71 research outputs found
Eliciting the Double-edged Impact of Digitalisation: a Case Study in Rural Areas
Designing systems that account for sustainability concerns demands for a
better understanding of the \textit{impact} that digital technology
interventions can have on a certain socio-technical context. However, limited
studies are available about the elicitation of impact-related information from
stakeholders, and strategies are particularly needed to elicit possible
long-term effects, including \textit{negative} ones, that go beyond the planned
system goals.
This paper reports a case study about the impact of digitalisation in remote
mountain areas, in the context of a system for ordinary land management and
hydro-geological risk control. The elicitation process was based on interviews
and workshops. In the initial phase, past and present impacts were identified.
In a second phase, future impacts were forecasted through the discussion of two
alternative scenarios: a dystopic, technology-intensive one, and a
technology-balanced one. The approach was particularly effective in identifying
negative impacts.
Among them, we highlight the higher stress due to the excess of connectivity,
the partial reduction of decision-making abilities, and the risk of
marginalisation for certain types of stakeholders. The study posits that before
the elicitation of system goals, requirements engineers need to identify the
socio-economic impacts of ICT technologies included in the system, as negative
effects need to be properly mitigated. Our study contributes to the literature
with: a set of impacts specific to the case, which can apply to similar
contexts; an effective approach for impact elicitation; and a list of lessons
learned from the experience.Comment: Accepted to IEEE RE 2023, International Conference on Requirements
Engineering, 10 pages plus 2 pages of reference
Smooth Lasso Estimator for the Function-on-Function Linear Regression Model
A new estimator, named as S-LASSO, is proposed for the coefficient function
of a functional linear regression model where values of the response function,
at a given domain point, depends on the full trajectory of the covariate
function. The S-LASSO estimator is shown to be able to increase the
interpretability of the model, by better locating regions where the coefficient
function is zero, and to smoothly estimate non-zero values of the coefficient
function. The sparsity of the estimator is ensured by a functional LASSO
penalty whereas the smoothness is provided by two roughness penalties. The
resulting estimator is proved to be estimation and pointwise sign consistent.
Via an extensive Monte Carlo simulation study, the estimation and predictive
performance of the S-LASSO estimator are shown to be better than (or at worst
comparable with) competing estimators already presented in the literature
before. Practical advantages of the S-LASSO estimator are illustrated through
the analysis of the well known \textit{Canadian weather} and \textit{Swedish
mortality dat
Functional clustering methods for resistance spot welding process data in the automotive industry
Quality assessment of resistance spot welding (RSW) joints of metal sheets in
the automotive industry is typically based on costly and lengthy off-line tests
that are unfeasible on the full production, especially on large scale. However,
the massive industrial digitalization triggered by the industry 4.0 framework
makes available, for every produced joint, on-line RSW process parameters, such
as, in particular, the so-called dynamic resistance curve (DRC), which is
recognized as the full technological signature of the spot welds. Motivated by
this context, the present paper means to show the potentiality and the
practical applicability to clustering methods of the functional data approach
that avoids the need for arbitrary and often controversial feature extraction
to find out homogeneous groups of DRCs, which likely pertain to spot welds
sharing common mechanical and metallurgical properties. We intend is to provide
an essential hands-on overview of the most promising functional clustering
methods, and to apply the latter to the DRCs collected from the RSW process at
hand, even if they could go far beyond the specific application hereby
investigated. The methods analyzed are demonstrated to possibly support
practitioners along the identification of the mapping relationship between
process parameters and the final quality of RSW joints as well as, more
specifically, along the priority assignment for off-line testing of welded
spots and the welding tool wear analysis. The analysis code, that has been
developed through the software environment R, and the DRC data set are made
openly available online at https://github.com/unina-sfere/funclustRSW
funcharts: Control charts for multivariate functional data in R
Modern statistical process monitoring (SPM) applications focus on profile
monitoring, i.e., the monitoring of process quality characteristics that can be
modeled as profiles, also known as functional data. Despite the large interest
in the profile monitoring literature, there is still a lack of software to
facilitate its practical application. This article introduces the funcharts R
package that implements recent developments on the SPM of multivariate
functional quality characteristics, possibly adjusted by the influence of
additional variables, referred to as covariates. The package also implements
the real-time version of all control charting procedures to monitor profiles
partially observed up to an intermediate domain point. The package is
illustrated both through its built-in data generator and a real-case study on
the SPM of Ro-Pax ship CO2 emissions during navigation, which is based on the
ShipNavigation data provided in the Supplementary Material
Tratamento endovascular das doenças da aorta torácica: análise dos resultados de um centro
Preliminary Assessment of Radiolysis for the Cooling Water System in the Rotating Target of {SORGENTINA}-{RF}
The SORGENTINA-RF project aims at developing a 14 MeV fusion neutron source featuring an emission rate in the order of 5-7 x 10(13) s(-1). The plant relies on a metallic water-cooled rotating target and a deuterium (50%) and tritium (50%) ion beam. Beyond the main focus of medical radioisotope production, the source may represent a multi-purpose neutron facility by implementing a series of neutron-based techniques. Among the different engineering and technological issues to be addressed, the production of incondensable gases and corrosion product into the rotating target deserves a dedicated investigation. In this study, a preliminary analysis is carried out, considering the general layout of the target and the present choice of the target material
INTERMEDIARIES BOOSTING THE DIGITAL TRANSFORMATION OF SMES: A COMPARATIVE ANALYSIS BETWEEN ITALY AND THE RUSSIAN FEDERATION
A Comparative Analysis Between Italian and Russian Measures Supporting the Digital Transformation of SMEs
An interpretable estimator for the function-on-function linear regression model with application to the Canadian weather data
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