scholarly journals Approximational Projection of a Network with an Arbitrary Structure

2018 ◽  
Vol 7 (3.2) ◽  
pp. 550
Author(s):  
Valerii Usenko ◽  
Olga Kodak ◽  
Iryna Usenko
Keyword(s):  
Network Structure ◽  
Large Scale ◽  
System Parameters ◽  
Arbitrary Structure ◽  
Large Scale Networks ◽  
Definition Of

Improving the efficiency of the functioning of the engineering networks of cities involves solving the issues of expanding and deepening the process of studying the interconnection of its components.An approximate definition of the property of the network structure's connectivity belongs to the conceptual class of diminishing the dimension of the multiplicity of system parameters. It studies the structures of networks with arbitrary reliability of its constituent parts. The reflection of the reliability values of the components of a redundant engineering network structure is appropriate for large-scale networks. The multiplicity of the network is projected onto the subspace of its parameters with variable values of the argument of the function of the integrity of the connectivity.  

scholarly journals Attention Networks and the Intrinsic Network Structure of the Human Brain

2021 ◽  
Author(s):  
Sebastian Markett ◽  
David Nothdurfter ◽  
Antonia Focsa ◽  
Martin Reuter ◽  
Philippe Jawinski
Keyword(s):  
Network Structure ◽  
Network Theory ◽  
Large Scale ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Relevant Information ◽  
Attention Network ◽  
Attention Networks ◽  
Large Scale Networks ◽  
The Brain

Attention network theory states that attention is not a unified construct but consists of three independent systems that are supported by separable distributed networks: an alerting network to deploy attentional resources in anticipation of upcoming events, an orienting network to direct attention to a cued location, and a control network to select relevant information at the expense of concurrently available information. Ample behavioral and neuroimaging evidence supports the dissociation of the three attention domains. The strong assumption that each attentional system is realized through a separable network, however, raises the question how these networks relate to the intrinsic network structure of the brain. Our understanding of brain networks has advanced majorly in the past years due to the increasing focus on brain connectivity. It is well established that the brain is intrinsically organized into several large-scale networks whose modular structure persists across task states. Existing proposals on how the presumed attention networks relate to intrinsic networks rely mostly on anecdotal and partly contradictory arguments. We addressed this issue by mapping different attention networks with highest spatial precision at the level of cifti-grayordinates. Resulting group maps were compared to the group-level topology of 23 intrinsic networks which we reconstructed from the same participants' resting state fMRI data. We found that all attention domains recruited multiple and partly overlapping intrinsic networks and converged in the dorsal fronto-parietal and midcingulo-insular network. While we observed a preference of each attentional domain for its own set of intrinsic networks, implicated networks did not match well to those proposed in the literature. Our results indicate a necessary refinement of the attention network theory.

scholarly journals A Multiobjective Evolutionary Approach for Solving Large-Scale Network Reconstruction Problems via Logistic Principal Component Analysis

2021 ◽  
Author(s):  
Chaolong Ying ◽  
Jing Liu ◽  
Kai Wu ◽  
Chao Wang
Keyword(s):  
Principal Component Analysis ◽  
Network Structure ◽  
Large Scale ◽  
Evolutionary Process ◽  
Principal Component ◽  
Reconstruction Algorithm ◽  
Component Analysis ◽  
Network Reconstruction ◽  
Reconstruction Error ◽  
Large Scale Networks

