Context modelling for natural Human Computer Interaction applications in e-health

The conception of IoT (Internet of Things) is accepted as the future tendency of Internet among academia and industry. It will enable people and things to be connected at anytime and anyplace, with anything and anyone. IoT has been proposed to be applied into many areas such as Healthcare, Transportation，Logistics, and Smart environment etc. However, this thesis emphasizes on the home healthcare area as it is the potential healthcare model to solve many problems such as the limited medical resources, the increasing demands for healthcare from elderly and chronic patients which the traditional model is not capable of. A remarkable change in IoT in semantic oriented vision is that vast sensors or devices are involved which could generate enormous data. Methods to manage the data including acquiring, interpreting, processing and storing data need to be implemented. Apart from this, other abilities that IoT is not capable of are concluded, namely, interoperation, context awareness and security & privacy. Context awareness is an emerging technology to manage and take advantage of context to enable any type of system to provide personalized services. The aim of this thesis is to explore ways to facilitate context awareness in IoT. In order to realize this objective, a preliminary research is carried out in this thesis. The most basic premise to realize context awareness is to collect, model, understand, reason and make use of context. A complete literature review for the existing context modelling and context reasoning techniques is conducted. The conclusion is that the ontology-based context modelling and ontology-based context reasoning are the most promising and efficient techniques to manage context. In order to fuse ontology into IoT, a specific ontology-based context awareness framework is proposed for IoT applications. In general, the framework is composed of eight components which are hardware, UI (User Interface), Context modelling, Context fusion, Context reasoning, Context repository, Security unit and Context dissemination. Moreover, on the basis of TOVE (Toronto Virtual Enterprise), a formal ontology developing methodology is proposed and illustrated which consists of four stages: Specification & Conceptualization, Competency Formulation, Implementation and Validation & Documentation. In addition, a home healthcare scenario is elaborated by listing its well-defined functionalities. Aiming at representing this specific scenario, the proposed ontology developing methodology is applied and the ontology-based model is developed in a free and open-source ontology editor called Protégé. Finally, the accuracy and completeness of the proposed ontology are validated to show that this proposed ontology is able to accurately represent the scenario of interest.

Predicción de tráfico de contenedores a corto plazo mediante técnicas de minería de datos : redes neuronales artificiales y redes bayesianas

El correcto pronóstico en el ámbito de la logística de transportes es de vital importancia para una adecuada planificación de medios y recursos, así como de su optimización. Hasta la fecha los estudios sobre planificación portuaria se basan principalmente en modelos empíricos; que se han utilizado para planificar nuevas terminales y desarrollar planes directores cuando no se dispone de datos iniciales, analíticos; más relacionados con la teoría de colas y tiempos de espera con formulaciones matemáticas complejas y necesitando simplificaciones de las mismas para hacer manejable y práctico el modelo o de simulación; que requieren de una inversión significativa como para poder obtener resultados aceptables invirtiendo en programas y desarrollos complejos. La Minería de Datos (MD) es un área moderna interdisciplinaria que engloba a aquellas técnicas que operan de forma automática (requieren de la mínima intervención humana) y, además, son eficientes para trabajar con las grandes cantidades de información disponible en las bases de datos de numerosos problemas prácticos. La aplicación práctica de estas disciplinas se extiende a numerosos ámbitos comerciales y de investigación en problemas de predicción, clasificación o diagnosis. Entre las diferentes técnicas disponibles en minería de datos las redes neuronales artificiales (RNA) y las redes probabilísticas o redes bayesianas (RB) permiten modelizar de forma conjunta toda la información relevante para un problema dado. En el presente trabajo se han analizado dos aplicaciones de estos casos al ámbito portuario y en concreto a contenedores. En la Tesis Doctoral se desarrollan las RNA como herramienta para obtener previsiones de tráfico y de recursos a futuro de diferentes puertos, a partir de variables de explotación, obteniéndose valores continuos. Para el caso de las redes bayesianas (RB), se realiza un trabajo similar que para el caso de las RNA, obteniéndose valores discretos (un intervalo). El principal resultado que se obtiene es la posibilidad de utilizar tanto las RNA como las RB para la estimación a futuro de parámetros físicos, así como la relación entre los mismos en una terminal para una correcta asignación de los medios a utilizar y por tanto aumentar la eficiencia productiva de la terminal. Como paso final se realiza un estudio de complementariedad de ambos modelos a corto plazo, donde se puede comprobar la buena aceptación de los resultados obtenidos. Por tanto, se puede concluir que estos métodos de predicción pueden ser de gran ayuda a la planificación portuaria. The correct assets’ forecast in the field of transportation logistics is a matter of vital importance for a suitable planning and optimization of the necessary means and resources. Up to this date, ports planning studies were basically using empirical models to deal with new terminals planning or master plans development when no initial data are available; analytical models, more connected to the queuing theory and the waiting times, and very complicated mathematical formulations requiring significant simplifications to acquire a practical and easy to handle model; or simulation models, that require a significant investment in computer codes and complex developments to produce acceptable results. The Data Mining (DM) is a modern interdisciplinary field that include those techniques that operate automatically (almost no human intervention is required) and are highly efficient when dealing with practical problems characterized by huge data bases containing significant amount of information. These disciplines’ practical application extends to many commercial or research fields, dealing with forecast, classification or diagnosis problems. Among the different techniques of the Data Mining, the Artificial Neuronal Networks (ANN) and the probabilistic – or Bayesian – networks (BN) allow the joint modeling of all the relevant information for a given problem. This PhD work analyses their application to two practical cases in the ports field, concretely to container terminals. This PhD work details how the ANN have been developed as a tool to produce traffic and resources forecasts for several ports, based on exploitation variables to obtain continuous values. For the Bayesian networks case (BN), a similar development has been carried out, obtaining discreet values (an interval). The main finding is the possibility to use ANN and BN to estimate future needs of the port’s or terminal’s physical parameters, as well as the relationship between them within a specific terminal, that allow a correct assignment of the necessary means and, thus, to increase the terminal’s productive efficiency. The final step is a short term complementarily study of both models, carried out in order to verify the obtained results. It can thus be stated that these prediction methods can be a very useful tool in ports’ planning.

