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Background: Display signage is ubiquitous and essential in hospitals to serve several clerical, operational, and clinical functions, including displaying notices, providing directions, and presenting clinical information. These functions improve efficiency and patient engagement, reduce errors, and enhance the continuity of care. Over time, signage has evolved from analog approaches such as whiteboards and handwritten notices to digital displays such as liquid crystal displays, light emitting diodes, and, now, electronic ink displays. Electronic ink displays are paper-like displays that are not backlit and show content by aligning microencapsulated color beads in response to an applied electric current. Power is only required to generate content and not to retain it. These displays are very readable, with low eye strain; minimize the emission of blue light; require minimal power; and can be driven by several data sources, ranging from virtual servers to electronic health record systems. These attributes make adapting electronic ink displays to hospitals an ideal use case. Objective: In this paper, we aimed to outline the use of signage and displays in hospitals with a focus on electronic ink displays. We aimed to assess the advantages and limitations of using these displays in hospitals and outline the various public-facing and patient-facing applications of electronic ink displays. Finally, we aimed to discuss the technological considerations and an implementation framework that must be followed when adopting and deploying electronic ink displays. Methods: The public-facing applications of electronic ink displays include signage and way-finders, timetables for shared workspaces, and noticeboards and bulletin boards. The clinical display applications may be smaller form factors such as door signs or bedside cards. The larger, =40-inch form factors may be used within patient rooms or at clinical command centers as a digital whiteboard to display general information, patient and clinician information, and care plans. In all these applications, such displays could replace analog whiteboards, noticeboards, and even other digital screens. Results: We are conducting pilot research projects to delineate best use cases and practices in adopting electronic ink displays in clinical settings. This will entail liaising with key stakeholders, gathering objective logistical and feasibility data, and, ultimately, quantifying and describing the effect on clinical care and patient satisfaction. Conclusions: There are several use cases in a clinical setting that may lend themselves perfectly to electronic ink display use. The main considerations to be studied in this adoption are network connectivity, content management, privacy and security robustness, and detailed comparison with existing modalities. Electronic ink displays offer a superior opportunity to future-proof existing practices. There is a need for theoretical considerations and real-world testing to determine if the advantages outweigh the limitations of electronic ink displays. [ABSTRACT FROM AUTHOR]

In vehicular cloud computing (VCC) systems, the vehicle cloud (VC) consists of computing resources for multiple vehicles to assist the remote cloud (RC) in making real-time decisions on driving vehicles, to improve road safety and driving comfort. The acquisition of additional cloud facilities to increase the capacity of VCC systems when processing intensive requests for cloud resources is costly. A recent approach uses multiple remote microclouds (RMCs) to assist RCs in processing requests because they are smaller and less costly than RCs. Therefore, this paper presents a VCC system with multiple RCs and RMCs, in which an algorithm for allocating request resources among VCs, RMCs, and RCs. Subsequently, this paper proposes an improved simulated annealing algorithm (ImSA) based on density of vehicles in a geographical area to deploy RCs and RMCs with the minimal deployment cost and response cost. For real applications, the accuracy and effectiveness of the proposed algorithm are evaluated on the basis of the real traffic data from three different areas (i.e., urban area, outskirts, and suburban area) in one week. [ABSTRACT FROM AUTHOR]

