literary works they used to read. The “experiments” compare the IP of texts of a language/translation to those of another language/translation by measuring the minimum average probability of finding joint readers (those who can read both texts because of similar short-term memory capacity) and by defining an “overlap index”. We also define the population of universal readers, people who can read any New Testament text in any language. Future work is vast, with many research tracks, because alphabetical literatures are very large and allow many experiments, such as comparing authors, translations or even texts written by artificial intelligence tools.

Social Media Cyberbullying Detection on Political Violence from Bangla Texts Using Machine Learning Algorithm

When someone threatens or humiliates another person online by sending those unpleasant messages or comments, this is known as Cyberbullying. Recently, Bangla text has been used much more often on social media. People communicate with others on social media through messages and comments. So bullies use social media as a rich environment to bully others, especially on political issues. Fights over Cyberbullying on political and social media posts are common today. Most of the time, it does a lot of damage. However, few works have been done for monitoring Bangla text on social media & no work has been done yet for detecting the bullying Bangla text on political issues due to the lack of annotated corpora and morphologic analyzers. In this work, we used several machine learning classifiers & a model. That will help to detect the Bangla bullying texts on social media. For this work, 11,000 Bangla texts have been collected from the comments section of political Facebook posts to make a new dataset and labelled the data as either bullied or not. This dataset has been used to train the machine learning classifier. The results indicate that Random Forest achieves superior accuracy of 91.08%.

Research on Translation Strategies of Political Texts for International Publicity from the Perspective of Eco-Translatology

Eco-translatology provides a new perspective and methodology for the international publicity translation of political texts.This paper applies the viewpoint and methodology of eco-translatology,focuses on the three-dimensional transformation of language,culture,and communication,and discusses how translators can adapt to the eco-environment of political texts through the specific example of the keynote speech of China’s president at the opening ceremony of the Third Belt and Road Forum for International Cooperation and select suitable translation strategies and techniques to achieve an ecological balance of the target text in multiple dimensions.

Deep-BERT:Transfer Learning for Classifying Multilingual Offensive Texts on Social Media

Offensive messages on social media,have recently been frequently used to harass and criticize people.In recent studies,many promising algorithms have been developed to identify offensive texts.Most algorithms analyze text in a unidirectional manner,where a bidirectional method can maximize performance results and capture semantic and contextual information in sentences.In addition,there are many separate models for identifying offensive texts based on monolin-gual and multilingual,but there are a few models that can detect both monolingual and multilingual-based offensive texts.In this study,a detection system has been developed for both monolingual and multilingual offensive texts by combining deep convolutional neural network and bidirectional encoder representations from transformers(Deep-BERT)to identify offensive posts on social media that are used to harass others.This paper explores a variety of ways to deal with multilin-gualism,including collaborative multilingual and translation-based approaches.Then,the Deep-BERT is tested on the Bengali and English datasets,including the different bidirectional encoder representations from transformers(BERT)pre-trained word-embedding techniques,and found that the proposed Deep-BERT’s efficacy outperformed all existing offensive text classification algorithms reaching an accuracy of 91.83%.The proposed model is a state-of-the-art model that can classify both monolingual-based and multilingual-based offensive texts.

针对文本情感分类任务的textSE-ResNeXt集成模型

针对深度学习方法中文本表示形式单一,难以有效地利用语料之间细化的特征的缺陷,利用中英文语料的不同特性,有区别地对照抽取中英文语料的特征提出了一种新型的textSE-ResNeXt集成模型。通过PDTB语料库对语料的显式关系进行分析,从而截取语料主要情感部分,针对不同中、英文情感词典进行情感程度关系划分以此获得不同情感程度的子数据集。在textSE-ResNeXt神经网络模型中采用了动态卷积核策略,以此对文本数据特征进行更为有效的提取,模型中融合了SEnet和ResNeXt,有效地进行了深层次文本特征的抽取和分类。将不同情感程度的子集上对textSE-ResNeXt模型采用投票集成的方法进一步提高分类效率。分别在中文酒店评论语料和六类常见英文分类数据集上进行实验。实验结果表明了本模型的有效性。

On Creative Strategies for Translating Guangxi Tourism Texts into English under the Perspective of ASEAN

Guangxi tourism texts are a kind of tool to show China's image.However,there are still lots of problems despite certain achievements in recent years in Chinese-to-English(C-E) translation of tourism texts.So,how to improve the quality of tourism materials is of great significance practically.The aim is to adopt the"Creation"Thought of Guo Moruo that emphasizes creation,charming translation,having empathy with the source language and experience,aiming at discovering proper and feasible translation standards and strategies and making it better serve for the tourism development between Guangxi and ASEAN countries.

Sentiment Analysis of Short Texts Based on Parallel DenseNet

Text sentiment analysis is a common problem in the field of natural language processing that is often resolved by using convolutional neural networks(CNNs).However,most of these CNN models focus only on learning local features while ignoring global features.In this paper,based on traditional densely connected convolutional networks(DenseNet),a parallel DenseNet is proposed to realize sentiment analysis of short texts.First,this paper proposes two novel feature extraction blocks that are based on DenseNet and a multiscale convolutional neural network.Second,this paper solves the problem of ignoring global features in traditional CNN models by combining the original features with features extracted by the parallel feature extraction block,and then sending the combined features into the final classifier.Last,a model based on parallel DenseNet that is capable of simultaneously learning both local and global features of short texts and shows better performance on six different databases compared to other basic models is proposed.

Implications of Reportage Texts in EFL Teaching

In this paper, the author discusses implications of original reportage texts in EFL teaching and learning from the perspectives of socio-linguistics and pragmatic competence. The author also discusses a proper approach for teaching medical postgraduate students, which is centered on students and based on research. This approach for teaching and leaning has been proved effective and students have improved in their socio-linguistic and pragmatic competences. This approach should have implications to EFL teachers who teach students of other specialties.

Intercultural Communication and Chinese Tourism Texts Translation

Intercultural communication language plays a crucial role in our global tourism.When we are doing translation we are doing intercultural communication in a sense,so it is necessary for translators to have intercultural communication awareness and be sensitive to the cultural elements in translation.Taking the perspective of intercultural communication,this paper analyses the cultural elements in Chinese tourism material translation in terms of culturally-loaded words and terms,and presents certain translation techniques a translator can use to deal with culturally-loaded words in their translation.

The Analysis of Previous Research on Fuzziness in Legal Texts

Different from precision,fuzziness owns some special features.This paper tries to do a preliminary analysis of previous research on fuzziness and fuzzy expressions in legal texts.

A Study on C-E Translation of Product Introductory Texts on Company Websites Under Skopos Theory

This paper takes the C-E translation of product introductory texts on official websites of three mobile phone makers as the study object under the Skopos theory, with an aim to identify and analyze the distinctive translation features of such special type of text. The exhausted parse and analysis bring out the findings that there exists a significant translation difference between the Chinese and English-version product introductory texts on official websites. It is found that Chinese introductory texts are more inclined to rely on exquisite words and redundant expressions to describe products’ features and functions, while switching to the corresponding English version, simple vocabularies and compact sentence structure are more frequent. Hereafter, this paper raises two practical guidelines to instruct translation activities in business contexts.

Skopos theory and translating strategies of cultural elements in tourism texts

Tourism texts （shortened as TT） have become a principal means of promoting tourism in China. Cultural elements are abundant in those texts. Therefore, the proper understanding and rendering of such messages is the key to the quality of TT translation. Based on Skopos theory the paper focuses on the translating strategies of TT cultural elements.

Using GM to Analyze EST Texts

The role of the grammatical metaphor （GM） theory to systemic-functional linguistics （SFL） as well as to metaphor studies has been generally acknowledged. Based on the framework of GM theory in SFL, this thesis, by conducting a statistical analysis of the distribution of 13 types of GM in 20 English for science and technology （EST） texts which are chosen at random and aimed at different readers, is intended, on the one hand, to test and verify the applicability and feasibility of Halliday＇s grammatical metaphor theory as well as the correctness of Halliday-Martin＇s claim and on the other, to analyze the reasons for using GM, especially experiential GM substantially in EST texts.

