Network Division Research Articles

A novel synthetical hierarchical community paradigm for social network division from the perspective of information ecosystem

A novel synthetical hierarchical community paradigm for social network division from the perspective of information ecosystem

A hybrid spatiotemporal model combining graph attention network and gated recurrent unit for regional composite air pollution prediction and collaborative control

Machine learning (ML) models have been extensively applied in air quality prediction. However, many of these models often failed to unveil complex mechanisms and regional spatiotemporal variations of composite air pollution. This brings uncertainties in using ML models for effective composite air pollution control. The present study developed a novel hybrid spatiotemporal model framework combining Graph Attention Network (GAT) and Gated Recurrent Unit (GRU), namely the GAT-GRU model, to foresee composite air pollutions with a focus on PM2.5 and O3. By extracting attention matrices for PM2.5O3 composite pollution and applying the Louvain algorithm, the framework established effective community network divisions for coordinated control of PM2.5O3 composite pollution. The framework was applied and tested in China's “2 + 26″ cities, a city cluster with most heavy PM2.5 and O3 pollution and precursor emission sources. The results demonstrate that the framework successfully captured spatiotemporal evolution of combined PM2.5 and O3 pollution. The attention matrix is autonomously generated during course of the model learning process with the aim to interpret the complex interactions among “2 + 26″ cities. The framework provides a new perspective for the interpretability of artificial intelligence models and offers a methodological support and scientific evidence for formulating regional pollution cooperative governance strategies.

Optimization of Division and Reconfiguration Locations of the Medium-Voltage Power Grid Based on Forecasting the Level of Load and Generation from Renewable Energy Sources

The article addresses challenges in optimizing the operation of medium voltage networks, emphasizing optimizing network division points and selecting the best network configuration for minimizing power and energy losses. It critically reviews recent research on the issue of network configuration optimization. The optimization of the medium voltage power grid reconfiguration process was carried out using known optimization tools. The novelty lies in the inclusion of a probabilistic approach in the decision-making process in forecasting loads and generation from renewable energy sources (RES). Optimization studies utilizing heuristic optimization methods were completed, and an algorithm was developed for forecasting load and power generated from RES based on historical data and current weather data obtained from weather API. The solution proposed in the article allows multiple applications, including optimizing network division points’ locations (which decreases financial costs of modernizing network infrastructure) as well as improving the reconfiguration process, resulting in lower power losses while maintaining voltage requirements.

Online Monitoring System of Electromechanical Transient Simulation Data of Distribution Network Based on Edge Computing

The current distribution network is developing toward the direction of information and intelligent distribution Internet of Things (IoT). In order to explore the online monitoring system for transient electromechanical simulation of distribution networks, this paper is based on the equivalent model of generator sets. Firstly, it describes the relevant theoretical knowledge of edge computing, designs the distribution IoT based on edge computing, and briefly introduces its network architecture. Secondly, based on the discrete-time domain equivalent model of generators, the electromechanical transient simulation distribution network is constructed by introducing the machine network division of the power network. Finally, the Western System Coordinating Council (WSCC)-3 units and 9 nodes are taken as an example, and simulation experiments are conducted under two fault simulation conditions to verify the effectiveness of the simulation model. The results show that under the two fault simulation conditions, the results of equivalent model simulation of generator terminal voltage and relative power angle change are like those of the Power System Analysis Software Package (PSASP). The changing trend of the two is similar and stable. After the PSASP results are stabilized at a value, the simulation results fluctuate extremely up and down the value. For example, under fault condition 1, the changing trend of the relative power angle of the No. 2 generator is first fluctuating and then becomes stable. After violent fluctuation, the relative power angle tends to be stable from about 20s to -12.35°. The result of PSASP software is stable at -12.35°. The transient electromechanical simulation of the generator equivalent model can provide some ideas for the online monitoring system of the distribution network.

Women's Solo Travel and Gender Equality: Insights from Labuan Bajo According to the SDG

Objective: This study aims to analyze the tourism network of Labuan Bajo, focusing on identifying key destinations and their roles within the network, particularly for women solo travelers. The objective is to enhance tourism management by understanding these dynamics. Theoretical Framework: This research is underpinned by tourist and gender studies, which provide a foundation for examining the connectivity and influence of tourist destinations, as well as the specific needs and patterns of woman solo travelers. Method: The methodology involves creating edge and node lists from TripAdvisor reviews, followed by network construction using centrality measures—degree, betweenness, and eigen centrality. Network visualization techniques are applied to interpret relationships between destinations. Data was collected from January 1, 2020, to September 1, 2023, with 2,843 reviews analyzed. Results and Discussion: The results reveal that Padar Island is the most central and influential destination, serving as a key hub for woman solo travelers. Other significant destinations include Loh Liang National Park, Kanawa Island,Kalong Island, and Cunca Wulang Waterfall. Rangko Cave, however, shows the lowest centrality measurements. The network's division into clusters highlights distinct patterns in woman solo travel behavior and preferences. These findings suggest strategic areas for investment and improvement to enhance tourist experiences and promote women's equality in travel. Research Implications: The study's findings provide practical insights for tourism management, suggesting targeted investments and infrastructure development in high-centrality areas. Improving safety, accessibility, and amenities at key hubs can create a more inclusive environment for woman solo travelers. Originality/Value: This study contributes to the literature by combining network analysis with gender-focused tourism research, offering a novel approach to understanding and improving tourism dynamics in emerging destinations. The insights gained can influence sustainable tourism development and gender equality in travel.

Transport SDN architecture for multi-layer transport slicing

The proposed architecture advances the concept of network slicing, crucial for beyond 5G services, by enabling dynamic resource allocation and customized partitioning in managed network infrastructures. This architecture addresses the challenges of provisioning end-to-end (E2E) slices across diverse network domains, which is complicated by technological heterogeneity and the variety of vendor solutions. By introducing a standardized transport network solution, we ensure seamless integration, equitable treatment of service requests, and the ability to meet diverse demands. The architecture is centered around a multi-layer transport network slicing architecture, which allows for the division of transport networks into virtual autonomous segments, each tailored for specific services or applications. This segmentation is essential for providing differentiated and personalized 5G services, optimizing network performance, and maximizing resource application. A key component of this architecture is the transport slice controller (TSC), which controls the provision and life-cycle management of transport slices, ensuring a standardized approach in the industry for the definition and realization of slices.

The “veins and arteries of the country” Imagined and actual exclusion from railway connectivity in Bulgaria, 1878–1908

The Bulgarian Principality, established in 1878, witnessed serious contentions over railway accessibility. The central planning state, through its de facto practices of catering to local interests, polarised regions contending against one another. It also witnessed strife between rich and poor articulated in class-based party politics as well as intra-elite struggles between traditional and new elites, fought out in the sphere of cultural capital. Claims to rail accessibility and its gains were expressed in social Darwinian, ethnic, nationalist, economist and socialist discourses. By contrast, the factual division of the railway network into state-run and privately operated services evoked a sense of unity. The Orient Railways served as Enemy Within due to its multinational ownership and profit-oriented policy, first under Maurice de Hirsch's control and later the Deutsche Bank's. This “negative integration” served to gloss over the many social, ethnic, ideological and regional fault lines running through the country which the central state had not managed to bridge.

Strategic Network Management for Modern Campuses: A Comprehensive Framework

Campus handling of networks has become critical in the continuously changing world of higher education. This paper offers a thorough method for managing and safeguarding networks in a campus setting with multiple departments. Our approach focuses on four departments: the administrative, civil, computer science and engineering (CSE), and electrical and electronics engineering (EEE) departments. It combines multiple networking technologies to improve security and maximize speed. Network division using virtual LANs (VLANs), efficient IP address allocation using Variable Length Subnet Masks (VLSM), simplified network configuration using Dynamic Host Configuration Protocol (DHCP), dynamic routing using Routing Information Protocol version 2 (RIPv2), granular access control using Access Control Lists (ACLs), enhanced security using Network Address Translation (NAT), secure remote access using Secure Shell version 2 (SSHv2), and improved network resilience through Link Aggregation are the main components of our system.

