Asymmetric Node Research Articles

Asymmetric node placement in fiber-based quantum networks

Asymmetric node placement in fiber-based quantum networks

Prevalence of Adenopathy at Chest Computed Tomography After Vaccination for Severe Acute Respiratory Syndrome Coronavirus 2.

This study aimed to determine the prevalence of axillary and subpectoral (SP) lymph nodes after ipsilateral COVID-19 vaccine administration on chest computed tomography (CT). Subjects with chest CTs between 2 and 25 days after a first or second vaccine dose, December 15, 2020, to February 12, 2021, were included. Orthogonal measures of the largest axillary and SP nodes were recorded by 2 readers blinded to vaccine administration and clinical details. A mean nodal diameter discrepancy of ≥6 mm between contralateral stations was considered positive for asymmetry. Correlation with the side of vaccination, using a Spearman rank correlation, was performed on the full cohort and after excluding patients with diseases associated with adenopathy. Of the 138 subjects (81 women, 57 men; mean [SD] age, 74.4 ± 11.7 years), 48 (35%) had asymmetrically enlarged axillary and/or SP lymph nodes, 42 (30%) had ipsilateral, and 6 (4%) had contralateral to vaccination ( P = 0.003). Exclusion of 29 subjects with conditions associated with adenopathy showed almost identical correlation, with asymmetric nodes in 32 of 109 (29%) ipsilateral and in 5 of 109 (5%) contralateral to vaccination ( P = 0.002). Axillary and/or SP lymph nodes ipsilateral to vaccine administration represents a clinical conundrum. Asymmetric nodes were detected at CT in 30% of subjects overall and 29% of subjects without conditions associated with adenopathy, approximately double the prevalence rate reported to the Centers for Disease Control and Prevention by vaccine manufacturers. When interpreting examinations correlation with vaccine administration timing and site is important for pragmatic management.

C-TOL: Convex triangulation for optimal node localization with weighted uncertainties

There is always a need to reduce localization error in any wireless sensor network (WSN), and our aim is to observe the impact of localization uncertainty on network awareness. When nodes are deployed in a 2D plane and their l2-norm ranged triangulations are found, usually the unweighted localization uncertainty values become absurdly large with large triangulation cases. Moreover, there is no regard for the disparity between the lengths of any two links on the localization uncertainty. The upper bound of uncertainty keeps on rising with formation of asymmetric node triangulations with longer internodal distances and sharper vertices. To address this gap, a convex combination weighted approach (C-TOL, standing for Convex-Triangulation for Optimal node Localization) for solving the localization uncertainty problem is described here. The advantage of the proposed method is shown with the help of rigorous mathematical analysis of weighted uncertainty behaviour. The relationship of sensor node symmetry with triangulation uncertainty is formulated algebraically by considering both symmetric as well as asymmetric triangulations. Cramer Rao bound is derived to justify estimation under triangulation uncertainty. This approach paves the way for the WSN to prioritize different kinds of triangulations. Numerical results reveal that the weighted method prefers triangulations with more symmetry; hence it consistently achieves significantly lower values of mean and standard deviations than the existing unweighted localization technique, especially for densely connected sensor networks. Moreover, the proposed method shows robust localization performance for sparsely deployed networks as well, when compared to recent methods in literature.

LocSpeck: A Collaborative and Distributed Positioning System for Asymmetric Nodes Based on UWB Ad-Hoc Network and Wi-Fi Fingerprinting.

This paper presents LocSpeck, a collaborative and distributed indoor positioning system for dynamic nodes connected using an ad-hoc network, based on inter-node relative range measurements and Wi-Fi fingerprinting. The proposed system operates using peer-to-peer range measurements and does not need ultra-wideband (UWB) fixed anchor, nor it needs a predefined network topology. The nodes could be asymmetric in terms of the available sensors onboard, the computational resources, and the power capacity. This asymmetry adversely affects the positioning performance of the weaker nodes. Collaboration between different nodes is achieved through a distributed estimator without the need of a single centralized computing element. The ranging measurement component of the system is based on the DW1000 UWB transceiver chip from Decawave, which is attached to a set of smartphones equipped with asymmetric sensors. The distributed positioning filter fuses, locally on each node, the relative range measurements, the reading from the internal sensors, and the Wi-Fi received signal strength indicator (RSSI) readings to obtain an estimate of the position of each node. The described system does not depend on fixed UWB anchors and supports online addition and removal of nodes and dynamic node role assignment, either as an anchor or as a rover. The performance of the system is evaluated by real-world test scenarios using a set of four smartphones navigating an indoor environment on foot. The performance is compared to that of a commercial UWB-based system. The results presented in this paper show that weak mobile nodes, in terms of available positioning sensors, can benefit from collaboration with other nearby nodes.

