A Personal Agent Architecture for Task Automation in the Web of Data. Bringing intelligence to everyday tasks

Internet está evolucionando hacia la conocida como Live Web. En esta nueva etapa en la evolución de Internet, se pone al servicio de los usuarios multitud de streams de datos sociales. Gracias a estas fuentes de datos, los usuarios han pasado de navegar por páginas web estáticas a interacturar con aplicaciones que ofrecen contenido personalizado, basada en sus preferencias. Cada usuario interactúa a diario con multiples aplicaciones que ofrecen notificaciones y alertas, en este sentido cada usuario es una fuente de eventos, y a menudo los usuarios se sienten desbordados y no son capaces de procesar toda esa información a la carta. Para lidiar con esta sobresaturación, han aparecido múltiples herramientas que automatizan las tareas más habituales, desde gestores de bandeja de entrada, gestores de alertas en redes sociales, a complejos CRMs o smart-home hubs. La contrapartida es que aunque ofrecen una solución a problemas comunes, no pueden adaptarse a las necesidades de cada usuario ofreciendo una solucion personalizada. Los Servicios de Automatización de Tareas (TAS de sus siglas en inglés) entraron en escena a partir de 2012 para dar solución a esta liminación. Dada su semejanza, estos servicios también son considerados como un nuevo enfoque en la tecnología de mash-ups pero centra en el usuarios. Los usuarios de estas plataformas tienen la capacidad de interconectar servicios, sensores y otros aparatos con connexión a internet diseñando las automatizaciones que se ajustan a sus necesidades. La propuesta ha sido ámpliamante aceptada por los usuarios. Este hecho ha propiciado multitud de plataformas que ofrecen servicios TAS entren en escena. Al ser un nuevo campo de investigación, esta tesis presenta las principales características de los TAS, describe sus componentes, e identifica las dimensiones fundamentales que los defines y permiten su clasificación. En este trabajo se acuña el termino Servicio de Automatización de Tareas (TAS) dando una descripción formal para estos servicios y sus componentes (llamados canales), y proporciona una arquitectura de referencia. De igual forma, existe una falta de herramientas para describir servicios de automatización, y las reglas de automatización. A este respecto, esta tesis propone un modelo común que se concreta en la ontología EWE (Evented WEb Ontology). Este modelo permite com parar y equiparar canales y automatizaciones de distintos TASs, constituyendo un aporte considerable paraa la portabilidad de automatizaciones de usuarios entre plataformas. De igual manera, dado el carácter semántico del modelo, permite incluir en las automatizaciones elementos de fuentes externas sobre los que razonar, como es el caso de Linked Open Data. Utilizando este modelo, se ha generado un dataset de canales y automatizaciones, con los datos obtenidos de algunos de los TAS existentes en el mercado. Como último paso hacia el lograr un modelo común para describir TAS, se ha desarrollado un algoritmo para aprender ontologías de forma automática a partir de los datos del dataset. De esta forma, se favorece el descubrimiento de nuevos canales, y se reduce el coste de mantenimiento del modelo, el cual se actualiza de forma semi-automática. En conclusión, las principales contribuciones de esta tesis son: i) describir el estado del arte en automatización de tareas y acuñar el término Servicio de Automatización de Tareas, ii) desarrollar una ontología para el modelado de los componentes de TASs y automatizaciones, iii) poblar un dataset de datos de canales y automatizaciones, usado para desarrollar un algoritmo de aprendizaje automatico de ontologías, y iv) diseñar una arquitectura de agentes para la asistencia a usuarios en la creación de automatizaciones. ABSTRACT The new stage in the evolution of the Web (the Live Web or Evented Web) puts lots of social data-streams at the service of users, who no longer browse static web pages but interact with applications that present them contextual and relevant experiences. Given that each user is a potential source of events, a typical user often gets overwhelmed. To deal with that huge amount of data, multiple automation tools have emerged, covering from simple social media managers or notification aggregators to complex CRMs or smart-home Hub/Apps. As a downside, they cannot tailor to the needs of every single user. As a natural response to this downside, Task Automation Services broke in the Internet. They may be seen as a new model of mash-up technology for combining social streams, services and connected devices from an end-user perspective: end-users are empowered to connect those stream however they want, designing the automations they need. The numbers of those platforms that appeared early on shot up, and as a consequence the amount of platforms following this approach is growing fast. Being a novel field, this thesis aims to shed light on it, presenting and exemplifying the main characteristics of Task Automation Services, describing their components, and identifying several dimensions to classify them. This thesis coins the term Task Automation Services (TAS) by providing a formal definition of them, their components (called channels), as well a TAS reference architecture. There is also a lack of tools for describing automation services and automations rules. In this regard, this thesis proposes a theoretical common model of TAS and formalizes it as the EWE ontology This model enables to compare channels and automations from different TASs, which has a high impact in interoperability; and enhances automations providing a mechanism to reason over external sources such as Linked Open Data. Based on this model, a dataset of components of TAS was built, harvesting data from the web sites of actual TASs. Going a step further towards this common model, an algorithm for categorizing them was designed, enabling their discovery across different TAS. Thus, the main contributions of the thesis are: i) surveying the state of the art on task automation and coining the term Task Automation Service; ii) providing a semantic common model for describing TAS components and automations; iii) populating a categorized dataset of TAS components, used to learn ontologies of particular domains from the TAS perspective; and iv) designing an agent architecture for assisting users in setting up automations, that is aware of their context and acts in consequence.

