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This paper describes the entire methodology for the development of a scale to measure Attitude towards Open Educational Resources (ATOER). Traditionally, it is observed that some teachers are more willing to share their work than others, indicating the need to understand teachers' psychological and behavioural determinants that influence use of OER. The paper presents the methodological rigour in the development of the 17 items two-factor scale that is valid and reliable to measure attitude towards OER. The psychometric properties of the scale include: Content Validity Ratio=0.9 and Cronbach α=0.897 with strong inter-items correlation. The two-factors attitude construct in the scale was also subjected to a good model fit using Structural Equation Modelling, which revealed a mediocre fit with 0.8 Root Mean Square Error Approximation value and the chi-square to degree of freedom ratio below 3.We also discuss the significance of the scale and how to use it with other variables effectively in different contexts to help develop appropriate strategies for promoting the use of OER in educational institutions.

PurposeThe purpose of this paper is to report the design of a lightweight tree-shaped support structure for fused deposition modeling (FDM) three-dimensional (3D) printed models when the printing path is considered as a constraint. Design/methodology/approachA hybrid of genetic algorithm (GA) and particle swarm optimization (PSO) is proposed to address the topology optimization of the tree-shaped support structures, where GA optimizes the topologies of the trees and PSO optimizes the geometry of a fixed tree-topology. Creatively, this study transforms each tree into an approximate binary tree such that GA can be applied to evolve its topology efficiently. Unlike FEM-based methods, the growth of tree branches is based on a large set of FDM 3D printing experiments. FindingsThe hybrid of GA and PSO is effective in reducing the volume of the tree supports. It is shown that the results of the proposed method lead to up to 46.71% material savings in comparison with the state-of-the-art approaches. Research limitations/implicationsThe proposed approach requires a large number of printing experiments to determine the function of the yield length of a branch in terms of a set of critical parameters. For brevity, one can print a small set of tree branches (e.g. 30) on a single platform and evaluate the function, which can be used all the time after that. The steps of GA for topology optimization and those of PSO for geometry optimization are presented in detail. Originality/valueThe proposed approach is useful for the designers and manufacturers to save materials and printing time in fabricating complex models using the FDM technique. It can be adapted to the design of support structures for other additive manufacturing techniques such as Stereolithography and selective laser melting.

We present a look-ahead based trajectory planning algorithm for computation of dynamically feasible trajectories for Unmanned Sea Surface Vehicles (USSV) operating in high seas states. The algorithm combines A* based heuristic search and locally bounded optimal planning under motion uncertainty using a variation of the minimax game-tree search. This allows the algorithm to compute trajectories that explicitly consider the possibility of the vehicle safely deviating from its original course due to the ocean waves within a specified lookahead region. The algorithm can adapt its search based on the user-specified risk thresholds. Moreover, the algorithm produces a contingency plan as a part of the computed trajectory. We demonstrate the capabilities of the algorithm using simulations.

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