Sewage flow optimization algorithm for large-scale urban sewer networks based on network community division

By considering the flow control of urban sewer networks to minimize the electricity consumption of pumping stations, a decomposition-coordination strategy for energy savings based on network community division is developed in this paper. A mathematical model characterizing the steady-state flow of urban sewer networks is first constructed, consisting of a set of algebraic equations with the structure transportation capacities captured as constraints. Since the sewer networks have no apparent natural hierarchical structure in general, it is very difficult to identify the clustered groups. A fast network division approach through calculating the betweenness of each edge is successfully applied to identify the groups and a sewer network with arbitrary configuration could be then decomposed into subnetworks. By integrating the coupling constraints of the subnetworks, the original problem is separated into N optimization subproblems in accordance with the network decomposition. Each subproblem is solved locally and the solutions to the subproblems are coordinated to form an appropriate global solution. Finally, an application to a specified large-scale sewer network is also investigated to demonstrate the validity of the proposed algorithm.

Robustness of community networks against cascading failures with heterogeneous redistribution strategies

Network robustness is one of the core contents of complex network security research.This paper focuses on the robustness of community networks with respect to cascading failures,considering the nodes influence and community heterogeneity.A novel node influence ranking method,community-based Clustering-LeaderRank(CCL)algorithm,is first proposed to identify influential nodes in community networks.Simulation results show that the CCL method can effectively identify the influence of nodes.Based on node influence,a new cascading failure model with heterogeneous redistribution strategy is proposed to describe and analyze node fault propagation in community networks.Analytical and numerical simulation results on cascading failure show that the community attribute has an important influence on the cascading failure process.The network robustness against cascading failures increases when the load is more distributed to neighbors of the same community instead of different communities.When the initial load distribution and the load redistribution strategy based on the node influence are the same,the network shows better robustness against node failure.

Probability Distribution of Edge in Adjacent Matrix of Aviation Network of China and Algorithm of Searching Non-overlap Community Structure Based on Complex Network

In order to discover the probability distribution feature of edge in aviation network adjacent matrix of China and on the basis of this feature to establish an algorithm of searching non-overlap community structure in network to reveal the inner principle of complex network with the feature of small world in aspect of adjacent matrix and community structure,aviation network adjacent matrix of China was transformed according to the node rank and the matrix was arranged on the basis of ascending node rank with the center point as original point.Adjacent probability from the original point to extension around in approximate area was calculated.Through fitting probability distribution curve,power function of probability distribution of edge in adjacent matrix arranged by ascending node rank was found.According to the feature of adjacent probability distribution,deleting step by step with node rank ascending algorithm was set up to search non-overlap community structure in network and the flow chart of algorithm was given.A non-overlap community structure with 10 different scale communities in aviation network of China was found by the computer program written on the basis of this algorithm.

Cascades with coupled map lattices in preferential attachment community networks

In this paper, cascading failure is studied by coupled map lattice （CML） methods in preferential attachment community networks. It is found that external perturbation R is increasing with modularity Q growing by simulation. In particular, the large modularity Q can hold off the cascading failure dynamic process in community networks. Furthermore, different attack strategies also greatly affect the cascading failure dynamic process. It is particularly significant to control cascading failure process in real community networks.

Properties of asymmetrically evolved community networks

This paper studies a simple asymmetrically evolved community network with a combination of preferential attachment and random properties. An important issue about community networks is to discover the different utility increments of two nodes, where the utility is introduced to investigate the asymmetrical effect of connecting two nodes. On the other hand, the connection of two nodes in community networks can be classified as two nodes belonging to the same or to different communities. The simulation results show that the model can reproduce a power-law utility 1 distribution P（u） - u^-σ, σ = 2 ＋1/p, which can be obtained by using mean-field approximation methods. Furthermore, P the model exhibits exponential behaviour with respect to small values of a parameter denoting the random effect in our model at the low-utility region and a power-law feature with respect to big values of this parameter at the high-utility region, which is in good agreement with theoretical analysis. This kind of community network can reproduce a unique utility distribution by theoretical and numerical analysis.

