7,280 research outputs found

    A Survey on Forensics and Compliance Auditing for Critical Infrastructure Protection

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    The broadening dependency and reliance that modern societies have on essential services provided by Critical Infrastructures is increasing the relevance of their trustworthiness. However, Critical Infrastructures are attractive targets for cyberattacks, due to the potential for considerable impact, not just at the economic level but also in terms of physical damage and even loss of human life. Complementing traditional security mechanisms, forensics and compliance audit processes play an important role in ensuring Critical Infrastructure trustworthiness. Compliance auditing contributes to checking if security measures are in place and compliant with standards and internal policies. Forensics assist the investigation of past security incidents. Since these two areas significantly overlap, in terms of data sources, tools and techniques, they can be merged into unified Forensics and Compliance Auditing (FCA) frameworks. In this paper, we survey the latest developments, methodologies, challenges, and solutions addressing forensics and compliance auditing in the scope of Critical Infrastructure Protection. This survey focuses on relevant contributions, capable of tackling the requirements imposed by massively distributed and complex Industrial Automation and Control Systems, in terms of handling large volumes of heterogeneous data (that can be noisy, ambiguous, and redundant) for analytic purposes, with adequate performance and reliability. The achieved results produced a taxonomy in the field of FCA whose key categories denote the relevant topics in the literature. Also, the collected knowledge resulted in the establishment of a reference FCA architecture, proposed as a generic template for a converged platform. These results are intended to guide future research on forensics and compliance auditing for Critical Infrastructure Protection.info:eu-repo/semantics/publishedVersio

    Exploring the Performance of an Artificial Intelligence-Based Load Sensor for Total Knee Replacements.

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    Using tibial sensors in total knee replacements (TKRs) can enhance patient outcomes and reduce early revision surgeries, benefitting hospitals, the National Health Services (NHS), stakeholders, biomedical companies, surgeons, and patients. Having a sensor that is accurate, precise (over the whole surface), and includes a wide range of loads is important to the success of joint force tracking. This research aims to investigate the accuracy of a novel intraoperative load sensor for use in TKRs. This research used a self-developed load sensor and artificial intelligence (AI). The sensor is compatible with Zimmer's Persona Knee System and adaptable to other knee systems. Accuracy and precision were assessed, comparing medial/lateral compartments inside/outside the sensing area and below/within the training load range. Five points were tested on both sides (medial and lateral), inside and outside of the sensing region, and with a range of loads. The average accuracy of the sensor was 83.41% and 84.63% for the load and location predictions, respectively. The highest accuracy, 99.20%, was recorded from inside the sensing area within the training load values, suggesting that expanding the training load range could enhance overall accuracy. The main outcomes were that (1) the load and location predictions were similar in accuracy and precision (p > 0.05) in both compartments, (2) the accuracy and precision of both predictions inside versus outside of the triangular sensing area were comparable (p > 0.05), and (3) there was a significant difference in the accuracy of load and location predictions (p < 0.05) when the load applied was below the training loading range. The intraoperative load sensor demonstrated good accuracy and precision over the whole surface and over a wide range of load values. Minor improvements to the software could greatly improve the results of the sensor. Having a reliable and robust sensor could greatly improve advancements in all joint surgeries

    Unleashing the power of artificial intelligence for climate action in industrial markets

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    Artificial Intelligence (AI) is a game-changing capability in industrial markets that can accelerate humanity's race against climate change. Positioned in a resource-hungry and pollution-intensive industry, this study explores AI-powered climate service innovation capabilities and their overall effects. The study develops and validates an AI model, identifying three primary dimensions and nine subdimensions. Based on a dataset in the fast fashion industry, the findings show that the AI-powered climate service innovation capabilities significantly influence both environmental and market performance, in which environmental performance acts as a partial mediator. Specifically, the results identify the key elements of an AI-informed framework for climate action and show how this can be used to develop a range of mitigation, adaptation and resilience initiatives in response to climate change

    Graduate Catalog of Studies, 2023-2024

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    Forschungsbericht / Hochschule Mittweida

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    Modern computing: Vision and challenges

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    Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress

    Research Assessment Exercise : Report 2023 : International evaluation of research at the University of Vaasa

