Structuring research methods and data with the research object model: genomics workflows as a case study

Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as “which particular data was input to a particular workflow to test a particular hypothesis?”, and “which particular conclusions were drawn from a particular workflow?”. Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well.

Debonding detection of FRP strengthened concrete beams by using impedance measurements and an ensemble PSO adaptive spectral model

An impedance-based midspan debonding identification method for RC beams strengthened with FRP strips is presented in this paper using piezoelectric ceramic (PZT) sensor?actuators. To reach this purpose, firstly, a two-dimensional electromechanical impedance model is proposed to predict the electrical admittance of the PZT transducer bonded to the FRP strips of an RC beam. Considering the impedance is measured in high frequencies, a spectral element model of the bonded-PZT?FRP strengthened beam is developed. This model, in conjunction with experimental measurements of PZT transducers, is used to present an updating methodology to quantitatively detect interfacial debonding of these kinds of structures. To improve the performance and accuracy of the detection algorithm in a challenging problem such as ours, the structural health monitoring approach is solved with an ensemble process based on particle of swarm. An adaptive mesh scheme has also been developed to increase the reliability in locating the area in which debonding initiates. Predictions carried out with experimental results have showed the effectiveness and potential of the proposed method to detect prematurely at its earliest stages a critical failure mode such as that due to midspan debonding of the FRP strip.

Arquitectura de información para medicion de rendimiento en entornos e-manufacturing

La implantación de las tecnologías Internet ha permitido la extensión del uso de estrategias e-manufacturing y el desarrollo de herramientas para la recopilación, transformación y sincronización de datos de fabricación vía web. En este ámbito, un área de potencial desarrollo es la extensión del virtual manufacturing a los procesos de Performance Management (PM), área crítica para la toma de decisiones y ejecución de acciones de mejora en fabricación. Este trabajo doctoral propone un Arquitectura de Información para el desarrollo de herramientas virtuales en el ámbito PM. Su aplicación permite asegurar la interoperabilidad necesaria en los procesos de tratamiento de información de toma de decisión. Está formado por tres sub-sistemas: un modelo conceptual, un modelo de objetos y un marco Web compuesto de una plataforma de información y una arquitectura de servicios Web (WS). El modelo conceptual y el modelo de objetos se basa en el desarrollo de toda la información que se necesita para definir y obtener los diferentes indicadores de medida que requieren los procesos PM. La plataforma de información hace uso de las tecnologías XML y B2MML para estructurar un nuevo conjunto de esquemas de mensajes de intercambio de medición de rendimiento (PMXML). Esta plataforma de información se complementa con una arquitectura de servicios web que hace uso de estos esquemas para integrar los procesos de codificación, decodificación, traducción y evaluación de los performance key indicators (KPI). Estos servicios realizan todas las transacciones que permiten transformar los datos origen en información inteligente usable en los procesos de toma de decisión. Un caso práctico de intercambio de datos en procesos de medición del área de mantenimiento de equipos es mostrado para verificar la utilidad de la arquitectura. ABSTRAC The implementation of Internet technologies has led to e-Manufacturing technologies becoming more widely used and to the development of tools for compiling, transforming and synchronizing manufacturing data through the Web. In this context, a potential area for development is the extension of virtual manufacturing to Performance Measurement (PM) processes, a critical area for decision-making and implementing improvement actions in manufacturing. This thesis proposes a Information Architecture to integrate decision support systems in e-manufacturing. Specifically, the proposed architecture offers a homogeneous PM information exchange model that can be applied trough decision support in emanufacturing environment. Its application improves the necessary interoperability in decision-making data processing tasks. It comprises three sub-systems: a data model, a object model and Web Framework which is composed by a PM information platform and PM-Web services architecture. . The data model and the object model are based on developing all the information required to define and acquire the different indicators required by PM processes. The PM information platform uses XML and B2MML technologies to structure a new set of performance measurement exchange message schemas (PM-XML). This PM information platform is complemented by a PM-Web Services architecture that uses these schemas to integrate the coding, decoding, translation and assessment processes of the key performance indicators (KPIs). These services perform all the transactions that enable the source data to be transformed into smart data that can be used in the decision-making processes. A practical example of data exchange for measurement processes in the area of equipment maintenance is shown to demonstrate the utility of the architecture.

Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

Adaptive Multi-Camera System for Real Time Object Detection

In this paper we present an adaptive multi-camera system for real time object detection able to efficiently adjust the computational requirements of video processing blocks to the available processing power and the activity of the scene. The system is based on a two level adaptation strategy that works at local and at global level. Object detection is based on a Gaussian mixtures model background subtraction algorithm. Results show that the system can efficiently adapt the algorithm parameters without a significant loss in the detection accuracy.

O'CIAO an object oriented programming model using CIAO Prolog

There have been several previous proposals for the integration of Object Oriented Programming features into Logic Programming, resulting in much support theory and several language proposals. However, none of these proposals seem to have made it into the mainstream. Perhaps one of the reasons for these is that the resulting languages depart too much from the standard logic programming languages to entice the average Prolog programmer. Another reason may be that most of what can be done with object-oriented programming can already be done in Prolog through the meta- and higher-order programming facilities that the language includes, albeit sometimes in a more cumbersome way. In light of this, in this paper we propose an alternative solution which is driven by two main objectives. The first one is to include only those characteristics of object-oriented programming which are cumbersome to implement in standard Prolog systems. The second one is to do this in such a way that there is minimum impact on the syntax and complexity of the language, i.e., to introduce the minimum number of new constructs, declarations, and concepts to be learned. Finally, we would like the implementation to be as straightforward as possible, ideally based on simple source to source expansions.

A model for integrating learning object repository resources into web videoconference services

Reusing Learning Objects saves time and reduce development costs. Hence, achieving their interoperability in multiple contexts is essential when creating a Learning Object Repository. On the other hand, novel web videoconference services are available due to technological advancements. Several benefits can be gained by integrating Learning Objects into these services. For instance, they can allow sharing, co-viewing and synchronized co-browsing of these resources at the same time that provide real time communication. However, several efforts need to be undertaken to achieve the interoperability with these systems. In this paper, we propose a model to integrate the resources of the Learning Object Repositories into web videoconference services. The experience of applying this model in a real e-Learning scenario achieving interoperability with two different web videoconference services is also described.

Assessing the impact of adaptive accessibility on the optimal transport policy implementation by using an integrated land-use/transport model for Madrid

Accessibility is an essential concept widely used to evaluate the impact of land-use and transport strategies in transport and urban planning. Accessibility is typically evaluated by using a transport model or a land-use model independently or successively without a feedback loop, thus neglecting the interaction effects between the two systems and the induced competition effects among opportunities due to accessibility improvements. More than a mere methodological curiosity, failure to account for land- use/transport interactions and the competition effect may result in large underestimation of the policy effects. With the recent development of land-use and transport interaction (LUTI) models, there is a growing interest in using these models to adequately measure accessibility and evaluate its impact. The current study joins this research stream by embedding an accessibility measure in a LUTI model with two main aims. The first aim is to account for adaptive accessibility, namely the adjustment of the potential accessibility due to the effect of competition among opportunities (e.g., workplaces) as a result of improved accessibility. LUTI models are particularly suitable for assessing adaptive accessibility because the competition factor is a function of the number of jobs, which is related to land-use attractiveness and the number of workers which is related, among other factors, to the transport demand. The second aim is to identify the optimal implementation scenario of policy measures on the basis of the potential and adaptive accessibility and analyse the results in terms of social welfare and accessibility. The metropolitan area of Madrid is used as a case-study and two transport policy instruments, namely a cordon toll and bus frequency increase, have been chosen for the simulation study in order to present the usefulness of the approach to urban planners and policy makers. The MARS model (Metropolitan Activity Relocation Simulator) calibrated for Madrid was employed as the analysis tool. The impact of accessibility is embedded in the model through a social welfare function that includes not only costs and benefits to both road users and transport operators, but also costs and benefits for the government and society in general (external costs). An optimisation procedure is performed by the MARS model for maximizing the value of objective function in order to find the best (optimal) policy imp lementations intensity (i.e., price, frequency). Last, the two policy strategies are evaluated in terms of their accessibility. Results show that the accessibility with competition factor influences the optimal policy implementation level and also generates different results in terms of social welfare. In addition, mapping the difference between the potential and the adaptive accessibility indicators shows that the main changes occur in areas where there is a strong competition among land-use opportunities.

