Quality management systems from the perspective of organization of complex systems

The aim of this model is to analyse quality management systems from the standpoint of the organization of complex systems introduced by Robert Rosen. The concept that an organized system, under certain conditions, can be modelled as a living system introduces unsuspected tools to analyse its behaviour. The model is oriented towards the understanding of the implications of modifications introduced in laboratories working with a quality organization following the ISO/IEC 17025 standard.This standard establishes management and technical requirements concerning the documental organization, control of the management and technical records, personnel, equipments, test or calibration methods, etc. The objective of the quality system implementation is to assure the quality of the product, the special consideration being the customer’s satisfaction with all aspects of the service the laboratory offers.The improper use of the quality system tools has an impact on the laboratory activity. The perception of this fact can be negligible at the moment it happens. The model allows us to realize that this alteration always has a negative impact on the customer and it specially affects the continuous improvement that the laboratory must implement.     

Packing problems and project scheduling models: an integrating perspective

This paper considers two problem classes, namely packing and project scheduling problems that are important to researchers as well as practitioners. The two problem categories are described, and a classification is given for the different kinds of packing problems and project scheduling concepts. While both problem classes are different with respect to their fields of application, similarities of their mathematical structures are examined. It is shown that all packing problems considered here are special cases of models for project scheduling. The aim is to indicate which project scheduling models can be used to capture the different types of packing problems. Finally, some implications for research on optimisation algorithms for these two problem classes are discussed, and the applicability of the results of this work in practice are pointed out.     

A perspective on artificial intelligence: Learning to learn

The classical approach to the acquisition of knowledge in artificial intelligence has been to program the intelligence into the machine in the form of specific rules for the application of the knowledge: expert systems. Unfortunately, the amount of time and resources required to program an expert system with sufficient knowledge for non-trivial problem-solving is prohibitively large. An alternative approach is to allow the machine tolearn the rules based upon trial-and-error interaction with the environment, much as humans do. This will require endowing the machine with a sophisticated set of sensors for the perception of the external world, the ability to generate trial actions based upon this perceived information, and a dynamic evaluation policy to allow it to measure the effectiveness of its trial actions and modify its repertoire accordingly. The principles underlying this paradigm, known ascollective learning systems theory, have already been applied to sophisticated gaming problems, demonstrating robust learning and dynamic adaptivity.The fundamental building block of a collective learning system is thelearning cell, which may be embedded in a massively parallel, hierarchical data communications network. Such a network comprising 100 million learning cells will approach the intelligence capacity of the human cortex. In the not-too-distant future, it may be possible to build a race of robotic slaves to perform a wide variety of tasks in our culture. This goal, while irresistibly attractive, is most certainly fraught with severe social, political, moral, and economic difficulties.This paper was given as an invited talk on the 12th Symposium on Operations Research, University of Passau, September 1987.     

On the variational integrating matrix for hyperbolic systems

We obtain a necessary and sufficient condition for a hyperbolic system to be an Euler-Lagrange system with a first-order Lagrangian up to multiplication by some matrix. If this condition is satisfied and an integral of the system is known to us, then we can construct a family of higher symmetries that depend on an arbitrary function. Also, we consider the systems that satisfy the above criterion and that possess a sequence of the generalized Laplace invariants with respect to one of the characteristics; then we prove that the generalized Laplace invariants with respect to the other characteristic are uniquely defined. __________ Translated from Fundamentalnaya i Prikladnaya Matematika (Fundamental and Applied Mathematics), Vol. 12, No. 7, pp. 251–262, 2006.     

Weak Dirichlet processes with a stochastic control perspective

The motivation of this paper is to prove verification theorems for stochastic optimal control of finite dimensional diffusion processes without control in the diffusion term, in the case where the value function is assumed to be continuous in time and once differentiable in the space variable (C^0,1$C^{0,1}$) instead of once differentiable in time and twice in space (C^1,2$C^{1,2}$), like in the classical results. For this purpose, the replacement tool of the Itô formula will be the Fukushima–Dirichlet decomposition for weak Dirichlet processes. Given a fixed filtration, a weak Dirichlet process is the sum of a local martingale M$M$ plus an adapted process A$A$ which is orthogonal, in the sense of covariation, to any continuous local martingale. The decomposition mentioned states that a C^0,1$C^{0,1}$ function of a weak Dirichlet process with finite quadratic variation is again a weak Dirichlet process. That result is established in this paper and it is applied to the strong solution of a Cauchy problem with final condition.     

A complex adaptive systems perspective of innovation diffusion: an integrated theory and validated virtual laboratory

In this paper we integrate the rich yet fragmented insights from the extensive literature on the diffusion of innovation into an elegant, coherent model. Using complex adaptive systems theory as the overarching framework, we integrate prior literature around three constructs: agents, interactions, and an environment. The integrated model is presented in both natural language and as an agent-based simulation model. A series of validation experiments instill confidence that our agent-based model (and similar others) can be used as a virtual research laboratory. We provide theoretical and methodological directions for future research.     

Multiple stochastic integrals constructed by special expansions of products of the integrating stochastic processes

The paper deals with problems of constructing multiple stochastic integrals in the case when the product of increments of the integrating stochastic process admits an expansion as a finite sum of series with random coefficients. This expansion was obtained for a sufficiently wide class including centered Gaussian processes. In the paper, some necessary and sufficient conditions are obtained for the existence of multiple stochastic integrals defined by an expansion of the product of Wiener processes. It was obtained a recurrent representation for the Wiener stochastic integral as an analog of the Hu–Meyer formula.     