Electroencephalogram based Causality Graph Analysis in Behavior Tasks of Parkinson’s Disease Patients

Electroencephalographic (EEG) signals of the human brains represent electrical activities for a number of channels recorded over a the scalp. The main purpose of this thesis is to investigate the interactions and causality of different parts of a brain using EEG signals recorded during a performance subjects of verbal fluency tasks. Subjects who have Parkinson's Disease (PD) have difficulties with mental tasks, such as switching between one behavior task and another. The behavior tasks include phonemic fluency, semantic fluency, category semantic fluency and reading fluency. This method uses verbal generation skills, activating different Broca's areas of the Brodmann's areas (BA44 and BA45). Advanced signal processing techniques are used in order to determine the activated frequency bands in the granger causality for verbal fluency tasks. The graph learning technique for channel strength is used to characterize the complex graph of Granger causality. Also, the support vector machine (SVM) method is used for training a classifier between two subjects with PD and two healthy controls. Neural data from the study was recorded at the Colorado Neurological Institute (CNI). The study reveals significant difference between PD subjects and healthy controls in terms of brain connectivities in the Broca's Area BA44 and BA45 corresponding to EEG electrodes. The results in this thesis also demonstrate the possibility to classify based on the flow of information and causality in the brain of verbal fluency tasks. These methods have the potential to be applied in the future to identify pathological information flow and causality of neurological diseases.

Dynamic visual servo control of a 4-axis joint tool to track image trajectories during machining complex shapes

A large part of the new generation of computer numerical control systems has adopted an architecture based on robotic systems. This architecture improves the implementation of many manufacturing processes in terms of flexibility, efficiency, accuracy and velocity. This paper presents a 4-axis robot tool based on a joint structure whose primary use is to perform complex machining shapes in some non-contact processes. A new dynamic visual controller is proposed in order to control the 4-axis joint structure, where image information is used in the control loop to guide the robot tool in the machining task. In addition, this controller eliminates the chaotic joint behavior which appears during tracking of the quasi-repetitive trajectories required in machining processes. Moreover, this robot tool can be coupled to a manipulator robot in order to form a multi-robot platform for complex manufacturing tasks. Therefore, the robot tool could perform a machining task using a piece grasped from the workspace by a manipulator robot. This manipulator robot could be guided by using visual information given by the robot tool, thereby obtaining an intelligent multi-robot platform controlled by only one camera.