Generating weighted community networks based on local events

Many realistic networks have community structures, namely, a network consists of groups of nodes within which links are dense but among which links are sparse. This paper proposes a growing network model based on local processes, the addition of new nodes intra-community and new links intra- or inter-community. Also, it utilizes the preferential attachment for building connections determined by nodes＇ strengths, which evolves dynamically during the growth of the system. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes＇ degrees and strengths.

A Hierarchical Virus Immunization Method for Community Networks

Due to the enormous harm of virus propagation,research regarding virus immunizations still absolutely necessary.In comparison to current researches,a new virus immunization method the hierarchical virus immunization method(HVIM) for community networks is proposed.Based on the virus transmission dynamic model SusceptibleInfectious-Removed and SusceptibleRemoved(SIRSR),HVIM considered the influence of external factors on the spread of viruses and only needs a portion of the network structure to be able to carry out immunization.Another pro for HVIM is that it is scalable and suitable for parallel computing which is a requirement in the big data era.Finally,a simulation dataset and a real dataset were used to run experiments,and the results of simulation showed that HVIM obviously is superior to others on the aspect of immunity.

Recommending Authors and Papers Based on ACTTM Community and Bilayer Citation Network

Citation network is often used for academic recommendation. However, it is difficult to achieve high recommendation accuracy and low time complexity because it is often very large and sparse and different citations have different purposes. What's more, some citations include unreasonable information, such as in case of intentional self-citation. To improve the accuracy of citation network-based academic recommendation and reduce the time complexity, we propose an academic recommendation method for recommending authors and papers. In which, an author-paper bilayer citation network is built, then an enhanced topic model, Author Community Topic Time Model(ACTTM) is proposed to detect high quality author communities in the author layer, and a set of attributes are proposed to comprehensively depict the author/paper nodes in the bilayer citation network. Experimental results prove that the proposed ACTTM can detect high quality author communities and facilitate low time complexity, and the proposed academic recommendation method can effectively improve the recommendation accuracy.

Periodic synchronization of community networks with non-identical nodes uncertain parameters and adaptive coupling strength

In this paper, we propose a novel approach for simultaneously identifying unknown parameters and synchronizing time-delayed complex community networks with nonidentical nodes. Based on the LaSalle＇s invariance principle, a cri- teflon is established by constructing an effective control identification scheme and adjusting automatically the adaptive coupling strength. The proposed control law is applied to a complex community network which is periodically synchro- nized with different chaotic states. Numerical simulations are conducted to demonstrate the feasibility of the proposed method.

Synchronization of coupled logistic maps on random community networks

The collective synchronization of a system of coupled logistic maps on random community networks is investigated. It is found that the synchronizability of the community network is affected by two factors when the size of the network and the number of connections are fixed. One is the number of communities denoted by the parameter rn, and the other is the ratio σ of the connection probability p of each pair of nodes within each community to the connection probability q of each pair of nodes among different communities. Theoretical analysis and numerical results indicate that larger rn and smaller σ are the key to the enhancement of network synchronizability. We also testify synchronous properties of the system by analysing the largest Lyapunov exponents of the system.

Cluster synchronization in community network with nonidentical nodes via intermittent pinning control

In this paper, cluster synchronization in community network with nonidentical nodes is investigated. By combining intermittency with a pinning control scheme, some effective controllers are designed. In the control scheme, only one node in each community is controlled and coupling weights of a spanning tree in each community are enhanced. Based on the Lyapunov function method and mathematical analysis technique, two results for achieving cluster synchronization are obtained. Noticeably, by introducing an adaptive strategy, some universal adaptive intermittent pinning controllers are designed for different networks. Finally, two numerical simulations are performed to verify the correctness of the derived results.

A Weighted Evolving Network with Community Size Preferential Attachment

Community structure is an important characteristic in real complex network.It is a network consists ofgroups of nodes within which links are dense but among which links are sparse.In this paper, the evolving network includenode, link and community growth and we apply the community size preferential attachment and strength preferentialattachment to a growing weighted network model and utilize weight assigning mechanism from BBV model.Theresulting network reflects the intrinsic community structure with generalized power-law distributions of nodes'degreesand strengths.

