Hidden

Table 1 Blind test results for "Lower wing skin" using network with 2 hidden nodes and training for 2000 iterations...

The computational process of analysis is hidden from the user, and visually the analysis is conducted in terms of M-02-91 or R6 [6] assessment procedure On the basis of data of stress state and defect configuration the necessary assessment parameters (limit load, stress intensity factor variation along the crack-like defect edge) are determined. Special attention is devoted to realization of sensitivity analysis. Effect of variations in calculated stress distribution and defect configuration are estimated by built-in way. 

The architecture of a backpropagation neuronal network is comparatively simple. The network consists of different neurone layers. The layer connected to the network input is called input layer while the layer at the network output is called the output layer. The different layers between input and output are named hidden layers. The number of neurones in the layers is determined by the developer of the network. Networks used for classification have commonly as much input neurones as there are features and as much output neurones as there are classes to be separated. 

Due to the limitation posed by the initial electrical leakage signal and by the chosen angle of incidence of 52 deg. diffracted signals from 8 mm deep machined notch were hidden. Defects with depth exceeding 12 mm could be detected and sized. The same difficulty was observed when the thickness of the sample was less than 30 mm. 

You will need to know addresses (http //www.) of the major Internet search engines. But search engines are still not perfected and the results may contain certain amount of noise, i. e, irrelevant information. Some companies use tricky things to get your attention we found many NDT related words like TOFD hidden as meta keywords in every page of some websites. If a search engine leads you to this site you will find no actual information provided, not even a single visible instance of the word TOFD. 

Another fundamental characteristic ofNDT data is that it is spatial. It is the use of an NDT signal, together with its location, which provides insight into the hidden nature of the test-piece. Any discussion of NDT inspection data assumes the spatial component is included. 

Many of the adsorbents used have rough surfaces they may consist of clusters of very small particles, for example. It appears that the concept of self-similarity or fractal geometry (see Section VII-4C) may be applicable [210,211]. In the case of quenching of emission by a coadsorbed species, Q, some fraction of Q may be hidden from the emitter if Q is a small molecule that can fit into surface regions not accessible to the emitter [211]. 

Computer simulations act as a bridge between microscopic length and time scales and tlie macroscopic world of the laboratory (see figure B3.3.1. We provide a guess at the interactions between molecules, and obtain exact predictions of bulk properties. The predictions are exact in the sense that they can be made as accurate as we like, subject to the limitations imposed by our computer budget. At the same time, the hidden detail behind bulk measurements can be revealed. Examples are the link between the diffiision coefficient and... 

In applying minimal END to processes such as these, one finds that different initial conditions lead to different product channels. In Figure 1, we show a somewhat truncated time lapse picture of a typical trajectory that leads to abstraction. In this rendering, one of the hydrogens of NHaD" " is hidden. As an example of properties whose evolution can be depicted we display interatomic distances and atomic electronic charges. Obviously, one can similarly study the time dependence of various other properties during the reactive encounter. 

J. Gao, K. Kuczera, B. Tldor, and M. Karplus. Hidden thermodynamics of mutant proteins A molecular dynamics analysis. Science, 244 1069-1072, 1989. 

We consider a two state system, state A and state B. A state is defined as a domain in phase space that is (at least) in local equilibrium since thermodynamic variables are assigned to it. We assume that A or B are described by a local canonical ensemble. There are no dark or hidden states and the probability of the system to be in either A or in B is one. A phenomenological rate equation that describes the transitions between A and B is... 

Figure 9-16. ArtiFicial neural network architecture with a two-layer design, compri ing Input units, a so-called hidden layer, and an output layer. The squares Inclosing the ones depict the bias which Is an extra weight (see Ref, [10 for further details),...

A back-propagation network usually consists of input units, one or more hidden layers and one output layer. Figure 9-16 gives an example of the architecture. 

Data mining provides methods foi the exti action of implicit oi hidden information from large data sets and comprises procedures for the generation of reasonable and dependable secondai information. 

The explorative analysis of data sets by visual data mining applications takes place in a three-step process During the first step (overview), the user can obtain an overview of the data and maybe can identify some basic relationships between specific data points. In the second step (filtering), dynamic and interactive navigation, selection, and query tools will be used to reorganize and filter the data set. Each interaction by the user will lead to an immediate update of the data scene and will reveal the hidden patterns and relationships. Finally, the patterns or data points can be analyzed in detail with specific detail tools. 

Visual data mining allows the visualization and detection of hidden relationships in sets of data. 

A most important task in the handling of molecular data is the evaluation of "hidden information in large chemical data sets. One of the differences between data mining techniques and conventional database queries is the generation of new data that are used subsequently to characterize molecular features in a more general way. Generally, it is not possible to hold all the potentially important information in a data set of chemical structures. Thus, the extraction of relevant information and the production of reliable secondary information are important topics. 

Fig. 10.22 Hidden Markov model used for protein sequence analysis, are match states (corresponding in this...

Mian, K Sjolander and D Haussler 1994. Hidden Markov Models in Computational Biology. Applications to Protein Modelling. Journal of Molecular Biology 235 1501-1531). 

Having built a hidden Markov model for a particular family of proteins, it can then b< used to search a database. A score is computed for each sequence in the database anc those sequences that score significantly more than other sequences of a similar length ar( identified. This was demonstrated for two key families of proteins, globins and kinases ii the original paper [Krogh et al. 1994]. For the kinases, 296 sequences with a Z score abov<... 

Eddy S R 1996. Hidden Markov Models. Current Opinion in Structural Biology 6 361-365. 

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