A framework for systems analysis for decision support systems

Comprehensive and elaborate systems analysis techniques have been developed in the past of routine and operational information systems. Developing support systems for organizational decision-making requires new tools and methodologies. We present a new framework for data collection and decision analysis which is useful for developing decision support systems. This task analysis methodology encompasses (1) event analysis, (2) participant analysis, and (3) decision content analysis. With a proper coding manual, it provides a framework for collecting relevant and detailed information required for decision support design and implementation. Further research is suggested for application and evaluation of the methodology in real-life DSS environments.     

Model-driven performance prediction of systems of systems

Systems of systems exhibit characteristics that pose difficulty in modelling and predicting their overall performance capabilities, including the presence of operational independence, emergent behaviour, and evolutionary development. When considering systems of systems within the autonomous defence systems context, these aspects become increasingly critical, as constraints on the performance of the final system are typically driven by hard constraints on space, weight and power. System execution modelling languages and tools permit early prediction of the performance of model-driven systems; however, the focus to date has been on understanding the performance of a model rather than determining whether it meets performance requirements, and only subsequently carrying out analysis to reveal the causes of any requirement violations. Moreover, such an analysis is even more difficult when applied to several systems cooperating to achieve a common goal—a system of systems. In this article, we propose an integrated approach to performance prediction of model-driven real-time embedded defence systems and systems of systems. Our architectural prototyping system supports a scenario-driven experimental platform for evaluating model suitability within a set of deployment and real-time performance constraints. We present an overview of our performance prediction system, demonstrating the integration of modelling, execution and performance analysis, and discuss a case study to illustrate our approach.     

Discrete two-time-scale systems

In this paper reduced-order modelling and control analysis of linear, discrete-time systems having dominant and non-dominant modes are presented. Decoupling of modes is achieved using an explicitly invertible linear transformation. A matrix norm condition is derived, the satisfaction of which enables approximate expressions for the block-diagonalizing matrices, eigenvalue distribution and state trajectories to be obtained. Design of stabilizing feedback controllers is developed and it is shown that two gain matrices are needed for separate assignment of dominant and non-dominant eigenvalues. The theoretical analysis is illustrated by control system examples.     

Performance analysis of large systems

A hybrid analytic and experimental approach to the analysis of large systems is described. The approach is iterative under the assumption that a correct analysis will not be made first time. It is primarily aimed at the analysis of the performance effect of proposed changes prior to coding them. The requirement is for a fairly approximate analysis that is easy to make. The approach is illustrated by an experiment on a relational database system but we believe it to be applicable to many kinds of large systems. The different reasons for analysing performance of a system are discussed and then the ways of approaching the analysis, with an outline of our approach. The details of our approach are given, and illustrated by our experiment.     

Logical problems of systems analysis of organization-and-engineering systems and main ways to solve them

Logical problems of systems analysis of organization-and-engineering systems in the modern industry are discussed. The logical foundations of the systems analysis are analyzed. A methodological function of objective structures in a systems analysis of organization-and-engineering systems is found, and a relationship of these structures as results of analysis and synthesis of objectives is established. The main ways to solve logical problems for systems analysis of organization-and-engineering systems that allow solving logical problems are identified. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 140–147, May–June 2006.     

Convergent systems

An equivalent relationship has been established between the problems of convergence or zero-input convergence of nonlinear systems and the problem of zero-input convergence of linear systems. A special feature is that the formulation of the problem and the analysis are done directly on a component-connection model instead of the usual input-output state model. As a consequence, the results obtained can be easily interpreted in terms of given practical systems.     

Linking soft systems methodology with data-focused information systems development

Abstract. Where the soft systems methodology (SSM) is used in the development of organizational information systems a clear division exists between the use of SSM to identify what information systems are required and conventional development activities in which it is decided how those information systems will be supplied. Discussion of how SSM might be more closely linked to conventional information systems development methodologies has been concentrated upon process-focused approaches to information systems development. This has been partly due to a perceived mismatch between the underlying philosophies of SSM and the alternative data-focused development methodologies. This paper argues that this perception may be mistaken; not only do the existing forms of data analysis have a large though unacknowledged subjective component but the SSM concept of appreciation may provide a model of human sense-making that the data-focused approaches currently lack and from which they may benefit. The idea of appreciation also allows that an alternative, interpretative form of data analysis might be used within SSM. It is therefore the conclusion of this paper that some closer integration of SSM with data-focused approaches to information systems development is theoretically feasible and may be practically desirable. A number of possible advantages of such integration are described.     