Cluster-modified function projective synchronisation of complex networks with asymmetric coupling

This paper investigates the cluster-modified function projective synchronisation (CMFPS) of a generalised linearly coupled network with asymmetric coupling and nonidentical dynamical nodes. A novel synchronisation scheme is proposed to achieve CMFPS in community networks. We use adaptive control method to derive CMFPS criteria based on Lyapunov stability theory. Each cluster of networks is synchronised with target system by state transformation with scaling function matrix. Numerical simulation results are presented finally to illustrate the effectiveness of this method.

Oscillation Model for Describing Network Dynamics Caused by Asymmetric Node Interaction

This paper proposes an oscillation model for analyzing the dynamics of activity propagation across social media networks. In order to analyze such dynamics, we generally need to model asymmetric interactions between nodes. In matrix-based network models, asymmetric interaction is frequently modeled by a directed graph expressed as an asymmetric matrix. Unfortunately, the dynamics of an asymmetric matrix-based model is difficult to analyze. This paper, first of all, discusses a symmetric matrix-based model that can describe some types of link asymmetry, and then proposes an oscillation model on networks. Next, the proposed oscillation model is generalized to arbitrary link asymmetry. We describe the outlines of four important research topics derived from the proposed oscillation model. First, we show that the oscillation energy of each node gives a generalized notion of node centrality. Second, we introduce a framework that uses resonance to estimate the natural frequency of networks. Natural frequency is important information for recognizing network structure. Third, by generalizing the oscillation model on directed networks, we create a dynamical model that can describe flaming on social media networks. Finally, we show the fundamental equation of oscillation on networks, which provides an important breakthrough for generalizing the spectral graph theory applicable to directed graphs.

A novel interface element with asymmetric nodes and its application on concrete-faced rockfill dam

Based on the Goodman element, the Guyan reduction method is introduced to develop the interface element with asymmetric nodes, which accomplishes the coarse-fine mesh transition between soil and structure in finite element models by providing a different number of nodes on the two sliding surfaces. The number of Gauss points is greater than that of the traditional Goodman element, which ensures its accuracy. The developed interface element is employed in the dynamic elasto-plastic analysis of CFRDs. The results indicate that the use of the constructed interface element can significantly decrease the number of elements with little influence on the accuracy.

The Waste Collection Vehicle Arc Routing Problem with Turn Constraints

To reduce the route length of MSW collection without intermediate facilities, A Waste Collection Vehicle Arc Routing Problem with turn constraints (WCVARPTC) model was proposed, which considers the actual traffic regulations: some streets can be traversed in only one direction; some turns will be forbidden when the common angle is too narrow. An asymmetric vehicle node routing problem (AVNRP) model was formulated to reduce the scale of the WCVARPTC. And a MULTI-ACS algorithm was designed for solving such an asymmetric one. The results of 2 benchmark instances for CVARP indicate that the best solutions has approached the best known solutions with deviation 0.28% and 0.16% respectively.

Dynamic lightpath provisioning in optical WDM mesh networks with asymmetric nodes

The wavelength selective switch-based reconfigurable optical add/drop multiplexers is a promising switching equipment for future reconfigurable wavelength-division multiplexing (WDM) mesh networks. However, its asymmetric switching property complicates the optimal routing and wavelength assignment problem. In an asymmetric switching scenario, using the classic Dijkstra's algorithm can lead to invalid paths traversing unconnected ports of an asymmetric node. To solve this problem, we propose both link-state (LS) and distance vector (DV) schemes for dynamic lightpath provisioning in optical WDM mesh networks with asymmetric nodes. The proposed LS schemes include the asymmetric switching-aware (ASA) Dijkstra's algorithm, the $$K$$ -shortest path-based algorithm, and the entire path searching (EPS) algorithm. Simulation results show that the ASA-Dijkstra's algorithm will bring notable improvement of the blocking performance with low computational complexity, while the EPS algorithm has much higher complexity and is not suitable to be employed in large-scale networks. On the other hand, our proposed DV solution, i.e., the information diffusion-based routing (IDBR), can achieve the lowest blocking probability with the lowest computational complexity. Moreover, IDBR does not require the distribution of local asymmetric switching information like the LS schemes, thus having a high level of topology confidentiality.

