Using clustering techniques for intelligent camera-based user interfaces

The area of Human-Machine Interface is growing fast due to its high importance in all technological systems. The basic idea behind designing human-machine interfaces is to enrich the communication with the technology in a natural and easy way. Gesture interfaces are a good example of transparent interfaces. Such interfaces must identify properly the action the user wants to perform, so the proper gesture recognition is of the highest importance. However, most of the systems based on gesture recognition use complex methods requiring high-resource devices. In this work, we propose to model gestures capturing their temporal properties, which significantly reduce storage requirements, and use clustering techniques, namely self-organizing maps and unsupervised genetic algorithm, for their classification. We further propose to train a certain number of algorithms with different parameters and combine their decision using majority voting in order to decrease the false positive rate. The main advantage of the approach is its simplicity, which enables the implementation using devices with limited resources, and therefore low cost. The testing results demonstrate its high potential.

Integración de Fuentes con Información de Contexto y Sistemas Interactivos

Durante el transcurso de esta Tesis Doctoral se ha realizado un estudio de la problemática asociada al desarrollo de sistemas de interacción hombre-máquina sensibles al contexto. Este problema se enmarca dentro de dos áreas de investigación: los sistemas interactivos y las fuentes de información contextual. Tradicionalmente la integración entre ambos campos se desarrollaba a través de soluciones verticales específicas, que abstraen a los sistemas interactivos de conocer los procedimientos de bajo nivel de acceso a la información contextual, pero limitan su interoperabilidad con otras aplicaciones y fuentes de información. Para solventar esta limitación se hace imprescindible potenciar soluciones interoperables que permitan acceder a la información del mundo real a través de procedimientos homogéneos. Esta problemática coincide perfectamente con los escenarios de \Computación Ubicua" e \Internet de las Cosas", donde se apunta a un futuro en el que los objetos que nos rodean serán capaces de obtener información del entorno y comunicarla a otros objetos y personas. Los sistemas interactivos, al ser capaces de obtener información de su entorno a través de la interacción con el usuario, pueden tomar un papel especial en este escenario tanto como consumidores como productores de información. En esta Tesis se ha abordado la integración de ambos campos teniendo en cuenta este escenario tecnológico. Para ello, en primer lugar se ha realizado un an álisis de las iniciativas más importantes para la definición y diseño de sistemas interactivos, y de las principales infraestructuras de suministro de información. Mediante este estudio se ha propuesto utilizar el lenguaje SCXML del W3C para el diseño de los sistemas interactivos y el procesamiento de los datos proporcionados por fuentes de contexto. Así, se ha reflejado cómo las capacidades del lenguaje SCXML para combinar información de diferentes modalidades pueden también utilizarse para procesar e integrar información contextual de diferentes fuentes heterogéneas, y por consiguiente diseñar sistemas de interacción sensibles al contexto. Del mismo modo se presenta a la iniciativa Sensor Web, y a su extensión semántica Semantic Sensor Web, como una iniciativa idónea para permitir un acceso y suministro homogéneo de la información a los sistemas interactivos sensibles al contexto. Posteriormente se han analizado los retos que plantea la integración de ambos tipos de iniciativas. Como resultado se ha conseguido establecer una serie de funcionalidades que son necesarias implementar para llevar a cabo esta integración. Utilizando tecnologías que aportan una gran flexibilidad al proceso de implementación y que se apoyan en recomendaciones y estándares actuales, se implementaron una serie de desarrollos experimentales que integraban las funcionalidades identificadas anteriormente. Finalmente, con el fin de validar nuestra propuesta, se realizaron un conjunto de experimentos sobre un entorno de experimentación que simula el escenario de la conducción. En este escenario un sistema interactivo se comunica con una extensión semántica de una plataforma basada en los estándares de la Sensor Web para poder obtener información y publicar las observaciones que el usuario realizaba al sistema. Los resultados obtenidos han demostrado la viabilidad de utilizar el lenguaje SCXML para el diseño de sistemas interactivos sensibles al contexto que requieren acceder a plataformas avanzadas de información para consumir y publicar información a la vez que interaccionan con el usuario. Del mismo modo, se ha demostrado cómo la utilización de tecnologías semánticas en los procesos de consulta y publicación de información puede facilitar la reutilización de la información publicada en infraestructuras Sensor Web por cualquier tipo de aplicación, y de este modo contribuir al futuro escenario de Internet de las Cosas. ABSTRACT In this Thesis, we have addressed the difficulties related to the development of context-aware human-machine interaction systems. This issue is part of two research fields: interactive systems and contextual information sources. Traditionally both fields have been integrated through domain-specific vertical solutions that allow interactive systems to access contextual information without having to deal with low-level procedures, but restricting their interoperability with other applications and heterogeneous data sources. Thus, it is essential to boost the research on interoperable solutions that provide access to real world information through homogeneous procedures. This issue perfectly matches with the scenarios of \Ubiquitous Computing" and \Internet of Things", which point toward a future in which many objects around us will be able to acquire meaningful information about the environment and communicate it to other objects and to people. Since interactive systems are able to get information from their environment through interaction with the user, they can play an important role in this scenario as they can both consume real-world data and produce enriched information. This Thesis deals with the integration of both fields considering this technological scenario. In order to do this, we first carried out an analysis of the most important initiatives for the definition and design of interactive systems, and the main infrastructures for providing information. Through this study the use of the W3C SCXML language is proposed for both the design of interactive systems and the processing of data provided by different context sources. Thus, this work has shown how the SCXML capabilities for combining information from different modalities can also be used to process and integrate contextual information from different heterogeneous sensor sources, and therefore to develope context-aware interaction systems. Similarly, we present the Sensor Web initiative, and its semantic extension Semantic Sensor Web, as an appropriate initiative to allow uniform access and delivery of information to the context-aware interactive systems. Subsequently we have analyzed the challenges of integrating both types of initiatives: SCXML and (Semantic) Sensor Web. As a result, we state a number of functionalities that are necessary to implement in order to perform this integration. By using technologies that provide exibility to the implementation process and are based on current recommendations and standards, we implemented a series of experimental developments that integrate the identified functionalities. Finally, in order to validate our approach, we conducted different experiments with a testing environment simulating a driving scenario. In this framework an interactive system can access a semantic extension of a Telco plataform, based on the standards of the Sensor Web, to acquire contextual information and publish observations that the user performed to the system. The results showed the feasibility of using the SCXML language for designing context-aware interactive systems that require access to advanced sensor platforms for consuming and publishing information while interacting with the user. In the same way, it was shown how the use of semantic technologies in the processes of querying and publication sensor data can assist in reusing and sharing the information published by any application in Sensor Web infrastructures, and thus contribute to realize the future scenario of \Internet of Things".

