Fuzzy Sets and Neural Networks

Abstract

It is possible that a better model for the behavior of a nerve cell may be provided by what might be called a fuzzy neuron, which is a generalization of the McCulloch-Pitts model. The concept of a fuzzy neuron employs some of the concepts and techniques of the theory of fuzzy sets which was introduced by Zadeh [2, 3] and applied to the theory of automaton by Wee and Fu [6], Tanaka et al. [7], Santo [8] and others. In effect, the introduction of fuzziness into the model of a neuron makes it better adapted to the study of the behavior of systems which are imprecisely defined by virtue of their high degree of complexity. Many of the biological systems, economic systems, urban systems and more generally, large-scale systems fall into this category.

In the nearly three decades since its publication, the pioneering work of McCulloch and Pitts [1], has had a profound influence on the development of the theory of neural nets, in addition to stimulating much of the early work in automata theory and regular events.

Although the McCulloch-Pitts model of a neuron has contributed a great deal to the understanding of the behavior of neural-like systems, it fails to reflect the fact that the behavior of even the simplest type of nerve cell exhibits not only randomness but, more importantly, a type of imprecision which is associated with the lack of sharp transition from the occurrence of an event to its non-occurrence.

In this paper, some basic properties of fuzzy neural networks as well as their applications to the synthesis of fuzzy automata are investigated. It is shown that any n-state minimal fuzzy automaton can be realized by a network of m fuzzy neurons, where ┌log₂ n┐ ? m ? 2n. Examples are given to illustrate the procedure. As an example of application, a realization of λ-fuzzy language recognizer using a fuzzy neural network is presented. The techniques described in this paper may be of use in the study of neural networks as well as in formal languages, pattern recognition, and learning.     

Task modelling for cooperative work

Modern work systems are characterized by a high amount of cooperation among working persons. Thus, task modelling for cooperative work is of great significance for an appropriate design of work systems. Due to the special characteristics of cooperative work, several requirements for the modelling technique have to be met. In this paper, first the requirements for a task modelling technique are derived and compared with existing approaches. Then, as no existing technique completely fulfils the important requirement for abstraction in order to model weakly structured activities , a new technique is presented, which is on the one hand essentially based on an existing modelling language for deterministic software intensive systems and on the other hand has been enlarged by additional concepts for being able to model tasks carried out cooperatively by human beings. The results of a case study in which the new technique has been applied are presented and discussed. Finally, an outlook towards future research concerning task modelling for cooperative work is given.     

Quantum ergonomics: shifting the paradigm of the systems agenda

Abstract

A paradigm is an accepted world view. If we do not continually question our paradigm then wider trends and movements will overtake the discipline leaving it ill adapted to future challenges. This Special Issue is an opportunity to keep systems thinking at the forefront of ergonomics theory and practice. Systems thinking prompts us to ask whether ergonomics, as a discipline, has been too timid? Too preoccupied with the resolution of immediate problems with industrial-age methods when, approaching fast, are developments which could render these operating assumptions an irrelevance. Practical case studies are presented to show how abstract systems problems can be tackled head-on to deliver highly innovative and cost-effective insights. The strategic direction of the discipline foregrounds high-quality systems problems. These are something the discipline is well able to respond to provided that the appropriate operating paradigms are selected.

Practitioner Summary: High-quality systems problems are the future of the discipline. How do we convert obtuse sounding systems concepts into practical interventions? In this paper, the essence of systems thinking is distilled and practical case studies used to demonstrate the benefits of this new paradigm.     

THE AXSÄTER INTEGRATED PRODUCTION-INVENTORY SYSTEM INTERPRETED IN TERMS OF THE THEORY OF RELATIVELY CLOSED SYSTEMS

Abstract

In this article we shall consider a model of an integrated production-inventory system recently proposed by Axsäter, This model concerns the behavior of a production system in which a number of products are produced by means of a set of facilities. The objective for us will be to interpret the model in terms of the theory of relatively closed systems (Grubbström, 1972; Grubbström and Lundquist, 1975) and thereby to show that the model may be formulated in this language and that this theory might cast some light upon the dynamic and structural relationships involved in the model. The theory has previously been applied to Walrasian economic systems and to decentralized decision making (Grubbström, 1976; Grubbström and Lundquist, 1975), and recently to hierarchical managerial systems (Lundquist, 1977).     

