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The communication link in the engineering of Internet of Vehicle (IOV) is more frequent than the communication link in the Mobile ad hoc Network (MANET). Therefore, the highly dynamic network routing reliability problem is a research hotspot to be solved.

The graph theory is used to model the MANET communication diagram on the highway and propose a new reliable routing method for internet of vehicles based on graph theory.

The expanded graph theory can help capture the evolution characteristics of the network topology and predetermine the reliable route to promote quality of service (QoS) in the routing process. The program can find the most reliable route from source to the destination from the MANET graph theory.

The good performance of the proposed method is verified and compared with the related algorithms of the literature.

This paper aims to propose a novel matrix-based systematic approach for vulnerability assessment.

The proposed method consists of two major steps. First, the power network is modeled as a topological combination of edges (transmission lines, transformers, etc.) and nodes (buses, substations, etc.). The second step is to use an axiomatic design-based index for topology analysis. This index is based on the systematic counting of possible routes from the start (generators) to destination (loads), considering load importance, before and after a disruption.

The effectiveness of the proposed method is demonstrated through an illustrative example and the Institute of Electrical and Electronics Engineers (IEEE) 14-bus power system. It was shown that the load’s importance influences the results of the vulnerability analysis. The proposed method has some advantages over traditional graph theory such as an explicit description of multiple transmission nodes and assets with multiple conversion processes. Furthermore, it would help the power grid operators and asset investment managers to be better to assess the vulnerable components.

The proposed method can be used in planning, optimization, robustness and hardening of power systems.

The paper presents a matrix-based systematic approach to evaluate and quantify the vulnerability of the power grid’s components.

Influencer marketing mediated by social media is prevalent in social commerce. Micro-, meso- and macro-influencers all play an irreplaceable role in marketing. The purpose of this paper is to explore how companies with limited budgets choose influencers according to products' various levels of brand familiarity.

This study constructs an evolutionary game model of influencer marketing based on evolutionary game theory on complex networks. This model initiates various networks to demonstrate how influencers disseminate information and constructs update mechanisms to depict how individuals react to this information based on individuals' information utility and friends' strategies.

Simulation results suggest that companies should invest more in macro-influencers than in meso-influencers, however investing all in macro-influencers is not a good choice. The investment in meso-influencers will increase as brand familiarity decreases, whereas it will not exceed investment in macro-influencers. Furthermore, the accumulation of micro-influencers can accelerate the marketing process.

This study examines the combined effects of micro-influencers, meso-influencers and macro-influencers in marketing by simulating the marketing process initiated by influencers on social media.

The purpose of this paper is to present a P2P network security pricing model that promotes more secure online information sharing in P2P networks through the creation of networks with increased resistance to malicious code propagation. Online information sharing is at an all‐time high partly due to the recent growth in, and use of, online peer‐to‐peer (P2P) networks.

The model integrates current research findings in incentive compatible network pricing with recent developments in complex network theory. File download prices in P2P networks are linked to network security using a graph theory measurement called the Pearson coefficient. The Pearson coefficient indicates a structural dimension of scale‐free networks (scale‐free networks like the internet) called preferential attachment. Preferential attachment refers to the network property where the probability for a node to connect to a new node is greater if the new node already has a high number of connections.

The P2P network security pricing model concept is illustrated to show how the model functions to create more secure P2P networks.

Future research in P2P network security pricing should focus on testing the model presented in this paper by numerical experiments and simulation including the tracking of malicious code propagation on networks grown under the pricing model.

The P2P network security pricing model demonstrated here is a different approach to network security that has a strong potential to impact on the future security of P2P and other computer based networks.

Textile manufacturers worldwide are reformulating their networks, often outsourcing them to maintain a competitive advantage and increase market share. From this perspective, the purpose of this study is support the partnership selection process to develop a sustainable chain that effectively meets customer needs. Brazil has the largest textile and apparel chain in the West and is distinguished by its completeness, from fiber production, spinning, weaving, knitting, finishing and sewing to fashion shows. However, a firm’s relationship, especially in the production stage, is based on informal contracts, which result in a negative operational impact.

A methodological framework was developed based on a stable matching process to determine the optimal supplier network structure. This study presents a model application for the denim apparel chain in northeast Brazil.

In these environments, providing choices and recommending suppliers can be beneficial for effectively attending to demand requests, reducing production costs and improving quality through collaboration with sense relationships in a network. Thus, this study presents a better match from the negotiators’ perspective.

The findings of this research are of primary interest for guiding collaborative network composition in the textile and apparel chain. In particular, apparel domain companies can improve their effectiveness in decision-making by measuring the characteristics and potential of all companies involved in networks.

The purpose of this paper is to explore the evolvement of investors’ behavior in stock market dynamically on the basis of non-cooperative strategy applied by investors in complex networks.

Using modeling and simulation research method, this study designs and conducts a mathematical modeling and its simulation experiment of financial market behavior according to research’s basic norms of complex system theory and methods. Thus the authors acquire needed and credible experimental data.

The conclusions drawn in this paper are as follows. The dynamical evolution of investors’ trading behavior is not only affected by the stock market network structure, but also by the risk dominance degree of certain behavior. The dynamics equilibrium of trading behavior’s evolvement is directly influenced by the risk dominance degree of certain behavior, connectivity degree and the heterogeneity of the stock market networks.

This paper focuses on the dynamical evolvement of investors’ behavior on the basis of the hypothesis that common investors prefer to mimic their network neighbors’ behavior through different analysis by the strategy of anti-coordination game in complex network. While the investors’ preference and the beliefs among them are not easy to quantify, that is deterministic or stochastic as the environment changes, and is heterogeneous definitely. Thus, these limitations should be broken through in the future research.

