Vertices In Network Research Articles

Analysis on evolution characteristics and influencing factors of global energy pattern under anti-globalization background

With the rapid development of international energy trade, its structure has shown a trend toward complexity and network development. The traditional unilateral or bilateral perspective of causal analysis can no longer explain the changes in the international energy trade network at this stage. This paper constructs the world energy trade network from 2000 to 2020, analyzes the structural characteristics of the network, and adopts the quadratic assignment procedure method to deconstruct and explain the structural evolution of the world energy trade network. The study shows that the global energy trade network is increasingly connected and has small-world characteristics; the growing global energy demand coexists with the increasing energy monopoly; GDP difference and geographical distance are the decisive factors in forming an international energy trade network. It is suggested that countries should strengthen the integrated development of energy trade; formulate differentiated regional policies according to the structure and economic development characteristics of national and regional energy trade; pay more attention to the hub vertexes in the international energy trade network; and formulate differentiated energy strategies for countries and regions with different development levels, taking into account their development situations.

Greedy and branches-and-boundaries methods for the optimal choice of a subset of vertices in a large communication network

The problems of the proposed paper are generated by the actual tasks of communication networks. The development of communication resources is accompanied by an increase in the dimension of existing communication networks, for which the usual tools for solving network problems are becoming increasingly ineffective.At the same time, the spectrum of communication network problems covers both classical graph theory problems and specialized problems linking them with mathematical models of various fields of mathematics, including optimization theory, dynamic programming, probability theory and the theory of heuristic algorithms. This paper is devoted to the study of the problem of optimal allocation of a certain resource on the objects of the communication network. In this case, a complete set of specialized equipment at the nodes of the communication network is considered as a resource. It is necessary to optimize the number of pieces of equipment with the condition that all fiber-optic communication lines of the network are under the control of installed reflectometers. To solve this problem, variants of two methods were described: the greedy algorithm and the method of branches and boundaries. On the basis of the described algorithms, the computer programs were implemented and computational experiments were carried out; in the latter, the dimension of the communication network was chosen high enough to guarantee the legality of using the selected variants of algorithms for real communication networks. A representative series of experiments has shown that it is more expedient to use variants of the greedy heuristic algorithm for the group of problems under consideration, this paper contains a detailed argumentation of the result obtained. The considered problem can also be transferred to cases of optimal placement of other resources on the objects of the communication network. At the same time, if there is a specific objective function, there will be another formalization of restrictions. But the approaches to choosing the optimum may be identical, which makes the results obtained in the paper more important due to their participation in potential generalizations of the problem.

Identifying and Eliminating Majority Illusion in Social Networks

Majority illusion occurs in a social network when the majority of the network vertices belong to a certain type but the majority of each vertex's neighbours belong to a different type, therefore creating the wrong perception, i.e., the illusion, that the majority type is different from the actual one. From a system engineering point of view, this motivates the search for algorithms to detect and, where possible, correct this undesirable phenomenon. In this paper we initiate the computational study of majority illusion in social networks, providing NP-hardness and parametrised complexity results for its occurrence and elimination.

Stanza-based networks for poetic texts: a pilot study

Abstract We use approaches from the theory of complex networks to analyze the Prologue to Moses, a poem by the Ukrainian writer and scholar Ivan Franko. The Ukrainian text (in the original orthography from 1905 and the modern one) and several translations into Polish, English, French, German, Italian, Portuguese, Slovak, and Spanish are studied. Networks are built in a manner that links are drawn between words (considered network vertices) within a stanza. Seven network parameters are calculated: all-degree centralization, assortativity, average path length, betweenness, clustering coefficient, density, and transitivity. Their dynamics is analyzed as the vertices with the highest numbers of links are removed from the networks one by one. The data obtained for the human-made translations are compared to those based on machine translations generated by the Google Translate service. Peculiarities of certain translations are underlined. Tentative correlation between the values of parameters and levels of language analyticity/syntheticity are established. Prospects toward automatic lemmatization and related problems to be solved are briefly outlined.

Teaching Methodology for Topography: Didactic Proposal for the Free Station Survey Method

This article presents an innovative proposal for teaching Topography topics, as there are no qualified official publications on the subject of study referring to topographic positioning by the free station method, resulting in a shortage of didactic material on this topic in educational institutions in Brazil. Thus, the research work resulted from the didactics applied in the Topography discipline, of the UFPE's Cartographic Engineering degree program. It was proposed to the students to accomplish some practices of the free station method during the Topography discipline development. Thus, the students carried out a theoretical study on the topic. Subsequently, field work was developed with topographic equipment containing a program for surveying by free station method. Topographic vertices of the cadastral reference network of the “Joaquim Amazonas” campus of UFPE served as reference and adjustment points. A comparative analysis of the results calculated manually with the results obtained by the internal programs of the topographic equipment was carried out, using the official coordinates of the cadastral network as references. A program was developed in MATLAB for fixing the learning, whose results were also compared with the same official reference coordinates. This made it possible to generate a complete quantitative statistical analysis of the results.