Currently, the problem of uncovering complex network structure and dynamics from time series is prominent in many fields. Despite the recent progress in this area, reconstructing large-scale networks from limited data remains a tough problem. Existing works treat connections of nodes as continuous values, leaving a challenge of setting a proper cut-off value to distinguish whether the connections exist or not. Besides, their performances on large-scale networks are far from satisfactory. Considering the reconstruction error and sparsity as two objectives, this paper proposes a subspace learning based evolutionary multiobjective network reconstruction algorithm, termed as SLEMO-NR, to solve the aforementioned problems. In the evolutionary process, we assume that binary-coded individuals obey the Bernoulli distribution and can use the probability and natural parameter as the alternative representations. Moreover, our approach utilizes the logistic principal component analysis (LPCA) to learn a subspace containing the features of network structure. The offspring solutions are generated in the learned subspace and then can be mapped back to the original space via LPCA. Benefitting from the alternative representations, a preference-based local search operator is proposed to concentrate on finding solutions approximate to the true sparsity. The experimental results on synthetic networks and six real-world networks demonstrate that, due to the well-learned network structure subspace and the preference-based strategy, our approach is effective in reconstructing large-scale networks compared to six existing methods.

scholarly journals Cerebral cartography and connectomics

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140173 ◽  
Author(s):  
Olaf Sporns
Keyword(s):  
Large Scale ◽  
Computational Models ◽  
Network Science ◽  
Temporal Dynamics ◽  
Functional Organization ◽  
Brain Connectivity ◽  
Hierarchical Organization ◽  
Large Scale Networks ◽  
Definition Of ◽  
The Brain

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics.

scholarly journals Spatiotemporal Large-Scale Networks Shaped by Air Mass Movements

2021 ◽  
Vol 6 ◽  
Author(s):  
M. Choufany ◽  
D. Martinetti ◽  
R. Senoussi ◽  
C. E. Morris ◽  
S. Soubeyrand
Keyword(s):  
Large Scale ◽  
Seasonal Pattern ◽  
Geographical Area ◽  
Three Dimensional ◽  
Mass Movements ◽  
Air Mass ◽  
Air Masses ◽  
Large Scale Networks ◽  
Definition Of ◽  
French Region

The movement of atmospheric air masses can be seen as a continuous flow of gases and particles hovering over our planet, and it can be locally simplified by means of three-dimensional trajectories. These trajectories can hence be seen as a way of connecting distant areas of the globe during a given period of time. In this paper we present a mathematical formalism to construct spatial and spatiotemporal networks where the nodes represent the subsets of a partition of a geographical area and the links between them are inferred from sampled trajectories of air masses passing over and across them. We propose different estimators of the intensity of the links, relying on different bio-physical hypotheses and covering adjustable time periods. This construction leads to a new definition of spatiotemporal networks characterized by adjacency matrices giving, e.g., the probability of connection between distant areas during a chosen period of time. We applied our methodology to characterize tropospheric connectivity in two real geographical contexts: the watersheds of the French region Provence-Alpes-Côte d’Azur and the coastline of the Mediterranean Sea. The analysis of the constructed networks allowed identifying a marked seasonal pattern in air mass movements in the two study areas. If our methodology is applied to samples of air-mass trajectories, with potential implications in aerobiology and plant epidemiology, it could be applied to other types of trajectories, such as animal trajectories, to characterize connectivity between different components of the landscape hosting the animals.

scholarly journals Visual Snow Syndrome as a Network Disorder: A Systematic Review

2021 ◽  
Vol 12 ◽  
Author(s):  
Antonia Klein ◽  
Christoph J. Schankin
Keyword(s):  
Large Scale ◽  
Case Reports ◽  
Visual Disturbance ◽  
Google Scholar ◽  
New Information ◽  
Visual Areas ◽  
Visual Cortices ◽  
Large Scale Networks ◽  
Definition Of ◽  
The Brain