Critical reflection on digital labor of network anchor: Specialized division of labour networks and atomization of labor

Critical reflection on digital labor of network anchor: Specialized division of labour networks and atomization of labor

A mathematical model for predicting the deformation of the hydraulic model of the dynamics of water flow and morphological parameters of the riverbed in small mountain rivers

In this article, the changes of the bed of the Govasoy river, which is one of the small mountain rivers, due to the influence of constructions and the formation of the sedimentation layer are studied on the basis of field studies. The mathematical model of predicting the deformation of water flow dynamics and the processes of the bed, and the experimental results are compared with numerical solutions. Information on the territorial division of irrigation networks and water consumers in the Govasay river basin, as well as their digital maps, was created on the basis of geo-information technology. The program was developed to ensure the rapid management of water resources.

SPATIAL PARTITION FOR HETEROGENEOUS CITY NETWORKS COMPOSED OF FACTORS THAT INFLUENCE THE DISTRIBUTION OF THE MACROSCOPIC FUNDAMENTAL DIAGRAM

Using a Macroscopic Fundamental Diagram (MFD) to implement partition control is effective in improving mobility in heterogeneous city networks. As one of the most complex issues in partition control, accurate sub-region partition is critical for control effectiveness. Current partition methods focus on the link density and precondition of existing MFD and disregard the factors that influence MFD distribution. To overcome this drawback, this study uses the characteristic value of the link and the intersection connected to the link as the analysis object and proposes an MFD sub-region partitioning method for large-scale networks. Firstly, the influences of road state parameters on MFD distribution are classified into traffic flow parameters, network physical properties, network operation mechanisms and emergencies. Simulation experiments are conducted to determine the degree to which these classifications affect MFD distribution. Secondly, a partition method combined with the link density and influence parameters of MFD is developed. The method is used for a preliminarily division of a road network through Minimum Spanning Tree (MST) and depth partition by the Normalised Cut (Ncut) algorithm. Finally, a case study is conducted in an actual city centre network, and results show that the developed method is superior to the single method based simply on link density.

Reconstruction and Layer Division of Unknown Multilayer Networks

Reconstruction and Layer Division of Unknown Multilayer Networks

Research on symptoms composition, time series evolution, and network visualisation of interstitial cystitis based on complex network community discovery algorithm.

We analyzed the symptoms composition of Interstitial Cystitis (IC), the regularity of the evolution of symptoms before and after treatment, and the visualization of the community network, to provide a reference for clinical diagnosis and treatment of Interstitial Cystitis. Based on the outpatient electronic case data of 552 patients with Interstitial Cystitis, we used a complex network community discovery algorithm, directed weighted complex network, and Sankey map to mine the data of the symptoms composition of Interstitial Cystitis, the evolution of symptoms before and after treatment and the visualization of the community network, to analyze the epidemiological characteristics of interstitial cystitis symptoms in the real world. By the community division of the complex network of interstitial cystitis symptoms, We finally obtained three core symptom communities. Among them, symptom community A (bladder-related symptoms) is the symptom community with the highest proportion of nodes (60.00%) in the complex network of Interstitial Cystitis, symptom community B (non-bladder-related symptoms 1) ranks second (32.00%) in a complex network of Interstitial Cystitis, and symptom community C (non-bladder-related symptoms 2) has the lowest proportion (8.00%). There is a complex evolutionary relationship between the symptoms of Interstitial Cystitis before and after treatment. Among the single symptoms before and after treatment, the decreased rate of Day frequency is 93.22%, and the reduced urgency rate is 93.07%. The decline rate of Nocturia was 82.33%. From the perspective of different communities, theoverall symptoms of symptom community A decreased by 34.39% after treatment, the general symptoms of symptom community B decreased by 35.37%, and the prevalent symptoms of symptom community C decreased by 71.43%. In the case of using diet regulation treatment to treat bladder pain, the cure rate of bladder pain can reach 22.67%. The cure rate of burning in bladders can get 15.38% with Percutaneous Sacral neuromodulation, 96.95% with diet regulation treatment, and 100% with Percutaneous Sacral neuromodulation. When using behavioral physiotherapy to treat bladder pain, 3.57% of the patient's symptoms change to bladder discomfort; 4% of the patient's symptoms change to bladder discomfort when using oral medicine to treat bladder pain.Symptom research methods based on community findings can effectively explore the rule of symptom outcome of Interstitial Cystitis before and after treatment, and the results are highly interpretable by professionals. The cover image is based on the Original Article Research on symptoms composition, time series evolution, and network visualisation of interstitial cystitis based on complex network community discovery algorithm by Lei Pang etal., https://doi.org/10.1049/syb2.12083.