Task: An Efficient Framework for Instant Error-Tolerant Spatial Keyword Queries on Road Networks

Instant spatial keyword queries return the results as soon as users type in some characters instead of a complete keyword, which allow users to query the geo-textual data in a type-as-you-search manner. However, the existing methods of instant spatial keyword queries suffer from several limitations. For example, the existing methods do not consider the typographical errors of input keywords, and cannot be applied to the road networks. To overcome these limitations, in this paper, we propose a new query type, i.e., instant error-tolerant spatial keyword queries on road networks. To answer the queries efficiently, we present a framework, termed as Task, which consists of index component, query component, and update component. In the index component, we design a novel index called reverse 2-hop label based trie, which seamlessly integrates spatial and textual information for each vertex of the road network. Based on our proposed index, we devise efficient algorithms to progressively return and update the query results in the query component and update component, respectively. Finally, we conduct extensive experiments on real-world road networks to evaluate the performance of our presented Task. Empirical results show that our proposed index and algorithms are up to 1--2 orders of magnitude faster than the baseline.

Temporal network modeling with online and hidden vertices based on the birth and death process

Complex networks have played an important role in describing real complex systems since the end of the last century. Recently, research on real-world data sets reports intermittent interaction among social individuals. In this paper, we pay attention to this typical phenomenon of intermittent interaction by considering the state transition of network vertices between online and hidden based on the birth and death process. By continuous-time Markov theory, we show that both the number of each vertex’s online neighbors and the online network size are stable and follow the homogeneous probability distribution in a similar form, inducing similar statistics as well. In addition, all propositions are verified via simulations. Moreover, we also present the degree distributions based on small-world and scale-free networks and find some regular patterns by simulations. The application in fitting real networks is discussed.

Epileptic-network-based prediction and control of seizures in humans

Epilepsy is now conceptualized as a network disease. The epileptic brain network comprises structurally and functionally connected cortical and subcortical brain regions – spanning lobes and hemispheres –, whose connections and dynamics evolve in time. With this concept, focal and generalized seizures as well as other related pathophysiological phenomena are thought to emerge from, spread via, and be terminated by network vertices and edges that also generate and sustain normal, physiological brain dynamics. Research over the last years has advanced concepts and techniques to identify and characterize the evolving epileptic brain network and its constituents on various spatial and temporal scales. Network-based approaches further our understanding of how seizures emerge from the evolving epileptic brain network, and they provide both novel insights into pre-seizure dynamics and important clues for success or failure of measures for network-based seizure control and prevention. In this review, we summarize the current state of knowledge and address several important challenges that would need to be addressed to move network-based prediction and control of seizures closer to clinical translation.

Informed simulation for dynamic path finding in human-operated container terminals

Path finding for human-operated vehicles in a maritime container terminal can be very demanding, especially when pursued under dynamic traffic conditions and based on decisions that are self-governing. Preventing collision and interference among internal transfer vehicles is a major task for operations managers in organizing container transfers from the quay to the yard at minimal congestion. To this matter, we propose a novel simulation framework as an effective tool for managing conflicting goals among straddle carrier (SC) drivers. The framework embeds both local and global search strategies that are used to determine the best path between any two vertices of the grid-like transfer network. Furthermore, it also allows to make path finding decisions based on either dynamic or static data. Numerical experiments prove the effectiveness of this informed simulation-based approach. Specifically, when critical extraordinary events arise and force, for instance, SCs to cover greater distances during container transfer, the difference in performance achieved by using the local/global path finding strategy in conjunction with static/dynamic data becomes more significant.

Comparative Study of Prism Octahedron Network via Eccentric Invariants

Topological indices are empirical features of graphs that characterize the topology of the graph and, for the most part, are graph independent. An important branch of graph theory is chemical graph theory. In chemical graph theory, the atoms corresponds vertices and edges corresponds covalent bonds. A topological index is a numeric number that represents the topology of underline structure. In this article, we examined the topological properties of prism octahedron network of dimension m and computed the total eccentricity, average eccentricity, Zagreb eccentricity, geometric arithmetic eccentricity, and atom bond connectivity eccentricity indices, which are used to utilize the distance between the vertices of a prism octahedron network.

Biotic interactions contribute more than environmental factors and geographic distance to biogeographic patterns of soil prokaryotic and fungal communities.