Aim: By reviewing the existing clinical studies about visual snow (VS) as a symptom or as part of visual snow syndrome (VSS), we aim at improving our understanding of VSS being a network disorder.Background: Patients with VSS suffer from a continuous visual disturbance resembling the view of a badly tuned analog television (i.e., VS) and other visual, as well as non-visual symptoms. These symptoms can persist over years and often strongly impact the quality of life. The exact prevalence is still unknown, but up to 2.2% of the population could be affected. Presently, there is no established treatment, and the underlying pathophysiology is unknown. In recent years, there have been several approaches to identify the brain areas involved and their interplay to explain the complex presentation.Methods: We collected the clinical and paraclinical evidence from the currently published original studies on VS and its syndrome by searching PubMed and Google Scholar for the term visual snow. We included original studies in English or German and excluded all reviews, case reports that did not add new information to the topic of this review, and articles that were not retrievable in PubMed or Google Scholar. We grouped the studies according to the methods that were used.Results: Fifty-three studies were found for this review. In VSS, the clinical spectrum includes additional visual disturbances such as excessive floaters, palinopsia, nyctalopia, photophobia, and entoptic phenomena. There is also an association with other perceptual and affective disorders as well as cognitive symptoms. The studies that have been included in this review demonstrate structural, functional, and metabolic alterations in the primary and/or secondary visual areas of the brain. Beyond that, results indicate a disruption in the pre-cortical visual pathways and large-scale networks including the default mode network and the salience network.Discussion: The combination of the clinical picture and widespread functional and structural alterations in visual and extra-visual areas indicates that the VSS is a network disorder. The involvement of pre-cortical visual structures and attentional networks might result in an impairment of “filtering” and prioritizing stimuli as top-down process with subsequent excessive activation of the visual cortices when exposed to irrelevant external and internal stimuli. Limitations of the existing literature are that not all authors used the ICHD-3 definition of the VSS. Some were referring to the symptom VS, and in many cases, the control groups were not matched for migraine or migraine aura.

scholarly journals A Multiobjective Evolutionary Approach for Solving Large-Scale Network Reconstruction Problems via Logistic Principal Component Analysis

2021 ◽  
Author(s):  
Chaolong Ying ◽  
Jing Liu ◽  
Kai Wu ◽  
Chao Wang
Keyword(s):  
Principal Component Analysis ◽  
Network Structure ◽  
Large Scale ◽  
Evolutionary Process ◽  
Principal Component ◽  
Reconstruction Algorithm ◽  
Component Analysis ◽  
Network Reconstruction ◽  
Reconstruction Error ◽  
Large Scale Networks

Currently, the problem of uncovering complex network structure and dynamics from time series is prominent in many fields. Despite the recent progress in this area, reconstructing large-scale networks from limited data remains a tough problem. Existing works treat connections of nodes as continuous values, leaving a challenge of setting a proper cut-off value to distinguish whether the connections exist or not. Besides, their performances on large-scale networks are far from satisfactory. Considering the reconstruction error and sparsity as two objectives, this paper proposes a subspace learning based evolutionary multiobjective network reconstruction algorithm, termed as SLEMO-NR, to solve the aforementioned problems. In the evolutionary process, we assume that binary-coded individuals obey the Bernoulli distribution and can use the probability and natural parameter as the alternative representations. Moreover, our approach utilizes the logistic principal component analysis (LPCA) to learn a subspace containing the features of network structure. The offspring solutions are generated in the learned subspace and then can be mapped back to the original space via LPCA. Benefitting from the alternative representations, a preference-based local search operator is proposed to concentrate on finding solutions approximate to the true sparsity. The experimental results on synthetic networks and six real-world networks demonstrate that, due to the well-learned network structure subspace and the preference-based strategy, our approach is effective in reconstructing large-scale networks compared to six existing methods.

