{"title":"Multiple Arabic Equivalents to English Medical Terms","authors":"Reima Al-Jarf","doi":"10.30560/ILR.V1N1P102","DOIUrl":"https://doi.org/10.30560/ILR.V1N1P102","url":null,"abstract":"Translation of medical texts poses several challenges to undergraduate student-translators due to multiple Arabic equivalents to English medical terms. For medical terms such as clinical, intensive care, polyp, and osteoporosis several Arabic equivalents exist. A sample of English medical terms with multiple Arabic equivalents was collected from several English-Arabic medical dictionaries to find out the types of multiple Arabic equivalents given, the shortcomings of Arabic equivalents, and the difficulties that students have with multiple Arabic equivalents. Two lists of categories with definitions and examples were developed and used in classifying and evaluating the equivalents. In addition, students answered an Arabic medical terminology test and responded to a questionnaire-survey to find out their difficulties. Results of the analysis and evaluation of the Arabic equivalents, medical terminology test, and responses to the questionnaire-survey are reported in detail. Recommendations for translation instruction are also given.","PeriodicalId":261061,"journal":{"name":"International Linguistics Research","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126849511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"You, Too, Will Speak English Soon: The Pros and Cons of English as a Business Lingua Franca","authors":"H. Wiggers","doi":"10.30560/ILR.V1N1P80","DOIUrl":"https://doi.org/10.30560/ILR.V1N1P80","url":null,"abstract":"This paper discusses the increasing use of English as a Business Lingua Franca (BELF). In particular, this paper examines case studies from several companies located in diverse countries (Japan, Germany, and Finland), where English has been implemented as an internal lingua franca. The case studies show that most employees at these companies adjusted to BELF in a very pragmatic manner, while others considered the employment of BELF to be an intrusive course of action. This paper also investigates how BELF is viewed by native speakers of English and argues that attitudes towards foreign language learning by native speakers of English may constitute an impediment to efficient communication between speakers of different native languages and backgrounds. Finally, this papers shows that the acceptance of BELF, at least to a certain degree, is dependent on attitudes towards the global spread of English.","PeriodicalId":261061,"journal":{"name":"International Linguistics Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129059706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Miss Predicting Readability of Health Educational Resources for Children Using Semantic Features","authors":"Yanmeng Liu","doi":"10.30560/ilr.v4n2p10","DOIUrl":"https://doi.org/10.30560/ilr.v4n2p10","url":null,"abstract":"The success of health education resources largely depends on their readability, as the health information can only be understood and accepted by the target readers when the information is uttered with proper reading difficulty. Unlike other populations, children feature limited knowledge and underdeveloped reading comprehension, which poses more challenges for the readability research on health education resources. This research aims to explore the readability prediction of health education resources for children by using semantic features to develop machine learning algorithms. A data-driven method was applied in this research:1000 health education articles were collected from international health organization websites, and they were grouped into resources for kids and resources for non-kids according to their sources. Moreover, 73 semantic features were used to train five machine learning algorithms (decision tree, support vector machine, k-nearest neighbors algorithm, ensemble classifier, and logistic regression). The results showed that the k-nearest neighbors algorithm and ensemble classifier outperformed in terms of area under the operating characteristic curve sensitivity, specificity, and accuracy and achieved good performance in predicting whether the readability of health education resources is suitable for children or not.","PeriodicalId":261061,"journal":{"name":"International Linguistics Research","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134055548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
