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Digital learning systems are crucial for education and data collected can analyse students learning performances to improve support. The purpose of this study is to design and build an asynchronous hardware and software system that can store data on a local device until able to share. It was developed for staff and students at university who are using the limited internet access in areas such as remote Northern Territory. This system can asynchronously link the users’ devices and the central server at the university using unstable internet.

A Learning Box has been build based on minicomputer and a web learning management system (LMS). This study presents different options to create such a system and discusses various approaches for data syncing. The structure of the final setup is a Moodle (Modular Object Oriented Developmental Learning Environment) LMS on a Raspberry Pi which provides a Wi-Fi hotspot. The authors worked with lecturers from X University who work in remote Northern Territory regions to test this and provide feedback. This study also considered suitable data collection and techniques that can be used to analyse the available data to support learning analysis by the staff. This research focuses on building an asynchronous hardware and software system that can store data on a local device until able to share. It was developed for staff and students at university who are using the limited internet access in areas such as remote Northern Territory. This system can asynchronously link the users’ devices and the central server at the university using unstable internet. Digital learning systems are crucial for education, and data collected can analyse students learning performances to improve support.

The resultant system has been tested in various scenarios to ensure it is robust when students’ submissions are collected. Furthermore, issues around student familiarity and ability to use online systems have been considered due to early feedback.

Monitoring asynchronous collaborative learning systems through analytics can assist students learning in their own time. Learning Hubs can be easily set up and maintained using micro-computers now easily available. A phone interface is sufficient for learning when video and audio submissions are supported in the LMS.

This study shows digital learning can be implemented in an offline environment by using a Raspberry Pi as LMS server. Offline collaborative learning in remote communities can be achieved by applying asynchronized data syncing techniques. Also asynchronized data syncing can be reliably achieved by using change logs and incremental syncing technique.

Focus on audio and video submission allows engagement in higher education by students with lower literacy but higher practice skills. Curriculum that clearly supports the level of learning required for a job needs to be developed, and the assumption that literacy is part of the skilled job in the workplace needs to be removed.

To the best of the authors’ knowledge, this is the first remote asynchronous collaborative LMS environment that has been implemented. This provides the hardware and software for opportunities to share learning remotely. Material to support low literacy students is also included.

The purpose of this paper is to investigate the cyber hygiene practices of remote workers.

This paper used two instruments: first, the Cyber Hygiene Inventory scale, which measures users’ information and computer security behaviors; second, the Recsem Inventory, developed within this paper’s context, to evaluate the cybersecurity measures adopted by organizations for remote workers. It was conducted on remote workers to examine their information security practices. The instrument was administered to a sample of 442 employees reached via the LinkedIn platform. Analyses were performed with SPSS v26, Python programming language and Seaborn library.

The findings indicate a significant correlation between the security measures implemented by companies and their employees’ cyber hygiene practices. A sector comparison revealed a significant difference in cyber hygiene levels between public and private sector workers.

This paper aims to provide policymakers with suggestions for enhancing the cyber hygiene of remote workers to facilitate compliance with corporate security protocols.

This paper’s conclusions highlight the importance of companies increasing their cybersecurity investments as remote work becomes more prevalent. This should consider not only corporate-level factors but also employees' information and computer security behaviors.

Protection motivation theory (PMT) explains that the intention to cope with information security risks is based on informed threat and coping appraisals. However, people cannot always make appropriate assessments due to possible ignorance and cognitive biases. This study proposes a research model that introduces four antecedent factors from ignorance and bias perspectives into the PMT model and empirically tests this model with data from a survey of electronic waste (e-waste) handling.

The data collected from 356 Chinese samples are analyzed via structural equation modeling (SEM).

The results revealed that for threat appraisal, optimistic bias leads to a lower perception of risks. However, factual ignorance (lack of knowledge of risks) does not significantly affect the perceived threat. For coping appraisal, practical ignorance (lack of knowledge of coping with risks) leads to low response efficacy and self-efficacy and high perceptions of coping cost, but the illusion of control overestimates response efficacy and self-efficacy.

First, this study addresses a new type of information security problem in e-waste handling. Second, this study extends the PMT model by exploring the roles of ignorance and bias as antecedents. Finally, the authors reinvestigate the basic constructs of PMT to identify how rational threat and coping assessments affect user intentions to cope with data security risks.