A formal framework for modelling complex network management systems

Society today is completely dependent on computer networks, the Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Subconsciously, we rely increasingly on network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect, and enhance the main distributed systems. Their role is secondary and is unknown and transparent to the users. They provide the necessary support to maintain the distributed systems whose services we use every day. If we do not consider network management systems during the development stage of distributed systems, then there could be serious consequences or even total failures in the development of the distributed system. It is necessary, therefore, to consider the management of the systems within the design of the distributed systems and to systematise their design to minimise the impact of network management in distributed systems projects. In this paper, we present a framework that allows the design of network management systems systematically. To accomplish this goal, formal modelling tools are used for modelling different views sequentially proposed of the same problem. These views cover all the aspects that are involved in the system; based on process definitions for identifying responsible and defining the involved agents to propose the deployment in a distributed architecture that is both feasible and appropriate.

Conceptual Modelling of Complex Network Management Systems

Society, as we know it today, is completely dependent on computer networks, Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Moreover, and unconsciously, all services and distributed systems require network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect or improve the main distributed systems. Their role is secondary and is unknown and transparent to the users. They provide the necessary support to maintain the distributed systems whose services we use every day. If we don’t consider network management systems during the development stage of main distributed systems, then there could be serious consequences or even total failures in the development of the distributed systems. It is necessary, therefore, to consider the management of the systems within the design of distributed systems and systematize their conception to minimize the impact of the management of networks within the project of distributed systems. In this paper, we present a formalization method of the conceptual modelling for design of a network management system through the use of formal modelling tools, thus allowing from the definition of processes to identify those responsible for these. Finally we will propose a use case to design a conceptual model intrusion detection system in network.

The mismatch negativity (MMN) response to complex tones and spoken words in individuals with aphasia

Background: The mismatch negativity (MMN) is a fronto-centrally distributed event-related potential (ERP) that is elicited by any discriminable auditory change. It is an ideal neurophysiological tool for measuring the auditory processing skills of individuals with aphasia because it can be elicited even in the absence of attention. Previous MMN studies have shown that acoustic processing of tone or pitch deviance is relatively preserved in aphasia, whereas the basic acoustic processing of speech stimuli can be impaired (e.g., auditory discrimination). However, no MMN study has yet investigated the higher levels of auditory processing, such as language-specific phonological and/or lexical processing, in individuals with aphasia. Aims: The aim of the current study was to investigate the MMN response of normal and language-disordered subjects to tone stimuli and speech stimuli that incorporate the basic auditory processing (acoustic, acoustic-phonetic) levels of non-speech and speech sound processing, and also the language-specific phonological and lexical levels of spoken word processing. Furthermore, this study aimed to correlate the aphasic MMN data with language performance on a variety of tasks specifically targeted at the different levels of spoken word processing. Methods M Procedures: Six adults with aphasia (71.7 years +/- 3.0) and six healthy age-, gender-, and education-matched controls (72.2 years +/- 5.4) participated in the study. All subjects were right-handed and native speakers of English. Each subject was presented with complex harmonic tone stimuli, differing in pitch or duration, and consonant-vowel (CV) speech stimuli (non-word /de:/versus real world/deI/). The probability of the deviant for each tone or speech contrast was 10%. The subjects were also presented with the same stimuli in behavioural discrimination tasks, and were administered a language assessment battery to measure their auditory comprehension skills. Outcomes O Results: The aphasic subjects demonstrated attenuated MMN responses to complex tone duration deviance and to speech stimuli (words and non-words), and their responses to the frequency, duration, and real word deviant stimuli were found to strongly correlate with performance on the auditory comprehension section of the Western Aphasia Battery (WAB). Furthermore, deficits in attentional lexical decision skills demonstrated by the aphasic subjects correlated with a word-related enhancement demonstrated during the automatic MMN paradigm, providing evidence to support the word advantage effect, thought to reflect the activation of language-specific memory traces in the brain for words. Conclusions: These results indicate that the MMN may be used as a technique for investigating general and more specific auditory comprehension skills of individuals with aphasia, using speech and/or non-speech stimuli, independent of the individual's attention. The combined use of the objective MMN technique and current clinical language assessments may result in improved rehabilitative management of aphasic individuals.

