Error and attack tolerance of layered complex networks.

Many complex systems may be described by not one but a number of complex networks mapped on each other in a multi-layer structure. Because of the interactions and dependencies between these layers, the state of a single layer does not necessarily reflect well the state of the entire system. In this paper we study the robustness of five examples of two-layer complex systems: three real-life data sets in the fields of communication (the Internet), transportation (the European railway system), and biology (the human brain), and two models based on random graphs. In order to cover the whole range of features specific to these systems, we focus on two extreme policies of system's response to failures, no rerouting and full rerouting. Our main finding is that multi-layer systems are much more vulnerable to errors and intentional attacks than they appear from a single layer perspective.

MR connectomics: a conceptual framework for studying the developing brain.

THE COMBINATION OF ADVANCED NEUROIMAGING TECHNIQUES AND MAJOR DEVELOPMENTS IN COMPLEX NETWORK SCIENCE, HAVE GIVEN BIRTH TO A NEW FRAMEWORK FOR STUDYING THE BRAIN: "connectomics." This framework provides the ability to describe and study the brain as a dynamic network and to explore how the coordination and integration of information processing may occur. In recent years this framework has been used to investigate the developing brain and has shed light on many dynamic changes occurring from infancy through adulthood. The aim of this article is to review this work and to discuss what we have learned from it. We will also use this body of work to highlight key technical aspects that are necessary in general for successful connectome analysis using today's advanced neuroimaging techniques. We look to identify current limitations of such approaches, what can be improved, and how these points generalize to other topics in connectome research.

CFD simulation of complex phenomena containing suspensions and flow throughporous media

There is an increasing reliance on computers to solve complex engineering problems. This is because computers, in addition to supporting the development and implementation of adequate and clear models, can especially minimize the financial support required. The ability of computers to perform complex calculations at high speed has enabled the creation of highly complex systems to model real-world phenomena. The complexity of the fluid dynamics problem makes it difficult or impossible to solve equations of an object in a flow exactly. Approximate solutions can be obtained by construction and measurement of prototypes placed in a flow, or by use of a numerical simulation. Since usage of prototypes can be prohibitively time-consuming and expensive, many have turned to simulations to provide insight during the engineering process. In this case the simulation setup and parameters can be altered much more easily than one could with a real-world experiment. The objective of this research work is to develop numerical models for different suspensions (fiber suspensions, blood flow through microvessels and branching geometries, and magnetic fluids), and also fluid flow through porous media. The models will have merit as a scientific tool and will also have practical application in industries. Most of the numerical simulations were done by the commercial software, Fluent, and user defined functions were added to apply a multiscale method and magnetic field. The results from simulation of fiber suspension can elucidate the physics behind the break up of a fiber floc, opening the possibility for developing a meaningful numerical model of the fiber flow. The simulation of blood movement from an arteriole through a venule via a capillary showed that the model based on VOF can successfully predict the deformation and flow of RBCs in an arteriole. Furthermore, the result corresponds to the experimental observation illustrates that the RBC is deformed during the movement. The concluding remarks presented, provide a correct methodology and a mathematical and numerical framework for the simulation of blood flows in branching. Analysis of ferrofluids simulations indicate that the magnetic Soret effect can be even higher than the conventional one and its strength depends on the strength of magnetic field, confirmed experimentally by Völker and Odenbach. It was also shown that when a magnetic field is perpendicular to the temperature gradient, there will be additional increase in the heat transfer compared to the cases where the magnetic field is parallel to the temperature gradient. In addition, the statistical evaluation (Taguchi technique) on magnetic fluids showed that the temperature and initial concentration of the magnetic phase exert the maximum and minimum contribution to the thermodiffusion, respectively. In the simulation of flow through porous media, dimensionless pressure drop was studied at different Reynolds numbers, based on pore permeability and interstitial fluid velocity. The obtained results agreed well with the correlation of Macdonald et al. (1979) for the range of actual flow Reynolds studied. Furthermore, calculated results for the dispersion coefficients in the cylinder geometry were found to be in agreement with those of Seymour and Callaghan.

