Providing Language Services in Small Health Care Provider Settings: Examples From the Field

Assesses recent innovations in language service programs and activities at healthcare provider settings with ten or fewer clinicians. Includes an eight-step plan to help providers develop a strategy to meet the needs of their patients

JTEC panel report on machine translation in Japan

The goal of this report is to provide an overview of the state of the art of machine translation (MT) in Japan and to provide a comparison between Japanese and Western technology in this area. The term 'machine translation' as used here, includes both the science and technology required for automating the translation of text from one human language to another. Machine translation is viewed in Japan as an important strategic technology that is expected to play a key role in Japan's increasing participation in the world economy. MT is seen in Japan as important both for assimilating information into Japanese as well as for disseminating Japanese information throughout the world. Most of the MT systems now available in Japan are transfer-based systems. The majority of them exploit a case-frame representation of the source text as the basis of the transfer process. There is a gradual movement toward the use of deeper semantic representations, and some groups are beginning to look at interlingua-based systems

Principles and Applications of Data Science

Data science is an emerging multidisciplinary field which lies at the intersection of computer science, statistics, and mathematics, with different applications and related to data mining, deep learning, and big data. This Special Issue on “Principles and Applications of Data Science” focuses on the latest developments in the theories, techniques, and applications of data science. The topics include data cleansing, data mining, machine learning, deep learning, and the applications of medical and healthcare, as well as social media

High Achieving English Language Learners: The Schooling Experiences of Former Ell Students Enrolled in Advanced High School Courses

With immigration at record levels, public schools are educating an increasing number of English Language Learners who are less academically successful. There is a dearth of research on academically successful former ELL students. The purpose of this study was to identify the shared schooling experiences, shared success factors, and shared inhibiting factors of former ELL students enrolled in AP and IB coursework at the high school level. This phenomenological study used structured student and teacher interviews as well as classroom observations for the generation and collection of data. Seven students participated in this study. This study found that former ELL students experienced positive teacher-student relationships, high expectations, teacher clarity, academic support networks, and course selection coaching at the middle school level. Participants also shared success factors to include high levels of success expectancy, school engagement, and early family support. Student inhibiting factors were related to low levels of school-family engagement at the high school level, course tracking, and threshold English language development. Student academic networks, explicit vocabulary instruction, and participation in extracurricular activities increased the acculturation of ELL students thus enabled them to access the college prep curriculum. This study found that teacher practice and school programs provided ELL and former ELL students with more positive academic trajectories

The Tertiary English Language Curriculum in China and its Delivery: A Critical Study

This thesis investigates the tertiary English language curriculum in China and its delivery, focusing on the intensive reading (IR) course for students studying English at degree level. It examines the extent to which IR realises the aims of the current English curriculum, revised in 2000 with the intention of introducing more contemporary approaches to English language teaching. It also examines how IR relates to the behaviour and beliefs of two teachers who deliver it, and to their students' participation and views. The study applies an ethnographic approach to collect its data and discourse analysis to analyse classroom discourse constructed in teacher-student interaction. Data was collected at a university in China and consists of classroom observations, audio recordings of classes, interviews with the teachers and students being observed, government documents, teachers' syllabi and teaching plans. Data analysis focuses on the textbooks that are used to deliver the revised curriculum; how teachers use these textbooks, and their mediation of book knowledge via the use of PowerPoint slides; and the language choices made by teachers in delivering knowledge from the textbooks and PowerPoint slides. Data analysis reveals that classroom practice is very much at odds with the principles set out in the 2000 Curriculum. Whereas this emphasises the use of Communicative language Teaching (CLT) and Task-based language teaching (TBLT), the use of English as a teaching medium, and a focus on student-centredness, the teaching itself is heavily textbook and PowerPoint slides orientated, with teachers acting as 'messengers' (Scollon 1999). The teachers tend to dominate classroom interaction to the point where students' voices are silenced. They make substantial use of L1 as the medium of instruction. A further disparity is shown between teachers' practice and students' expectations. Driven by the nature of their English language needs and engagements in world affairs, students are asking for more opportunities to practise what they have learnt and express the wish that teachers would move away from a traditional teaching pedagogy towards a more student-centred approach. This thesis aims to encourage teachers, teacher educators, policy makers, and material developers to reflect on what is happening in ELT classrooms and to consider what steps need to be taken to improve tertiary level ELT in China

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

On Improving Generalization of CNN-Based Image Classification with Delineation Maps Using the CORF Push-Pull Inhibition Operator

Deployed image classification pipelines are typically dependent on the images captured in real-world environments. This means that images might be affected by different sources of perturbations (e.g. sensor noise in low-light environments). The main challenge arises by the fact that image quality directly impacts the reliability and consistency of classification tasks. This challenge has, hence, attracted wide interest within the computer vision communities. We propose a transformation step that attempts to enhance the generalization ability of CNN models in the presence of unseen noise in the test set. Concretely, the delineation maps of given images are determined using the CORF push-pull inhibition operator. Such an operation transforms an input image into a space that is more robust to noise before being processed by a CNN. We evaluated our approach on the Fashion MNIST data set with an AlexNet model. It turned out that the proposed CORF-augmented pipeline achieved comparable results on noise-free images to those of a conventional AlexNet classification model without CORF delineation maps, but it consistently achieved significantly superior performance on test images perturbed with different levels of Gaussian and uniform noise