Empirical processes of multidimensional systems with multiple mixing properties

We establish a multivariate empirical process central limit theorem for stationary R^d-valued stochastic processes (X_i)_i≥1 under very weak conditions concerning the dependence structure of the process. As an application, we can prove the empirical process CLT for ergodic torus automorphisms. Our results also apply to Markov chains and dynamical systems having a spectral gap on some Banach space of functions. Our proof uses a multivariate extension of the techniques introduced by Dehling et al. (2009) [9] in the univariate case. As an important technical ingredient, we prove a 2pth moment bound for partial sums in multiple mixing systems.     

Finite horizon semi-Markov decision processes with application to maintenance systems

This paper investigates finite horizon semi-Markov decision processes with denumerable states. The optimality is over the class of all randomized history-dependent policies which include states and also planning horizons, and the cost rate function is assumed to be bounded below. Under suitable conditions, we show that the value function is a minimum nonnegative solution to the optimality equation and there exists an optimal policy. Moreover, we develop an effective algorithm for computing optimal policies, derive some properties of optimal policies, and in addition, illustrate our main results with a maintenance system.     

Target setting,lean systems and viable systems: a systems perspective on control and performance measurement

The paper starts with a critique of the reductionist approach to control and performance measurement that emphasizes the parts of a system in isolation. The critique provides the basis for a shift in focus to a systems perspective that emphasizes the interactions between the parts of a system. It is argued that this shift is important because the behaviour of a system is a product of the interactions of the parts not the behaviour of the parts in isolation. Two systems approaches to control and performance management are compared and critiqued: Beer's viable system model and Seddon's lean systems. The paper concludes with the advancement of a model for control and performance measurement that not only integrates the work of Beer and Seddon but also compensates for the weaknesses in these approaches through the inclusion of a process of boundary critique.     

Autonomous control of complex systems: robotic applications

One of the biggest challenges of any control paradigm is being able to handle large complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Soft computing, a collection of fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be a powerful tool for adding autonomy to many complex systems. For such systems the size soft computing control architecture will be nearly infinite. Examples of complex systems are power networks, national air traffic control system, an integrated manufacturing plant, etc. In this paper a new rule base reduction approach is suggested to manage large inference engines. Notions of rule hierarchy and sensor data fusion are introduced and combined to achieve desirable goals. New paradigms using soft computing approaches are utilized to design autonomous controllers for a number of robotic applications at the ACE Center are also presented briefly.     

Investment evaluation within project management: an information systems perspective

This paper is seeking to make a contribution through exploring project managementfrom the perspective of information systems (IS) investment evaluation.Organizational investments in IS are significant in financial terms and, as aresult, management would appear set to increasingly scrutinize such expenditurethrough tighter forms of decision-making and corporate governance. Inturn, this has increased the motivation of project managers toappropriately evaluate the impact of their IS before,during and after the investments are signed off. Thisperspective is not restricted to any one industry sector, with the authorseeking motivation for a better understanding of investment evaluation within aproject management context. This paper sets out to explain why andhow investment evaluation should be embedded in project managementin order to support an increase in the effectiveness of project management,thereby increasing the prospects of project success. While doing so,the reader will be provided with several touch-points that serve to outline thepurpose and challenges facing those seeking to evaluate their investments. Theauthor starts off with a contextualization of project management and its phasedactivities, such that a clear understanding of the contribution that investmentevaluation plays within robust project management can be demonstrated. Then, theperspective of investment versus consumption is presented, groundedwithin the strategic grid, which classifies information technology-basedprojects as either: strategic, turnaround, factory or support. The author thenpresents evaluation as a life-cycle process, where evaluation is classified intofour distinctive phases, namely ex-ante evaluation, metrics,command and control and ex-post evaluation, in doing so,emphasizing that evaluation needs to be seen as a process that runs through thelife cycle of a project rather than as a hurdle that needs to be cleared toensure financial approval.     

Maslov complex germ method for systems with second-class constraints

We study the semiclassical mechanics of systems with second-class constraints. We assume that the quantum mechanics of such a system is constructed by the Batalin–Fradkin–Tyutin method, where some additional coordinates and momenta are introduced and second-class constraints are converted into firstclass constraints. We also assume that the algebraic quantization method is used to quantize the extended system. To construct the semiclassical approximation, we use the Maslov complex germ theory. We study the semiclassical states of a system with second-class constraints, their scalar product, and the action of semiclassical observables in the first order of the semiclassical expansion. We consider the transformation of semiclassical states in the course of evolution.     

Interactive visualization in multiclass learning: integrating the SASSC algorithm with KLIMT

The paper deals with multiclass learning from the perspective of analytically interpreting the results of the analysis as well as that of navigating into them by using interactive visualization tools. It is showed that by combining the Sequential Automatic Search of Subset of Classifiers (SASSC) algorithm with the interactive visualization of classification trees provided by the Klassification—Interactive Methods for Trees (KLIMT) software it is possible to highlight important information deriving from the knowledge extraction process without neglecting the prediction accuracy of the classification method. Empirical evidence from two benchmark datasets demonstrates the advantages deriving from the joint use of SASSC and KLIMT.