Face encoding and recognition in the human brain.

A dissociation between human neural systems that participate in the encoding and later recognition of new memories for faces was demonstrated by measuring memory task-related changes in regional cerebral blood flow with positron emission tomography. There was almost no overlap between the brain structures associated with these memory functions. A region in the right hippocampus and adjacent cortex was activated during memory encoding but not during recognition. The most striking finding in neocortex was the lateralization of prefrontal participation. Encoding activated left prefrontal cortex, whereas recognition activated right prefrontal cortex. These results indicate that the hippocampus and adjacent cortex participate in memory function primarily at the time of new memory encoding. Moreover, face recognition is not mediated simply by recapitulation of operations performed at the time of encoding but, rather, involves anatomically dissociable operations.

Speech technology in the year 2001.

This paper introduces the session "Technology in the Year 2001" and is the first of four papers dealing with the future of human-machine communication by voice. In looking to the future it is important to recognize both the difficulties of technological forecasting and the frailties of the technology as it exists today--frailties that are manifestations of our limited scientific understanding of human cognition. The technology to realize truly advanced applications does not yet exist and cannot be supported by our presently incomplete science of speech. To achieve this long-term goal, the authors advocate a fundamental research program using a cybernetic approach substantially different from more conventional synthetic approaches. In a cybernetic approach, feedback control systems will allow a machine to adapt to a linguistically rich environment using reinforcement learning.

