This article presents an overview of action research conducted in an EFL university context, regarding primarily the relationship between individual possible self-images, socially constructed possible self-images, and language-learning motivation. The study used three cycles of action research over the course of one 15-week university semester, utilizing mixed-methods data collection and analysis. The results provide support for the assertion that initially inquiring with students as to their language possible self-images might assist the teacher to create more motivating lessons through self-enhancement activities. Furthermore, the article provides context-dependent evidence that assisting students to focus their language-learning possible selfimages may positively affect motivation and bring a heightened recognition of self-regulation in language learning.
Three-dimensional (3D) ultrasound is becoming common for non-invasive medical imaging because of its high accuracy, safety, and ease of use. Unlike other modalities, ultrasound transducers require little power, which makes hand-held imaging platforms possible, and several low-resolution 2D devices are commercially available today. However, the extreme computational requirements (and associated power requirements) of 3D ultrasound image formation has, to date, precluded hand-held 3D capable devices.We describe the Sonic Millip3De, a new system architecture and accelerator for 3D ultrasound beamformation-the most computationally intensive aspect of image formation. Our three-layer die-stacked design features a custom beamsum accelerator that employs massive data parallelism and a streaming transform-select-reduce pipeline architecture enabled by our new iterative beamsum delay calculation algorithm. Based on RTL-level design and floorplanning for an industrial 45nm process, we show Sonic Millip3De can enable 3D ultrasound with a fully sampled 128x96 transducer array within a 16W full-system power budget (400x less than a conventional DSP solution) and will meet a 5W safe power target by the 11nm node.
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