856 resultados para Language and Communication Technologies


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In Europe, Cardiovascular Diseases (CVD) are the leading source of death, causing 45% of all deceases. Besides, Heart Failure, the paradigm of CVD, mainly affects people older than 65. In the current aging society, the European MyHeart Project was created, whose mission is to empower citizens to fight CVD by leading a preventive lifestyle and being able to be diagnosed at an early stage. This paper presents the development of a Heart Failure Management System, based on daily monitoring of Vital Body Signals, with wearable and mobile technologies, for the continuous assessment of this chronic disease. The System makes use of the latest technologies for monitoring heart condition, both with wearable garments (e.g. for measuring ECG and Respiration); and portable devices (such as Weight Scale and Blood Pressure Cuff) both with Bluetooth capabilities

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Coal is the most plentiful and evenly distributed fossil fuel worldwide. Based on current production, it is estimated that the reserves will last approximately 130 years. Its use worldwide has been increasing, mainly due to consumption by emerging countries. CO2 emissions generated by combustion and the repercussions of such on climate change support the view that it could no longer be used. CO2 capture may be the solution to continue using it, which would cater for the growing energy demand worldwide. The aim of this study is to compare different processes concerning CO2 capture that may be economically viable, ultimately showing that coal, a fossil energy source widely distributed around the world, can, as a result of using different CO2 capture processes, be used as a clean source of electricity. Hence, in places where geological hurdles may render the costs of CO2 storage considerably higher, since it might have to travel far, coal may be used for other purposes, thus valorising CO2 within the industrial sector. This research is focused on the technical and economic comparison of the most relevant CO2 capture projects designed in Spain using different existing technologies. The oxyfuel project in Ciuden (Leon, Spain), the IGCC Elcogas, precombustion CO2-capture project (Puertollano, Spain) and the postcombustion project in Carboneras (Almeria, Spain) will be analyzed in order to assess the options available to valorise captured CO2. Valorising captured CO2 may be an adequate solution in areas where, although CO2 capture is still possible, storage is not equally so, thus generating a further benefit. The possible uses of CO2 will be assessed in vegetable growing greenhouses, harnessing CO2 in vegetable life cycles. This will also be used in growing algae for subsequent biodiesel production. Both CO2 capture and valorising will eventually lead to the clean use of coal, which will thus enhance the level of self-supply, aiding the development of electric vehicles, which require large amounts of electricity, as well as improve the level of energy autonomy in countries around the world. Another type of fuel, biodiesel, will also be obtained, without this affecting international food prices.

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The TALISMAN+ project, financed by the Spanish Ministry of Science and Innovation, aims to research and demonstrate innovative solutions transferable to society which offer services and products based on information and communication technologies in order to promote personal autonomy in prevention and monitoring scenarios. It will solve critical interoperability problems among systems and emerging technologies in a context where heterogeneity brings about accessibility barriers not yet overcome and demanded by the scientific, technological or social-health settings.

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Coal is the most plentiful and evenly distributed fossil fuel worldwide. Based on current production, it is estimated that the reserves will last approximately 130 years. Its use worldwide has been increasing, mainly due to consumption by emerging countries. CO2 emissions generated by combustion and the repercussions of such on climate change support the view that it could no longer be used. CO2 capture may be the solution to continue using it, which would cater for the growing energy demand worldwide. The aim of this study is to compare different processes concerning CO2 capture that may be economically viable, ultimately showing that coal, a fossil energy source widely distributed around the world, can, as a result of using different CO2 capture processes, be used as a clean source of electricity. Hence, in places where geological hurdles may render the costs of CO2 storage considerably higher, since it might have to travel far, coal may be used for other purposes, thus valorizing CO2 within the industrial sector. This research is focused on the technical and economic comparison of the most relevant CO2 capture projects designed in Spain using different existing technologies. The oxyfuel project in Ciuden (Leon, Spain), the IGCC Elcogas, precombustion CO2-capture project (Puertollano, Spain) and the postcombustion project in Carboneras (Almeria, Spain) will be analyzed in order to assess the options available to valorizecaptured CO2. Valorizing captured CO2 may be an adequate solution in areas where, although CO2 capture is still possible, storage is not equally so, thus generating a further benefit. The possible uses of CO2 will be assessed in vegetable growing greenhouses, harnessing CO2 in vegetable life cycles. This will also be used in growing algae for subsequent biodiesel production. Both CO2capture and valorizing will eventually lead to the clean use of coal, which will thus enhance the level of self-supply, aiding the development of electric vehicles, which require large amounts of electricity, as well as improve the level of energy autonomy in countries around the world. Another type of fuel, biodiesel, will also be obtained, without this affecting international food prices.