Toward the ultimate synthesis/recognition system.

This paper predicts speech synthesis, speech recognition, and speaker recognition technology for the year 2001, and it describes the most important research problems to be solved in order to arrive at these ultimate synthesis and recognition systems. The problems for speech synthesis include natural and intelligible voice production, prosody control based on meaning, capability of controlling synthesized voice quality and choosing individual speaking style, multilingual and multidialectal synthesis, choice of application-oriented speaking styles, capability of adding emotion, and synthesis from concepts. The problems for speech recognition include robust recognition against speech variations, adaptation/normalization to variations due to environmental conditions and speakers, automatic knowledge acquisition for acoustic and linguistic modeling, spontaneous speech recognition, naturalness and ease of human-machine interaction, and recognition of emotion. The problems for speaker recognition are similar to those for speech recognition. The research topics related to all these techniques include the use of articulatory and perceptual constraints and evaluation methods for measuring the quality of technology and systems.

3D visual sensing of human hand for remote operation of a robotic hand

New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.

Interoperability of Cross-Border European Egovernment Services: Some Design Issues

The authors analyse some of the research outcomes achieved during the implementation of the EC GUIDE research project “Creating an European Identity Management Architecture for eGovernment”, as well as their personal experience. The project goals and achievements are however considered in a broader context. The key role of Identity in the Information Society was emphasised, that the research and development in this field is in its initial phase. The scope of research related to Identity, including the one related to Identity Management and Interoperability of Identity Management Systems, is expected to be further extended. The authors analyse the abovementioned issues in the context established by the EC European Interoperability Framework (EIF) as a reference document on interoperability for the Interoperable Delivery of European eGovernment Services to Public Administrations, Business and Citizens (IDABC) Work Programme. This programme aims at supporting the pan-European delivery of electronic government services.

Human Capital Decisions and Employee Satisfaction at Selected Hotels in India

Understanding the role of human capital is one of the key considerations in delivering and sustaining competitiveness. Managing employees in the hospitality industry is particularly a challenging task as the industry is considered to be labor intensive. High turnover and increasing employee demands are among the problems that are identified as threats to maintaining a strong competitive position. Successful hotels attempt to retain their best employees in an effort to adapt to changing environments and increased competition. Effective hotel human resource systems can produce positive outcomes, through effective employee retention strategies that focus on work force motivation, attitudes and perception. The positive implementation of these strategies can influence and create employee satisfaction. This study aims to focus on the relationship between the mediating variables of motivation, attitudes, perception and their effect on employee satisfaction. These findings are based upon an extensive survey carried out between April 2009 and June 2009 in the small mountainous state of Uttarakhand, located within the Indian sub-continent. Although the area of study is confined to the Kumaon region of Uttarakhand, the authors contend that the findings and implications can be applied to other remote developing tourist destinations in other regions.

Human-driven benthic jellyfish blooms: Causes and consequences for coastal marine ecosystems

Coastal marine ecosystems are among the most impacted globally, attributable to individual and cumulative effects of human disturbance. Anthropogenic nutrient loading is one stressor that commonly affects nearshore ecosystems, including seagrass beds, and has positive and negative effects on the structure and function of coastal systems. An additional, previously unexplored mechanistic pathway through which nutrients may indirectly influence nearshore systems is by driving blooms of benthic jellyfish. My dissertation research, conducted on Abaco Island, Bahamas, focused on elucidating the role that benthic jellyfish have in structuring systems in which they are common (i.e., seagrass beds), and explored mechanistic processes that may drive blooms of this taxa. ^ To establish that human disturbances (e.g., elevated nutrient availability) may drive increased abundance and size of benthic jellyfish, Cassiopea spp., I conducted surveys in human-impacted and unimpacted coastal sites. Jellyfish were more abundant (and larger) from human-impacted areas, positively correlated to elevated nutrient availability. In order to elucidate mechanisms linking Cassiopea spp. with elevated nutrients, I evaluated whether zooxanthellae from Cassiopea were higher from human-disturbed systems, and whether Cassiopea exhibited increased size following nutrient input. I demonstrated that zooxanthellae population densities were elevated in human-impacted sites, and that nutrients led to positive jellyfish growth. ^ As heightened densities of Cassiopea jellyfish may exert top-down and bottom-up controls on flora and fauna in impacted seagrass beds, I sought to examine ecological responses to Cassiopea. I evaluated whether there was a relationship between high Cassiopea densities and lower benthic fauna abundance and diversity in shallow seagrass beds. I found that Cassiopea have subtle effects on benthic fauna. However, through an experiment conducted in a seagrass bed in which nutrients and Cassiopea were added, I demonstrated that Cassiopea can result in seagrass habitat modification, with negative consequences for benthic fauna. ^ My dissertation research demonstrates that increased human-driven benthic jellyfish densities may have indirect and direct effects on flora and fauna of coastal marine systems. This knowledge will advance our understanding of how human disturbances shift species interactions in coastal ecosystems, and will be critical for effective management of jellyfish blooms.^

