A pilot project of a cancer patient library in Italy: results of a customer-satisfaction survey and its products

AIMS: The purpose of this study is to determine the degree of satisfaction of users of the Cancer Information Point section of the Library for Patients (CIP-LP), active since 1998 at the National Cancer Institute of Aviano, Italy. The CIP-LP is based on a skilled intermediary, adequate informative material and a specific location, within the Scientific Library of the Institute. PATIENTS AND METHODS: A survey was developed to assess service functionality and quality from the users' viewpoint. During a 6-month period, a questionnaire was mailed to 194 patients and relatives who previously used the CIP-LP; 113 (58%) were returned and processed. RESULTS: Of the respondents, 91% were pleased with the CIP-LP and 95% would recommend the service to other people. The information obtained contributed to a clearer understanding of the illness and treatment (45% as first answer) and a better control of the situation (33%). Fifty-one per cent evaluated the information received as 'good', 42%'excellent' and 4%'of sufficient quality'. CONCLUSION: This survey shows the appreciation and usefulness in the users' perception of a specific hospital library for cancer patients and their relatives, providing an information service supplementary to doctor-patient communication.     

A method for the integer-order approximation of fractional-order systems

A procedure for approximating fractional-order systems by means of integer-order state-space models is presented. It is based on the rational approximation of fractional-order operators suggested by Oustaloup. First, a matrix differential equation is obtained from the original fractional-order representation. Then, this equation is realized in a state-space form that has a sparse block-companion structure. The dimension of the resulting integer-order model can be reduced using an efficient algorithm for rational L₂ approximation. Two numerical examples are worked out to show the performance of the suggested technique.     

Experimental validation of a continuous-time MCSI algorithm with bounded adaptive gains

Model reference adaptive control algorithms with minimal controller synthesis have proven to be an effective solution to tame the behaviour of linear systems subject to unknown or time-varying parameters, unmodelled dynamics and disturbances. However, a major drawback of the technique is that the adaptive control gains might exhibit an unbounded behaviour when facing bounded disturbances. Recently, a minimal controller synthesis algorithm with an integral part and either parameter projection or σ-modification strategies was proposed to guarantee boundedness of the adaptive gains. In this article, these controllers are experimentally validated for the first time by using an electro-mechanical system subject to significant rapidly varying disturbances and parametric uncertainty. Experimental results confirm the effectiveness of the modified minimal controller synthesis methods to keep the adaptive control gains bounded while providing, at the same time, tracking performances similar to that of the original algorithm.     

Frequency-domain approach to robust PI control

The paper considers the problem of designing PI controllers for industrial processes approximated by a first-order time-delayed model. The suggested frequency-domain approach is based on a normalized open-loop transfer function and makes use of the loci of constant stability margins and other performance indices in the parameter space. In this way, it is possible to evaluate the effects of uncertainties in the process parameters and, thus, control system robustness. Some examples show how the procedure operates.     

Model reduction for control systems with restricted complexity controllers

The problem of reduced-order modelling is considered in connection with the design of restricted complexity controllers. The suggested reduction method develops in two phases: (i) a simple frequency response of the overall feedback control system is determined according to the design specifications; (ii) a reduced-order transference of the controlled plant is obtained by solving a linear set of equations in such a way that its behaviour approximates that of the original plant at frequencies which are meaningful for the overall transfer function derived in the first step (e.g. resonance and cutoff frequencies). An example shows how the procedure yields a reduced-order model suitable for designing robust controllers whereas other standard methods, based on properties of the plant only, fail.     

Information retrieval and machine learning for probabilistic schema matching

Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distributed IR in federated digital libraries. This paper introduces a probabilistic framework, called sPLMap, for automatically learning schema mapping rules, based on given instances of both schemas. Different techniques, mostly from the IR and machine learning fields, are combined for finding suitable mapping candidates. Our approach gives a probabilistic interpretation of the prediction weights of the candidates, selects the rule set with highest matching probability, and outputs probabilistic rules which are capable to deal with the intrinsic uncertainty of the mapping process. Our approach with different variants has been evaluated on several test sets.