Practices and risks associated with operation of tie-down lashings in the vehicle transport industry

Load restraint systems in automobile transport utilise tie-down lashings placed over the car’s tyres, which are tensioned manually by the operator using a ratchet assembly. This process has been identified as a significant manual handling injury risk. The aim of this study was to gain insight on the current practices associated with tie-down lashings operation, and identify the gaps between current and optimal practice. We approached this with qualitative and quantitative assessments and one numerical simulation to establish: (i) insight into the factors involved in ratcheting; (ii) the required tension to hold the car on the trailer; and (iii) the tension achieved by drivers in practice and associated joint loads. We identified that the method recommended to the drivers was not used in practice. Drivers instead tensioned the straps to the maximum of their capability, leading to over-tensioning and mechanical overload at the shoulder and elbow. We identified the postures and strategies that resulted in the lowest loads on the upper body during ratcheting (using both hands and performing the task with their full body). This research marks the first step towards the development of a training programme aiming at changing practice to reduce injury risks associated with the operation of tie-down lashings in the automobile transport industry.

Practitioner Summary: The study investigated current practice associated with the operation of tie-down lashings through qualitative (interviews) and quantitative (biomechanical analysis) methods. Operators tended to systematically over-tension the lashings and consequently overexert, increasing injury risks.     

Adaptive observer design for discrete time LTV systems

In this paper, the discrete-time exponential forgetting factor observer is specialised for the joint estimation of state and parameters, leading to an adaptive observer in which the decay rates of the estimation errors for the two distinct objects can be quasi-separated. The effectiveness of the observer is demonstrated through numerical simulation.     

Towards a set of agrosystem-specific cropland mapping methods to address the global cropland diversity

Accurate cropland information is of paramount importance for crop monitoring. This study compares five existing cropland mapping methodologies over five contrasting Joint Experiment for Crop Assessment and Monitoring (JECAM) sites of medium to large average field size using the time series of 7-day 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) mean composites (red and near-infrared channels). Different strategies were devised to assess the accuracy of the classification methods: confusion matrices and derived accuracy indicators with and without equalizing class proportions, assessing the pairwise difference error rates and accounting for the spatial resolution bias. The robustness of the accuracy with respect to a reduction of the quantity of calibration data available was also assessed by a bootstrap approach in which the amount of training data was systematically reduced. Methods reached overall accuracies ranging from 85% to 95%, which demonstrates the ability of 250 m imagery to resolve fields down to 20 ha. Despite significantly different error rates, the site effect was found to persistently dominate the method effect. This was confirmed even after removing the share of the classification due to the spatial resolution of the satellite data (from 10% to 30%). This underlines the effect of other agrosystems characteristics such as cloudiness, crop diversity, and calendar on the ability to perform accurately. All methods have potential for large area cropland mapping as they provided accurate results with 20% of the calibration data, e.g. 2% of the study area in Ukraine. To better address the global cropland diversity, results advocate movement towards a set of cropland classification methods that could be applied regionally according to their respective performance in specific landscapes.     

Exploring educational immersive videogames: an empirical study with a 3D multimodal interaction prototype

ABSTRACT

Gestural interaction devices emerged and originated various studies on multimodal human–computer interaction to improve user experience (UX). However, there is a knowledge gap regarding the use of these devices to enhance learning. We present an exploratory study which analysed the UX with a multimodal immersive videogame prototype, based on a Portuguese historical/cultural episode. Evaluation tests took place in high school environments and public videogaming events. Two users would be present simultaneously in the same virtual reality (VR) environment: one as the helmsman aboard Vasco da Gama’s fifteenth-century Portuguese ship and the other as the mythical Adamastor stone giant at the Cape of Good Hope. The helmsman player wore a VR headset to explore the environment, whereas the giant player used body motion to control the giant, and observed results on a screen, with no headset. This allowed a preliminary characterisation of UX, identifying challenges and potential use of these devices in multi-user virtual learning contexts. We also discuss the combined use of such devices, towards future development of similar systems, and its implications on learning improvement through multimodal human–computer interaction.     

