scholarly journals EPIDEMIC INDIVIDUAL-BASED MODELS APPLIED IN RANDOM AND SCALE-FREE NETWORKS

2020 ◽  
Vol 38 (1) ◽  
pp. 102
Author(s):  
Christofer Roque Ribeiro SILVA ◽  
Alexandre Celestino Leite ALMEIDA ◽  
Rodrigo Tomás Nogueira CARDOSO ◽  
Ricardo Hiroshi Caldeira TAKAHASHI
Keyword(s):  
Large Scale ◽  
Deterministic Model ◽  
Statistical Tests ◽  
Network Models ◽  
Scale Free ◽  
Individual Based Models ◽  
Network Topologies ◽  
Large Scale Networks ◽  
The Individual

This work proposes a version of the Individual-Based Model (IBM) that converges, on average, to the result of the SIR (Susceptible-Infected-Recovered) model, and studies the effect of this IBM in two types of networks: random and scale-free. A numerical computational case study is considered, using large scale networks implemented by an efficient framework. Statistical tests are performed to show the similarities and differences between the network models and the deterministic model taken as a baseline. Simulation results verify that different network topologies alter the behavior of the epidemic propagation in the following aspects: temporal evolution, basal reproducibility and the number of infected in the final.

Incremental Community Detection on Large Complex Attributed Network

2021 ◽  
Vol 15 (6) ◽  
pp. 1-20
Author(s):  
Zhe Chen ◽  
Aixin Sun ◽  
Xiaokui Xiao
Keyword(s):  
Community Detection ◽  
Large Scale ◽  
Network Data ◽  
Topological Information ◽  
Community Membership ◽  
Attributed Network ◽  
Benchmark Datasets ◽  
Modularity Maximization ◽  
Large Scale Networks

Community detection on network data is a fundamental task, and has many applications in industry. Network data in industry can be very large, with incomplete and complex attributes, and more importantly, growing. This calls for a community detection technique that is able to handle both attribute and topological information on large scale networks, and also is incremental. In this article, we propose inc-AGGMMR, an incremental community detection framework that is able to effectively address the challenges that come from scalability, mixed attributes, incomplete values, and evolving of the network. Through construction of augmented graph, we map attributes into the network by introducing attribute centers and belongingness edges. The communities are then detected by modularity maximization. During this process, we adjust the weights of belongingness edges to balance the contribution between attribute and topological information to the detection of communities. The weight adjustment mechanism enables incremental updates of community membership of all vertices. We evaluate inc-AGGMMR on five benchmark datasets against eight strong baselines. We also provide a case study to incrementally detect communities on a PayPal payment network which contains users with transactions. The results demonstrate inc-AGGMMR’s effectiveness and practicability.

scholarly journals The unraveling of balanced complexes in metabolic networks

2021 ◽  
Author(s):  
Damoun Langary ◽  
Anika Kueken ◽  
Zoran Nikoloski
Keyword(s):  
Steady State ◽  
Large Scale ◽  
Metabolic Networks ◽  
Network Models ◽  
Steady States ◽  
Biochemical Networks ◽  
Computational Approaches ◽  
Metabolic Models ◽  
Large Scale Networks ◽  
General Conditions

Balanced complexes in biochemical networks are at core of several theoretical and computational approaches that make statements about the properties of the steady states supported by the network. Recent computational approaches have employed balanced complexes to reduce metabolic networks, while ensuring preservation of particular steady-state properties; however, the underlying factors leading to the formation of balanced complexes have not been studied, yet. Here, we present a number of factorizations providing insights in mechanisms that lead to the origins of the corresponding balanced complexes. The proposed factorizations enable us to categorize balanced complexes into four distinct classes, each with specific origins and characteristics. They also provide the means to efficiently determine if a balanced complex in large-scale networks belongs to a particular class from the categorization. The results are obtained under very general conditions and irrespective of the network kinetics, rendering them broadly applicable across variety of network models. Application of the categorization shows that all classes of balanced complexes are present in large-scale metabolic models across all kingdoms of life, therefore paving the way to study their relevance with respect to different properties of steady states supported by these networks.