Human-driven Benthic Jellyfish Blooms: Causes and Consequences for Coastal Marine Ecosystems

Coastal marine ecosystems are among the most impacted globally, attributable to individual and cumulative effects of human disturbance. Anthropogenic nutrient loading is one stressor that commonly affects nearshore ecosystems, including seagrass beds, and has positive and negative effects on the structure and function of coastal systems. An additional, previously unexplored mechanistic pathway through which nutrients may indirectly influence nearshore systems is by driving blooms of benthic jellyfish. My dissertation research, conducted on Abaco Island, Bahamas, focused on elucidating the role that benthic jellyfish have in structuring systems in which they are common (i.e., seagrass beds), and explored mechanistic processes that may drive blooms of this taxa. To establish that human disturbances (e.g., elevated nutrient availability) may drive increased abundance and size of benthic jellyfish, Cassiopea spp., I conducted surveys in human-impacted and unimpacted coastal sites. Jellyfish were more abundant (and larger) from human-impacted areas, positively correlated to elevated nutrient availability. In order to elucidate mechanisms linking Cassiopea spp. with elevated nutrients, I evaluated whether zooxanthellae from Cassiopea were higher from human-disturbed systems, and whether Cassiopea exhibited increased size following nutrient input. I demonstrated that zooxanthellae population densities were elevated in human-impacted sites, and that nutrients led to positive jellyfish growth. As heightened densities of Cassiopea jellyfish may exert top-down and bottom-up controls on flora and fauna in impacted seagrass beds, I sought to examine ecological responses to Cassiopea. I evaluated whether there was a relationship between high Cassiopea densities and lower benthic fauna abundance and diversity in shallow seagrass beds. I found that Cassiopea have subtle effects on benthic fauna. However, through an experiment conducted in a seagrass bed in which nutrients and Cassiopea were added, I demonstrated that Cassiopea can result in seagrass habitat modification, with negative consequences for benthic fauna. My dissertation research demonstrates that increased human-driven benthic jellyfish densities may have indirect and direct effects on flora and fauna of coastal marine systems. This knowledge will advance our understanding of how human disturbances shift species interactions in coastal ecosystems, and will be critical for effective management of jellyfish blooms.

Concept maps as a tool to analyze the ideas of teacher training students regarding what to teach on human nutrition in Primary Education

Concept maps are a technique used to obtain a visual representation of a person's ideas about a concept or a set of related concepts. Specifically, in this paper, through a qualitative methodology, we analyze the concept maps proposed by 52 groups of teacher training students in order to find out the characteristics of the maps and the degree of adequacy of the contents with regard to the teaching of human nutrition in the 3rd cycle of primary education. The participants were enrolled in the Teacher Training Degree majoring in Primary Education, and the data collection was carried out through a training activity under the theme of what to teach about Science in Primary School? The results show that the maps are a useful tool for working in teacher education as they allow organizing, synthesizing, and communicating what students know. Moreover, through this work, it has been possible to see that future teachers have acceptable skills for representing the concepts/ideas in a concept map, although the level of adequacy of concepts/ideas about human nutrition and its relations is usually medium or low. These results are a wake-up call for teacher training, both initial and ongoing, because they shows the inability to change priorities as far as the selection of content is concerned.