Roles of mutual help of local community networks in community health activities: Improvement for the quality of life of older people in Thailand

Objectives: This study aimed to describe work and activities of community networks focusing on the improvement of the quality of life (QOL) of older people in Thailand.The understanding of the work can help enhancing the community development and strengthening of local communities and their networks.Methods: Qualitative methods including in-depth interview,observation,and focus group discussion were employed to the study.64 participants participated to the study and were recruited from 4 key actors within the community.Content analysis was used to analyze the obtained data.This study was conducted in 6 local administrative organizations (LAOs) which selected from the outstanding areas of the project.Each LAO represents one sub-district of the regions of Thailand namely;(1) the upper north,(2) the lower north,(3)the upper eastern,(4) the lower eastern,(5) the central and (6) the south.Results: The findings of this study were categorized into three main themes: (1) Social capital including people in the community,social groups,and organizations,(2) Mutual help/collaboration activities composed of six sets of activities related to social capitals working on the improvement of QOL of older people,and (3) Impacts of the mutual help/collaboration activities on older people and local communities who help to improve of QOL of older people.Conclusion: The findings are important features for the community development.These themes should be recommended for community nurses,health related groups and organizations for the improvement of QOL of older people in the community.

Supply Community Network:A Taxonomy of Flow Dimensions

Supply chain management(SCM)and its associated activities continue to evolve as new communication technologies and cooperative efforts emerge to facilitate system-wide process integration;the context within which supply chains(SCs)operate,the technologies,and performance enhancement mechanisms have all changed.Thus,linear-based SCs are increasingly being challenged as firms look towards a more networked approach to maximize performance amid growing market dynamics.This paper,however,recognizing inherent similarities between social structure of Social Internet of Things(SIoT)principles and what we term supply community networks(SCN)from literature,seeks to cross-pollinate the two in a way capable of dealing with these market dynamics.Our contribution is,therefore,a new‘setting’of social relationships between supply community agents(SCA)within SCN mirroring interactions played out in the physical world;SCAs autonomously sense each other,exchange information and interact within SCN mimicking the behavior of humans.Also,it identifies the bounds of flow,i.e.all possible dimensions within a SCN which need to be understood to support relationship management.Therefore,communications are improved,sharpening SCAs synchronization in a way responsive to customer needs.

The Supernetwork Model of Social Networking Services

The unique ways of information organization and dissemination was examined through the microblog and the real-name social network as the representatives of the new virtual social networks. In order to discuss the interrelation and interaction of the two dimensions-topic and user, a supernetwork model was established based on the supernetwork research method. Through the actual data, a supernetwork topology diagram and the changing rule of user participation were attained. And it was concluded that the key factor of dealing with emergent online public sentiment should start with affecting the opinions of key figures, whose opinions would further affect the public opinions.

The social determinants of health influencing obesity for the aged in the Pakpoon community context:A qualitative study

Objective:This study aimed to describe the social determinants of health influencing obesity for the aged in a community context and based on the perspectives of various stakeholders.Methods:This was qualitative content analysis study using data from the focus group,individual in-depth interview,and observation.The study population was domiciled in Pakpoon Village,Mung Dis-trict,Nakhon Si Thammarat Province,a tight-knit settlement typical of most retirement communities.Data were collected through two focus group discussions,direct observation,and in-depth interviews with 19 participants.Respondents represented key community groups:local nurses and public health officers,elderly residents,family caregivers(family members),and village health volunteers.Results:The participants shared similar perspectives about the social determinants of health influencing obesity in the aged,which spanned three themes.These were:1)neighborhood food environment(easy access to unhealthy food,no choice to recruit healthy food);2)social networks influencing obesity(family affects food choices and prohibitions on exercise;belief,and socially imposed body image per-ceptions contributing to obesity in the aged);and 3)knowledge,attitudes,and beliefs behind lifestyle choices that cause obesity in the elderly(lack of awareness,personal attitudes,job and familial duties as barriers to engaging in physical activities;over-consumption behaviors lead to obesity in older people).Conclusion:These three themes were the root causes of obesity in the elderly in Pakpoon’s retirement community.This finding suggests that policymakers and nurses can create healthy environments,both to treat and prevent obesity,by raising awareness in younger generations,providing aging the provision of healthy food choices for older adults,encouraging health care professionals to share knowledge,and by modifying the attitudes and beliefs of both caregivers and older adults.

