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Ant Colony Optimization and Particle Swarm Optimization represent two widely used Swarm Intelligence (SI) optimization techniques. Information processing using Multiple-Valued Logic (MVL) is carried out using more than two discrete logic levels. In this paper, we compare two the SI-based algorithms in synthesizing MVL functions. A benchmark consisting of 50,000 randomly generated 2-variable 4-valued functions is used for assessing the performance of the algorithms using the benchmark. Simulation results show that the PSO outperforms the ACO technique in terms of the average number of product terms (PTs) needed. We also compare the results obtained using both ACO-MVL and PSO-MVL with those obtained using Espresso-MV logic minimizer. It is shown that on average, both of the SI-based techniques produced better results compared to those produced by Espresso-MV. We show that the SI-based techniques outperform the conventional direct-cover (DC) techniques in terms of the average number of product terms required.

The purpose of this paper is to develop a new mathematical method for the reliability analysis and evaluation of multi-state system (MSS) reliability that agrees with specifics of such system. It is possible based on the application of multiple-valued logic (MVL) that is a natural extension of Boolean algebra used in reliability analysis.

Similar to Boolean algebra, MVL is used for the constriction of the structure function of the investigated system. The interpretation of the structure function of the MSS in terms of MVL allows using mathematical methods and approaches of this logic for the analysis of the structure function.

The logical differential calculus is one of mathematical approaches in MVL. The authors develop new method for MSS reliability analysis based on logical differential calculus, in particular direct partial logical derivatives, for the investigation of critical system states (CSSs). The proposed method allows providing the qualitative and quantitative analyses of MSS: the CSS can be defined for all possible changes of any system component or group of components, and probabilities of this state can also be calculated.

The proposed method permits representing the MSS in the form of a structure function that is interpreted as MVL function and provides the system analyses without special transformation into Boolean interpretation and with acceptable computational complexity.

The purpose of this paper is to show how metamaterials with extreme values of permittivity and permeability, may be effectively used to design artificial magnetic conductors (AMC) at a given frequency. In particular, this paper theoretically determines, for the different polarizations of the incidence field, the conditions under which metamaterials can behave as an AMC.

In order to find out the required values of the constitutive parameters, this paper has done a theoretical analysis based on the transmission-line theory. The obtained analytical reflection coefficient has been particularized for the different possible polarizations of the incidence field in order to find the constitutive parameters values that this paper needs for the AMC behavior.

Depending on the polarization of the field, it is shown that different values of the constitutive parameters are needed to get AMCs. In particular, it is shown that in the case of TEM and TE polarizations, a large value of the permeability is enough to obtain an AMC boundary condition. In the case of the TM polarization, instead, the AMC boundary condition is effectively achieved by using a material with vanishing permittivity. The role of the permittivity in the three polarizations is discussed. Finally, possible implementations and applications at microwave and optical frequencies are presented.

The idea of using miniaturized inclusions to obtain AMCs is not completely new. However, to the authors' best knowledge, a complete and rigorous theoretical analysis showing the capabilities and the limits of this approach has not yet been presented in the open technical literature.

New approaches for non‐classical neural‐based computing are introduced. The developed approaches utilize new concepts in three‐dimensionality, invertibility and reversibility to perform the required neural computing. The various implementations of the new neural circuits using the introduced paradigms and architectures are presented, several applications are shown, and the extension for the utilization in neural‐systolic computing is also introduced.

The new neural paradigms utilize new findings in computational intelligence and advanced logic synthesis to perform the functionality of the basic neural network (NN). This includes the techniques of three‐dimensionality, invertibility and reversibility. The extension of implementation to neural‐systolic computing using the introduced reversible neural‐systolic architecture is also presented.

Novel NN paradigms are introduced in this paper. New 3D paradigm of NL circuits called three‐dimensional inverted neural logic (3DINL) circuits is introduced. The new 3D architecture inverts the inputs and weights in the standard neural architecture: inputs become bases on internal interconnects, and weights become leaves of the network. New reversible neural network (RevNN) architecture is also introduced, and a RevNN paradigm using supervised learning is presented. The applications of RevNN to multiple‐output feedforward discrete plant control and to reversible neural‐systolic computing are also shown. Reversible neural paradigm that includes reversible neural architecture utilizing the extended mapping technique with an application to the reversible solution of the maze problem using the reversible counterpropagation NN is introduced, and new neural paradigm of reversibility in both architecture and training using reversibility in independent component analysis is also presented.

Since the new 3D NNs can be useful as a possible optimal design choice for compacting a learning (trainable) circuit in 3D space, and because reversibility is essential in the minimal‐power computing as the reduction of power consumption is a main requirement for the circuit synthesis of several emerging technologies, the introduced methods for non‐classical neural computation are new and interesting for the design of several future technologies that require optimal design specifications such as three‐dimensionality, regularity, super‐high speed, minimum power consumption and minimum size such as in low‐power control, adiabatic signal processing, quantum computing, and nanotechnology.

The green building (GB) maintenance industry has been under increasing pressure by designers to demonstrate its evaluation and information management of building information modelling based model checking (BMC) to the competency's performance and design knowledge of building control instrument. This main problem has been termed as maintenance planning level. Although maintenance planning has been explored in GB maintenance environments, less is known about what maintenance planning problems currently exist and what their causes are, such as the recent fire in the Grenfell Tower (14 June 2017, about 80 fatalities) in North Kensington, West London. The aim of this paper is to identify how GB maintenance environments could integrate BMC within their processes. The purpose of this study is to assess the BMC technology management of GB maintenance ecosystem and that of a soft skills level to establish the impact of innovation policy features on database and safety risk function mechanism.

To achieve this aim, a comprehensive literature review of the existing conceptualisation of BMC practices is reviewed and the main features of Information and Communication Technology tools and techniques currently being employed on such GB maintenance ecosystem is carried out to evaluate the strengths and weaknesses of the previous studies. The conceptual framework explores the importance of integration of BMC in the construction phase to identify alternative methods in the automation system (AS) process to co-generate, monitor and optimise BMC.

The results confirm that BMC tool positively influences database application and risk mechanism of construction project safety while agreeableness negatively does. Besides, database application has a negative influence on innovation policy of company towards BMC implementation. Propositions derived not only shed light on guidance for future research on the soft skills of construction organisations, but also provide decision-making support through a better understanding of the factors affecting soft skills level amongst biggest construction companies.

Thus far, this study advances the knowledge about how GB maintenance environments can ensure BMC delivery. This paper highlights the need for further research to integrate BMC in GB maintenance environments validates the framework across the construction phase with different GB project managers and engineers.

This paper aims to identify the different system approach using building information modelling (BIM) technology that is equipped with automated evaluation processes. BIM research has mainly focused on theoretical models of acceptance in the green building (GB) maintenance industry. However, BIM has the potential to the competency’s performance and design knowledge of building control instrument. Realising this potential requires a study of BIM at the maintenance planning level, which is considered to be BIM-based model checking (BMC). BMC and its effect in the maintenance planning have not been sufficiently investigated.

The aim of this paper is to present a critical review of literature on the theoretical background of BMC practices and the main features of information and communication technology tools and techniques in the GB maintenance projects.

A theoretical framework of BMC is developed and presented. The proposed model incorporates requirement for maintaining a competency’s performance on maintenance planning schemes of GB projects and the importance of early integration of BMC in the design phase to identify alternative methods to cogenerate, monitor and optimise BMC.

It is found that variables facilitating BMC are integrated at different GB maintenance environments levels and are shaped by the context. Directions for future research are presented.