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The purpose of this paper is to acquaint a wide audience of readers with some of the unique remote sensing and navigation capabilities of animals.

Biomimetic comparison of remote sensors evolved by animals and sensors designed by man. The study and comparison includes thermal infrared sensors used by snakes, echolocation used by bats and dolphins, and navigation methods used by birds. Countermeasures used by prey to avoid capture are also considered.

Some animals have remote sensing and navigation capabilities that are considerably more efficient than those provided by the human body or designed by man.

Sensor designers may be encouraged to use the biometic approach in the design of new sensors.

The paper provides a better understanding of animal behaviour, especially their unique abilities to remotely sense, echolocate and navigate with high accuracy over considerable distances.

The paper presents a comparison of remote sensors used by animals with those developed by humans. Remote sensor designers can learn to improve their sensor designs by studying animal sensors within a biomimetic framework.

Vertical handoff mechanism (VHO) becomes very popular because of the improvements in the mobility models. These developments are less to certain circumstances and thus do not provide support in generic mobility, but the vertical handover management providing in the heterogeneous wireless networks (HWNs) is crucial and challenging. Hence, this paper introduces the vertical handoff management approach based on an effective network selection scheme.

This paper aims to improve the working principle of previous methods and make VHO more efficient and reliable for the HWN.Initially, the handover triggering techniques is modelled for identifying an appropriate place to initiate handover based on the computed coverage area of cellular base station or wireless local area network (WLAN) access point. Then, inappropriate networks are eliminated for determining the better network to perform handover. Accordingly, a network selection approach is introduced on the basis ofthe Fractional-dolphin echolocation-based support vector neural network (Fractional-DE-based SVNN). The Fractional-DE is designed by integrating Fractional calculus (FC) in Dolphin echolocation (DE), and thereby, modifying the update rule of the DE algorithm based on the location of the solutions in past iterations. The proposed Fractional-DE algorithm is used to train Support vector neural network (SVNN) for selecting the best weights. Several parameters, like Bit error rate (BER), End to end delay (EED), jitter, packet loss, and energy consumption are considered for choosing the best network.

The performance of the proposed VHO mechanism based on Fractional-DE is evaluated based on delay, energy consumption, staytime, and throughput. The proposed Fractional-DE method achieves the minimal delay of 0.0100 sec, the minimal energy consumption of 0.348, maximal staytime of 4.373 sec, and the maximal throughput of 109.20 kbps.

In this paper, a network selection approach is introduced on the basis of the Fractional-Dolphin Echolocation-based Support vector neural network (Fractional-DE-based SVNN). The Fractional-DE is designed by integrating Fractional calculus (FC) in Dolphin echolocation (DE), and thereby, modifying the update rule of the DE algorithm based on the location of the solutions in past iterations. The proposed Fractional-DE algorithm is used to train SVNN for selecting the best weights. Several parameters, like Bit error rate (BER), End to end delay (EED), jitter, packet loss, and energy consumption are considered for choosing the best network.The performance of the proposed VHO mechanism based on Fractional-DE is evaluated based on delay, energy consumption, staytime, and throughput, in which the proposed method offers the best performance.

The optimization and tradeoff of cost-time-quality-risk in one dimension and this four-dimensional problem in ambiguous mode and risk can be neither predicted nor estimated. This study aims to solve this problem and rank fuzzy numbers using an innovative algorithm “STHD” and a special technique “radius of gyration” (ROG) for fuzzy answers, respectively.

First, it is the optimization of a fully fuzzy four-dimensional problem which has never been dealt with in regard to risk in ambiguous mode and complexities. Therefore, the risk is a parameter which has been examined neither in probability and estimableness mode nor in the ambiguous mode so far. Second, it is a fully fuzzy tradeoff which, based on the principle of incompatibility “Zadeh, 1973”, proposes that when the complexity of a system surpasses the limited point, it becomes impossible to define the performance of that system accurately, precisely and meaningfully. The authors believe that this principle is the source of fuzzy logic. Third, for calculating and ranking fuzzy numbers of answers, a special technique for fuzzy numbers has been used. Fourth, For the sake of ease, precision and efficiency, an innovative algorithm called the technique of hunting dolphins “STHD” has been used. Finally, the problem is very close to reality. By applying risk in ambiguous mode, the problem has been realistically looked at.