Recent studies have shown distinct soil microbial assembly patterns across taxonomic types, habitat types and regions, but little is known about which factors play a dominant role in soil microbial communities. To bridge this gap, we compared the differences in microbial diversity and community composition across two taxonomic types (prokaryotes and fungi), two habitat types (Artemisia and Poaceae) and three geographic regions in the arid ecosystem of northwest China. To determine the main driving factors shaping the prokaryotic and fungal community assembly, we carried out diverse analyses including null model, partial mantel test and variance partitioning analysis etc. The findings suggested that the processes of community assembly were more diverse among taxonomic categories in comparison to habitats or geographical regions. The predominant driving factor of soil microbial community assembly in arid ecosystem was biotic interactions between microorganisms, followed by environmental filtering and dispersal limitation. Network vertex, positive cohesion and negative cohesion showed the most significant correlations with prokaryotic and fungal diversity and community dissimilarity. Salinity was the major environmental variable structuring the prokaryotic community. Although prokaryotic and fungal communities were jointly regulated by the three factors, the effects of biotic interactions and environmental variables (both are deterministic processes) on the community structure of prokaryotes were stronger than that of fungi. The null model revealed that prokaryotic community assembly was more deterministic, whereas fungal community assembly was structured by stochastic processes. Taken together, these findings unravel the predominant drivers governing microbial community assembly across taxonomic types, habitat types and geographic regions and highlight the impacts of biotic interactions on disentangling soil microbial assembly mechanisms.

Layer-Specific Modules Detection in Cancer Multi-Layer Networks.

Multi-layer networks provide an effective and efficient tool to model and characterize complex systems with multiple types of interactions, which differ greatly from the traditional single-layer networks. Graph clustering in multi-layer networks is highly non-trivial since it is difficult to balance the connectivity of clusters and the connection of various layers. The current algorithms for the layer-specific clusters are criticized for the low accuracy and sensitivity to the perturbation of networks. To overcome these issues, a novel algorithm for the layer-specific module in multi-layer networks based on nonnegative matrix factorization (LSNMF) is proposed by explicitly exploring the specific features of vertices. LSNMF first extract features of vertices in multi-layer networks by using nonnegative matrix factorization (NMF) and then decompose features of vertices into the common and specific components. The orthogonality constraint is imposed on the specific components to ensure the specificity of features of vertices, which provides a better strategy to characterize and model the structure of layer-specific modules. The extensive experiments demonstrate that the proposed algorithm dramatically outperforms state-of-the-art baselines in terms of various measurements. Furthermore, LSNMF efficiently extracts stage-specific modules, which are more likely to enrich the known functions, and also associate with the survival time of patients.

Algorithm for finding subcritical paths on network diagrams

Objectives . Network diagrams are used as an information support element in planning and project management processes for structuring planned work and calculating project efficiency characteristics. In order to optimize and balance resources used in projects, it becomes necessary to locate in these models not only the critical path of the maximum weighted length, but also the subcritical paths closest to it having a shorter length in relation to it. The aim of the work is to synthesize and analyze an algorithm for finding k -shortest paths between the input and output network vertices, on which basis the above-mentioned subcritical paths can be identified. Methods . The provisions of graph theory and group theory, as well as the method of dynamic programming, were used. Results . An algorithm for finding k- shortest paths in contourless directed graphs having a strict order relation was developed. Abstract elements were defined according to group theory in graphs as p- contours, between which a multilevel structure of relations for implementing the necessary search of paths was then established. For substantiating the efficiency of the constructed algorithm, the validity of the main provisions was demonstrated as follows: firstly, the multilevel system of relations is exhaustive; secondly, there is no loss in the final solution during the operation of the algorithm; thirdly, the paths obtained as a result of the work of the algorithm satisfy the main required relation between them. Numerically, the algorithm was implemented by the dynamic programming method extended by means of an additional functional relationship, implying the presence of suboptimal policies. Conclusions . The conducted runs of computational experiments confirmed the operability and efficiency of the software-implemented algorithm. The performed analysis demonstrated the good convergence characteristics of the proposed algorithm as compared with other algorithms of this class applied to network diagrams. On this basis, it can be recommended for practical use in project management information systems.

Grey Median Problem and Vertex Optimality

The median problem is a basic model in location theory and transportation sciences. This problem deals with locating a facility on a network, to minimize the sum of weighted distances between the facility and the vertices of the network. In this paper, the cases that weights of vertices, edge lengths or both of them are grey numbers, are considered. For all these cases, we show that the set of vertices of network contains a solution of the median problem. This property is called vertex optimality. Median problem with grey parameters and its properties are first considered in this paper.

BioNAR: an integrated biological network analysis package in bioconductor.

