Decentralising resource management in operating systems

This dissertation explores operating system mechanisms to allow resource-aware applications to be involved in the process of managing resources under the premise that these applications (1) potentially have some (implicit) notion of their future resource demands and (2) can adapt their resource demands. The general idea is to provide feedback to resource-aware applications so that they can proactively participate in the management of resources. This approach has the benefit that resource management policies can be removed from central entities and the operating system has only to provide mechanism. Furthermore, in contrast to centralised approaches, application specific features can be more easily exploited. To achieve this aim, I propose to deploy a microeconomic theory, namely congestion or shadow pricing, which has recently received attention for managing congestion in communication networks. Applications are charged based on the potential "damage" they cause to other consumers by using resources. Consumers interpret these congestion charges as feedback signals which they use to adjust their resource consumption. It can be shown theoretically that such a system with consumers merely acting in their own self-interest will converge to a social optimum. This dissertation focuses on the operating system mechanisms required to decentralise resource management this way. In particular it identifies four mechanisms: pricing & charging, credit accounting, resource usage accounting, and multiplexing. While the latter two are mechanisms generally required for the accurate management of resources, pricing & charging and credit accounting present novel mechanisms. It is argued that congestion prices are the correct economic model in this context and provide appropriate feedback to applications. The credit accounting mechanism is necessary to ensure the overall stability of the system by assigning value to credits

Advances in Modeling of Fluid Dynamics

This book contains twelve chapters detailing significant advances and applications in fluid dynamics modeling with focus on biomedical, bioengineering, chemical, civil and environmental engineering, aeronautics, astronautics, and automotive. We hope this book can be a useful resource to scientists and engineers who are interested in fundamentals and applications of fluid dynamics

Women in Artificial intelligence (AI)

This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI

Bifurcation analysis of the Topp model

In this paper, we study the 3-dimensional Topp model for the dynamicsof diabetes. We show that for suitable parameter values an equilibrium of this modelbifurcates through a Hopf-saddle-node bifurcation. Numerical analysis suggests thatnear this point Shilnikov homoclinic orbits exist. In addition, chaotic attractors arisethrough period doubling cascades of limit cycles.Keywords Dynamics of diabetes · Topp model · Reduced planar quartic Toppsystem · Singular point · Limit cycle · Hopf-saddle-node bifurcation · Perioddoubling bifurcation · Shilnikov homoclinic orbit · Chao

Dynamical systems : mechatronics and life sciences

Proceedings of the 13th Conference „Dynamical Systems - Theory and Applications" summarize 164 and the Springer Proceedings summarize 60 best papers of university teachers and students, researchers and engineers from whole the world. The papers were chosen by the International Scientific Committee from 315 papers submitted to the conference. The reader thus obtains an overview of the recent developments of dynamical systems and can study the most progressive tendencies in this field of science

Using knowledge elicitation techniques to establish a baseline of quantitative measures of computational thinking skill acquisition among university computer science students.

