The Implementation of Process Standard of Teaching English at Smk Negeri 1 Gianyar

The present study only focused on the implementation of process standard in teaching English in terms of planning, teaching process, assessment used in the lesson plan and the problems faced by the teacher in implementing the process standard of teaching English in SMK Negeri 1 Gianyar. The subjects of the study were the students, and the English Teachers in SMK Negeri 1 Gianyar. There were some resources used by the researcher to help him in collecting data such as checklist, observation sheet, and interview guide. The data were described based on the planning, implementation of process standard in teaching and the assessment used in the lesson plan. Based on the findings and discussion, the researcher found some points related to the implementation of process standard in teaching English in SMK Negeri 1 Gianyar, namely: a) The English teachers at SMK Negeri 1 Gianyar still had problems in term of planning process standard in teaching English. It was found that the all subjects did not make the preparation for teaching English by themselves. They made it because of the formal supervision only. b) The English teachers at SMK Negeri 1 Gianyar did not fully apply the process standard in teaching English.c) It was found that the types of assessment used by the subjects in their lesson plan were spoken and written test. The assessment was not considered relevance because It did not cover three domains of learning. They were: cognitive domain, affective domain and psychomotor domain. In cognitive domain the teacher did not ask the students to produce sentences and answering questions based on the topic. In affective domain, the teacher did not ask the students to work in pair to make a dialog. The last in psychomotor domain, they did not ask the students to perform their work

Distributed implementation of standard oracle operators

The standard oracle operator corresponding to a function f is a unitary operator that computes this function coherently, i.e. it maintains superpositions. This operator acts on a bipartite system, where the subsystems are the input and output registers. In distributed quantum computation, these subsystems may be spatially separated, in which case we will be interested in its classical and entangling capacities. For an arbitrary function f, we show that the unidirectional classical and entangling capacities of this operator are log_{2}(n_{f}) bits/ebits, where n_{f} is the number of different values this function can take. An optimal procedure for bidirectional classical communication with a standard oracle operator corresponding to a permutation on Z_{M} is given. The bidirectional classical capacity of such an operator is found to be 2log_{2}(M) bits. The proofs of these capacities are facilitated by an optimal distributed protocol for the implementation of an arbitrary standard oracle operator.Comment: 4.4 pages, Revtex 4. Submitted to Physical Review Letter

Implementation of standard testbeds for numerical relativity

We discuss results that have been obtained from the implementation of the initial round of testbeds for numerical relativity which was proposed in the first paper of the Apples with Apples Alliance. We present benchmark results for various codes which provide templates for analyzing the testbeds and to draw conclusions about various features of the codes. This allows us to sharpen the initial test specifications, design a new test and add theoretical insight.Comment: Corrected versio

Raising the standard of applied dementia care research : addressing the implementation error

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Enabling Massive Deep Neural Networks with the GraphBLAS

Deep Neural Networks (DNNs) have emerged as a core tool for machine learning. The computations performed during DNN training and inference are dominated by operations on the weight matrices describing the DNN. As DNNs incorporate more stages and more nodes per stage, these weight matrices may be required to be sparse because of memory limitations. The GraphBLAS.org math library standard was developed to provide high performance manipulation of sparse weight matrices and input/output vectors. For sufficiently sparse matrices, a sparse matrix library requires significantly less memory than the corresponding dense matrix implementation. This paper provides a brief description of the mathematics underlying the GraphBLAS. In addition, the equations of a typical DNN are rewritten in a form designed to use the GraphBLAS. An implementation of the DNN is given using a preliminary GraphBLAS C library. The performance of the GraphBLAS implementation is measured relative to a standard dense linear algebra library implementation. For various sizes of DNN weight matrices, it is shown that the GraphBLAS sparse implementation outperforms a BLAS dense implementation as the weight matrix becomes sparser.Comment: 10 pages, 7 figures, to appear in the 2017 IEEE High Performance Extreme Computing (HPEC) conferenc