＂I＇m here to discuss my final grade!＂ A study of the speech act of complaint by Malaysian ESL learners

The present study investigates the preferred strategies of the speech act of complaint by Malaysian ESL learners. The subjects were selected from Malaysian university students majoring in English at University Sains Malaysia. Data were collected through an open-ended questionnaire in the form of a discourse completion task and a semi-structured interview. The responses were analyzed based on Rinnert and Nogami＇s （2006） taxonomy of the speech act of complaint to examine the main components of complaint, the level of directness and the degree of mitigation. It is anticipated that the findings will be able to provide valuable insights into teaching and learning English in non-native settings.

Application of intelligence-based computational techniques for classification and early differential diagnosis of COVID-19 disease

Clinical methods are used for diagnosing COVID-19 infected patients,but reports posit that,several people who were initially tested positive of COVID-19,and who had some underlying diseases,turned out having negative results after further tests.Therefore,the performance of clinical methods is not always guaranteed.Moreover,chest X-ray image data of COVID-19 infected patients are mostly used in the computational models for COVID-19 diagnosis,while the use of common symptoms,such as fever,cough,fatigue,muscle aches,headache,etc.in computational models is not yet reported.In this study,we employed seven classification algorithms to empirically test and verify their efficacy when applied to diagnose COVID-19 using the aforementioned symptoms.We experimented with Logistic Regression(LR),Support Vector Machine(SVM),Naïve Byes(NB),Decision Tree(DT),Multilayer Perceptron(MLP),Fuzzy Cognitive Map(FCM)and Deep Neural Network(DNN)algorithms.The techniques were subjected to random undersampling and oversampling.Our results showed that with class imbalance,MLP and DNN outperform others.However,without class imbalance,MLP,FCM and DNN outperform others with the use of random undersampling,but DNN has the best performance by utilizing random oversampling.This study identified MLP,FCM and DNN as better classifiers over LR,NB,DT and SVM,so that healthcare software system developers can adopt them to develop intelligence-based expert systems which both medical personnel and patients can use for differential diagnosis of COVID-19 based on the aforementioned symptoms.However,the test of performance must not be limited to the traditional performance metrics.

Sub-Saharan Migrants in Moroccan Print Media:Discourses of Violence,Security,and Illegality before and after the Migration Reform

Morocco currently occupies a curious position as both a country of transit and a country of installation for migrants originating from Sub-Saharan countries.Even though the new migration policy reform has provided migrants with some new rights,public opinion is still unready to shape and reshape their perceptions of’black’African migrants.The situation of those migrants has grabbed media attention,especially in newspapers;hundreds of articles and reports have been written in newspapers,criticising or denouncing the phenomenon.Although the currently available body research has tended to neglect the linguistic ways in which such media convey meaning along the side of their use of images,little attention has been paid to language-based media.As such,this paper scrutinises(i)the depiction of Sub-Saharan migrants in Moroccan print newspapers headlines before and after the migration reform,and(ii)it considers how reports on‘black’African migrants in Morocco may lead to propagating stereotypical acts and xenophobia towards this category.The study examines the topics covered and reveals the patterns used in the coverage of related topics,such as illegality and violence,before and after the new migration policy in 2013.With these objectives in mind,this study is based on qualitative data of news items and reports from the two daily printed newspapers,Assabah and Almassae.Relying on Critical Discourse Analysis and Content Analysis has demonstrated an overgeneralisation of Sub-Saharan migrants in news headlines in general.The results also show a dramatic change in the thematic coverage during the selected period.