Ontology-based explanation of classifiers

The rise of data mining and machine learning use in many applications has brought new challenges related to classification. Here, we deal with the following challenge: how to interpret and understand the reason behind a classifier's prediction. Indeed, understanding the behaviour of a classifier is widely recognized as a very important task for wide and safe adoption of machine learning and data mining technologies, especially in high-risk domains, and in dealing with bias.We present a preliminary work on a proposal of using the Ontology-Based Data Management paradigm for explaining the behavior of a classifier in terms of the concepts and the relations that are meaningful in the domain that is relevant for the classifier

Rejection Properties of Stochastic-Resonance-Based Detectors of Weak Harmonic Signals

In (V. Galdi et al., Phys. Rev. E57, 6470, 1998) a thorough characterization in terms of receiver operating characteristics (ROCs) of stochastic-resonance (SR) detectors of weak harmonic signals of known frequency in additive gaussian noise was given. It was shown that strobed sign-counting based strategies can be used to achieve a nice trade-off between performance and cost, by comparison with non-coherent correlators. Here we discuss the more realistic case where besides the sought signal (whose frequency is assumed known) further unwanted spectrally nearby signals with comparable amplitude are present. Rejection properties are discussed in terms of suitably defined false-alarm and false-dismissal probabilities for various values of interfering signal(s) strength and spectral separation.Comment: 4 pages, 5 figures. Misprints corrected. PACS numbers added. RevTeX

An exact approach for the bilevel knapsack problem with interdiction constraints and extensions

We consider the bilevel knapsack problem with interdiction constraints, an extension of the classic 0–1 knapsack problem formulated as a Stackelberg game with two agents, a leader and a follower, that choose items from a common set and hold their own private knapsacks. First, the leader selects some items to be interdicted for the follower while satisfying a capacity constraint. Then the follower packs a set of the remaining items according to his knapsack constraint in order to maximize the profits. The goal of the leader is to minimize the follower’s total profit. We derive effective lower bounds for the bilevel knapsack problem and present an exact method that exploits the structure of the induced follower’s problem. The approach strongly outperforms the current state-of-the-art algorithms designed for the problem. We extend the same algorithmic framework to the interval min–max regret knapsack problem after providing a novel bilevel programming reformulation. Also for this problem, the proposed approach outperforms the exact algorithms available in the literature

Evaluation of current trends of climatic actions in europe based on observations and regional reanalysis

Since extreme values of climatic actions are commonly derived assuming the climate being stationary over time, engineering structures and infrastructures are designed considering design actions derived under this assumption. Owing to the increased relevance of the expected climate change effects and the correlated variations of climate actions extremes, ad hoc strategies for future adaption of design loads are needed. Moreover, as current European maps for climatic actions are generally based on observations collected more than 20 years ago, they should be updated. By a suitable elaboration of the projections of future climate changes, the evolution over time of climatic actions can be assessed; this basic and crucial information allows us to facilitate future adaptations of climatic load maps, thus improving the climate resilience of structures and infrastructures. In this paper, current trends of climatic actions in Europe, daily maximum and minimum temperatures, daily precipitation, and ground snow loads, are investigated based on available gridded datasets of observations (E-OBS) and regional reanalysis (Uncertainties in Ensembles of Regional Re-Analyses, UERRA), to assess their suitability to be used in the elaboration of maps for climatic actions. The results indicate that the E-OBS gridded datasets reproduce trends in extreme temperatures and precipitation well in the investigated regions, while reanalysis data, which include snow water equivalent, show biases in the assessment of ground snow load modifications over the years in comparison with measurements. As far as climate change effects are concerned, trends of variation of climatic actions are estimated considering subsequent time windows, 40 years in duration, covering the period 1950–2020. Results, in terms of factors of change, are critically discussed, also in comparison with the elaborations of reliable datasets of real observations, considering a case study covering Germany and Switzerland

Probabilistic assessment of roof snow load and the calibration of shape coefficients in the eurocodes

In modern structural codes, the reference value of the snow load on roofs is commonly given as the product of the characteristic value of the ground snow load at the construction site multiplied by the shape coefficient. The shape coefficient is a conversion factor which depends on the roof geometry, its wind exposure, and its thermal properties. In the Eurocodes, the characteristic roof snow load is either defined as the value corresponding to an annual probability of exceedance of 0.02 or as a nominal value. In this paper, an improved methodology to evaluate the roof snow load characterized by a given probability of exceedance (e.g., p=0.02 in one year) is presented based on appropriate probability density functions for ground snow loads and shape coefficients, duly taking into account the influence of the roof’s geometry and its exposure to wind. In that context, the curves for the design values of the shape coefficients are provided as a function of the coefficient of variation (COVg) of the yearly maxima of the snow load on the ground expected at a given site, considering three relevant wind exposure conditions: sheltered or non-exposed, semisheltered or normal, and windswept or exposed. The design shape coefficients for flat and pitched roofs, obtained considering roof snow load measurements collected in Europe during the European Snow Load Research Project (ESLRP) and in Norway, are finally compared with the roof snow load provisions given in the relevant existing Eurocode EN1991-1-3: 2003 and in the new version being developed (prEN1991-1-3: 2020) for the “second generation” of the Eurocodes

Influence of reinforcing steel corrosion on life cycle reliability assessment of existing R.C. Buildings

Time-dependent reliability assessment is a crucial aspect of the decision process for rehabilitation of existing reinforced concrete structures. Since the assessment strongly depends on degradation of materials with time, the paper focuses on the influence of corrosion in reinforcing steel on time-reliability curves of relevant reinforced concrete (r.c.) structures, built in Italy in the 1960s, belonging to different building categories. To realistically represent the probability distribution functions (pdf s) of the relevant properties of reinforcing steel and concrete commonly adopted in the 1960s, stochastic models for steel yielding and concrete compressive strength have been derived, by means of a suitable cluster analysis, from secondary databases of test results gathered at that time in Italy on concrete and steel rebar specimens. This cluster analysis, based on Gaussian mixture models, provides a powerful tool to "objectively" extract material classes and associated probability density functions from databases of experimental test results. In the study, different degradation conditions and several reinforcing steel and concrete classes are considered, also aiming to scrutinize their influence on the time-dependent reliability curves. Finally, to stress the significance of the study, the time-dependent reliability curves so obtained are critically examined and discussed also in comparison with the target reliability levels currently adopted in the Eurocodes

Exploiting programmable architectures for WiFi/ZigBee inter-technology cooperation

The increasing complexity of wireless standards has shown that protocols cannot be designed once for all possible deployments, especially when unpredictable and mutating interference situations are present due to the coexistence of heterogeneous technologies. As such, flexibility and (re)programmability of wireless devices is crucial in the emerging scenarios of technology proliferation and unpredictable interference conditions. In this paper, we focus on the possibility to improve coexistence performance of WiFi and ZigBee networks by exploiting novel programmable architectures of wireless devices able to support run-time modifications of medium access operations. Differently from software-defined radio (SDR) platforms, in which every function is programmed from scratch, our programmable architectures are based on a clear decoupling between elementary commands (hard-coded into the devices) and programmable protocol logic (injected into the devices) according to which the commands execution is scheduled. Our contribution is two-fold: first, we designed and implemented a cross-technology time division multiple access (TDMA) scheme devised to provide a global synchronization signal and allocate alternating channel intervals to WiFi and ZigBee programmable nodes; second, we used the OMF control framework to define an interference detection and adaptation strategy that in principle could work in independent and autonomous networks. Experimental results prove the benefits of the envisioned solution