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The transition towards 5G-based smart network industries is concomitant with a fundamental change of the traditional physical infrastructures driven by digitalization which pervades all decision-relevant components of the infrastr...
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The transition towards 5G-based smart network industries is concomitant with a fundamental change of the traditional physical infrastructures driven by digitalization which pervades all decision-relevant components of the infrastructure value chains. The goal of this paper is to develop a network economic foundation for 5G-based network slicing based on a generalization of the concept of virtual networks combining a required sequence of virtual networks in order to fulfill the necessities of smart network industries. The key concept to analyze the economic incentives of the different actors involved is the well-established concept of opportunity costs of usage of scarce network resources. The allocation problem of traffic service providers fundamentally differs from the allocation problem of virtual network providers. Whereas interoperability and interconnection between different virtual networks are not standardized significant standardization efforts via network slicing can be observed in particular from the perspective of end-to-end QoS guarantees. 5G-based big data use cases with cross-border challenges for network slicing, and the subsequent interoperability of virtual networks, enable tremendous potential for innovation in smart physical infrastructures. The 5G-based European Future Railway Mobile Communication System and cross-border oriented, 5G-based connected, cooperative, and automated mobility applications are investigated with a large and open set of heterogeneous use cases requiring cross-border standardization of QoS-differentiated network slices.
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Federated cloud networking is needed to allow the seamless and efficient interconnection of resources distributed among different clouds. This work introduces a new cloud network federation framework for the automatic provision of...
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Federated cloud networking is needed to allow the seamless and efficient interconnection of resources distributed among different clouds. This work introduces a new cloud network federation framework for the automatic provision of Layer 2 (L2) and Layer 3 (L3) virtual networks to interconnect geographically distributed cloud infrastructures in a hybrid cloud scenario. This framework provides a simple, secure and elastic solution to create and manage federated networks across heterogeneous cloud providers, with abstraction of the underlying technologies. The paper also analyzes the main technologies and topologies that can used the framework to construct L2 and L3 overlay networks within hybrid clouds. In order to demonstrate the viability of the proposed solution and compare the different topologies, the article shows a proof-of-concept of a real federated network deployment in a hybrid cloud, which spans a local private cloud, managed with OpenNebula, and two public clouds, two different regions of Amazon EC2. Results show that L2 and L3 overlay connectivity can be achieved with a minimal bandwidth overhead, lower than 10%.
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Starting from an industry where production is provided by a public monopolist, we observe the effects of a sequence of reforms within the network industry on consumer surplus. Using a simple comparative statics framework, we find ...
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Starting from an industry where production is provided by a public monopolist, we observe the effects of a sequence of reforms within the network industry on consumer surplus. Using a simple comparative statics framework, we find the indifference conditions for the consumer surplus under the following regimes: a public monopoly, an unregulated private monopoly, a regulated private monopoly, a vertically disintegrated monopoly, a duopoly and a liberalized market. The results are determined by the relative size of the x-inefficiencies of the public monopolist, allocative inefficiencies of the private monopoly, the cost of unbundling and the costs related to establishing a competitive market.
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In this paper, real frequency design equations of narrowband impedance matching network with complex terminations are derived; which are used to design L, Pi and T type of networks. In the approach, there is no need to have termin...
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In this paper, real frequency design equations of narrowband impedance matching network with complex terminations are derived; which are used to design L, Pi and T type of networks. In the approach, there is no need to have termination models with component values, it is enough to have measurement values of termination impedances. A few examples are solved to exhibit the have measurement values of termination impedances. A few examples are solved to exhibit the merits and application of the derived equations.
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The modern telecommunication has come into the Long-Term Evolution (LTE) era. The whole transmission network gradually has evolved to the IP network. The overall network organization is likewise becoming more and more similar to t...
