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Seminario internazionale di progettazione “Mantova: architettura come modificazione”- Progetto di M. Iori, R. Marone, G. Pulcini
No full textThe Inverse Gamma process for modeling state-dependent deterioration processes
No full textThis paper proposes a non-stationary Inverse Gamma process for modeling state-
dependent
deterioration processes with non linear trend. The proposed processes are mathematically
more tractable than previously proposed state-dependent processes because, unlike the previous models,
the Inverse Gamma process is a time-continuous and state-continuous model and does not require discretization
of time and state. The conditional distribution of the deterioration growth over a generic time
interval, the conditional distribution of the residual life and the residual reliability of the unit, given the
current state, are provided. Maximum likelihood estimates of the parameters which index the proposed
process are also discussed. Finally, the proposed model is applied to the wear process of the liners of
some Diesel engines which was previously analyzed and proved to be a purely state-dependent process.
The comparison of the inferential results obtained under the competing models shows the ability of the
Inverse Gamma process to adequately model the observed state-dependent wear process
A time-discrete extended Gamma process for time-dependent degradation phenomena
No full textThe non-stationary Gamma process is a widely used mathematical model to describe degradation phenomena whose growth rate at time t depends only on the current age of the item and not on the accumulated damage up to t. Nevertheless, the Gamma process is not a proper choice when there is empirical evidence that the variance-to-mean ratio of the process varies with time, because the Gamma process implies a constant variance-to-mean ratio. This paper proposes a generalization of the non-stationary Gamma process, which can be viewed as a time discretization of the extended Gamma process and allows one to describe time-dependent degradation phenomena whose variance varies with time t, not necessarily in proportion to the mean. A way to approximate the exact distribution of the degradation growth over a given time interval is given and a test for assessing whether the assumption of the Gamma process can be rejected or not is discussed. Finally, the proposed model is applied to a real dataset consisting of the sliding wear data of four metal alloy specimens
An empirical mixed-effect regression model for comparative analysis of long-term SOFC degradation tests
No full textHow to go non- monotonic through context-sensitiveness
No full textIn this paper we review some ways of producing non-monotonic logics by considering context-sensitive inferences. These approaches are all based on the notion of control set, a piece of logical machinery recently introduced in [3] and further developed in [7, 4, 14]. A control set informally refers to a set of contexts S which are supposed to prohibit the implementation of specific inferences in a proof system
A competing risks model with degradation phenomena and catastrophic failures
No full textThis paper proposes a competing risks model for the reliability analysis of units subject
both to degradation phenomena and catastrophic failures. The paper is mainly addressed to the
analysis of real data presented in Huang and Askin (2003) which refer to some electronic devices
subject to two independent failure modes. The first one is the light intensity degradation, which is
treated as a degradation phenomenon since the degradation level is observed and measured at
prefixed times. The other one is the solder/Cu pad interface fracture, which is classified as a
catastrophic failure. The main reliability characteristics of the units are estimated, such as the
probability density functions and the cumulative distribution functions of each failure mode in the
presence of both the modes, the hazard function, the unit reliability under the competing risks
model, and the proportion of failures caused by each failure mode during the whole life of the unit
A New Estimation Algorithm for Interval Censored Data from Repairable Systems
Full text linkFor a minimally repaired system, whose failure process is described by a non-homogeneous Poisson process (NHPP), the classical maximum likelihood estimation procedures cannot be used when the system failures are hidden and detected only at inspection epochs. By assuming that the failure process follows a NHPP with power law intensity function, the Expectation-Maximization (EM) algorithm was recently proposed to estimate the model parameters and a procedure to test the presence of trend in the real failure data of some components of identical medical infusion pumps was discussed. However, the EM algorithm suffers in this application from some limitations due to its complexity and the large computational time required for convergence. This paper proposes a new estimation algorithm which is still iterative but, unlike the EM algorithm, is not based on the expectation of the log-likelihood function with respect to the conditional distribution of the unobserved data, but rather on the expectation of the conditioning variables, that is, of the unknown age of the system at the previous failure. This approach allows one to specify a simpler and much faster estimation procedure. A comparison between the proposed and the EM algorithms shows that the former performs as well as the latter, while requiring a drastically reduced computational burden. In addition, the proposed scheme can be applied to other intensity functions, such as the log-linear and the 2-parameter logarithmic functions. As a result, the test hypothesis of no trend in one of the analyzed datasets, which can not be rejected under the power law intensity function, is instead rejected under the alternative hypothesis of a log-linear intensity function
Adding logic to the toolbox of molecular biology
No full textThe aim of this paper is to argue that logic can a play an important
role in the ``toolbox'' of molecular biology. We show how
biochemical pathways, i.e., transitions from a molecular aggregate to
another molecular aggregate, can be viewed as deductive processes. In
particular, our logical approach to molecular biology --- developed in
the form of a natural deduction system --- is centered on the notion
of Curry-Howard isomorphism, a cornerstone in nineteenth-century
proof-theory
A Logic of Non-Monotonic Interactions
Full text linkIn this paper, which is part of the Zsyntax project outlined in Boniolo et al. (2010) [2], we provide a proof-theoretical setting for the study of context-sensitive interactions by means of a non-monotonic conjunction operator. The resulting system is a non-associative variant of MLLpol (the multiplicative polarised fragment of Linear Logic) in which the monotonicity of interactions, depending on the context, is governed by specific devices called control sets. Following the spirit of Linear Logic, the ordinary sequent calculus presentation is also framed into a theory of proof-nets and the set of sequential proofs is shown to be sound and complete with respect to the class of corresponding proof-nets. Some possible biochemical applications are also discussed
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