17 resultados para Radial distribution networks
em BORIS: Bern Open Repository and Information System - Berna - Suiça
Resumo:
To characterize the zonal distribution of three-dimensional (3D) T1 mapping in the hip joint of asymptomatic adult volunteers.
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Background The purpose of the present study was to investigate the radial distribution patterns of cartilage degeneration in dysplastic hips at different stages of secondary osteoarthritis (OA) by using radial delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC), and to assess whether pre-contrast measurements are necessary. Methods Thirty-five hips in 21 subjects (mean age ± SD, 27.6 ± 10.8 years) with acetabular dysplasia (lateral CE angle < 25°) were studied. Severity of OA was assessed on radiographs using Tönnis grading. Pre- (T1pre) and post-contrast T1 (T1Gd) values were measured at 7 sub-regions on radial reformatted slices acquired from a 3-dimensional (3D) T1 mapping sequence using a 1.5 T MR scanner. Values of radial T1pre, T1Gd and ΔR1 (1/T1Gd - 1/T1pre) of subgroups with different severity of OA were compared to those of the subgroup without OA using nonparametric tests, and bivariate linear Pearson correlations between radial T1Gd and ΔR1 were analyzed for each subgroup. Results Compared to the subgroup without OA, the subgroup with mild OA was observed with a significant decrease in T1Gd in the anterosuperior to superior sub-regions (mean, 476 ~ 507 ms, p = 0.026 ~ 0.042) and a significant increase in ΔR1 in the anterosuperior to superoposterior and posterior sub-regions (mean, 0.93 ~ 1.37 s-1, p = 0.012 ~ 0.042). The subgroup with moderate to severe OA was observed with a significant overall decrease in T1Gd (mean, 404 ~ 452 ms, p = 0.001 ~ 0.020) and an increase in ΔR1 (mean, 1.17 ~1.69 s-1, p = 0.001 ~ 0.020). High correlations were observed between radial T1Gd and ΔR1 for all subgroups (r = −0.869 ~ −0.944, p < 0.001). Conclusions Radial dGEMRIC without pre-contrast measurements is useful for evaluating different patterns of cartilage degeneration in the entire hip joint of patients with hip dysplasia, particularly for those in early stages of secondary OA.
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Content Distribution Networks are mandatory components of modern web architectures, with plenty of vendors offering their services. Despite its maturity, new paradigms and architecture models are still being developed in this area. Cloud Computing, on the other hand, is a more recent concept which has expanded extremely quickly, with new services being regularly added to cloud management software suites such as OpenStack. The main contribution of this paper is the architecture and the development of an open source CDN that can be provisioned in an on-demand, pay-as-you-go model thereby enabling the CDN as a Service paradigm. We describe our experience with integration of CDNaaS framework in a cloud environment, as a service for enterprise users. We emphasize the flexibility and elasticity of such a model, with each CDN instance being delivered on-demand and associated to personalized caching policies as well as an optimized choice of Points of Presence based on exact requirements of an enterprise customer. Our development is based on the framework developed in the Mobile Cloud Networking EU FP7 project, which offers its enterprise users a common framework to instantiate and control services. CDNaaS is one of the core support components in this project as is tasked to deliver different type of multimedia content to several thousands of users geographically distributed. It integrates seamlessly in the MCN service life-cycle and as such enjoys all benefits of a common design environment, allowing for an improved interoperability with the rest of the services within the MCN ecosystem.
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The proliferation of multimedia content and the demand for new audio or video services have fostered the development of a new era based on multimedia information, which allowed the evolution of Wireless Multimedia Sensor Networks (WMSNs) and also Flying Ad-Hoc Networks (FANETs). In this way, live multimedia services require real-time video transmissions with a low frame loss rate, tolerable end-to-end delay, and jitter to support video dissemination with Quality of Experience (QoE) support. Hence, a key principle in a QoE-aware approach is the transmission of high priority frames (protect them) with a minimum packet loss ratio, as well as network overhead. Moreover, multimedia content must be transmitted from a given source to the destination via intermediate nodes with high reliability in a large scale scenario. The routing service must cope with dynamic topologies caused by node failure or mobility, as well as wireless channel changes, in order to continue to operate despite dynamic topologies during multimedia transmission. Finally, understanding user satisfaction on watching a video sequence is becoming a key requirement for delivery of multimedia content with QoE support. With this goal in mind, solutions involving multimedia transmissions must take into account the video characteristics to improve video quality delivery. The main research contributions of this thesis are driven by the research question how to provide multimedia distribution with high energy-efficiency, reliability, robustness, scalability, and QoE support over wireless ad hoc networks. The thesis addresses several problem domains with contributions on different layers of the communication stack. At the application layer, we introduce a QoE-aware packet redundancy mechanism to reduce the impact of the unreliable and lossy nature of wireless environment to disseminate live multimedia content. At the network layer, we introduce two routing protocols, namely video-aware Multi-hop and multi-path hierarchical routing protocol for Efficient VIdeo transmission for static WMSN scenarios (MEVI), and cross-layer link quality and geographical-aware beaconless OR protocol for multimedia FANET scenarios (XLinGO). Both protocols enable multimedia dissemination with energy-efficiency, reliability and QoE support. This is achieved by combining multiple cross-layer metrics for routing decision in order to establish reliable routes.
