Technological convergence: a strategic perspective

The information and communication technologies (ICT) sectors are in a process of technological convergence. Determinant factors in this process are the liberalisation of the telecommunications markets and technological change. Many firms are engaged in a process of mergers and alliances to position themselves in this new framework. Technological and demand uncertainties are very important. Our objective in this paper is to study the economic determinants of the strategies of the firms. With this aim, we review some key technological and demand aspects. We shed some light on the strategic motivations of the firms by establishing a parallel with the evolution of the retailing sector

The efficiency of direct payments versus tax reductions under uncertainty

This paper analyzes the optimal behavior of farmers in the presence of direct payments and uncertainty. In an empirical analysis for Switzerland, it confirms previously obtained theoretical results and determines the magnitude of the theoretical predicted effects. The results show that direct payments increase agricultural production between 3.7% to 4.8%. Alternatively to direct payments, the production effect of tax reductions is evaluated in order to determine its magnitude. The empirical analysis corroborates the theoretical results of the literature and demonstrates that tax reductions are also distorting, but to a substantially lesser degree if losses are not offset. However, tax reductions, independently whether losses are offset or not, lead to higher government spending than pure direct payments

Prices versus exams as strategic instruments for competing universities

In this paper we investigate the optimal choice of prices and/or exams by universities in the presence of credit constraints. We first compare the optimal behavior of a public, welfare maximizing, monopoly and a private, profit maximizing, monopoly. Then we model competition between a public and a private institution and investigate the new role of exams/prices in this environment. We find that, under certain circumstances, the public university may have an interest to raise tuition fees from minimum levels if it cares for global welfare. This will be the case provided that (i) the private institution has higher quality and uses only prices to select applicants, or (ii) the private institution has lower quality and uses also exams to select students. When this is the case, there are efficiency grounds for raising public prices

Robust fault detection using consistency techniques for uncertainty handling

Often practical performance of analytical redundancy for fault detection and diagnosis is decreased by uncertainties prevailing not only in the system model, but also in the measurements. In this paper, the problem of fault detection is stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem can be solved using modal interval analysis and consistency techniques. Consistency techniques are then shown to be particularly efficient to check the consistency of the analytical redundancy relations (ARRs), dealing with uncertain measurements and parameters. Through the work presented in this paper, it can be observed that consistency techniques can be used to increase the performance of a robust fault detection tool, which is based on interval arithmetic. The proposed method is illustrated using a nonlinear dynamic model of a hydraulic system

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

Prediction of postprandial blood glucose under intra-patient variability and uncertainty and its use in the design of insulin dosing strategies for type 1 diabetic patients

In this thesis I propose a novel method to estimate the dose and injection-to-meal time for low-risk intensive insulin therapy. This dosage-aid system uses an optimization algorithm to determine the insulin dose and injection-to-meal time that minimizes the risk of postprandial hyper- and hypoglycaemia in type 1 diabetic patients. To this end, the algorithm applies a methodology that quantifies the risk of experiencing different grades of hypo- or hyperglycaemia in the postprandial state induced by insulin therapy according to an individual patient’s parameters. This methodology is based on modal interval analysis (MIA). Applying MIA, the postprandial glucose level is predicted with consideration of intra-patient variability and other sources of uncertainty. A worst-case approach is then used to calculate the risk index. In this way, a safer prediction of possible hyper- and hypoglycaemic episodes induced by the insulin therapy tested can be calculated in terms of these uncertainties.