Optimización del software empotrado de los equipos HMI y sDIAG del TCMS COSMOS

Trabajo realizado en la empresa CAF Power&Automation

Motion Planning and Controls with Safety and Temporal Constraints

Motion planning, or trajectory planning, commonly refers to a process of converting high-level task specifications into low-level control commands that can be executed on the system of interest. For different applications, the system will be different. It can be an autonomous vehicle, an Unmanned Aerial Vehicle(UAV), a humanoid robot, or an industrial robotic arm. As human machine interaction is essential in many of these systems, safety is fundamental and crucial. Many of the applications also involve performing a task in an optimal manner within a given time constraint. Therefore, in this thesis, we focus on two aspects of the motion planning problem. One is the verification and synthesis of the safe controls for autonomous ground and air vehicles in collision avoidance scenarios. The other part focuses on the high-level planning for the autonomous vehicles with the timed temporal constraints. In the first aspect of our work, we first propose a verification method to prove the safety and robustness of a path planner and the path following controls based on reachable sets. We demonstrate the method on quadrotor and automobile applications. Secondly, we propose a reachable set based collision avoidance algorithm for UAVs. Instead of the traditional approaches of collision avoidance between trajectories, we propose a collision avoidance scheme based on reachable sets and tubes. We then formulate the problem as a convex optimization problem seeking control set design for the aircraft to avoid collision. We apply our approach to collision avoidance scenarios of quadrotors and fixed-wing aircraft. In the second aspect of our work, we address the high level planning problems with timed temporal logic constraints. Firstly, we present an optimization based method for path planning of a mobile robot subject to timed temporal constraints, in a dynamic environment. Temporal logic (TL) can address very complex task specifications such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints. We then translate the MTL formulae into mixed integer linear constraints and solve the associated optimization problem using a mixed integer linear program solver. We have applied our approach on several case studies in complex dynamical environments subjected to timed temporal specifications. Secondly, we also present a timed automaton based method for planning under the given timed temporal logic specifications. We use metric interval temporal logic (MITL), a member of the MTL family, to represent the task specification, and provide a constructive way to generate a timed automaton and methods to look for accepting runs on the automaton to find an optimal motion (or path) sequence for the robot to complete the task.

Data-stream driven Fuzzy-granular approaches for system maintenance

Intelligent systems are currently inherent to the society, supporting a synergistic human-machine collaboration. Beyond economical and climate factors, energy consumption is strongly affected by the performance of computing systems. The quality of software functioning may invalidate any improvement attempt. In addition, data-driven machine learning algorithms are the basis for human-centered applications, being their interpretability one of the most important features of computational systems. Software maintenance is a critical discipline to support automatic and life-long system operation. As most software registers its inner events by means of logs, log analysis is an approach to keep system operation. Logs are characterized as Big data assembled in large-flow streams, being unstructured, heterogeneous, imprecise, and uncertain. This thesis addresses fuzzy and neuro-granular methods to provide maintenance solutions applied to anomaly detection (AD) and log parsing (LP), dealing with data uncertainty, identifying ideal time periods for detailed software analyses. LP provides deeper semantics interpretation of the anomalous occurrences. The solutions evolve over time and are general-purpose, being highly applicable, scalable, and maintainable. Granular classification models, namely, Fuzzy set-Based evolving Model (FBeM), evolving Granular Neural Network (eGNN), and evolving Gaussian Fuzzy Classifier (eGFC), are compared considering the AD problem. The evolving Log Parsing (eLP) method is proposed to approach the automatic parsing applied to system logs. All the methods perform recursive mechanisms to create, update, merge, and delete information granules according with the data behavior. For the first time in the evolving intelligent systems literature, the proposed method, eLP, is able to process streams of words and sentences. Essentially, regarding to AD accuracy, FBeM achieved (85.64+-3.69)%; eGNN reached (96.17+-0.78)%; eGFC obtained (92.48+-1.21)%; and eLP reached (96.05+-1.04)%. Besides being competitive, eLP particularly generates a log grammar, and presents a higher level of model interpretability.