The Inter-cloud meta-scheduling

Inter-cloud is a recently emerging approach that expands cloud elasticity. By facilitating an adaptable setting, it purposes at the realization of a scalable resource provisioning that enables a diversity of cloud user requirements to be handled efficiently. This study’s contribution is in the inter-cloud performance optimization of job executions using metascheduling concepts. This includes the development of the inter-cloud meta-scheduling (ICMS) framework, the ICMS optimal schemes and the SimIC toolkit. The ICMS model is an architectural strategy for managing and scheduling user services in virtualized dynamically inter-linked clouds. This is achieved by the development of a model that includes a set of algorithms, namely the Service-Request, Service-Distribution, Service-Availability and Service-Allocation algorithms. These along with resource management optimal schemes offer the novel functionalities of the ICMS where the message exchanging implements the job distributions method, the VM deployment offers the VM management features and the local resource management system details the management of the local cloud schedulers. The generated system offers great flexibility by facilitating a lightweight resource management methodology while at the same time handling the heterogeneity of different clouds through advanced service level agreement coordination. Experimental results are productive as the proposed ICMS model achieves enhancement of the performance of service distribution for a variety of criteria such as service execution times, makespan, turnaround times, utilization levels and energy consumption rates for various inter-cloud entities, e.g. users, hosts and VMs. For example, ICMS optimizes the performance of a non-meta-brokering inter-cloud by 3%, while ICMS with full optimal schemes achieves 9% optimization for the same configurations. The whole experimental platform is implemented into the inter-cloud Simulation toolkit (SimIC) developed by the author, which is a discrete event simulation framework

Learning heterogeneous subgraph representations for team discovery

The team discovery task is concerned with finding a group of experts from a collaboration network who would collectively cover a desirable set of skills. Most prior work for team discovery either adopt graph-based or neural mapping approaches. Graph-based approaches are computationally intractable often leading to sub-optimal team selection. Neural mapping approaches have better performance, however, are still limited as they learn individual representations for skills and experts and are often prone to overfitting given the sparsity of collaboration networks. Thus, we define the team discovery task as one of learning subgraph representations from a heterogeneous collaboration network where the subgraphs represent teams which are then used to identify relevant teams for a given set of skills. As such, our approach captures local (node interactions with each team) and global (subgraph interactions between teams) characteristics of the representation network and allows us to easily map between any homogeneous and heterogeneous subgraphs in the network to effectively discover teams. Our experiments over two real-world datasets from different domains, namely DBLP bibliographic dataset with 10,647 papers and IMDB with 4882 movies, illustrate that our approach outperforms the state-of-the-art baselines on a range of ranking and quality metrics. More specifically, in terms of ranking metrics, we are superior to the best baseline by approximately 15 % on the DBLP dataset and by approximately 20 % on the IMDB dataset. Further, our findings illustrate that our approach consistently shows a robust performance improvement over the baselines

Graphlet Correlations for Network Comparison and Modelling: World Trade Network Example

We propose methods on two fundamental graph theoretic problems: (1) network comparison, and (2) network modelling. Our methods are applied to five real-world network types, with an emphasis on world trade networks (WTNs), which we choose due to the world's current economic crisis. Finding topological similarities of complex networks is computationally intractable due to NP-Completeness of the subgraph isomorphism problem. Hence, simple heuristics have been used for this purpose. The most sophisticated heuristics are based on graph spectra and small subnetworks including graphlets. Among these, graphlets are preferred since spectra do not provide a direct real-world interpretation of network structure. However, current graphlet-based techniques can be improved. We improve graphlet-based heuristics by defining a new network topology descriptor, Graphlet Correlation Matrix (GCM), which eliminates all redundancies and quantifies the dependencies in graphlet properties. Then, we introduce a new network distance measure, Graphlet Correlation Distance (GCD), that compares GCMs of two networks. We show that GCD has the best network classification performance, is highly noise-tolerant, and is computationally efficient. Using this methodology, we highlight a three-layer organization in the WTNs: core, broker, and periphery. Furthermore, we uncover the link between the dynamic changes in oil price and trade network topology. Network models should shed light on the rules governing the formation of real networks. Using GCD, we identify models that fit five real-world network types. However, none of these standard network models fit WTNs. Hence, we introduce two new network models: one that mimics the Gravity Model of Trade, and the other that mimics brokerage / peripheral positioning of a country in WTN. Also, we show that economic wealth indicators of a country are predictive of its future brokerage position. Finally, we use exponential-family random graph modelling approach to build a generic framework that enables modelling based on any graphlet property.Open Acces

