Different Levels Of Hierarchy Research Articles

Hierarchy and scales in marine ecohydrodynamics

Recent investigations reveal, in marine ecosystems, an ecohydrodynamic hierarchical organization resulting from the different rates of ecological processes confronted to a multi-scale physical environment. Major marine hydrodynamic processes are briefly analyzed here in an ecohydrodynamic perspective, emphasizing the effects they have on ecosystems at different levels of hierarchy and identifying appropriate “spectral windows” for modelling. A case study application to the Northern Bering Sea's Summer Ecohydrodynamics is given in illustration.

AN ARTIFICIAL INTELLIGENCE APPROACH TO ANALOG CIRCUIT DESIGN

This article deals with a new approach to an intelligent analog circuit design. The iterative closed loop design methodology adopts an expert system approach to provide topological synthesis, the SPICE circuit simulator to evaluate the circuit performance and a new approach of the diagnostic expert system to provide advice on how to improve the design. Unlike previous design methods, this approach introduces formal circuit representation for both numerical and heuristic knowledge of the design system. The predicate logic circuit representation is proposed to introduce a new concept of a formal analog circuit description language. The language syntax and semantics provide precise symbolic description of analog circuits functionality at different levels of hierarchy and connectivities together with transistor sizes of CMOS circuits at the transistor level. Different levels of hierarchy with circuit structures and performance parameters are presented in detail. It is shown how sentence conversion rules of language grammar can be used to derive transistor level circuits from input performance specifications through all intermediate levels of hierarchy. The implementation of the methodology and associated experimental results for CMOS operational amplifier designs are presented.

Mapping Between Economic Information Systems and Economic Structure

The State Economic Information Systems (SEIS) should he a homomorphic mapping to national economic structure. As economic structure is variable, changes of SEIS including its goals, structure functions and behaviours are inevitable. In this paper two types of model of Economic Information Systems (EIS) are proposed: Functional Model (FM) of EIS and Hierarchical Model (HM) of SEIS. In point of FM-EIS consists of three functional systems: while in point of HM. SEIS consists of different subsystems (EISs). which are subordinate to four administrative levels respectively. As for FM, reform of economic structure is reflected as alternation of coupling degree among functional systems. As for HM-the reform is mirrored as expansion and transfer of functions. Vie divide transfer of functions into two types: vertical transfer of functions among subsystems at different levels of hierarchy, and horizontal transfer of functions at the same level.

Taxonomy of co-ordination processes

The hierarchy of information units and interactions in managing of Organizational Systems is rather complicated. Interactions between departments of different levels of hierarchy are named [1]. This paper deals with the coordination as the 'Vertical informational interfaces between the units called elementary management cycles which compose the structure of managing process. The taxonomy of co-ordination processes presented in this paper is based on the decomposition of information processing at managing in so called the Space of Processes [2].

Estimates of Heritability from Transformed Percentage Sib Data with Unequal Subclass Numbers

In estimating heritability by variance componient analysis with unequal subclass numbers and transformed percentage data (transformed by sin-' V/x) very often the difficulty will arise that the binomial components of variance will differ not merely between the different levels of hierarchy, but also between subclasses at one level if the degree of inequality between subclass sizes is large. A method of estimating binomial variance components, which is also suitable for computer programming, is given. The variance component estimates for a double nested classification, in the reverse order of hierarchy, are: