Search

In recent years, the potential of the metaverse as a tool to connect people has been increasingly recognized. The opportunities offered by the metaverse seem enormous in many sectors and fields of application. However, on the academic side, although a growing number of papers have been found to address the adoption of the metaverse, a clear overview of the solutions in place and their impact on education has been largely neglected so far. In the context of increasing challenges found with the metaverse, this review aims to investigate the role of the metaverse as tool in education. This contribution aims to address this research gap by offering a state-of-the-art analysis of the role the metaverse plays in education in relation to the future of work. The study is based on a systematic review approach performed by means of the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol. The findings of this research help us to better understand the benefits, potential and risks of the metaverse as a tool for immersive and innovative learning experiences. Implications are discussed and streams for future investigation are identified.

Leather material is used in different industrial sectors that generate high quantities of wastes, especially during the cutting phase. This study aims to propose a reuse path for leather scraps focused on the production of an insulation panel. The technical feasibility evaluation demonstrated that the innovative material has acceptable performance to be applied as thermal insulation for building. The preliminary life cycle assessment study compared the environmental performance of the innovative panel against a polyurethane panel. Results demonstrated benefits in some impact and damage categories (−36% in terms of climate change and −15% in terms of ReCiPe single score).

The CUbesat Solar Polarimeter (CUSP) project aims to develop a constellation of two CubeSats orbiting the Earth to measure the linear polarisation of solar flares in the hard X-ray band by means of a Compton scattering polarimeter on board of each satellite. CUSP will allow to study the magnetic reconnection and particle acceleration in the flaring magnetic structures. CUSP is a project approved for a Phase A study by the Italian Space Agency in the framework of the Alcor program aimed to develop CubeSat technologies and missions., Comment: SPIE Astronomical Telescopes + Instrumentation, 17 - 22 July 2022, Montr\'eal, Qu\'ebec, Canada

In this paper, we deal with the design of a sustainable network of charging stations for electric vehicles circulating in an urban area. The major obstacles to E-Mobility (EM) development are still to be found into heated debates both in the scientific and industrial field and into a lacking of a widespread, accessible and homogeneous recharge infrastructure for the electric vehicles. In this work, we face the problem known as location optimization of charging stations and offer a heuristic method to design a sustainable infrastructure for the electric vehicles charging into urban contexts. In particular, the research can help mayors and governors of cities to take decisions concerning the number, the type and the placement of charging stations, taking into account the estimated hourly demand of charging services. Obviously, the design of an appropriate network includes the definition of all the needed costs to build the infrastructure and then the analysis of economic sustainability of the network basing on the revenues coming from estimated demand. The profitability of single charging stations is one of the main criteria to choose for the installation of a station. In this study we assume homogeneous pricing policy like in a monopoly scenario among charging stations. Future research can investigate on the effect of different prices applied by stations in the network design.

Industrialized societies depend on the proper functioning of a whole range of technological infrastructures, such as electricity, road and railway networks and telecommunications which, due to their importance, are generically referred to as critical infrastructures (CIs). Technical failures, natural disasters and malicious events, if not terrorist, could have devastating effects on these infrastructures. The events of the last few years have accelerated efforts to identify and designate CIs at national and European levels and have reinforced concerns about increasing their protection in sensitive sectors for the safety of the individual and the community. The aim of this research is to provide the basic elements to understand the issue along with the reasons for its importance both at national, European and international level. In particular, after analyzing the origin of the problem, a systematic literature review is carried out to study the current research around future perspectives relating to the management of Cis, with particular focus on three research questions: RQ1 “What types of risk assessment methods are used to manage CIs?”, RQ2 “What are the environmental risk mitigation strategies for CIs?” and RQ3 “What is the role of the human factor in the prevention of risks for CIs?”. The results aim to be guidelines for decision makers and researchers interested in this topic.

The emergencies management in industrial plants is an issue widely discussed in the literature and in the European legislative framework. Despite the large interest shown by the different actors involved in emergencies management, neither scientific nor in industrial field, have developed intelligent tools to support the decisions in these particular contexts. This work, realized inside an Italian financed project (DIEM-SSP), faces the problem to evacuate the greater number of persons from a risky area and transfer them in a unique destination outside from this area using the available and limited resources. Supposing that these persons have problem of mobility, the problem to solve becomes this: collect the highest number of persons from several origins and bring them into a unique destination, using a limited number of capacitated vehicles respecting a time limit. This problem has been modelled as a Multi origins Capacitated Team Orienteering Problem (Mo-CTOP) and solved implementing Ants Colony Optimization algorithm (ACOa). Results and tests are given in order to validate the proposed model and to offer a solution for a real case treaty into the abovementioned project.