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We describe some of the novel aspects and motivations behind the design and implementation of the Ciao multiparadigm programming system. An important aspect of Ciao is that it provides the programmer with a large number of useful features from different programming paradigms and styles, and that the use of each of these features can be turned on and off at will for each program module. Thus, a given module may be using e.g. higher order functions and constraints, while another module may be using objects, predicates, and concurrency. Furthermore, the language is designed to be extensible in a simple and modular way. Another important aspect of Ciao is its programming environment, which provides a powerful preprocessor (with an associated assertion language) capable of statically finding non-trivial bugs, verifying that programs comply with specifications, and performing many types of program optimizations. Such optimizations produce code that is highly competitive with other dynamic languages or, when the highest levéis of optimization are used, even that of static languages, all while retaining the interactive development environment of a dynamic language. The environment also includes a powerful auto-documenter. The paper provides an informal overview of the language and program development environment. It aims at illustrating the design philosophy rather than at being exhaustive, which would be impossible in the format of a paper, pointing instead to the existing literature on the system.

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This issue's Works-In-Progress department has four entries related to the issue's theme, Information and Communication Technologies for Development (ICTD). They are “Sustainable ICT in Agricultural Value Chains”, “Measuring Social Inclusion in Primary Schools”, “An Architecture for Green Mobile Computation”, and “Improving Communication in Resource-Poor Settings”. A fifth entry, “mFeel: An Affective Mobile System”, covers the mFeel mobile system, which combines context awareness with affective and cognitive techniques.

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In this Master’s Thesis a new Distributed Award Protocol (DAP) for robot communication and cooperation is presented. Task assignment (contract awarding) is done dynamically with contracts assigned to robots based upon the best bid received. Instead of having a manager and a contractor it is proposed a fully distributed bidding/awarding mechanism without a distinguished master. The best bidding robots are awarded with contract for execution. The contractors make decisions locally. This brings the following benefits: no communication bottleneck, low computational power requirement, increased robustness. DAP can handle multitasking. Tasks can be injected into system during the execution of already allocated tasks. As tasks have priorities, in the next cycle after taking into account actual bid parameters of all robots, tasks can be re-allocated. The aim is to minimize a global cost function which is a compromise between cost of task execution and cost of resources usage. Information about tasks and bid values is spread among robots with the use of a Round Robin Route, which is a novel solution proposed in this work. This method allows also identifying failed robots. Such failed robot is eliminated from the list of awarded robots and its replacement is found so the task is still executed by a team. If the failure of a robot was temporary (e.g. communication noise) and the robot can recover, it can again participate in the next bidding/awarding process. Using a bidding/awarding mechanism allows robots to dynamically relocate among tasks. This is also contributes to system robustness. DAP was evaluated through multiple experiments done in the multi-robot simulation system. Various scenarios were tested to check the idea of the main algorithm. Different failures of robots (communication failures, partial hardware malfunctions) were simulated and observations were made regarding how DAP recovers from them. Also the DAP flexibility to environment changes was watched. The experiments in the simulated environment confirmed the above features of DAP.