Oceanografia e Química: unindo conhecimentos em prol dos oceanos e da sociedade

The marine environment is certainly one of the most complex systems to study, not only because of the challenges posed by the nature of the waters, but especially due to the interactions of physical, chemical and biological processes that control the cycles of the elements. Together with analytical chemists, oceanographers have been making a great effort in the advancement of knowledge of the distribution patterns of trace elements and processes that determine their biogeochemical cycles and influences on the climate of the planet. The international academic community is now in prime position to perform the first study on a global scale for observation of trace elements and their isotopes in the marine environment (GEOTRACES) and to evaluate the effects of major global changes associated with the influences of megacities distributed around the globe. This action can only be performed due to the development of highly sensitive detection methods and the use of clean sampling and handling techniques, together with a joint international program working toward the clear objective of expanding the frontiers of the biogeochemistry of the oceans and related topics, including climate change issues and ocean acidification associated with alterations in the carbon cycle. It is expected that the oceanographic data produced this coming decade will allow a better understanding of biogeochemical cycles, and especially the assessment of changes in trace elements and contaminants in the oceans due to anthropogenic influences, as well as its effects on ecosystems and climate. Computational models are to be constructed to simulate the conditions and processes of the modern oceans and to allow predictions. The environmental changes arising from human activity since the 18th century (also called the Anthropocene) have made the Earth System even more complex. Anthropogenic activities have altered both terrestrial and marine ecosystems, and the legacy of these impacts in the oceans include: a) pollution of the marine environment by solid waste, including plastics; b) pollution by chemical and medical (including those for veterinary use) substances such as hormones, antibiotics, legal and illegal drugs, leading to possible endocrine disruption of marine organisms; and c) ocean acidification, the collateral effect of anthropogenic emissions of CO2 into the atmosphere, irreversible in the human life time scale. Unfortunately, the anthropogenic alteration of the hydrosphere due to inputs of plastics, metal, hydrocarbons, contaminants of emerging concern and even with formerly "exotic" trace elements, such us rare earth elements is likely to accelerate in the near future. These emerging contaminants would likely soon present difficulties for studies in pristine environments. All this knowledge brings with it a great responsibility: helping to envisage viable adaptation and mitigation solutions to the problems identified. The greatest challenge faced by Brazil is currently to create a framework project to develop education, science and technology applied to oceanography and related areas. This framework would strengthen the present working groups and enhance capacity building, allowing a broader Brazilian participation in joint international actions and scientific programs. Recently, the establishment of the National Institutes of Science and Technology (INCTs) for marine science, and the creation of the National Institute of Oceanographic and Hydrological Research represent an exemplary start. However, the participation of the Brazilian academic community in the latest assaults on the frontier of chemical oceanography is extremely limited, largely due to: i. absence of physical infrastructure for the preparation and processing of field samples at ultra-trace level; ii. limited access to oceanographic cruises, due to the small number of Brazilian vessels and/or absence of "clean" laboratories on board; iii. restricted international cooperation; iv. limited analytical capacity of Brazilian institutions for the analysis of trace elements in seawater; v. high cost of ultrapure reagents associated with processing a large number of samples, and vi. lack of qualified technical staff. Advances in knowledge, analytic capabilities and the increasing availability of analytical resources available today offer favorable conditions for chemical oceanography to grow. The Brazilian academic community is maturing and willing to play a role in strengthening the marine science research programs by connecting them with educational and technological initiatives in order to preserve the oceans and to promote the development of society.