Driven by the Industry 4.0 paradigm and the resulting demand for connectivity in industrial networking, there is a convergence of formerly isolated operational technology and information technology networks. This convergence leads to attack surfaces on industrial networks. Therefore, a holistic approach of countermeasures is needed to protect against cyber attacks. One element of these countermeasures is the use of certificate-based authentication for industrial components communicating on the field level. This in turn requires the management of certificates, private keys, and trust anchors in the communication endpoints. The work at hand surveys the topic of certificate management in industrial networking environments throughout their life cycle, from manufacturing until their disposal. To the best of the authors' knowledge, there is no work yet that surveys the topic of certificate management in industrial networking environments. The work at hand considers contributions from research papers, industrial communication standards, and contributions that originate from the IT domain. In total, 2042 results from IEEE Xplore, Science Direct, Scopus, and Springer Link were taken into account. After applying inclusion and exclusion criteria and title, abstract, and full-text analysis, 20 contributions from research papers were selected. In addition to the presentation of their key contributions, the work at hand provides a synopsis that compares the overarching aspects. This comprises different proposed entity architectures, certificate management functions, involvement of different stakeholders, and consideration of life cycle stages. Finally, research gaps that are to be filled by further work are identified. While the topic of certificate management has already been addressed by the IT domain, its incorporation into industrial communication standards began significantly later and is still the subject of research work. [ABSTRACT FROM AUTHOR]

Smart grids are one of the last decades' innovations in electrical energy. They bring relevant advantages compared to the traditional grid and significant interest from the research community. Assessing the field's evolution is essential to propose guidelines for facing new and future smart grid challenges. In addition, knowing the main technologies involved in the deployment of smart grids (SGs) is important to highlight possible shortcomings that can be mitigated by developing new tools. This paper contributes to the research trends mentioned above by focusing on two objectives. First, a bibliometric analysis is presented to give an overview of the current research level about smart grid deployment. Second, a survey of the main technological approaches used for smart grid implementation and their contributions are highlighted. To that effect, we searched the Web of Science (WoS), and the Scopus databases. We obtained 5,663 documents from WoS and 7,215 from Scopus on smart grid implementation or deployment. With the extraction limitation in the Scopus database, 5,872 of the 7,215 documents were extracted using a multi-step process. These two datasets have been analyzed using a bibliometric tool called bibliometrix. The main outputs are presented with some recommendations for future research. [ABSTRACT FROM AUTHOR]

In a globalized world at the present time, the realization of improving efficiency and minimizing costs during different stages of the application lifecycle, have confused software engineers on how they should deploy their applications and workload. It is noticed that many native applications of cloud computing and services comprises a lot of micro-services into the bargain traditional monolithic services. These services have almost been deprecated in application life-cycle mostly because of problems like maintaining, scaling, and other dynamics associated with it. Furthermore, developers focus their attention on containers. Machine resources are more effectively used by containers than a virtual machine (VM) and reduces the overhead of using a VM. Moreover, containers facilitate developers to create, deploy or delete applications without much effort. In order to manage multiple container applications, some of the container orchestration platforms like Kubernetes, Docker Swarm are introduced by cloud providers. In this paper, a study is conducted on how to deploy and manage applications using containerization with Kubernetes, from a cloud administrator’s perspective [ABSTRACT FROM AUTHOR]

With the rapid advancement of wearable devices, Human Activities Recognition (HAR) based on these devices has emerged as a prominent research field. The objective of this study is to enhance the recognition performance of HAR by proposing an LSTM-1DCNN recognition algorithm that utilizes a single triaxial accelerometer. This algorithm comprises two branches: one branch consists of a Long and Short-Term Memory Network (LSTM), while the other parallel branch incorporates a one-dimensional Convolutional Neural Network (1DCNN). The parallel architecture of LSTM-1DCNN initially extracts spatial and temporal features from the accelerometer data separately, which are then concatenated and fed into a fully connected neural network for information fusion. In the LSTM-1DCNN architecture, the 1DCNN branch primarily focuses on extracting spatial features during convolution operations, whereas the LSTM branch mainly captures temporal features. Nine sets of accelerometer data from five publicly availableHAR datasets are employed for training and evaluation purposes. The performance of the proposed LSTM-1DCNN model is compared with five other HAR algorithms including Decision Tree, Random Forest, Support Vector Machine, 1DCNN, and LSTM on these five public datasets. Experimental results demonstrate that the F1-score achieved by the proposed LSTM-1DCNN ranges from 90.36% to 99.68%, with a mean value of 96.22% and standard deviation of 0.03 across all evaluated metrics on these five public datasetsoutperforming other existingHAR algorithms significantly in terms of evaluationmetrics used in this study. Finally the proposed LSTM-1DCNN is validated in real-world applications by collecting acceleration data of seven human activities for training and testing purposes. Subsequently, the trained HAR algorithm is deployed on Android phones to evaluate its performance. Experimental results demonstrate that the proposed LSTM-1DCNNalgorithm achieves an impressive F1-score of 97.67% on our self-built dataset. In conclusion, the fusion of temporal and spatial information in the measured data contributes to the excellent HAR performance and robustness exhibited by the proposed 1DCNN-LSTM architecture. [ABSTRACT FROM AUTHOR]