An MDL approach to efficiently discover communities in bipartite network

An minimum description length(MDL) criterion is proposed to choose a good partition for a bipartite network. A heuristic algorithm based on combination theory is presented to approach the optimal partition. As the heuristic algorithm automatically searches for the number of partitions, no user intervention is required. Finally, experiments are conducted on various datasets, and the results show that our method generates higher quality results than the state-of-art methods, cross-association and bipartite, recursively induced modules. Experiment results also show the good scalability of the proposed algorithm. The method is applied to traditional Chinese medicine(TCM) formula and Chinese herbal network whose community structure is not well known, and found that it detects significant and it is informative community division.

Community-based flood disaster management for older adults in southern of Thailand:A qualitative study

Objective:This study explored the approaches for community-based flood disaster management for older adults in Southern Thailand.It sought to understand community culture for supporting older adults and promoting community strength in case of flood disaster.Method:This was a qualitative content analysis study using data from observation,in-depth interviews,secondary data,and focus group discussion.One hundred and twenty-seven people in total were selected specifically for the study,including Local Administration Organization(LAO),community leaders,public sector officers,civil groups,and older adult groups and family caregivers.Results:The results of this study were two main themes,focusing on 1)approaches to community-based flood disaster management for older adults as follows:eight approaches in the phase of prevention and preparedness in flood disaster management for older adults,eight approaches in the phase of response in flood disaster management for older adults,and six approaches in the phase of recovery and rehabilitation in flood disaster management for older adults;and 2)factors contributing to success in flood disaster management for older adults has four factors,including the human factor,the work factor,the data factor,and the resource factor.Conclusion:The findings showed significant roles in improving the potential and strength in communitybased flood disaster management for older adults and providing suggestions for community nurses and health practice personnel involving in flood disaster management to mitigate the potential influence on older adults in the community.

Congestion warning method based on the Internet of vehicles and community discovery of complex networks

The traffic congestion occurs frequently in urban areas, while most existing solutions only take effects after congesting. In this paper, a congestion warning method is proposed based on the Internet of vehicles（IOV） and community discovery of complex networks. The communities in complex network model of traffic flow reflect the local aggregation of vehicles in the traffic system, and it is used to predict the upcoming congestion. The real-time information of vehicles on the roads is obtained from the IOV, which includes the locations, speeds and orientations of vehicles. Then the vehicles are mapped into nodes of network, the links between nodes are determined by the correlations between vehicles in terms of location and speed. The complex network model of traffic flow is hereby established. The communities in this complex network are discovered by fast Newman（FN） algorithm, and the congestion warnings are generated according to the communities selected by scale and density. This method can detect the tendency of traffic aggregation and provide warnings before congestion occurs. The simulations show that the method proposed in this paper is effective and practicable, and makes it possible to take action before traffic congestion.

Design and implementation of tourism system based on interactive narrative technique

In order to meet requirements of the tourists in the process of visit and realize the purpose of the social propaganda for scenic spot, interactive narrative technique and SNS platform are combined to form a kind of new interactive narrative technique in this paper. In this paper, with Unity3d engine as the core, tourism system is expanded the development, combined with the tourism information overlay function of Ctrip Travel, the attractions sharing function of Baidu Map, and the community function of Footprint. The purpose involves design, development and optimizing debug of techniques, such as network communication, UI interaction, cross-platform calls, database access and etc. The main goal of this paper is to provide internal visit narrative community service in limited and fixed scenic area and turning the corresponding service object by mass of visitors to the visitors of scenic spot, and to make the function of App specific, simple and explicit.