12,299 research outputs found
Agrammatic but numerate
A central question in cognitive neuroscience concerns the extent to
which language enables other higher cognitive functions. In the
case of mathematics, the resources of the language faculty, both
lexical and syntactic, have been claimed to be important for exact
calculation, and some functional brain imaging studies have shown
that calculation is associated with activation of a network of
left-hemisphere language regions, such as the angular gyrus and
the banks of the intraparietal sulcus. We investigate the integrity
of mathematical calculations in three men with large left-hemisphere
perisylvian lesions. Despite severe grammatical impairment
and some difficulty in processing phonological and orthographic
number words, all basic computational procedures were intact
across patients. All three patients solved mathematical problems
involving recursiveness and structure-dependent operations (for
example, in generating solutions to bracket equations). To our
knowledge, these results demonstrate for the first time the remarkable
independence of mathematical calculations from language
grammar in the mature cognitive system
Effects of problem size, operation, and working-memory span on simple-arithmetic strategies: differences between children and adults?
Adult’s simple-arithmetic strategy use depends on problem-related characteristics, such as problem size and operation, and on individual-difference variables, such as working-memory span. The current study investigates (a) whether the effects of problem size, operation, and working-memory span on children’s simple-arithmetic strategy use are equal to those observed in adults, and (b) how these effects emerge and change across age. To this end, simple-arithmetic performance measures and a working-memory span measure were obtained from 8-year-old, 10-year-old, and 12-year old children. Results showed that the problem-size effect in children results from the same strategic performance differences as in adults (i.e., size-related differences in strategy selection, retrieval efficiency, and procedural efficiency). Operation-related effects in children were equal to those observed in adults as well, with more frequent retrieval use on multiplication, more efficient strategy execution in addition, and more pro-nounced changes in multiplication. Finally, the advantage of having a large working-memory span was also present in children. The differences and similarities across children’s and adult’s strategic performance and the relevance of arithmetic models are discussed
A First Practical Fully Homomorphic Crypto-Processor Design: The Secret Computer is Nearly Here
Following a sequence of hardware designs for a fully homomorphic
crypto-processor - a general purpose processor that natively runs encrypted
machine code on encrypted data in registers and memory, resulting in encrypted
machine states - proposed by the authors in 2014, we discuss a working
prototype of the first of those, a so-called `pseudo-homomorphic' design. This
processor is in principle safe against physical or software-based attacks by
the owner/operator of the processor on user processes running in it. The
processor is intended as a more secure option for those emerging computing
paradigms that require trust to be placed in computations carried out in remote
locations or overseen by untrusted operators.
The prototype has a single-pipeline superscalar architecture that runs
OpenRISC standard machine code in two distinct modes. The processor runs in the
encrypted mode (the unprivileged, `user' mode, with a long pipeline) at 60-70%
of the speed in the unencrypted mode (the privileged, `supervisor' mode, with a
short pipeline), emitting a completed encrypted instruction every 1.67-1.8
cycles on average in real trials.Comment: 6 pages, draf
Unsupervised Visual and Textual Information Fusion in Multimedia Retrieval - A Graph-based Point of View
Multimedia collections are more than ever growing in size and diversity.
Effective multimedia retrieval systems are thus critical to access these
datasets from the end-user perspective and in a scalable way. We are interested
in repositories of image/text multimedia objects and we study multimodal
information fusion techniques in the context of content based multimedia
information retrieval. We focus on graph based methods which have proven to
provide state-of-the-art performances. We particularly examine two of such
methods : cross-media similarities and random walk based scores. From a
theoretical viewpoint, we propose a unifying graph based framework which
encompasses the two aforementioned approaches. Our proposal allows us to
highlight the core features one should consider when using a graph based
technique for the combination of visual and textual information. We compare
cross-media and random walk based results using three different real-world
datasets. From a practical standpoint, our extended empirical analysis allow us
to provide insights and guidelines about the use of graph based methods for
multimodal information fusion in content based multimedia information
retrieval.Comment: An extended version of the paper: Visual and Textual Information
Fusion in Multimedia Retrieval using Semantic Filtering and Graph based
Methods, by J. Ah-Pine, G. Csurka and S. Clinchant, submitted to ACM
Transactions on Information System
Flexible and efficient IR using array databases
textabstractThe Matrix Framework is a recent proposal by IR researchers to flexibly represent all important information retrieval models in a single multi-dimensional array framework. Computational support for exactly this framework is provided by the array database system SRAM (Sparse Relational Array Mapping) that works on top of a DBMS. Information retrieval models can be specified in its comprehension-based array query language, in a way that directly corresponds to the underlying mathematical formulas. SRAM efficiently stores sparse arrays in (compressed) relational tables and translates and optimizes array queries into relational queries. In this work, we describe a number of array query optimization rules and demonstrate their effect on text retrieval in the TREC TeraByte track (TREC-TB) efficiency task, using the Okapi BM25 model as our example. It turns out that these optimization rules enable SRAM to automatically translate the BM25 array queries into the relational equivalent of inverted list processing including compression, score materialization and quantization, such as employed by custom-built IR systems. The use of the high-performance MonetDB/X100 relational backend, that provides transparent database compression, allows the system to achieve very fast response times with good precision and low resource usage
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