Idioms are a very important part of the English language: you are told that if you want to go far (succeed) you should pull your socks up (make a serious effort to improve your behaviour, the quality of your work, etc.) and use your grey matter (brain).1 Learning and translating idioms have always been very difficult for foreign language learners. The present paper explores some of the reasons why English idiomatic expressions are difficult to learn and translate. It is not the aim of this paper to attempt a comprehensive survey of the vast amount of material that has appeared on idioms in Adams and Kuder (1984), Alexander (1984), Dixon (1983), Kirkpatrick (2001), Langlotz (2006), McCarthy and O'Dell (2002), and Wray (2002), among others. The paper concentrates on idioms as a learning-translation problem; it makes no claim to be comprehensive or academically rigorous. Leech (1989) defines an idiom as follows: “An idiom is a group of two or more words which we have to treat as a unit in learning a language. We cannot arrive at the meaning of the idiom just by adding together the meanings of the words inside it. E.g.John and Mary usedto be hardup (='They had very little money'.)”(P.186) To be more exact, an idiom is a sequence of words which is semantically and syntactically restricted, so that they function as a single unit. From a semantic point of view, the meanings of the individual words cannot be summed to produce the meanings of the idiomatic expression as a whole. Thus, fly off the handle, which means lose one's temper, cannot be understood in terms of the meanings of fly, off, or handle. The idiom phrase hot air, which means empty or boastful talk, is neither hot nor air; with hot air we are dealing with a set phrase where the meaning cannot be suggested on the basis of the two constituent words. The idiomatic meaning of spill the beans in So who spilt the beans (=told the secret) about her affair with David? has nothing to do with beans or with spilling in its literal sense. The foreign-language learner is left trying to figure out where and how the beans were spilt. From a syntactic viewpoint, the constituent parts of an idiom often do not permit the usual variability they display in other contexts. The point to be emphasized here is this: most idioms do not lend themselves easily to manipulation by speakers and writers; they are invariable and must be learned as wholes, but concord ofnumber, person and gender in the idiom phrase is still necessary, i.e. the verbs must be put into the correct form, and pronouns must agree with their antecedents: I don't give a hoot for her opinion! 2 • She doesn't give a hoot for my opinion! etc.)║He won, but only by the skin of his teeth2• She won, but only by the skin of her teeth• Iwon, but only by the skin ofmy teeth,I had to run for the train, and caught it by the skin of myteeth, etc.║He kept pullingmy arm, throwing me off my balance 2 • She kept pulling his arm, throwing him off his balance • We kept pullingher arm, throwingher offher balance, etc.2 The present paper is divided into five parts, as follows: Part I: An Overview; PART II: Learner’s Difficulties with Idioms; PART III: Some Pedagogical recommendations and Suggestions about Idioms; Part IV: Activities to Practice Idiomatic Expressions; Part V: Summary and Conclusion.
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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Abstract
The aim of the current research is to prepare an integrated learning program based on mathematics standards for the next generation of the NYS and to investigate its impact on the development of the teaching performance of middle school mathematics teachers and the future thinking skills of their students. To achieve the objectives of the research, the researcher prepared a list of mathematics standards for the next generation, which were derived from a list of standards. He also prepared a list of the teaching competencies required for middle school mathematics teachers in light of the list of standards, as well as clarified the foundations of the training program and its objectives and the mathematical
... Show MoreIn the knowledge society, artificial intelligence (AI) forms a cornerstone of global education. This quasi-experimental study examines the impact of an Intelligent Adaptive Learning Strategy (IALS) on flexible thinking (FT) and academic achievement among 60 3rd-year undergraduate students at the College of Education/University of Baghdad (experimental n = 30; control n = 30). The IALS was implemented via an AI-supported educational platform, while the control group received conventional instruction. Post-test intervention assessments included an FT test (10 items, content validity = 0.89, Cronbach’s α = 0.87) and an achievement test (10 objective items, α = 0.85). Results revealed statistically significant superiority of the exp
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Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil
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This research aims to know the role and impact of participation in the capabilities of human resources programs, and for the purpose of measuring it has been determined the dimensions of these two variables by relying on standards for this purpose, was chosen as the Ministry of Higher Education and Scientific Research / device supervision and scientific calendar as one of the important departments in the ministry and includes a large number of individuals at different organizational levels for the purpose of answering a questionnaire prepared for the purpose of measurement and access to the results and the achievement of the objectives of the research and which ha
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