Reverse logistics practices for recovering mobile phones in Spain

The main objective of this article is to characterize the reverse logistics system for mobile phones in Spain. The study includes the characterization of the different actors involved in the reverse logistics system and the description of the most common logistics practices in the sector. We will also opose alternative practices for managing this complex reverse logistics system and finally, we analyse the challenges of the current reverse logistics model. Some alternatives for the current model are location of reception points for end-of-use mobiles, the need to legislate the secondhand mobile phone market, and the location of the necessary recycling centres according to current legislation.

Innnovation and new business models for the regional development: travel and transportation

Regional development could present different strategies: •Relocation of industry clusters •Foreign Direct Investment attraction •Innovation based on new business models The Regional Government of Madrid (3rd largest GDP in the EU) selected strategic industries to compete & innovate: •Travel & Transportation •Aerospace •Nanotech. & •Biotech. •ICTs. •Energy

Reverse logistics systems for waste generated throughout vehicles life-cycle

Waste produced during the service life of automobiles has received much less attention than end-of-life vehicles themselves. In this paper, we deal with the set up of a reverse logistics system for the collection and treatment of use-phase residues. First, the type of waste arising during vehicles? service life is characterized. Data were collected in collaboration with SIGRAUTO, the product stewardship organization in charge of vehicles? recovery in Spain. Next, three organizational models are proposed. The three alternatives are benchmarked and assessed from a double organizational and operational perspective for the particular case of the Madrid region in Spain

Methodologies for Designing and Developing New Concepts in Vertical Transportation

Escalator and moving walkway are multibody systems with a design of more than a century. Developed methodology allows studying and improving any subsystem of both systems. In addition, new concepts can be developed and tested without the necessity and cost of a real construction. CITEF (Railway Technologies Research Centre) has been modelling escalators for more than four years. Several complex and innovative models has been developed to characterize static, kinematic and dynamic escalator behaviour. The high number of mechanical elements that are part of escalators complicate modelling task. In this way, methodologies and tools have been developed in order to automate these task and saving computational and time costs. Developed methodologies have been validated with the results of comparing real measurements and simulated outputs from a dynamic model.

High-Speed Rail Versus Air Transportation: Case Study of Madrid–Barcelona, Spain.

Travel time savings, better quality of the supplied services, greater comfort for the users, and improved accessibility are the main factors of success of High Speed Rail(HSR)links. This paper presents the results from a revealed and stated preference survey conducted to both HSR and air transport users in the Madrid Barcelona corridor. The data gathered from the stated preference survey was used to calibrate a modal choice model aiming at explaining competition between HSR and air transportation in the corridor. From the model, the authors obtain that prices and service frequency are the most important variables to compete with the other mode. In addition, they found that check-in and security controls at the airport are a crucial variable for the users in their modal choice. Other policies, such as the improvement of parking facilities at the train stations, play a secondary role.