The results showed that the algorithm was highly robust, with its performance depending very little on the regulation of the parameters. Ranking fuzzy numbers using the ROG indicated the flexibility of fuzzy logic, and it was also determined that the most appropriate regulations were to ensure low time, risk and cost but maximum quality in calculations, which were produced non-uniformly based on the levels of Pareto answers.

The ROG and Chanas Fuzzy Critical Path Method as developed by other researchers have been used. Despite the increase in limitations, parameters can develop. The originality of this study with regard to evaluating the results of tradeoff combinatorial optimization is upon decision-making which has a special and highly strategic role in the fate of the project, with the research been conducted with a special approach and different tools in a fully fuzzy environment.

Students with special needs include children with impaired attention, disruptive behavior, learning disabilities, and developmental disorders, among many other conditions. When a child has been diagnosed with such a disorder, his or her parents may seek treatment that could assist the child to be more academically and socially successful. Numerous interventions exist for the treatment of childhood disorders; however, these treatment methods differ in the types and amounts of evidence supporting their usefulness and effectiveness (Lilienfeld, 2005).

Offshore structures are among the structures exposed to fire more often. Most of these structures are likely to be associated with flammable materials. In this research, some of the structures constructed on top of marine decks have been studied.

For this purpose, the upper-bound theory of plastic analysis has been used to investigate its collapse behavior. In this way, genetic algorithm has been used for application of the combination of elementary mechanisms in the classic plastic analysis problem.

The studied structures are optimized by plastic analysis theory before and after the fire and their failure modes are compared with each other. The comparison of the results indicates significant changes in the load factor value, as well as the critical collapse mode of the structure before and after the fire.

Results indicate that the combination of plastic analysis and a genetic algorithm can predict the collapse mode of the structure before and after the fire accurately.

From a supply chain perspective, logistics firms collaborate with other supply chain members to extend their business scope. Investment in circular economy projects in the supply chain can not only broaden the scope of business but also increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects. How to coordinate multiple circular economy supply chain projects is at the core of its operation.

This paper first analyzes some typical supply chain projects in China and summarizes the main features of these projects. Secondly, considering the benefits of the project and the stakes of each project, a multi-stage stochastic programming model is established. Finally, Cplex, nested decomposition, LocalSolver and other methods are adopted to simulate and analyze the model.

The final experimental results find that the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

There are still some limitations to this study; for example, it is limited to the analysis of circular economy supply chain projects in China. The study focused on third-party logistics companies, and other enterprises in the circular economy supply chain were not considered. The research also assumed that the benefits of each circular economy project and the stakes of each project were known, which may not always be the case in real-world scenarios.

This manuscript found that investing in other circular economy projects in the supply chain can broaden the scope of business and increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects, such as recycling and repurposing initiatives. It highlights the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

This paper aims to present a new physically inspired meta-heuristic algorithm, which is called Plasma Generation Optimization (PGO). To evaluate the performance and capability of the proposed method in comparison to other optimization methods, two sets of test problems consisting of 13 constrained benchmark functions and 6 benchmark trusses are investigated numerically. The results indicate that the performance of the proposed method is competitive with other considered state-of-the-art optimization methods.

In this paper, a new physically-based metaheuristic algorithm called plasma generation optimization (PGO) algorithm is developed for solving constrained optimization problems. PGO is a population-based optimizer inspired by the process of plasma generation. In the proposed algorithm, each agent is considered as an electron. Movement of electrons and changing their energy levels are based on simulating excitation, de-excitation and ionization processes occurring through the plasma generation. In the proposed PGO, the global optimum is obtained when plasma is generated with the highest degree of ionization.

A new physically-based metaheuristic algorithm called the PGO algorithm is developed that is inspired from the process of plasma generation.