This paper aims to present a literature review of remote monitoring systems for water infrastructure in the Global South.

Following initial scoping searches, further examination was made of key remote monitoring technologies for water infrastructure in the Global South. A standard literature search methodology was adopted to examine these monitoring technologies and their respective deployments. This hierarchical approach prioritised “peer-reviewed” articles, followed by “scholarly” publications, then “credible” information sources and, finally, “other” relevant materials. The first two search phases were conducted using academic search services (e.g. Scopus and Google Scholar). In the third and fourth phases, Web searches were carried out on various stakeholders, including manufacturers, governmental agencies and non-governmental organisations/charities associated with Water, Sanitation and Hygiene (WASH) in the Global South.

This exercise expands the number of monitoring technologies considered in comparison to earlier review publications. Similarly, preceding reviews have largely focused upon monitoring applications in sub-Saharan Africa (SSA). This paper explores opportunities in other geographical regions and highlights India as a significant potential market for these tools.

This review predominantly focuses upon information/data currently available in the public domain.

Remote monitoring technologies enable the rapid detection of broken water pumps. Broken water infrastructure significantly impacts many vulnerable communities, often leading to the use of less protected water sources and increased exposure to water-related diseases. Further to these public health impacts, there are additional economic disadvantages for these user communities.

This literature review has sought to address some key technological omissions and to widen the geographical scope associated with previous investigations.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Customers today expect businesses to cater to their individual needs by tailoring the products they purchase to their own preferences. The term “Industry 5.0” refers to a new wave of manufacturing that aims to meet each customer's unique demands. Even while Industry 4.0 allowed for mass customization, that wasn't good enough before, customers today demand individualized products at scale, and Industry 5.0 is driving the transition from mass customization to mass personalization to meet these demands. It caters to the individual needs of each consumer by meeting their demands. More specialized components for use in medicine are made possible by the widespread customization made possible by Industry 5.0. These individualized parts are included into the medical care of the patient to meet their specific needs and preferences. In the current medical revolution, an enabling technology of Industry 5.0 can produce medical implants, artificial organs, bodily fluids, and transplants with pinpoint accuracy. With the advent of AI-enabled sensors, we now live in a world where data can be swiftly analyzed. Machines may be programmed to make complex choices on the fly. In the medical field, these innovations allow for exact measurement and monitoring of human body variables according to the individual's needs. They aid in monitoring the body's response to training for peak performance. It allows for the digital dissemination of accurate healthcare data networks. In order to collect and exchange relevant patient data, every equipment is online.

Creating a new product or service promotes the status quo changes, seeking economic value and solving customer's urgent problems. Entrepreneurs play an important role in this changing process through start-ups and small and medium enterprises (SMEs), considered one of the leading forces driving an economy’s innovative and competitive power. However, despite the importance of entrepreneurs, public policies to foster entrepreneurship ecosystems could be ineffective in emerging countries. Therefore, action research proposes the qualification of entrepreneurs for the structuring of new businesses through remote orientation, connecting the country's main economic centers to emerging areas.

The study is qualitative research comprising two phases. The first phase consisted of four-month action research, connecting two researchers and three groups of specialists (from Sao Paulo), with three groups of entrepreneurs (located in Manaus in the Amazon region), through a remote orientation in entrepreneurship, lean start-up, lean product and process development (LPPD). The second phase, conducted by a third researcher, regards a case study grounded on interviews and data collection with the entrepreneurs to capture the outcomes of the remote orientation process.

The remote orientation helped shorten the geographical distance of Amazonas to approach the integration of business, research and knowledge exchange of such distinct areas in the same country. If a remote orientation program was established as public policy, it could enact subsequent cycles of the lean start-up model. Furthermore, the remote orientation could be an alternative to compose the training subsystem in the entrepreneurship ecosystem proposed by Isenberg (2011). On the other hand, a remote orientation could fail to shorten the distance of human values and beliefs, which cannot be neglected when facing a rich territory like the Amazon.

Because of the chosen research approach, a qualitative and exploratory study based on a combination of action research, interviews and case studies, the results may lack generalizability. However, further studies can replicate the remote orientation process conducted in the region of Manaus – Amazon, to obtain distinct results regarding the advantages, disadvantages and effectiveness of remote orientation as entrepreneurship ecosystem’s human capital dimension development.

