Vertical Alignment

education system. However, all of these parts share the common goal of educating students so that they become successful citizens. Hence, education researchers have begun discussing whether the overall education system can be strengthened by aligning these different parts. Vertical alignment is the alignment of different parts of an entire education system.

©2013 Texas Education Agency. All Rights Reserved 2013 Introduction to the Revised Mathematics TEKS: Vertical Alignment Chart Kindergarten – Grade 3 11 Applying Strategies for Estimation (4) Number and operations. The student applies mathematical process standards to develop and use strategies and methods for whole number computations in order to solve problems with efficiency and accuracy. The student is expected to: (B) round to the nearest 10 or 100 or use compatible numbers to estimate

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Current Si microwire-array solar cell designs use a series of cleanroom processes, such as photolithography and metal evaporation, to obtain and retain the preferred, predominantly vertical, orientation of the microwires. For many materials, epitax- ial growth of vertically oriented microwires on a substrate, and removal of the wires from the substrate while retaining the vertical alignment of the microwire array, is not possible or economical. Colloidal methods have been used to synthesize high-aspect ratio nano- and microwires composed of metal oxide, [9] metal chalcogenide, [27] group III-V [28] and elemental semiconductor materials. [10] These processes pro- duce a randomly oriented solution of particles, but the scalability of such processes could be leveraged if a self- or directed-assembly process could be developed that would align the randomly oriented suspension of microwires into the desired verti- cally oriented microwire array.

The concept of a "vertical city," as sketched out in a new book by architects Kenneth King and Kellogg Wong, is something more than a hyper-dense Gotham, though. Yes, there are a lot of towering buildings but also parks, schools, hospitals and restaurants at upper levels, as well. Essentially, it's a vision of a complete ecosystem in the sky—a place you never have to leave if you don't want to.

used to compute scores of topologically aligning pairs of nodes from different networks. Also, it includes BLAST scores (Altschul et al., 1990) for sequence similarity between nodes (proteins) into the node alignment by having a user-defined weight λ that controls for the relative contribution of topological similarity, whereas 1 − λ controls for the contribution of sequence similarity. IsoRank constructs the node alignment based on these scores using a greedy strategy. Later, IsoRank was extended to perform multiple local and global alignments between networks (Singh et al., 2008; Liao et al., 2009). Global network alignment algorithms based purely on network topology, called GRAAL (Kuchaiev et al., 2010) and H-GRAAL (Milenkovic et al., 2010), have also been designed. They can align networks of any type, not only biological ones, since they do not rely on sequence similarity information between nodes. Instead, both algorithms heavily rely on “graphlet degrees,” which give a highly constraining quantification of the topological similarity between nodes (Milenkovic and Prˇzulj, 2008). GRAAL is a seed-and-extend approach, while H-GRAAL is based on the Hungarian algorithm (Kuhn, 1955) for solving the assignment problem.

Automatic word alignment is a vital component of nearly all current statistical translation pipelines. Al- though state-of-the-art translation models use rules that operate on units bigger than words (like phrases or tree fragments), they nearly always use word alignments to drive extraction of those translation rules. The dominant approach to word alignment has been the IBM models (Brown et al., 1993) together with the HMM model (Vogel et al., 1996). These models are unsupervised, making them applicable to any language pair for which parallel text is avail- able. Moreover, they are widely disseminated in the open-source GIZA++ toolkit (Och and Ney, 2004). These properties make them the default choice for most statistical MT systems.

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UPD1 tags: locked at any given moment for the past, can be unlocked for the future → to be used for prompt reconstruction (note: alignment always “lagging behind”, by construction) UPD3 tags: similar, with some fraction of the past unlock-able as well → to be used for bulk processing after 24h

If a vehicle features rear wheel toe adjustment, we can achieve optimum wheel alignment using the total four- wheel alignment, which includes adjust- ment of all four wheels, allowing toe ad- justment to bring the thrust angle to ideal zero, or as close to zero as possible. If the thrust angle is off zero, this can contribute to vehicle dog-tracking (crooked body relative to direction of travel), increased tire wear and unequal left/right turning. Total four-wheel alignment allows you to adjust and hopefully correct rear axle thrust angle,

IT executives for many years. Although the issue has been recognized as an ongoing concern within organizations for decades, very little has been done to foster the alignment. Alignment entails more than the executive level communication of business strategy to IT; IT-Business Alignment requires action from both IT and the business enterprise to ensure IT delivers services that directly contribute to the delivery of business outcomes.

One of the critical stages in a display production line is the image alignment of displays that includes the precise adjustment of the geometric parameters and the color of the image. The mutual inuences of the parameters of the display's image necessitate a complex and interactive alignment process. In this paper, the eect of the mutual inuences of geometric parameters on the alignment process of a display's image are shown, a suitable model for the geometric characteristics of a display's image are suggested and, then, the unknown parameters of the proposed model are estimated by the RLS estimator. Using an o-line estimator, an initial measure of the values of the unknown parameters of the display model is obtained. To modify the model parameters of the consecutive video displays on the production line, an on-line estimator is applied. Variations of the parameters of the display model on a production line are traced using on-line estimation. This model estimation is used to implement an adaptive alignment algorithm. Both the adaptive and the proportional alignment processes have been experimentally implemented under similar working conditions. Experimental results show that the use of the adaptive alignment process considerably increases the speed and reliability of convergence of geometric parameters to their desired values. An IA-32, 3.4 GHz Pentium P4 processor has been used in this research. Considering the rapid developments in UDSM technology and the IA-64 architecture, the application of the proposed adaptive alignment algorithm in an auto-alignment system has the potential for real-time implementation in the near future.

other sentence alignment program. Sentence alignment has to be stored in XCES Align format according to the input requirements of the clue aligner (see the example in figure 3). Secondly, we need to create alignment clue databases that will be used for the automatic word alignment. The easiest way to do that is to apply the clue aligner itself which will create several clue databases from the corpus that can directly be used by ICA. Existing clue databases (for instance from previous runs) can also be used. How- ever, be aware that they have to be appropriate for the lan- guage pair and corpus under consideration. Finally, all in- formation about the corpus files and alignment clues have to be set in a configuration file that is used by ICA. All steps above can be taken by a simple call to a pre-defined Make- file that will perform all tasks and setups in one go using Uplug and its alignment tools.

Neither do the other episodes illustrate “simultaneous and concurrent” events flowing through the four alignment factors. Episode 2, for example, from 1993 to 1995 was initiated when FPI diversified its product line from grain bin manufacture to livestock feeding and equipment manufacture by acquisition of manufacturing companies in those industries (SI-2). As a result, FPI established additional divisions for its poultry and livestock product lines (OS-2). However, there were no substantive changes in IS structure and processes; that is, the company felt that it could manage its new product lines with existing systems and software. Hence just two events were linked in this episode.

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