Функционално и императивно реактивно програмирање употребом генерализације монаде наставка у програмском језику C++.

Постоји велики број проблема који захтевају писање програмских система који имају компоненте које се извршавају међусобно асинхроно једне од других...There is a big class of problems that require software systems with asynchronously executed components..

Automation for network security configuration: state of the art and research trends

The size and complexity of modern computer networks are progressively increasing, as a consequence of novel architectural paradigms such as the Internet of Things and network virtualization. Consequently, a manual orchestration and configuration of network security functions is no more feasible, in an environment where cyber attacks can dramatically exploit breaches related to any minimum configuration error. A new frontier is then the introduction of automation in network security configuration, i.e., automatically designing the architecture of security services and the configurations of network security functions, such as firewalls, VPN gateways, etc. This opportunity has been enabled by modern computer networks technologies, such as virtualization. In view of these considerations, the motivations for the introduction of automation in network security configuration are first introduced, alongside with the key automation enablers. Then, the current state of the art in this context is surveyed, focusing on both the achieved improvements and the current limitations. Finally, possible future trends in the field are illustrated

Generalized asset integrity games

Generalized assets represent a class of multi-scale adaptive state-transition systems with domain-oblivious performance criteria. The governance of such assets must proceed without exact specifications, objectives, or constraints. Decision making must rapidly scale in the presence of uncertainty, complexity, and intelligent adversaries. This thesis formulates an architecture for generalized asset planning. Assets are modelled as dynamical graph structures which admit topological performance indicators, such as dependability, resilience, and efficiency. These metrics are used to construct robust model configurations. A normalized compression distance (NCD) is computed between a given active/live asset model and a reference configuration to produce an integrity score. The utility derived from the asset is monotonically proportional to this integrity score, which represents the proximity to ideal conditions. The present work considers the situation between an asset manager and an intelligent adversary, who act within a stochastic environment to control the integrity state of the asset. A generalized asset integrity game engine (GAIGE) is developed, which implements anytime algorithms to solve a stochastically perturbed two-player zero-sum game. The resulting planning strategies seek to stabilize deviations from minimax trajectories of the integrity score. Results demonstrate the performance and scalability of the GAIGE. This approach represents a first-step towards domain-oblivious architectures for complex asset governance and anytime planning

Unmasking The Language Of Science Through Textual Analyses On Biomedical Preprints And Published Papers

Scientific communication is essential for science as it enables the field to grow. This task is often accomplished through a written form such as preprints and published papers. We can obtain a high-level understanding of science and how scientific trends adapt over time by analyzing these resources. This thesis focuses on conducting multiple analyses using biomedical preprints and published papers. In Chapter 2, we explore the language contained within preprints and examine how this language changes due to the peer-review process. We find that token differences between published papers and preprints are stylistically based, suggesting that peer-review results in modest textual changes. We also discovered that preprints are eventually published and adopted quickly within the life science community. Chapter 3 investigates how biomedical terms and tokens change their meaning and usage through time. We show that multiple machine learning models can correct for the latent variation contained within the biomedical text. Also, we provide the scientific community with a listing of over 43,000 potential change points. Tokens with notable changepoints such as “sars” and “cas9” appear within our listing, providing some validation for our approach. In Chapter 4, we use the weak supervision paradigm to examine the possibility of speeding up the labeling function generation process for multiple biomedical relationship types. We found that the language used to describe a biomedical relationship is often distinct, leading to a modest performance in terms of transferability. An exception to this trend is Compound-binds-Gene and Gene-interacts-Gene relationship types

