36 resultados para approach to information systems

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Epileptic seizures are due to the pathological collective activity of large cellular assemblies. A better understanding of this collective activity is integral to the development of novel diagnostic and therapeutic procedures. In contrast to reductionist analyses, which focus solely on small-scale characteristics of ictogenesis, here we follow a systems-level approach, which combines both small-scale and larger-scale analyses. Peri-ictal dynamics of epileptic networks are assessed by studying correlation within and between different spatial scales of intracranial electroencephalographic recordings (iEEG) of a heterogeneous group of patients suffering from pharmaco-resistant epilepsy. Epileptiform activity as recorded by a single iEEG electrode is determined objectively by the signal derivative and then subjected to a multivariate analysis of correlation between all iEEG channels. We find that during seizure, synchrony increases on the smallest and largest spatial scales probed by iEEG. In addition, a dynamic reorganization of spatial correlation is observed on intermediate scales, which persists after seizure termination. It is proposed that this reorganization may indicate a balancing mechanism that decreases high local correlation. Our findings are consistent with the hypothesis that during epileptic seizures hypercorrelated and therefore functionally segregated brain areas are re-integrated into more collective brain dynamics. In addition, except for a special sub-group, a highly significant association is found between the location of ictal iEEG activity and the location of areas of relative decrease of localised EEG correlation. The latter could serve as a clinically important quantitative marker of the seizure onset zone (SOZ).

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In rapidly evolving domains such as Computer Assisted Orthopaedic Surgery (CAOS) emphasis is often put first on innovation and new functionality, rather than in developing the common infrastructure needed to support integration and reuse of these innovations. In fact, developing such an infrastructure is often considered to be a high-risk venture given the volatility of such a domain. We present CompAS, a method that exploits the very evolution of innovations in the domain to carry out the necessary quantitative and qualitative commonality and variability analysis, especially in the case of scarce system documentation. We show how our technique applies to the CAOS domain by using conference proceedings as a key source of information about the evolution of features in CAOS systems over a period of several years. We detect and classify evolution patterns to determine functional commonality and variability. We also identify non-functional requirements to help capture domain variability. We have validated our approach by evaluating the degree to which representative test systems can be covered by the common and variable features produced by our analysis.

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The field of animal syndromic surveillance (SyS) is growing, with many systems being developed worldwide. Now is an appropriate time to share ideas and lessons learned from early SyS design and implementation. Based on our practical experience in animal health SyS, with additions from the public health and animal health SyS literature, we put forward for discussion a 6-step approach to designing SyS systems for livestock and poultry. The first step is to formalise policy and surveillance goals which are considerate of stakeholder expectations and reflect priority issues (1). Next, it is important to find consensus on national priority diseases and identify current surveillance gaps. The geographic, demographic, and temporal coverage of the system must be carefully assessed (2). A minimum dataset for SyS that includes the essential data to achieve all surveillance objectives while minimizing the amount of data collected should be defined. One can then compile an inventory of the data sources available and evaluate each using the criteria developed (3). A list of syndromes should then be produced for all data sources. Cases can be classified into syndrome classes and the data can be converted into time series (4). Based on the characteristics of the syndrome-time series, the length of historic data available and the type of outbreaks the system must detect, different aberration detection algorithms can be tested (5). Finally, it is essential to develop a minimally acceptable response protocol for each statistical signal produced (6). Important outcomes of this pre-operational phase should be building of a national network of experts and collective action and evaluation plans. While some of the more applied steps (4 and 5) are currently receiving consideration, more emphasis should be put on earlier conceptual steps by decision makers and surveillance developers (1-3).

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In recent years, Geographic Information Systems (GIS) have increasingly been used in a wide array of application contexts for development cooperation in lowlands and mountain areas. When used for planning, implementation, and monitoring, GIS is a versatile and highly efficient tool, particularly in mountain areas characterized by great spatial diversity and inaccessibility. However, the establishment and application of GIS in mountain regions generally presents considerable technical challenges. Moreover, it is necessary to address specific institutional and organizational issues regarding implementation.

