Managing the uncertainty of conformity assessment in environmental testing by machine learning

D’Emilia, Giulio; Gasbarro, David Di; Gaspari, Antonella; Natale, Emanuela

doi:10.1016/j.measurement.2017.12.034

Cited by 12 publications

(3 citation statements)

References 18 publications

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“…In a previous application [11], the authors dealt with the aforementioned issues related to the reconstruction of the maps of a building, and assessed the uncertainty of determination of them, with reference to an Italian baroque church, characterized by a complex structure, where hundreds of people may be present at once. The evaluation of the measurement uncertainty is an essential step [12,13], especially when it comes to very critical applications regarding safety and public health aspects.…”

Section: Introductionmentioning

confidence: 99%

Metrological issues in the use of mobile mapping systems for planning emergency response

Chiominto,

D’Emilia,

Gaspari

et al. 2023

J. Phys.: Conf. Ser.

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The paper intends to investigate some metrological aspects concerning data acquisition in determining the slope of escape routes in existing building, in order to provide this information as input for subsequent evacuation planning algorithms. The analysis is based on the point cloud acquired by a laser scanner and deepens different aspect that can impact on the slope uncertainty, linked to the choice of the algorithm for determining the slope itself, the values of the different parameters to set, and the different possible study strategies of the floor surface. The analysis will be conducted by using a commercial software, with the aim, in a future work, of investigating other kinds of algorithms and approaches, but also non-commercial data processing methods that may provide further useful information.

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Section: Introductionmentioning

confidence: 99%

Metrological issues in the use of mobile mapping systems for planning emergency response

Chiominto,

D’Emilia,

Gaspari

et al. 2023

J. Phys.: Conf. Ser.

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“…In fact, the expansion of agriculture has to face several issues: limited fresh water, reduced arable land and the reduction of manual labor. IoT solutions help farmers by ensuring high productivity and efficiency [5]. In particular, IoT technology allows the growth of precision agriculture, which reduces operational costs and guarantees an optimization of the natural resources.…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis of Wireless Sensor Network for Smart Farming Applications

Catelani

Ciani

Bartolini

et al. 2021

Sensors

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Wireless Sensor Networks are subjected to some design constraints (e.g., processing capability, storage memory, energy consumption, fixed deployment, etc.) and to outdoor harsh conditions that deeply affect the network reliability. The aim of this work is to provide a deeper understanding about the way redundancy and node deployment affect the network reliability. In more detail, the paper analyzes the design and implementation of a wireless sensor network for low-power and low-cost applications and calculates its reliability considering the real environmental conditions and the real arrangement of the nodes deployed in the field. The reliability of the system has been evaluated by looking for both hardware failures and communication errors. A reliability prediction based on different handbooks has been carried out to estimate the failure rate of the nodes self-designed and self-developed to be used under harsh environments. Then, using the Fault Tree Analysis the real deployment of the nodes is taken into account considering the Wi-Fi coverage area and the possible communication link between nearby nodes. The findings show how different node arrangements provide significantly different reliability. The positioning is therefore essential in order to obtain maximum performance from a Wireless sensor network.

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“…Furthermore, simulation data should be validated after part manufacturing, especially after additional thermal treatments, by comparison with measurements of different possible parameters such as microstructural variations, induced stresses and deviations on the part dimensions [10], [11]. This comparison requires the theoretical/experimental analysis of all the uncertainty contributions involved in the measurement process in order to assess the compatibility between model results and measurement data in probabilistic terms [12].…”

Section: Introductionmentioning

confidence: 99%

Uncertainty assessment for measurement and simulation in selective laser melting: a case study of an aerospace part

et al. 2020

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<p class="Abstract"><span lang="EN-US">In this work, the additive manufacturing process selective laser melting is analysed with the aim of realising a complex piece for aerospace applications. In particular, the effect of the manufacturing process and of the following thermal treatments on the dimensions of the workpiece is evaluated. The study is based on a hybrid approach including a simulation of the whole manufacturing process by advanced software packages and the dimensional measurements of the realised pieces taken by a coordinate measuring machine (CMM). The integrated use of simulation and measurements is carried out with the aim of validating the simulation results and of identifying the operational limits of both approaches; this analysis is based on metrological evaluation of the results of both the simulation and the tests, taking into account the uncertainty of the data. In addition, the main causes of uncertainty for the simulation activity and the experimental data have been identified, and the effects of some of them have also been experimentally evaluated. Based on the experimental validation, the simulation seems to predict the absolute displacement of the supports of the piece in a satisfactory way, while it is unable, in the actual configuration, to assess the conformity of the surface to its very tight shape tolerances. Conformity assessment of the surface should be carried out by CMM measurement. Integrated use of simulation and experimental results is expected to strongly improve the accuracy of simulation results for the effective and accurate design and control of the additive manufacturing process, including dimensional control and thermal treatments to mitigate induced thermal stresses.</span></p>

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Managing the uncertainty of conformity assessment in environmental testing by machine learning

Cited by 12 publications

References 18 publications

Metrological issues in the use of mobile mapping systems for planning emergency response

Metrological issues in the use of mobile mapping systems for planning emergency response

Reliability Analysis of Wireless Sensor Network for Smart Farming Applications

Uncertainty assessment for measurement and simulation in selective laser melting: a case study of an aerospace part

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