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The modern telecommunication has come into the Long-Term Evolution (LTE) era. The whole transmission network gradually has evolved to the IP network. The overall network organization is likewise becoming more and more similar to the metropolitan data network. A mobile Packet Transport Network (PTN) transmission network construction is investigated. The specific bearing requirements of time division long-term evolution (TD-LTE) are analyzed. The topology structures of L3 and L2/L3 and the equipment applications in different network levels of the PTN network are discussed. The existing problems concerning the circuit scheduling, disaster tolerance requirement, security connection and business pressure are analyzed in detail. Their corresponding optimization strategies are presented. Finally, the network level having a clear, robust and complete coverage is reached. It proves that the optimized network can meet the third level of the disaster tolerance international standard SHARE 78.
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This paper investigates the roles of firm size, age, and industrial networking in determining firm growth. Analyses using the 2-year panel data of 7,889 Korean manufacturing firms between 1994 and 2003 confirm that firm size and a...
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This paper investigates the roles of firm size, age, and industrial networking in determining firm growth. Analyses using the 2-year panel data of 7,889 Korean manufacturing firms between 1994 and 2003 confirm that firm size and age have significant negative effects on firm growth and significant positive impacts on firm survival. R&D and export activities are found to facilitate both firm growth and survival. The primary focus of this study is to examine the effects of industrial networking, such as subcontracting and clustering, on firm growth. The results show that subcontracting does not yield any positive effect for firm growth, but encumbers survival, which may be accounted for by the high subcontracting intensity among small firms. Clustering, on the other hand, is found to promote firm growth and survival. There is, however, little evidence that such a positive effect of clustering is derived from network externalities through cooperation and competition among firms in a cluster per se.
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By a News Reporter-Staff News Editor at Network Daily News – Fresh data on
Mathematics are presented in a new report. According to news reporting out of L’Aquila, Italy, by NewsRx
editors, research stated, “The analysis of el...
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By a News Reporter-Staff News Editor at Network Daily News – Fresh data on
Mathematics are presented in a new report. According to news reporting out of L’Aquila, Italy, by NewsRx
editors, research stated, “The analysis of electrocardiogram (ECG) signals are among the key factors in the
diagnosis of cardiovascular diseases (CVDs). However, automatic processing of ECG in clinical practice is
still restrained by the accuracy of existing algorithms.”
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By a News Reporter-Staff News Editor at Network Daily News - Fresh data on
Mathematics are presented in a new report. According to news reporting out of L’Aquila, Italy, by NewsRx
editors, research stated, “The analysis of ele...
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By a News Reporter-Staff News Editor at Network Daily News - Fresh data on
Mathematics are presented in a new report. According to news reporting out of L’Aquila, Italy, by NewsRx
editors, research stated, “The analysis of electrocardiogram (ECG) signals are among the key factors in the
diagnosis of cardiovascular diseases (CVDs). However, automatic processing of ECG in clinical practice is
still restrained by the accuracy of existing algorithms.”
Our news journalists obtained a quote from the research from the University of L’Aquila, “Deep learning
methods have recently achieved striking success in a variety of task including predictive healthcare. Graph
neural networks are a class of machine learning algorithms which can learn by directly extracting important
information from graph-structured data, and perform prediction on unknown data. Such algorithms are
suitable for mining complex graph data, deducing useful predictions. In this work, we present a Graph
Neural Network (GNN) model trained in two datasets with more than 107,000 single -lead signal images
extracted from laboratories of Boston’s Beth Israel Hospital and of the Massachusetts Institute of Technology
(MITBIH), and 1.5 million labeled exams analyzed by the Physikalisch-Technische Bundesanstalt
(PTB). Our proposed GNN achieves promising performance, i.e., the results show that ECG classification
based on GNNs using either single-lead or 12-lead setup is closer to the human-level in standard clinical
practice. By several testing instances, the proposed approach obtains an accuracy of 1.0, thereby outperforming
various state-of-the-art baselines by both databases with respect to effectiveness and timing
efficiency.”
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