Algebraic multiscale grid coarsening using unsupervised machine learning for subsurface flow simulation

Subsurface flow simulation is vital for many geoscience applications, including geoenergy extraction and gas (energy) storage. Reservoirs are often highly heterogeneous and naturally fractured. Therefore, scalable simulation strategies are crucial to enable efficient and reliable operational strategies. One of these scalable methods, which has also been recently deployed in commercial reservoir simulators, is algebraic multiscale (AMS) solvers. AMS, like all multilevel schemes, is found to be highly sensitive to the types (geometries and size) of coarse grids and local basis functions. Commercial simulators benefit from a graph-based partitioner; e.g., METIS to generate the multiscale coarse grids. METIS minimizes the amount of interfaces between coarse partitions, while keeping them of similar size which may not be the requirement to create a coarse grid. In this work, we employ a novel approach to generate the multiscale coarse grids, using unsupervised learning methods which is based on optimizing different parameter. We specifically use the Louvain algorithm and Multi-level Markov clustering. The Louvain algorithm optimizes modularity, a measure of the strength of network division while Markov clustering simulates random walks between the cells to find clusters. It is found that the AMS performance is improved when compared with the existing METIS-based partitioner on several field-scale test cases. This development has the potential to enable reservoir engineers to run ensembles of thousands of detailed models at a much faster rate.

EEG Functional Connectivity in Motor Task: Experience of Application of Graph Analysis

The goal of this work is the application of graph analysis for the research of brain network organization during motor task (clenching/unclenching the fingers of the right hand). In this approach the brain is considered as a single network (graph), where the nodes are individual leads, and the edges are coherence indicators. The approach allows to study the processes of segregation (network division into clusters) and integration (network unification) as well as to identify the most highly active nodes in the networks through which the greatest volumes of information transfers. The work revealed that the movement of the right hand is associated with global and local neural network rearrangements – increase of global network efficiency of whole brain and left hemisphere separately and the formation of local clusters for processing information in areas, connected with hand movement and also in some non-specific for the hand movement areas, probably connected with executive functions.

Methodology for Placing Devices for Sectioning the Electrical Grid 0,4 kV

A literature review was carried out, which showed a shift in the emphasis of digital transformation of the electric power industry on the development of methods and means of automation of rural electric networks of 0.4-10 kilovolts. It is shown that the actual direction of automation of rural electric networks is the development of means of their partitioning and redundancy, including the creation of relatively inexpensive devices for partitioning – dividing power lines into sections. The use of these devices requires the creation of methods for selecting their installation locations in electrical networks. (Research purpose) The research purpose is developing a methodology for locating the installations for sectioning the electrical grid. (Materials and methods) Analyzed literature sources, existing methods for selecting installation sites for partitioning tools. We used general scientific methods, methods of reliability theory, electrical engineering. (Results and discussion) Suggested options for the placement of devices for dividing the electrical network, depending on the purpose of their use. The criteria for choosing the installation locations of the electrical network division devices were given, which included ensuring the protection of the power transmission line from remote short circuits, primarily single-phase, increasing the reliability of power supply to consumers, preventing voltage deviation from exceeding permissible limits. Presented a methodology for selecting the installation locations of electrical network division devices according to the proposed criteria. (Conclusions) It was revealed that for radial and radial with soldering of electrical networks, the main criterion is to ensure the protection of remote short circuits, and an additional one is to increase the reliability of power supply. It has been shown that for ring networks, the main criterion is to prevent voltage deviation from exceeding permissible limits along with the criterion of ensuring protection from remote short circuits, and the criterion for increasing reliability is an additional one. It was established that the final place of installation of devices for dividing the electrical network into sections in each case is determined taking into account the specified criteria so that the main ones are not violated.