The results indicate that the performance of the proposed method is competitive with other state-of-the-art methods.

The purpose of this paper is to evaluate the performance of social spider algorithm (SSA) to solve constrained structural optimisation problems and to compare its results with others algorithms such as genetic algorithm, particle swarm optimisation, differential evolution and artificial bee colony.

To handle the constraints of the problems, this paper couples to the SSA an efficient selection criteria proposed in the literature that promotes a tournament between two solutions in which the feasible or less infeasible solution wins. The discussion is conducted on the competitiveness of the SSA with other algorithms as well as its performance in constrained problems.

SSA is a population algorithm proposed for global optimisation inspired by the foraging of social spiders. A spider moves on the web towards the position of the prey, guided by vibrations that occur around it in different frequencies. The SSA was proposed to solve problems without constraints, but these are present in most of practical problems. This paper evaluates the performance of SSA to solve constrained structural optimisation problems and compares its results with other algorithms such as genetic algorithm, particle swarm optimisation, differential evolution and artificial bee colony.

The proposed algorithm has no limitations, and it can be applied in other classes of constrained optimisation problems.

This paper evaluated the proposed algorithm with a benchmark of constrained structural optimisation problems intensely used in the literature, but it can be applied to solve real constrained optimisation problems in engineering and others areas.

This is the first paper to evaluate the performance of SSA in constrained problems and to compare its results with other algorithms traditional in the literature.

The purpose of this paper is to provide an overview of the wide range of biomimetic sensor technology and innovations.

The reader is introduced to biomimetic sensors, their types, their advantages and how they are different from traditional sensors. Background information is also provided regarding sensor design, inspiration and innovation.

There are two approaches to sensor design, which lead to diverse advantages and innovations. Classification of biomimetic sensors indicated which natural senses are underutilized by sensor designers and researchers.

The paper provides information of value for those seeking innovative sensor designs and research information for those who want to research in this area.

The purpose of this paper is to articulate a meaningful response to recent calls to “indigenize” and “decolonize” the Anthropocene in the social sciences and humanities; and in doing so to challenge and extend dominant conceptualisations of the Anthropocene offered to date within a posthuman and more-than-human intellectual context.

The paper develops a radical material and relational ontology, purposefully drawing on an indigenous knowledge framework, as it is specifically exemplified in Maori approaches to anthropogenic impacts on species and multi-species entanglements. The paper takes as its focus particular species of whales, trees and humans and their entanglements. It also draws on, critically engages with, and partially integrates posthuman and more-than-human theory addressing the Anthropocene.

The findings of this study are that we will benefit from approaching the Anthropocene from situated and specific ontologies rooted in place, which can frame multi-species encounters in novel and productive ways.

The paper calls for a more expansive and critical version of social science in which the relations between human and more-than-human becomes much more of a central concern; but in doing so it must recognize the importance of multiple histories, knowledge systems and narratives, the marginalization of many of which can be seen as a symptom of ecological crisis. The paper also proposes adopting Zoe Todd’s suggested tools to further indigenize the Anthropocene – though there remains much more scope to do so both theoretically and methodologically.

The paper argues that Anthropocene narratives must incorporate deeper colonial histories and their legacies; that related research must pay greater attention to reciprocity and relatedness, as advocated by posthuman scholarship in developing methodologies and research agendas; and that non-human life should remain firmly in focus to avoid reproducing human exceptionalism.

In societies where populations are coming to terms in different ways with living through an era of environmental breakdown, it is vital to seek out forms of knowledge and progressive collaboration that resonate with place and with which progressive science and humanities research can learn and collaborate; to highlight narratives which “give life and dimension to the strategies – oppositional, affirmative, and yes, often desperate and fractured – that emerge from those who bear the brunt of the planet’s ecological crises” (Nixon, 2011, p. 23).

The paper is original in approaching the specific and situated application of indigenous ontologies in some of their grounded everyday social complexity, with the potential value of opening up the Anthropocene imaginary to a more radical and ethical relational ontology.