The outcomes of this research have the potential to start discussions regarding the adoption of remote orientation as a public policy to develop entrepreneurship skills in emerging regions, not only in Brazil but worldwide. The Brazilian case could be a relevant benchmark due to the large territory and economic and social disparities impacting education and entrepreneurship.

Through start-ups and SMEs, entrepreneurship has innovation potential and is the most solid way to bring economic development. For emerging countries, it can be real game-changer in the economic order. The development of entrepreneurship skills through this remote orientation experience can help reduce the economic and social gaps in countries with relevant disparities like Brazil and other emerging countries.

This paper fulfills an identified need to “move the needle of entrepreneurship in the right direction” (Isenberg, 2010) by creating local solutions for global challenges. Policymakers and leaders need to continue the experiment and learn how to improve the entrepreneurship ecosystem. In this sense, the action research approach, combined with the remote orientation, proposes an alternative to promote changes in how human capital dimension can be developed in this challenging ecosystem.

It is well known in the mining industry that the increase in failures and breakdowns is due mainly to a poor maintenance policy for the equipment, in addition to the difficult access that specialized personnel have to combat the breakdown, which translates into more machine downtime. For this reason, this study aims to propose a remote assistance model for diagnosing and repairing critical breakdowns in mining industry trucks using augmented reality techniques and data analytics with a quality approach that considerably reduces response times, thus optimizing human resources.

In this work, the six-phase CRIPS-DM methodology is used. Initially, the problem of fault diagnosis in trucks used in the extraction of material in the mining industry is addressed. The authors then propose a model under study that seeks a real-time connection between a service technician attending the truck at the mine site and a specialist located at a remote location, considering the data transmission requirements and the machine's characterization.

It is considered that the theoretical results obtained in the development of this study are satisfactory from the business point of view since, in the first instance, it fulfills specific objectives related to the telecare process. On the other hand, from the data mining point of view, the results manage to comply with the theoretical aspects of the establishment of failure prediction models through the application of the CRISP-DM methodology. All of the above opens the possibility of developing prediction models through machine learning and establishing the best model for the objective of failure prediction.

The original contribution of this work is the proposal of the design of a remote assistance model for diagnosing and repairing critical failures in the mining industry, considering augmented reality and data analytics. Furthermore, the integration of remote assistance, the characterization of the CAEX, their maintenance information and the failure prediction models allow the establishment of a quality-based model since the database with which the learning machine will work is constantly updated.

This paper examines an employee's recovery process in the remote-working context. It explores which elements of remote work are energy-consuming for employees and what action they can take to instigate the essential recovery strategy of psychological detachment.

The study adopts a qualitative research approach based on 89 semi-structured interviews with employees working from home with six large corporations from multiple industries. The data were interpreted using thematic analysis.

The study identifies a main theme – the energy-consuming elements of remote work – and three sub-themes: extended working hours, intensive working and reduced social support. Each theme incorporates elements controlled by individuals (internal) and those beyond their control (external). Second, the authors identified strategies that helped individuals to detach from work, and devised four sub-themes, the authors labeled cognitive controlling, physical disconnection from work, time-bound routines and non-work activities.

This is the first study to focus on recovery as a process in the context of remote working, and it contributes to the knowledge of psychological detachment and strategies for recovery and to the literature on contemporary remote working.

This article surveys why libraries are vulnerable to social engineering attacks and how to manage risks of human-caused cyber threats on organizational level; investigates Estonian library staff awareness of information security and shares recommendations concerning focus areas that should be given more attention in the future.

The data used in this paper is based on an overview of relevant literature highlighting the theoretical points and giving the reasons why human factor is considered the weakest link in information security and cyber security and studying how to mitigate the related risks in the organisation. To perform the survey, a web questionnaire was designed which included 63 sentences and was developed based on the knowledge-attitude-behaviour (KAB) model supported by Kruger and Kearney and Human Aspects of Information Security Questionnaire (HAIS-Q) designed by Parsons et al.

The research results show that the information security awareness of library employees is at a good level; however, awareness in two focus areas needs special attention and should be improved. The output of this study is the mapping of seven focus areas of information security policy in libraries based on the HAIS-Q framework and the KAB model.

The cyber awareness of library employees has not been studied in the world using HAIS-Q and KAB model, and to the best of the authors’ knowledge, no research has been previously carried out in the Estonian library context into cyber security awareness.