Biological function in protein complexes emerges from more than just the sum of their parts: molecules interact in a range of different sub-complexes and transfer signals/information around internal pathways. Modern proteomic techniques are excellent at producing a parts-list for such complexes, but more detailed analysis demands a network approach linking the molecules together and analysing the emergent architectural properties. Methods developed for the analysis of networks in social sciences have proven very useful for splitting biological networks into communities leading to the discovery of sub-complexes enriched with molecules associated with specific diseases or molecular functions that are not apparent from the constituent components alone. Here, we present the Bioconductor package BioNAR, which supports step-by-step analysis of biological/biomedical networks with the aim of quantifying and ranking each of the network's vertices based on network topology and clustering. Examples demonstrate that while BioNAR is not restricted to proteomic networks, it can predict a protein's impact within multiple complexes, and enables estimation of the co-occurrence of metadata, i.e. diseases and functions across the network, identifying the clusters whose components are likely to share common function and mechanisms. The package is available from Bioconductor release 3.17: https://bioconductor.org/packages/release/bioc/html/BioNAR.html.

Comparative Study of Planar Octahedron Molecular Structure via Eccentric Invariants

A branch of graph theory that makes use of a molecular graph is called chemical graph theory. Chemical graph theory is used to depict a chemical molecule. A graph is connected if there is an edge between every pair of vertices. A topological index is a numerical value related to the chemical structure that claims to show a relationship between chemical structure and various physicochemical attributes, chemical reactivity, or, you could say, biological activity. In this article, we examined the topological properties of a planar octahedron network of m dimensions and computed the total eccentricity, average eccentricity, Zagreb eccentricity, geometric arithmetic eccentricity, and atom bond connectivity eccentricity indices, which are used to determine the distance between the vertices of a planar octahedron network.

Evaluation of the applicability of the lattice radiotherapy technique at the National Cancer Institute - INCA.

Lattice is a 3-dimensional spatially fractionated radiotherapy that uses a distribution of high-doses, similar to spheres at vertices of a 3D network or matrix. These vertices that receive the high-dose are called peaks, while the rest of the target volume that receives a lower dose, is called the valley. This study aims to verify the technical feasibility for Spatially Fractionated Radiation Therapy treatment using the Lattice technique performed with VMAT at the National Cancer Institute José Alencar Gomes da Silva - INCA, Unit I. Ten patient cases were selected, with gross tumor volumes ranging from 90 to 1734 cc. A literature review was carried out to determine the geometry, the distribution of peaks and the peak to valley dose ratio that will be used in the Lattice technique plans. The dose distributions in the targets and organs at risk of the Lattice plans were clinically compared with the plans without the peaks. A configuration of spheres with diameter of 1.2 cm, separated center-to-center by 3 cm and with a prescription of 14 Gy in a single dose at these peaks was estabilished, while the valley had a prescription of 25 Gy in 5 fractions. Despite the increase in the prescribed equivalent dose in 2 Gy fractions from 40 Gy to 79.3 Gy, the median increase in doses to the OARs was 2.7%, with a maximum increase of 14.7%. The quality control of the plans was approved through the gamma analysis of the measurements performed with the Varian EPID. These findings demonstrate the technical feasibility of SFRT using the lattice technique with VMAT, and suggest that it may provide an effective delivery of high radiation therapy doses to tumors while minimizing the damage to surrounding healthy tissues.

A Discussion of “A Note on Universal Inference” by Tse and Davison

A Discussion of “A Note on Universal Inference” by Tse and Davison

Managing Time Expanded Networks through Project and Lift: the Lift Issue

Time Expanded Networks, built by considering the vertices of a base network over some time space, are powerful tools for the formulation of problems that simultaneously involve resource assignment and scheduling. Still, in most cases, deriving algorithms from those formulations is difficult, due to both the size of the resulting models and the propagation of time rounding errors. The purpose of this paper is to address this algorithmic issue. We propose a generic Project and Lift decomposition scheme, and focus, inside this decomposition scheme, on the Lift issue, which consists in turning a solution defined on the base network into a solution in the time expanded space.

BCCC Disjoint Path Construction Algorithm and Fault-Tolerant Routing Algorithm under Restricted Connectivity

Connectivity in large-scale data center networks is a critical indicator to evaluate network state. A feasible and performance-guaranteed algorithm enables us to find disjoint paths between network vertices to ensure effective data transfer and to maintain the normal operation of network in case of faulty nodes. As an important data center network, BCube Connected Crossbars (BCCC) has many excellent properties that have been widely studied. In this paper, we first propose a vertex disjoint path algorithm with the time complexity of O(nk) in BCCC, where n denotes a switch connected to n servers and k denotes dimension. Then, we prove that the restricted connectivity of BCCC(n,k). Finally, we present an O(knκ1(G)) fault-free algorithm in BCCC, where κ1(G) is the restricted connectivity. This algorithm can obtain a fault-free path between any two distinct fault-free vertices under the condition that each vertex has at least one fault-free neighbor in the BCCC and a set of faulty vertices F with |F|<κ1(G).