The purpose of this study was to establish a baseline of quantitative measures of computational thinking skill acquisition as an aid in evaluating student outcomes for programming competency. Proxy measures for the desired skill levels were identified that reliably differentiate the conceptual representations of computer science students most likely, from those least likely, to have attained the desired level of programming skill. Insights about the development of computational thinking skills across the degree program were gained by analyzing variances between these proxy measures and the conceptual representations of cross-sections of participating students partitioned by levels of coursework attainment, programming experience, and academic performance. Going forward, similar measures can provide a basis for quantitative assessment of individual attainment of the desired learning outcome. The voluntary participants for this study were students enrolled in selected undergraduate computer science courses at the University. Their conceptual representations regarding programming concepts were elicited with a repeated, open card sort task and stimuli set as used for prior studies of computer science education. A total of 135 students participated, with 124 of these providing 296 card sorts. Differences between card sorts were quantified with the edit distance metric which provided a basis for statistical analysis. Card sorts from cross-sections of participants were compared and contrasted using graph theory algorithms to calculate measures of average segment length of minimum spanning trees (orthogonality), to identify clusters of highly similar card sorts, and to reduce clusters down to individual exemplar card sorts. Variances in distance between the card sorts of cross-sections of participants and the identified exemplars were analyzed with one-way ANOVAs to evaluate differences in development of conceptual representations relative to coursework attainment and programming experience. Findings Collections of structurally similar card sorts were found to align with categorizations identified in earlier studies of computer science education. A logistic regression identified two exemplar sorts representing deep factor categorizations that reliably predicted those participants most, and least likely to have attained the desired level of programming skill. Measures of proximal distance between participants' card sorts and these two exemplars were found to decrease, indicating greater similarity, as students attained progressive coursework milestones. This finding suggests that proximal distances to exemplars of common categorizations for this stimuli set can effectively differentiate conceptual development levels of students between, as well as within, cross-sections selected by achievement of coursework milestones. Measures of proximal distances to one exemplar of deep factor categorization were found to increase, indicating less similarity, as participants’ levels of programming experience increased. This finding was contrary to the theoretical framework for skill acquisition. Further analysis found that variances in experience level as captured by the study instrument were not equally distributed among the cross-sections. The preponderance of participants reporting greater levels of experience were degree majors not required to enroll in the courses most likely to develop that specific conceptualization. Therefore, for this deep factor categorization, instruction was found to have a greater influence on conceptual development than programming experience. However, it is possible that other categorizations, such as those related to software engineering technology, may be found to be more influenced by experience. The orthogonality of participant card sorts was found to increase with each category of increase in academic performance, as in keeping with prior studies. Orthogonality also increased with greater levels of programming experience as expected by the theoretical framework. However, since experience was not equally distributed across categories of coursework achievement, the relationship between the orthogonality of participant card sorts and milestones of coursework achievement was not found to be statistically significant overall. Based on the findings, the researcher concludes that a baseline of quantitative measures of computational thinking skills can be constructed based upon categorizations of elicited conceptual representations and associated exemplar card sorts. Eleven categorizations identified in a prior study of computer science seniors appear to represent reasonable expectations for deep factor categorizations. Follow up research is recommended (a) to identify for each categorization the exemplar card sorts that may be specific to different degree majors, and (b) to identify which categorizations may be more influenced by programming experience than by instruction. Given an elicitation tool that prompts for the specific categorizations and a set of exemplar representations as proposed above, instructional programs can establish expected ranges of proximal distance measures to specific exemplars. These exemplars should be selected according to particular categorizations, degree majors, and coursework milestones. These differentiated measures will serve as evidence that students are meeting the instructional program learning objective for developing competency in the design and implementation of computer-based solutions

Examination of existing facilities management approaches to climate change and future directions

It is widely accepted that human activities have contributed to changing the world’s climate and that the pace of this change is ever increasing. Two approaches are being promoted by the international community to address the issue of climate change (1) Mitigation, seeking to reduce the amount of CO2; (2) Adaptation, which seeks to alter the way humankind live and work in response to the changing climate. Whilst facilities managers and their organisations have prioritised mitigation action, there is less evidence to suggest that they are addressing the implications that a changing climate may have on the demands being placed on their organisation’s hard and soft facilities (adaptation). This paper reports findings from a case study and questionnaire survey to ascertain the present approach taken by facilities managers to address mitigation and adaptation, their respective drivers, their view on climate change and their environmental inclination. It concludes that the facilities manager's approach to climate change is derived by a combination of factors; namely a) Organisation approach to climate change b) Legislation and c) the facilities mangers perception of the risks posed by future climate change and of the use of risk assessment methods and climate change projection data. The study concludes that the prevailing measure for addressing climate change impacts is reactive in nature, taking the form of Disaster Recovery and Business Continuity Planning. The practical implication of the work is in the realization that mitigation, being quantifiable and legislative driven, is viewed as a strategic issue and of importance to an organisations Corporate Social Responsibility agenda which can be planned over the longer term (10-20 yrs). Adaptation on the other hand is measured through successful survival, increased resilience and adaptive capacity (absence of quantitative performance target), each of which are viewed as short term operational issues and as such adaptation struggles to find strategic importance. If organisations are to adapt to inevitable climate change then this situation needs to change