Interactive Management of Human Factors Knowledge for Human Systems Integration Using Systems Modeling Language

Abstract

The field of Human Factors in Knowledge Management is often seen as a problem of capturing, organizing, and retrieving information to build knowledge. This process is inextricably bound up with human cognition and, as such, the management of knowledge occurs within an intricately structured behavioral, cultural, and social context. This paper emphasizes the importance of interactive human factors in knowledge management and introduces a model-based human systems integration framework based on systems modeling language (SysML).     

A Dss Classification Model for Research in Human Resource Information Systems

Abstract

Any field of study can benefit from a framework into which past and present research can be classified and from which potential research hypotheses can be generated. This article develops a decision support system classification model for research in human resource information systems (HRIS), a model that can then be utilized for evaluating whether an HRIS does provide a competitive advantage for an organization in today's ever-changing, fast-paced, global business environment. As background for this article, the topics of managerial decision making, decision support systems, human resource information systems, and the principle of competitive advantage are reviewed.     

Consequences of nonclassical measurement for the algorithmic description of continuous dynamical systems

Abstract

Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a.continuous dynamical system with countably many quasistable states has at least the computational power of a universal Turing machine. Such an analysis assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.     

Systems featuring chain structures – a generalized Bond Graph modelling

ABSTRACT

The study presents power flow modelling for dynamic systems featuring chain structures. For this purpose, the Bond Graph method is particularly suitable. This tool describes engineering systems in different fields via domain-independent graphical representation using general dynamic modelling for any physical system. Even repetitive constructions called chains can be modelled. This paper aims for power flow based dynamical models of serial type chain structures. Further graphical systematization identifies four basic scalar segments which again correlate with four general vectorial total model structures. Examples and general algorithms, to obtain the scalar segment model and the vectorial overall model, support the proposed modeling. The main vectorial modelling element is identified as a relative coordinate transformation. The approach includes usage for open and closed chains plus rings of ring structures. It aims at universal usage independent of serial chain structure type, application domain or software tool. Moreover, it can be used beneficially in various non-physical fields.     

Modified gradient dynamic approach to the tensor complementarity problem

ABSTRACT

Nonlinear gradient dynamic approach for solving the tensor complementarity problem (TCP) are presented. Theoretical analysis shows that each of the defined dynamical system models ensures the convergence. The computer-simulation results further substantiate that the considered dynamical system can solve the TCP.     

Dynamical properties of partial-discharge patterns

Abstract

In this paper, Partial Discharge pattern as an indicator of the fault state of insulation systems of medium voltage overhead lines with covered conductors are described, analyzed, and their dynamical properties are researched. Application of data obtained in natural environment with huge variety of noise interferences, affected by various weather conditions, location and time of the day lead to questioning whether the PD-activity can be considered as a system with emergent-like behaviour. The complexity of obtained data and several signal types are examined and described in this contribution. As a main result, a complexity of signals is researched using approximate entropy, sample entropy, and correlation dimension. Finally, 0-1 test for chaos is used to show chaos of almost all signals and for one signal randomness is detected using newly applied stress test. In this paper, Partial Discharge pattern as an indicator of the fault state of insulation systems of medium voltage overhead lines with covered conductors are described, analyzed, and their dynamical properties are researched.     

Autopoiesis and systems education: Implications for practice

In this paper, I will discuss the application of Maturana and Varela's theories of autopoiesis, cognition and language to the notions of worldview, worldview change and curriculum design. The context for this discussion is the education of systems concepts, thinking and practice. It has been argued that systemic thinking requires the adoption of particular assumptions into the worldview of the student, independent of the systems concepts under study. This raises the question of how best to structure a curriculum to meet this end. It will be argued that autopoietic theory, when applied to systems education has significant implications for curriculum design.     

Expertise transfer,knowledge elicitation,and delayed recall in a design context

Abstract

This paper describes a new method for knowledge elicitation that may contribute to effective expertise transfer from human experts to knowledge-based systems. The method was applied to knowledge transfer in an aerospace design context. Knowledge was transferred directly from an expert designer to both expert and novice “receivers” of information. Transfer occurred in a natural way, without intervention from a knowledge engineer. To evaluate the process, the information receivers were required to recall the transmitted knowledge after a seven week delay. Results suggest that this method can be effective for expertise transfer and can indicate desirable characteristics for knowledge-based systems which aim to be adaptable to users’ differing levels of competence.     