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Background: Healthy diet and regular physical activity are powerful tools in reducing diabetes and cardiometabolic risk. Various international scientific and health organizations have advocated the use of new technologies to solve these problems. The PREDIRCAM project explores the contribution that a technological system could offer for the continuous monitoring of lifestyle habits and individualized treatment of obesity as well as cardiometabolic risk prevention. Methods: PREDIRCAM is a technological platform for patients and professionals designed to improve the effectiveness of lifestyle behavior modifications through the intensive use of the latest information and communication technologies. The platform consists of a web-based application providing communication interface with monitoring devices of physiological variables, application for monitoring dietary intake, ad hoc electronic medical records, different communication channels, and an intelligent notification system. A 2-week feasibility study was conducted in 15 volunteers to assess the viability of the platform. Results: The website received 244 visits (average time/session: 17 min 45 s). A total of 435 dietary intakes were recorded (average time for each intake registration, 4 min 42 s ± 2 min 30 s), 59 exercises were recorded in 20 heart rate monitor downloads, 43 topics were discussed through a forum, and 11 of the 15 volunteers expressed a favorable opinion toward the platform. Food intake recording was reported as the most laborious task. Ten of the volunteers considered long-term use of the platform to be feasible. Conclusions: The PREDIRCAM platform is technically ready for clinical evaluation. Training is required to use the platform and, in particular, for registration of dietary food intake.

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There is an increasing tendency of turning the current power grid, essentially unaware of variations in electricity demand and scattered energy sources, into something capable of bringing a degree of intelligence by using tools strongly related to information and communication technologies, thus turning into the so-called Smart Grid. In fact, it could be considered that the Smart Grid is an extensive smart system that spreads throughout any area where power is required, providing a significant optimization in energy generation, storage and consumption. However, the information that must be treated to accomplish these tasks is challenging both in terms of complexity (semantic features, distributed systems, suitable hardware) and quantity (consumption data, generation data, forecasting functionalities, service reporting), since the different energy beneficiaries are prone to be heterogeneous, as the nature of their own activities is. This paper presents a proposal on how to deal with these issues by using a semantic middleware architecture that integrates different components focused on specific tasks, and how it is used to handle information at every level and satisfy end user requests.

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Currently, student dropout rates are a matter of concern among universities. Many research studies, aimed at discovering the causes, have been carried out. However, few solutions, that could serve all students and related problems, have been proposed so far. One such problem is caused by the lack of the "knowledge chain educational links" that occurs when students move onto higher studies without mastering their basic studies. Most regulated studies imparted at universities are designed so that some basic subjects serve as support for other, more complicated, subjects, thus forming a complicated knowledge network. When a link in this chain fails, student frustration occurs as it prevents him from fully understanding the following educational links. In this proposal we try to mitigate these disasters that stem, for the most part, the student?s frustration beyond his college stay. On one hand, we make a dissertation on the student?s learning process, which we divide into a series of phases that amount to what we call the "learning lifecycle." Also, we analyze at what stage the action by the stakeholders involved in this scenario: teachers and students; is most important. On the other hand, we consider that Information and Communication Technologies ICT, such as Cloud Computing, can help develop new ways, allowing for the teaching of higher education, while easing and facilitating the student?s learning process. But, methods and processes need to be defined as to direct the use of such technologies; in the teaching process in general, and within higher education in particular; in order to achieve optimum results. Our methodology integrates, as another actor, the ICT into the "Learning Lifecycle". We stimulate students to stop being merely spectators of their own education, and encourage them to take an active part in their training process. To do this, we offer a set of useful tools to determine not only academic failure causes, (for self assessment), but also to remedy these failures (with corrective actions); "discovered the causes it is easier to determine solutions?. We believe this study will be useful for both students and teachers. Students learn from their own experience and improve their learning process, while obtaining all of the "knowledge chain educational links? required in their studies. We stand by the motto "Studying to learn instead of studying to pass". Teachers will also be benefited by detecting where and how to strengthen their teaching proposals. All of this will also result in decreasing dropout rates.

