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Redundancies

Redundancy is a term often confused with resilience. In effect, redundancy is a strategy one may choose to implement in pursuit of a resilient system. It can be defined as the Provision of multiple components or mechanisms to achieve the same function such that failure of one or more of the components or mechanisms does not prevent the performance of the function [3]. In other words redundancy represents the inclusion of additional hardware or functionality which might not be critically required during normal operation but is seamlessly available should it be called upon in situations of failure. For example, one might choose to operate a system with not one but two databases hosted in different geographical locations and synchronised in real time. Should one fail the system can be designed to automatically revert to the alternative without any obvious impact on the user. [Pg.104]

Whilst the provision of redundancy has no impact on the likelihood that individual components will fail, it provides a means by which the service can continue in an interrupted manner in the face of component failure. This gives personnel time to address the problem without the added pressure of dealing with an outage. Components which commonly employ redundancy include  [Pg.104]

Redundancy is a technique that aims to provide an excess of resources to maintain proper functioning. In general, redundancy is available in three settings  [Pg.16]

The importance of redundancy is that it enables detection of random failures that occur pimctually. In the context of systematic failures, redundancy will only detect the presence of a defect in the software application (for example, the unit of calcnlation does not know/caimot undertake more additions). Therefore, redundancy is generally enhanced by the rrse of diversity. [Pg.16]

Execution redundancy consists of running the same application twice using the same processing unit (processor, etc.). The results are usually compared by a device external to the processor, with any discord causing a fallback of the computing unit (fail-stop behavior). This technique is often used in programmable logic controllers. [Pg.17]

The first use of an execution redundancy can be used to detect memory failures. To do this, one program is loaded into two different memory areas (two different addressing areas of the memory, two different memory media, etc.). Therefore, memory failure (RAM, ROM (read-only memory), EPROM (erasable programmable ROM), EEPROM (electrically erasable programmable ROM), etc.) can be detected alongside intermittent failures of the processing unit. [Pg.17]

It should be noted that certain failures of shared hardware devices (comparison unit, processing unit) are not detected and thus remain hidden. Indeed, there are two possibilities for masking errors  [Pg.17]

After equipment is selected, the next step in the conceptual design process is the decision to use multiple instruments to serve the same purpose -redundancy. Redundancy is configured to provide continued system operation even though one or more specific instruments may fail - fault tolerance. Some redundant architectures provide fault tolerance against a [Pg.94]

Assessment Criteria FMEDA only Prior Use IEC 61508 Certification [Pg.95]

Assessment or operational nours oasea on manufactured units X X [Pg.95]

Assessment or i-ieia i-aiiure Keturn System - fieid faiiures corrected X X [Pg.95]

One would think that if we put 10 copies of that gene [that lead to a certain protein being produced] in [a cell], we should get 10 times as much protein produced. But, it has been found that often the more copies of the gene you put in, the less protein you get out. [Pg.414]

Because the consequences of control failure are so severe, there is often a built-in redundancy, so that if the primary system fails, there is a secondary system to keep some semblance of balance. This secondary system is often the vestigial remains of a more primitive system present in lower life forms, and does not exert control as precisely as does the primary system. An example of this is cutaneous sweating in paraplegic humans. The human thermoregulatory system is controlled quite well by the hypothalamus in the human midbrain. In response to thermal challenges, signals [Pg.414]

Many cellular metabolic pathways also show redundancy. If, for some reason, a critical metabolic substrate is in short supply, there often are alternative metabolic pathways to allow the cell to survive the shortage. These alternative mechanisms are usually not as efficient, or they may produce unusable metabolic wastes, so these pathways are not normally used by the cell. Anaerobic metabolism of glucose is an example of an alternative metabolic mechanism when sufficient oxygen is not available (see Section 3.9). [Pg.415]

The manipulation of cellular metabolic pathways in bioreactors is the aim of metabolic engineering. Cells are used that are capable of producing useful biochemicals. However, they often don t produce them in economical qnantities. Changing the genetic machinery of the cell or changing the composition of the bioreactor growth medium can enhance by several hundred percent the amounts of useful products. [Pg.415]

however, there is complete damage to a neural system, then the brain must sort out how to compensate for the damaged neurons. It can often do so by adaptive plasticity, rcCTuiting neural networks not usually involved in performance of the lost function. This process takes a longer time in order to learn anew how to perform the task. [Pg.415]


This approach to synthesis is one of making a series of best local decisions. Equipment is added only if it can be justified economically on the basis of the information available, albeit an incomplete picture. This keeps the structure irreducible, and features which are technically or economically redundant are not included. [Pg.8]

Figure 1.7 An initial structure for the manufacture of benzene from toluene and hydrogen incorporating some redundant features. Figure 1.7 An initial structure for the manufacture of benzene from toluene and hydrogen incorporating some redundant features.
The approach to heat exchanger network design discussed so far is based on the creation of an irreducible structure. No redundant features were included. Of course, when the network is optimized, some of the features might be removed by the optimization. The scope for the optimization to remove features results from the assumptions made during the creation of the initial structure. However, no attempt was made to deliberately include redundant features. [Pg.394]

