Viability assessment of WPS 2.0 services as communication standard for expensive web-based machine learning analysis. A case of study : Indoor Location

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesCommunication between client and server is a key factor in the modern age. Nowadays, telecommunications are at the base of every system and Software that is available. The way Software communicates can determine the efficacy of it. In the GIS world, a server is often used for offloading expensive tasks such as geospatial operations or statistical analysis. This technique improves the performance of the Software systems and makes them able to scale based on the demand on real time. For making the communication between client and server more efficient, interoperable and standard, the OGC released the standard WPS. WPS defines abstract operations that are able to describe a client server communication for remote process executions. This thesis focuses on the asynchronous execution feature introduced in the version 2.0 of WPS. The main goal is to study how asynchronous process execution can benefit a client both in performance and availability. The result are promising and it is demonstrated that WPS is a solid standard for describing web services operations. Based on the obtained results, future studies can extend the standard in order to make it more general and suitable for more situations

Diseño de una arquitectura para la integración de información semi-estructurada proveniente de páginas web y su mejora con contenido semántico

Treball Final de Grau en Enginyeria Informàtica. Codi: EI1054. Curs acadèmic 2013-2014En este documento se presenta una propuesta de arquitectura Software para el desarrollo de aplicaciones Web de extracción, transformación y distribución de información a partir de páginasWeb. En el proceso de transformación de los datos, éstos se amplían añadiendo contenido semántico (meta-datos). La información ampliada se distribuye en formato XML. La arquitectura propuesta se compone de módulos para la realización de las tareas necesarias. Con n demostrativo, se han creado dos aplicaciones Web, una para servir la información de los trenes de la Comunidad Valenciana y la otra para proporcionar información acerca del servicio de préstamo de bicis en Castellón Bicicas. Finalmente, se ha desarrollado un tercer proyecto para la integración de los dos anteriores en una aplicación Web para la plani cación de rutas de transporte intermodales

Design and construction of a distributed sensor NET for biotelemetric monitoring of brain energetic metabolism using microsensors and biosensors

Neurochemical pathways involved in brain physiology or disease pathogenesis are mostly unknown either in physiological conditions or in neurodegenerative diseases. Nowadays the most frequent usage for biotelemetry is in medicine, in cardiac care units or step-down units in hospitals, even if virtually any physiological signal could be transmitted (FCC, 2000; Leuher, 1983; Zhou et al., 2002). In this chapter we present a wireless device connected with microsensors and biosensors capable to detect real-time variations in concentrations of important compounds present in central nervous system (CNS) and implicated in brain energetic metabolism (Bazzu et al., 2009; Calia et al., 2009)

Chemically modified β-cyclodextrins useful in developing biosensors of agricultural and food relevance

β-cyclodextrin (β-CD), a natural, non-toxic cycloeptaamilose macrocycle, is a useful biomatrix for immobilizing enzymes on a biosensor surface because of the affinity of its cavity for hydrophobic guest molecules (e.g., aminoacids). In this work β-CD has been successfully modified with different poly-carboxylic acids (PCAs) including 1,2,3,4-butanetetracarboxylic acid. Time activation, pH, pressure and stoichiometry were optimized in order to achieve selected substitutions on the macrocycle hydroxy groups. The modified β-CDs, prepared under mild conditions, are completely water-soluble and could be grafted on a biosensor surface

Velocity Saturation effect on Low Frequency Noise in short channel Single Layer Graphene FETs

Graphene devices for analog and RF applications are prone to Low Frequency Noise (LFN) due to its upconversion to undesired phase noise at higher frequencies. Such applications demand the use of short channel graphene transistors that operate at high electric fields in order to ensure a high speed. Electric field is inversely proportional to device length and proportional to channel potential so it gets maximized as the drain voltage increases and the transistor length shrinks. Under these conditions though, short channel effects like Velocity Saturation (VS) should be taken into account. Carrier number and mobility fluctuations have been proved to be the main sources that generate LFN in graphene devices. While their contribution to the bias dependence of LFN in long channels has been thoroughly investigated, the way in which VS phenomenon affects LFN in short channel devices under high drain voltage conditions has not been well understood. At low electric field operation, VS effect is negligible since carriers velocity is far away from being saturated. Under these conditions, LFN can be precicely predicted by a recently established physics-based analytical model. The present paper goes a step furher and proposes a new model which deals with the contribution of VS effect on LFN under high electric field conditions. The implemented model is validated with novel experimental data, published for the first time, from CVD grown back-gated single layer graphene transistors operating at gigahertz frequencies. The model accurately captures the reduction of LFN especially near charge neutrality point because of the effect of VS mechanism. Moreover, an analytical expression for the effect of contact resistance on LFN is derived. This contact resistance contribution is experimentally shown to be dominant at higher gate voltages and is accurately described by the proposed model.Comment: Main Manuscript:10 pages, 6 figure

Understanding the Bias Dependence of Low Frequency Noise in Sin-gle Layer Graphene FETs