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Background: fMRI Resting State Networks (RSNs) have gained importance in the present fMRI literature. Although their functional role is unquestioned and their physiological origin is nowadays widely accepted, little is known about their relationship to neuronal activity. The combined recording of EEG and fMRI allows the temporal correlation between fluctuations of the RSNs and the dynamics of EEG spectral amplitudes. So far, only relationships between several EEG frequency bands and some RSNs could be demonstrated, but no study accounted for the spatial distribution of frequency domain EEG. Methodology/Principal Findings: In the present study we report on the topographic association of EEG spectral fluctuations and RSN dynamics using EEG covariance mapping. All RSNs displayed significant covariance maps across a broad EEG frequency range. Cluster analysis of the found covariance maps revealed the common standard EEG frequency bands. We found significant differences between covariance maps of the different RSNs and these differences depended on the frequency band. Conclusions/Significance: Our data supports the physiological and neuronal origin of the RSNs and substantiates the assumption that the standard EEG frequency bands and their topographies can be seen as electrophysiological signatures of underlying distributed neuronal networks.
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Costly on-site node repairs in wireless mesh networks (WMNs) can be required due to misconfiguration, corrupt software updates, or unavailability during updates. We propose ADAM as a novel management framework that guarantees accessibility of individual nodes in these situations. ADAM uses a decentralised distribution mechanism and self-healing mechanisms for safe configuration and software updates. In order to implement the ADAM management and self-healing mechanisms, an easy-to-learn and extendable build system for a small footprint embedded Linux distribution for WMNs has been developed. The paper presents the ADAM concept, the build system for the Linux distribution and the management architecture.
Resumo:
OBJECTIVE: To investigate topographic and age-dependent adaptation of subchondral bone density in the elbow joints of healthy dogs by means of computed tomographic osteoabsorptiometry (CTOAM). Animals-42 elbow joints of 29 clinically normal dogs of various breeds and ages. PROCEDURES: Subchondral bone densities of the humeral, radial, and ulnar joint surfaces of the elbow relative to a water-hydroxyapatite phantom were assessed by means of CTOAM. Distribution patterns in juvenile, adult, and geriatric dogs (age, < 1 year, 1 to 8 years, and > 8 years, respectively) were determined and compared within and among groups. RESULTS: An area of increased subchondral bone density was detected in the humerus distomedially and cranially on the trochlea and in the olecranon fossa. The ulna had maximum bone densities on the anconeal and medial coronoid processes. Increased bone density was detected in the craniomedial region of the joint surface of the radius. A significant age-dependent increase in subchondral bone density was revealed in elbow joint surfaces of the radius, ulna, and humerus. Mean subchondral bone density of the radius was significantly less than that of the ulna in paired comparisons for all dogs combined and in adult and geriatric, but not juvenile, dog groups. CONCLUSIONS AND CLINICAL RELEVANCE: An age-dependent increase in subchondral bone density at the elbow joint was revealed. Maximal relative subchondral bone densities were detected consistently at the medial coronoid process and central aspect of the humeral trochlea, regions that are commonly affected in dogs with elbow dysplasia.