CONCEPT OF THE IMPROVEMENT OF A KEY PUBLIC SPACE (USING THE EXAMPLE OF «ALLEY OF ARCHITECTS», VORONEZH)

2020 ◽  
pp. 97-109
Author(s):  
С. Л. Подвальный ◽  
О. А. Сотникова ◽  
Я. А. Золотухина
Keyword(s):  
Urban Environment ◽  
Public Space ◽  
Large Scale ◽  
Economic Value ◽  
Ecological Condition ◽  
Territory Design ◽  
Definition Of ◽  
The City ◽  
Modern Technologies ◽  
Intensive Growth

Постановка задачи. В настоящее время формирование современной комфортной городской среды приобретает особое социально-экономическое значение и выдвигается в число приоритетных государственных масштабных программ. В связи с этим необходимо разработать концепцию благоустройства ключевого общественного пространства, а именно: определить основные и сопутствующие функции данной территории, создать эскизное предложение проекта благоустройства с учетом всех необходимых норм и стандартов, внедрить современные технологии. Результаты. Выполнен эскизный дизайн-проект «Аллеи архитекторов» по ул. Орджоникидзе г. Воронеж, включающий в себя основные элементы по зонированию территории, проектированию акцентных объектов и внедрению инновационных технологий «умного города», позволяющих повысить уровень комфорта горожан. Выводы. Благоустройство населенных мест приобретает особое значение в условиях дискомфорта среды. С выполнением комплекса мероприятий, направленных на благоустройство, и с внедрением современных технологий значительно улучшается экологическое состояние, внешний облик города. Оздоровление и модернизация среды, которая окружает человека в городе, благотворно влияет на психофизическое состояние, что особенно важно в период интенсивного роста городов. Statement of the problem. Currently the formation of the modern comfortable urban environment is gaining a special social and economic value and moving forward in the priorities of state large-scale programs. The purpose of development of the concept of improvement of public space is definition of the main and accompanying functions of this territory, design of the outline offer of the project of improvement considering all necessary norms and standards and implementation of modern technologies. Results. The conceptual project of “Alley of Architects” includes the basic elements of territory zoning, design of accent objects and implementation of technologies of a “smart-city”. These elements allow one to increase the level of comfort of inhabitants. Conclusions. Improvement of the inhabited places is of particular importance in the conditions of discomfort of the environment. Carrying out a complex of the actions directed to gardening and improvement, introducing modern technologies, the ecological condition, the physical appearance of the city considerably improves. Improvement and modernization of the environment which surrounds the person in the city influences a psychophysical state well that especially important during intensive growth of the cities.

Bottlenecks in the Implementation of On-Site Wastewater Treatment Plants on a Large Scale in The Netherlands

1990 ◽  
Vol 22 (3-4) ◽  
pp. 291-298
Author(s):  
Frits A. Fastenau ◽  
Jaap H. J. M. van der Graaf ◽  
Gerard Martijnse
Keyword(s):  
Wastewater Treatment ◽  
The Netherlands ◽  
Large Scale ◽  
Wastewater Treatment Plants ◽  
Housing Stock ◽  
Research Work ◽  
Field Research ◽  
Domestic Wastewater ◽  
Research Programme ◽  
Definition Of

More than 95 % of the total housing stock in the Netherlands is connected to central sewerage systems and in most cases the wastewater is treated biologically. As connection to central sewerage systems has reached its economic limits, interest in on-site treatment of the domestic wastewater of the remaining premises is increasing. A large scale research programme into on-site wastewater treatment up to population equivalents of 200 persons has therefore been initiated by the Dutch Ministry of Housing, Physical Planning and Environment. Intensive field-research work did establish that the technological features of most on-site biological treatment systems were satisfactory. A large scale implementation of these systems is however obstructed in different extents by problems of an organisational, financial and/or juridical nature and management difficulties. At present research is carried out to identify these bottlenecks and to analyse possible solutions. Some preliminary results are given which involve the following ‘bottlenecks':-legislation: absence of co-ordination and absence of a definition of ‘surface water';-absence of subsidies;-ownership: divisions in task-setting of Municipalities and Waterboards; divisions involved with cost-sharing;-inspection; operational control and maintenance; organisation of management;-discharge permits;-pollution levy;-sludge disposal. Final decisions and practical elaboration of policies towards on-site treatment will have to be formulated in a broad discussion with all the authorities and interest groups involved.

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