This letter investigates the bias-dependent low frequency noise of single layer graphene field-effect transistors. Noise measurements have been conducted with electrolyte-gated graphene transistors covering a wide range of gate and drain bias conditions for different channel lengths. A new analytical model that accounts for the propagation of the local noise sources in the channel to the terminal currents and voltages is proposed in this paper to investigate the noise bias dependence. Carrier number and mobility fluctuations are considered as the main causes of low frequency noise and the way these mechanisms contribute to the bias dependence of the noise is analyzed in this work. Typically, normalized low frequency noise in graphene devices has been usually shown to follow an M-shape dependence versus gate voltage with the minimum near the charge neutrality point (CNP). Our work reveals for the first time the strong correlation between this gate dependence and the residual charge which is relevant in the vicinity of this specific bias point. We discuss how charge inhomogeneity in the graphene channel at higher drain voltages can contribute to low frequency noise; thus, channel regions nearby the source and drain terminals are found to dominate the total noise for gate biases close to the CNP. The excellent agreement between the experimental data and the predictions of the analytical model at all bias conditions confirms that the two fundamental 1/f noise mechanisms, carrier number and mobility fluctuations, must be considered simultaneously to properly understand the low frequency noise in graphene FETs. The proposed analytical compact model can be easily implemented and integrated in circuit simulators, which can be of high importance for graphene based circuits design.Comment: 18 pages, 10 figure

In-home monitoring system based on WiFi fingerprints for ambient assisted living

This paper presents an in-home monitoring system based on WiFi fingerprints for Ambient Assisted Living. WiFi fingerprints are used to continuously locate a patient at the different rooms in her/his home. The experiments performed provide a correctly location rate of 96% in the best case of all studied scenarios. The behavior obtained by location monitoring allows to detect anomalous behavior such as long stays in rooms out of the common schedule. The main characteristics of the presented system are: a) it is robust enough to work without an own WiFi access point, which in turn means a very affordable solution; b) low obtrusiveness, as it is based on the use of a mobile phone; c) highly interoperable with other wireless connections (bluetooth, RFID) present in current mobile phones; d) alarms are triggered when any anomalous behavior is detected

Deployment of an open sensorized platform in a smart city context

The race to achieve smart cities is producing a continuous effort to adapt new developments and knowledge, for administrations and citizens. Information and Communications Technology are called on to be one of the key players to get these cities to use smart devices and sensors (Internet of Things) to know at every moment what is happening within the city, in order to make decisions that will improve the management of resources. The proliferation of these “smart things” is producing significant deployment of networks in the city context. Most of these devices are proprietary solutions, which do not offer free access to the data they provide. Therefore, this prevents the interoperability and compatibility of these solutions in the current smart city developments. This paper presents how to embed an open sensorized platform for both hardware and software in the context of a smart city, more specifically in a university campus. For this integration, GIScience comes into play, where it offers different open standards that allow full control over “smart things” as an agile and interoperable way to achieve this. To test our system, we have deployed a network of different sensorized platforms inside the university campus, in order to monitor environmental phenomena

Green infrastructure planning based on ecosystem services multicriteria evaluation: the case of the metropolitan wine landscapes of Bordeaux

Excessive anthropogenic activities affect landscape patterns and trigger a decrease of natural capital and the level of quality of life. Green infrastructures (GIs) are commonly accepted by scholars as solutions for restoring degraded areas and providing a variety of ecosystem services (ESs). The other way around, the capacity to deliver ESs can be assumed as a relevant starting point for GIs analysis and planning. The assessment of ESs needs extensive investigation and applications, to provide planners, policy makers, and institutional stakeholders with an adequate evaluation tool. The multi-facet nature of ESs assessment implies the use of complex tools able to consider many concerns. In this regard, multicriteria analysis (MCA) is a very popular tool due to its capacity to intertwine a variety of issues in a rigorous way and to support participatory and transparent decision making in the public domain. In this study, we aim at contributing to the integration of GI design into spatial planning starting from the assessment of the net benefit delivered to local society by a GI in the metropolitan area of Bordeaux (France). We assessed the net benefit by confronting the ESs deliverable by the GI and the cost sustained for its construction and maintenance. We applied an MCA-based method to the selection of the most efficient alternative out of three GI paths. We demonstrate that our method is useful for the assessment of cultural and regulating ESs, comparing the GI design alternatives, and considering the preference model of the stakeholders within GI planning and design

Bias Dependent Variability of Low Frequency Noise in Single Layer Graphene FETs

Low-frequency noise (LFN) variability in graphene transistors (GFETs) is for the first time researched in this work. LFN from an adequate statistical sample of long-channel solution-gated single-layer GFETs is measured in a wide range of operating conditions while a physics-based analytical model is derived that accounts for the bias dependence of LFN variance with remarkable performance. It is theoretically proved and experimentally validated that LFN deviations in GFETs stem from physical mechanisms that generate LFN. Thus, carrier number DN due to trapping/detrapping process and mobility fluctuations Dm which are the main causes of LFN, define its variability likewise as its mean value. DN accounts for an M-shape of normalized LFN variance versus gate bias with a minimum at the charge neutrality point (CNP) as it was the case for normalized LFN mean value while Dm contributes only near the CNP for both variance and mean value. Trap statistical nature is experimentally shown to differ from classical Poisson distribution at silicon-oxide devices, and this is probably caused by electrolyte interface in GFETs under study. Overall, GFET technology development is still in a premature stage which might cause pivotal inconsistencies affecting the scaling laws in GFETs of the same process