Networks of innovation: measuring, modelling and enhancing innovation in surgery

The rate of innovation occurring in surgery is beyond our systemic capacity to quantify, with several methodological and practical challenges. The existing paucity of surgical innovation metrics presents a global healthcare problem especially as surgical innovations become increasingly costlier at a time when healthcare provision is experiencing a radical transformation driven by pressures to reduce costs, an ageing population with ever-increasing healthcare needs and patients with growing expectations. This thesis aims to devise a novel, quantitative, network-based framework that will permit modelling and measuring surgical innovation to add the most value to patient care. It involves the systematic, graphical and analytical assessment of surgical innovation in a way that has never been done before. This is based on successful models previously applied in the industry with advanced analytical techniques derived from social science (network analysis). In doing so, it offers an exciting new perspective and opportunity for understanding how the innovation process originates and evolves in surgery and how it can be measured in terms of value and virality, a priority for the NHS, RCS, Imperial and the wider surgical community. The ability to measure value and rank innovations is expected to play a fundamental role in guiding policy, strategically direct surgical research funding, and uncover innovation barriers and catalysts. This will ensure participation in the forefront of novel surgical technology and lay the scientific foundations for the development of improved healthcare models and services to enhance the quality of healthcare delivered.Open Acces

Imitation Learning for Swarm Control using Variational Inference

Swarms are groups of robots that can coordinate, cooperate, and communicate to achieve tasks that may be impossible for a single robot. These systems exhibit complex dynamical behavior, similar to those observed in physics, neuroscience, finance, biology, social and communication networks, etc. For instance, in Biology, schools of fish, swarm of bacteria, colony of termites exhibit flocking behavior to achieve simple and complex tasks. Modeling the dynamics of flocking in animals is challenging as we usually do not have full knowledge of the dynamics of the system and how individual agent interact. The environment of swarms is also very noisy and chaotic. We usually only can observe the individual trajectories of the agents. This work presents a technique to learn how to discover and understand the underlying governing dynamics of these systems and how they interact from observation data alone using variational inference in an unsupervised manner. This is done by modeling the observed system dynamics as graphs and reconstructing the dynamics using variational autoencoders through multiple message passing operations in the encoder and decoder. By achieving this, we can apply our understanding of the complex behavior of swarm of animals to robotic systems to imitate flocking behavior of animals and perform decentralized control of robotic swarms. The approach relies on data-driven model discovery to learn local decentralized controllers that mimic the motion constraints and policies of animal flocks. To verify and validate this technique, experiments were done on observations from schools of fish and synthetic data from boids model