A Comparative Analysis of Dam Safety Assurance Laws

2014 ◽  
Vol 1 (1) ◽  
pp. 29-57 ◽  
Author(s):  
John Dean Pisaniello
Keyword(s):  
Comparative Analysis ◽  
Large Scale ◽  
Safety Management ◽  
Dam Safety ◽  
Safety Issues ◽  
Safety Assurance ◽  
The World ◽  
The Individual ◽  
Privately Owned

A number of horrific failures of both public and privately owned dams in recent decades has triggered serious concern over the safety of dams throughout the world. However, in Australia, although much Government attention is being devoted to the medium- to large-scale dams, minimal attention is being paid to the serious potential cumulative, catchment-wide problems associated with smaller private dams. The paper determines how to consider addressing hazardous private dam safety issues generally through a comparative analysis of international dam safety policy/law systems. The analysis has identified elements of best and minimum practice that can and do exist successfully to provide deserved assurance to the community of the proper safety management of hazardous private dams at both the individual and cumulative, catchment-wide levels. These elements provide benchmarks that enable ‘appropriate’ legislative arrangements to be determined for different jurisdictional circumstances as illustrated with an Australian policy-deficient case study.

scholarly journals Distance-Based Routing Strategy for Traffic Transport in Spatial Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Wei Huang ◽  
Xiang Pan ◽  
Xi Yang ◽  
Jianhua Zhang
Keyword(s):  
Spatial Scale ◽  
Large Scale ◽  
Spatial Information ◽  
Good Choice ◽  
Spatial Distance ◽  
Greedy Routing ◽  
Scale Free ◽  
Routing Strategy ◽  
Scale Free Networks ◽  
Large Scale Networks

It is well known that routing strategies based on global topological information is not a good choice for the enhancement of traffic throughput in large-scale networks due to the heavy communication cost. On the contrary, acquiring spatial information, such as spatial distances among nodes, is more feasible. In this paper, we propose a novel distance-based routing strategy in spatial scale-free networks, called LDistance strategy. The probability of establishing links among nodes obeys the power-law in the spatial network under study. Compared with the LDegree strategy (Wang et al., 2006) and the mixed strategy (a strategy combining both greedy routing strategy and random routing strategy), results show that our proposed LDistance strategy can further enhance traffic capacity. Besides, the LDistance strategy can also achieve a much shorter delivering time than the LDegree strategy. Analyses reveal that the superiority of our strategy is mainly due to the interdependent relationship between topological and spatial characteristics in spatial scale-free networks. Furthermore, along transporting path in the LDistance strategy, the spatial distance to destination decays more rapidly, and the degrees of routers are higher than those in the LDegree strategy.

scholarly journals Strategies for Monitoring Multiuse Trail Networks

2017 ◽  
Vol 2644 (1) ◽  
pp. 100-110 ◽  
Author(s):  
Greg Lindsey ◽  
Jeffrey S. Wilson ◽  
Jueyu Wang ◽  
Tracy Hadden-Loh
Keyword(s):  
Nonprofit Organizations ◽  
Large Scale ◽  
Low Cost ◽  
Facility Planning ◽  
Monitoring Networks ◽  
Site Specific ◽  
New Challenges ◽  
Large Scale Networks ◽  
Selection Of

Many municipalities, park districts, and nonprofit organizations have begun monitoring nonmotorized traffic on multiuse trails as the need for information about the use of facilities has grown and relatively low-cost sensors for automated monitoring have become available. As they have gained experience, they have begun to move from site-specific monitoring on individual trails to a more comprehensive monitoring of trail networks. This case study review compares strategies developed by 10 organizations for monitoring traffic on multiuse trails, including local, multicounty, statewide, and multistate trail networks. The focus is on approaches to the design of monitoring networks, particularly the rationales or objectives for monitoring and the selection of monitoring sites. It is shown that jurisdictions are following principles of monitoring established by FHWA and that the design of monitoring networks is evolving to meet new challenges, including monitoring large-scale networks. Relevant outcomes and implications for practice are summarized. The researchers concluded that FHWA guidelines can be adapted to many circumstances and can increase information for decision making. Trail monitoring is informing decisions related to facility planning, investment, and safety.

scholarly journals Efficient network immunization under limited knowledge

2020 ◽  
Author(s):  
Yangyang Liu ◽  
Hillel Sanhedrai ◽  
GaoGao Dong ◽  
Louis M. Shekhtman ◽  
Fan Wang ◽  
...  
Keyword(s):  
Large Scale ◽  
Complete Information ◽  
Analytical Framework ◽  
Epidemic Spreading ◽  
Scale Free ◽  
Scaling Relationship ◽  
Optimal Value ◽  
Random Failure ◽  
Large Scale Networks ◽  
Significant Attention

