A Secure Energy Aware Game Theory (SEGaT) Mechanism for Coordination in WSANs

A novel secure energy aware game theory (SEGaT) method has proposed to have better coordination in wireless sensor actor networks. An actor has a cluster of sensor nodes which is required to perform different action based on the need that emerge in the network individually or sometime with coordination from other actors. The method has different stages for the fulfilment of these actions. Based on energy aware actor selection (EAAS), selection of number of actors and their approach is the initial step followed by the selection of best team of sensors with each actor to carry out the action and lastly the selection of reliable node within that team to finally nail the action into place in the network for its smooth working and minimum compromise in the energy The simulations are done in MATLAB and result of the energy and the packet delivery ratio are compared with game theory (GaT) and real time energy constraint (RTEC) method. The proposed protocol performs better in terms of energy consumption, packet delivery ratio as compared to its competitive protocols.

Artificial intelligence in customer-facing financial services: a systematic literature review and agenda for future research

PurposeThe objective of this study is to provide a systematic review of the literature on artificial intelligence (AI) in customer-facing financial services, providing an overview of explored contexts and research foci, identifying gaps in the literature and setting a comprehensive agenda for future research.Design/methodology/approachCombining database (i.e. Scopus, Web of Science, EBSCO, ScienceDirect) and manual journal search, the authors identify 90 articles published in Australian Business Deans Council (ABDC) journals for investigation, using the TCCM (Theory, Context, Characteristics and Methodology) framework.FindingsThe results indicate a split between data-driven and theory-driven research, with most studies either adopting an experimental research design focused on testing the accuracy and performance of AI algorithms to assist with credit scoring or investigating AI consumer adoption behaviors in a banking context. The authors call for more research building overarching theories or extending existing theoretical perspectives, such as actor networks. More empirical research is required, especially focusing on consumers' financial behaviors as well as the role of regulation, ethics and policy concerned with AI in financial service contexts, such as insurance or pensions.Research limitations/implicationsThe review focuses on AI in customer-facing financial services. Future work may want to investigate back-office and operations contexts.Originality/valueThe authors are the first to systematically synthesize the literature on the use of AI in customer-facing financial services, offering a valuable agenda for future research.

Actor-networks, a Project in Engineering Education

Actor-network theory represents a way to look at things, very different from traditional approaches. Convinced that actor-networks can provide an excellent mindset to deal with innovation in engineering education we present a concise background on the topic oriented to this knowledge area. We deal with knowledge, learning, contexts, and actor networking within situated cooperative environments. We deal with the articulation of planned approaches and policies, providing ideas to explore contexts in which we can improve people’s involvement and design some innovative strategies and artifacts. We address the conciliation of sensibilities that normally wouldn’t be able to cooperate. We try to imagine a space of translations and negotiations that facilitate the formulation of problems as a combination of detours and extensions, constructing alignments to a goal

Spatial evolution path of Gulangyu Island historical international community: from the perspective of actor-network theory

Gulangyu Island is a special case of social development and changes since modern China. In the past, Chinese and foreign people lived together and Chinese and Western cultures coexisted, resulting in an international community with outstanding cultural diversity and modern quality of life. As a functional carrier, space is of great reference significance to the research on the spatial evolution path of the Gulangyu international community with the accelerating globalization and rapid expansion of urbanization. Based on the interpretation of historical maps and the integration of historical geographic information, this paper explores the evolution path of Gulangyu community space in modern times from the perspective of actor-network theory. It is found that: (1) The change of key actors promotes the spatial evolution of the Gulangyu international community. (2) In the stage of foreign culture dissemination (1840–1902), foreign nationals, as key actors, promoted the formation and development of actor-networks through administrative recruitment and other means, and promoted Gulangyu Island to change from a traditional Minnan community to a modern community form, with the embryonic form of an international community beginning to emerge. (3) In the stage of multicultural integration (1903–1940), overseas Chinese returning home became key actors. The concept of a combination of Western cultures was not only embodied in community management but also acted on space practice to promote the multicultural integration of the Gulangyu international community. This paper summarizes the effects of various factors on the evolution of community space, to provide a reference for other coastal cities to rationally develop islands and promote the multicultural integration of local communities.

Distributed partition detection and recovery using UAV in wireless sensor and actor networks

Wireless Sensor and Actor Networks (WSANs) have been extensively employed in various domains ranging from elementary data collection to real-time control and monitoring for critical applications. Network connectivity is a vital robustness measure for overall network performance. Different network functions such as routing, scheduling, and QoS provisioning depends on network connectivity. The failure of articulation points in the network disassociates the network into disjoint segments. We proposed Distributed Partition Detection and Recovery using Unmanned Aerial Vehicle (UAV) (DPDRU) algorithm, as an optimal solution to recover the partitioned network. It consists of three steps: Initialization, Operational and Detection, and Recovery. In the Initialization phase sink node collects all the information about the network. In the Operational and Detection phase, network nodes communicate regularly by exchanging HEARTBEATS, detects failure if some nodes do not get a message from the neighbor node and send failure reports, and sink node identifies network partition. In the recovery phase, the sink node sends UAV at the positional coordinates of the failed node and examines network recovery after UAV reaches the desired location. Our approach primarily focuses on reducing message overhead by sending few update messages to sink node and energy consumption by engaging network nodes only for communication. The requirements of the recovery process (physical movement and communication) are fulfilled by UAV. The algorithm is tested according to the following parameters: Detection Time, Recovery Time, message overhead, and distance traveled by UAV. Simulation results validate the efficacy of the proposed algorithm based on these parameters to provide reliable results. The minimum and the maximum number of messages transmitted are 11 for 10 nodes and 24 for 100 nodes respectively. Hence these results demonstrate that the message overhead in our proposed solution is less as compared to other techniques when the number of nodes increases.