Rigorous development of safety-critical systems

Nowadays, computer-based systems tend to become more complex and control increasingly critical functions affecting different areas of human activities. Failures of such systems might result in loss of human lives as well as significant damage to the environment. Therefore, their safety needs to be ensured. However, the development of safety-critical systems is not a trivial exercise. Hence, to preclude design faults and guarantee the desired behaviour, different industrial standards prescribe the use of rigorous techniques for development and verification of such systems. The more critical the system is, the more rigorous approach should be undertaken. To ensure safety of a critical computer-based system, satisfaction of the safety requirements imposed on this system should be demonstrated. This task involves a number of activities. In particular, a set of the safety requirements is usually derived by conducting various safety analysis techniques. Strong assurance that the system satisfies the safety requirements can be provided by formal methods, i.e., mathematically-based techniques. At the same time, the evidence that the system under consideration meets the imposed safety requirements might be demonstrated by constructing safety cases. However, the overall safety assurance process of critical computerbased systems remains insufficiently defined due to the following reasons. Firstly, there are semantic differences between safety requirements and formal models. Informally represented safety requirements should be translated into the underlying formal language to enable further veri cation. Secondly, the development of formal models of complex systems can be labour-intensive and time consuming. Thirdly, there are only a few well-defined methods for integration of formal verification results into safety cases. This thesis proposes an integrated approach to the rigorous development and verification of safety-critical systems that (1) facilitates elicitation of safety requirements and their incorporation into formal models, (2) simplifies formal modelling and verification by proposing specification and refinement patterns, and (3) assists in the construction of safety cases from the artefacts generated by formal reasoning. Our chosen formal framework is Event-B. It allows us to tackle the complexity of safety-critical systems as well as to structure safety requirements by applying abstraction and stepwise refinement. The Rodin platform, a tool supporting Event-B, assists in automatic model transformations and proof-based verification of the desired system properties. The proposed approach has been validated by several case studies from different application domains.

Identification d’une architecture à base de composants dans une application orientée objets à l’aide d’une analyse dynamique

Un système, décrit avec un grand nombre d'éléments fortement interdépendants, est complexe, difficile à comprendre et à maintenir. Ainsi, une application orientée objet est souvent complexe, car elle contient des centaines de classes avec de nombreuses dépendances plus ou moins explicites. Une même application, utilisant le paradigme composant, contiendrait un plus petit nombre d'éléments, faiblement couplés entre eux et avec des interdépendances clairement définies. Ceci est dû au fait que le paradigme composant fournit une bonne représentation de haut niveau des systèmes complexes. Ainsi, ce paradigme peut être utilisé comme "espace de projection" des systèmes orientés objets. Une telle projection peut faciliter l'étape de compréhension d'un système, un pré-requis nécessaire avant toute activité de maintenance et/ou d'évolution. De plus, il est possible d'utiliser cette représentation, comme un modèle pour effectuer une restructuration complète d'une application orientée objets opérationnelle vers une application équivalente à base de composants tout aussi opérationnelle. Ainsi, La nouvelle application bénéficiant ainsi, de toutes les bonnes propriétés associées au paradigme composants. L'objectif de ma thèse est de proposer une méthode semi-automatique pour identifier une architecture à base de composants dans une application orientée objets. Cette architecture doit, non seulement aider à la compréhension de l'application originale, mais aussi simplifier la projection de cette dernière dans un modèle concret de composant. L'identification d'une architecture à base de composants est réalisée en trois grandes étapes: i) obtention des données nécessaires au processus d'identification. Elles correspondent aux dépendances entre les classes et sont obtenues avec une analyse dynamique de l'application cible. ii) identification des composants. Trois méthodes ont été explorées. La première utilise un treillis de Galois, la seconde deux méta-heuristiques et la dernière une méta-heuristique multi-objective. iii) identification de l'architecture à base de composants de l'application cible. Cela est fait en identifiant les interfaces requises et fournis pour chaque composant. Afin de valider ce processus d'identification, ainsi que les différents choix faits durant son développement, j'ai réalisé différentes études de cas. Enfin, je montre la faisabilité de la projection de l'architecture à base de composants identifiée vers un modèle concret de composants.