Subjective quality assessment of an adaptive video streaming model

With the recent increased popularity and high usage of HTTP Adaptive Streaming (HAS) techniques, various studies have been carried out in this area which generally focused on the technical enhancement of HAS technology and applications. However, a lack of common HAS standard led to multiple proprietary approaches which have been developed by major Internet companies. In the emerging MPEG-DASH standard the packagings of the video content and HTTP syntax have been standardized; but all the details of the adaptation behavior are left to the client implementation. Nevertheless, to design an adaptation algorithm which optimizes the viewing experience of the enduser, the multimedia service providers need to know about the Quality of Experience (QoE) of different adaptation schemes. Taking this into account, the objective of this experiment was to study the QoE of a HAS-based video broadcast model. The experiment has been carried out through a subjective study of the end user response to various possible clients’ behavior for changing the video quality taking different QoE-influence factors into account. The experimental conclusions have made a good insight into the QoE of different adaptation schemes which can be exploited by HAS clients for designing the adaptation algorithms.

Towards a Learning Object pedagogical quality metric based on the LORI evaluation model

Evaluating and measuring the pedagogical quality of Learning Objects is essential for achieving a successful web-based education. On one hand, teachers need some assurance of quality of the teaching resources before making them part of the curriculum. On the other hand, Learning Object Repositories need to include quality information into the ranking metrics used by the search engines in order to save users time when searching. For these reasons, several models such as LORI (Learning Object Review Instrument) have been proposed to evaluate Learning Object quality from a pedagogical perspective. However, no much effort has been put in defining and evaluating quality metrics based on those models. This paper proposes and evaluates a set of pedagogical quality metrics based on LORI. The work exposed in this paper shows that these metrics can be effectively and reliably used to provide quality-based sorting of search results. Besides, it strongly evidences that the evaluation of Learning Objects from a pedagogical perspective can notably enhance Learning Object search if suitable evaluations models and quality metrics are used. An evaluation of the LORI model is also described. Finally, all the presented metrics are compared and a discussion on their weaknesses and strengths is provided.

Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

Emotion is generally argued to be an influence on the behavior of life systems, largely concerning flexibility and adaptivity. The way in which life systems acts in response to a particular situations of the environment, has revealed the decisive and crucial importance of this feature in the success of behaviors. And this source of inspiration has influenced the way of thinking artificial systems. During the last decades, artificial systems have undergone such an evolution that each day more are integrated in our daily life. They have become greater in complexity, and the subsequent effects are related to an increased demand of systems that ensure resilience, robustness, availability, security or safety among others. All of them questions that raise quite a fundamental challenges in control design. This thesis has been developed under the framework of the Autonomous System project, a.k.a the ASys-Project. Short-term objectives of immediate application are focused on to design improved systems, and the approaching of intelligence in control strategies. Besides this, long-term objectives underlying ASys-Project concentrate on high order capabilities such as cognition, awareness and autonomy. This thesis is placed within the general fields of Engineery and Emotion science, and provides a theoretical foundation for engineering and designing computational emotion for artificial systems. The starting question that has grounded this thesis aims the problem of emotion--based autonomy. And how to feedback systems with valuable meaning has conformed the general objective. Both the starting question and the general objective, have underlaid the study of emotion, the influence on systems behavior, the key foundations that justify this feature in life systems, how emotion is integrated within the normal operation, and how this entire problem of emotion can be explained in artificial systems. By assuming essential differences concerning structure, purpose and operation between life and artificial systems, the essential motivation has been the exploration of what emotion solves in nature to afterwards analyze analogies for man--made systems. This work provides a reference model in which a collection of entities, relationships, models, functions and informational artifacts, are all interacting to provide the system with non-explicit knowledge under the form of emotion-like relevances. This solution aims to provide a reference model under which to design solutions for emotional operation, but related to the real needs of artificial systems. The proposal consists of a multi-purpose architecture that implement two broad modules in order to attend: (a) the range of processes related to the environment affectation, and (b) the range or processes related to the emotion perception-like and the higher levels of reasoning. This has required an intense and critical analysis beyond the state of the art around the most relevant theories of emotion and technical systems, in order to obtain the required support for those foundations that sustain each model. The problem has been interpreted and is described on the basis of AGSys, an agent assumed with the minimum rationality as to provide the capability to perform emotional assessment. AGSys is a conceptualization of a Model-based Cognitive agent that embodies an inner agent ESys, the responsible of performing the emotional operation inside of AGSys. The solution consists of multiple computational modules working federated, and aimed at conforming a mutual feedback loop between AGSys and ESys. Throughout this solution, the environment and the effects that might influence over the system are described as different problems. While AGSys operates as a common system within the external environment, ESys is designed to operate within a conceptualized inner environment. And this inner environment is built on the basis of those relevances that might occur inside of AGSys in the interaction with the external environment. This allows for a high-quality separate reasoning concerning mission goals defined in AGSys, and emotional goals defined in ESys. This way, it is provided a possible path for high-level reasoning under the influence of goals congruence. High-level reasoning model uses knowledge about emotional goals stability, letting this way new directions in which mission goals might be assessed under the situational state of this stability. This high-level reasoning is grounded by the work of MEP, a model of emotion perception that is thought as an analogy of a well-known theory in emotion science. The work of this model is described under the operation of a recursive-like process labeled as R-Loop, together with a system of emotional goals that are assumed as individual agents. This way, AGSys integrates knowledge that concerns the relation between a perceived object, and the effect which this perception induces on the situational state of the emotional goals. This knowledge enables a high-order system of information that provides the sustain for a high-level reasoning. The extent to which this reasoning might be approached is just delineated and assumed as future work. This thesis has been studied beyond a long range of fields of knowledge. This knowledge can be structured into two main objectives: (a) the fields of psychology, cognitive science, neurology and biological sciences in order to obtain understanding concerning the problem of the emotional phenomena, and (b) a large amount of computer science branches such as Autonomic Computing (AC), Self-adaptive software, Self-X systems, Model Integrated Computing (MIC) or the paradigm of models@runtime among others, in order to obtain knowledge about tools for designing each part of the solution. The final approach has been mainly performed on the basis of the entire acquired knowledge, and described under the fields of Artificial Intelligence, Model-Based Systems (MBS), and additional mathematical formalizations to provide punctual understanding in those cases that it has been required. This approach describes a reference model to feedback systems with valuable meaning, allowing for reasoning with regard to (a) the relationship between the environment and the relevance of the effects on the system, and (b) dynamical evaluations concerning the inner situational state of the system as a result of those effects. And this reasoning provides a framework of distinguishable states of AGSys derived from its own circumstances, that can be assumed as artificial emotion.