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STUDY DESIGN: In vitro testing of vertebroplasty techniques including pulsed jet-lavage for fat and marrow removal in human cadaveric lumbar and thoracic vertebrae. OBJECTIVE: To develop jet-lavage techniques for vertebroplasty and investigate their effect on cement distribution, injection forces, and fat embolism. SUMMARY OF BACKGROUND DATA: The main complications of cement vertebroplasty are cement leakage and pulmonary fat embolism, which can have fatal consequences and are difficult to prevent reliably by current vertebroplasty techniques. METHODS: Twenty-four vertebrae (Th8-L04) from 5 osteoporotic cadaver spines were grouped in triplets depending on bone mineral density (BMD). Before polymethylmethacrylate (PMMA) vertebroplasty, a pulsatile jet-lavage for removal of intertrabecular fat and bone marrow was performed in 2 groups with 8 specimens each, performing radial and axial irrigation from the biopsy needles. One hundred mL of Ringer solution were injected through 1 pedicle and regained by low vacuum via the contralateral pedicle. Eight control vertebrae were not irrigated. All specimens underwent standardized PMMA cement augmentation injecting 20% of the vertebral volume. Injection forces, cement distribution, and extravasations were quantified. RESULTS: All irrigation solution could be retrieved with the vacuum applied. A Kruskal-Wallis test revealed significantly higher injection forces of the control group as compared with the irrigated groups (P = 0.021). Dilatation of the syringe at forces above 300 N occurred in 75% of the untreated compared with 12.5% of the lavaged specimens. CT distribution analysis showed more homogenous cement distribution of the cement and significantly less extravasation in the irrigated specimens. CONCLUSION: The developed lavage technique for vertebroplasty showed to be feasible and reproducible. The reduction of injection forces would allow the use of more viscous PMMA cement lowering the risk for cement embolization and results in a safer procedure. The wash-out of bone marrow and the possible reduction of pulmonary fat embolism have to be verified with in vivo models.
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Various applications for the purposes of event detection, localization, and monitoring can benefit from the use of wireless sensor networks (WSNs). Wireless sensor networks are generally easy to deploy, with flexible topology and can support diversity of tasks thanks to the large variety of sensors that can be attached to the wireless sensor nodes. To guarantee the efficient operation of such a heterogeneous wireless sensor networks during its lifetime an appropriate management is necessary. Typically, there are three management tasks, namely monitoring, (re) configuration, and code updating. On the one hand, status information, such as battery state and node connectivity, of both the wireless sensor network and the sensor nodes has to be monitored. And on the other hand, sensor nodes have to be (re)configured, e.g., setting the sensing interval. Most importantly, new applications have to be deployed as well as bug fixes have to be applied during the network lifetime. All management tasks have to be performed in a reliable, time- and energy-efficient manner. The ability to disseminate data from one sender to multiple receivers in a reliable, time- and energy-efficient manner is critical for the execution of the management tasks, especially for code updating. Using multicast communication in wireless sensor networks is an efficient way to handle such traffic pattern. Due to the nature of code updates a multicast protocol has to support bulky traffic and endto-end reliability. Further, the limited resources of wireless sensor nodes demand an energy-efficient operation of the multicast protocol. Current data dissemination schemes do not fulfil all of the above requirements. In order to close the gap, we designed the Sensor Node Overlay Multicast (SNOMC) protocol such that to support a reliable, time-efficient and energy-efficient dissemination of data from one sender node to multiple receivers. In contrast to other multicast transport protocols, which do not support reliability mechanisms, SNOMC supports end-to-end reliability using a NACK-based reliability mechanism. The mechanism is simple and easy to implement and can significantly reduce the number of transmissions. It is complemented by a data acknowledgement after successful reception of all data fragments by the receiver nodes. In SNOMC three different caching strategies are integrated for an efficient handling of necessary retransmissions, namely, caching on each intermediate node, caching on branching nodes, or caching only on the sender node. Moreover, an option was included to pro-actively request missing fragments. SNOMC was evaluated both in the OMNeT++ simulator and in our in-house real-world testbed and compared to a number of common data dissemination protocols, such as Flooding, MPR, TinyCubus, PSFQ, and both UDP and TCP. The results showed that SNOMC outperforms the selected protocols in terms of transmission time, number of transmitted packets, and energy-consumption. Moreover, we showed that SNOMC performs well with different underlying MAC protocols, which support different levels of reliability and energy-efficiency. Thus, SNOMC can offer a robust, high-performing solution for the efficient distribution of code updates and management information in a wireless sensor network. To address the three management tasks, in this thesis we developed the Management Architecture for Wireless Sensor Networks (MARWIS). MARWIS is specifically designed for the management of heterogeneous wireless sensor networks. A distinguished feature of its design is the use of wireless mesh nodes as backbone, which enables diverse communication platforms and offloading functionality from the sensor nodes to the mesh nodes. This hierarchical architecture allows for efficient operation of the management tasks, due to the organisation of the sensor nodes into small sub-networks each managed by a mesh node. Furthermore, we developed a intuitive -based graphical user interface, which allows non-expert users to easily perform management tasks in the network. In contrast to other management frameworks, such as Mate, MANNA, TinyCubus, or code dissemination protocols, such as Impala, Trickle, and Deluge, MARWIS offers an integrated solution monitoring, configuration and code updating of sensor nodes. Integration of SNOMC into MARWIS further increases performance efficiency of the management tasks. To our knowledge, our approach is the first one, which offers a combination of a management architecture with an efficient overlay multicast transport protocol. This combination of SNOMC and MARWIS supports reliably, time- and energy-efficient operation of a heterogeneous wireless sensor network.
