Innovative Ecosystem Model of Vaccine Lifecycle Management

The COVID-19 pandemic has severely tested humanity, revealing the need to develop and improve the medical, economic, managerial, and IT components of vaccine management systems. The vaccine lifecycle includes vaccine research and development, production, distribution, and vaccination of the population. To manage this cycle effectively the proper organizational and IT support model of the interaction of vaccine lifecycle management stakeholders is needed—which are an innovation ecosystem and an appropriate virtual platform. A literature review has revealed the lack of methodological basis for the vaccine innovation ecosystem and virtual platform. This article is devoted to the development of a complex approach for the development of an innovation ecosystem based on vaccine lifecycle management and a virtual platform which provides the data exchange environment and IT support for the ecosystem stakeholders. The methodological foundation of the solution, developed in the article, is an enterprise architecture approach, CALS technologies, supply chain management and an open innovation philosophy. The results, presented in the article, are supposed to be a reference set of models for the creation of a vaccine innovation ecosystem, both during pandemics and periods of stable viral load.

A Lightweight Authentication Scheme Based on Consortium Blockchain for Cross-Domain IoT

Internet of Things (IoT) has been ubiquitous in both industrial and living areas, but also known for its weak security. Being as the first defense line against various cyberattacks, authentication is even more critical to IoT applications. Moreover, there has been a growing demand for cross-domain collaboration, leading to an increasing need for cross-domain authentication. Recently, certificate-based authentication schemes have been extensively studied. However, many of these schemes are not efficient in computation, storage, and communication, which are highly required in IoT. In this paper, we propose a lightweight authentication scheme based on consortium blockchain and design a cryptocurrency-like digital token to build trust. Furthermore, trust lifecycle management is performed by manipulating the amount of tokens. The comprehensive analysis and evaluation demonstrate that the proposed scheme is resistant to various common attacks and more efficient than competitor schemes in terms of storage, communication, and authentication cost.

Assessing The Maturity Of The Asset Lifecycle Management In The Case Of The Massachusetts Bay Transportation Authority (MBTA)

Asset management is a central capability that organizations have to perform well. Asset management is concerned about the management of assets that are valuable or potentially valuable to an organization. This article focuses on asset management as it is performed in the railway transit industry. The past decade has seen a number of positive changes in the way that transit agencies manage their assets. While many transit agencies have introduced asset management approaches, work still needs to be done in the area of how we assess the maturity of asset management programs. This article proposes a framework for assessing the maturity of asset management programs, especially those that are used to manage individual assets according to their lifecycles. To illustrate the value of the proposed asset management maturity framework, we describe the asset management transformation at a transit agency and use the proposed framework to document the gains of the improvement effort.

Life–Cycle Oriented Risk Assessment Using a Monte Carlo Simulation

State of the art mechatronic systems are complex assemblies of various parts and sub-systems. In such an interconnected system, even relatively cheap parts can have a major impact on the overall performance due to unexpected failure. Hence, lifecycle management has major implications on the successful modification of existing products. Potential savings due to changes in production and procurement must be compared to the implied risk of products failing in the field due to these changes. This work documents a generic approach for risk assessment based on the distribution of the expected savings and incident costs over the whole lifecycle. To do so, a stochastic model is introduced to quantify the expected savings and costs given a non-risk-free product modification. Using a Monte Carlo simulation, the effects of uncertainty are incorporated into the risk management. The model and simulation are deployed within an industrial use case. The application demonstrates both the appropriateness of the tool and its useability.

Retención de la información en la empresa: cuestión de sostenibilidad

It is not sustainable to keep all information indefinitely. Retention is an essential aspect of corporate information governance that facilitates data and document lifecycle management. Future trends in information technologies lead us to reflect on the methodologies available and the professional qualifications needed to find new ways to help define and implement the necessary retention policies in companies and organizations. Resumen Guardar toda la información indefinidamente no es sostenible. La retención es un aspecto esencial de la gobernanza de la información que facilita la gestión del ciclo de vida de datos y documentos. Las tendencias futuras de las tecnologías de información nos llevan a reflexionar sobre las metodologías disponibles y las cualificaciones profesionales necesarias para encontrar nuevos caminos que ayuden la definición y aplicación de las necesarias políticas de retención en empresas y organizaciones.

Digital transformation in topographic databases

The increasingly widespread implementation of databases with geographical component, as well as the impregnation of geolocation culture, is driving a transformation in the storage, management and exploitation of geospatial information. Real-world elements go from being modeled as mere geometric representations, with just cartographic purposes, to be features with their own entity. Unique identifiers and lifecycle management are assigned to these features, allowing interactions between feature instances from different databases, that is, facilitating digital transformation and, therefore, increasing exponentially the exploitation possibilities.In this regard, the National Geographic Institute of Spain (IGN, by its Spanish acronym) have implemented several processes in its National Topographic Database, such as the connection with the cadastral information, in order to take advantage of its updates and give feedback to improve cadastral data; or the link with the information, in addresses form, provided from different public administration, that is processed to geolocate features in the topographic database. Likewise, work is being done in order to implement new processes that allow linking with other data sets.These processes, in addition to reusing information produced by different public administrations, constitute an advance towards the objective of geospatial information databases continuous updating.

Overview of Explainable Artificial Intelligence for Prognostic and Health Management of Industrial Assets Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Surveys on explainable artificial intelligence (XAI) are related to biology, clinical trials, fintech management, medicine, neurorobotics, and psychology, among others. Prognostics and health management (PHM) is the discipline that links the studies of failure mechanisms to system lifecycle management. There is a need, which is still absent, to produce an analytical compilation of PHM-XAI works. In this paper, we use preferred reporting items for systematic reviews and meta-analyses (PRISMA) to present a state of the art on XAI applied to PHM of industrial assets. This work provides an overview of the trend of XAI in PHM and answers the question of accuracy versus explainability, considering the extent of human involvement, explanation assessment, and uncertainty quantification in this topic. Research articles associated with the subject, since 2015 to 2021, were selected from five databases following the PRISMA methodology, several of them related to sensors. The data were extracted from selected articles and examined obtaining diverse findings that were synthesized as follows. First, while the discipline is still young, the analysis indicates a growing acceptance of XAI in PHM. Second, XAI offers dual advantages, where it is assimilated as a tool to execute PHM tasks and explain diagnostic and anomaly detection activities, implying a real need for XAI in PHM. Third, the review shows that PHM-XAI papers provide interesting results, suggesting that the PHM performance is unaffected by the XAI. Fourth, human role, evaluation metrics, and uncertainty management are areas requiring further attention by the PHM community. Adequate assessment metrics to cater to PHM needs are requested. Finally, most case studies featured in the considered articles are based on real industrial data, and some of them are related to sensors, showing that the available PHM-XAI blends solve real-world challenges, increasing the confidence in the artificial intelligence models’ adoption in the industry.