Quantum Secret Sharing with Graph States

Revised Selected Papers - http://www.memics.cz/2012/International audienceWe study the graph-state-based quantum secret sharing protocols [24,17] which are not only very promising in terms of physical implementation, but also resource efficient since every player's share is composed of a single qubit. The threshold of a graph-state-based protocol admits a lower bound: for any graph of order n, the threshold of the corresponding n-player protocol is at least 0.506n. Regarding the upper bound, lexicographic product of the C 5 graph (cycle of size 5) are known to provide n-player protocols which threshold is n − n 0.68. Using Paley graphs we improve this bound to n − n 0.71. Moreover, using probabilistic methods, we prove the existence of graphs which associated threshold is at most 0.811n. Albeit non-constructive, probabilistic methods permit to prove that a random graph G of order n has a threshold at most 0.811n with high probability. However, verifying that the threshold of a given graph is acually smaller than 0.811n is hard since we prove that the corresponding decision problem is NP-Complete. These results are mainly based on the graphical characterization of the graph-state-based secret sharing properties, in particular we point out strong connections with domination with parity constraints

Reshare an Operational Ontology Framework for Research Modeling, Combining and Sharing

Scientists always face difficulties dealing with disjointed information. There is a need for a standardized and robust way to represent and exchange knowledge. Ontology has been widely used for this purpose. However, since research involves semantics and operations, we need to conceptualize both of them. In this thesis, we propose ReShare to provide a solution for this problem. Maximizing utilization while preserving the semantics is one of the main challenges when the heterogeneous knowledge is combined. Therefore, operational annotations were designed to allow generic object modeling, binding and representation. Furthermore, a test bed is developed and preliminary results are presented to show the usefulness and robustness of our approach. Moreover, two aggregation techniques for fusing ontology matchers are investigated as an initial work for building an algorithm which converts descriptive ontologies into operational ones

Model counting for reactive systems

Model counting is the problem of computing the number of solutions for a logical formula. In the last few years, it has been primarily studied for propositional logic, and has been shown to be useful in many applications. In planning, for example, propositional model counting has been used to compute the robustness of a plan in an incomplete domain. In information-flow control, model counting has been applied to measure the amount of information leaked by a security-critical system. In this thesis, we introduce the model counting problem for linear-time properties, and show its applications in formal verification. In the same way propositional model counting generalizes the satisfiability problem for propositional logic, counting models for linear-time properties generalizes the emptiness problem for languages over infinite words to one that asks for the number of words in a language. The model counting problem, thus, provides a foundation for quantitative extensions of model checking, where not only the existence of computations that violate the specification is determined, but also the number of such violations. We solve the model counting problem for the prominent class of omega-regular properties. We present algorithms for solving the problem for different classes of properties, and show the advantages of our algorithms in comparison to indirect approaches based on encodings into propositional logic. We further show how model counting can be used for solving a variety of quantitative problems in formal verification, including probabilistic model checking, quantitative information-flow in security-critical systems, and the synthesis of approximate implementations for reactive systems.Das Modellzählproblem fragt nach der Anzahl der Lösungen einer logischen Formel, und wurde in den letzten Jahren hauptsächlich für Aussagenlogik untersucht. Das Zählen von Modellen aussagenlogischer Formeln hat sich in vielen Anwendungen als nützlich erwiesen. Im Bereich der künstlichen Intelligenz wurde das Zählen von Modellen beispielsweise verwendet, um die Robustheit eines Plans in einem unvollständigen Weltmodell zu bewerten. Das Zählen von Modellen kann auch verwendet werden, um in sicherheitskritischen Systemen die Menge an enthüllten vertraulichen Daten zu messen. Diese Dissertation stellt das Modellzählproblem für Linearzeiteigenschaften vor, und untersucht dessen Rolle in der Welt der formalen Verifikation. Das Zählen von Modellen für Linearzeiteigenschaften führt zu neuen quantitativen Erweiterungen klassischer Verifikationsprobleme, bei denen nicht nur die Existenz eines Fehlers in einem System zu überprüfen ist, sondern auch die Anzahl solcher Fehler. Wir präsentieren Algorithmen zur Lösung des Modellzählproblems für verschiedene Klassen von Linearzeiteigenschaften und zeigen die Vorteile unserer Algorithmen im Vergleich zu indirekten Ansätzen, die auf Kodierungen der untersuchten Probleme in Aussagenlogik basieren. Darüberhinaus zeigen wir wie das Zählen von Modellen zur Lösung einer Vielzahl quantitativer Probleme in der formalen Verifikation verwendet werden kann. Dies beinhaltet unter anderem die Analyse probabilistischer Modelle, die Kontrolle quantitativen Informationsflusses in sicherheitskritischen Systemen, und die Synthese von approximativen Implementierungen für reaktive Systeme