Fuel cell based trigeneration plants, that utilize absorption chillers to convert waste heat into cooling energy, are a promising technology to satisfy heat, power, and cooling demand in warm climates. Polymer electrolyte membrane fuel cells, that operate at low temperature ( 100 ° C), are the most technologically mature among the several types of fuel cells. Thermally activated cooling technologies are widely utilized in trigeneration plants to improve their efficiency. However, absorption chillers require relatively high grade thermal energy and their coupling with low temperature fuel cells is relatively untapped. Herein, we perform a techno-economic analysis of a trigeneration plant based on low temperature polymer electrolyte membrane fuel cells and half-effect absorption chillers. A thermo-chemical model is developed to estimate the performance of a cogeneration plant based on low temperature fuel cells and of the half-effect absorption chiller. The behavior of such combined heat, cooling, and power plant is also analyzed within real energy management scenarios, considering different energy demands, climatic conditions, energy costs, and plant layouts. The control strategy of the power plant is optimized through a graph-based methodology previously developed and validated by the authors. Total energy cost and CO2 emissions are then compared to those of a reference scenario where electricity is acquired from the distribution grid, thermal energy is produced through a natural gas boiler, and a mechanical chiller is used for cooling. The results show that the utilization of half-effect absorption chillers boosts the environmental and economic benefits for all the considered scenarios. We also demonstrate that the utilization of the absorption chiller reduces the imbalance between the results obtained for the different scenarios (i.e. climates), although economic and environmental benefits associated to distributed generation are strongly influenced by the energy context.

We consider the problem of designing a distribution network for a logistics provider that acquires products from multiple facilities and then delivers those products to many retail outlets. Potential locations for consolidation facilities that combine shipments for cost reduction and service improvements are considered. The problem is formulated with direct shipment and consolidation opportunities. A novel mathematical model is derived to solve a complex facility location problem determining: (i) the location and capacity level of warehouses to open; (ii) the distribution route from each production facility to each retailer outlet; and (iii) the quantity of products stocked at each warehouse and retailer. A genetic algorithm and a specific problem heuristic are designed, tested and compared on several realistic scenarios.

The recent advances in technology sectors often clash with traditional organizational paradigms which can limit or make difficult an efficient implementation in the real world. In this paper we show how it is possible to exploit the advantages of innovative technologies in manufacturing when these are supported by new and efficient methods for production management. More in details, we face a flow shop scheduling problem in a shoe manufacturing system in which overtaking of jobs is allowed thanks to an innovative transportation system. Overtaking means that a job can be put in waiting state and another job can surpass it, allowing the change of the scheduling sequence. Preemption is not allowed. The objective function of the problem is the minimization of the maximum lateness. We propose a decentralized model, based on multi-agent system theory, to represent the production cells of the plant and to include the potentiality offered by overtaking of jobs at decisional level. The adoption of a decentralized approach increases the system flexibility since each machine is able to solve its local scheduling problem. Adding or removing machines to the plant will not imply a change in the scheduling algorithms. The outcomes of this work are reached firstly through a formulation of the problem with three flow shop scheduling models, secondly through a comparison of the models with respect to different performance indicators. The results highlight as the decentralized approach is able to reach comparable performances with the centralized one for a relevant number of instances. Moreover sensitivity analysis shows as in the decentralized model the computational time required to solve bigger instances increases less quickly than in the case of centralized ones. Finally, simulations of the decentralized approach clarify as the correlation of the local solution procedure is effected by the number of machines of the flow shop and the coordination mechanism is effected by the number of the jobs to be scheduled.

This article provides a model based on the Multi Agent System (MAS) paradigm that acts as a methodological basis for evaluating the dynamics in a collaborative environment. The model dynamics is strictly driven by the competence concept. In the provided MAS, the agents represent the actors operating on a given area. In particular, the proposed agents are composed of three distinct typologies: (i) the territorial agent, (ii) the enterprise agent, and (iii) the public agent. Each agent has its local information and goals, and interacts with others by using an interaction protocol. The decision-making processes and the competencies characterize in a specific way each one of the different agent typologies working in the system.

This paper provides a model based on the Multi Agent System (MAS) paradigm that acts as a methodological basis for evaluating the dynamics in a collaborative environment. The model dynamics is strictly driven by the competence concept. In the provided MAS, the agents represent the actors operating on a given area. In particular, the proposed agents are composed of three distinct typologies: (i) the territorial agent, (ii) the enterprise agent, and (iii) the public agent. Each agent has its local information and goals, and interacts with others by using an interaction protocol. The decision-making processes and the competencies characterize in a specific way each one of the different agent typologies working in the system.

