Dimension Clause Samples

Dimension. Family and context affective-emotional. Family and affective-emotional (present) context: home, partner, family, children… Specific Inherent Needs.

Dimension. Decision-making regarding migration (autonomous/family/other); Migration history.

Dimension. All files have to be dimensioned when the layout is 90% fixed. The dimensions are to be in metric and imperial. Dimensions should be placed in a 2D level.

Dimension reduction in Classification of EEG data by standard deterministic methods (Inria Leading the Task, M10 – M22) / ITT 1.1 Literature review and tests with traditional methods 4. 1.2 Classify the data using the features proposed in WP3 4.1.3 Apply the classifiers on the data acquired in WP2 Task 4.2 Optimisation of the tools of task1 using GA (Inria Leading the Task, M15 – M30) / ITT UNEX 2.1 Build a GA to optimize the parameters of the deterministic methods used in task 1 4.2.2 Perform parallel coding of this GA 4.2.3 Comparison with deterministic approaches Task 4.3 Build/use new classification methods using GP (WP1) (INESC-ID Leading the Task, M22 – M36) / ITT, UNEX, Inria Task Objectives Apply GP classification methods developed in WP1 combined with the features obtained in WP3. 4.3.1 Build a GP dedicated to this problem 4.3.2 Develop a Parallel implementation of this GP 4.3.3 Performance evaluation of each problem D 4.1 Classification of EEG signals with chaos-based features M24 Inria

Dimension. 3 Dimension 4

Dimension. Finally, assuming that all computational-intensive kernels are executed on GPU, it is beneficial to reshape all relevant arrays in this fashion, since the potential overheads of the CPU- executed code are in this case negligible. We conclude by observing that this technique (i) transparently solves any uncoalesced accesses introduced by other compiler op- timizations such as tiling, and (ii) yields speed-ups as high as 28×. 4. Experimental Results‌ Experimental Setup. We study the impact of our optimizations on two heterogenous commodity systems: a desktop5 and an integrated mobile6 solution. We compile (i) the sequential-CPU kernel with the gcc compiler versions 4.6.1 and 4.4.3, respectively, with compiler option -O3, and (ii) a very similar version of the CPU code with NVIDIA’s nvcc compiler for OpenCL version 4.2 and 4.1, respectively, with default compiler options. Reported speed- ups were averaged among 20 independent runs. × × × We estimate the three contracts described in Section 2.1: (i) an European option, named Simple, (ii) a discrete barrier option, named Medium, and (iii) a daily-monitored barrier option, named Complex. These contracts are written in terms of a number of underlyings, u, and dates, d: 1 1, 3 5 and 3 367, respectively. This amounts to very different runtime behavior, since u and d dictate (i) the amount of data processed per iteration and (ii) the weight each basic-block kernel has in the overall computation. In addition, we estimate the contracts with both single precision (SimpleF) and double precision (SimpleD) floating points. From a compute perspective this accentuates the different runtime be- havior, as double are more expensive than float operations (and require twice the space). From a financial perspective we note that the results of our parallel versions are equal to the sequential one, with precision higher than 0.001%. This is a consequence of the Sobol quasi-random generator being modeled as described in Sec- tion 2.2, where the parallel implementation preserves the modulo associativity semantics exhibited by the sequential version. Figures 9, 10 and 11 show the speed-up measurements for the described contracts under different optimization conditions. Read- ings for the gaming system are reported as vertical labels over plain area bars, while readings for the mobile solution are reported as horizontal, white labels over crossed regions. All histograms present error bars indicating the standard deviation of the measur...

Dimension. It allows valid combinations of dimensions. • Formula. It supports complex expressions based on XPath, which can be applied to instance documents to validate your information.

Dimension. The supply teacher will be expected to work a normal teaching day (unless specific agreement is in place). The supply teacher will be required to cover class teacher supervision duties where appropriate. Example day; 0800 – arrive and prepare for the day 0830 – 1030 – Teaching 1030 – 1045 – Break 1045 – 1200 – Teaching 1200 – 1300 – Lunch 1300 – 1500 – Teaching 1500 – 1530 – final marking, notes for class teacher etc Line management of the supply teacher will be the Head of Primary. Direct advice and planning will be provided by the class teacher or other members of Primary staff.

Dimension. 4.1. Subject to the limits of functionalities coverage and number of Users, as established in the Subscription Form, the CLIENT may designate the CLIENT's collaborators who may access and use the Service - provided that, such collaborators are integrated in the CLIENT's internal organization and operation - for that purpose, requesting the access credentials for those who access and use the Software ("Users"). 4.2. The CLIENT understands and agrees that the ADMIN activity of its Users is carried out at its own risk and that it is solely responsible for such activities. 4.3. Unless otherwise stated in the Subscription Form (e.g. in case the CLIENT is benefiting from a special volume discount or similar) the CLIENT may increase or reduce the Dimension upon written notice to C-MORE at least 30 (thirty) days in advance, provided that this does not imply a negative variation of more than 20% in cases where the CLIENT has benefited from a volume discount, with which, the cancellation of this Subscription and corresponding Subscription Form will occur and a new negotiation for a new Subscription agreement will take place.