Search results

The purpose of this paper is to develop a highly miniaturized wireless inertial sensor system based on a novel 3D packaging technique using a flexible printed circuit (FPC). The device is very suitable for wearable applications in which small size and lightweight are required such as body area network, medical, sports and entertainment applications.

Modern wireless inertial measurement units are typically implemented on a rigid 2D printed circuit board (PCB). The design concept presented here is based around the use of a novel planar, six‐faceted, crucifix or cross‐shaped FPC instead of a rigid PCB. A number of specific functional blocks (such as microelectromechanical systems gyroscope and accelerometer sensors, microcontroller (MCU), radio transceiver, antenna, etc.) are first assigned to each of the six faces which are each 1 cm² in area. The FPC cross is then developed into a 1 cm³, 3D configuration by folding the cross at each of five bend planes. The result is a low‐volume and lightweight, 1 cm³ wireless inertial sensor that can sense and send motion sensed data wirelessly to a base station. The wireless sensor device has been designed for low power operation both at the hardware and software levels. At the base station side, a radio receiver is connected to another MCU unit, which sends received data to a personal computer (PC) and graphical user interface. The industrial, scientific and medical band (2.45 GHz) is used to achieve half duplex communication between the two sides.

A complete wireless sensor system has been realized in a 3D cube form factor using an FPC. The packaging technique employed during the work is shown to be efficient in fabricating the final cubic system and resulted in a significant saving in the final size and weight of the system. A number of design issues are identified regarding the use of FPC for implementing the 3D structure and the chosen solutions are shown to be successful in dealing with these issues.

Currently, a limitation of the system is the need for an external battery to power the sensor system. A second phase of development would be required to investigate the possibility of the integration of a battery and charging system within the cube structure. In addition, the use of flexible substrate imposes a number of restrictions in terms of the ease of manufacturability of the final system due to the requirement of the required folding step.

The small size and weight of the developed system is found to be extremely useful in different deployments. It would be useful to further explore the system performance in different application scenarios such as wearable motion tracking applications. In terms of manufacturability, component placement needs to be carefully considered, ensuring that there is sufficient distance between the components, bend planes and board edges and this leads to a slightly reduced usable area on the printed circuit.

This paper provides a novel and useful method for realizing a wireless inertial sensor system in a 3D package. The value of the chosen approach is that a significant reduction in the required system volume is achieved. In particular, a 78.5 per cent saving in volume is obtained in decreasing the module size from a 25 to a 15 mm³ size.

This study aims to propose a computationally efficient framework for multi-objective optimization (MO) of antennas involving nested kriging modeling technology. The technique is demonstrated through a two-objective optimization of a planar Yagi antenna and three-objective design of a compact wideband antenna.

The keystone of the proposed approach is the usage of recently introduced nested kriging modeling for identifying the design space region containing the Pareto front and constructing fast surrogate model for the MO algorithm. Surrogate-assisted design refinement is applied to improve the accuracy of Pareto set determination. Consequently, the Pareto set is obtained cost-efficiently, even though the optimization process uses solely high-fidelity electromagnetic (EM) analysis.

The optimization cost is dramatically reduced for the proposed framework as compared to other state-of-the-art frameworks. The initial Pareto set is identified more precisely (its span is wider and of better quality), which is a result of a considerably smaller domain of the nested kriging model and better predictive power of the surrogate.

The proposed technique can be generalized to accommodate low- and high-fidelity EM simulations in a straightforward manner. The future work will incorporate variable-fidelity simulations to further reduce the cost of the training data acquisition.

The fast MO optimization procedure with the use of the nested kriging modeling technology for approximation of the Pareto set has been proposed and its superiority over state-of-the-art surrogate-assisted procedures has been proved. To the best of the authors’ knowledge, this approach to multi-objective antenna optimization is novel and enables obtaining optimal designs cost-effectively even in relatively high-dimensional spaces (considering typical antenna design setups) within wide parameter ranges.

Although significant research has examined the concept of transformational leadership, few studies have explored the indirect impact of transformational leadership on individual and organizational outcomes within the context of crisis. Accordingly, this study aims to advance our understanding of the indirect impact of transformational leadership on school performance and principals' work alienation within the context of the COVID-19 pandemic. In doing so, this study contributes to this developing stream of literature by hypothesizing the indirect effect of two relational resources, namely employee trust and relational coordination, which mediate the relationship between transformational leadership, school performance and principals' work alienation.

This study draws on a unique sample of 634 principals from Irish primary schools navigating the COVID-19 crisis. Structural equation modeling (SEM) was performed using Mplus 8.3 to test the hypothesized model.

Mixed findings emerged concerning the mediating process of relational resources and their impact on transformational leadership, school performance and principals' work-alienation. In particular, support is found for the critical role of principals whose transformational leadership style can help increase school performance. However, evidence suggests that employee trust does not mediate the relationship between transformational leadership and principals' work alienation.

This study provides several practical insights for education professionals, policymakers and HRM practitioners across each phase of the crisis management cycle. Firstly, regarding the pre-crisis stage, educational institutions should invest in targeted leadership development programs that prioritize relationship-building and effective communication among stakeholders. Second, during crises, the study emphasizes the role of relational resources in mediating the impact of leadership on school performance. Moreover, the study illustrates the importance of proactively cultivating strong connections with stakeholders, fostering timely, problem-solving-based communication. Finally, in the post-crisis phase, collaboration with government stakeholders is recommended to inform recovery policies.

