RELATIONSHIP BETWEEN WORD AND BIT LEVEL SYSTOLIC ARRAYS AS APPLIED TO MATRIX multiplied by MATRIX MULTIPLICATIONS.

The mapping of matrix multiplied by matrix multiplication onto both word and bit level systolic arrays has been investigated. It has been found that well defined word and bit level data flow constraints must be satisfied within such circuits. An efficient and highly regular bit level array has been generated by exploiting the basic compatibilities in data flow symmetries at each level of the problem. A description of the circuit which emerges is given and some details relating to its practical implementation are discussed.

‘Facing the Fact: Word and Image in Muriel Rukeyser’s “Worlds Alongside”’

This essay explores an example of a little-known, yet highly significant part of Rukeyser’s early oeuvre: the magazine photo-narrative. Profoundly engaged with the documentary expression of the 1930s, Rukeyser utilised the genre’s methods, aesthetics and images to create a hybrid text reporting the realities of the Depression in lyrical, imaginative terms. The result is a conflation of what Rukeyser understood to constitute poetry, and therefore life: the document and the unverifiable fact, presented in an innovative format that is shaped by Rukeyser’s ethical poetics of connection to construct lessons in creative exchange and being in the world.

The last word:Family members' descriptions of end-of-life care in long-term care facilities

A postal survey was used to collect data from family members of deceased residents of six long-term care (LTC) facilities in order to explore end-of-life (EOL) care using the Family Perception of Care Scale. This article reports on the results of thematic analysis of family member comments provided while completing the survey. Family comments fell into two themes: 1) appreciation for care and 2) concerns with care. The appreciation for care theme included the following subthemes: psychosocial support, family care, and spiritual care. The concerns with care theme included the subthemes: physical care, staffing levels, staff knowledge, physician availability, communication, and physical environment. This study identified the need for improvement in EOL care skills among LTC staff and attending physicians. As such, there is a need to implement continuing education to address these issues. © 2006 Centre for Bioethics, IRCM.

Boost your word power: Katherine Rogers and Maggie Bennett describe a tool that can help students prepare their life science assignments

Anatomy and physiology refers to the structure and function of the human body. Students studying this module, known as life science or bioscience, develop knowledge of the structure (anatomy) and function (physiology) of the body that can be applied in clinical practice and support other study courses.

The idea, the machine, and the art: word and image in the 21st century

Taking in recent advances in neuroscience and digital technology, Gander and Garland assess the state of the inter-arts in America and the Western world, exploring and questioning the primacy of affect in an increasingly hypertextual everyday environment. In this analysis they signal a move beyond W. J. T. Mitchell’s coinage of the ‘imagetext’ to an approach that centres the reader-viewer in a recognition, after John Dewey, of ‘art as experience’. New thinking in cognitive and computer sciences about the relationship between the body and the mind challenges any established definitions of ‘embodiment’, ‘materiality’, ‘virtuality’ and even ‘intelligence, they argue, whilst ‘Extended Mind Theory’, they note, marries our cognitive processes with the material forms with which we engage, confirming and complicating Marshall McLuhan’s insight, decades ago, that ‘all media are “extensions of man”’. In this chapter, Gander and Garland open paths and suggest directions into understandings and critical interpretations of new and emerging imagetext worlds and experiences.

Interpretable and Reconfigurable Clustering of Document Datasets by Deriving Word-based Rules

Clusters of text documents output by clustering algorithms are often hard to interpret. We describe motivating real-world scenarios that necessitate reconfigurability and high interpretability of clusters and outline the problem of generating clusterings with interpretable and reconfigurable cluster models. We develop two clustering algorithms toward the outlined goal of building interpretable and reconfigurable cluster models. They generate clusters with associated rules that are composed of conditions on word occurrences or nonoccurrences. The proposed approaches vary in the complexity of the format of the rules; RGC employs disjunctions and conjunctions in rule generation whereas RGC-D rules are simple disjunctions of conditions signifying presence of various words. In both the cases, each cluster is comprised of precisely the set of documents that satisfy the corresponding rule. Rules of the latter kind are easy to interpret, whereas the former leads to more accurate clustering. We show that our approaches outperform the unsupervised decision tree approach for rule-generating clustering and also an approach we provide for generating interpretable models for general clusterings, both by significant margins. We empirically show that the purity and f-measure losses to achieve interpretability can be as little as 3 and 5%, respectively using the algorithms presented herein.

Generating a Word-Emotion Lexicon from #Emotional Tweets

Research in emotion analysis of text suggest that emotion lexicon based features are superior to corpus based n-gram features. However the static nature of the general purpose emotion lexicons make them less suited to social media analysis, where the need to adopt to changes in vocabulary usage and context is crucial. In this paper we propose a set of methods to extract a word-emotion lexicon automatically from an emotion labelled corpus of tweets. Our results confirm that the features derived from these lexicons outperform the standard Bag-of-words features when applied to an emotion classification task. Furthermore, a comparative analysis with both manually crafted lexicons and a state-of-the-art lexicon generated using Point-Wise Mutual Information, show that the lexicons generated from the proposed methods lead to significantly better classi- fication performance.