An alternative approach is to create a reducible structure that deliberately includes redundant features and then subject this to optimization. Redundant features are then removed by the optimization. [Pg.394]

In high permeability reservoirs, wells may produce dry oil for a limited time following a shut-in period, during which gravity forces have segregated oil and water near the wellbore. In fields with more production potential than production capacity, wells can be alternately produced and shut in (intermittentproduction) to reduce the field water cut. This may still be an attractive option at reduced rates very late in field life, if redundant facilities can be decommissioned to reduce operating costs. [Pg.362]

The calculation of characteristic values causes a high amount of values which contain redundant informations. Due to this the forth partial step will be to reduce this amount of values using extraction methods. This can be realized with statistical methods like cross correlation analysis. [Pg.16]

Naturally, such a high probability of detection of theoretically 100% never can be realized in practice. The inspector will not recognize all good visible indications at any time because he cannot always be fiilly concentrated on his task, which is called "human factor". This human factor appears in any visual inspection and may be reduced only by a second redundant inspection or extreme signals as a light flash or an acustic signal. [Pg.676]

The coordinates are redundant since they can be detennined from the condition drat the X, Y, Z)... [Pg.162]

In this way the optimization can be cast m temis of the original coordinate set, including the redundancies. Exactly the same transfomiations between Cartesian and internal coordinate quantities hold as for the non-redundant case (see the next section), but with the generalized inverse replacing the regular inverse. [Pg.2344]

The redundant optimization scheme [53] can be applied to natural internal coordinates, which are sometimes redundant for polycyclic and cage compounds. It can also be applied directly to the underlying primitives. [Pg.2344]

Pulay P and FogarasI G 1992 Geometry optimization In redundant Internal coordinates J. Chem. Phys. 96 2856... [Pg.2357]

Peng C, Ayala P Y, Schlegel H B and Frisch M J 1996 Using redundant Internal coordinates to optimize equilibrium geometries and transition states J. Comput. Chem. 17 49... [Pg.2357]

Load balancing can then be achieved in NAMD 2 by moving compute objects and patches between nodes. But what if a compute object and a patch it depends on are on different nodes Compute objects individually communicating with off-node patches would generate a huge amount of redundant communication. Therefore, patches are represented on other nodes by proxy patches, which implement the same interface as home patches for dealing with compute objects and handling dependencies but receive coordinates from and... [Pg.478]

A second notion is that each atom i.s described twice - in a column and in a row. Matrices in which all elements are shown twice are called redundant. A non-redun-dant matrix contains each element only once (e,g., only the top right or bottom left triangle of the matrix, as can be seen later). [Pg.34]

As can be seen in Figure 2-13, the diagonal elements of the matrix are always zero and it is symmetric around the diagonal elements (undirected, unlabeled graph). Thus, it is a redundant matrix and can be reduced to half of its entries (Figure 2-14b. For clarity, all zero entries are omitted in Figures 2-14b-d. [Pg.35]

Figure 2-16. a) The redundant incidence matrix of ethanal can be compressed by b) omitting the zero values and c) omitting the hydrogen atoms, in the non-square matrix, the atoms are listed in columns and the bonds in rows. [Pg.37]

Figure 2-17. a) The redundanl bond malrix of ethanal with ihe zero values omitted, b) It can be compressed by reduction to the top right triangle, c) Omitting the hydrogen atoms provides the simplest non-redundant matrix representation. [Pg.37]

Both tables, the atom and the bond lists, are linked through the atom indices. An alternative coimection table in the form of a redundant CT is shown in Figure 2-21. There, the first two columns give the index of an atom and the corresponding element symbol. The bond list is integrated into a tabular form in which the atoms are defined. Thus, the bond list extends the table behind the first two columns of the atom list. An atom can be bonded to several other atoms the atom with index 1 is connected to the atoms 2, 4, 5, and 6. These can also be written on one line. Then, a given row contains a focused atom in the atom list, followed by the indices of all the atoms to which this atom is bonded. Additionally, the bond orders are inserted directly following the atom in-... [Pg.40]

Figure 2-22. Non-redundant connection table of ethanal. Only non-hydrogen atoms are considered bonds with the lowest indices are counted once (see Figure 2-21). Figure 2-22. Non-redundant connection table of ethanal. Only non-hydrogen atoms are considered bonds with the lowest indices are counted once (see Figure 2-21).
Almost all chemical information systems work with tlicir own special type of connection table. They often use various formats distinguishing between internal and external connection tables. In most cases, the internal connection tables arc redundant, thus allowing maximum flexibility and increasing the speed of data processing. The external connection tables are usually non-redundant in order to save disk space. Although a connection table can be cprcsented in many different ways, the core remains the same the list of atoms and the list of bonds. Thus, the conversion of one connection table format into another is usually a fairly straightforward task. [Pg.42]

