‘Reading Aran knitting: stitches, text andinterpretation’

The densely textured surfaces of Aran knitting seem to invite interpretation. They have been ‘read’ as identity documents, family trees, references to natural and spiritual phenomena, or even maps. This paper traces the search for meaning in Aran knitting, examining how these stitch patterns have been ‘read’ in the contexts of tourism, fine art and fashion. As Jo Turney (2013:55) argues, the idea of knitted textiles as communicative media in non-literate societies ‘consigns the garments to a preindustrial era of more rural and simple times’, situating them in an imagined state of ‘stasis’. Thus the ways in which Aran stitches are ‘read’ sometimes obscure the processes through which they are ‘written’, whether in terms of individual authorship and creativity, or in terms of their manufacture. Regardless of the historical veracity of claims that particular Aran stitch patterns index features of the social, natural or spiritual worlds, analysing the ways they have been ‘read’ in the context of comparable textile traditions, other crafts which have taken on ‘heritage’ souvenir status, and Irish national identity, reveals how Aran knitting has performed broader communicative functions (see Sonja Andrew 2008), which continue to be subverted and elaborated by fine artists, and translated into couture and mass market fashion products.

Teaching Art History to Design Students

Art History is often seen as a mandatory core course in the curricula of design programs but it is rarely tailored to the needs and goals of such programs. Instead, the traditional chronological organization of lecture topics, invariably beginning with the “Venus of Willendorf” (c. 25,000 BC) is presented in order to impart to the students a supposed holistic “big picture.” This essay outlines the re-structuring of a two-semester first-year faculty-wide introductory art history course, entitled “History of Art and Design,” in the Faculty of Fine Arts and Design at Izmir University of Economics, Izmir, Turkey. The course was re-configured from a conventional chronologically-presented (time-oriented) lecture series to a thematically presented (topic-oriented) lecture series more relevant to the students of the faculty – architecture, interior architecture, graphic design, industrial design, and fashion design students.

ALEA: Fine-Grain Energy Profiling with Basic Block Sampling

Energy efficiency is an essential requirement for all contemporary computing systems. We thus need tools to measure the energy consumption of computing systems and to understand how workloads affect it. Significant recent research effort has targeted direct power measurements on production computing systems using on-board sensors or external instruments. These direct methods have in turn guided studies of software techniques to reduce energy consumption via workload allocation and scaling. Unfortunately, direct energy measurements are hampered by the low power sampling frequency of power sensors. The coarse granularity of power sensing limits our understanding of how power is allocated in systems and our ability to optimize energy efficiency via workload allocation.
We present ALEA, a tool to measure power and energy consumption at the granularity of basic blocks, using a probabilistic approach. ALEA provides fine-grained energy profiling via sta- tistical sampling, which overcomes the limitations of power sens- ing instruments. Compared to state-of-the-art energy measurement tools, ALEA provides finer granularity without sacrificing accuracy. ALEA achieves low overhead energy measurements with mean error rates between 1.4% and 3.5% in 14 sequential and paral- lel benchmarks tested on both Intel and ARM platforms. The sampling method caps execution time overhead at approximately 1%. ALEA is thus suitable for online energy monitoring and optimization. Finally, ALEA is a user-space tool with a portable, machine-independent sampling method. We demonstrate two use cases of ALEA, where we reduce the energy consumption of a k-means computational kernel by 37% and an ocean modelling code by 33%, compared to high-performance execution baselines, by varying the power optimization strategy between basic blocks.

Commentary on Fine Arts Copyright Act 1862

Legislation conferring copyright protection on paintings, drawings, and photographs for the life of the author plus a seven year post mortem term. The Act was also innovative in de-coupling the copyright term from the event of publication, in providing artists with a new form of ‘moral rights' protection, and in introducing the concept of "originality" as the standard threshold for copyright protection.
The commentary explores the background to the legislation, and in particular, the international copyright regime, the nature of the art market in eighteenth and early nineteenth centuries, the role of the Society of Artists in lobbying for legislative protection, and the impetus which the International Exhibition provided for securing the same. The commentary also considers how the 1862 Bill, in its earliest incarnation, incorporated elements that would have signalled a radical departure from established copyright norms. In particular, the Bill proposed: that copyright protection should not be contingent upon registration; and that protection should be offered on a universal basis, regardless of an artists' nationality, and regardless of where the work in question was created.

Multi-scale colorectal tumour segmentation using a novel coarse to fine strategy

This paper addresses the problem of colorectal tumour segmentation in complex real world imagery. For efficient segmentation, a multi-scale strategy is developed for extracting the potentially cancerous region of interest (ROI) based on colour histograms while searching for the best texture resolution. To achieve better segmentation accuracy, we apply a novel bag-of-visual-words method based on rotation invariant raw statistical features and random projection based l2-norm sparse representation to classify tumour areas in histopathology images. Experimental results on 20 real world digital slides demonstrate that the proposed algorithm results in better recognition accuracy than several state of the art segmentation techniques.