884 resultados para Network-based positioning
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It is well known that multiple-input multiple-output (MIMO) techniques can bring numerous benefits, such as higher spectral efficiency, to point-to-point wireless links. More recently, there has been interest in extending MIMO concepts tomultiuser wireless systems. Our focus in this paper is on network MIMO, a family of techniques whereby each end user in a wireless access network is served through several access points within its range of influence. By tightly coordinating the transmission and reception of signals at multiple access points, network MIMO can transcend the limits on spectral efficiency imposed by cochannel interference. Taking prior information-theoretic analyses of networkMIMO to the next level, we quantify the spectral efficiency gains obtainable under realistic propagation and operational conditions in a typical indoor deployment. Our study relies on detailed simulations and, for specificity, is conducted largely within the physical-layer framework of the IEEE 802.16e Mobile WiMAX system. Furthermore,to facilitate the coordination between access points, we assume that a high-capacity local area network, such as Gigabit Ethernet,connects all the access points. Our results confirm that network MIMO stands to provide a multiple-fold increase in spectralefficiency under these conditions.
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This paper describes a Computer-Supported Collaborative Learning (CSCL) case study in engineering education carried out within the context of a network management course. The case study shows that the use of two computing tools developed by the authors and based on Free- and Open-Source Software (FOSS) provide significant educational benefits over traditional engineering pedagogical approaches in terms of both concepts and engineering competencies acquisition. First, the Collage authoring tool guides and supports the course teacher in the process of authoring computer-interpretable representations (using the IMS Learning Design standard notation) of effective collaborative pedagogical designs. Besides, the Gridcole system supports the enactment of that design by guiding the students throughout the prescribed sequence of learning activities. The paper introduces the goals and context of the case study, elaborates onhow Collage and Gridcole were employed, describes the applied evaluation methodology, anddiscusses the most significant findings derived from the case study.
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BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.
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Soil infiltration is a key link of the natural water cycle process. Studies on soil permeability are conducive for water resources assessment and estimation, runoff regulation and management, soil erosion modeling, nonpoint and point source pollution of farmland, among other aspects. The unequal influence of rainfall duration, rainfall intensity, antecedent soil moisture, vegetation cover, vegetation type, and slope gradient on soil cumulative infiltration was studied under simulated rainfall and different underlying surfaces. We established a six factor-model of soil cumulative infiltration by the improved back propagation (BP)-based artificial neural network algorithm with a momentum term and self-adjusting learning rate. Compared to the multiple nonlinear regression method, the stability and accuracy of the improved BP algorithm was better. Based on the improved BP model, the sensitive index of these six factors on soil cumulative infiltration was investigated. Secondly, the grey relational analysis method was used to individually study grey correlations among these six factors and soil cumulative infiltration. The results of the two methods were very similar. Rainfall duration was the most influential factor, followed by vegetation cover, vegetation type, rainfall intensity and antecedent soil moisture. The effect of slope gradient on soil cumulative infiltration was not significant.
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The COP9 signalosome (CSN) is an evolutionarily conserved macromolecular complex that interacts with cullin-RING E3 ligases (CRLs) and regulates their activity by hydrolyzing cullin-Nedd8 conjugates. The CSN sequesters inactive CRL4(Ddb2), which rapidly dissociates from the CSN upon DNA damage. Here we systematically define the protein interaction network of the mammalian CSN through mass spectrometric interrogation of the CSN subunits Csn1, Csn3, Csn4, Csn5, Csn6 and Csn7a. Notably, we identified a subset of CRL complexes that stably interact with the CSN and thus might similarly be activated by dissociation from the CSN in response to specific cues. In addition, we detected several new proteins in the CRL-CSN interactome, including Dda1, which we characterized as a chromatin-associated core subunit of multiple CRL4 proteins. Cells depleted of Dda1 spontaneously accumulated double-stranded DNA breaks in a similar way to Cul4A-, Cul4B- or Wdr23-depleted cells, indicating that Dda1 interacts physically and functionally with CRL4 complexes. This analysis identifies new components of the CRL family of E3 ligases and elaborates new connections between the CRL and CSN complexes.
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Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.
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The Iowa Department of Education (DE) was appropriated $1.45 million for the development and implementation of a statewide work-based learning intermediary network. This funding was awarded on a competitive basis to 15 regional intermediary networks. Funds received by the regional intermediary networks from the state through this grant are to be used to develop and expand work-based learning opportunities within each region. A match of resources equal to 25 percent was a requirement of the funding. This match could include private donations, in-kind contributions, or public moneys. Funds may be used to support personnel responsible for the implementation of the intermediary network program components.
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AIM: To provide insight into cancer registration coverage, data access and use in Europe. This contributes to data and infrastructure harmonisation and will foster a more prominent role of cancer registries (CRs) within public health, clinical policy and cancer research, whether within or outside the European Research Area. METHODS: During 2010-12 an extensive survey of cancer registration practices and data use was conducted among 161 population-based CRs across Europe. Responding registries (66%) operated in 33 countries, including 23 with national coverage. RESULTS: Population-based oncological surveillance started during the 1940-50s in the northwest of Europe and from the 1970s to 1990s in other regions. The European Union (EU) protection regulations affected data access, especially in Germany and France, but less in the Netherlands or Belgium. Regular reports were produced by CRs on incidence rates (95%), survival (60%) and stage for selected tumours (80%). Evaluation of cancer control and quality of care remained modest except in a few dedicated CRs. Variables evaluated were support of clinical audits, monitoring adherence to clinical guidelines, improvement of cancer care and evaluation of mass cancer screening. Evaluation of diagnostic imaging tools was only occasional. CONCLUSION: Most population-based CRs are well equipped for strengthening cancer surveillance across Europe. Data quality and intensity of use depend on the role the cancer registry plays in the politico, oncomedical and public health setting within the country. Standard registration methodology could therefore not be translated to equivalent advances in cancer prevention and mass screening, quality of care, translational research of prognosis and survivorship across Europe. Further European collaboration remains essential to ensure access to data and comparability of the results.