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Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

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One of the major challenges for a mission to the Jovian system is the radiation tolerance of the spacecraft (S/C) and the payload. Moreover, being able to achieve science observations with high signal to noise ratios (SNR), while passing through the high flux radiation zones, requires additional ingenuity on the part of the instrument provider. Consequently, the radiation mitigation is closely intertwined with the payload, spacecraft and trajectory design, and requires a systems-level approach. This paper presents a design for the Io Volcano Observer (IVO), a Discovery mission concept that makes multiple close encounters with Io while orbiting Jupiter. The mission aims to answer key outstanding questions about Io, especially the nature of its intense active volcanism and the internal processes that drive it. The payload includes narrow-angle and wide-angle cameras (NAC and WAC), dual fluxgate magnetometers (FGM), a thermal mapper (ThM), dual ion and neutral mass spectrometers (INMS), and dual plasma ion analyzers (PIA). The radiation mitigation is implemented by drawing upon experiences from designs and studies for missions such as the Radiation Belt Storm Probes (RBSP) and Jupiter Europa Orbiter (JEO). At the core of the radiation mitigation is IVO's inclined and highly elliptical orbit, which leads to rapid passes through the most intense radiation near Io, minimizing the total ionizing dose (177 krads behind 100 mils of Aluminum with radiation design margin (RDM) of 2 after 7 encounters). The payload and the spacecraft are designed specifically to accommodate the fast flyby velocities (e.g. the spacecraft is radioisotope powered, remaining small and agile without any flexible appendages). The science instruments, which collect the majority of the high-priority data when close to Io and thus near the peak flux, also have to mitigate transient noise in their detectors. The cameras use a combination of shielding and CMOS detectors with extremely fast readout to mi- imize noise. INMS microchannel plate detectors and PIA channel electron multipliers require additional shielding. The FGM is not sensitive to noise induced by energetic particles and the ThM microbolometer detector is nearly insensitive. Detailed SNR calculations are presented. To facilitate targeting agility, all of the spacecraft components are shielded separately since this approach is more mass efficient than using a radiation vault. IVO uses proven radiation-hardened parts (rated at 100 krad behind equivalent shielding of 280 mils of Aluminum with RDM of 2) and is expected to have ample mass margin to increase shielding if needed.

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Based on an integrative brain model which focuses on memory-driven and EEG state-dependent information processing for the organisation of behaviour, we used the developmental changes of the awake EEG to further investigate the hypothesis that neurodevelopmental abnormalities (deviations in organisation and reorganisation of cortico-cortical connectivity during development) are involved in the pathogenesis of schizophrenia. First-episode, neuroleptic-naive schizophrenics and their matched controls and three age groups of normal adolescents were studied (total: 70 subjects). 19-channel EEG delta-theta, alpha and beta spectral band centroid frequencies during resting (baseline) and after verbal stimuli were used as measure of the level of attained complexity and momentary excitability of the neuronal network (working memory). Schizophrenics compared with all control groups showed lower delta-theta activity centroids and higher alpha and beta activity centroids. Reactivity centroids (centroid after stimulus minus centroid during resting) were used as measure of update of working memory. Schizophrenics showed partial similarities in delta-theta and beta reactivity centroids with the 11-year olds and in alpha reactivity centroids with the 13-year olds. Within the framework of our model, the results suggest multifactorially elicited imbalances in the level of excitability of neuronal networks in schizophrenia, resulting in network activation at dissociated complexity levels, partially regressed and partially prematurely developed. It is hypothesised that activation of age- and/or state-inadequate representations for coping with realities becomes manifest as productive schizophrenic symptoms. Thus, the results support some aspects of the neurodevelopmental hypothesis.

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he notion of outsourcing – making arrangements with an external entity for the provision of goods or services to supplement or replace internal efforts – has been around for centuries. The outsourcing of information systems (IS) is however a much newer concept but one which has been growing dramatically. This book attempts to synthesize what is known about IS outsourcing by dividing the subject into three interrelated parts: (1) Traditional Information Technology Outsourcing, (2) Information Technolgy Offshoring, and (3) Business Process Outsourcing. The book should be of interest to all academics and students in the field of Information Systems as well as corporate executives and professionals who seek a more profound analysis and understanding of the underlying factors and mechanisms of outsourcing.

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A key challenge for land change science in general and research on swidden agriculture in particular, is linking land cover information to human–environment interactions over larger spatial areas. In Lao PDR, a country facing rapid and multi-level land change processes, this hinders informed policy- and decision-making. Crucial information on land use types and people involved is still lacking. This article proposes an alternative approach for the description of landscape mosaics. Instead of analyzing local land use combinations, we studied land cover mosaics at a meso-level of spatial scale and interpreted these in terms of human–environmental interactions. These landscape mosaics were then overlaid with population census data. Results showed that swidden agricultural landscapes, involving 17% of the population, dominate 29% of the country, while permanent agricultural landscapes involve 74% of the population in 29% of the territory. Forests still form an important component of these landscape mosaics.