Summary Software‐defined networking (SDN) is an emerging networking architecture paradigm that decouples the control and data planes. The problem of figuring out the number and positions of controllers and mapping of switches to them is known as the controller placement problem. To provide the resilience against the failure of a controller, each switch is mapped to a primary controller (first reference controller or FRC) and a backup controller (second reference controller or SRC). An existing work aims to minimize the worst‐case latency (WCL) from switch to controller when a controller fails. But this work misses the constraint specifying the definition of a switch's SRC, which might cause an increase in the latency between some switches and their controllers in the event of a controller failure. In order to address this issue, a model is proposed in this paper by incorporating the missing constraint. But the addition of this constraint can potentially cause an increase in the minimum number of required controllers. In order to address this issue, a second model is proposed in this paper by modifying the capacity constraint based on the observation that the capacity of a controller need not be reserved for all the switches for which it acts as SRC. The two proposed models aim at minimizing the WCL from switch to controller when a controller fails. Three network topologies are used to test the proposed models and compare their performance with the existing model in terms of principal and subsidiary metrics. The results demonstrate that the proposed models perform on equal level with the existing model in terms of WCL from switch to SRC while outperforming it in terms of average latency (AL). For example, the first proposed model achieves an average AL reduction of 21.63%, 8.55%, and 25.13% compared with the existing model on three networks. Similarly, the second proposed model achieves an average AL reduction of 21.3%, 8.55%, and 24.19% in each network on three networks. Moreover, the second proposed model achieves a fair trade‐off between the minimum number of controllers required and AL while outperforming both the existing and the first proposed models in terms of the average percentage of reserved controller capacity. [ABSTRACT FROM AUTHOR]

Artificial intelligence technologies based on deep convolutional neural networks and large language models have made significant breakthroughs in many tasks, such as image recognition, target detection, semantic segmentation, and natural language processing, but also face a conflict between the high computational capacity of the algorithms and limited deployment resources. Quantization, which converts floating-point neural networks into low-bit-width integer networks, is an important and essential technique for efficient deployment and cost reduction in edge computing. This paper analyzes various existing quantization methods, showcases the deployment accuracy of advanced techniques, and discusses the future challenges and trends in this domain. [ABSTRACT FROM AUTHOR]

The benefits of teacher-facing dashboards are incontestable, yet their evidence is finite in terms of long-term use, meaningful usability, and maturity level. Thus, this paper uses design science research and critical theory to design and develop TEADASH to support teachers in making decisions on teaching and learning. Three cycles of design science research and multiple small loops were implemented to develop the dashboard. The tool was then deployed and evaluated in real time with the authentic courses. Five courses from two Swedish universities were included in this study. The co-design with teachers is crucial to the applicability of this dashboard, while letting teachers use the tool during their courses is more important to help them to recognize the features they actually use and the tool's usefulness for their teaching practices. TEADASH can address the prior matters, align with the learning design, and meet teachers' needs. The technical and co-design aspects, as well as the advantages and challenges of applying TEADASH in practice, are also discussed here. [ABSTRACT FROM AUTHOR]