Impact of BIM/LEAN on the interaction of construction project design teams

Tesis por compendio[ES] Los equipos de diseño de los proyectos de construcción están compuestos por diferentes interesados; esto podría dificultar las interacciones. Las metodologías BIM y Lean tienen un impacto positivo en los proyectos de construcción. Además, hay pruebas de la aplicación conjunta de BIM y Lean; sin embargo, se desconoce la relación empírica entre las prácticas Lean y los usos de BIM en la fase de diseño. Tampoco existe una comprensión más profunda de los fenómenos sociales que se generan entre los equipos de diseño cuando se aplican las metodologías de gestión BIM-Lean. Por lo tanto, el objetivo de esta investigación es entender el impacto de las prácticas de gestión de diseño Lean (LDM) y los usos BIM en la interacción de los equipos de diseño de los proyectos de construcción. El método de investigación tiene dos fases: 1) la creación de herramientas para evaluar el nivel de aplicación de las prácticas LDM y los usos BIM, y para comprender las interacciones en un equipo de diseño; y 2) el análisis de las relaciones entre BIM, Lean y la interacción, basado en información empírica de proyectos de construcción en fase de diseño. Los resultados presentan un instrumento de evaluación de usos del BIM y un cuestionario de prácticas de LDM para medir la gestión del diseño, y un método para comprender los diferentes tipos de interacción en un equipo de diseño. Basados en los datos de 64 proyectos, un análisis chi cuadrado reveló 33 relaciones empíricas entre los usos del BIM y las prácticas LDM; además, la aplicación de los usos del BIM implica una mayor aplicación de las prácticas LDM. El proyecto que aplica la gestión BIM-Lean logra numerosas interacciones en su equipo de diseño; flujos de información transparentes, ordenados y estandarizados; un entorno de colaboración, confianza y aprendizaje; y una gestión del compromiso. Todos estos elementos de interacción no son visibles en el proyecto, en el que no se aplicó la gestión BIM-lean.[CAT] Els equips de diseny dels projectes de construcción están compostos per diferents interesats; açó podría dificultar les interaccions. Les metodologies BIM i Lean tenen un impacte positiu en els projectes de construcció. A més, ni hi ha proves de l'aplicació conjunta de BIM i Lean; no obstant, es desconeix la relació empírica entre practiques Lean i els usos de BIM en fase de diseny. Tampoc existix una comprensió mes profunda dels fenómens socials que es generen entre els equips de diseny quan s'apliquen les metodologies de gestió BIM-Lean. Per tant, l'objectiu d'esta investigació es entendre l'impacte de les practiques de gestió de diseny Lean (LDM) i els usos BIM en l'interacció dels equips de diseny dels projectes de construcción. El métode de investigació te dos fases: 1) la creació de ferramentes per a evaluar el nivell d'aplicació de les practiques LDM i els usos BIM, i per a comprendre les interaccions en un equip de diseny; i 2) l'análisis de les relacions entre BIM, Lean i la interacció, basades en informació empírica de projectes de construcció en fase de diseny. Els resultats presenten un instrument d'evaluació d'usos del BIM i un questionari de practiques de LDM per a mesurar la gestió del diseny, i un método per a comprendre els diferents tipos d'interacció en un equip de diseny. Basades en les dades de 64 projectes, un análisis chi cuadrado va revelar 33 relacions empíricas entre els usos del BIM i les práctiques LDM; a més, l¿aplicació dels usos del BIM implica una major aplicació de les práctiques LDM. El projecte que aplica la gestió BIM-Lean obté nombroses interaccions en el seu equip de diseny; fluxes d'informació transparents, ordenats i estandarizats; un entorn de colaboració, confiança i aprenentatge; i una gestió del compromis. Tots estos elements d'interacció no son visibles en el projecte, en el que no es va aplicar la gestió BIM-lean.[EN] Design teams of construction projects are composed of different stakeholders; this fact could make the interactions difficult. BIM and Lean methodologies have a positive impact on construction projects. Besides, there is evidence of the combined implementation of BIM and Lean; however, it is not known the empirical relationship between Lean practices and BIM uses in the design phase. Also, there is not a deeper understanding of the social phenomena that are generated among design teams when BIM-Lean management methodologies are implemented. Therefore, the objective of this research is to understand the impact of Lean design management (LDM) practices, and BIM uses in the interaction of construction project design teams. The research method has two phases: (1) the creation of tools to assess the level of implementation of LDM practices and BIM uses and to understand the interactions in a design team; and (2) the relationship analyses between BIM, Lean, and interaction, based on empirical information from construction projects in the design phase. The results present a BIM uses assessment tool and an LDM practices questionnaire to measure the design management and a method to understand the different types of interaction in a design team. Based on data from 64 projects, a chi-square analysis revealed 33 empirical relationships between BIM uses and LDM practices; also, the application of BIM uses implies a greater application of LDM practices. The project that applies BIM-Lean management achieves many interactions among its design team; transparent, orderly, and standardized information flows; a collaborative, trust, and learning environment; and commitment management. All these interaction elements are not visible in the project, where BIM-lean management was not applied.Herrera Valencia, RF. (2020). Impact of BIM/LEAN on the interaction of construction project design teams [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/158718TESISCompendi

Graph neural networks for seizure discrimination based on electroencephalogram analysis