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Social interactions are a very important component in people"s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times" Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links" weights are a measure of the"influence" a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.
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Data are urgently needed to better understand processes of care in Swiss primary care (PC). A total of 2027 PC physicians, stratified by canton, were invited to participate in the Swiss Primary care Active Monitoring network, of whom 200 accepted to join. There were no significant differences between participants and a random sample drawn from the same physician databases based on sex, year of obtaining medical school diploma, or location. The Swiss Primary care Active Monitoring network represents the first large-scale, nationally representative practice-based research network in Switzerland and will provide a unique opportunity to better understand the functioning of Swiss PC.
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Tämä diplomityö käsittelee sääntöpohjaisen verkkoon pääsyn hallinnan (NAC) ratkaisuja arkkitehtonisesta näkökulmasta. Työssä käydään läpi Trusted Computing Groupin, Microsoft Corporationin, Juniper Networksin sekä Cisco Systemsin NAC-ratkaisuja. NAC koostuu joukosta uusia sekä jo olemassa olevia teknologioita, jotka auttavat ennalta määriteltyyn sääntökantaan perustuen hallitsemaan suojattuun verkkoon pyrkivien laitteiden tietoliikenneyhteyksiä. Käyttäjän tunnistamisen lisäksi NAC pystyy rajoittamaan verkkoon pääsyä laitekohtaisten ominaisuuksien perusteella, esimerkiksi virustunnisteisiin ja käyttöjärjestelmäpäivityksiin liittyen ja paikkaamaan tietyin rajoituksin näissä esiintyviä puutteita verkkoon pääsyn sallimiseksi. NAC on verraten uusi käsite, jolta puuttuu tarkka määritelmä. Tästä johtuen nykymarkkinoilla myydään ominaisuuksiltaan puutteellisia tuotteita NAC-nimikkeellä. Standardointi eri valmistajien NAC-komponenttien yhteentoimivuuden takaamiseksi on meneillään, minkä perusteella ratkaisut voidaan jakaa joko avoimia standardeja tai valmistajakohtaisia standardeja noudattaviksi. Esitellyt NAC-ratkaisut noudattavat standardeja joko rajoitetusti tai eivät lainkaan. Mikään läpikäydyistä ratkaisuista ei ole täydellinen NAC, mutta Juniper Networksin ratkaisu nousee niistä potentiaalisimmaksi jatkokehityksen ja -tutkimuksen kohteeksi TietoEnator Processing & Networks Oy:lle. Eräs keskeinen ongelma NAC-konseptissa on työaseman tietoverkolle toimittama mahdollisesti valheellinen tietoturvatarkistuksen tulos, minkä perusteella pääsyä osittain hallitaan. Muun muassa tähän ongelmaan ratkaisuna voisi olla jo nykytietokoneista löytyvä TPM-siru, mikä takaa tiedon oikeellisuuden ja koskemattomuuden.
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Communications play a key role in modern smart grids. New functionalities that make the grids ‘smart’ require the communication network to function properly. Data transmission between intelligent electric devices (IEDs) in the rectifier and the customer-end inverters (CEIs) used for power conversion is also required in the smart grid concept of the low-voltage direct current (LVDC) distribution network. Smart grid applications, such as smart metering, demand side management (DSM), and grid protection applied with communications are all installed in the LVDC system. Thus, besides remote connection to the databases of the grid operators, a local communication network in the LVDC network is needed. One solution applied to implement the communication medium in power distribution grids is power line communication (PLC). There are power cables in the distribution grids, and hence, they may be applied as a communication channel for the distribution-level data. This doctoral thesis proposes an IP-based high-frequency (HF) band PLC data transmission concept for the LVDC network. A general method to implement the Ethernet-based PLC concept between the public distribution rectifier and the customerend inverters in the LVDC grid is introduced. Low-voltage cables are studied as the communication channel in the frequency band of 100 kHz–30 MHz. The communication channel characteristics and the noise in the channel are described. All individual components in the channel are presented in detail, and a channel model, comprising models for each channel component is developed and verified by measurements. The channel noise is also studied by measurements. Theoretical signalto- noise ratio (SNR) and channel capacity analyses and practical data transmission tests are carried out to evaluate the applicability of the PLC concept against the requirements set by the smart grid applications in the LVDC system. The main results concerning the applicability of the PLC concept and its limitations are presented, and suggestion for future research proposed.
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To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR,MAPK14, BCL2L1, KRT18,PTPN6, CASP3, TGFBR2,AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.
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The purpose of this Master’s thesis is to study value co-creation in emerging value network. The main objective is to examine how value is co-created in bio-based chemicals value network. The study provides insights to different actors’ perceived value in the value network and enlightens their motivations to commit to the collaborative partnerships with other actors. Empirical study shows that value co-creation is creation of mutual value for both parties of the relationship by combining their non-competing resources to achieve a common goal. Value co-creation happens in interactions, and trust, commitment and information sharing are essential prerequisites for value co-creation. Value co-creation is not only common value creation, but it is also value that emerges for each actor because of the co-operation with the other actor. Even though the case companies define value mainly in economic terms, the other value elements like value of the partnership, knowledge transfer and innovation are more important for value co-creation.