Adults with dyslexia exhibit large effects of crowding, increased dependence on cues, and detrimental effects of distractors in visual search tasks

Difficulties in visual attention are increasingly being linked to dyslexia. To date, the majority of studies have inferred functionality of attention from response times to stimuli presented for an indefinite duration. However, in paradigms that use reaction times to investigate the ability to orient attention, a delayed reaction time could also indicate difficulties in signal enhancement or noise exclusion once oriented. Thus, in order to investigate attention modulation and visual crowding effects in dyslexia, this study measured stimulus discrimination accuracy to rapidly presented displays. Adults with dyslexia (AwD) and controls discriminated the orientation of a target in an array of different numbers of - and differently spaced - vertically orientated distractors. Results showed that AwD: were disproportionately impacted by (i) close spacing and (ii) increased numbers of stimuli, (iii) did use pre-cues to modulate attention, but (iv) used cues less successfully to counter effects of increasing numbers of distractors. A greater dependence on pre-cues, larger effects of crowding and the impact of increased numbers of distractors all correlated significantly with measures of literacy. These findings extend previous studies of visual crowding of letters in dyslexia to non-complex stimuli. Overall, AwD do not use cues less, but they do use cues less successfully. We conclude that visual attention is an important factor to consider in the aetiology of dyslexia. The results challenge existing theoretical accounts of visual attention deficits, which alone are unable to comprehensively explain the pattern of findings demonstrated here.

Peculiarities of the Electronic Educational and Methodological Complex under the Point-rating Technology

At present in the sphere of electronic learning in the light of solving tasks put by the Bologna Declaration an important place is being taken by electronic educational and methodological complexes (EMC).The authors have put forward new components of EMC necessary for the organization of educational process and for the determination of labour intensity according to modules and students’ activity type. They also suggested a technology of defining the rating of the grade in the credit-module system.

Development of Procedures of Recognition of Objects with Usage Multisensor Ontology Controlled Instrumental Complex

The ontological approach to structuring knowledge and the description of data domain of knowledge is considered. It is described tool ontology-controlled complex for research and developments of sensor systems. Some approaches to solution most frequently meeting tasks are considered for creation of the recognition procedures.

Biomedical relation extraction:from binary to complex

Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are crucial for virtually every process in a living cell. Information about these interactions provides the foundations for new therapeutic approaches. In recent years, more interests have been shifted to the extraction of complex relations such as biomolecular events. While complex relations go beyond binary relations and involve more than two arguments, they might also take another relation as an argument. In the paper, we conduct a thorough survey on the research in biomedical relation extraction. We first present a general framework for biomedical relation extraction and then discuss the approaches proposed for binary and complex relation extraction with focus on the latter since it is a much more difficult task compared to binary relation extraction. Finally, we discuss challenges that we are facing with complex relation extraction and outline possible solutions and future directions.

Introduction of novel video-based tasks to clinical fMRI: Comparing traditional fMRI tasks with novel video-based tasks for mapping brain language areas

Recently, blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has become a routine clinical procedure for localization of language and motor brain regions and has been replacing more invasive preoperative procedures. However, the fMRI results from these tasks are not always reproducible even from the same patient. Evaluating the reproducibility of language and speech mapping is especially complicated due to the complex brain circuitry that may become activated during the functional task. Non-language areas such as sensory, attention, decision-making, and motor brain regions may also be activated in addition to the specific language regions during a traditional sentence-completion task. In this study, I test a new approach, which utilizes 4-minute video-based tasks, to map language and speech brain regions for patients undergoing brain surgery. Results from 35 subjects have shown that the video-based task activates Wernicke’s area, as well as Broca’s area in most subjects. The computed laterality indices, which indicate the dominant hemisphere from that functional task, have indicated left dominance from the video-based tasks. This study has shown that the video-based task may be an alternative method for localization of language and speech brain regions for patients who are unable to complete the sentence-completion task.

