Hierarchical computer system

On the other hand, the apparatus is so cheap and simple to use that it may be feasible to run several independent systems in parallel. The obvious analogy is between a hierarchical computer system linked to a mainframe and a series of dedicated microcomputers. Also the cheapness, speed and simplicity of non-segmented systems make them attractive for a small number of determinations, less than would be considered viable with Autoanalysers. 

Figure 3. Configuration of distributed hierarchical computer system for fermentation pilot plant.

The winch continuously controls and minimizes the traction force and torque exerted on the vehicle by the cable. It is located about 6 m above the upper part of the slab. In the event of emergency it can extract the vehicle from the space between the tanks. Control of the MIR system is achieved by a hierarchical computer system. A microprocessor carries out elementary orders and checks. 

Typical examples of hierarchical database systems arc the file system of personal computers or the organization of parts (e.g., a construction plan). In the case of car parts, the objects (e.g. B = rear suspension, E = right wheel, J = rim, K = screw) are... 

Woodruff and co-workers introduced the expert system PAIRS [67], a program that is able to analyze IR spectra in the same manner as a spectroscopist would. Chalmers and co-workers [68] used an approach for automated interpretation of Fourier Transform Raman spectra of complex polymers. Andreev and Argirov developed the expert system EXPIRS [69] for the interpretation of IR spectra. EXPIRS provides a hierarchical organization of the characteristic groups that are recognized by peak detection in discrete ames. Penchev et al. [70] recently introduced a computer system that performs searches in spectral libraries and systematic analysis of mixture spectra. It is able to classify IR spectra with the aid of linear discriminant analysis, artificial neural networks, and the method of fe-nearest neighbors. 

The hierarchical approach was developed in the early days of computer-aided planning and can be visualized by a pyramid (Fig. 12.1). It was the right solution to the challenges of the restricted capability of computer systems at that time that required a decomposition of problems to reduce their size. 

The concentration of all automation functions within a single computer (Section 7.19.1) may be possible for a very simple plant, but this type of configuration is inefficient for more complex processes for which there could be many thousands of connections between plant and computer. Currently, small industrial processes are controlled by a hierarchical architecture consisting of a central computer (usually a minicomputer), which is used to solve central automation problems, together with a series of peripheral computers (generally microprocessors which are called front-end computers) which control different sections of the plant (Fig. 7.104a). This type of architecture is termed a decentralised computer system. 

Fig. 7.104. (a) Two-level hierarchical computer control system (decentralised computer system), (b) Three-stage hierarchical computer control... 

Johansson, C., Lansner, A. A hierarchical brain-mspired computing system. In International Symposium on Nonlinear Theory and its applications (NOLTA), Bologna, Italy, pp. 599-603... 

The hierarchical multicomputer system described at the Karlsruhe conference was the Argonne-developed PHYLIS system (56, 57). The original PHYLIS (a mnemonic for PHYsics on-Line Information Station) system was designed to handle the data acquisition and analysis, both for the inelastic scattering experiments at the 4.5-MeV Van de Graaff and the multiparameter experiments at the 12-MeV tandem machine, on a real-time basis to allow the experimenters to make use of the results of the analysis to change the course of their experiments. The system s small computer was... 

The memory in the memory hierarchy of a computer system is used to store information, instructions, and data that will be used by the computer system. Memory is often classified as registers, cache memory, main memory, hard disk, floppy disk, and tapes. These are pictured in a hierarchal form in Fig. 10 with locations within each type of memory randomly accessible except for tapes. Tapes are sequentially accessible, and in the long run each disk data unit is accessible in equal time, but at a given time the access time for a particular unit is dependent on the location of the disk components. The term access designates the memory activities that are associated with either a read or a write. Randomly accessible means that a memory location may be read or written in the same amount of time irregardless of the order of accesses of memory locations, and sequentially accessible means that the time required to access a memory location is dependent on location of the immediate prior memory access. 

An earlier implementation of the CASTOR system on a CDC-Cyber computer system, using the CDC-IMF-facihty (formerly EDMS) had proven the practical applicability of the underlying theory as well as the usability of the ancillary systems, e.g., data capture and conversion, semi-automatic addition of by-products, paphical output. The database model of EDMS was CODASYL-based. Our implementation, however, used the hierarchical components, e.g., the member-owner construct, for the sole purpose of data storage optimisation. The main parts used a relational model. The relational model became dominant in an ADABAS implementation, where member-owner sentences were replaced by dynamic field constructs. The present goal of development is a purely relational implementation under a portable relational DBMS. 

Cava, R.A., Luzzardi, P.R.G., Freitas, C.M.D.S. The Bifocal Tree a Technique for the Visualization of Hierarchical Information Structures. In IHC 2002 — 5th Workshop On Human Factors In Computer Systems, Fortaleza (2002)... 

Preliminary investigations prior to the development of the AutoNom computer system had concluded that the hierarchical principle underlying the approach to a chemical name construction (parent, substituent, substituent-on-substituent, etc.) should be followed as faithfully as possible while designing the appropriate data format for the name generation analysis. It was decided to implement the format based on an ordered binary tree concept as fulfilling the majority of both nomenclature and system-performance requirements. The data structure maintained in the memory of the computer during nomenclature-guided analysis of the input compound will be hereafter referred to as the name tree . 

G.N. Lance and W.T. Williams, A general theory of classificatory sorting strategies. 1. Hierarchical systems, Comput. J., 9 (1967) 373-380. 

From a software point of view, it is desirable to have a well-structured hierarchical description for the different biomacromolecules in the simulation system. Such a hierarchy should provide data structures and access functions on the atomic, residue, molecule, and system levels. This allows routines for the evaluation of energy terms to be set up at the level of residue pairs. Experience [14] suggests that this setup is advantageous since it provides a route to easily and intuitively implement the computational algorithms sketched below. 

Willett, P., Wintermann, V., and Bawden, D. (1986) Implementation of non-hierarchic cluster analysis methods in chemical information systems Selection of compounds for biological testing and clustering of substructure search output. J. Chem. Inf. Comput. Sci. 26, 109-118. 

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