Redundant, isomorphic structures have to be eliminated by the computer before it produces a result. The determination of whether structures are isomorphic or not stems from a mathematical operation called permutation the structures are isomorphic if they can be interconverted by permutation (Eq. (6) see Section 2.8.7). The permutation P3 is identical to P2 if a mathematical operation (P ) is applied. This procedure is described in the example using atom 4 of P3 (compare Figure 2-40, third line). In permutation P3 atom 4 takes the place of atom 5 of the reference structure but place 5 in P2. To replace atom 4 in P2 at position 5, both have to be interchanged, which is expressed by writing the number 4 at the position of 5 in P. Applying this to all the other substituents, the result is a new permutation P which is identical to P]. [Pg.58]

Once the quality of the dataset is defined, the next task is to improve it. Again, one has to remove outliers, find out and remove redundant objects (as they deliver no additional information), and finally, select the optimal subset of descriptors. [Pg.205]

Another misleading feature of a dataset, as mentioned above, is redundancy. This means that the dataset contains too many similar objects contributing no... [Pg.206]

One can find more details on the algorithm in Section 4.3.4. This time the learning yielded essentially improved results. It is sufficient to say that if in the case of the primary dataset, only 21 compoimds from 91 were classified correctly, whereas in the optimized dataset (i.e., that with no redundancy) the correctness of classification was increased to 65 out of 91. [Pg.207]

We have already mentioned that real-world data have drawbacks which must be detected and removed. We have also mentioned outliers and redundancy. So far, only intuitive definitions have been given. Now, aimed with information theory, we are going firom the verbal model to an algebraic one. [Pg.212]

Equation (4) provides a value of AICO = 0.00852. As we see, the populations of classes 3 and 8 bear redundancy in information, as their JCOs are quite low here. In contrast, classes 6 and 7 are clearly outliers. Their JCOs are too high in compar-... [Pg.212]


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Active redundancy

Analysis maximum redundancy

Analytical Redundancy Relations

And redundancy

Applicative redundancy

Atomic orbitals redundancy

Biological redundancy

Bond redundant

Chemical signals redundancy

Chemokine receptors redundancy

Choice and redundancy of descriptors

Coding redundancy

Codon redundancy

Conditional active redundancy

Conformation Redundancy

Connection redundant

Control systems, redundant, chemical plant

Control systems, redundant, chemical plant design

Conversion factors between some redundant units and the SI

Cross-redundancy checks

Cryptochromes redundancy, functional

Cyclic redundancy checking

Cytokines redundancy

Damage protection redundancy

Data redundancy

Dataset redundancy

Degree of redundancy

Design redundancy

Dismissal redundancy

Dissimilar redundancy

Drying process redundancy

Employment redundancy

Fault redundancy

Fault tolerance hardware redundancy

Fault tolerance redundancy

Fault tolerance software redundancy

Finding redundant reactions

Finding redundant species

Full active redundancy

Functional redundancy

Functional redundancy principle

GenBank redundancy

Gene redundancy

Genome redundancy

Hardware and functional redundancy

Hardware redundancy

Hardware redundancy to increase coverage of dangerous failures

Hartree-Fock theory redundant parameters

Homogeneous redundancy

Identification of Redundant Reaction Steps Based on Entropy Production

Increase in Weight and Cost due to Redundant Systems

Information redundancy

Integral/primary redundancy

Interleukin redundancy

Logic solver redundancy

Making Anchors Redundant

Molecular symmetry, redundancy from

Mutant redundancy

Neuron redundancy

Non-Redundant database

Observability and Redundancy

Orbital rotations redundant parameters

Partial active redundancy

Peptide redundancy

REDUNDANCY, DIVERSITY AND INDEPENDENCE

Recombination/gene redundancy

Redundance

Redundancy analysis

Redundancy analytical

Redundancy check algorithm

Redundancy condition

Redundancy fail-safe

Redundancy from molecular

Redundancy function

Redundancy in Synchronization

Redundancy index

Redundancy measure

Redundancy observations

Redundancy partial

Redundancy physical

Redundancy removal

Redundancy, eliminating

Redundancy, genetic code

Redundancy, triple

Redundant

Redundant

Redundant Verification

Redundant and backup components

Redundant aperturing

Redundant array of inexpensive disks,

Redundant chemical diversity

Redundant code

Redundant compounds

Redundant condition

Redundant coordinates

Redundant data sets

Redundant equation system

Redundant equations

Redundant features

Redundant genes

Redundant instrumentation

Redundant internal coordinates

Redundant manipulators

Redundant measured variable

Redundant measurement

Redundant operators

Redundant parameters

Redundant points

Redundant pressure sensors

Redundant properties

Redundant reactions

Redundant rotations

Redundant signal

Redundant species

Redundant symmetry coordinates

Redundant systems

Redundant transformations

Redundant units

Redundant variables

Redundant weights

Reliability redundancy

Removing redundant anchors

Safety systems, redundant/backup

Software redundancy

Speech, redundancy

Standby redundancy

Static redundancy

Subject redundancy

Synchronization redundancy

System Redundancy

Temporal redundancy

Time redundancy

Triple Modular Redundancy

Triple modular redundant architecture

Weight and Cost Penalties Associated with Redundant Systems

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