Background Optical measurement techniques and recent advances in wearable technology have made heart rate (HR) sensing simpler and more affordable. Objectives The Polar OH1 is an arm worn optical heart rate monitor. The objectives of this study are two-fold; 1) to validate the OH1 optical HR sensor with the gold standard of HR measurement, electrocardiography (ECG), over a range of moderate to high intensity physical activities, 2) to validate wearing the OH1 at the temple as an alternative location to its recommended wearing location around the forearm and upper arm. Methods Twenty-four individuals participated in a physical exercise protocol, by walking on a treadmill and riding a stationary spin bike at different speeds while the criterion measure, ECG and Polar OH1 HR were recorded simultaneously at three different body locations; forearm, upper arm and the temple. Time synchronised HR data points were compared using Bland-Altman analyses and intraclass correlation. Results The intraclass correlation between the ECG and Polar OH1, for the aggregated data, was 0.99 and the estimated mean bias ranged 0.27–0.33 bpm for the sensor locations. The three sensors exhibited a 95% limit of agreement (LoA: forearm 5.22, -4.68 bpm; upper arm 5.15, -4.49; temple 5.22, -4.66). The mean of the ECG HR for the aggregated data was 112.15 ± 24.52 bpm. The intraclass correlation of HR values below and above this mean were 0.98 and 0.99 respectively. The reported mean bias ranged 0.38–0.47 bpm (95% LoA: forearm 6.14, -5.38 bpm; upper arm 6.07, -5.13 bpm; temple 6.09, -5.31 bpm), and 0.15–0.16 bpm (95% LoA: forearm 3.99, -3.69 bpm; upper arm 3.90, -3.58 bpm; temple 4.06, -3.76 bpm) respectively. During different exercise intensities, the intraclass correlation ranged 0.95–0.99 for the three sensor locations. During the entire protocol, the estimated mean bias was in the range -0.15–0.55 bpm, 0.01–0.53 bpm and -0.37–0.48 bpm, for the forearm, upper arm and temple locations respectively. The corresponding upper limits of 95% LoA were 3.22–7.03 bpm, 3.25–6.82 bpm and 3.18–7.04 bpm while the lower limits of 95% LoA were -6.36–(-2.35) bpm, -6.46–(-2.30) bpm and -7.42–(-2.41) bpm. Conclusion Polar OH1 demonstrates high level of agreement with the criterion measure ECG HR, thus can be used as a valid measure of HR in lab and field settings during moderate and high intensity physical activities.

Path planning is a vital and challenging component in the support of Unmanned Aerial Vehicles (UAVs) and their deployment in autonomous missions, such as following ground moving target. Few attempts are reported in the literature on multirotor UAV path planning techniques for following ground moving targets despite the great improvement in their control dynamics, flying behaviors and hardware specifications. These attempts suffer several drawbacks including their hardware dependency, high computational requirements, inability to handle obstacles and dynamic environments in addition to their low performance regarding the moving target speed variations. In this paper, a novel dynamic Artificial Potential Field (D-APF) path planning technique is developed for multirotor UAVs for following ground moving targets. The UAV produced path is a smooth and flyable path suitable to dynamic environments with obstacles and can handle different motion profiles for the ground moving target including change in speed and direction. Additionally, the proposed path planning technique effectively supports UAVs following ground moving targets while maneuvering ahead and at a standoff distance from the target. It is hardware-independent where it can be used on most types of multirotor UAVs with an autopilot flight controller and basic sensors for distance measurements. The developed path planning technique is tested and validated against existing general potential field techniques for different simulation scenarios in ROS and gazebo-supported PX4-SITL. Simulation results show that the proposed D-APF is better suited for UAV path planning for following moving ground targets compared to existing general APFs. In addition, it outperforms the general APFs as it is more suitable for UAVs flying in environments with dynamic and unknown obstacles. INDEX TERMS Unmanned Aerial Vehicles, path planning, Artificial Potential Field, ground moving targets.

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Objective: The aim of this paper is to provide a comprehensive and original review of the theoretical development of the individual operational cognitive readiness (OCR) theory. Background: Cognitive readiness (CR) is a concept that has the potential to predict the performance of human individuals and teams prior to engaging in complex, dynamic, and resource-limited task environments. However, the current state of the literature is confusing and laborious, with heterogeneous views regarding the theoretical frameworks among leading researchers. Method: This review (1) undertakes a systematic approach toward categorizing published CR literature into theoretical and measurement contributions across the different levels of CR, (2) carries a critical evaluation of the CR and OCR theoretical frameworks, and (3) provides directions for future research guided by gaps identified during the review process and other published literatures. Results: Results from the categorization of published CR literature provide a new, valuable, synthesized CR library for researchers to consult to streamline their CR literature review process. Critical examination of the CR and OCR theoretical frameworks leads to positing that new components should be explored for OCR. Conclusion: There are many possible directions for future research including evaluating domain-independent components of OCR and evaluating the relationship between biofeedback measures and performance in CR models. Application: The Defense domain continues to be the focal application of CR. However, CR could be used by other application domains, such as sports and emergency services, that require their working personnel to engage in complex, uncertain, and dynamic task environments.

Dynamic resilience is a temporal process that reflects individuals’ capability to overcome task-induced stress and sustain their performance during task-related events. First-order autoregressive (AR(1)) modelling is posited for measuring individuals’ dynamic resilience over time. The current research investigated this by testing 30 adults in a dynamic decision-making task. AR(1) modelling was conducted on the data, and was compared against a modified seismic resilience metric for concurrent validity purposes. Results revealed that AR(1) modeled parameters are applicable in assessing participants’ dynamic resilience, with analyses supporting their use to distinguish between individuals that can overcome task-induced stress and those that cannot, as well as, in the classification of individuals’ dynamic resilience.

Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) Application of an Evolutionary Algorithm-based Ensemble Model to Job-Shop SchedulingChoo Jun TAN, Siew Chin NEOH, Chee Peng LIM, Samer HANOUN, Wai Peng WONG, Chu Kong LOO, Li ZHANG, Saeid NAHAVANDI Abstract In this paper, a novel evolutionary algorithm is applied to tackle job-shop scheduling tasks in manufacturing environments. Specifically, a modified micro genetic algorithm (MmGA) is used as the building block to formulate an ensemble model to undertake multi-objective optimisation problems in job-shop scheduling. The MmGA ensemble is able to approximate the optimal solution under the Pareto optimality principle. To evaluate the effectiveness of the MmGA ensemble, a case study based on real requirements is conducted. The results positively indicate the effectiveness of the MmGA ensemble in undertaking job-shop scheduling problems.

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This paper considers a flowshop scheduling problem with two criteria, where the primary (dominant) criterion is the minimization of material waste and the secondary criterion is the minimization of the total tardiness time. The decision maker does not authorize trade-offs between the criteria. In view of the nature of this problem, a hierarchical (lexicographical) optimization approach is followed. An effective greedy heuristic is proposed to minimize the material waste and a simulated annealing (SA) algorithm is developed to minimize the total tardiness time, subjective to the constraint computed for the primary criterion. The solution accuracy is compared with the optimal solution obtained by complete enumeration for randomly generated problem sets. From the results, it is observed that the greedy heuristic produces the optimal solution and the SA solution does not differ significantly from the optimal solution.