Affectation de composantes basée sur des contraintes énergétiques dans une architecture multiprocesseurs en trois dimensions

La lithographie et la loi de Moore ont permis des avancées extraordinaires dans la fabrication des circuits intégrés. De nos jours, plusieurs systèmes très complexes peuvent être embarqués sur la même puce électronique. Les contraintes de développement de ces systèmes sont tellement grandes qu’une bonne planification dès le début de leur cycle de développement est incontournable. Ainsi, la planification de la gestion énergétique au début du cycle de développement est devenue une phase importante dans la conception de ces systèmes. Pendant plusieurs années, l’idée était de réduire la consommation énergétique en ajoutant un mécanisme physique une fois le circuit créé, comme par exemple un dissipateur de chaleur. La stratégie actuelle est d’intégrer les contraintes énergétiques dès les premières phases de la conception des circuits. Il est donc essentiel de bien connaître la dissipation d’énergie avant l’intégration des composantes dans une architecture d’un système multiprocesseurs de façon à ce que chaque composante puisse fonctionner efficacement dans les limites de ses contraintes thermiques. Lorsqu’une composante fonctionne, elle consomme de l’énergie électrique qui est transformée en dégagement de chaleur. Le but de ce mémoire est de trouver une affectation efficace des composantes dans une architecture de multiprocesseurs en trois dimensions en tenant compte des limites des facteurs thermiques de ce système.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

" Nonlinear Signal Processing of Electroencephalogram .' Application in the Study of Neurodynamics. "

Interfacings of various subjects generate new field ofstudy and research that help in advancing human knowledge. One of the latest of such fields is Neurotechnology, which is an effective amalgamation of neuroscience, physics, biomedical engineering and computational methods. Neurotechnology provides a platform to interact physicist; neurologist and engineers to break methodology and terminology related barriers. Advancements in Computational capability, wider scope of applications in nonlinear dynamics and chaos in complex systems enhanced study of neurodynamics. However there is a need for an effective dialogue among physicists, neurologists and engineers. Application of computer based technology in the field of medicine through signal and image processing, creation of clinical databases for helping clinicians etc are widely acknowledged. Such synergic effects between widely separated disciplines may help in enhancing the effectiveness of existing diagnostic methods. One of the recent methods in this direction is analysis of electroencephalogram with the help of methods in nonlinear dynamics. This thesis is an effort to understand the functional aspects of human brain by studying electroencephalogram. The algorithms and other related methods developed in the present work can be interfaced with a digital EEG machine to unfold the information hidden in the signal. Ultimately this can be used as a diagnostic tool.

Some Aspects of Domain Specific Conceptual Modeling for Simulation of Logistic Terminal Operations

When simulation modeling is used for performance improvement studies of complex systems such as transport terminals, domain specific conceptual modeling constructs could be used by modelers to create structured models. A two stage procedure which includes identification of the problem characteristics/cluster - ‘knowledge acquisition’ and identification of standard models for the problem cluster – ‘model abstraction’ was found to be effective in creating structured models when applied to certain logistic terminal systems. In this paper we discuss some methods and examples related the knowledge acquisition and model abstraction stages for the development of three different types of model categories of terminal systems