Training Effective Node Classifiers for Cascade Classification

Cascade classifiers are widely used in real-time object detection. Different from conventional classifiers that are designed for a low overall classification error rate, a classifier in each node of the cascade is required to achieve an extremely high detection rate and moderate false positive rate. Although there are a few reported methods addressing this requirement in the context of object detection, there is no principled feature selection method that explicitly takes into account this asymmetric node learning objective. We provide such an algorithm here. We show that a special case of the biased minimax probability machine has the same formulation as the linear asymmetric classifier (LAC) of Wu et al. (linear asymmetric classifier for cascade detectors, 2005). We then design a new boosting algorithm that directly optimizes the cost function of LAC. The resulting totally-corrective boosting algorithm is implemented by the column generation technique in convex optimization. Experimental results on object detection verify the effectiveness of the proposed boosting algorithm as a node classifier in cascade object detection, and show performance better than that of the current state-of-the-art.

Pkd1l1 as a molecular sensor of fluid flow during the breaking of left-right symmetry

In mammals, left-right symmetry is broken during development by motile cilia-driven fluid flow in the embryonic node. How this ‘nodal flow’ is sensed remains the subject of debate. In kidney, fluid flow/membrane stress is sensed by polycystin protein complexes composed of Pkd1 and Pkd2 which reside in primary cilia. Pkd2 also plays a role in determining left-right asymmetry but no role has been found for Pkd1. We have isolated the ENU mouse mutant rks which harbours a mutation in the Pkd1-related gene Pkd1l1. Pkd1l1rks mutants exhibit severe left-right defects, loss of asymmetric gene expression but normal node cilia structure and motility. These data reveal the functional relationships between Pkd1 and Pkd1l1 which appear to be split between kidney development and left-right asymmetry respectively. Pkd2lrm4 mutants strongly phenocopy Pkd1l1rks embryos with severe left-right defects. Based on this, we hypothesise that Pkd1l1 and Pkd2 are both required for the sensation of nodal flow. In support, we find that Pkd1l1 localises to primary cilia in a Pkd2-dependent manner and that Pkd1l1 and Pkd2 can form physical associations. The Pkd1l1rks point mutation lies in an extracellular PKD domain, specifically implicating this domain in the establishment of left-right asymmetry. We are performing cell-based experiments to understand the mechanism of Pkd1l1 function as well as computational and biophysical assays to assess the nature of the PKD domain and how its structure and function are affected by the Pkd1l1rks mutation.

Comparative Study of Symmetrical and Asymmetrical Network Parameters in Smart Grid Infrastructure

this paper, a comparative study of symmetric and asymmetric network for smart grid is proposed. In smart grid different nodes may be present with different capabilities, such as depending upon manufacturer, sensitivity of different nodes may changes. This significantly keeps impacts on the range of the parent node. Random nature of the infrastructure may changes the power capabilities to send the information to the parent node. This needs the power which is directly proportional to the physical distance between respective nodes. RPL (Routing Protocol for Low Power and Lossy Network) is proposed for the LLN (Low Power and Lossy Network) network which closely resemblance the infrastructure of smart grid. It's independent on the physical layer parameters and useful in the Cognitive Radio aspect. For symmetric nodes we compute the bidirectional links and node can directly communicate with its parent node without any extra overhead, however in asymmetric nature node needs to discover the multiple paths and may increase the overhead. In this paper we proposed different parameter which keeps significant impact on asymmetric network for smart grid.

Modeling bee swarming behavior through diffusion adaptation with asymmetric information sharing

Honeybees swarm when they move to a new site for their hive. During the process of swarming, their behavior can be analyzed by classifying them as informed bees or uninformed bees, where the informed bees have some information about the destination while the uninformed bees follow the informed bees. The swarm's movement can be viewed as a network of mobile nodes with asymmetric information exchange about their destination. In these networks, adaptive and mobile agents share information on the fly and adapt their estimates in response to local measurements and data shared with neighbors. Diffusion adaptation is used to model the adaptation process in the presence of asymmetric nodes and noisy data. The simulations indicate that the models are able to emulate the swarming behavior of bees under varied conditions such as a small number of informed bees, sharing of target location, sharing of target direction, and noisy measurements.