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Grid connected solar plants are a good opportunity for their use for research as a secondary objective. In countries were feed-in tariffs are still active, it is possible to include in the design of the solar plant elements for its use for research. In the case of the solar plant presented here both objectives are covered. The solar plant of this work is formed by PV modules of three different technologies: Multicrystalline, amorphous and CdTe. In one part of the solar plant, the three technologies are working at the same conditions, not only ambient conditions but also similar voltage and current input to the inverters. Both the commercial and the experimental parts of the solar plant have their own independent inverters with their meters but are finally connected to the same meter to inject. In this work we analyse the results for the first year of operation of the experimental solar plant. Productions of three different technologies in exactly the same conditions are compared and presented. According to the results, all the three technologies have conversion efficiencies dropping when the temperature increases. Amorphous module experiences the lesser reduction, whereas the multicrystalline module suffers the most.

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An important part of human intelligence, both historically and operationally, is our ability to communicate. We learn how to communicate, and maintain our communicative skills, in a society of communicators – a highly effective way to reach and maintain proficiency in this complex skill. Principles that might allow artificial agents to learn language this way are in completely known at present – the multi-dimensional nature of socio-communicative skills are beyond every machine learning framework so far proposed. Our work begins to address the challenge of proposing a way for observation-based machine learning of natural language and communication. Our framework can learn complex communicative skills with minimal up-front knowledge. The system learns by incrementally producing predictive models of causal relationships in observed data, guided by goal-inference and reasoning using forward-inverse models. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime TV-style interview, using multimodal communicative gesture and situated language to talk about recycling of various materials and objects. S1 can learn multimodal complex language and multimodal communicative acts, a vocabulary of 100 words forming natural sentences with relatively complex sentence structure, including manual deictic reference and anaphora. S1 is seeded only with high-level information about goals of the interviewer and interviewee, and a small ontology; no grammar or other information is provided to S1 a priori. The agent learns the pragmatics, semantics, and syntax of complex utterances spoken and gestures from scratch, by observing the humans compare and contrast the cost and pollution related to recycling aluminum cans, glass bottles, newspaper, plastic, and wood. After 20 hours of observation S1 can perform an unscripted TV interview with a human, in the same style, without making mistakes.

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We present a methodology for legacy language resource adaptation that generates domain-specific sentiment lexicons organized around domain entities described with lexical information and sentiment words described in the context of these entities. We explain the steps of the methodology and we give a working example of our initial results. The resulting lexicons are modelled as Linked Data resources by use of established formats for Linguistic Linked Data (lemon, NIF) and for linked sentiment expressions (Marl), thereby contributing and linking to existing Language Resources in the Linguistic Linked Open Data cloud.

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In the smart building control industry, creating a platform to integrate different communication protocols and ease the interaction between users and devices is becoming increasingly important. BATMP is a platform designed to achieve this goal. In this paper, the authors describe a novel mechanism for information exchange, which introduces a new concept, Parameter, and uses it as the common object among all the BATMP components: Gateway Manager, Technology Manager, Application Manager, Model Manager and Data Warehouse. Parameter is an object which represents a physical magnitude and contains the information about its presentation, available actions, access type, etc. Each component of BATMP has a copy of the parameters. In the Technology Manager, three drivers for different communication protocols, KNX, CoAP and Modbus, are implemented to convert devices into parameters. In the Gateway Manager, users can control the parameters directly or by defining a scenario. In the Application Manager, the applications can subscribe to parameters and decide the values of parameters by negotiating. Finally, a Negotiator is implemented in the Model Manager to notify other components about the changes taking place in any component. By applying this mechanism, BATMP ensures the simultaneous and concurrent communication among users, applications and devices.

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AFRICA BUILD (AB) is a Coordination Action project under the 7th European Framework Programme having the aim of improving the capacities for health research and education in Africa through Information and Communication Technologies (ICT). This project, started in 2012, has promoted health research, education and evidence-based practice in Africa through the creation of centers of excellence, by using ICT,?know-how?, eLearning and knowledge sharing, through Web-enabled virtual communities.