The healthcare services cost are constantly increasing during the last 20 years. This trend has two origins: on one hand the people resort to drugs and healthcare services more often than in the past because more medical treatment are known; on the other hand, this evolution was not supported by an intelligent growth and design of healthcare structure and services. Indeed, a lot of hospital processes, such as drugs and equipments purchasing and managing, are not under control of hospital managers. This work faces the cost and management criticalities presenting a healthcare system as a multi-agent cooperative network. The proposed model faces the challenge of (i) gaining the benefits deriving from successful collaborative models already used in industrial systems and (ii) transferring the most appropriate industrial management practices. The model exploits an operations research technique based on combinatorial auctions in order to effective assign drugs to wards.

The cost of services provided by public and private healthcare systems is nowadays becoming critical. This work tackles the criticalities of hospital equipments and drugs management by emphasizing its implications on the whole healthcare system efficiency. The work presents a multi-agent based model for decisional cooperation in order to address the problem of integration of departments, wards and personnel for improving equipments, and drugs management. The proposed model faces the challenge of (i) gaining the benefits deriving from successful collaborative models already used in industrial systems and (ii) transferring the most appropriate industrial management practices to healthcare systems.

The reduction of a Manufacturing System Complexity is possible adopting a decentralized approach focused on optimization at operation level, and on coordination at higher level of production plant. This point of view, inherited by multi agent models, can increase the flexibility and reduce the complexity of the system management. We apply this principle to a shoe manufacturing system, characterized by an automated transportation who, governed by scheduling rules, can exploit the overtake capability. The operational objectives of the plant are to augment the capacity of the system, to rapidly react to market changes and to obtain a better balance machine work load.

In this work we proposed an integrated support system combining a meta-heuristic algorithm and a multicriteria decision analysis method to solve an orienteering problem applied to car-pooling system. For this purpose a Genetic Algorithm (GA), an Analytical Hierarchy Process (AHP) are implemented. The research is based on the awareness that decision makers (DMs) often face situations in which different conflicting viewpoints (goals or criteria) are to be considered. Current car-pooling web platforms are focused on the exchange of information among potential users and drivers. The aim of this work is to include in web platform a decision procedure to support driver to organize the tour considering more criteria. The driver has to decide which tour does and which users to take into the trip Preliminary test are given to validate the functionality and usefulness of created integrated decision support system.

During the last years the decision making processes is evolving becoming more and more distributed and asynchronous. In order to support decision-makers who are not at the same place at the same time are defined cooperation processes and a set of models able to support designers of Cooperative decision support framework. One of this, proposed in this thesis, is a Reference Model to build Multi Agent System able to represent complex and distributed system composed by several intelligent collaborative entities. Following this definition, it is possible define like collaborative network a lot of complex system such as: 1. Flexible Manufacturing Systems (FMSs) that are defined by Ciliers (Ciliers P., 1998) as complex systems in which the knowledge of the system elements composition and the interaction between the environment and the system, is not enough to understand the system functioning; 2. Industrial Clusters (ICs) that can be defined as socioeconomic entities characterized by a social community of people and a population of economic agents localized in close proximity in a specific geographic region that interact to reach similar outcomes (Marshall, 1925); 3. Supply Chains (SCs), network of suppliers, factories, warehouses, distribution centres and retailers that operate in integrated manner (Fox, 1992) with the same aim of reducing inventory and costs, adding value, extending resource and accelerating the time to market. 4. Healthcare Systems, composed by several entities interacting in a great number of critical processes. The internal dynamics of an hospital represents a complex non-linear structure hard to manage in centralized way (Harper 2002). The above mentioned list represents only a part of the numerousness examples of system that can be represented as collaborative networks and that need to be managed in distributed manner due to complexity and to great amount of information necessary to take any kind of decision. There are not many models able to represent and manage this kind of distributed systems, Petri nets represent one of this but present some limits due to: (i) the model become too large and complex even for a modest size problem (Wang J., Deng Y., 1999); (ii) the difficulty to make even a little change to a previously built model. The Multi Agent System (MAS) approach aim to overcome these limits of rigidity and computing complexity trough: (i) the possibility to solve complex problem solving a set of easier local problems; (ii) the opportunity to change some problem parameters or to substitute any system element without discard entirely the original model. The MAS are widely studied in literature like method able to represent dynamic and distributed system with several decision makers having different information domains. It is possible to observe a lack in investigate the problem solving ability of intelligent agents in a multi-agent setting and a variety of representation methods. The difficulty of apply this model approach reside into the activity of architecture design used by the system elements to speak and act. The number and the kind of relations among the system entities became the most important indicator of the model's complexity. For this reason the outcome of my researches can be presented as a reference model integrating two types of approach for the models creation in the MAS field. The main scope is to provide the guidelines able to support the designer in the system modelling like MAS, indicating also in which scenario is more convenient to adopt an approach oriented to Operation Research (OR) technique or another one. The Reference Model is evaluated and validated thanks to several application in different contests, some of whom are mentioned at the beginning of this abstract.