Computational Approaches to Generating Diverse Enzyme Panels

Ph. D. ThesisMotivation Enzymes are complex macromolecules crucial to life on earth. From bacteria to human beings, all organisms use enzymes to catalyse the many thousands of chemical reactions occurring in their cells. Enzyme functions are so diverse that the use of enzymes in industries like pharmaceuticals and agriculture has gained popularity over recent years as ”biocatalysts”. Unfortunately, the confident laboratory-based characterisation of enzyme function has lagged behind a massive increase in sequencing data, slowing down initiatives that look to use biocatalysts as part of their chemical processes. Computational methods for identifying biocatalysts do exist, but often falter due to the complexity of enzymes and sequence bias, leaving much of the catalytic space of enzymes and their families undiscovered. This thesis has two major themes: the development of in silico approaches for curating diverse panels of novel enzyme sequences for experimental characterisation, and of tooling that integrates in silico panel creation and in vitro enzyme characterisation into a unified and iterative framework. Contributions of this thesis The contributions of this thesis can be divided into the two larger themes, starting with the diverse panel selection of sequences from an enzyme family: • A novel type of protein network based on patterns of coevolving residues that can be used to identify functionally-interesting groupings in enzyme families. • The automatic sampling of functionally diverse subsets of enzyme sequences by solving the maximum diversity problem. - i - • A study into the viability of artificially increasing enzyme family diversity through neural networks-based generation of synthetic sequences. The second theme, which deals with built tools for bridging the gap between the in silico and in vitro side of enzyme family exploration: • A platform that integrates the panel selection process and resulting characterisation data to promote an iterative approach to exploring enzyme families. • A repository for storing the metadata generated by the major steps of characterisation assays in the lab.EPSRC and Prozomix Limite

Assumption management in model-based systems engineering: an aircraft design perspective.

Early design of complex systems is characterised by significant uncertainty due to lack of knowledge, which can impede the design process. In order to proceed with the latter, assumptions are typically introduced to fill knowledge gaps. However, the uncertainty inherent in the assumptions constitutes a risk to be mitigated. In fact, assumptions can negatively impact the system if they turn out to be invalid, such as causing system failure, violation of requirements, or budget and schedule overruns. Within this context, the aim of this research was to develop a computational approach to support assumption management in model-based systems engineering, with an explicit consideration of the uncertainty in assumptions. To achieve the research aim, the objectives were to: (1) devise methods to enable assumption management in a model-based design environment; and (2) devise methods to manage risk of change due to invalid assumptions, with an explicit consideration of both assumptions and margins. The scope was limited to the early stages of aircraft design. To evaluate this research, a demonstration was performed based on two use cases to assess whether the methods work as intended. The developed methods were demonstrated to industry experts in order to obtain feedback on expected usefulness in practice, thus assessing the impact of this research. The experts concluded that the proposed methods are innovative, useful and relevant to industry, where these methods can lead to: (i) fewer undesired iterations, due to earlier identification and management of risks associated with assumptions; and (ii) a better margin balance, due to timely and interactive margin revision. Future work includes further industrial evaluation, extending the research scope and studying the scalability and associated costs of the proposed methods.PhD in Aerospac

Design Transactions

Design Transactions presents the outcome of new research to emerge from ‘Innochain’, a consortium of six leading European architectural and engineering-focused institutions and their industry partners. The book presents new advances in digital design tooling that challenge established building cultures and systems. It offers new sustainable and materially smart design solutions with a strong focus on changing the way the industry thinks, designs, and builds our physical environment. Divided into sections exploring communication, simulation and materialisation, Design Transactions explores digital and physical prototyping and testing that challenges the traditional linear construction methods of incremental refinement. This novel research investigates ‘the digital chain’ between phases as an opportunity for extended interdisciplinary design collaboration. The highly illustrated book features work from 15 early-stage researchers alongside chapters from world-leading industry collaborators and academics

Design Transactions: Rethinking Information for a New Material Age

Design Transactions presents the outcome of new research to emerge from ‘Innochain’, a consortium of six leading European architectural and engineering-focused institutions and their industry partners. The book presents new advances in digital design tooling that challenge established building cultures and systems. It offers new sustainable and materially smart design solutions with a strong focus on changing the way the industry thinks, designs, and builds our physical environment. Divided into sections exploring communication, simulation and materialisation, Design Transactions explores digital and physical prototyping and testing that challenges the traditional linear construction methods of incremental refinement. This novel research investigates ‘the digital chain’ between phases as an opportunity for extended interdisciplinary design collaboration. The highly illustrated book features work from 15 early-stage researchers alongside chapters from world-leading industry collaborators and academics