Training domain

Defining the training domain is the prerequisite for assessing the domain extrapolation. Commonly in QSAR modeling, a training domain is viewed as an TV-dimensional space, where N is the number of descriptors in the model. We... 

Figure 6.9 The focused domain representing the training domain of a tree. For an unknown chemical predicted by the tree, its classification is determined by a terminal node (e.g., dark circle) to which it belongs. There are three descriptors used in the path (bold line) from the root to the terminal node and the range of these three descriptors across all chemicals in the training set determines the training domain.

We draw on an internal BAE Systems development project, Integrated Aircrew Training (lAT), as an exemplar. lAT interconnects multiple systems and participants - air and ground assets - into a training SoS. As would be expected we have identified a number of sources of complexity in the analysis of this SoS, chiefly the exponential impact of interactions among increasing numbers of system elements on analysis complexity. However, the training domain provides constraints which may be captured as feature models to structure the analysis. 

Result. Final set of test-techniques applicable when training domain testers and used to develop concrete test cases. 

TRACS International has provided training and consultancy In Exploration and Production related issues for many clients world-wide since 1992. This book has gradually developed from course materials, discussions with clients and material available in the public domain. 

Neural networks have the following advantages (/) once trained, their response to input data is extremely fast (2) they are tolerant of noisy and incomplete input data (J) they do not require knowledge engineering and can be built direcdy from example data (4) they do not require either domain models or models of problem solving and (5) they can store large amounts of information implicitly. 

Tools to apply such a more broad view of a process would pay inherently safer dividends. One tool might include instructions on how to estimate the life cycle cost of proposed alternative solutions. Such a tool is not presently fully developed and available in the public domain. Training to assist in estimating life cycle cost is needed. 

Time-domain plots must be used for all linear and reciprocating motion machinery. They are useful in the overall analysis of machine-trains to study changes in operating conditions. However, time-domain data are difficult to use. Because all the vibration data in this type of plot are added together to represent the total displacement at any given time, it is difficult to directly see the contribution of any particular vibration source. 

Frequency-domain data are obtained by converting time-domain data using a mathematical technique referred to as Fast Fourier Transform (FFT). FFT allows each vibration component of a complex machine-train spectrum to be shown as a discrete frequency peak. The frequency-domain amplitude can be the displacement per unit time related to a particular frequency, which is plotted as the Y-axis against frequency as the X-axis. This is opposed to time-domain spectrums that sum the velocities of all frequencies and plot the sum as the Y-axis against time... 

Time-domain data are presented with amplitude as the vertical axis and elapsed time as the horizontal axis. Time-domain profiles are the sum of all vibration components (i.e., frequencies, impacts, and other transients) that are present in the machine-train and its installed system. Time traces include all frequency components, but the individual components are more difficult to isolate than with frequency-domain data. 

With frequency-domain analysis, the average spectmm for a machine-train signature can be obtained. Recurring peaks can be normalized to present an accurate representation of the machine-train condition. Figure 43.20 illustrates a simplified relationship between the two methods (i.e., time-domain and frequency-domain). 

The real advantage of frequency-domain analysis is the ability to normalize each vibration component so that a complex machine-train spectrum can be divided into discrete components. This ability simplifies isolation and analysis of mechanical degradation within the machine-train. 

In addition, it should be noted that frequency-domain analysis can be used to determine the phase relationships for harmonic vibration components in a typical machine-train spectrum. Frequency-domain normalizes any or all running speeds, where time-domain analysis is limited to true running speed. 

The frequency-domain, or TFT, signature acquired at each measurement point is an actual representation of the individual machine-train component s motion at that point on the machine. Without knowing the specific location and orientation, it is difficult - if not impossible - to correctly identify incipient problems. In simple terms, the TFT signature is a photograph of the mechanical motion of a machine-train in a specific direction and at a specific point and time. 

Repeated twisting of the spindle s tube or the solid shaft used in jackshafts results in a reduction in the flexible drive s stiffness. When this occurs, the drive loses some of its ability to absorb torsional transients. As a result, damage may result to the driven unit. Unfortunately, the limits of single-channel, frequency-domain data acquisition prevents accurate measurement of this failure mode. Most of the abnormal vibration that results from fatigue occurs in the relatively brief time interval associated with startup, when radical speed changes occur, or during shutdown of the machine-train. As a result, this type of data acquisition and analysis cannot adequately capture these... 

Parchmaim et al., 2006 Nieuwe Scheikunde in the Netherlands Driessen Meinema, 2003). For this purpose, we use a synthesis of framewoiks and combine this into a domain-specific curriculum theory (Van Berkel, 2005). VanBerkel s theory is based on the work of Roberts on curriculum emphases, of Schwab on curriculum stractures, of Kuhn on normal science and scientific training and that of Goodlad et al. on cmriculum representations. 

Domain theory. A set of rules and facts to be used in explaining how the training example is an example of the target concept. 

A number of solid compounds have been examined with this time-domain method since the first report of coherent phonons in GaAs [10]. Coherent phonons were created at the metal/semiconductor interface of a GaP photodiode [29] and stacked GaInP/GaAs/GalnP layers [30]. Cesium-deposited [31-33] and potassium-deposited [34] Pt surfaces were extensively studied. Manipulation of vibrational coherence was further demonstrated on Cs/Pt using pump pulse trains [35-37]. Magnetic properties were studied on Gd films [38, 39]. 

The next few steps are very similar to those required in any software project. One of the first stages is the clear definition of the knowledge domain. It must be clear which problems the expert system must solve. It is at this stage not the intention to define how this can be done. Clarity and specificity must be the major guides here. Fuzziness at this stage will, more than in classical software projects, have to be paid for later when different interpretations cause misunderstandings. Equally important is the clear definition of the end user(s). An expert system set up as decision support tool for professionals is totally different from an expert system that can be used as a training support for less professional people. 

As a result, VEGA creates a PDF file that contains all the information about the prediction, including the final assessment of the prediction, the list of the six most similar compounds found in the training and test set of the model, the list of all Applicability Domain indices and a reasoning on SAs with a brief explanation of their meaning. 

The evaluation for aquatic toxicity on daphnids and fish is reported in Tables 12 and 13. Bold values indicate that compounds are out of the model applicability domain (ECOSAR) or that the prediction is not reliable. ECOSAR and ToxSuite are able to predict all the selected compounds while T.E.S.T. fails in prediction for the daphnia toxicity of perfluorinated compounds (PFOS and PFOA). Tables 12 and 13 include also a limited number of experimental results provided by the model training dataset (some data are extracted from USEPA Ecotox database). Predicted results are in agreement for five compounds only (2, 3, 5, 13 and 14) for both endpoints while the predictions for the other compounds are highly variable. 

Obviously this is a little difficult to interpret, although with experience you can train yourself to extract all the frequencies by eye... (only kidding ) The FID is a time domain display but what we really need is a frequency domain display (with peaks rather than cosines). To bring about this magic, we make use of the work of Jean Baptiste Fourier (1768-1830) who was able to relate time-domain to frequency-domain data. These days, there are superfast algorithms to do this and it all happens in the background. It is worth knowing a little about this relationship as we will see later when we discuss some of the tricks that can be used to extract more information from the spectrum. 

Deployment It is in this phase that the business or domain makes its transition to the to-be model, adopting new processes, hardware, and software. It involves things such as software and hardware installation, tools to upgrade or migrate to new releases, documentation, acceptance testing, and user and administrator training. Note that user docu-... 

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