0000000001008725
AUTHOR
Paolo Zanetti
Human capital evaluation in knowledge-based organizations based on big data analytics
Abstract Starting from a Human Capital Analysis Model, this work introduces an original methodology for evaluating the performance of employees. The proposed architecture, particularly well suited to the special needs of knowledge-based organizations, is articulated into a framework able to manage cases where data is missing and an adaptive scoring algorithm takes into account seniority, performance, and performance evolution trends, allowing employee evaluation over longer periods. We developed a flexible software tool that gathers data from organizations in an automatic way – through adapted connectors – and generates abundant results on the measurement and distribution of employees’ perf…
Performance and energy optimisation in CPUs through fuzzy knowledge representation
Abstract This paper presents an automatic design space exploration using processor design knowledge for the multi-objective optimisation of a superscalar microarchitecture enhanced with selective load value prediction (SLVP). We introduced new important SLVP parameters and determined their influence regarding performance, energy consumption, and thermal dissipation. We significantly enlarged initial processor design knowledge expressed through fuzzy rules and we analysed its role in the process of automatic design space exploration. The proposed fuzzy rules improve the diversity and quality of solutions, and the convergence speed of the design space exploration process. Experiments show tha…
A study on forecasting electricity production and consumption in smart cities and factories
Abstract The electrical power sector must undergo a thorough metamorphosis to achieve the ambitious targets in greenhouse gas reduction set forth in the Paris Agreement of 2015. Reducing uncertainty about demand and, in case of renewable electricity generation, supply is important for the determination of spot electricity prices. In this work we propose and evaluate a context-based technique to anticipate the electricity production and consumption in buildings. We focus on a household with photovoltaics and energy storage system. We analyze the efficiency of Markov chains, stride predictors and also their combination into a hybrid predictor in modelling the evolution of electricity producti…
Digitization, Epistemic Proximity, and the Education System: Insights from a Bibliometric Analysis
Advances in IoT, AI, Cyber-Physical Systems, Computational Intelligence, and Big Data Analytics require organizations and workforce to be able and willing to learn how to interact with digital technology. In organizations, coordination and cooperation between actors with expertise in business and technology is fundamental, but integration is hard without understanding the terminology and problems of the interlocutor. Epistemic proximity becomes prominent, underlining the importance of an education focused on flexibility, willingness to cope with the unknown, and interdisciplinarity. The main goal of this work is to provide a perspective on how the education system is evolving to support org…