Inscribing Asymmetry: Johann Zoffany's Banyan and ‘The Extension of Knowledge’

This article focuses on the banyan tree in Johann Zoffany's conversation piece painted in Lucknow around 1786–87. One of the most striking motifs in the composition, it has rarely been analyzed, especially within the context of what Warren Hastings called, ‘the extension of knowledge’ in colonial India. Specifically, I examine how its conflation with the artist's self-portrait spatialized the primeval within the orbit of collecting for the ‘gentleman Orientalist’. Such an interpolation, I suggest, links key members of Lucknow's colonial elite portrayed in the painting with the newly instituted Asiatic Society in nearby Calcutta. To this end, I look at how the banyan encodes asymmetrical patterns of knowledge within new European loci of history and geography in India. Not only does it situate the performance of colonial gentlemanliness in a sensibility for the protean, it also conveys Zoffany's own agency in producing and affixing colonial knowledge. Thus, I discuss how the banyan metonymically stands for an emergent network of colonial cosmopolitanism in two very different centres of collecting and knowledge-formation. Furthermore, I posit that Zoffany anchors colonial knowledge in asymmetrical nodes through which ‘native’ cultural spaces and paradigms were rearranged into an uneven grid of information.

The Twenty-First Century Security Environment: Challenges for Joint Forces

The twenty-first century battlefield is increasingly characterised by asymmetric warfare, irregular techniques and multi-centric nodes of power. This requires a balanced joint force that is able to adapt to new operational requirements as well as meet conventional strategic needs. But is the military establishment ready for the challenges of globalised (in)security?

Asymboost-based fisher linear classifier for face recognition

When using AdaBoost to select discriminant features from some feature space (e.g. Gabor feature space) for face recognition, cascade structure is usually adopted to leverage the asymmetry in the distribution of positive and negative samples. Each node in the cascade structure is a classifier trained by AdaBoost with an asymmetric learning goal of high recognition rate but only moderate low false positive rate. One limitation of AdaBoost arises in the context of skewed example distribution and cascade classifiers: AdaBoost minimizes the classification error, which is not guaranteed to achieve the asymmetric node learning goal. In this paper, we propose to use the asymmetric AdaBoost (AsymBoost) as a mechanism to address the asymmetric node learning goal. Moreover, the two parts of the selecting features and forming ensemble classifiers are decoupled, both of which occur simultaneously in AsymBoost and AdaBoost. Fisher Linear Discriminant Analysis (FLDA) is used on the selected features to learn a linear discriminant function that maximizes the separability of data among the different classes, which we think can improve the recognition performance. The proposed algorithm is demonstrated with face recognition using a Gabor based representation on the FERET database. Experimental results show that the proposed algorithm yields better recognition performance than AdaBoost itself.

Queueing Networks and Markov Chains: Modeling and Performance Evaluation with Computer Science Applications

Preface to the Second Edition. Preface to the First Edition. 1. Introduction. 1.1 Motivation. 1.2 Methodological Background. 1.3 Basics of Probability and Statistics. 2. Markov Chains. 2.1 Markov Processes. 2.2 Performance Measures. 2.3 Generation Methods. 3. Steady-State Solutions of Markov Chains. 3.1 Solution for a Birth Death Process. 3.2 Matrix-Geometric Method: Quasi-Birth-Death Process. 3.3 Hessenberg Matrix: Non-Markovian Queues. 3.4 Numerical Solution: Direct Methods. 3.5 Numerical Solution: Iterative Methods. 3.6 Comparison of Numerical Solution Methods. 4. Steady-State Aggregation/Disaggregation Methods. 4.1 Courtois' Approximate Method. 4.2 Takahashi's Iterative Method. 5. Transient Solution of Markov Chains. 5.1 Transient Analysis Using Exact Methods. 5.2 Aggregation of Stiff Markov Chains. 6. Single Station Queueing Systems. 6.1 Notation. 6.2 Markovian Queues. 6.3 Non-Markovian Queues. 6.4 Priority Queues. 6.5 Asymmetric Queues. 6.6 Queues with Batch Service and Batch Arrivals. 6.7 Retrial Queues. 6.8 Special Classes of Point Arrival Processes. 7. Queueing Networks. 7.1 Definitions and Notation. 7.2 Performance Measures. 7.3 Product-Form Queueing Networks. 8. Algorithms for Product-Form Networks. 8.1 The Convolution Algorithm. 8.2 The Mean Value Analysis. 8.3 Flow Equivalent Server Method. 8.4 Summary. 9. Approximation Algorithms for Product-Form Networks. 9.1 Approximations Based on the MVA. 9.2 Summation Method. 9.3 Bottapprox Method. 9.4 Bounds Analysis. 9.5 Summary. 10. Algorithms for Non-Product-Form Networks. 10.1 Nonexponential Distributions. 10.2 Different Service Times at FCFS Nodes. 10.3 Priority Networks. 10.4 Simultaneous Resource Possession. 10.5 Prograrns with Internal Concurrency. 10.6 Parallel Processing. 10.7 Networks with Asymmetric Nodes. 10.8 Networks with Blocking. 10.9 Networks with Batch Service. 11. Discrete-Event Simulation. 11.1 Introduction to Simulation. 11.2 Simulative or Analytic Solution? 11.3 Classification of Simulation Models. 11.4 Classification of Tools in DES. 11.5 The Role of Probability and Statistics in Simulation. 11.6 Applications. 12. Performance Analysis Tools. 12.1 PEPSY. 12.2 SPNP. 12. 3 MOSEL-2. 12.4 SHARPE. 12.5 Characteristics of Some Tools. 13. Applications. 13.1 Case Studies of Queueing Networks. 13.2 Case Studies of Markov Chains. 13.3 Case Studies of Hierarchical Models. Glossary. Bibliography. Index.

