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To solve problems of low intelligence and poor robustness of traditional navigation systems, the purpose of this paper is to propose a brain-inspired localization method of the unmanned aerial vehicle (UAV).

First, the yaw angle of the UAV is obtained by modeling head direction cells with one-dimension continuous attractor neural network (1 D-CANN) and then inputs into 3D grid cells. After that, the motion information of the UAV is encoded as the firing of 3 D grid cells using 3 D-CANN. Finally, the current position of the UAV can be decoded from the neuron firing through the period-adic method.

Simulation results suggest that continuous yaw and position information can be generated from the conjunctive model of head direction cells and grid cells.

The proposed period-adic cell decoding method can provide a UAV with the 3 D position, which is more intelligent and robust than traditional navigation methods.

This research aims to determine whether the educational influence of the cybersecurity awareness campaign on the audience (their knowledge, behaviour and potential cybersecurity culture) matches the campaign’s educational objectives. The research focuses on the knowledge component of this metric by examining the awareness campaign audience’s interpretative role in processing the campaign content, through the lens of active audience theory (AAT).

Using reflective practices, this research examines a single longitudinal case study of a cybersecurity awareness and education campaign which aims to raise awareness amongst school learners. Artefacts from a single sample are examined.

Reflexive practices using theories such as active audience can assist in identifying deviations between the message a campaign intends to communicate and the message that the campaign audience receives.

Using this research approach, measurements could only be obtained for campaign messages depicted in artefacts. Future interventions should be designed to facilitate a more rigorous analysis of the audiences’ interpretation of all campaign messages using ATT.

This paper applied principles of ATT to examine the audience’s interpretative role in processing an awareness campaign’s content based on artifacts they created after exposure to the campaign. Conducting such analyses as part of a reflective process between cyber awareness/education campaign cycles provides a way to identify areas or topics within the campaign that require corrective action.

The purpose of this paper is to solve the capacitated location routing problem (CLRP), which is an NP-hard problem that involves making strategic decisions as well as tactical and operational decisions, using a hybrid particle swarm optimization (PSO) algorithm.

PSO, which is a population-based metaheuristic, is combined with a variable neighborhood strategy variable neighborhood search to solve the CLRP.

The algorithm is tested on a set of instances available in the literature and gave good quality solutions, results are compared to those obtained by other metaheuristic, evolutionary and PSO algorithms.

Local search is a time consuming phase in hybrid PSO algorithms, a set of neighborhood structures suitable for the solution representation used in the PSO algorithm is proposed in the VNS phase, moves are applied directly to particles, a clear decoding method is adopted to evaluate a particle (solution) and there is no need to re-encode solutions in the form of particles after applying local search.

Reliability of RAM memory systems is impaired by environmental disturbances, causing soft errors, whereby one data bit is transformed to another bit. Single‐error correcting codes with memory scrubbing offer the most effective method to recover from such errors. This paper analyzes the reliability and determines the MTTF for simplex and duplex memory systems with single‐error correction and/or soft‐error scrubbing recovery. It extends previous work on the deterministic scrubbing recovery of simplex memory systems by using a more general model that takes into account cancelling soft errors. In the duplex memory system an additional level of static redundancy is proposed by employing a decoding algorithm at the memory module level. The reliability analysis of the duplex system with soft‐error scrubbing takes into account the decoder output which upon scrubbing transforms words with a number of multiple errors to words with a different number of errors. Computer results show that this combination of data and system redundancy provides more reliability than either data or system redundancy alone.

The purpose of this paper is to explore the strategy for latecomers in large developing countries under globalization. The relationship between innovation and learning is deeply studied.

The paper formulates an in‐depth case study on the digital video player industry through consideration of government documents, reports, and research papers; intensive interviews; and questionnaire study.

The firms in developing countries might be able to innovate before they can match the firms in advanced countries in technological capabilities, and innovation is the most effective way of learning. The firms can achieve competitive advantage owing to the effect of the national value network, the nature of architectural technology, and the relationships between them in product development. The national market should be deliberately taken as a strategic asset for the technological learning and latecomers should learn how to exploit the advantage of globalization.

The paper tries to understand how firms in developing countries conduct learning by innovating to build their competitive advantages.

The purpose of this paper is to present a reversible flux linkage model of the switched reluctance motor so that the rotor position can be computed analytically.

The presented flux linkage model uses a Fermi function like equation with four coefficients to fit flux linkage characteristics. In this work, the coefficients are calculated from flux‐current‐angle data using numerical curve fitting with the least squares method. A rotor position model is then derived by inverting the flux linkage model. With a simple estimation scheme based on the rotor position model, the rotor position is estimated continuously. Simulation and experiments are then performed to verify the proposed method.

The presented flux linkage model agrees well with flux linkage characteristics. The average absolute relative error (AARE) of the model varies between 0.3 per cent and 5.3 per cent. With the derived rotor position model, rotor position can be estimated conveniently for either steady or dynamic operations.

The simulation and experimental results indicate that the presented model is an eligible candidate for applications such as rotor position estimation, performance simulation and other model based controls.

Unlike previously reported methods, the presented flux linkage model is reversible so that a rotor position model can be derived and the rotor position can be computed analytically.

Gloria Pritchett – the fiery and caring Latina mother in Modern Family – is believed to recreate cultural and gender stereotypes. This audience study was interested in situating her as an intersectional representation to recognize that numerous social categories coproduce her characterization not just one. Textual analyses of open-ended questions reveal that participants tend to explicitly and exclusively discuss her stereotypes in ethnic and gender terms, with an emphasis on the former. However, a semantic analysis of the words/adjectives used to describe Gloria Pritchett suggested these share meaning across multiple social categories. Some aspects of her representation, like those based on ethnicity and gender (her Latina wisdom) or ethnicity and social class (her social mobility from Colombia to the United States), were found commendable, respectable, and likable. Eventually, the social identities encompassing Gloria Pritchett are taken apart and compounded, which in turn, suggest that her intersectionality was malleable for viewers.