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Publications

2023

SDG commentary: service ecosystems with the planet - weaving the environmental SDGs with human services

Authors
Teixeira, JG; Gallan, AS; Wilson, HN;

Publication
JOURNAL OF SERVICES MARKETING

Abstract
Purpose - Humanity and all life depend on the natural environment of Planet Earth, and that environment is in acute crisis across land, sea and air. One of a set of commentaries on how service can address the UN's sustainable development goals (SDGs), the authors focus on environmental goals SDG 13 (climate action), SDG 14 (life below water) and SDG 15 (life on land). This paper aims to propose a conceptual framework that incorporates the natural environment into transformative services. Design/methodology/approach - The authors trace the evolution of service thinking about the natural environment, from a stewardship perspective of the environment as a set of resources to be managed, through an acknowledgement of nonhuman organisms as actors that can participate in service exchange, towards an emergent concept of ecosystems as integrating human social actors and other biological actors who engage fully in value co-creation. Findings - The authors derive a framework integrating human and other life forms as co-creating actors, drawing on shared natural resources to achieve mutualism, where each actor can have a net benefit from the relationship. Future research questions are posited that may help services research address SDGs 13-15. Originality/value - The framework integrates ideas from environmental ecosystem literature to inform the nature of ecosystems. By integrating environmental actors and ecological insights into the understanding of service ecosystems, service scholars are well placed to make unique contributions to the global challenge of creating a sustainable future.

2023

Predicting Hard Disk Drive faults, failures and associated misbehavior's

Authors
Harrison, C; Balu, H; Dutra, I;

Publication
2023 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS, IPDPSW

Abstract
Magnetic hard disk drives continue to be heavily used to store global information. However, due to the physical characteristics these components fatigue and fail, sometimes in unexpected ways. A failing hard disk can cause problems to a group of hard disks and result in suboptimal performance which impacts cloud providers. To address failures, redundancies are put in place, but these redundancies have a high cost. Utilizing Machine learning we identify predictive failure features within a hard disk vendor's Hard Disk Drive Model line which can be used as an early failure prediction method which may be used to reduce redundancies in cloud storage infrastructures.

2023

The assessment of performance trends and convergence in education and training systems of European countries

Authors
Camanho, AS; Stumbriene, D; Barbosa, F; Jakaitiene, A;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
The Strategic Framework for European Cooperation in Education and Training (ET 2020) aimed to pro-mote the exchange of best practices among the Member States. This paper assesses the performance evo-lution of European countries in terms of the common objectives for the education sector. The framework used to evaluate European education systems is based on constructing a composite indicator adopting a benefit-of-the-doubt approach. The evaluation of performance change over time is done using a Global Malmquist Index. Sigma and beta convergence of EU countries are also explored using non-parametric frontier techniques. The results are analysed for the period 2009-2018 and discussed in light of the goals envisaged and the national policies adopted. The results revealed a trend of improvement in the perfor-mance of education systems in most European countries in the period analysed. Although most European countries moved closer to the European best practice frontier over time, as confirmed by the values of sigma-convergence, a few countries are still lagging considerably below their peers, as revealed by the existence of divergence in beta.(c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )

2023

Geometric and Physical Building Representation and Occupant's Movement Models for Fire Building Evacuation Simulation

Authors
Neto, J; Morais, AJ; Gonçalves, R; Coelho, AL;

Publication
PROCEEDINGS OF SEVENTH INTERNATIONAL CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGY, ICICT 2022, VOL. 2

Abstract
Building evacuation simulation allows for a better assessment of fire safety conditions in existing buildings, which is why it is of interest to develop an easyto-use-Web platform that helps fire safety technicians in this assessment. To achieve this goal, the geometric and physical representation of the building and installed fire safety devices are necessary, as well as the modelling of occupant movement. Although these are widely studied areas, in this paper, we present two new model approaches, either for the physical and geometric representation of a building or for the occupant's movement simulation, during a building evacuation process. To test both models, we develop a multi-agentWeb simulator platform. The tests carried out show the suitability of the model approaches herein presented.

2023

The Role of Data-Driven Solutions for SMES in Responding to COVID-19

Authors
Almeida, F; Wasim, J;

Publication
INTERNATIONAL JOURNAL OF INNOVATION AND TECHNOLOGY MANAGEMENT

Abstract
This study aims to explore the role of small and medium-sized enterprises (SMEs) in developing data-driven solutions to address the direct and indirect challenges posed by COVID-19. A sample of six case studies of SMEs from the UK and Portugal were selected to explore in-depth the experience of these companies in proposing innovative solutions in the pandemic context. The findings reveal that the pandemic caused amplifying effects on the digitalization of organizations and the emergence of data-driven solutions. However, the development of a data-driven approach involves not only technologies but also the digitalization of processes and highly skilled human resources. The pandemic was also a catalyst for the emergence of collaborative initiatives that have enabled the development of solutions involving diverse players from science, business, and civilian society. This study offers innovative contributions by focusing exclusively on companies developing data-driven solutions supported by technologies such as the internet of things (IoT), big data, and artificial intelligence.

2023

Execution time as a key parameter in the waste collection problem

Authors
Silva, S; Pereira, I; Lima, J; Silva, MT; Gomes, T;

Publication
Iberian Conference on Information Systems and Technologies, CISTI

Abstract
Proper waste management has been recognized as a tool for the green transition towards a more sustainable economy. For instance, most studies dealing with municipal solid wastes in the literature focus on environmental aspects, proposing new routes for recycling, composting and landfilling. However, there are other aspects to be improved in the systems that deal with municipal solid waste, especially in the transportation sector. Scholars have been exploring alternatives to improve the performance in waste collection tasks since the late 50s, for example, considering the waste collection problem as static. The transition from a static approach to a dynamic is necessary to increase the feasibility of the solution, requiring faster algorithms. Here we explore the improvement in the performance of the guided local search metaheuristic available in OR-Tools upon different execution times lower than 10 seconds to solve the capacitated waste collection problem. We show that increasing the execution time from 1 to 10 seconds can overcome savings of up to 1.5 km in the proposed system. Considering application in dynamic scenarios, the 9 s increase in execution time (from 1 to 10 s) would not hinder the algorithm's feasibility. Additionally, the assessment of the relation between performance in different execution times with the dataset's tightness revealed a correlation to be explored in more detail in future studies. The work done here is the first step towards a shift of paradigm from static scenarios in waste collection to dynamic route planning, with the execution time established according to the conclusions achieved in this study. © 2023 ITMA.

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