Object Kinetic Monte Carlo calculations of irradiated Fe-Cr dilute alloys: The effect of the interaction radius between substitutional Cr and self-interstitial Fe

ObjectKineticMonteCarlo models allow for the study of the evolution of the damage created by irradiation to time scales that are comparable to those achieved experimentally. Therefore, the essential ObjectKineticMonteCarlo parameters can be validated through comparison with experiments. However, this validation is not trivial since a large number of parameters is necessary, including migration energies of point defects and their clusters, binding energies of point defects in clusters, as well as the interactionradii. This is particularly cumbersome when describing an alloy, such as the Fe–Cr system, which is of interest for fusion energy applications. In this work we describe an ObjectKineticMonteCarlo model for Fe–Cr alloys in the dilute limit. The parameters used in the model come either from density functional theory calculations or from empirical interatomic potentials. This model is used to reproduce isochronal resistivity recovery experiments of electron irradiateddiluteFe–Cr alloys performed by Abe and Kuramoto. The comparison between the calculated results and the experiments reveal that an important parameter is the capture radius between substitutionalCr and self-interstitialFe atoms. A parametric study is presented on the effect of the capture radius on the simulated recovery curves.

Adaptive fuzzy knowledge-based systems for control metabots' mobility on virtual environments

The confluence of three-dimensional (3D) virtual worlds with social networks imposes on software agents, in addition to conversational functions, the same behaviours as those common to human-driven avatars. In this paper, we explore the possibilities of the use of metabots (metaverse robots) with motion capabilities in complex virtual 3D worlds and we put forward a learning model based on the techniques used in evolutionary computation for optimizing the fuzzy controllers which will subsequently be used by metabots for moving around a virtual environment.

Moving Object Detection for Real-Time High-Quality Lightweight Applications on Smart Cameras

Here, a novel and efficient strategy for moving object detection by non-parametric modeling on smart cameras is presented. Whereas the background is modeled using only color information, the foreground model combines color and spatial information. The application of a particle filter allows the update of the spatial information and provides a priori information about the areas to analyze in the following images, enabling an important reduction in the computational requirements and improving the segmentation results

3D Object following based on visual information for Unmanned Aerial Vehicles

This article presents a novel system and a control strategy for visual following of a 3D moving object by an Unmanned Aerial Vehicle UAV. The presented strategy is based only on the visual information given by an adaptive tracking method based on the color information, which jointly with the dynamics of a camera fixed to a rotary wind UAV are used to develop an Image-based visual servoing IBVS system. This system is focused on continuously following a 3D moving target object, maintaining it with a fixed distance and centered on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigation