On a meaningful integration of web services in data-intensive biomedical environments: The DICODE approach

This paper reports on an innovative approach that aims to reduce information management costs in data-intensive and cognitively-complex biomedical environments. Recognizing the importance of prominent high-performance computing paradigms and large data processing technologies as well as collaboration support systems to remedy data-intensive issues, it adopts a hybrid approach by building on the synergy of these technologies. The proposed approach provides innovative Web-based workbenches that integrate and orchestrate a set of interoperable services that reduce the data-intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and concentrate on creative activities.

Implementation of intelligent data acquisition system for ITER fast controllers using RIO devices.

A basic requirement of the data acquisition systems used in long pulse fusion experiments is the real time physical events detection in signals. Developing such applications is usually a complex task, so it is necessary to develop a set of hardware and software tools that simplify their implementation. This type of applications can be implemented in ITER using fast controllers. ITER is standardizing the architectures to be used for fast controller implementation. Until now the standards chosen are PXIe architectures (based on PCIe) for the hardware and EPICS middleware for the software. This work presents the methodology for implementing data acquisition and pre-processing using FPGA-based DAQ cards and how to integrate these in fast controllers using EPICS.

La videovigilancia : tecnologías actuales y aspectos sociopolíticos

En este Proyecto de fin de carrera titulado: LA VÍDEOVIGILANCIA: TECNOLOGÍAS ACTUALES Y ASPECTOS SOCIOPOLÍTICOS, tiene como objetivo hacer un estudio en los sistemas de Vídeovigilancia basado en cámaras-IP, con fines de seguridad, control o supervisión. Nos basaremos en exponer los sistemas Vídeovigilancia basados en cámara-IP actuales de ultima generación, cuya principal virtud de estos sistemas, es la comunicación con otros lugares, o espacios públicos como privados y poder visualizar tanto en vivo como en diferido lo que este pasando en ese lugar y en ese momento o haya pasado a través del protocolo de comunicación-IP. Se explicara desde el más básico al más complejo sistema de videovigilancia-IP, también explicaremos su puesta en practica mediante los múltiples interconexiones que estos conlleven. Llegando a este punto, se nos plantea las siguientes cuestiones que da origen a este PFC. Estos sistemas de Vídeovigilancia-IP, captan las imágenes por medio de las cámaras-IP, proporcionando su facilidad tanto de visionado/grabacion, como de control, ya que no es necesario estar presente e interactuando con otros sistemas digitales de diverso índole actuales, gracias al protocolo-IP. Estos sistemas-IP, tienen su puesta en práctica mediante las instalaciones requeridas ,estas podrán ser sencillas o muy complejas de todos los sistemas-IP. Debido al gran aumento masivo, las tecnologías actuales de diverso índole de cámaras-IP en materia de la vídeovigilancia en lugares públicos, y privados en nuestra sociedad actual, lo hace un medio particularmente invasivo y por ello resulta necesario tanto la concurrencia de condiciones que legitimen los tratamientos de datos de personas identificables, como la definición de los principios y garantías que deban aplicarse ya que estas, repercutirán sobre los derechos de las personas, lo que obligara a fijar ciertas garantías. Se nos plantea los casos en los que la captación y/o tratamiento de imágenes con fines de Vídeovigilancia que pertenezcan a personas identificadas o identificables, ha obligado a España, y según dispuesto por la Directiva 95/46/CE del Parlamento Europeo, a regularizar esta situación mediante la Ley Orgánica de Protección de Datos (LOPD) 15/1999 de 13 de diciembre, bajo los procedimientos del Estado español en materia sociopolítica, y dando vigor a esta ley, mediante la aprobación de la Instrucción 1/2006 de 8 de noviembre de 2006, cuyo máximo organismo es la Agencia española de Protección de Datos (AGPD). Una vez planteada la motivación y justificación del proyecto, se derivan unos objetivos a cumplir con la realización del mismo. Los objetivos del proyecto se pueden diferenciar en dos clases principalmente. Los objetivos principales y objetivos secundarios. Los objetivos principales de este PFC, nacen directamente de las necesidades planteadas originalmente en materia de Vídeovigilancia, tanto tecnológicamente basado en las cámaras-IP en la captación y/o tratamiento de imágenes, así como sociopolíticamente donde trataremos de describirlo mediante las indicaciones y criterios con casos prácticos y de cómo deben de aplicarse según la instrucción 1/2006 mediante la LOPD en materia de Vídeovigilancia, en cuanto a la protección de datos que puedan repercutir sobre el derecho de las personas. Por otra parte los objetivos secundarios, son la extensión del objetivo primario y son de orden cuantificador en este PFC, dando una explicación más exhaustiva del objetivo principal. ABSTRACT In this final year project, entitled: THE VIDEOSURVEILLANCE: CURRENT TECHNOLOGIES AND POLITICALSOCIALS ASPECTS, aims to make a study of video surveillance systems based on IP cameras, for security, control or supervision. We will rely on to expose the camera based video surveillance systems IP-current last generation, whose main virtue of these systems, is communication with other places, or public and private spaces and to view both live and time so this happening in that place and at that time or passed through-IP communication protocol. He explained from the most basic to the most complex-IP video surveillance system, also explain its implementation into practice through multiple interconnections that these entail. Arriving at this point, we face the following issues which gave rise to this PFC. These IP-video surveillance systems, captured images through IP-cameras, providing both ease of viewing / recording, as a control, since it is not necessary to be present and interacting with other digital systems such diverse today, thanks IP-protocol. These systems-IP, have their implementation through the facilities required, these can be simple or very complex all-IP video surveillance systems. Due to the large increase in mass, current technologies of different kinds of IP cameras for video surveillance in public places, and private in our society, it makes a particularly invasive and therefore attendance is necessary both conditions that legitimize data processing of identifiable people, as the definition of the principles and safeguards to be applied as these will impact on the rights of the people, which forced to set certain guarantees. We face those cases in which the uptake and / or image processing video surveillance purposes belonging to identified or identifiable, has forced Spain, and as required by Directive 95/46/EC of the European Parliament, to regularize this situation by the Organic Law on Data Protection (LOPD) 15/1999 of December 13, under the procedures of the Spanish State in sociopolitical, and giving effect to this Act, with the approval of the Instruction 1/2006 of 8 November 2006, the governing body is the Spanish Agency for Data Protection (AGPD). Once raised the motivation and justification for the project, resulting in meeting targets to achieve the same. Project objectives can be differentiated into two main classes, the main objectives and secondary objectives: The main objectives of this PFC, born directly from requirements originally raised for capturing both technologically imaging me and try to describe where sociopolitically, the details and criteria as case studies and should be applied according to the instruction 1 / 2006 by the LOPD on video surveillance system in terms of data protection that could impact on the right people. Moreover the secondary objectives are the extension of the primary and are of a quantifier in this PFC, giving a fuller explanation of the main objective.

Optimisation of algorithms to compute information theoretic indexes

Analysis of big amount of data is a field with many years of research. It is centred in getting significant values, to make it easier to understand and interpret data. Being the analysis of interdependence between time series an important field of research, mainly as a result of advances in the characterization of dynamical systems from the signals they produce. In the medicine sphere, it is easy to find many researches that try to understand the brain behaviour, its operation mode and its internal connections. The human brain comprises approximately 1011 neurons, each of which makes about 103 synaptic connections. This huge number of connections between individual processing elements provides the fundamental substrate for neuronal ensembles to become transiently synchronized or functionally connected. A similar complex network configuration and dynamics can also be found at the macroscopic scales of systems neuroscience and brain imaging. The emergence of dynamically coupled cell assemblies represents the neurophysiological substrate for cognitive function such as perception, learning, thinking. Understanding the complex network organization of the brain on the basis of neuroimaging data represents one of the most impervious challenges for systems neuroscience. Brain connectivity is an elusive concept that refers to diferent interrelated aspects of brain organization: structural, functional connectivity (FC) and efective connectivity (EC). Structural connectivity refers to a network of physical connections linking sets of neurons, it is the anatomical structur of brain networks. However, FC refers to the statistical dependence between the signals stemming from two distinct units within a nervous system, while EC refers to the causal interactions between them. This research opens the door to try to resolve diseases related with the brain, like Parkinson’s disease, senile dementia, mild cognitive impairment, etc. One of the most important project associated with Alzheimer’s research and other diseases are enclosed in the European project called Blue Brain. The center for Biomedical Technology (CTB) of Universidad Politecnica de Madrid (UPM) forms part of the project. The CTB researches have developed a magnetoencephalography (MEG) data processing tool that allow to visualise and analyse data in an intuitive way. This tool receives the name of HERMES, and it is presented in this document. Analysis of big amount of data is a field with many years of research. It is centred in getting significant values, to make it easier to understand and interpret data. Being the analysis of interdependence between time series an important field of research, mainly as a result of advances in the characterization of dynamical systems from the signals they produce. In the medicine sphere, it is easy to find many researches that try to understand the brain behaviour, its operation mode and its internal connections. The human brain comprises approximately 1011 neurons, each of which makes about 103 synaptic connections. This huge number of connections between individual processing elements provides the fundamental substrate for neuronal ensembles to become transiently synchronized or functionally connected. A similar complex network configuration and dynamics can also be found at the macroscopic scales of systems neuroscience and brain imaging. The emergence of dynamically coupled cell assemblies represents the neurophysiological substrate for cognitive function such as perception, learning, thinking. Understanding the complex network organization of the brain on the basis of neuroimaging data represents one of the most impervious challenges for systems neuroscience. Brain connectivity is an elusive concept that refers to diferent interrelated aspects of brain organization: structural, functional connectivity (FC) and efective connectivity (EC). Structural connectivity refers to a network of physical connections linking sets of neurons, it is the anatomical structur of brain networks. However, FC refers to the statistical dependence between the signals stemming from two distinct units within a nervous system, while EC refers to the causal interactions between them. This research opens the door to try to resolve diseases related with the brain, like Parkinson’s disease, senile dementia, mild cognitive impairment, etc. One of the most important project associated with Alzheimer’s research and other diseases are enclosed in the European project called Blue Brain. The center for Biomedical Technology (CTB) of Universidad Politecnica de Madrid (UPM) forms part of the project. The CTB researches have developed a magnetoencephalography (MEG) data processing tool that allow to visualise and analyse data in an intuitive way. This tool receives the name of HERMES, and it is presented in this document.

Brain tissue segmentation on Diffusion Weighted Magnetic Resonance data

Introduction Diffusion weighted Imaging (DWI) techniques are able to measure, in vivo and non-invasively, the diffusivity of water molecules inside the human brain. DWI has been applied on cerebral ischemia, brain maturation, epilepsy, multiple sclerosis, etc. [1]. Nowadays, there is a very high availability of these images. DWI allows the identification of brain tissues, so its accurate segmentation is a common initial step for the referred applications. Materials and Methods We present a validation study on automated segmentation of DWI based on the Gaussian mixture and hidden Markov random field models. This methodology is widely solved with iterative conditional modes algorithm, but some studies suggest [2] that graph-cuts (GC) algorithms improve the results when initialization is not close to the final solution. We implemented a segmentation tool integrating ITK with a GC algorithm [3], and a validation software using fuzzy overlap measures [4]. Results Segmentation accuracy of each tool is tested against a gold-standard segmentation obtained from a T1 MPRAGE magnetic resonance image of the same subject, registered to the DWI space. The proposed software shows meaningful improvements by using the GC energy minimization approach on DTI and DSI (Diffusion Spectrum Imaging) data. Conclusions The brain tissues segmentation on DWI is a fundamental step on many applications. Accuracy and robustness improvements are achieved with the proposed software, with high impact on the application’s final result.

Meter data management for smart monitoring power networks

The electrical power distribution and commercialization scenario is evolving worldwide, and electricity companies, faced with the challenge of new information requirements, are demanding IT solutions to deal with the smart monitoring of power networks. Two main challenges arise from data management and smart monitoring of power networks: real-time data acquisition and big data processing over short time periods. We present a solution in the form of a system architecture that conveys real time issues and has the capacity for big data management.

Processing and validation of JEFF3-3.1.2 Cross-section Library into Various Formats: ACE, PENDF, GENDF, MATXSR and BOXER.

Following the processing and validation of JEFF-3.1 performed in 2006 and presented in ND2007, and as a consequence of the latest updated of this library (JEFF-3.1.2) in February 2012, a new processing and validation of JEFF-3.1.2 cross section library is presented in this paper. The processed library in ACE format at ten different temperatures was generated with NJOY-99.364 nuclear data processing system. In addition, NJOY-99 inputs are provided to generate PENDF, GENDF, MATXSR and BOXER formats. The library has undergone strict QA procedures, being compared with other available libraries (e.g. ENDF/B-VII.1) and processing codes as PREPRO-2000 codes. A set of 119 criticality benchmark experiments taken from ICSBEP-2010 has been used for validation purposes.

MIA - a free and open source software for gray scale medical image analysis

Background Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large. Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also accessable to researchers that have no background or little in software development because they take care of otherwise complex tasks. Specifically, the management of working memory is taken care of automatically, usually at the price of requiring more it. As a result, processing large data sets with these tools becomes increasingly difficult on work station class computers. One alternative to using these high level processing tools is the development of new algorithms in a languages like C++, that gives the developer full control over how memory is handled, but the resulting workflow for the prototyping of new algorithms is rather time intensive, and also not appropriate for a researcher with little or no knowledge in software development. Another alternative is in using command line tools that run image processing tasks, use the hard disk to store intermediate results, and provide automation by using shell scripts. Although not as convenient as, e.g. visual programming, this approach is still accessable to researchers without a background in computer science. However, only few tools exist that provide this kind of processing interface, they are usually quite task specific, and don’t provide an clear approach when one wants to shape a new command line tool from a prototype shell script. Results The proposed framework, MIA, provides a combination of command line tools, plug-ins, and libraries that make it possible to run image processing tasks interactively in a command shell and to prototype by using the according shell scripting language. Since the hard disk becomes the temporal storage memory management is usually a non-issue in the prototyping phase. By using string-based descriptions for filters, optimizers, and the likes, the transition from shell scripts to full fledged programs implemented in C++ is also made easy. In addition, its design based on atomic plug-ins and single tasks command line tools makes it easy to extend MIA, usually without the requirement to touch or recompile existing code. Conclusion In this article, we describe the general design of MIA, a general purpouse framework for gray scale image processing. We demonstrated the applicability of the software with example applications from three different research scenarios, namely motion compensation in myocardial perfusion imaging, the processing of high resolution image data that arises in virtual anthropology, and retrospective analysis of treatment outcome in orthognathic surgery. With MIA prototyping algorithms by using shell scripts that combine small, single-task command line tools is a viable alternative to the use of high level languages, an approach that is especially useful when large data sets need to be processed.

DCE@urLAB: a dynamic contrast-enhanced MRI pharmacokinetic analysis tool for preclinical data

Background DCE@urLAB is a software application for analysis of dynamic contrast-enhanced magnetic resonance imaging data (DCE-MRI). The tool incorporates a friendly graphical user interface (GUI) to interactively select and analyze a region of interest (ROI) within the image set, taking into account the tissue concentration of the contrast agent (CA) and its effect on pixel intensity. Results Pixel-wise model-based quantitative parameters are estimated by fitting DCE-MRI data to several pharmacokinetic models using the Levenberg-Marquardt algorithm (LMA). DCE@urLAB also includes the semi-quantitative parametric and heuristic analysis approaches commonly used in practice. This software application has been programmed in the Interactive Data Language (IDL) and tested both with publicly available simulated data and preclinical studies from tumor-bearing mouse brains. Conclusions A user-friendly solution for applying pharmacokinetic and non-quantitative analysis DCE-MRI in preclinical studies has been implemented and tested. The proposed tool has been specially designed for easy selection of multi-pixel ROIs. A public release of DCE@urLAB, together with the open source code and sample datasets, is available at http://www.die.upm.es/im/archives/DCEurLAB/ webcite.

OSIRIS – The scientific camera system onboard Rosetta

The Optical, Spectroscopic, and Infrared Remote Imaging System OSIRIS is the scientific camera system onboard the Rosetta spacecraft (Figure 1). The advanced high performance imaging system will be pivotal for the success of the Rosetta mission. OSIRIS will detect 67P/Churyumov-Gerasimenko from a distance of more than 106 km, characterise the comet shape and volume, its rotational state and find a suitable landing spot for Philae, the Rosetta lander. OSIRIS will observe the nucleus, its activity and surroundings down to a scale of ~2 cm px−1. The observations will begin well before the onset of cometary activity and will extend over months until the comet reaches perihelion. During the rendezvous episode of the Rosetta mission, OSIRIS will provide key information about the nature of cometary nuclei and reveal the physics of cometary activity that leads to the gas and dust coma. OSIRIS comprises a high resolution Narrow Angle Camera (NAC) unit and a Wide Angle Camera (WAC) unit accompanied by three electronics boxes. The NAC is designed to obtain high resolution images of the surface of comet 7P/Churyumov-Gerasimenko through 12 discrete filters over the wavelength range 250–1000 nm at an angular resolution of 18.6 μrad px−1. The WAC is optimised to provide images of the near-nucleus environment in 14 discrete filters at an angular resolution of 101 μrad px−1. The two units use identical shutter, filter wheel, front door, and detector systems. They are operated by a common Data Processing Unit. The OSIRIS instrument has a total mass of 35 kg and is provided by institutes from six European countries

Segregating the functions of human hippocampus

It is now accepted that hippocampal lesions impair episodic memory. However, the precise functional role of the hippocampus in episodic memory remains elusive. Recent functional imaging data implicate the hippocampus in processing novelty, a finding supported by human in vivo recordings and event-related potential studies. Here we measure hippocampal responses to novelty, using functional MRI (fMRI), during an item-learning paradigm generated from an artificial grammar system. During learning, two distinct types of novelty were periodically introduced: perceptual novelty, pertaining to the physical characteristics of stimuli (in this case visual characteristics), and exemplar novelty, reflecting semantic characteristics of stimuli (in this case grammatical status within a rule system). We demonstrate a left anterior hippocampal response to both types of novelty and adaptation of these responses with stimulus familiarity. By contrast to these novelty effects, we also show bilateral posterior hippocampal responses with increasing exemplar familiarity. These results suggest a functional dissociation within the hippocampus with respect to the relative familiarity of study items. Neural responses in anterior hippocampus index generic novelty, whereas posterior hippocampal responses index familiarity to stimuli that have behavioral relevance (i.e., only exemplar familiarity). These findings add to recent evidence for functional segregation within the human hippocampus during learning.

Cerebral energetics and the glycogen shunt: Neurochemical basis of functional imaging

Positron-emission tomography and functional MRS imaging signals can be analyzed to derive neurophysiological values of cerebral blood flow or volume and cerebral metabolic consumption rates of glucose (CMRGlc) or oxygen (CMRO2). Under basal physiological conditions in the adult mammalian brain, glucose oxidation is nearly complete so that the oxygen-to-glucose index (OGI), given by the ratio of CMRO2/CMRGlc, is close to the stoichiometric value of 6. However, a survey of functional imaging data suggests that the OGI is activity dependent, moving further below the oxidative value of 6 as activity is increased. Brain lactate concentrations also increase with stimulation. These results had led to the concept that brain activation is supported by anaerobic glucose metabolism, which was inconsistent with basal glucose oxidation. These differences are resolved here by a proposed model of glucose energetics, in which a fraction of glucose is cycled through the cerebral glycogen pool, a fraction that increases with degree of brain activation. The “glycogen shunt,” although energetically less efficient than glycolysis, is followed because of its ability to supply glial energy in milliseconds for rapid neurotransmitter clearance, as a consequence of which OGI is lowered and lactate is increased. The value of OGI observed is consistent with passive lactate efflux, driven by the observed lactate concentration, for the few experiments with complete data. Although the OGI changes during activation, the energies required per neurotransmitter release (neuronal) and clearance (glial) are constant over a wide range of brain activity.

Imaging neuroscience: Principles or maps?

This article reviews some recent trends in imaging neuroscience. A distinction is made between making maps of functional responses in the brain and discerning the rules or principles that underlie their organization. After considering developments in the characterization of brain imaging data, several examples are presented that highlight the context-sensitive nature of neuronal responses that we measure. These contexts can be endogenous and physiological, reflecting the fact that each cortical area, or neuronal population, expresses its dynamics in the context of interactions with other areas. Conversely, these contexts can be experimental or psychological and can have a profound effect on the regional effects elicited. In this review we consider experimental designs and analytic strategies that go beyond cognitive subtraction and speculate on how functional imaging can be used to address both the details and principles underlying functional integration and specialization in the brain.