Nowadays, more cars are being added to the roads, which increases the risk of deadly accidents and the average commuter's daily travel time. To address these issues, vehicular ad hoc networks (VANETs) were developed, facilitating communication both among vehicles and between vehicles and infrastructure. Due to the great mobility of vehicles, the primary issue in VANETs is the requirement for very short communication latency, particularly for applications related to safety. Moreover, security is a significant concern that arises from Because nodes share sensitive information with one another about themselves and their surroundings. The infrastructure-based elements defined as roadside units (RSU) were formulated to overcome this problem by allowing information to be transmitted amongst vehicles, which could then be used to increase system safety and efficiency. However, in order to achieve certain desired Quality of Service (QoS), such as service coverage, throughput, reduced latency, or energy consumption, there are primary obstacles that arise when implementing (RSUs). These obstacles include performance issues, data security during transfer, and overall cost considerations. This article introduces a thorough survey of Roadside Units (RSUs) in VANET networks, providing an examination of the current research trends in this field. The survey explores the strengths, weaknesses, specific scenarios, methods, topologies, and potential future improvements of RSUs. Additionally, the paper focuses on three key aspects of RSUs: deployment, management, and security, analyzing their prominent features, motivations, challenges, methodology aspects, real datasets, metrics, and performance measures. [ABSTRACT FROM AUTHOR]

This paper mainly studies the deployment of hybrid sensors on highways. By constructing the deployment location constraint model, the overall accuracy of sensor deployment can be maximized. In addition, in order to meet the needs of intelligent transportation, the consideration of traffic data communication is added to the work. The highway under study is first divided into several units, and the combination type of sensors is used to represent the possible layout of two adjacent sensors. Then, a 0–1 optimization model reflecting the interaction between the sensor position and the server position is established. Then, a two-step search algorithm is proposed to find the optimal solution of the model and determine the deployment scheme with maximum accuracy. Finally, an example is given to verify the method. The results show that there are significant differences between uniform unit-deployment schemes and non-uniform unit-deployment schemes. Through the sensitivity analysis of each factor, the influence of budget and communication radius on the deployment plan is proven. In addition, the ramp length can also have a negative impact on the target value. [ABSTRACT FROM AUTHOR]

Despite an exponential increase in publications on clinical prediction models over recent years, the number of models deployed in clinical practice remains fairly limited. In this paper, we identify common obstacles that impede effective deployment of prediction models in healthcare, and investigate their underlying causes. We observe a key underlying cause behind most obstacles — the improper development and evaluation of prediction models. Inherent heterogeneities in clinical data complicate the development and evaluation of clinical prediction models. Many of these heterogeneities in clinical data are unreported because they are deemed to be irrelevant, or due to privacy concerns. We provide real-life examples where failure to handle heterogeneities in clinical data, or sources of biases, led to the development of erroneous models. The purpose of this paper is to familiarize modeling practitioners with common sources of biases and heterogeneities in clinical data, both of which have to be dealt with to ensure proper development and evaluation of clinical prediction models. Proper model development and evaluation, together with complete and thorough reporting, are important prerequisites for a prediction model to be effectively deployed in healthcare. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to review and gather the latest critical success factors (CSF) of Lean Six Sigma (LSS) deployment and implementation into a comprehensive list of factors. Design/methodology/approach – The approach taken by authors in this study was to analyze the latest literature review starting 2010 onwards and focus on CSFs of LSS (not dedicated as Lean or Six Sigma) by excluding other improvement methodologies or initiatives, e.g. Lean, Six Sigma, TQM, TRIZ etc. Findings – Five significant CSFs were identified (initially 97 CSFs listed from 13 papers) out of nine groups/headers listed in clustering analysis using Affinity Diagram tool and new headers mapping. Practical implications – Most of the organisations were aware of the success story on LSS, but did not scrutinize or consider its CSFs. By knowing the outcome of this paper, it can help open eyes regarding readiness before implementing LSS. Originality/value – At the end of this paper, the authors tried to cluster the CSFs similarities that could intentionally provide the guidelines and references to industries/companies for successful deployment and implementation of LSS in future endeavours. [ABSTRACT FROM AUTHOR]