Viscous Open Data: The Roles of Intermediaries in an Open Data Ecosystem

Open data have the potential to improve the governance of universities as public institutions. In addition, open data are likely to increase the quality, efficacy and efficiency of the research and analysis of higher education systems by providing a shared empirical base for critical interrogation and reinterpretation. Drawing on research conducted by the Emerging Impacts of Open Data in Developing Countries project, and using an ecosystems approach, this research paper considers the supply, demand and use of open data as well as the roles of intermediaries in the governance of South African public higher education. It shows that government's higher education database is a closed and isolated data source in the data ecosystem; and that the open data that are made available by government is inaccessible and rarely used. In contrast, government data made available by data intermediaries in the ecosystem are being used by key stakeholders. Intermediaries are found to play several important roles in the ecosystem: (i) they increase the accessibility and utility of data; (ii) they may assume the role of a “keystone species” in a data ecosystem; and (iii) they have the potential to democratize the impacts and use of open data. The article concludes that despite poor data provision by government, the public university governance open data ecosystem has evolved because intermediaries in the ecosystem have reduced the viscosity of government data. Further increasing the fluidity of government open data will improve access and ensure the sustainability of open data supply in the ecosystem.     

Multi-contact vertical ladder climbing with an HRP-2 humanoid

We describe the research and the integration methods we developed to make the HRP-2 humanoid robot climb vertical industrial-norm ladders. We use our multi-contact planner and multi-objective closed-loop control formulated as a QP (quadratic program). First, a set of contacts to climb the ladder is planned off-line (automatically or by the user). These contacts are provided as an input for a finite state machine. The latter builds supplementary tasks that account for geometric uncertainties and specific grasps procedures to be added to the QP controller. The latter provides instant desired states in terms of joint accelerations and contact forces to be tracked by the embedded low-level motor controllers. Our trials revealed that hardware changes are necessary, and parts of software must be made more robust. Yet, we confirmed that HRP-2 has the kinematic and power capabilities to climb real industrial ladders, such as those found in nuclear power plants and large scale manufacturing factories (e.g. aircraft, shipyard) and construction sites.     

Examining the predictive relationship between personality and emotion traits and students’ agent-directed emotions: towards emotionally-adaptive agent-based learning environments

The current study examined the relationships between learners’ (\(N = 123\)) personality traits, the emotions they typically experience while studying (trait studying emotions), and the emotions they reported experiencing as a result of interacting with four pedagogical agents (agent-directed emotions) in MetaTutor, an advanced multi-agent learning environment. Overall, significant relationships between a subset of trait emotions (trait anger, trait anxiety) and personality traits (agreeableness, conscientiousness, and neuroticism) were found for four agent-directed emotions (enjoyment, pride, boredom, and neutral) though the relationships differed between pedagogical agents. These results demonstrate that some trait emotions and personality traits can be used to predict learners’ emotions directed toward specific pedagogical agents (with different roles). Results provide suggestions for adapting pedagogical agents to support learners’ (with certain characteristics; e.g., high in neuroticism or agreeableness) experience of adaptive emotions (e.g., enjoyment) and minimize their experience on non-adaptive emotions (e.g., boredom). Such an approach presents a scalable and easily implementable method for creating emotionally-adaptive, agent-based learning environments, and improving learner-pedagogical agent interactions in order to support learning.     

Functional Diversity,Absorptive Capability and Product Success: The Moderating Role of Project Complexity in New Product Development Teams

Absorptive capability appears to be an appealing concept in the technology and innovation management literature. Though absorptive capability attracts researchers from a variety of disciplines, team‐level empirical research on it is scant. In this study, we operationalized team absorptive capability as a multidimensional construct involving knowledge acquisition, assimilation and exploitation. This study also explores the moderating effect of project complexity between team absorptive capability and new product success. In studying the data from 239 new product development projects using partial least squares structural equation modelling, we found that team functional diversity is a significant determinant of team absorptive capability. Moreover, regarding the relationships between team absorptive capability and new product success, we uncovered that (i) new product success is dependent on the ability to understand the acquired knowledge, and (ii) the teams appear to be more cautious in putting the assimilated knowledge into practice to the extent that project complexity increases.     

A method to select a successful interoperability solution through a simulation approach

Enterprise applications and software systems need to be interoperable in order to achieve seamless business across organizational boundaries and thus realize virtual networked organizations. Our proposition can be considered as an interoperability project selection approach and is based on three steps: (1) Modelling both collaborative business processes and potential related interoperability projects; (2) Evaluating the accessibility of each project regarding the current state of the organization; (3) Simulating each project and assessing the associated performance. These results are finally projected on a comparison matrix used as a decision support to select the most appropriate interoperability solution. An application case extracted from the French aerospace sector demonstrates the applicability and the benefits of the proposition.