Exploring EFL Learners Reading Comprehension Problems in Reading ESP Texts

By considering the fact that in EFL （English as foreign language） contexts learners need reading comprehension skill more than other skills in their academic studies, reading comprehension should be attached more importance especialy in ESP （English for specific purposes） classes in which reading ability plays a crucial role in the students＇ academic success. But in order to help learners in the best possible way, teachers need to identify their learners＇ problems in reading ESP texts. Detecting the problematic areas for the students will assist teachers better design and apply appropriate methods and strategies to solve their students＇ reading comprehension problems. Therefore, the following research was an attempt to explore the EFL learners＇ reading comprehension problmes in reading ESP texts in ESP classes. For the purpose of the study, five passages from their coursebook were selected and they were asked to underline the syntactically problematic parts in the passages. The subjects of the study were composed of 185 homogenous engineering students who were learning english as a foregin langauge. Chi-square analysis showed that 15 major syntactic categories are serious hurdle to reading comprehension of ESP texts. The results and implications are discussed in the light of TLA （teachers＇ language awareness）.

CUNEIFORM TEXTS IN JAPANESE COLLECTIONS

In early 2009, I had the chance to visit six Japanese university libraries or museums, which house 15 cuneiform tablets, seven royal inscriptions and one cylinder seal. Most of them seem to have been acquired from some

On Translation of Classical Chinese Literary Texts

Chinese classical literature is precious treasure of the world literature. In order to transmit and carry forward it, translation is an effective and necessary way, especially as the development ofglobalization and China＇s economy. This paper mainly discusses the history, difficulties, ways and skills on translation of classical Chinese literary texts in this paper.

AB104.Validation of the international reading speed texts in a Canadian sample

Background:The International Reading Speed Texts(IReST)were developed in Europe as a standardized measure to assess continuous reading in normally sighted and visually impaired individuals.The IReST is used throughout the United States and Canada to assess reading speed;however,the normative values may not be valid in North America(NA).Additionally there are no normative values for individuals with visual impairments.The aim of this study was to validate the IReSTs in a normally sighted English-speaking NA sample with and without a simulated reduction in visual acuity.Methods:Fifty undergraduate students from Concordia University participated in this study.Participants were systematically assigned to a counterbalanced order of testing conditions and were asked to read all 10 IReSTs aloud.The normal and impaired vision conditions were counterbalanced such that the first set of five IReSTs were read with either the participants normal/corrected-to-normal vision or with a simulated 20/80 visual impairment.Results:Multiple two-sample dependent t-tests using a Holm-Bonferroni correction for multiple comparisons were used to compare the IReST values(means and standard deviations)to the current sample;the results showed statistically significant differences between the current samples mean reading speed and the values provided by the IReSTs.In all cases,P were equal to or less than 0.005.Mean difference scores ranged from 14.87 to 30.05 wpm,with 95%confidence intervals ranging from 4.82 to 43.32.Measures of effect size using bias corrected Hedge’s g*ranged from 0.83 to 1.32,with 95%confidence intervals ranging from 0.25 to 1.93.Multiple two-sample dependent t-tests using a Holm-Bonferroni correction for multiple comparisons were used to compare the mean reading speed in wpm of the normal and impaired vision conditions;the results showed statistically significant differences between the mean reading speeds of the normal vision condition and the simulated impairment condition on the IReSTs.In all cases,the P were less than 0.001.Mean difference scores ranged from 25.44 to 41.8 wpm,with 95%confidence intervals ranging from 21.66 to 46.Measures of effect size using bias corrected Hedge’s g*ranged from 2.74 to 3.81,with 95%confidence intervals ranging from 1.97 to 4.74.Further Bayesian analyses revealed BF10 factors ranging from 1.277×107 to 7.334×1011,indicating decisive evidence for the research.Conclusions:There are statistically significant differences in reading speed between the NA English sample and the normative values established by the IReST;such that reading speeds of the NA English sample are slower than the normative values of the IReST.Additionally,participants in the simulated impairment condition read the IReSTs significantly slower than the normal vision condition.