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    The University of Vaasa is a business-oriented and multidisciplinary science university established in 1968. The university’s strategy focuses on three areas of research: management and change, finance and economic decision-making, and energy and sustainable development. It highlights multidisciplinary research with strong disciplinary knowledge integrated through research platforms to support solving important global challenges. The core mission is to advance new knowledge and to “Energise Business and Society.” The University of Vaasa has a core faculty of 584 and 5,203 students with 190 international students and 296 PhD students. International accreditations, unique research infrastructure, and partnerships with global businesses and organisations make the University of Vaasa a trusted and valued partner within both regional and international innovation ecosystems. The Universities Act (Section 87. Evaluation (Amendment 1302/2013)) stipulates that universities must evaluate their research activities. In line with the strategy of the University of Vaasa, the university evaluates its research activities every five years in order to strengthen the quality of the research internationally, to advance academic and societal impacts of the research, and to further develop the research activities and environment. The previous research evaluations were carried out in 2010 and in 2015. This third research evaluation covered research activities from 2015 to 2020. Diversity, meaningfulness, and focus on future were important features of the research assessment exercise (RAE). The RAE was carried out as a multilevel and multidimensional evaluation targeting research environment, research cooperation and funding, publications, and scientific activities including societal impact. In addition to research groups and the university as a whole, it focused on schools and platforms. The evaluation material and the expert panels’ interviews thus covered three different levels of the university organisation. A Steering Committee consisting of members of the Research Council of the University of Vaasa (2021–2023) was nominated to support and guide the research evaluation. The RAE Univaasa 2022 followed practices of responsible evaluation. Engagement of the research units and researchers was an important aspect of the evaluation process. The evaluation team designed, organised, and implemented the different phases of the RAE in collaboration with the heads of the schools, platforms, and research group leaders. All evaluated units got basic summaries of their research output and bibliometric reports before preparing their self-evaluation reports. The material and the bibliometric reports aimed to provide the units tools for self-reflection and further development of their research. In addition to the CWTS analysis prepared by Leiden University, SciVal analyses on Scopus publications were performed for each unit by the Tritonia Academic Library. Bibliometric analyses also included results from AI-analysis of the themes of open access publications (OSUVA, 2018-2021). The external evaluation was performed by five panels of independent scientific experts. Four of the panels were discipline-specific (based on the school’s disciplines). These school-based panels were asked to provide written comments by comparing each research group’s research to the international and national level of research in the respective field. Based on the research group level evaluations, each school-based panel was asked to offer an overall assessment of the school’s research activities and quality of research. A separate team of the panellists were responsible for the assessment of the three research platforms. The University Panel, consisting of the panel chair and the chairs of the school-based panels, was asked to provide an integrating evaluation of the quality of research activities and environment at the University of Vaasa and to offer recommendations for how the university should develop its research. The results of the assessment and the expert panels’ reports and recommendations will have an effect on the strategic development of research within the university from 2023 onwards. Evaluation indicated that several research groups are currently at a high international level. The areas represented at the University of Vaasa are ones where excellent researchers have many possibilities. The societal impact of research and the industrial cooperation with regional businesses and also the wider interaction with the society work very well at the University of Vaasa. The flexibility of the cooperation seems to be far greater than in many other universities. Many of the projects contribute clearly to the research and the education of the university and provide useful information for the companies the research groups partner with. However, building international research capacity will remain challenging. This is partly a product of the size of the University and the research groups, most of which are relatively small and rely on a small number of high performing professors. The international experts gave several recommendations on how to improve the quality of research at the University of Vaasa. Externally funded projects that support the university’s aim to become an international research university should be encouraged. The experts suggested that the strategy is augmented with more concrete goals on the research focus, quality, and volume. The implementation plan should specify at some level what would be the areas, or modes of operation, in which the university wants to excel, and how this excellence is going to be measured. Recruitment should be prioritised based on the strategy of the university and the availability of excellent people. The university also should consider using international Professors of Practice and inviting more international Visiting Professorships. Moreover, increased possibilities for faculty and PhD students to engage in international activities could boost production of top-level research. The panels also assessed the role of the evaluated units and the internal cooperation within the university. The research groups vary a lot in their size, but also in their cohesion. The panellists saw that in terms of organisation, some groups were tight clusters, while other groups did not seem to have a clear structure. They considered that it would be very useful if each researcher would have an intellectual home base at the university. The panellists perceived the relationship between research groups and platforms to be unclear. The model was considered complicated relative to the size of the schools and the university. The panellists suggested reviewing the role and form of the platforms. In particular, the panellists suggested that in relation to the service of schools and their research groups, the platforms should have a supporting role, instead of trying to form research identities of their own. However, the panellists also considered that there is no definite need to have all the platforms operate in the same way
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