Detecting conflictive cultural factors in complex scenarios of intervention: Military and local actors in interaction

The integration of cultural elements into the operational planning process is a complex task that requires practical and theroretical tools for a wide comprehension of the context to help solve the problem. This article shows the results of an empirical research which presents conflicting cultural factors as the starting point for the construction of mediating structures. The main result of our research is a partial cognitive structure, a system of ideas, represented in a template listing the basic conflictive factors at the tactical level that military could find in the development of their tasks. The template is also a valuable aid to design military training curricula and to be applied to any post-conflict stability operation in complex environments resulting from irregular or asymmetric conflicts.

Using GeoGebra to study complex functions

The aim of this workshop to present some of the strategies studied to use GeoGebra in the analysis of complex functions. The proposed tasks focus on complex analysis topics target for students of the 1st year of higher education, which can be easily adapted to pre-university students. In the first part of this workshop we will illustrate how to use the two graphical windows of GeoGebra to represent complex functions of complex variable. The second part will present the use of the dynamic color Geogebra in order to obtain Coloring domains that correspond to the graphic representation of complex functions. Finally, we will use the threedimensional graphics window in GeoGebra to study the component functions of a complex function. During the workshop will be provided scripts orientation of the different tasks proposed to be held on computers with Geogebra version 5.0 or high.

Decoding complex flow phenomena via Dynamic Mode Decomposition

In this thesis, the viability of the Dynamic Mode Decomposition (DMD) as a technique to analyze and model complex dynamic real-world systems is presented. This method derives, directly from data, computationally efficient reduced-order models (ROMs) which can replace too onerous or unavailable high-fidelity physics-based models. Optimizations and extensions to the standard implementation of the methodology are proposed, investigating diverse case studies related to the decoding of complex flow phenomena. The flexibility of this data-driven technique allows its application to high-fidelity fluid dynamics simulations, as well as time series of real systems observations. The resulting ROMs are tested against two tasks: (i) reduction of the storage requirements of high-fidelity simulations or observations; (ii) interpolation and extrapolation of missing data. The capabilities of DMD can also be exploited to alleviate the cost of onerous studies that require many simulations, such as uncertainty quantification analysis, especially when dealing with complex high-dimensional systems. In this context, a novel approach to address parameter variability issues when modeling systems with space and time-variant response is proposed. Specifically, DMD is merged with another model-reduction technique, namely the Polynomial Chaos Expansion, for uncertainty quantification purposes. Useful guidelines for DMD deployment result from the study, together with the demonstration of its potential to ease diagnosis and scenario analysis when complex flow processes are involved.

Direct Visualization Of The Action Of Triton X-100 On Giant Vesicles Of Erythrocyte Membrane Lipids.

The raft hypothesis proposes that microdomains enriched in sphingolipids, cholesterol, and specific proteins are transiently formed to accomplish important cellular tasks. Equivocally, detergent-resistant membranes were initially assumed to be identical to membrane rafts, because of similarities between their compositions. In fact, the impact of detergents in membrane organization is still controversial. Here, we use phase contrast and fluorescence microscopy to observe giant unilamellar vesicles (GUVs) made of erythrocyte membrane lipids (erythro-GUVs) when exposed to the detergent Triton X-100 (TX-100). We clearly show that TX-100 has a restructuring action on biomembranes. Contact with TX-100 readily induces domain formation on the previously homogeneous membrane of erythro-GUVs at physiological and room temperatures. The shape and dynamics of the formed domains point to liquid-ordered/liquid-disordered (Lo/Ld) phase separation, typically found in raft-like ternary lipid mixtures. The Ld domains are then separated from the original vesicle and completely solubilized by TX-100. The insoluble vesicle left, in the Lo phase, represents around 2/3 of the original vesicle surface at room temperature and decreases to almost 1/2 at physiological temperature. This chain of events could be entirely reproduced with biomimetic GUVs of a simple ternary lipid mixture, 2:1:2 POPC/SM/chol (phosphatidylcholine/sphyngomyelin/cholesterol), showing that this behavior will arise because of fundamental physicochemical properties of simple lipid mixtures. This work provides direct visualization of TX-100-induced domain formation followed by selective (Ld phase) solubilization in a model system with a complex biological lipid composition.