Including Qualitative Knowledge in Semiqualitative Dynamical Systems

A new method to incorporate qualitative knowledge in semiqualitative systems is presented. In these systems qualitative knowledge may be expressed in their parameters, initial conditions and/or vector fields. The representation of qualitative knowledge is made by means of intervals, continuous qualitative functions and envelope functions. A dynamical system is defined by differential equations with qualitative knowledge. This definition is transformed into a family of dynamical systems. In this paper the semiqualitative analysis is carried out by means of constraint satisfaction problems, using interval consistency techniques

Searching for similar semiqualitative temporal patterns in time-series databases

A way to obtain behaviour patterns of semiqualitative models of dynamic systems automatically is proposed in this paper. The temporal evolution of these models is stored into a database. This is a time series database. This database may be obtained as is explained in [Ortega et al . 1999] or by means of sensor data. In any way, the database contains the values of state variables and parameters. Searching for similar patterns in such database is essential, because it helps in predictions, hypothesis testing and, in general, in data mining and rule discovery. A language to carry out queries about the qualitative and temporal properties of this time-series database is also proposed. This language allows us to study all the states of a dynamic system: the stationary and the transient states. The language is also intended to classify the different qualitative behaviours of our model. This classification may be carried out according to a specific criterion or automatically by means of clustering algorithms. The semiqualitative behaviour of a system is expressed by means of hierarchical rules obtained by means of machine learning algorithms. The methodology is applied to a logistics growth model with a delay.Ministerio de Ciencia y Tecnología TIC98-1635-

Semiqualitative Methodology to Reasoning about Dynamic Systems

En este artículo se propone una metodología para razonar sobre los modelos semicualitativos construidos para sistemas dinámicos con conocimiento cualitativo y cuantitativo. La información cualitativa de estos sistemas puede componerse de: operadores cualitativos, etiquetas cualitativas, funciones de bandas y funciones continuas cualitativas. Se presenta un formalismo para incorporar esta información a los modelos. La metodología propuesta permite estudiar no sólo del régimen estacionario, ampliamente estudiado en la literatura, sino que además posibilita realizar un estudio del régimen transitorio de los sistemas. Se presenta también un estudio teórico sobre la validez de las conclusiones obtenidas la metodología. Los comportamientos del sistema se pueden obtener automáticamente aplicando algoritmos de clustering y se expresan mediante un conjunto de reglas jerárquicas obtenidas mediante algoritmos genéticos. La metodología se ha aplicado a un par de modelos, siendo uno el modelo de dos estanques interconectados y otro un modelo de crecimiento logístico donde se ha incorporado un retraso en el bucle de realimentación.In this article a methodology to reason over semiqualitative models built for dinamic systems with qualitative and quantitative knowledge is proposed. The qualitative information of these systems can be composed of: qualitative operators, qualitative labels, bands functions and qualitative continuous functions. A formalism to incorporate this information to the models is presented. The proposed methodology allows to study not just about the stationary regime, widely studied in the literature, but also it makes possible to carry out a study of the transitory regime of the systems. It also presents a theoretical study about the validity of the conclusions obtained in the methodology. The behaviours of the system can be obtained automatically applying clustering algorithms and are expressed through a set of hierarchical rules obtained from genetics algorithms. The methodology has been applied to a couple of models, one of them is the interconnected pools model and the other a logistical growing model where a delay in the feedback curls has been incorporated

Stability of quantized conductance levels in memristors with copper filaments: toward understanding the mechanisms of resistive switching

Memristors are among the most promising elements for modern microelectronics, having unique properties such as quasi-continuous change of conductance and long-term storage of resistive states. However, identifying the physical mechanisms of resistive switching and evolution of conductive filaments in such structures still remains a major challenge. In this work, aiming at a better understanding of these phenomena, we experimentally investigate an unusual effect of enhanced conductive filament stability in memristors with copper filaments under the applied voltage and present a simplified theoretical model of the effect of a quantum current through a filament on its shape. Our semi-quantitative, continuous model predicts, indeed, that for a thin filament, the "quantum pressure" exerted on its walls by the recoil of charge carriers can well compete with the surface tension and crucially affect the evolution of the filament profile at the voltages around 1V. At lower voltages, the quantum pressure is expected to provide extra stability to the filaments supporting quantized conductance, which we also reveal experimentally using a novel methodology focusing on retention statistics. Our results indicate that the recoil effects could potentially be important for resistive switching in memristive devices with metallic filaments and that taking them into account in rational design of memristors could help achieve their better retention and plasticity characteristics.Comment: version accepted for publication in Phys. Rev. Applied, including improved statistic

Elucidating regulatory mechanisms downstream of a signaling pathway using informative experiments

Signaling cascades are triggered by environmental stimulation and propagate the signal to regulate transcription. Systematic reconstruction of the underlying regulatory mechanisms requires pathway-targeted, informative experimental data. However, practical experimental design approaches are still in their infancy. Here, we propose a framework that iterates design of experiments and identification of regulatory relationships downstream of a given pathway. The experimental design component, called MEED, aims to minimize the amount of laboratory effort required in this process. To avoid ambiguity in the identification of regulatory relationships, the choice of experiments maximizes diversity between expression profiles of genes regulated through different mechanisms. The framework takes advantage of expert knowledge about the pathways under study, formalized in a predictive logical model. By considering model-predicted dependencies between experiments, MEED is able to suggest a whole set of experiments that can be carried out simultaneously. Our framework was applied to investigate interconnected signaling pathways in yeast. In comparison with other approaches, MEED suggested the most informative experiments for unambiguous identification of transcriptional regulation in this system

Earth Observing System. Volume 1, Part 2: Science and Mission Requirements. Working Group Report Appendix

Areas of global hydrologic cycles, global biogeochemical cycles geophysical processes are addressed including biological oceanography, inland aquatic resources, land biology, tropospheric chemistry, oceanic transport, polar glaciology, sea ice and atmospheric chemistry