Transportation infrastructure impacts on firm location: the effect of a new metro line in the suburbs of Madrid

Firm location patterns emerge as a consequence of multiple factors, including firm considerations, labor force availability, market opportunities, and transportation costs. Many of these factors are influenced by changes in accessibility wrought by new transportation infrastructure. In this paper we use spatial statistical techniques and a micro-level data base to evaluate the effects of Madrid?s metro line 12 (known as Metrosur) expansion on business location patterns. The case study is the municipality of Alcorcon, which is served by the new metro line since 2003. Specifically, we explore the location patterns by different industry sectors, to evaluate if the new metro line has encouraged the emergence of a ?Metrosur spatial economy?. Our results indicate that the pattern of economic activity location is related to urban accessibility and that agglomeration, through economies of scale, also plays an important role. The results presented in this paper provide evidence useful to inform efficient transportation, urban, and regional economic planning.

Robustness and Recoverability in Transport Logistics

Abstract Transport is the foundation of any economy: it boosts economic growth, creates wealth, enhances trade, geographical accessibility and the mobility of people. Transport is also a key ingredient for a high quality of life, making places accessible and bringing people together. The future prosperity of our world will depend on the ability of all of its regions to remain fully and competitively integrated in the world economy. Efficient transport is vital in making this happen. Operations research can help in efficiently planning the design and operating transport systems. Planning and operational processes are fields that are rich in combinatorial optimization problems. These problems can be analyzed and solved through the application of mathematical models and optimization techniques, which may lead to an improvement in the performance of the transport system, as well as to a reduction in the time required for solving these problems. The latter aspect is important, because it increases the flexibility of the system: the system can adapt in a faster way to changes in the environment (i.e.: weather conditions, crew illness, failures, etc.). These disturbing changes (called disruptions) often enforce the schedule to be adapted. The direct consequences are delays and cancellations, implying many schedule adjustments and huge costs. Consequently, robust schedules and recovery plans must be developed in order to fight against disruptions. This dissertation makes contributions to two different fields: rail and air applications. Robust planning and recovery methods are presented. In the field of railway transport we develop several mathematical models which answer to RENFE’s (the major railway operator in Spain) needs: 1. We study the rolling stock assignment problem: here, we introduce some robust aspects in order to ameliorate some operations which are likely to fail. Once the rolling stock assignment is known, we propose a robust routing model which aims at identifying the train units’ sequences while minimizing the expected delays and human resources needed to perform the sequences. 2. It is widely accepted that the sequential solving approach produces solutions that are not global optima. Therefore, we develop an integrated and robust model to determine the train schedule and rolling stock assignment. We also propose an integrated model to study the rolling stock circulations. Circulations are determined by the rolling stock assignment and routing of the train units. 3. Although our aim is to develop robust plans, disruptions will be likely to occur and recovery methods will be needed. Therefore, we propose a recovery method which aims to recover the train schedule and rolling stock assignment in an integrated fashion all while considering the passenger demand. In the field of air transport we develop several mathematical models which answer to IBERIA’s (the major airline in Spain) needs: 1. We look at the airline-scheduling problem and develop an integrated approach that optimizes schedule design, fleet assignment and passenger use so as to reduce costs and create fewer incompatibilities between decisions. Robust itineraries are created to ameliorate misconnected passengers. 2. Air transport operators are continuously facing competition from other air operators and different modes of transport (e.g., High Speed Rail). Consequently, airline profitability is critically influenced by the airline’s ability to estimate passenger demands and construct profitable flight schedules. We consider multi-modal competition including airline and rail, and develop a new approach that estimates the demand associated with a given schedule; and generates airline schedules and fleet assignments using an integrated schedule design and fleet assignment optimization model that captures the impacts of schedule decisions on passenger demand.

