Workflow Modelling in Grid System for Satellite Data Processing

This paper focuses on a problem of Grid system decomposition by developing its object model. Unified Modelling Language (UML) is used as a formalization tool. This approach is motivated by the complexity of the system being analysed and the need for simulation model design.

Metadata and Geospatial Data Processing on the Base of XML and Grid

The software architecture and development consideration for open metadata extraction and processing framework are outlined. Special attention is paid to the aspects of reliability and fault tolerance. Grid infrastructure is shown as useful backend for general-purpose task.

Grid Infrastructure for Satellite Data Processing in Ukraine

In this paper conceptual foundations for the development of Grid systems that aimed for satellite data processing are discussed. The state of the art of development of such Grid systems is analyzed, and a model of Grid system for satellite data processing is proposed. An experience obtained within the development of the Grid system for satellite data processing in the Space Research Institute of NASU-NSAU is discussed.

Distributed Visualization Systems in Remote Sensing Data Processing Grid

Implementation of GEOSS/GMES initiative requires creation and integration of service providers, most of which provide geospatial data output from Grid system to interactive user. In this paper approaches of DOS- centers (service providers) integration used in Ukrainian segment of GEOSS/GMES will be considered and template solutions for geospatial data visualization subsystems will be suggested. Developed patterns are implemented in DOS center of Space Research Institute of National Academy of Science of Ukraine and National Space Agency of Ukraine (NASU-NSAU).

Advances in characterisation, calibration and data processing speed of optical coherence tomography systems

This thesis describes advances in the characterisation, calibration and data processing of optical coherence tomography (OCT) systems. Femtosecond (fs) laser inscription was used for producing OCT-phantoms. Transparent materials are generally inert to infra-red radiations, but with fs lasers material modification occurs via non-linear processes when the highly focused light source interacts with the materials. This modification is confined to the focal volume and is highly reproducible. In order to select the best inscription parameters, combination of different inscription parameters were tested, using three fs laser systems, with different operating properties, on a variety of materials. This facilitated the understanding of the key characteristics of the produced structures with the aim of producing viable OCT-phantoms. Finally, OCT-phantoms were successfully designed and fabricated in fused silica. The use of these phantoms to characterise many properties (resolution, distortion, sensitivity decay, scan linearity) of an OCT system was demonstrated. Quantitative methods were developed to support the characterisation of an OCT system collecting images from phantoms and also to improve the quality of the OCT images. Characterisation methods include the measurement of the spatially variant resolution (point spread function (PSF) and modulation transfer function (MTF)), sensitivity and distortion. Processing of OCT data is a computer intensive process. Standard central processing unit (CPU) based processing might take several minutes to a few hours to process acquired data, thus data processing is a significant bottleneck. An alternative choice is to use expensive hardware-based processing such as field programmable gate arrays (FPGAs). However, recently graphics processing unit (GPU) based data processing methods have been developed to minimize this data processing and rendering time. These processing techniques include standard-processing methods which includes a set of algorithms to process the raw data (interference) obtained by the detector and generate A-scans. The work presented here describes accelerated data processing and post processing techniques for OCT systems. The GPU based processing developed, during the PhD, was later implemented into a custom built Fourier domain optical coherence tomography (FD-OCT) system. This system currently processes and renders data in real time. Processing throughput of this system is currently limited by the camera capture rate. OCTphantoms have been heavily used for the qualitative characterization and adjustment/ fine tuning of the operating conditions of OCT system. Currently, investigations are under way to characterize OCT systems using our phantoms. The work presented in this thesis demonstrate several novel techniques of fabricating OCT-phantoms and accelerating OCT data processing using GPUs. In the process of developing phantoms and quantitative methods, a thorough understanding and practical knowledge of OCT and fs laser processing systems was developed. This understanding leads to several novel pieces of research that are not only relevant to OCT but have broader importance. For example, extensive understanding of the properties of fs inscribed structures will be useful in other photonic application such as making of phase mask, wave guides and microfluidic channels. Acceleration of data processing with GPUs is also useful in other fields.

Services for Satellite Data Processing

Data processing services for Meteosat geostationary satellite are presented. Implemented services correspond to the different levels of remote-sensing data processing, including noise reduction at preprocessing level, cloud mask extraction at low-level and fractal dimension estimation at high-level. Cloud mask obtained as a result of Markovian segmentation of infrared data. To overcome high computation complexity of Markovian segmentation parallel algorithm is developed. Fractal dimension of Meteosat data estimated using fractional Brownian motion models.

Web designers, social e-value creation and e-business planning:understanding resistance from conflicting demands

This chapter investigates the conflicting demands faced by web designers in the development of social e-atmospherics that aim to encourage e-value creation, thus strengthening and prolonging market planning strategies. While recent studies have shown that significant shifts are occurring concerning the importance of users’ generated content by way of social e-communication tools (e.g. blogs), these trends are also creating expectations that social and cultural cues ought to become a greater part of e-atmospherics and e-business strategies. Yet, there is growing evidence that organizations are resisting such efforts, fearing that they will lose control of their e-marketing strategy. This chapter contributes to the theory and literature on online cross-cultural understanding and the impact website designers (meso-level) can have on improving the sustainability of e-business planning, departing from recent studies that focus mainly on firms’ e-business plans (macro-level) or final consumers (micro-level). A second contribution is made with respect to online behavior regarding the advancement of technologies that facilitate the development and shaping of new social e-atmospherics that affect users’ behavior and long term e-business strategies through the avoidance of traditional, formal decision making processes and marketing strategy mechanisms implemented by firms. These issues have been highlighted in the literature on the co-production and co-creation of value, which few organizations have thus far integrated in their strategic and pragmatic e-business plans. Drawing upon fifteen online interviews with web designers in the USA, as key non-institutional actors at the meso-level who are developing what future websites will be like, this chapter analyzes ways in which identifying points of resistance and conflicting demands can lead to engagement with the debate over the online co-creation of value and more sustainable future e-business planning. A number of points of resistance to the inclusion of more e-social atmospherics are identified, and the implications for web designers’ roles and web design planning are discussed along with the limitations of the study and potential future research for e-business studies.

Large scale data processing using MapReduce

As massive data sets become increasingly available, people are facing the problem of how to effectively process and understand these data. Traditional sequential computing models are giving way to parallel and distributed computing models, such as MapReduce, both due to the large size of the data sets and their high dimensionality. This dissertation, as in the same direction of other researches that are based on MapReduce, tries to develop effective techniques and applications using MapReduce that can help people solve large-scale problems. Three different problems are tackled in the dissertation. The first one deals with processing terabytes of raster data in a spatial data management system. Aerial imagery files are broken into tiles to enable data parallel computation. The second and third problems deal with dimension reduction techniques that can be used to handle data sets of high dimensionality. Three variants of the nonnegative matrix factorization technique are scaled up to factorize matrices of dimensions in the order of millions in MapReduce based on different matrix multiplication implementations. Two algorithms, which compute CANDECOMP/PARAFAC and Tucker tensor decompositions respectively, are parallelized in MapReduce based on carefully partitioning the data and arranging the computation to maximize data locality and parallelism.

Data Science Seminar: Generic Big Data Processing for Advancing Situation Awareness and Decision-Support

The generation of heterogeneous big data sources with ever increasing volumes, velocities and veracities over the he last few years has inspired the data science and research community to address the challenge of extracting knowledge form big data. Such a wealth of generated data across the board can be intelligently exploited to advance our knowledge about our environment, public health, critical infrastructure and security. In recent years we have developed generic approaches to process such big data at multiple levels for advancing decision-support. It specifically concerns data processing with semantic harmonisation, low level fusion, analytics, knowledge modelling with high level fusion and reasoning. Such approaches will be introduced and presented in context of the TRIDEC project results on critical oil and gas industry drilling operations and also the ongoing large eVacuate project on critical crowd behaviour detection in confined spaces.

DESIGN OF EFFICIENT IN-NETWORK DATA PROCESSING AND DISSEMINATION FOR VANETS

By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment.

MEVA-Ambiental: MEtodologia per a la Valoració de l'Aprenentatge. Centrada en l'educació ambiental

Aquest projecte abasta el disseny i el desenvolupament d’un model prototípic de Metodologia per a la Valoració de l’Aprenentatge Ambiental, a la qual anomenem “MEVA-Ambiental”. Per a fer possible aquesta fita ens hem basat en fonaments ontològics i constructivistes per representar i analitzar el coneixement a fi de poder quantificar l’Increment de Coneixement (IC). Per nosaltres l’IC esdevé un indicador socio-educatiu que ens servirà per a determinar l’efectivitat dels tallers d’educació ambiental en percentatge. En procedir d’aquesta manera, les qualificacions resultats poden es poden prendre com punt de partida per a desenvolupar estudis en el temps i comprendre com “s’ancora” el nou coneixement a l’estructura cognitiva dels aprenents. Més enllà del plantejament teòric de mètode, també proveïm la solució tècnica que mostra com n’és de funcional i d’aplicable la part empírica metodològica. A aquesta solució que hem anomenat “MEVA-Tool”, és una eina virtual que automatitza la recollida i tractament de dades amb una estructura dinàmica basada en “qüestionaris web” que han d’emplenar els estudiants, una “base de dades” que acumula la informació i en permet un filtratge selectiu, i més “Llibre Excel” que en fa el tractament informatiu, la representació gràfica dels resultats, l’anàlisi i conclusions.

Anàlisi del riu Llobregat com a via de transport del Baix Llobregat a l'època romana, amb eines SIG

Desenvolupament d'un Sistema d'Informació Geogràfica (SIG), que permeti analitzar les funcions dels jaciments romans de la zona del riu Llobregat i consultar els jaciments, emmagatzemats en una base de dades de forma espacial.

Implantación de una solución SIG para la ayuda a la toma dedecisiones para la explotación de recursos del subsuelo

L'objectiu és una aplicació que permeti realitzar el càlcul del volum de terres disponibles en el subsòl d'un àrea seleccionada. L'objectiu final del projecte serà crear un Sistema d'Informació Geogràfica SIG que ajudi a valorar quines parcel¿les de l'àrea seleccionada són les que disposen de més volum de terres per iniciar la seva explotació. Per a això, es disposa del programari gvSIG i les seves extensions (SEXTANTE) i de tota la informació que es pugui obtenir sobre els SIG, Cartografia, Geodèsia... Per dur a terme aquest projecte es necessita tenir experiència en Bases de dades, Programació Orientada a Objectes i seria recomanable tenir coneixements sobre Enginyeria del Programador. El projecte se centrarà en la utilització de gvSIG, com un exemple concret de programari SIG de lliure accés, solució desenvolupada per la ¿Conselleria d%o2019Obris Publiquis de la Generalitat Valenciana¿. Una part d'aquest projecte consistirà a avaluar aquest programari. El resultat final serà l'obtenció dels coneixements necessaris per poder treballar amb dades espacials a més d'una aplicació SIG per al càlcul del volum de terres d'un àrea seleccionada.

SIG i Arqueologia : el riu Llobregat i la seva relació amb el territori en l'època romana

Aquest treball se centra en la utilització i aplicació de les tecnologies dels Sistemes d'Informació Geogràfica; en concret es realitza una pràctica sobre el traçat del riu Llobregat a l'època romana.