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Storing and recalling spiking sequences is a general problem the brain needs to solve. It is, however, unclear what type of biologically plausible learning rule is suited to learn a wide class of spatiotemporal activity patterns in a robust way. Here we consider a recurrent network of stochastic spiking neurons composed of both visible and hidden neurons. We derive a generic learning rule that is matched to the neural dynamics by minimizing an upper bound on the Kullback–Leibler divergence from the target distribution to the model distribution. The derived learning rule is consistent with spike-timing dependent plasticity in that a presynaptic spike preceding a postsynaptic spike elicits potentiation while otherwise depression emerges. Furthermore, the learning rule for synapses that target visible neurons can be matched to the recently proposed voltage-triplet rule. The learning rule for synapses that target hidden neurons is modulated by a global factor, which shares properties with astrocytes and gives rise to testable predictions.
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Here, by the example of the transfer of cultivated plants in the context of the correspondence networks of Albrecht von Haller and the Economic Society, a multi-level network analysis is suggested. By a multi-level procedure, the chronological dynamics, the social structure, the spatial distribution and the functional networking are analyzed one after the other. These four levels of network analysis do not compete with each other but are mutually supporting. This aims at a deeper understanding of how these networks contributed to an international transfer of knowledge in the 18th century.
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In this paper, we present a revolutionary vision of 5G networks, in which SDN programs wireless network functions, and where Mobile Network Operators (MNO), Enterprises, and Over-The-Top (OTT) third parties are provided with NFV-ready Network Store. The proposed Network Store serves as a digital distribution platform of programmable Virtualized Network Functions (VNFs) that enable 5G application use-cases. Currently existing application stores, such as Apple's App Store for iOS applications, Google's Play Store for Android, or Ubuntu's Software Center, deliver applications to user specific software platforms. Our vision is to provide a digital marketplace, gathering 5G enabling Network Applications and Network Functions, written to run on top of commodity cloud infrastructures, connected to remote radio heads (RRH). The 5G Network Store will be the same to the cloud as the application store is currently to a software platform.
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User experience on watching live videos must be satisfactory even under the inuence of different network conditions and topology changes, such as happening in Flying Ad-Hoc Networks (FANETs). Routing services for video dissemination over FANETs must be able to adapt routing decisions at runtime to meet Quality of Experience (QoE) requirements. In this paper, we introduce an adaptive beaconless opportunistic routing protocol for video dissemination over FANETs with QoE support, by taking into account multiple types of context information, such as link quality, residual energy, buffer state, as well as geographic information and node mobility in a 3D space. The proposed protocol takes into account Bayesian networks to define weight vectors and Analytic Hierarchy Process (AHP) to adjust the degree of importance for the context information based on instantaneous values. It also includes a position prediction to monitor the distance between two nodes in order to detect possible route failure.
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Content-Centric Networking (CCN) naturally supports multi-path communication, as it allows the simultaneous use of multiple interfaces (e.g. LTE and WiFi). When multiple sources and multiple clients are considered, the optimal set of distribution trees should be determined in order to optimally use all the available interfaces. This is not a trivial task, as it is a computationally intense procedure that should be done centrally. The need for central coordination can be removed by employing network coding, which also offers improved resiliency to errors and large throughput gains. In this paper, we propose NetCodCCN, a protocol for integrating network coding in CCN. In comparison to previous works proposing to enable network coding in CCN, NetCodCCN permit Interest aggregation and Interest pipelining, which reduce the data retrieval times. The experimental evaluation shows that the proposed protocol leads to significant improvements in terms of content retrieval delay compared to the original CCN. Our results demonstrate that the use of network coding adds robustness to losses and permits to exploit more efficiently the available network resources. The performance gains are verified for content retrieval in various network scenarios.