paper-with-me

Papers

The Energy Worker Profiler from Technologies to Skills to Realize Energy Efficiency in Manufacturing

2023-01-23 · Silvia Fareri, Riccardo Apreda, Valentina Mulas, Ruben Alonso

In recent years, the manufacturing sector has been responsible for nearly 55 percent of total energy consumption, inducing a major impact on the global ecosystem. Although stricter regulations, restrictions on heavy manufacturing and technological advances are increasing its sustainability, zero-emission and fuel-efficient manufacturing is still considered a utopian target. In parallel,companies that have invested in digital innovation now need to align their internal competencies to maximize their return on investment. Moreover, a primary feature of Industry 4.0 is the digitization of production processes, which offers the opportunity to optimize energy consumption. However, given the speed with which innovation manifests itself, tools capable of measuring the impact that technology is having on digital and green professions and skills are still being designed. In light of the above, in this article we present the Worker Profiler, a software designed to map the skills currently possessed by workers, identifying misalignment with those they should ideally possess to meet the renewed demands that digital innovation and environmental preservation impose. The creation of the Worker Profiler consists of two steps: first, the authors inferred the key technologies and skills for the area of interest, isolating those with markedly increasing patent trends and identifying green and digital enabling skills and occupations. Thus, the software was designed and implemented at the user-interface level. The output of the self-assessment is the definition of the missing digital and green skills and the job roles closest to the starting one in terms of current skills; both the results enable the definition of a customized retraining strategy. The tool has shown evidence of being user-friendly, effective in identifying skills gaps and easily adaptable to other contexts.

📄 PDF Abstract BibTeX arXiv:2301.09445

Code (0)

등록된 구현이 없습니다.

Methods 이 논문이 사용한 방법론

SPEED The monocular depth estimation (MDE) is the task of estimating depth from a single frame. This information is an essential knowledge in many computer vision tasks such as scene…
ALIGN In the ALIGN method, visual and language representations are jointly trained from noisy image alt-text data. The image and text encoders are learned via contrastive loss…

Similar Papers 제목 키워드 기반

Analysis of Arctic Buoy Dynamics using the Discrete Fourier Transform and Principal Component Analysis

2023-07-20 · James H. Hepworth, Amit Kumar Mishra

Sea-Ice drift affects various global processes including the air-sea-ice energy system, numerical ocean modelling, and maritime activity in the polar regions. Drift has been investigated via various technologies ranging …

The Language Demographics of Amazon Mechanical Turk

2014-01-01 · TACL 2014 1 · Ellie Pavlick, Matt Post, Ann Irvine, Dmitry Kachaev 외

We present a large scale study of the languages spoken by bilingual workers on Mechanical Turk (MTurk). We establish a methodology for determining the language skills of anonymous crowd workers that is more robust than s…

Machine TranslationTranslation

Complement or substitute? How AI increases the demand for human skills

2024-12-27 · Elina Mäkelä, Fabian Stephany

This paper examines whether artificial intelligence (AI) acts as a substitute or complement to human labour, drawing on 12 million online job vacancies from the United States spanning 2018-2023. We adopt a two-pronged ap…

Ethics

Low-skilled Occupations Face the Highest Upskilling Pressure

2021-01-27 · Di Tong, Lingfei Wu, James Allen Evans

Substantial scholarship has estimated the susceptibility of jobs to automation, but little has examined how job contents evolve in the information age as new technologies substitute for tasks, shifting required skills ra…

A Mathematical Framework for AI-Human Integration in Work

2025-05-29 · L. Elisa Celis, Lingxiao Huang, Nisheeth K. Vishnoi

The rapid rise of Generative AI (GenAI) tools has sparked debate over their role in complementing or replacing human workers across job contexts. We present a mathematical framework that models jobs, workers, and worker-…