Increasing the accuracy of positive displacement meters for the measurement of volume in liquid hydrocarbon logistics

Accuracy in the liquid hydrocarbons custody transfer is mandatory because it has a great economic impact. By far the most accurate meter is the positive displacement (PD) meter. Increasing such an accuracy may adversely affect the cost of the custody transfer, unless simple models are developed in order to lower the cost, which is the purpose of this work. PD meter consists of a fixed volume rotating chamber. For each turn a pulse is counted, hence, the measured volume is the number of pulses times the volume of the chamber. It does not coincide with the real volume, so corrections have to be made. All the corrections are grouped by a meter factor. Among corrections highlights the slippage flow. By solving the Navier-Stokes equations one can find an analytical expression for this flow. It is neither easy nor cheap to apply straightforward the slippage correction; therefore we have made a simple model where slippage is regarded as a single parameter with dimension of time. The model has been tested for several PD meters. In our careful experiments, the meter factor grows with temperature at a constant pace of 8?10?5?ºC?1. Be warned

Methodology for assessing regional economic impacts of charging HGVs in Spain: an integrated approach through a random utility based multiregional input-output and a road transportation network model

An integrated approach composed of a random utility-based multiregional input-output model and a road transport network model was developed for evaluating the application of a fee to heavy-goods vehicles (HGVs) in Spain. For this purpose, a distance-based charge scenario (in euros per vehicle kilometer) for HGVs was evaluated for a selected motorway network in Spain. Although the aim of this charging policy was to increase the efficiency of transport, the approach strongly identified direct and indirect impacts on the regional economy. Estimates of the magnitude and extent of indirect effects on aggregated macroeconomic indicators (employment and gross domestic product) are provided. The macroeconomic effects of the charging policy were found to be positive for some regions and negative for other regions.

Demo paper: tablet-based visualization of transportation data in Madrid using SPARQLStream

In this demo paper we describe an iOS-based application that allows visualizing live bus transport data in Madrid from static and streaming RDF endpoints, reusing the Web services provided by the bus transport authority in the city and wrapping them using SPARQLStream

Does high speed rail compete fairly with other transportation modes? Madrid-Barcelona case study

Transportation modes produce many external costs such as congestion, accidents, and environmental impacts (pollution, noise and so on). From the microeconomic theory it is well known that in order to maximize social welfare, transportation modes should internalize the marginal costs they produce. Allocative efficiency is achieved when all transportation modes are priced at their social marginal cost. The objective of this research is to evaluate to what extent different passenger transport modes internalize their social marginal costs. This analysis is important since it affects the competitiveness of the different transport modes for a given OD pair. The case study analyzed is the corridor Madrid-Barcelona in Spain and the different transport modes have been considered (cars, buses, high-speed train and air). The research calculates the marginal social cost per user for each transportation mode, and it compares it with the average fare—allowing for the effect of discriminatory taxes—currently paid by the users. The external costs are calculated according to the guidelines established by the European Union. The gap between the marginal social cost and the price paid by users will provide the extra cost per passenger that each transport mode should have to pay for internalizing the external cost it produces. The research shows that external costs already produced by road and air transport modes are much higher than those produced by rail. However, the results show that road transport already internalizes every external costs it produces because users pay high fuel taxes. In other words, although rail transportation produces lower external costs, road transportation pays more than it should on the basis of the social marginal costs. The results of this work might be of help for Europ ean policy actions to be undertaken in the future.

Analysis of alternative tendering mechanisms for transportation Public-Private Partnerships

This paper describes a theoretical model based primarily on transaction costs, for comparing the various tendering mechanisms used for transportation Public-Private Partnership (PPP) projects. In particular, the model contrasts negotiated procedures with the open procedure, as defined by the current European Union legislation on public tendering. The model includes both ex ante transaction costs (borne during the tendering stage) and ex post transaction costs (such as enforcement costs, re-negotiation costs, and costs arising from litigation between partners), explaining the trade-off between them. Generally speaking, it is assumed that the open procedure implies lower transaction costs ex ante, while the negotiated procedure reduces the probability of the appearance of new contingencies not foreseen in the contract, hence diminishing the expected value of transaction costs ex post. Therefore, the balance between ex ante and ex post transaction costs is the main criterion for deciding whether the open or negotiated procedure would be optimal. Notwithstanding, empirical evidence currently exists only on ex ante transaction costs in transportation infrastructure projects. This evidence has shown a relevant difference between the two procedures as far as ex ante costs are concerned, favouring the open procedure. The model developed in this paper also demonstrates that a larger degree of complexity in a contract does not unequivocally favour the use of a negotiated procedure. Only in those cases dealing with very innovative projects, where important dimensions of the quality of the asset or service are not verifiable, may we observe an advantage in favour of the negotiated procedure. The bottom line is that we find it difficult to justify the employment of negotiated procedures in most transportation PPP contracts, especially in the field of roads. Nevertheless, the field remains open for future empirical work and research on the levels of transaction costs borne ex post in PPP contracts, as well as on the probabilities of such costs appearing under any of the procurement procedures.