This paper aims to address the dynamical evolvement of investors’ behavior in stock market networks on the principle of non-cooperative represented by anti-coordination game in networks for the first time, considering that investors prefer to mimic their network neighbors’ behavior through different analysis by the strategy of differential choosing in every time step. The methodology designed and used in this study is a pioneering and exploratory experiment.

This research will analyze the traditional Iranian buildings according to the climatic factors by the use of graph theory. By this way, the hypothesis that climate factor has a major effect on the organization of the spaces in traditional Iranian buildings will be tested. Access graphs have been used to clarify the connectivity and depth of a building’s spaces from the socio-cultural point of view. However, it cannot be applied to climate studies. Thus, this study developed the existing technique to define building layouts in terms of climate and thermal comfort. The thermal comfort was graphically evaluated by the two main factors like solar gain and wind effect, with the use of a simple multi-attribute rating technique. All the analysis had been done in the interval of zero (the worst condition) to three (the best condition). The proposed orientation-weighted graph method proved that the thermal comfort factors of the buildings under study match the seasonal movements of their inhabitants. Consequently, the developed orientation-weighted graph method can be used to study space organization in traditional Iranian building in terms of solar gain and wind effect.

This study aims to design a multivariate control chart that improves the applicability of the traditional Hotelling T² chart. This new type of multivariate control chart displays sufficient information about the states and relationships of the variables in the production process. It is used to make better quality control decisions during the production process.

Multivariate data are collected at an equal time interval and are represented by nodes of the graph. The edges connecting the nodes represent the sequence of operation. Each node is plotted on the control chart based on their Hotelling T² statistical distance. The changing behavior of each pair of input and output nodes is studied by the neural network. A case study from the cement industry is conducted to validate the control chart.

The finding of this paper is that the points and lines in the classic Hotelling T² chart are effectively substituted by nodes and edges of the graph respectively. Nodes and edges have dimension and color and represent several attributes. As a result, this control chart displays much more information than the traditional Hotelling T² control chart. The pattern of the plot represents whether the process is normal or not. The effect of the sequence of operation is visible in the control chart. The frequency of the happening of nodes is recognized by the size of nodes. The decision to change the product feature is assisted by finding the shortest path between nodes. Moreover, consecutive nodes have different behaviors, and that behavior change is recognized by neural network.

Modifying the classical Hotelling T² control chart by integrating with the concept of graph theory and neural network is new of its kind.

Purpose – For decades, archivists have been appraising, preserving, and providing access to digital records by using archival theories and methods developed for paper records. However, production and consumption of digital records are informed by social and industrial trends and by computer and data methods that show little or no connection to archival methods. The purpose of this chapter is to reexamine the theories and methods that dominate records practices. The authors believe that this situation calls for a formal articulation of a new transdiscipline, which they call computational archival science (CAS).

Design/Methodology/Approach – After making a case for CAS, the authors present motivating case studies: (1) evolutionary prototyping and computational linguistics; (2) graph analytics, digital humanities, and archival representation; (3) computational finding aids; (4) digital curation; (5) public engagement with (archival) content; (6) authenticity; (7) confluences between archival theory and computational methods: cyberinfrastructure and the records continuum; and (8) spatial and temporal analytics.

Findings – Each case study includes suggestions for incorporating CAS into Master of Library Science (MLS) education in order to better address the needs of today’s MLS graduates looking to employ “traditional” archival principles in conjunction with computational methods. A CAS agenda will require transdisciplinary iSchools and extensive hands-on experience working with cyberinfrastructure to implement archival functions.

Originality/Value – We expect that archival practice will benefit from the development of new tools and techniques that support records and archives professionals in managing and preserving records at scale and that, conversely, computational science will benefit from the consideration and application of archival principles.

This paper aims to define the socio-spatial considerations of apartment users in Cairo, during their decision-making process. It provides a set of socio-spatial guidelines for professional architecture designers that are based on regionalist sociological theories and the evaluation of participant responses. These guidelines can also help users choose better plan configurations or make socially conscious adjustments as formal residential interiors in Egypt are not arranged based on social interaction at home or the cultural specificity of the region. On the other hand, users have little clue about choosing better plan configurations for sustainable social relationships. Moreover, the private housing sector has mostly neglected the social boundaries that traditionally shaped home interiors. This is because the designers focus on physical attributes to satisfy market demand and economic aspects.

The research reviewed past literature on the impact of different home arrangements relative to inhabitant and social relationships. Simultaneously, preliminary open-ended sorting surveys were undertaken at the Cityscape 2020 exhibition. Based on the results, a comprehensive online survey was developed to map the socio-spatial preferences of users. Finally, a sample of 150 apartment plans was analyzed by using the justified plan graph (JPG) theory to reveal the most common arrangements in the speculative market, measuring unit depth.

The findings of this study will benefit the following: practitioners, including architects and real estate developers, will be able to learn about end-user preferences and offer better products (residential units). Designers can rely on a reference that visualizes recommended home arrangements in the form of justified graphs. This research will expose the academic theories that currently shape residential plans and those that are overlooked and need to be applied. Academics, on the other hand, will learn about the market, and the extent of the influence of architectural theory.

The value of this paper lies in the gathering of theoretical recommendations on traditional home arrangements and investigating the preferences of both professionals and laypeople when choosing between apartments. The open-ended study in this research will test its efficiency in the Egyptian context and serve as a reference for future social studies. It highlights the importance of cultural adequacy and how to design homes related to local residents’ natural lifestyle, by doing so, people will be able to overview the options available in the market and how to manipulate their own houses to control or encourage different social interactions.