Targeted immunization or attacks of large-scale networks has attracted significant attention by the scientific community. However, in real-world scenarios, knowledge and observations of the network may be limited thereby precluding a full assessment of the optimal nodes to immunize (or remove) in order to avoid epidemic spreading such as that of current COVID-19 epidemic. Here, we study a novel immunization strategy where only n nodes are observed at a time and the most central between these n nodes is immunized (or attacked). This process is continued repeatedly until 1 − p fraction of nodes are immunized (or attacked). We develop an analytical framework for this approach and determine the critical percolation threshold pc and the size of the giant component P∞; for networks with arbitrary degree distributions P(k). In the limit of n → ∞ we recover prior work on targeted attack, whereas for n = 1 we recover the known case of random failure. Between these two extremes, we observe that as n increases, pc increases quickly towards its optimal value under targeted immunization (attack) with complete information. In particular, we find a new scaling relationship between |pc(∞) − pc(n) | and n as |pc(∞) − pc(n)| ~ n−1 exp(−αn). For Scale-free (SF) networks, where P(k) ~ k−γ, 2 < γ < 3, we find that pc has a transition from zero to non-zero when n increases from n = 1 to order of logN (N is the size of network). Thus, for SF networks, knowledge of order of logN nodes and immunizing them can reduce dramatically an epidemics.

scholarly journals Time-resolved connectome of the five-factor model of personality

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
L. Passamonti ◽  
R. Riccelli ◽  
I. Indovina ◽  
A. Duggento ◽  
A. Terracciano ◽  
...  
Keyword(s):  
Large Scale ◽  
Ad Hoc ◽  
Factor Model ◽  
Five Factor Model ◽  
Future Research ◽  
Time Resolved ◽  
Personality Differences ◽  
Network Time ◽  
Large Scale Networks ◽  
The Individual

Abstract The human brain is characterized by highly dynamic patterns of functional connectivity. However, it is unknown whether this time-variant ‘connectome’ is related to the individual differences in the behavioural and cognitive traits described in the five-factor model of personality. To answer this question, inter-network time-variant connectivity was computed in n = 818 healthy people via a dynamical conditional correlation model. Next, network dynamicity was quantified throughout an ad-hoc measure (T-index) and the generalizability of the multi-variate associations between personality traits and network dynamicity was assessed using a train/test split approach. Conscientiousness, reflecting enhanced cognitive and emotional control, was the sole trait linked to stationary connectivity across several circuits such as the default mode and prefronto-parietal network. The stationarity in the ‘communication’ across large-scale networks offers a mechanistic description of the capacity of conscientious people to ‘protect’ non-immediate goals against interference over-time. This study informs future research aiming at developing more realistic models of the brain dynamics mediating personality differences.

Thinking in multitudes: Questionnaires and composite cases in early American psychology

2020 ◽  
Vol 33 (3-4) ◽  
pp. 160-174 ◽  
Author(s):  
Jacy L. Young
Keyword(s):  
Scientific Reasoning ◽  
Large Scale ◽  
Individual Case ◽  
Early American ◽  
Large Scale Data ◽  
American Psychology ◽  
Questionnaire Research ◽  
The Individual ◽  
Scale Data

In the late 19th century, the questionnaire was one means of taking the case study into the multitudes. This article engages with Forrester’s idea of thinking in cases as a means of interrogating questionnaire-based research in early American psychology. Questionnaire research was explicitly framed by psychologists as a practice involving both natural historical and statistical forms of scientific reasoning. At the same time, questionnaire projects failed to successfully enact the latter aspiration in terms of synthesizing masses of collected data into a coherent whole. Difficulties in managing the scores of descriptive information questionnaires generated ensured the continuing presence of individuals in the results of this research, as the individual case was excerpted and discussed alongside a cast of others. As a consequence, questionnaire research embodied an amalgam of case, natural historical, and statistical thinking. Ultimately, large-scale data collection undertaken with questionnaires failed in its aim to construct composite exemplars or ‘types’ of particular kinds of individuals; to produce the singular from the multitudes.

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