On hybrid systems and closed-loop MPC systems

The following five classes of hybrid systems were recently proven to be equivalent: linear complementarity, extended linear complementarity, mixed logical dynamical systems, piecewise affine systems and max-min-plus-scaling systems. Some of the equivalences were obtained under additional assumptions, such as boundedness of certain system variables. In this paper, for linear or hybrid plants in closed-loop with a model predictive control (MPC) controller based on a linear model fulfilling linear constraints on input and state variables and utilizing a quadratic cost criterion, we provide a simple and direct proof that the closed-loop system is a subclass of any of the former five classes of hybrid systems. This result is of extreme importance, as it opens up the use of tools developed for the mentioned hybrid model classes, such as (robust) stability and safety analysis tools, to study closed-loop properties of MPC     

Data dependent systems technique: a methodology with an application to human systems

The objective of this paper is to introduce the application of Data Dependent Systems (DDS) methodology to the field of ergonomics. Many current techniques in ergonomics utilize static models, which can have significant limitations. DDS is a stochastic modelling and analysis technique that can be used to capture the dynamics of a system through quantitative analysis of the available data. DDS has been successfully applied to the analysis of manufacturing processes and the surfaces generated by those processes. In this research, DDS was used to analyse time-based hand-skin temperature data for the evaluation of two types of glove liners to be used underneath latex gloves. DDS was able to capture the differences between the two glove liners and the two subjects. The implications of the results and the potential of the DDS methodology are discussed.     

Data dependent systems technique: a methodology with an application to human systems

The objective of this paper is to introduce the application of Data Dependent Systems (DDS) methodology to the field of ergonomics. Many current techniques in ergonomics utilize static models, which can have significant limitations. DDS is a stochastic modelling and analysis technique that can be used to capture the dynamics of a system through quantitative analysis of the available data. DDS has been successfully applied to the analysis of manufacturing processes and the surfaces generated by those processes. In this research, DDS was used to analyse time-based hand-skin temperature data for the evaluation of two types of glove liners to be used underneath latex gloves. DDS was able to capture the differences between the two glove liners and the two subjects. The implications of the results and the potential of the DDS methodology are discussed.     

Human centred systems: An urgent problem for systems designers

Systems, machines and organisation of forms developed in the Engineering and Manufacturing sectors frequently lay the basis for systems design philosophy at a general level. An analysis of technological change in these sectors reveals that the resultant deskilling is not limited to the shop floor and is now spreading to intellectual work. The impact of ‘machine based systems’ on designers is explored in some detail and suggests the need for alternatives which are based on ‘human centred systems’. Some attempts to design sub-systems are described.     

Observers for Takagi-Sugeno fuzzy systems

We focus on the analysis and design of two different sliding mode observers for dynamic Takagi-Sugeno (TS) fuzzy systems. A nonlinear system of this class is composed of multiple affine local linear models that are smoothly interpolated by weighting functions resulting from a fuzzy partitioning of the state space of a given nonlinear system subject to observation. The Takagi-Sugeno fuzzy system is then an accurate approximation of the original nonlinear system. Our approach to the analysis and design of observers for Takagi-Sugeno fuzzy systems is based on extending sliding mode observer schemes to the case of interpolated multiple local affine linear models. Thus, our main contribution is nonlinear observer analysis and design methods that can effectively deal with model/plant mismatches. Furthermore, we consider the difficult case when the weighting functions in the Takagi-Sugeno fuzzy system depend on the estimated state.     

