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Supervised

As the safety and quality of industrial components, equipments and constructions is correlated with the inspection sensitivity and this is influenced in radiography by the film system class, a continuous supervision of the film systems on the market seems to be urgently necessary. To support the confidence of the film users in the film properties specified by the film manufacturers such a system for quality assurance for industrial x-ray films is proposed by some manufacturers and BAM. This system will be open to all manufacturers, distributers and users of x-ray films. It will deal with all film systems inclusive those which are not specified by a manufacturer as for instance mixed systems. The system for quality assurance will be based... [Pg.552]

At the beginning of the supervision of films systems first of all the influences of the exposure-and processing installations of the project partners on the determination of the film system parameters shall be found out and subsequently the equipments for measurement shjdl be compared one with another. This round robin test comprises in detail ... [Pg.553]

Checking of NDT devices is mandatory and is strictly regulated. Checking is performed and supervised by National metrological service. The term calibration is rather new in our practice. The works on calibration of NDT equipment are presented in the block-scheme 2. [Pg.964]

The primary developers of NAMD 1 were M. Nelson, W. Humphrey, A. Gursoy, A. Dalke and R. Brunner. The primary developers of NAMD 2 were J. Phillips, A. Shinozaki, R. Brunner, N. Krawetz, M. Bhandarkar and A. Gursoy. NAMD development was performed at the National Institutes of Health Resource for Concurrent Biological Computing under the supervision of principal investigators L.V. Kale, R. Skeel, and K. Schulten. This work was... [Pg.480]

The underlying learning process can follow different concepts. The two major learning strategies are unsupervised learning and supervised learning. [Pg.441]

Table 9-1 summarizes common methods for unsupervised and supervised learning. [Pg.442]

Figure 9-17. Outline of the procedure for supervised learning The output of the netw/ork is compared with the target value or vector, which yields the error The weights of the network are then adapted to reduce this error. Figure 9-17. Outline of the procedure for supervised learning The output of the netw/ork is compared with the target value or vector, which yields the error The weights of the network are then adapted to reduce this error.
A counter-propagation network is a method for supervised learning which can be used for prediction, It has a two-layer architecture where each netiron in the upper layer, the Kohonen layer, has a corresponding netiron in the lower layer, the output layer (sec Figure 9-21). A trained counter-propagation network can be used as a look-up tabic a neuron in one layer is used as a pointer to the other layer. [Pg.459]

Tt provides unsupervised (Kohonen network) and supervised (counter-propagation network) learning techniques with planar and toroidal topology of the network. [Pg.461]

Classification describes the process of assigning an instance or property to one of several given classes. The classes are defined beforehand and this class assignment is used in the learning process, which is therefore supervised. Statistical methods and decision trees (cf. Section 9.3) are also widely used for classification tasks. [Pg.473]

A counter-propagation neural network is a method for supervised learning which can be used for predictions. [Pg.481]

In many cases, structure elucidation with artificial neural networks is limited to backpropagation networks [113] and, is therefore performed in a supervised man-... [Pg.536]

Multiple linear regression is strictly a parametric supervised learning technique. A parametric technique is one which assumes that the variables conform to some distribution (often the Gaussian distribution) the properties of the distribution are assumed in the underlying statistical method. A non-parametric technique does not rely upon the assumption of any particular distribution. A supervised learning method is one which uses information about the dependent variable to derive the model. An unsupervised learning method does not. Thus cluster analysis, principal components analysis and factor analysis are all examples of unsupervised learning techniques. [Pg.719]

Discriminant emalysis is a supervised learning technique which uses classified dependent data. Here, the dependent data (y values) are not on a continuous scale but are divided into distinct classes. There are often just two classes (e.g. active/inactive soluble/not soluble yes/no), but more than two is also possible (e.g. high/medium/low 1/2/3/4). The simplest situation involves two variables and two classes, and the aim is to find a straight line that best separates the data into its classes (Figure 12.37). With more than two variables, the line becomes a hyperplane in the multidimensional variable space. Discriminant analysis is characterised by a discriminant function, which in the particular case of hnear discriminant analysis (the most popular variant) is written as a linear combination of the independent variables ... [Pg.719]

Experiments involving the use of dimethyl sulphate should be carried out by students only under immediate supervision. Not only is the vapour of dimethyl sulphate highly poisonousy but the cold liquid itself is absorbed easily through the skin, with toxic results individual susceptibility to ditnethyl sulphate poisoning varies and may be very high. If the sulphate is splashed on to the hands, wash immediately with plenty of concentrated ammonia solution in order to hydrolyse the methyl sulphate before it can be absorbed through the skin (see p. 528). [Pg.220]

The notes on First Aid have been based on the memorandum Safeguards in the Laboratory compiled by the Science Masters. Association and the Association of Women Science Teachers. This report has, however, been considerably modified and amplified for our purpose, and we are greatly indebted to Dr. F. B. Parsons, M.D., for very kindly supervising our final draft and thus ensuring its medical accuracy. [Pg.593]

Time, Cost, and Equipment Precipitation gravimetric procedures are time-intensive and rarely practical when analyzing a large number of samples. liowever, since much of the time invested in precipitation gravimetry does not require an analyst s immediate supervision, it may be a practical alternative when working with only a few samples. Equipment needs are few (beakers, filtering devices, ovens or burners, and balances), inexpensive, routinely available in most laboratories, and easy to maintain. [Pg.255]

The International Bureau of Weights and Measures, BIPM (Parc de Saint-Cloud, France) is described in Appendix X2 of Ref 4. This bureau operates under the exclusive supervision of the International Committee for Weights and Measures (CIPM). [Pg.568]

Dronabinol is indicated for the treatment of the nausea and vomiting produced by cancer chemotherapy in patients who have failed to respond adequately to other conventional treatments. This agent may be habit forming and can be expected to produce disturbing psychomimetic reactions. It should only be used under close supervision. [Pg.204]

Level devices can be divided into two broad groups those that indicate level and those that provide means to control level. Indication devices report where the level is at any given point in the process. Control devices provide supervision of the process and can be used to initiate other devices to control process levels. [Pg.206]


See other pages where Supervised is mentioned: [Pg.293]    [Pg.345]    [Pg.44]    [Pg.195]    [Pg.464]    [Pg.528]    [Pg.528]    [Pg.441]    [Pg.441]    [Pg.442]    [Pg.442]    [Pg.455]    [Pg.455]    [Pg.462]    [Pg.465]    [Pg.481]    [Pg.481]    [Pg.670]    [Pg.240]    [Pg.56]    [Pg.439]    [Pg.105]    [Pg.519]    [Pg.170]    [Pg.441]    [Pg.445]    [Pg.17]    [Pg.239]   
See also in sourсe #XX -- [ Pg.302 ]

See also in sourсe #XX -- [ Pg.146 , Pg.153 , Pg.165 ]




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Administration and supervision

Administration of Quality Supervision

Administration of Quality Supervision Inspection and Quarantine

Alarms supervision

Algorithms, supervised learning

Artificial neural network supervised classification

Artificial neural networks supervised

Audits/auditing supervisions

Budget planning, control of safety expenditure and supervision

CLASSIFICATION SUPERVISED LEARNING WITH HIGH-DIMENSIONAL BIOLOGICAL DATA

Chemists’ work supervision

Chemometrics supervised techniques

Children, supervision

Classification analysis supervised

Classification, supervised

Coal mining supervision

Competent supervision

Competitive supervised

Conference for the Supervision

Consequences of Inadequate Supervision

Costs supervision

Data supervised

Different Forms of Supervision

Driver Supervision

Electrically Supervised Systems

Employer supervision

Examples of Supervised and Unsupervised Investigations

Expected Supervision

Feature selection supervised learning

Flow injection analysis system supervision

Hazards minimum supervision

Higher supervision services

How many process drivers can a manager supervise

Human factors supervision

Human resources supervising

Incident Investigation supervision

Joint supervisions

Laboratory supervision

Machines data supervised

Management supervision

Medical supervision

Methadone supervised consumption

Monitoring and Supervision

Neural networks supervised learning

Nonclassification, Supervised Learning Problems

Nurses supervision

Pattern recognition supervised techniques

Pattern supervised

Personnel management/supervision

Pipelines supervision

REGULATORY SUPERVISION

Remote supervision

Safety supervision

Segmentation supervised

Site Safety Supervision Plan System

Site safety supervision

Structure Supervised learning

Study of Supervision

Supervise/manage/direct facilities

Supervise/manage/direct facilities management

Supervised Analysis

Supervised Independence

Supervised SIMCA

Supervised Training Issues

Supervised and Unsupervised Variable Selection

Supervised and unsupervised pattern recognition

Supervised areas

Supervised chemometric analysis

Supervised classification problems

Supervised classification techniques

Supervised classification, chemometrics

Supervised classification, unsupervised

Supervised data mining

Supervised discriminant analysis

Supervised elimination

Supervised field experience

Supervised forward selection

Supervised learning

Supervised learning artificial neural networks

Supervised learning classification trees

Supervised learning comparison

Supervised learning enhancement

Supervised learning linear discriminant analysis

Supervised learning methods

Supervised learning partitions

Supervised learning support vector machines

Supervised learning techniques

Supervised learning, definition

Supervised linear learning machine

Supervised methods

Supervised neural network

Supervised pattern recognition

Supervised pattern recognition SIMCA method

Supervised pattern recognition discriminant analysis

Supervised principal-component analysis

Supervised scoring model

Supervised statistical learning

Supervised support vector machines

Supervised variable selection

Supervising

Supervising officer

Supervision

Supervision Assessment

Supervision Type

Supervision active

Supervision athletics

Supervision coalmining

Supervision control system

Supervision controls

Supervision duties

Supervision familiarity

Supervision forms

Supervision improvement

Supervision indirect

Supervision management training

Supervision of Plant Operations

Supervision of War Department Civilian Protection Schools

Supervision of laboratories

Supervision science

Supervision supervisors responsibilities

Supervision surface

Supervision underground

Supervision, training and maintenance

Training supervised

Training supervising

Training supervision

Two Levels of Supervision

Unsupervised and Supervised Segmentation Methods

Women, supervision

Workers supervision

Young persons supervision

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