The impact of macroeconomic leading indicators on inventory management

Forecasting tactical sales is important for long term decisions such as procurement and informing lower level inventory management decisions. Macroeconomic indicators have been shown to improve the forecast accuracy at tactical level, as these indicators can provide early warnings of changing markets while at the same time tactical sales are sufficiently aggregated to facilitate the identification of useful leading indicators. Past research has shown that we can achieve significant gains by incorporating such information. However, at lower levels, that inventory decisions are taken, this is often not feasible due to the level of noise in the data. To take advantage of macroeconomic leading indicators at this level we need to translate the tactical forecasts into operational level ones. In this research we investigate how to best assimilate top level forecasts that incorporate such exogenous information with bottom level (at Stock Keeping Unit level) extrapolative forecasts. The aim is to demonstrate whether incorporating these variables has a positive impact on bottom level planning and eventually inventory levels. We construct appropriate hierarchies of sales and use that structure to reconcile the forecasts, and in turn the different available information, across levels. We are interested both at the point forecast and the prediction intervals, as the latter inform safety stock decisions. Therefore the contribution of this research is twofold. We investigate the usefulness of macroeconomic leading indicators for SKU level forecasts and alternative ways to estimate the variance of hierarchically reconciled forecasts. We provide evidence using a real case study

An ontology-driven architecture for data integration and management in home-based telemonitoring scenarios

The shift from traditional medical care to the use of new technology and engineering innovations is nowadays an interesting and growing research area mainly motivated by a growing population with chronic conditions and disabilities. By means of information and communications technologies (ICTs), telemedicine systems offer a good solution for providing medical care at a distance to any person in any place at any time. Although significant contributions have been made in this field in recent decades, telemedicine and in e-health scenarios in general still pose numerous challenges that need to be addressed by researchers in order to take maximum advantage of the benefits that these systems provide and to support their long-term implementation. The goal of this research thesis is to make contributions in the field of home-based telemonitoring scenarios. By periodically collecting patients' clinical data and transferring them to physicians located in remote sites, patient health status supervision and feedback provision is possible. This type of telemedicine system guarantees patient supervision while reducing costs (enabling more autonomous patient care and avoiding hospital over flows). Furthermore, patients' quality of life and empowerment are improved. Specifically, this research investigates how a new architecture based on ontologies can be successfully used to address the main challenges presented in home-based telemonitoring scenarios. The challenges include data integration, personalized care, multi-chronic conditions, clinical and technical management. These are the principal issues presented and discussed in this thesis. The proposed new ontology-based architecture takes into account both practical and conceptual integration issues and the transference of data between the end points of the telemonitoring scenario (i.e, communication and message exchange). The architecture includes two layers: 1) a conceptual layer and 2) a data and communication layer. On the one hand, the conceptual layer based on ontologies is proposed to unify the management procedure and integrate incoming data from all the sources involved in the telemonitoring process. On the other hand, the data and communication layer based on web service technologies is proposed to provide practical back-up to the use of the ontology, to provide a real implementation of the tasks it describes and thus to provide a means of exchanging data. This architecture takes advantage of the combination of ontologies, rules, web services and the autonomic computing paradigm. All are well-known technologies and popular solutions applied in the semantic web domain and network management field. A review of these technologies and related works that have made use of them is presented in this thesis in order to understand how they can be combined successfully to provide a solution for telemonitoring scenarios. The design and development of the ontology used in the conceptual layer led to the study of the autonomic computing paradigm and its combination with ontologies. In addition, the OWL (Ontology Web Language) language was studied and selected to express the required knowledge in the ontology while the SPARQL language was examined for its effective use in defining rules. As an outcome of these research tasks, the HOTMES (Home Ontology for Integrated Management in Telemonitoring Scenarios) ontology, presented in this thesis, was developed. The combination of the HOTMES ontology with SPARQL rules to provide a flexible solution for personalising management tasks and adapting the methodology for different management purposes is also discussed. The use of Web Services (WSs) was investigated to support the exchange of information defined in the conceptual layer of the architecture. A generic ontology based solution was designed to integrate data and management procedures in the data and communication layer of the architecture. This is an innovative REST-inspired architecture that allows information contained in an ontology to be exchanged in a generic manner. This layer structure and its communication method provide the approach with scalability and re-usability features. The application of the HOTMES-based architecture has been studied for clinical purposes following three simple methodological stages described in this thesis. Data and management integration for context-aware and personalized monitoring services for patients with chronic conditions in the telemonitoring scenario are thus addressed. In particular, the extension of the HOTMES ontology defines a patient profile. These profiles in combination with individual rules provide clinical guidelines aiming to monitor and evaluate the evolution of the patient's health status evolution. This research implied a multi-disciplinary collaboration where clinicians had an essential role both in the ontology definition and in the validation of the proposed approach. Patient profiles were defined for 16 types of different diseases. Finally, two solutions were explored and compared in this thesis to address the remote technical management of all devices that comprise the telemonitoring scenario. The first solution was based on the HOTMES ontology-based architecture. The second solution was based on the most popular TCP/IP management architecture, SNMP (Simple Network Management Protocol). As a general conclusion, it has been demonstrated that the combination of ontologies, rules, WSs and the autonomic computing paradigm takes advantage of the main benefits that these technologies can offer in terms of knowledge representation, work flow organization, data transference, personalization of services and self-management capabilities. It has been proven that ontologies can be successfully used to provide clear descriptions of managed data (both clinical and technical) and ways of managing such information. This represents a further step towards the possibility of establishing more effective home-based telemonitoring systems and thus improving the remote care of patients with chronic diseases