Provincial-Scale Research on the Eco-Security Structure in the Form of an Ecological Network of the Upper Yellow River: A Case Study of the Ningxia Hui Autonomous Region

Important for promoting the integrated protection and systematic management of mountains, rivers, forests, farmlands, lakes, grasslands, and sandy areas, ecological networks form the backbone of the regional ecological security pattern. An improved morphological spatial pattern analysis coupled with a minimum cumulative resistance model (MSPA–MCR) based on multi-source data was used to study, on a provincial scale, the ecological security pattern of Ningxia, an ecologically fragile region in the upper reaches of the Yellow River in China. The results show the following: (1) A reasonable classification of ecological sources and ecological corridors is key to constructing hierarchical ecological networks. Classifying ecological sources by replacing patch areas with energy factors and identifying the importance of ecological corridors by modifying the gravity model with the energy factors proposed in this paper could improve the rationality of the hierarchical structure division of ecological networks. (2) Grassland as the substrate vegetation type is an important ecological source type in arid and semi-arid ecologically fragile areas, and forests and lake wetlands are the main ecological source types in mountainous areas and oasis areas, respectively. The study area was located in the arid–semi-arid transitional area, with a variety of ecological types, such as mountain, oasis, and desert. Therefore, the complex ecological source types of forest–grassland–wetland appear in some areas. (3) There are 45 ecological patch groups that can be classified as ecological sources in Ningxia, including 10 primary source groups. The number of primary source groups is small, and their spatial distribution is unbalanced. There are two categories of ecological corridors, the river corridor and the mountain corridor, and the network connectivity is poor. (4) The ecological network structure of Ningxia is presented as an ecological security structure consisting of one belt, three screens, three corridors, and five clusters, forming a hierarchical nested ecological network security structure system.

Single point lidar technology for ground clearance measurement in medium voltage overhead lines with the deployment of Unmanned Aerial System (UAS) in TNB distribution network division

Single point lidar technology for ground clearance measurement in medium voltage overhead lines with the deployment of Unmanned Aerial System (UAS) in TNB distribution network division

A graphic partition method based on nodes learning for energy pipelines network simulation

The network of energy pipelines is extremely important for the proper functioning of a modern society. Even though measurement instruments and sensors are currently widely used to monitor the network’s operational status in real time, it is expensive to deploy these extra devices for a large city-scale network. Numerical simulation of fluid networks offers a rather easy and effective technique to track the work performance of pipelines. Because of the computational intensiveness of the pipeline network, it is most suitable to deploy such a massive simulation program on a supercomputer with a parallel technique. The performance of this kind of parallel simulation may undoubtedly be enhanced if the pipeline network is reasonably divided into several subnetworks in which the fluid flows are resolved independently. In this paper, we concentrate on how to achieve a computationally balanced subnetwork partition scheme and propose an acceleration method for energy pipeline network simulations based on a graph partition algorithm. In our approach, each node of the network takes part in the decision of dividing the entire network by learning the weight of its neighbors. Moreover, we utilize graph-tree transformations to merge locally related components as much as possible, and together with subgraph rebalancing, the pipeline network division quality is improved considerably. Numerical simulations show that our approach is much better than others for the degree of balance, and the cut edge ratio is also lower than others when it is compared with the random, k-means, and METIS methods.

Developing a CNN-based, block-scale oriented Local Climate Zone mapping approach: A case study in Guangzhou

The limited available urban land in megacities is represented by large areas of impervious underlying surfaces and buildings, which are expressed by the basic urban fabric unit of the “city block.” The concept of the Local Climate Zone (LCZ) scheme is capable of quantifying the combined influences that different urban elements have on block-scale local climates, rendering block-scale LCZ classification and block-scale-oriented LCZ map production crucial for climate-conscious urban planning and design. Taking the city of Guangzhou as a case study, deep learning was combined with the Convolutional Neural Network (CNN) to perform effective image recognition, vector cutting, and automatic area statistics based on multilevel road networks. Road network division, block area processing, characteristic parameter calculation, and LCZ classification were integrated to automatically generate block-scale-oriented LCZ maps, which was achieved via threshold contrast using the recommended parameter intervals of the calculated characteristic parameters. Basic land surface temperature (LST) data for summer to winter in Guangzhou were then applied, and correlation analysis was conducted between the block-scale LST vector and LCZ characteristic parameters. The results demonstrate the applicability and potential of the CNN algorithm for urban climate analysis. The developed CNN-based LCZ mapping approach prioritizes “block” scale analysis and typical characteristic parameters in each block are obtained with high calculation accuracy. This study contributes to guiding parameterized climate-sensitive urban planning.