The Industrial Metaverse paradigm can be broadly described as a virtual environment that integrates various technologies such as augmented reality and mixed reality to enhance business operations and processes. It aims to streamline workflows, reduce error rates, improve efficiency, and provide a more engaging experience for employees. The promise of the Industrial Metaverse to drive sustainability and resource efficiency is compelling. Using advanced technologies such as the Industrial Metaverse is vital in an endeavor to have a competitive edge in a rapidly evolving business environment. However, the environmental impact of the technologies underpinning the Industrial Metaverse, like data centers and network infrastructure, should not be overlooked. The ecological footprint of these technologies must be considered in the sustainability equation. Researchers have warned that, by 2025, without sustainable artificial intelligence (AI) practices, AI will consume more energy than the human workforce, significantly offsetting zero carbon gains. As the Metaverse persists in evolving and gaining momentum, it will be necessary for companies to prioritize sustainability and explore new ways to balance technological advancements with environmental stewardship. However, recent studies have conjectured that the Metaverse holds the potential to reduce carbon emissions, as digital replacements for physical goods become more prevalent and physical activities like mobility and construction are reduced. Moreover, the specific extent to which this substitution can alleviate environmental concerns remains an open issue, presenting a knowledge gap in understanding the real-world impact of digital replacements. Thus, the objective of this paper is to provide a comprehensive review of the Industrial Metaverse, as well as explore the environmental impact of the Industrial Metaverse. The integrative literature review design and methodological approach involved multiple sources from the Web of Science and databases such as the ACM library, IEEE Library, and Google Scholar, which were analyzed to provide a comprehensive understanding of the developments in the Industrial Metaverse. Firstly, by considering the Industrial Metaverse's architecture, we elucidate the Industrial Metaverse concept and the associated enabling technologies. Secondly, we performed an exploration through a discussion of the prevalent use cases and the deployment of the emerging Industrial Metaverse. Thirdly, we explored the impact of the Industrial Metaverse on the environment. Lastly, we address novel security and privacy risks, as well as upcoming research challenges, keeping in mind that the Industrial Metaverse is based on a strong data fabric. The results point to the Industrial Metaverse as having both positive and negative environmental effects in terms of energy consumption, e-waste, and pollution. Research, however, indicates that most Industrial Metaverse applications have a positive environmental impact and subsequently trend toward sustainability. Finally, for sustainability in the Industrial Metaverse, enterprises may consider utilizing renewable energy sources and cloud services. Furthermore, we examined the effects of products on the environment, as well as in the creation of a circular economy. [ABSTRACT FROM AUTHOR]

Objective: This paper explores Australian military families' use of social media and digital communication to maintain and strengthen parent–child relationships during military deployments. Background: The physical and emotional well‐being of children and partners of military serving members is affected by service. Maintaining positive family relationships between military members and their children during periods of absence (including deployment) is important for parental relationships as well as the well‐being of the child. Method: A qualitative meta‐analysis is used to collate data from two previous studies of Australian Defence Force (ADF) families with children, in order to generate a new data set from which novel insights were drawn. Results: Families show a preference for social media and digital communication methods, and digital technologies affordances and practicalities are well suited for Defence families with children. There are a range of benefits; digital technologies are used to strengthen relationships between children and their deployed parent. The study highlights a range of challenges for deployed parents as well as points to the work required from the at‐home parent in facilitating these connections. Conclusion: Maintaining positive family relationships between military members and their children during times of absences is important for both relationships. This paper explores how ADF families use social and digital communication during military absences and outlines the role these technologies play as a medium for strengthening familial relationship. Implications. The findings of this paper highlight the importance of digital and social communication technologies for supporting families during absences. This has implications for the ADF, who might look to reduce members' access to such communication for security concerns. Reduced family well‐being may also have impacts on retention, a key issue for military organizations. Accordingly, the findings of this paper may be used to inform decisions about restricting internet and social media access for deployed military members. [ABSTRACT FROM AUTHOR]