REVELING IN DECEPTION: A BOOK REVIEW

Abstract

Encrypting a message by bitwise XORing it with a repeated keystream is known to be insecure. In this article we show that given the ciphertext and a Markov chain language model, the Viterbi algorithm can find the plaintext that is best with respect to the model. This approach is shown to more efficiently reconstruct English language plaintext than an earlier method.     

A Two-Stage BNF Specification of Natural Language

Abstract

This paper presents a method of using BNF to specify natural language in such a way that a relatively small grammar of English can express the major grammatical constraints of the language and can be refined without undue proliferation of the rules. The results show that the departures of natural language from a context-free language are of a very restricted kind. The analysis obtained for sentences of the scientific literature is relevant for information processing     

Synergy Between Business Process and Systems Reengineering

Abstract

Business process reengineering (BPR) and systems reengineering (SR) often are implemented separately, in an uncoordinated fashion. Yet practitioners realize that BPR can be informed by SR and that SR can benefit from the application of BPR concepts. This article presents an integrated BPR and SR model that exploits the synergy of integrated BDR and SR. the model has been applied successfully in practice and shows how to tailor this model to meet each organization's situation.     

Acceptance,emotion and behaviour

Abstract

The introduction of standards will hopefully ensure that users can access particular computer resources through a communications network for their own purposes without major problems. The International Standards Organisation (ISO) has developed a seven-layer reference model which is to be used for the purpose of incorporating standards relating to the interconnection of open systems (OSI). It is important that the human factors requirements are considered in relation to this model if the aim of generality of use is to be achieved. This paper considers some of the major human factors requirements and describes an approach to translating them into design standards which can be implemented. The approach starts from a consideration of user activity and develops into a language interface which could reside in layers of the reference model.     

Using trust for detecting deceitful agents in artificial societies

Trust is one of the most important concepts guiding decision-making and contracting in human societies. In artificial societies, this concept has been neglected until recently. The inherent benevolence assumption implemented in many multiagent systems can have hazardous consequences when dealing with deceit in open systems. The aim of this paper is to establish a mechanism that helps agents to cope with environments inhabited by both selfish and cooperative entities. This is achieved by enabling agents to evaluate trust in others. A formalization and an algorithm for trust are presented so that agents can autonomously deal with deception and identify trustworthy parties in open systems. The approach is twofold: agents can observe the behavior of others and thus collect information for establishing an initial trust model. In order to adapt quickly to a new or rapidly changing environment, one enables agents to also make use of observations from other agents. The practical relevance of these ideas is demonstrated by means of a direct mapping from a scenario to electronic commerce.     

A Methodology for Modeling and Optimizing Social Systems

Abstract

A system methodology for modeling and optimizing social systems is presented. It allows constructing dynamical models formulated stochastically, i.e., their results are given by confidence intervals. The models provide optimal intervention ways to reach the stated objectives. Two optimization methods are used: (1) to test strategies and scenarios and (2) to optimize with a genetic algorithm. The application case presented is a small nonformal education Spanish business. First, the model is validated in the 2008–2012 period, and subsequently, the optimal way to obtain a maximum profit in the 2013–2025 period is obtained using the two methods.     

Constrained dynamical systems,robust model reference adaptive control,and unreliable reference signals

ABSTRACT

In this paper, we address the robust control design problem for nonlinear dynamical systems tracking unreliable reference signals. Specifically, we present robust model reference adaptive control laws that guarantee uniform ultimate boundedness of the trajectory tracking error for nonlinear plants that are affected by matched, unmatched, and parametric uncertainties, and are subject to constraints on the state space and the measured output. These control laws guarantee satisfactory results even in case the reference trajectory or the reference output signal do not verify the given constraints and hence, may draw the plant's trajectory or measured output outside their constraint sets. A numerical example involving the attitude control of a spacecraft illustrates the feasibility of the theoretical results presented.     

Chaotic Cipher Using the Duffing Equation

ABSTRACT

We propose a plain files cipher by means of a stream cryptosystem scheme with chaotic addition and a symmetric key. The sequence of numbers used for encryption is generated by a continuous chaotic dynamical system; in particular, we choose the forced Duffing equation since this kind of systems is sensitive to the initial conditions. In a chaotic system, the answer can became periodic during the process of numeric integration. We introduce an heuristic method to break this periodicity.