Dynamic optimization of airspace sector grouping

The current airspace configuration is highly structured, fixed and is less responsive to changes causing the overall system to lack the flexibility, adaptability, and responsibility needed to handle the increasing air traffic demands in the near future. The work presented in this thesis aims at improving the flexibility and adaptability of today's airspace management in Europe in a pretactical context. We focus on the development of a method to support a process of automatic generation of a sequence of sector configurations composed of predefined sectors. Airspace configurations should be dynamically adjusted to provide maximum efficiency and flexibility in response to demand fluctuations. We dynamically build configurations by combining existing elementary sectors. In this step, any sector combination which forms controllable airspace blocks is eligible and may be used during the day of operation. In this work, we developed efficient methods to solve DAC problem. We formulated and study the sectorization problem from an algorithmic point of view. We proposed methods based on a mathematical modeling and heuristic optimization techniques. We also introduced here an approach to evaluate the workload inside sectors

Quelques extensions des level sets et des graph cuts et leurs applications à la segmentation d'images et de vidéos

Image processing techniques are now widely spread out over a large quantity of domains: like medical imaging, movies post-production, games... Automatic detection and extraction of regions of interest inside an image, a volume or a video is challenging problem since it is a starting point for many applications in image processing. However many techniques were developed during the last years and the state of the art methods suffer from some drawbacks: The Level Sets method only provides a local minimum while the Graph Cuts method comes from Combinatorial Community and could take advantage of the specificity of image processing problems. In this thesis, we propose two extensions of the previously cited methods in order to soften or remove these drawbacks. We first discuss the existing methods and show how they are related to the segmentation problem through an energy formulation. Then we introduce stochastic perturbations to the Level Sets method and we build a more generic framework: the Stochastic Level Sets (SLS). Later we provide a direct application of the SLS to image segmentation that provides a better minimization of energies. Basically, it allows the contours to escape from local minimum. Then we propose a new formulation of an existing algorithm of Graph Cuts in order to introduce some interesting concept for image processing community: like initialization of the algorithm for speed improvement. We also provide a new approach for layer extraction from video sequence that retrieves both visible and hidden layers in it.Les techniques de traitement d'image sont maintenant largement répandues dans une grande quantité de domaines: comme l'imagerie médicale, la post-production de films, les jeux... La détection et l'extraction automatique de régions d'intérêt à l'intérieur d'une image, d'un volume ou d'une vidéo est réel challenge puisqu'il représente un point de départ pour un grand nombre d'applications en traitement d'image. Cependant beaucoup de techniques développées pendant ces dernières années et les méthodes de l'état de l'art souffrent de quelques inconvénients: la méthode des ensembles de niveaux fournit seulement un minimum local tandis que la méthode de coupes de graphe vient de la communauté combinatoire et pourrait tirer profit de la spécificité des problèmes de traitement d'image. Dans cette thèse, nous proposons deux prolongements des méthodes précédemment citées afin de réduire ou enlever ces inconvénients. Nous discutons d'abord les méthodes existantes et montrons comment elles sont liées au problème de segmentation via une formulation énergétique. Nous présentons ensuite des perturbations stochastiques a la méthode des ensembles de niveaux et nous établissons un cadre plus générique: les ensembles de niveaux stochastiques (SLS). Plus tard nous fournissons une application directe du SLS à la segmentation d'image et montrons qu'elle fournit une meilleure minimisation des énergies. Fondamentalement, il permet aux contours de s'échapper des minima locaux. Nous proposons ensuite une nouvelle formulation d'un algorithme existant des coupes de graphe afin d'introduire de nouveaux concepts intéressant pour la communauté de traitement d'image: comme l'initialisation de l'algorithme pour l'amélioration de vitesse. Nous fournissons également une nouvelle approche pour l'extraction de couches d'une vidéo par segmentation du mouvement et qui extrait à la fois les couches visibles et cachées présentes