1,721,077 research outputs found
Proceedings of the 1995 International Workshop on Soft Computing in Remote Sensing Data Analysis
No full textThis volume collect papers presented at the International Workshop on Soft Computing in Remote Sensing Data Analysis, that deal with non conventional techniques based on soft computing methods for the solution of complex problems in Remote Sensing data analysis and recognitio
FUZZY DECISION-MAKING IN THE CLASSIFICATION OF MULTISOURCE REMOTE-SENSING DATA
No full textOur objective was to develop a knowledge-based strategy for the classification, considered a cognitive process, of multisource data including remote sensing images. The main feature of our approach is the use of fuzzy sets as the representation framework. This strategy supports two supervised image classification procedures, one based on a fuzzy statistical classifier and the other on a feed-forward fuzzy trained neural network. Approximate reasoning techniques, based on fuzzy production rules, are applied to model the multifactorial evaluation process in which results from the classification of remote-sensing images are integrated with other data. An example of multisource remote-sensing data classification applied in fire prevention is presented together with numerical results and an experimental verification of the approach
Il Progetto di Territorio Snodo 2 – Abruzzo. Un modello di sviluppo innovativo per l’Abruzzo e l’Italia Mediana
No full textThe project “Junction 2 Territories” (PdT2) is the continuation of the research on “Junction Territories” and condenses all the national and regional experiences of the innovative programs of the Ministry of Infrastructure and Transport. The Abruzzo Region, considered the PdT2 as "a coherent and integrated system of interventions for the development of the regional territory, in the context of Lazio-Abruzzo territorial strategic platform", addressed by identifying the “Central Abruzzo Quadrangle” (L'Aquila, Carsoli, Avezzano, Sulmona) in the framework of the Median Macroregion, as well as the development project of the relative Settlement, Cultural, Natural and Environmental System, also with regard to the more specific theme of the sustainable Social housing
Managerial Hedging and Portfolio Monitoring
No full textIncentive compensation induces correlation between the portfolio of managers and the cash flow of the firms they manage. This correlation exposes managers to risk and hence gives them an incentive to hedge against the poor performance of their firms. We study the agency problem between shareholders and a manager when the manager can hedge his compensation using financial markets and shareholders can monitor the manager's portfolio in order to keep him from hedging, but monitoring is costly. We find that the optimal incentive compensation and governance provisions have the following properties:
(i) the manager's portfolio is monitored only when the firm performs poorly, (ii) the manager’s compensation is more sensitive to firm performance when the cost
of monitoring is higher or when hedging markets are more developed, and (iii)
conditional on the firm’s performance, the manager’s compensation is lower
when his portfolio is monitored, even if no hedging is revealed by monitoring.
Moreover, the model suggests that the optimal level of portfolio monitoring is
higher for managers of firms whose performance can be hedged more easily,
such as larger firms and firms in more developed financial markets
LEARNING OF UNCERTAIN CLASSIFICATION RULES IN BIOMEDICAL IMAGES - THE CASE OF COLPOSCOPIC IMAGES
No full textKnowledge acquisition is always a critical step in the development of a knowledge-based computing system. In the particular area of the interpretation of biomedical images, the assignment of meanings to image patterns is based on obscure and intrinsically vague criteria which are difficult to assess and transform into a suitable machine representation. Automatic learning techniques may be a promising tool in addressing this problem. The paper illustrates a methodological procedure based on fuzzy set theory and using fuzzy logic for the automatic learning of classification rules for biomedical image interpretation systems. It also provides a detailed description of the application of the procedure in the development of a system for the automatic detection of preneoplastic and neoplastic lesions in colposcopic images. Plans to employ the system contemplate its use in educational applications, in diagnostic review for research purposes, and as an online support in clinical practice
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