Mythen und Mythenbildung in Kunst und Werbung

Aufgrund der breiten aktuellen Verwendung des Mythen-Begriffs in Kunst und Werbung, aber darüber hinaus auch in nahezu allen Bereichen gesellschaftlichen Lebens und vor allem in der Philosophie ergibt sich die Notwendigkeit, einen erweiterten Mythos-Begriff über das Historisch-Authentische hinaus zu verfolgen. Ausgehend von einer strukturalen Annäherung an den Mythos-Begriff im Sinne des von Roland Barthes vorgeschlagenen sekundären semiologischen Systems, d.h. einer semiologischen Sinnverschiebung zur Schaffung einer neuen – mythischen – Bedeutung, fordert diese neue Bedeutung eine Analyse, eine Mythenanalyse heraus. Dies ist deshalb so entscheidend, weil eben diese neue Bedeutung ihr mythisches Profil im Sinne von Hans Blumenberg durch forcierte Bedeutsamkeit für Individuen oder für bestimmte gesellschaftliche Gruppierungen unterlegt, z.B. durch bewusst intensive Wiederholung eines Themas oder durch unerwartete Koinzidenzen von Ereignissen oder durch Steigerung bzw. Depotenzierung von Fakten. Der erweiterte Mythen-Begriff verlangt nach einer Strukturierung und führt dabei zu unterschiedlichen Mythen-Ansätzen: zum Ursprungsstoff des authentischen Mythos und darauf basierender Geisteslage, zum Erkennen eines reflektierten Mythos, wenn es um das Verhältnis Mythos/Aufklärung geht, zum Zeitgeist-Mythos mit seinen umfangreichen Ausprägungen ideologischer, affirmativer und kritischer Art oder zu Alltagsmythen, die sich auf Persönlichkeitskulte und Sachverherrlichungen beziehen. Gerade der letztere Typus ist das Terrain der Werbung, die über den Gebrauchswert eines Produktes hinaus Wert steigernde Tauschwerte durch symbolische Zusatzattribute erarbeiten möchte. Hierbei können Markenmythen unterschiedlichster Prägung entstehen, denen wir täglich im Fernsehen oder im Supermarkt begegnen. Die Manifestation des Mythos in der Kunst ist einerseits eine unendliche Transformationsgeschichte mythischer Substanzen und andererseits ein überhöhender Bezug auf Zeitgeisterscheinungen, etwa bei dem Mythos des Künstlers selbst oder der durch ihn vorgenommenen „Verklärung des Gewöhnlichen“. Die Transformationsprozesse können u.a . prototypisch an zwei Beispielketten erläutert werden, die für den Kunst/Werbung-Komplex besonders interessant sind, weil ihr Charakter sich in einem Fall für die Werbung als äußerst Erfolg versprechend erwiesen hat und weil sich im zweiten Fall geradezu das Gegenteil abzeichnet: Zum einen ist es die Mythengestalt der Nymphe, jene jugendliche, erotisch-verführerische Frauengestalt, die über ihre antiken Wurzeln als Sinnbild der Lebensfreude und Fruchtbarkeit hinaus in und nach der Renaissance ihre Eignung als Verbildlichung der Wiederzulassung des Weiblichen in der Kunst beweist und schließlich der Instrumen-talisierung der Werbung dient. Im anderen Fall ist es die Geschichte der Medusa, die man idealtypisch als die andere Seite der Nympha bezeichnen kann. Hier hat Kunst Auf-klärungsarbeit geleistet, vor allem durch die Verschiebung des medusischen Schreckens von ihr weg zu einer allgemein-medusischen Realität, deren neue Träger nicht nur den Schrecken, sondern zugleich ihre Beteiligung an der Schaffung dieses Schreckens auf sich nehmen. Mythosanalyse ist erforderlich, um die Stellungnahmen der Künstler über alle Epochen hinweg und dabei vor allem diese Transformationsprozesse zu erkennen und im Sinne von Ent- oder Remythologisierung einzuordnen. Die hierarchische Zuordnung der dabei erkannten Bedeutungen kann zu einem Grundbestandteil einer praktischen Philosophie werden, wenn sie einen Diskurs durchläuft, der sich an Jürgen Habermas’ Aspekt der Richtigkeit für kommunikatives Handeln unter dem Gesichtspunkt der Toleranz orientiert. Dabei ist nicht nur zu beachten, dass eine verstärkte Mythenbildung in der Kunst zu einem erweiterten Mythen-begriff und damit zu dem erweiterten, heute dominierenden Kunstbegriff postmoderner Prägung geführt hat, sondern dass innerhalb des aktuellen Mythenpakets sich die Darstellungen von Zeitgeist- und Alltagsmythen zu Lasten des authentischen und des reflektierten Mythos entwickelt haben, wobei zusätzlich werbliche Markenmythen ihre Entstehung auf Verfahrensvorbildern der Kunst basieren. Die ökonomische Rationalität der aktuellen Gesellschaft hat die Mythenbildung keines-wegs abgebaut, sie hat sie im Gegenteil gefördert. Der neuerliche Mythenbedarf wurde stimuliert durch die Sinnentleerung der zweckrationalisierten Welt, die Ersatzbedarf anmeldete. Ihre Ordnungsprinzipien durchdringen nicht nur ihre Paradedisziplin, die Ökonomie, sondern Politik und Staat, Wissenschaft und Kunst. Das Umschlagen der Aufklärung wird nur zu vermeiden sein, wenn wir uns Schritt für Schritt durch Mythenanalyse unserer Unmündigkeit entledigen.