Este estudio presenta una investigación sobre la clasificación de Convulsiones Psicógenas No Epilépticas (PNES) y Convulsiones Epilépticas (ES) utilizando datos de EEG y Redes Neuronales de Grafos (GNN). El modelo propuesto muestra un rendimiento destacable, superando los resultados previos del estado del arte y logrando una precisión notable en la clasificación ternaria. Mediante el uso de una arquitectura GNN, el modelo distingue de manera efectiva entre PNES y ES con una precisión del 92.9%. Además, al emplear la validación cruzada "Leave One Group Out", el modelo logra una precisión aún mayor del 97.58%, superando la precisión más alta reportada en el estado del arte de 94.4%. Asimismo, al ampliar la clasificación para incluir a pacientes sanos, el modelo alcanza una precisión del 91.12%, superando la mejor precisión conocida del estado del arte de 85.7%. Estos hallazgos resaltan el potencial del modelo para clasificar y diferenciar de manera precisa estas condiciones médicas utilizando datos de EEG. El trabajo futuro incluye la exploración de biomarcadores para la clasificación binaria utilizando las capacidades de explicabilidad del modelo, contribuyendo al desarrollo de herramientas de diagnóstico objetivas y estrategias de tratamiento personalizadas. Además, este estudio compara el rendimiento, las metodologías y los conjuntos de datos de estudios similares del estado del arte, proporcionando una visión general completa de la investigación en clasificación de convulsiones. En conclusión, este estudio demuestra el éxito del modelo propuesto en la clasificación de PNES y ES, allanando el camino para futuros avances en el campo y beneficiando a pacientes y profesionales de la salud en el diagnóstico y tratamiento.This study presents a research investigation on the classification of Psychogenic Non-Epileptic Seizures (PNES) and Epileptic Seizures (ES) using EEG data and Graph Neural Networks (GNN). The proposed model demonstrates outstanding performance, surpassing previous state-of-the-art results and achieving remarkable accuracy in ternary classification. By utilizing a GNN architecture, the model effectively distinguishes between PNES and ES with an accuracy of 92.9%. Moreover, when employing Leave One Group Out crossvalidation, the model achieves an even higher accuracy of 97.58%, outperforming the highest reported state-of-the-art accuracy of 94.4%. Furthermore, by extending the classification to include healthy patients, the model achieves an accuracy of 91.12%, surpassing the bestknown state-of-the-art accuracy of 85.7%. These findings highlight the potential of the model in accurately classifying and differentiating these medical conditions using EEG data. Future work includes the exploration of biomarkers for binary classification using the model's explainability capabilities, contributing to the development of objective diagnostic tools and personalized treatment strategies. Additionally, this study compares the performance, methodologies, and datasets of similar studies from the state-of-the-art, providing a comprehensive overview of seizure classification research. In conclusion, this study demonstrates the success of the proposed model in classifying PNES and ES, paving the way for further advancements in the field and benefiting patients and healthcare practitioners in diagnosis and treatment

High performance network function virtualization for user-oriented services

The Network Function Virtualization (NFV) paradigm proposes to transform those network functions today running on dedicated and often closed appliances (e.g., firewall, wan accelerator) into pure software images, called Virtual Network Functions (VNFs), which can be consolidated and executed on high-volume standard servers. In this context, this dissertation focuses on the possibility of enabling each single end user (and not only network operators) to set up network services by means of NFV, allowing him to custoimize the set of services that are active on his Internet connection. This goal mainly requires to address flexibility and performance issues. Regarding to the former, it is important: (i) to support services including both network (e.g., firewall) and cloud (e.g., storage server) applications; (ii) to allow the user to define the service with an intuitive and high-level abstraction, hiding infrastructure-layer details. Instead, with respect to performance, multiple software-based services operating on the user's traffic should not introduce penalties in the user’s Internet experience. This dissertation solves the above issues by proposing a number of improvements in the context of Network Function Virtualization, both in terms of high level models and architectures to define and instantiate network services, and in terms of mechanisms to efficiently interconnect VNFs. Experimental results demonstrate that the goal of allowing end users to deploy services operating on their own traffic is feasible without impacting the Internet experience