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In the past decade, more than 700 million people are affected by some kind of disability or handicap. In this context, the research interest in assistive robotics is growing up. For people with mobility impairments, daily life operations, as dressing or feeding, require the assistance of dedicated people; thus, the use of devices providing independent mobility can have a large impact on improving their life quality. The purpose of this paper is to present the development of a robotic system aimed at assisting people with this kind of severe motion disabilities by providing a certain level of autonomy.

The system is based on a hierarchical architecture where, at the top level, the user generates simple and high-level commands by resorting to a graphical user interface operated via a P300-based brain computer interface. These commands are ultimately converted into joint and Cartesian space tasks for the robotic system that are then handled by the robot motion control algorithm resorting to a set-based task priority inverse kinematic strategy. The overall architecture is realized by integrating control and perception software modules developed in the robots and systems environment with the BCI2000 framework, used to operate the brain–computer interfaces (BCI) device.

The effectiveness of the proposed architecture is validated through experiments where a user generates commands, via an Emotiv Epoc+ BCI, to perform assistive tasks that are executed by a Kinova MOVO robot, i.e. an omnidirectional mobile robotic platform equipped with two lightweight seven degrees of freedoms manipulators.

The P300 paradigm has been successfully integrated with a control architecture that allows us to command a complex robotic system to perform daily life operations. The user defines high-level commands via the BCI, letting all the low-level tasks, for example, safety-related tasks, to be handled by the system in a completely autonomous manner.

A minimum‐time path‐following algorithm for industrial robots is presented in this paper.

The algorithm generates off‐line a trajectory that, by exploiting knowledge of the dynamic model, takes into account the actuators' torque limits while preserving the geometric path.

The algorithm has been designed, implemented and extensively tested on a Comau SMART H4 robot, a closed‐chain six‐degree‐of‐freedom industrial manipulator.

The algorithm is currently part of the new generation of industrial controllers of the Comau robots, the C4G controller. It is a feature added as with the name SmartMove4.

The paper presents a new minimum‐time path‐following algorithm for industrial robots that, by exploiting knowledge of the dynamic model, takes into account the actuators' torque limits while preserving the geometric path.

This paper introduces the second part of a AAAJ special issue on accounting, accountability and management during the COVID-19 emergency. The authors analyse the themes that emerge from the second part of the special issue, which allows us to identify the diverse accounting and accountability practices across different geographical and organisational contexts. The authors also provide an overall picture of the contributions of the special issue, with insights into avenues of future research.

Building on the first part of the AAAJ special issue, the paper draws together and identifies additional emerging themes related to research into the COVID-19 pandemic and how it impacts accounting, accountability and management practices. The authors reflect on the contributions of the special issue to the interdisciplinary accounting research project.

The authors identify two macro-themes and outline their contributions to the accounting literature. The first deals with the changes and dangers of accounting and accountability practices during the pandemic. The second considers accountability practices in a broader sense, including reporting, disclosure and rhetorical practices in the management of COVID-19.

The paper shows the pervasive role of accounting and accountability in the unprecedented and indiscriminate health crisis of COVID-19. It highlights the important role of special issues in producing timely research that responds to unfolding events.

This paper contributes to current debates on the roles of accounting and accountability during COVID-19 by drawing together the themes of the special issue and identifying future interdisciplinary accounting research on the pandemic's aftermath.

As the number of web applications is increasing day by day web mining acts as an important tool to extract useful information from weblogs and analyse them according to the attributes and predict the usage of a website. The main aim of this paper is to inspect how process mining can be used to predict the web usability of hotel booking sites based on the number of users on each page, and the time of stay of each user. Through this paper, the authors analyse the web usability of a website through process mining by finding the web usability metrics. This work proposes an approach to finding the usage of a website using the attributes available in the weblog which predicts the actual footfall on a website.

PROM (Process Mining tool) is used for the analysis of the event log of a hotel booking site. In this work, authors have used a case study to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.

This article first provided an overview of process mining, then focused on web mining and later discussed process mining techniques. It also described different target languages: system nets (i.e. Petri nets with an initial and a final state), inductive miner and heuristic miner, graphs showing the change in behaviour of the dataset and predicting the outcome, that is the webpage having the maximum number of hits.

In this work, a case study has been used to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.

This paper aims to shed light on how family firms execute open innovation strategies by managing internal and external knowledge flows.

First, through a comprehensive literature review, the paper identifies the barriers to the acquisition and transfer of knowledge in open innovation processes. Second, it presents and discusses the results of an exploratory case study on Loccioni, an Italian family firm providing high-tech measurement solutions, highlighting how this family firm managed to overcome the barriers in executing an open innovation strategy.

The case study shows that Loccioni faced specific challenges in acquiring and transferring knowledge in its open innovation processes and developed two idiosyncratic capabilities – labelled imprinting and fraternization – that helped the firm overcome the barriers to knowledge acquisition and transfer. The analysis shows that these two capabilities are enabled by the distinctive goals and social capital characterizing family firms.

The paper creates a link between open innovation and family business research with an empirically grounded model illustrating how the idiosyncratic capabilities of a family firm help overcome the critical barriers to the acquisition and transfer of knowledge in executing an open innovation strategy.