Multiprocessor systems with preemptive priorities

A system with N processors and R job classes subject to a preemptive priority scheduling discipline is considered. Exact analysis is presented for the case R = 2, under Markovian assumptions. That analysis suggests a method for obtaining approximate solutions for arbitrary R. The implementation of the methods is discussed and numerical results for some special cases are given.     

Modeling learning technology systems as business systems

The design of Learning Technology Systems, and the Software Systems that support them, is largely conducted on an intuitive, ad hoc basis, thus resulting in inefficient systems that defectively support the learning process. There is now justifiable, increasing effort in formalizing the engineering of Learning Technology Systems in order to achieve better learning effectiveness as well as development efficiency. This paper presents such an approach for designing Learning Technology Systems and their most popular specialization, the Web-based Learning Systems, by modeling them as business systems, using business-modeling methods. The aim is to provide an in-depth analysis and comprehension of the Learning Technology Systems and Web-based Learning Systems domain, that can be used for improving the systems themselves, as well as for building the supporting software systems. Our work is based upon the Learning Technology Systems Architecture standard of IEEE LTSC, on the empirical results of designing Web-based Learning Systems for university courses and on the practices of the Rational Unified Process and the Unified Modeling Language.     

Piecewise quadratic stability of fuzzy systems

Presents an approach to stability analysis of fuzzy systems. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The approach exploits the gain-scheduling nature of fuzzy systems and results in stability conditions that can be verified via convex optimization over linear matrix inequalities. Examples demonstrate the many improvements over analysis based on a single quadratic Lyapunov function. Special attention is given to the computational aspects of the approach and several methods to improve the computational efficiency are described     

Evaluating scalability in heterogeneous systems

This paper presents a new expression for an isoefficiency function which can be applied both to homogeneous and heterogeneous systems. Using this new function, called H-isoefficiency, it is now possible to analyze the scalability of heterogeneous clusters. In order to show how this new metric can be used, a theoretical a priori analysis of the scalability of a Gauss Elimination algorithm is presented, together with a model evaluation which demonstrates the correlation between the theoretical analysis and the experimental results.     

Knowledge-support systems

The social role of information technology is analysed in order to provide a framework for reasonable requirements for knowledge support systems. The many different scientific and engineering communities targeted on the development of specific knowledge support technologies are noted, and the problems of integrating developments from different communities are highlighted. The architectures of current integrated knowledge support systems are analysed within the social framework and the strengths and weaknesses of current modules are evaluated. Major system developments in recent years are used to exemplify the analysis, and expected directions for future development are outlined. The framework, analyses and examples are used to define a structured requirements specification for future research and development related to knowledge support systems.     

Development of decision support systems based on intellectual technology of artificial immune systems

This paper is dedicated to development of intellectual technology of real-time processing, analysis and prediction of multidimensional data based on biological approach of Artificial Immune Systems.     

微分代数系统结构化分析

对工程和科学问题进行建模和仿真的时候,人们常常很自然地会用微分代数系统对这些问题进行描述.为了检验微分代数系统的初始相容性并进行求解,对微分代数系统进行结构化分析非常重要.本文对经典的微分代数系统结构化分析方法进行了深入的研究;提出了一种新的结构化分析方法,可以高效地对大规模、高阶高指标的微分代数系统进行结构化分析,并快速检验其初始相容性;证明了该方法的终止性,分析了其最坏时间复杂度.该方法的关键在于对最大加权二部子图的使用,而最大加权二部子图则来源于原始系统的加权二部图.实验结果显示,该方法能高效地完成对微分代数系统的结构化分析.     

Static analysis of real-time distributed systems

A static analysis for reasoning about the temporal behaviors of programs in real-time distributed programming languages is proposed. The analysis is based on the action set semantics using the pure maximal parallelism model. It is shown how to specify and verify various timing properties of real-time programs. The approach provides only an approximate timing behavior, because the state information is ignored. However, many interesting properties such as parallel actions, deadlocks, livelocks, terminations, temporal errors, and failures, can be identified. Furthermore, the approach is compositional and thus makes it possible to reason about the timing properties incrementally. The method not only leads to efficient algorithms for the static analysis of CSP programs but also applies to many other languages