Designing in the real world is complex anyway - so what?

Designing is a heterogeneous, fuzzily defined, floating field of various activities and chunks of ideas and knowledge. Available theories about the foundations of designing as presented in "the basic PARADOX" (Jonas and Meyer-Veden 2004) have evoked the impression of Babylonian confusion. We located the reasons for this "mess" in the "non-fit", which is the problematic relation of theories and subject field. There seems to be a comparable interface problem in theory-building as in designing itself. "Complexity" sounds promising, but turns out to be a problematic and not really helpful concept. I will argue for a more precise application of systemic and evolutionary concepts instead, which - in my view - are able to model the underlying generative structures and processes that produce the visible phenomenon of complexity. It does not make sense to introduce a new fashionable meta-concept and to hope for a panacea before having clarified the more basic and still equally problematic older meta-concepts. This paper will take one step away from "theories of what" towards practice and doing and try to have a closer look at existing process models or "theories of how" to design instead. Doing this from a systemic perspective leads to an evolutionary view of the process, which finally allows to specify more clearly the "knowledge gaps" inherent in the design process. This aspect has to be taken into account as constitutive of any attempt at theory-building in design, which can be characterized as a "practice of not-knowing". I conclude, that comprehensive "unified" theories, or methods, or process models run aground on the identified knowledge gaps, which allow neither reliable models of the present, nor reliable projections into the future. Consolation may be found in performing a shift from the effort of adaptation towards strategies of exaptation, which means the development of stocks of alternatives for coping with unpredictable situations in the future.

Generative Temporal Planning with Complex Processes

Autonomous vehicles are increasingly being used in mission-critical applications, and robust methods are needed for controlling these inherently unreliable and complex systems. This thesis advocates the use of model-based programming, which allows mission designers to program autonomous missions at the level of a coach or wing commander. To support such a system, this thesis presents the Spock generative planner. To generate plans, Spock must be able to piece together vehicle commands and team tactics that have a complex behavior represented by concurrent processes. This is in contrast to traditional planners, whose operators represent simple atomic or durative actions. Spock represents operators using the RMPL language, which describes behaviors using parallel and sequential compositions of state and activity episodes. RMPL is useful for controlling mobile autonomous missions because it allows mission designers to quickly encode expressive activity models using object-oriented design methods and an intuitive set of activity combinators. Spock also is significant in that it uniformly represents operators and plan-space processes in terms of Temporal Plan Networks, which support temporal flexibility for robust plan execution. Finally, Spock is implemented as a forward progression optimal planner that walks monotonically forward through plan processes, closing any open conditions and resolving any conflicts. This thesis describes the Spock algorithm in detail, along with example problems and test results.

Impacto de la apertura en la conectividad e integración de Colombia en la red mundial de comercio

La liberalización colombiana es analizada, con frecuencia, con los coeficientes de apertura, este documento, en cambio, presenta un análisis complementario a través de algoritmos usados en la teoría de redes para caracterizar sistemas complejos. Esta nueva aproximación devela estructuras de la red mundial de comercio antes y después de la apertura, así como cambios en la posición colombiana.

El liderazgo organizacional: una aproximación desde la perspectiva etológica

La presente investigación plantea la necesidad fundamental de generar un proceso de análisis, tendiente a proponer dinámicas organizativas humanas, desde un enfoque etológico. La etología aparece entonces como un estudio sistemático del comportamiento animal, sus formas de asociación, su disparidad, pero sobre todo, su accionar orgánico en la búsqueda de un comportamiento colectivo que propenda por el bien común. En esta medida el liderazgo surge como una posibilidad clara de fomentar relaciones humanas centradas en las diferentes vertientes relacionales; cultura, comunicación, comunidad, axiología, y finalmente etología. Así mismo, se examinan las diferentes estrategias que el liderazgo como posibilidad de cambio dentro de las organizaciones, puede ser fundamentado mediante procesos de comparación etológica, y así generar propuestas que configuren un quehacer organizacional desde la solidaridad, el liderazgo, y el desenvolvimiento interno y externo de las organizaciones.