This study makes several contributions to the literature on leadership and crisis management. First, this study adds new insights suggesting how principals as leaders influence school performance during crisis. Second, by adopting a relational perspective, this study suggests two types of relational resources (i.e. employee trust and relational coordination), as the mediators between transformational leadership, school performance and principals' work alienation. Third, this study moves the existing research on leadership during crisis forward by focusing on the functional effectiveness of leadership while focusing on the principals' work alienation during the pandemic.

The purpose of this paper is to enhance understanding of the conceptualisation and operationalisation of public value in practice by applying Moore's (1995) strategic triangle as an analytical framework to study strategic management and management control practices in relation to public value.

The paper uses an interpretative longitudinal case study approach including qualitative methods of document studies and interviews between 2017 and 2019.

In the strategic triangle, the three nodes of authorising environment, public value creation and operational capacity are interdependent, and alignment is a necessity for a strategy to be successful. But this alignment is vulnerable. The findings suggest three propositions: (1) strategic alignment is vulnerable to management control practices having a strong focus on performance measurements, (2) strategic alignment is vulnerable to standardised management control practices and (3) strategic alignment is vulnerable to politically driven management control practices.

With the strategic triangle as a base, this paper tries to understand what kind of management control practices enable and/or constrain public value, as there has been a call for this kind of research. In this way it adds to earlier research on public value, to the growing interest in the strategic triangle as an analytical framework in analysing empirical material and to the request for more empirical studies on the subject. The strategic triangle also embraces political factors, government agendas and political leadership for which there has also been a call for more research.

Preventive ergonomics is essential to protecting the health and safety of workers as is recognizing human variability. The purpose of this paper is to describe a Unity-based application designed for three-dimensional postural analysis and visualizations using motion capture data. Integration with virtual reality (VR) technologies allows the user to be immersed in the simulated working environment without the need for a physical prototype. The proposed application aims to facilitate the application of ergonomic principles in workplace design and assessment for a proactive, participatory and inclusive approach to worker well-being.

The authors developed an application that leverages motion capturing techniques and VR technologies and aims to support the analysts in the ergonomic assessment of physical prototypes as well as future workplaces. An innovative postural prediction module helps the analyst understanding what postures different users are likely to assume in the interaction with the workplace from a single data record.

The functionalities of the proposed application are illustrated on some case studies, presenting how different information is made available and can support workplace analysts and designers in an industrial context.

This paper provides insights into the experience and research carried out by an automotive company in the application of wearable sensors and VR to support a proactive and participatory approach to workplace ergonomics.

COVID-19 has dramatically changed how people live, socialise and think about their future. The disruptive shock that hit societies all over the world had a significantly negative impact on businesses, creating not only economic discontinuity but also uncertainty and disorientation. This special issue on COVID-19 aims to phrase the pandemic crisis and its impact on how to do business.

The authors follow MacInnis’s (2011) suggestion that a conceptual article sees what others have identified in a new or revised way.

The authors develop the crisis management framework. The authors acknowledge that disruptive events may be repeated, and their consequences will have long-term and permanent impacts. These aspects highlight the need for a systemic approach in which the focus is not limited to an analysis of the cause of the crisis and ways of solving it but includes the paths through which the business, economic and social systems evolve because of the crisis.

Managerial policies, business models and practices that have been effective up to now will probably no longer work. Beyond this backdrop, the articles compiled in this special issue aim to help set the agenda for post-COVID business research

The authors identify four primary themes captured by these articles: strategies, capabilities, organisational transformations and value processes. In their entirety, they represent pieces of a conceptual puzzle that do not provide knowledge of “hard facts” but rather a “soft interpretation of how to approach the “new normal”, i.e. a new social and business context.

Rapid sensitivity analysis and near-optimal decision-making in contested environments are valuable requirements when providing military logistics support. Port of debarkation denial motivates maneuver from strategic operational locations, further complicating logistics support. Simulations enable rapid concept design, experiment and testing that meet these complicated logistic support demands. However, simulation model analyses are time consuming as output data complexity grows with simulation input. This paper proposes a methodology that leverages the benefits of simulation-based insight and the computational speed of approximate dynamic programming (ADP).

This paper describes a simulated contested logistics environment and demonstrates how output data informs the parameters required for the ADP dialect of reinforcement learning (aka Q-learning). Q-learning output includes a near-optimal policy that prescribes decisions for each state modeled in the simulation. This paper's methods conform to DoD simulation modeling practices complemented with AI-enabled decision-making.

This study demonstrates simulation output data as a means of state–space reduction to mitigate the curse of dimensionality. Furthermore, massive amounts of simulation output data become unwieldy. This work demonstrates how Q-learning parameters reflect simulation inputs so that simulation model behavior can compare to near-optimal policies.

Fast computation is attractive for sensitivity analysis while divorcing evaluation from scenario-based limitations. The United States military is eager to embrace emerging AI analytic techniques to inform decision-making but is hesitant to abandon simulation modeling. This paper proposes Q-learning as an aid to overcome cognitive limitations in a way that satisfies the desire to wield AI-enabled decision-making combined with modeling and simulation.