Postnatal differentiation of rat optic nerve fibers: electron microscopic observations on the development of nodes of Ranvier and axoglial relations.

The postnatal differentiation of rat optic nerve fibres was examined by transmission electron microscopy. The results show that many early developing axons contain clusters of vesiculotubular profiles prior to myelination. At places vesicular elements appear to fuse with the axolemma, and, in addition, some axons exhibit deep axolemmal invaginations and axoplasmic lamellated bodies. It is suggested that these features might reflect axolemmal remodelling, possibly involving axoglial signalling and/or functional differentiation of the axolemma. The size distribution of unmyelinated optic nerve axons changes little during development. Ensheathment of larger axons commences 6 days postnatally. The subsequent formation of compact myelin sheaths is accompanied by an increase in axonal diameter. The early sheaths are a few microns long and separated by long bare axon segments. In optic nerves from 10-12-day-old rat pups, a few sheaths consisting of about five layers border primitive asymmetric nodes with a patchy axolemmal undercoating. Extensions from one of the terminating sheaths are often associated with undercoated patches of axolemma. Relatively differentiated nodes of Ranvier first appear 14-16 days after birth. The continued nodal maturation involves establishment of a regular nodal geometry, increasing distinctness of the axolemmal undercoating, and formation of perinodal astrocytic processes embedded in an extracellular node gap substance. The results are compared with available data on the conduction properties of rat optic nerve fibres during development.

Asymmetric dislocation nodes in CuAl alloys

Single crystals of Cu-5 and Cu-10 at% Al are strained at room temperature up to the onset of stage II of the work-hardening curve. TEM images show periodic dislocation networks with asymmetric nodes of primary, secondary, and Lomer-Cottrell dislocations as unit elements. Two geometrically different types of nodes can occur. The internal stresses associated with these nodes are numerically computed within the framework of the anisotropic theory of elasticity. When the experimentally observed configurations are compared with the calculated stress-free equilibrium positions marked deviations are evident. These differences are attributed to the high friction stress in these alloys. Einkristalle der Legierungen Cu-5 und Cu-10 At% Al werden bei Raumtemperatur bis zum Beginn des Bereiches II der Verfestigungskurve verformt. TEM-Aufnahmen zeigen periodische Versetzungsgitter, die aus asymmetrischen Knoten mit primaren, sekundaren und Lomer-Cottrell-Versetzungen als Einheitselement aufgebaut sind. Zwei geometrisch verschiedene Knotentypen konnen auftreten. Die von diesen Knoten verursachten inneren Spannungsfelder werden im Rahmen der anisotropen Elastizitatstheorie numerisch berechnet. Die experimentell beobachteten Gleichgewichtskonfigurationen werden mit den berechneten spannungsfreien Gleichgewichtspositionen verglichen. Die dabei festgestellten Abweichungen sind auf die hohen Reibungskrafte in diesen Legierungen zuruckzufuhren.

The Determination of Homogenized Group Diffusion Theory Parameters

A method for obtaining homogenized group-diffusion-theory parameters for heterogeneous nodes (fuel regions plus control elements plus structure) in slab geometry is described. The parameters obtained reproduce exactly the neutron leakage and the integrated reaction rates of the node when it becomes part of a reactor. However, for asymmetric nodes they depend on the fluxes and currents at the surfaces of the node. The sensitivity of this dependence is examined for a one-group model, and numerical examples are given to illustrate that for symmetric nodes, the equivalent parameters are indeed exact and independent of conditions outside the node. For unsymmetric nodes, it is shown that using a set of parameters that is an average of two sets of “exact parameters,” one appropriate to large values of current-to-flux ratio at one of the nodal surfaces and the other appropriate to small values, still yields quite accurate results. For both cases comparisons with results obtained using standard flux-weighted parameters are made.