Keep It Simple Sheffield – a KISS approach to the Arabic track

Sheffield’s participation in the inaugural Arabic cross language track is described here. Our goal was to examine how well one could achieve retrieval of Arabic text with the minimum of resources and adaptation of existing retrieval systems. To this end the public translators used for query translation and the minimal changes to our retrieval system are described. While the effectiveness of our resulting system is not as high as one might desire, it nevertheless provides reasonable performance particularly in the monolingual track: on average, just under four relevant documents were found in the 10 top ranked documents

ENGLISH LEARNING STRATEGIES FOR TOURISM MANAGEMENT STUDENTS WITH MULTI CULTURAL BACKGROUND AT BANDUNG INSTITUTE OF TOURISM

Learning strategies are used to help students understand any information and solve any language learning problems. A learning strategy is a learner’s approach to learning and using information. The learning strategies include strategies for learning how to paraphrase critical or important or main information, picture information to promote understanding and remembering, ask questions and make predictions about text information and identify unknown words in the text. They also help students study information for developing memories or mnemonics and other devices to aid memorization of facts as well as strategies for learning new vocabulary, write sentences and paragraphs, monitor their work for errors and confidently approach. For example : reading strategies that help students figure out what a word is, comprehend what they are reading , acquire vocabulary and understand the structure of text. All of these strategies are essential for a well – integrated, balanced reading program. In other words, an order or array of strategies in other areas is necessary for students success. In this observation, the theory of learning strategies in the second language literature is adapted from Wenden and Rubin (1987 : 72) that can be classified into three strategies. Firstly, meta cognitive strategies are thinking about learning process, planning for learning, monitoring of comprehension and self evaluation after learners have completed their activities. While cognitive strategies related to individual learning tasks. The last type of strategy is social or affective strategies which concern with influence of social learning and process on learning. The writer found out that students who do not know or use good learning strategies often learn passively and ultimately fail in school. A teacher has an important role in learner’s learning strategy, therefore a teacher should be able to give instruction which focuses on making the students more active learners by teaching them how to learn and use what they have learned to overcome problems and successful . Such problems can occur in second language classes, in which students are learning a new language in an environment where that language is widely used for everyday communicatio

Baja SAE eCVT Mechanical Design

This objective of this project was to design, manufacture, and test the mechanical systems of an electronically-controlled continuously variable transmission (eCVT) for the Cal Poly Baja SAE vehicle

Spartan Daily, January 15, 1943

Volume 31, Issue 62https://scholarworks.sjsu.edu/spartandaily/10723/thumbnail.jp

A method for supporting heterogeneous-group formation through heuristics and visualization

Group formation is a key issue in e-learning environments that make use of collaborative work to enhance student performance. While there are many ways to arrange students to work in cooperative groups, recent works have shown that learning styles offer good opportunities to organize students. Particularly, it seems the case that regarding learning styles, heterogeneous groups tend to perform better than groups formed by students with similar characteristics. This work addresses the issue of supporting the authors’ task of forming effective learner groups to improve student and group performance. This support is provided through a supervised method which, backed by a visualization tool, is able to produce groups with a good level of heterogeneity. Moreover, this method is not time-consuming for teachers.This project has been funded by the Spanish Ministry of Science and Education (TIN2007-64718) and Comunidad Autonoma de Madrid (S2009/TIC-1650)

The Design and Manufacture of an Elevating/Articulating Manual Wheelchair Legrest

For people bound to a wheelchair, the ability to elevate one\u27s legs is as much a comfort concern as it is a health concern. The elevation of one\u27s legs changes the user\u27s sitting position, thereby increasing their comfort level while at the same time increasing circulation, ultimately aiding in the prevention of pressure sores and lower extremity swelling. Unfortunately, the motion of current legrests on manual wheelchairs does not accurately match the motion of the user\u27s lower leg. This mismatch of motion causes the legrest to push up on the leg, shortening it while applying torque to the hip. An elevating/articulating wheelchair legrest that consisted of a planar sixbar linkage coupled with a worm gear set was designed and manufactured to address the shortcomings of standard elevating legrests. The legrest prototype elevates and articulates simultaneously from a single user interface, allowing the user\u27s leg to be straight in the elevated position. The prototype design was evaluated by a potential user, his nurse, and the Director of Rehabilitation Engineering at the Massachusetts Hospital School. The collective response from this evaluation was very favorable. The design was successful in meeting the design specifications. Further modifications are needed before the design is ready for the commercial market

Exploring Enhanced Code-Switched Noising for Pretraining in Neural Machine Translation

Multilingual pretraining approaches in Neural Machine Translation (NMT) have shown that training models to denoise synthetic code-switched data can yield impressive performance gains --- owing to better multilingual semantic representations and transfer learning. However, they generated the synthetic code-switched data using non-contextual, one-to-one word translations obtained from lexicons - which can lead to significant noise in a variety of cases, including the poor handling of polysemes and multi-word expressions, violation of linguistic agreement and inability to scale to agglutinative languages. To overcome these limitations, we propose an approach called Contextual Code-Switching (CCS), where contextual, many-to-many word translations are generated using a `base' NMT model. We conduct experiments on 3 different language families - Romance, Uralic, and Indo-Aryan - and show significant improvements (by up to 5.5 spBLEU points) over the previous lexicon-based SOTA approaches. We also observe that small CCS models can perform comparably or better than massive models like mBART50 and mRASP2, depending on the size of data provided. We empirically analyse several key factors responsible for these - including context, many-to-many substitutions, code-switching language count etc. - and prove that they all contribute to enhanced pretraining of multilingual NMT models