Sequential and Parallel Models

2021 ◽  
pp. 45-51
Author(s):  
Dimitris Souravlias ◽  
Konstantinos E. Parsopoulos ◽  
Ilias S. Kotsireas ◽  
Panos M. Pardalos
Keyword(s):  
Parallel Models

scholarly journals The Wada Test: contributions to standardization of the stimulus for language and memory assessment

2004 ◽  
Vol 62 (3a) ◽  
pp. 582-587 ◽  
Author(s):  
Maria Joana Mäder ◽  
Bellkiss Wilma Romano ◽  
Luciano De Paola ◽  
Carlos Eduardo Soares Silvado
Keyword(s):  
Stimulus Type ◽  
Refractory Epilepsy ◽  
Normal Subjects ◽  
Brazilian Population ◽  
Memory Testing ◽  
Wada Test ◽  
Presurgical Evaluation ◽  
Memory Assessment ◽  
Parallel Models

The Wada Test (WT) is part of the presurgical evaluation for refractory epilepsy. The WT is not standardized and the protocols differ in important ways, including stimulus type of material presented for memory testing, timing of presentations and methods of assessment. The aim of this study was to contribute to establish parameters for a WT to Brazilian population investigating the performance of 100 normal subjects, without medication. Two parallel models were used based on Montreal Procedure adapted from Gail Risse's (MEG-MN,EUA) protocol. The proportions of correct responses of normal subjects submitted to two parallel WT models were investigated and the two models were compared. The results showed that the two models are similar but significant differences among the stimulus type were observed. The results suggest that the stimulus type may influence the results of the WT and should be considered when constructing models and comparing different protocols.

Parallel Models of Computation

1995 ◽  
Author(s):  
Raymond Greenlaw ◽  
H. James Hoover ◽  
Walter L. Ruzzo
Keyword(s):  
Parallel Computation ◽  
Qualitative Difference ◽  
Atomic Data ◽  
Machine Model ◽  
Processing Elements ◽  
Fine Grained ◽  
Qualitative Level ◽  
Parallel Models ◽  
Bit Vector ◽  
Data Objects

Before we can discuss the difficulty of solving a problem, we must first choose a suitable machine model in which to describe our computations. A machine model is a parameterized description of a class of machines. Each machine in the class is obtained from the model by giving specific values for the parameters. For example, a Turing machine is specified by giving the number of work tapes, symbol set, and program. The choice of model that we make depends on how we wish to balance such factors as simplicity, generality, historical use, novelty, plausibility of actual implementation, and ease of programming. This flexibility inevitably leads to a proliferation of different models, and parallel computation is no exception to this tendency toward diversity. The menagerie of parallel models includes bit vector machines (Pratt and Stockmeyer [293]), Boolean circuits (Borodin [40]), parallel random access machines, or PRAMs (Fortune and Wyllie [109], Goldschlager [126]), k-PRAMs (Savitch and Stimson [323]), alternating Turing machines (Chandra, Kozen, and Stockmeyer [49]), parallel pointer machines (Cook and Dymond [68], Dymond [98], Dymond and Cook [99, 100]), aggregates ([98, 99, 100]), conglomerates (Goldschlager [126]), and a large variety of machines based on fixed interconnection networks, such as grids, hypercubes, and shuffle-exchange (see Leighton [228]). Such variety makes it difficult to compare competing models. At the qualitative level, models can be distinguished by their processor granularity and their interconnection pattern. One important distinction among models is in the granularity with which they treat parallel operations. A model can be fine-grained and treat bit operations as the basic unit of parallel computation, or it can be coarsegrained and, for example, treat local sub computations on processors as the fundamental unit. In addition the model can be structured, in which case the machine can only manipulate atomic data objects and cannot access their representations (as bits for example). Another important qualitative difference among models is the nature of the communications between processing elements. Some models allow unrestricted communication between processing elements at any time. Other models require a fixed communication pattern. In some models there is no charge for the communication pathway between elements, in others there is.

scholarly journals Spectroscopic studies of OB stars in the Magellanic Clouds with VLT-UVES

2003 ◽  
Vol 212 ◽  
pp. 176-177
Author(s):  
Christopher J. Evans ◽  
Paul A. Crowther ◽  
Alexander W. Fullerton ◽  
D. John Hillier
Keyword(s):  
Mass Loss ◽  
Model Atmosphere ◽  
Spectroscopic Studies ◽  
Magellanic Clouds ◽  
Ob Stars ◽  
Plane Parallel ◽  
Parallel Models ◽  
Cno Abundances ◽  
Loss Rates

We present results from optical and ultraviolet analysis of nine LMC/SMC supergiants. Temperatures, mass-loss rates and CNO abundances are obtained using the non-LTE, line-blanketed model atmosphere code of Hillier & Miller (1998). In general, the derived temperatures are significantly lower than those determined from unblanketed, plane-parallel models.

Commitment to company and union: Parallel models.

1984 ◽  
Vol 69 (3) ◽  
pp. 367-371 ◽  
Author(s):  
Cynthia V. Fukami ◽  
Erik W. Larson
Keyword(s):  
Parallel Models

scholarly journals “Serial” effects in parallel models of reading

2012 ◽  
Vol 64 (4) ◽  
pp. 267-291 ◽  
Author(s):  
Ya-Ning Chang ◽  
Steve Furber ◽  
Stephen Welbourne
Keyword(s):  
Parallel Models ◽  
Models Of Reading
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